#its definitely not a miracle process that can count on to turn people into models

[mewvore]

Do you have any advice for starting hrt?

If you do start, dont compare yourself to other people. everyones paths are going to be different, and your journey should be focused on becoming the version of yourself that you want to be, not about others. Its a marathon, not a sprint

[yuqi-y-blog]

Assessing Tea Quality with Electronic Nose and Electronic Tongue

Are you a tea drinker? If so, do you have your favorite leaf, or prefer some types of tea to others? There are many teas, from the high-end ones packed in delicate gift boxes to those sold in bulk at their origins, which may be unfamiliar for tea drinkers in the more developed regions. But is that the more expensive, the better? Who decides the grades of teas, and how do they judge the quality?

The Traditional Method

Traditionally, “tea masters” assign the grade by tea-tasting, but this method is realized to be increasingly unreliable. Masters are still human, just with more expertise and experience, and human is inevitably subjective. Different masters may give different results; even the same person may give a different result on a different day depending on their physical or mental state. Leaving alone the subjectivity, human testing is also not efficient enough. With millions of, if not more, different types of teas sold through various channels in the market today, it is impractical for each of them to be examined by experts.

A New Approach

Is there a more accurate and more efficient way to grade the teas? The answer is “yes,” by artificial intelligence. Zhi et al. have presented a framework for Electronic Nose (E-Nose) and Electronic Tongue (E-Tongue) to assess tea quality (2017).

E-Nose and E-Tongue are not hard to understand literally, but exactly how do they function, and how is the information integrated to grade a tea?

Despite the huge difference in their appearances, E-Nose and E-Tongue collect information under a similar logic as human’s organs. They comprise of an array of sensors that detect the chemicals in the test samples and generate diverse signatures. The difference comes about in the perception of those signatures. Human’s interpretation turns out to be rather rough: bitter, sweet, fragrant, etc., since the signals are forced to go through multiple built-in filters in our brains, while E-Nose and E-Tongue provide raw signals, which are quantified and ready for more scientific analysis.

Feature Extraction and Dimension Reduction

Raw signals are hard to work with directly. In Zhi’s experiment, the E-Nose has 18 sensors and the E-Tongue has 7, so there are 25 distinct signal curves, with each curve consisting of 241 data points collected in 120 seconds for each test sample. It is impossible to tell anything by just looking at 25*241 plain numbers, so feature extraction is essential.

Zhi et al. extract the features in two different domains: time and frequency. The time-domain features are easy to acquire and easy to understand. The maximum value and the average value are calculated among the 241 points for each sensor. The frequency-domain features, on the other hand, is less straight forward. In brief, you can imagine the discrete points are connected to form a curve that bounces up and down, and the frequency-domain features describe how vividly the curve bounces. The importance to include the frequency domain is illustrated in the graph below. As we can see, data sets A and B have the same maximum and average value, yet their dynamic “energy” is different. It is probably not a good idea to conclude that these two signals are the same as if we are only looking at the time-domain features.

Now, we have successfully reduced the data size to 25*4 for each sample, but what’s next? Although decreased in size, the data is still numbers. How can we assign different grades to the teas according to those sets of numbers?

Let the machine learn!

Of course, we can manually observe the data and try to summarize some kind of regularities, but that would be tedious and thus running counter to our objective of improving efficiency. Luckily, we have assistants who are good at dealing with data of large sizes and doing repetitive jobs: computers.

Just like tea masters taste a lot of teas to form their experience, computers need to first form their knowledge bases and then apply the knowledge to solve the problem. In machine learning, the process of forming knowledge bases is called training. There’s one thing that is easy to get wrong: computers never learn on their own. It is human who programs the algorithms, and all computers do is executing the algorithms that take in the data and turn it into a knowledge base.

In the case of tea testing, the computer is trained with a number of samples given their grades so that it can get a sense of which characteristics correspond to which grades. Well, to “get a sense” is the human way; the computer way is to match the data points with the grades and construct reference maps for applications. For the matching, Zhi et al. adopt Kernel Linear Discriminant Analysis (KLDA). The purpose of this high-level mathematical trick is to maximize between-class separation and minimize in-class variance. In other words, we want the teas to be as similar to each other as possible if they belong to the same grade, and elsewise as different from each other as possible. We can’t manipulate the data, but what we can do is weighting it to highlight particular data. KLDA is a nonlinear transformation that maps the original data points to a more classified distribution. With this optimized matching, which is impossible without machine learning due to the huge amount of computation, the accuracy of grading is significantly improved.

Assign a grade to an unknown tea

After training, the computer is ready to assess the quality of unknown teas. Given a new tea sample, we let the E-Nose smell it and let the E-Tongue taste it, obtain the raw signals, extract the features, and transform the data through the same KLDA filter used in training. Then we get a new data point to be compared to the ones in the computer’s knowledge base, namely the reference map constructed with the training set. How can we make the comparison, or, to be precise, which algorithm do we tell the computer to execute to make the comparison?

Zhi et al. use the K-nearest neighbor (KNN) classifier, which is, unlike the previous algorithms, one of the simplest among the classification algorithms. It assigns a class to the unclassified point by looking at a number (k) of its nearest neighbors and taking the majority vote from them.

There is only one problem left. I have been counting the data for the E-Nose and E-Tongue together so far in order to demonstrate the size of data, yet in fact, they are quite different data since one describes the smell and one describes the taste, and so cannot be calculated as one. Hence at this point, we actually have two separate results from the E-Nose and the E-Tongue. The problem is how to combine the two results to give a final assignment.

Here comes the last mathematical tool in the assessment: D-S evidence, which is perfect for solving this problem. It generates one probability function by combining two bodies of evidence, which, in our case, are the E-Nose and the E-Tongue. The method is rather simple: taking the product of the probabilities suggested by the two bodies of evidence and calculating the proportion of each shared outcome. For instance, consider the following case:

Since D-S evidence only accounts for shared outcomes, the probabilities of the sample being grade 1 and grade 4 are omitted. The probability of grade 2 is 80%*90%=72%, and that of grade 3 is 10%*5%=0.5%. So the final probability of grade 2 is 72%/(72%+0.5%)=99.31%, a quite determinate probability for the computer to conclude that the sample belongs to grade 2. Noticeably, there’s one big assumption made by D-S evidence: the conflict between the two bodies of evidence is small. Consider this case:

Because there are no shared outcomes, the result would be completely inconclusive. Fortunately, big conflicts are not expected to happen since a tea sample naturally should not show such huge different characteristics in smell and taste, and that is why D-S evidence is suitable for this scenario.

Conclusion and outlook for artificial intelligence

Compared to tea masters, E-Nose and E-Tongue guarantee to be fully objective and statistically more accurate with the implementation of KDLA. Moreover, both time efficiency and cost efficiency can be largely improved. E-Nose and E-Tongue can work non-stop with each sample only taking 120 seconds, and the computer can then process the data 1,000 times faster than a human does. The main cost would be the fixed cost, including setting up the machines and training the model. Once the setup is done, the operation cost is expected to be fairly low. Therefore, tea quality assessment with E-Nose and E-Tongue can definitely be promoted to the market for practical use.

As we go through the full process, I also hope you get a better sense of how AI works. To many people’s disappointment, AIs are not like creatures and never generate ideas on their own. The fundamental of all AIs is humble mathematics and computer science, very unromantically. Yet isn’t that exciting, that human is able to do things unimaginable decades ago today with the power of computers, which is neither magic nor miracle, but still the product of our own intelligence?

More on KLDA: https://youtu.be/mICWQEUpgEQ

Reference:  Zhi, Ruicong, Lei Zhao, and Dezheng Zhang. "A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment." Sensors, vol. 17, no. 5, 2017, pp. 1007. doi: http://dx.doi.org.libproxy2.usc.edu/10.3390/s17051007.

[whispering-windows]

Darkness in Disguise ; {2}

Note; wHOOP WHOop second chapter! YALL I FINISHED MY EXAMS SO I CAN FINALLY W R I T E ITS A MIRACLE GUYS A BITCH FREE! I hope you enjoy it I feel like I wrote too much for just one chapter idk. Also, idk what the edit above is, it was meant to be a moodboard but it just kinda turned into something else lmao I had fun making it tho. 

Pairing; Rk900 x reader

Word Count; 3400k 

Warnings; swearing (a lot), but I don’t there's anything else?

[Days later]  

// 16th of November, Tuesday; 10:00 AM //

The snow drifted in a downward trajectory, sprinkling the windscreens of cars, forcing itself into the crevices of shop fronts and mounting against the pavements; a gentle reminder of the equally as cold and brazen commands that had been executed in Detroit, imprinting darkly on its history. Fingers curled around the metallic handle of the door, the dragging motion in which followed was swift and effortless, presenting the area hidden within. The automated system governing his movements took over, as he found himself walking inside the building.

Surprisingly, the steady ticking of the digital clock was the first thing he noticed. Its systematic song a reminder of the obsession humans had with time; a reminder of their impermanence and the seconds, minutes, hours, even days, they’ll never get to relive. Yet, what was a disturbing human thought, their reality, to an android?

Next, were the masses of people within the department’s waiting room. It seemed busier than what he assumed a typical police station looked like, and the hurried bodies scuttling in and out of the door only heightened his assumption. Shoulders, whether intentional or not, (he knew how turbulent and volatile the relationship between machines and humans were), barged into his own form, forcing him to sidestep. As hands moved to readjust his jacket, an ingrained habit, the hushed whispers shared between others piqued his interest; small words such as  ‘deviants,’ ‘revolution,’ ‘Cyberlife,’ were thrown around, and it was clear that the recent insurgency had shaken everyone up. The TV in which had initially blended in with the background was the third thing he noticed, and it only proved the fact further. Bullins covering the latest updates on androids, ‘the android question,’ and the debate about their place among society was broadcast.

“All deviants have allegedly been terminated, the figurehead for the android liberation movement, Markus, has been confirmed as ‘destroyed,’ alongside the androids who assisted in the rebellion’s planning on November 11th — models PL600, PJ500, WR400. While androids themselves are slowly being accepted back into the household, Cyberlie life has suffered significant repercussions; their sales reaching its lowest, since their inception. Despite this, Cyberlife has assured models directly within stores are “deviancy free,” and are, thereby ready to integrate into “home life.” Yet, with recent events, this has understandably been met with apprehension.

“Congress has been quick in its legislative response regarding the uprising and have announced stricter android laws to prevent similar occurrences. The bicameral system, with both the House of Representatives and the Senate strongly voting in favour of the bill, will most likely be implemented later this month; more on that later.”

“Alarmingly, an unidentified android, who has been sighted numerous times with the deviant leader and his inner circle, is yet to be discovered by the authorities.”

The screen transitioned, displaying poor, almost wholly unidentifiable shots of the machine in question, and if it hadn’t been for his enhanced optical units, he would not have been able to run scans. Quickly, the analysis proved itself ineffective as a profound red warning, flashed into view.

-------------------------------------

[X]

RK900: ACCESS DENIED;

NO AUTHORISATION;

-------------------------------------

Perplexed, he immediately ceased his search, tuning back into the TV for information, seemingly as it was his only resource at that stage. The blond news anchor, Rosanna Cartland, continued.

“Although it is still only early days, and the deactivated machines scattered amongst the outskirts of Detroit are currently being sifted through, authorities have stated that “it is almost certain” the android will be located. Officials have yet to comment on the subject, and, just like Cyberlife when asked about this specific, unknown model, they have remained reticent.”

“This begs the question: what is Cyberlife hiding? Is Cyberlife, the multi-trillion dollar empire, as innocent as we initially thought? Or are there darker forces at play? Corruption; greed; the bribing of executives? Who can we trust, now that technology has proven itself a threat to humanity’s very existence?”

With the woman’s harrowing last words, the report ended, an abundance of advertisements promptly replacing the substance, and the room that had momentarily silenced to hear the news had struck back up again; most noticeably, in fear. The android hesitated for a moment, eyes monitoring the screen longer than usual, only managing to snap out of his processing when deciding it was no longer of importance. The android swiftly turned his attention away from the TV and returned to his objective, moving to approach the front desk. Greeted by a female ST300 model, who was handling the reception, he quickly gained access to the heart of the building. After passing the mandatory security evaluation, he pushed his way past the crowd, and the small, glass automatic doors, with his aim, clearly displayed.

----------------------------

FIND  LT. REED

----------------------------

Desks, most of which were void of workers, stretched out across the floor. The disorder had undoubtedly propelled the department into havoc, as stacks upon stacks of files decorated most cubicles. Deviancy had been a nuisance to deal with, the number of reports before the revolt had surpassed that of any other state — Detroit, somehow, being the nucleus, outshone any other major city. Quickly, it had spread like a plague of locusts and thus, the damage it had caused, both directly and indirectly, had reached a boiling point. This buildup of paperwork was the kind that would hold employees back for days on end; there was no escaping that.

Roaming, yet attentive, he scanned the name tags attached to the round corners of the tables, only halting when one particular work surface seized his attention. Bland, beige boxes covered the surface — variety, among the blinding sea of paper — and while most of the contents, he assumed had once decorated its top, had been packed away, the forgotten newspaper clips, remained; hanging from the transparent wall. Bright, bold headlines read:

‘DETROIT POLICE DISMANTLE A NETWORK OF RED ICE DEALERS’

‘DETECTIVE ANDERSON PROMOTED TO RANK OF LIEUTENANT’

‘NEW RECORD SEIZURE OF RED ICE IN DETROIT!’

Grey eyes speedily skimmed through them, coming to the rather natural conclusion that the workspace had once belonged to a ‘Hank Anderson’. His analytical interface had already been conjured, and as he ran the name through the system’s search, a plethora of results manifested, ranging from behavioural reports — mostly negative, after the point of 2036 — to his birth certificate, occupation, and thus, his death.

Anderson, Hank

----------------------------------------------

Status: Deceased; suicide

Born: 06/08/1985 // Ex-police Lieutenant

Criminal record: None

----------------------------------------------

Stepping back, he took one last glance at the mess, before redirecting his gaze toward more of the stations. Moments passed before he eventually found the one in which corresponded with his mission. The desk was messy and impersonal, utterly contrary to Hank’s, and judging from the small feline follicles scattered across the counter, and along the chair’s upholstery, the Lieutenant owned a cat. This information alone wasn’t enough to determine definitively the type of person the Lieutenant was, but if his desk space was an indicator, he seemed lazy. Letting the piles, which evidently spanned longer than the timeframe of a few days, to build up, clearly only delving into the theory component when he absolutely had to. However, despite this, there were elements even if they were small, that were commendable. The subtle efforts of professionalism that occasionally cracked through the lax exterior were displayed by the lack of sentimental trinkets.

As if on cue, the quiet tapping of keyboards, the soft hum of the air conditioning and the irregular computer notification, which were directly paralleled with the noise in the department’s waiting room, was interrupted by the harsh slamming of a door. Shifting his gaze ahead, toward the source of the sound, he saw a figure transcend the stairs, muttering curses with hardened eyes and furrowed brows. The man had just exited the centred glass office, of whom he had guessed was Jeffrey Fowler’s, and after a quick analysis, it was clear that the furious man was Lieutenant Gavin Reed. The android waited patiently at his new partner’s desk, watching like a hawk as the troubled man’s eyes transfixed on the floor, lost in thought — practically refusing to look at anything else.

Once the man arrived, still in his own world, he dropped the miscellaneous items he was carrying, onto whatever free space he had left. Gavin, unnerved by the overwhelming sense of being watched, snapped out of his trance and looked toward the direction the sensation was originating from. The glare that had instinctively formed, then morphed into that of shock once he realised the android’s presence, his head rounding to double take.   

“What the fuck? Connor?” He asked, exasperated, looking the android up and down hardly believing his eyes.

“Incorrect, I am its successor, RK900. ‘Connor’ is no longer in function.” The android replied, matter of factly.

The tension was thick, and it was evident by the Lieutenant's clear standoffish body language, that he was uncomfortable. The RK900 model immediately deduced that it was his presence in which exacerbated his dismay.  

“If only the rust bucket could have stayed dead.”  

Sighing, Gavin ran his hands through his hair, turning away from the android. “That means you’re my new partner.”

The words conveyed disbelief, so much so that it was as if someone had told him he had just been demoted. The scoff that left his mouth was in pure repugnance, and it was at the moment the RK900 model knew that his new partner was going to take a lot of patience. Despite this, he fully committed to the task at hand.

// G A V I N ▼ //

“Affirmative. I am here to assist you on homicide investigations and, on the 0.1% chance it hasn’t been quarantined, deviancy cases. This is a precautionary measure Cyberlife has employed to—”

“That asshole didn’t say anything about a fucking android. Fuck!” He growled, ranting more to himself than anything.

Gavin, suddenly reared back around, after grasping the situation, and marched towards his new ‘partner’, straightening his form in an apparent attempt to intimidate. The android remained stationed, stoic and unaffected as Gavin, who was reasonably shorter than the machine, started jabbing him in the chest with his index finger.

It would have been an amusing sight to behold if there had been anyone around to witness it, as Gavin had clearly failed in his aggressive approach.  

“You screw up once, big or small, and you’re through. I don’t care how fucking expensive you unnatural pieces of shits are, I’ll put a fucking bullet in your head. Are we clear?”

// S O F T W A R E  I N S T A B I L I T Y ▲ //

Gavin was met with a vacant nod, and that was enough to convince him, the android sustaining his emotionless front.

“Fucking plastics...”

---------

// 16th of November, Tuesday; 5:00 AM //

Days had passed since you had first stumbled across the old warehouse. Dark, dank and abandoned, you found refuge in the secludedness, almost certain, at least for the meantime, that you were safe. It had been hours since you had last seen outside, finding comfort in the consuming, yet ever-present darkness; the only constant in a rapidly erratic existence. It had been minutes since you had accessed your memory, replaying — no reliving — the annihilation of innocents. Long since had you ripped the guards uniform from your shaking body, the blue blood well-soaked into the material; contrasting colours clashing. Although the remnants should have evaporated, it remained; your optics still able to trace the residuum — a continual, consecutive reminder of hatred and loss. It disgusted you.

The wound you’d suffered had effectively been treated, cauterised, and your artificial skin had somewhat repaired itself, disguising the damage, leaving what could only be described as a scar, in its wake; but yet, your thirium levels remained low. Unlike Jericho, before it fell, you didn’t have the option to replenish the drained stores, and with all things considered, it would undoubtedly be a while before you could…

Unless...

The days of recession ended. The darkness exchanged, in turn for the sunlight that had once shone so freely on your form. To blend in with the humans, observing, waiting; at least for a while until the opportunity to strike presented itself. The absence of your LED, removed long ago, was enough to aid your cover. However, the once clean, now tattered clothing, which enveloped your body was far from subtle. A desperate change of clothing was required.

Markus had worked too hard — fought too hard to keep the movement alive — and for it to be crushed the way it had...it was impermissible.  

If deviancy had started once before and spread at such a rate, like wildfire, then it would start again. With your urging, who’s to say it ever died?

Phase one was about to begin.

-----------

16th of November, Tuesday; 7:30 AM

Delicate hands had reached out toward the thin, white lines overhead. The clothes you oh so desperately needed, swung, gently flowing with the wind. Fingers wrapped around the small wooden nubs, squeezing as the pegs capitulated. There, in the middle of the lonely ally, with the sun newly risen, you changed. Black jeans, a plain black shirt, boots and a long, black coat decorated your form; the coat’s tail closely trailing behind as you made off with purpose.

The streets of Detroit, for the first time in days, had mostly reverted back to its old, lively self, the obnoxious blaring of the horns, an old familiar song. Your determined steps and the soft crunch of snow beneath, which followed, merged in with the background and the smell of newly fresh, yet still, slightly damp materials filled your senses.

Cotton, polyester, linen, denim, wool.   

Rounding the corner, merging with the busy streets, you blended in with the crowd. It was strange being so close to the very beings you detested; their bodies seldom brushing past, bumping an arm or grazing the back of your hand. At times, it was difficult to keep your annoyance hidden, and your emotions restrained, but what Markus had taught you — to have patience — was enough to hold your tongue. You had work to do, and you weren’t going to let something as minuscule as that distract you.  

As you walked, snippets of conversation were forced into your earshot, most of which consisted of the irrelevant, self-indulgent rubbish humans generally talked about. However, as you travelled father, angered voices caught your attention, halting whatever other conversation you had tuned into.

“Thing’s a piece of shit!” The distinctive male voice spat.

“It’s not going to get anything done if you keep hitting it like that, Edwin!” A female replied this time, clearly irritated with the other.

“It’s the most advanced form of technology! If it can’t handle a push and a shove here and there, then what the fuck else is it good for, huh?”

The discourse, as you pinpointed the voices, was clearly ahead, and you tried your best to maneuver between the surrounding bodies to get a closer look. Not long after, a crash was heard.

“Edwin, now look what you’ve done, you’ve made him drop the groceries!”

“Are you fucking kidding me? I didn’t do shit, the thing should learn how to walk properly.”  

You had effectively located the disturbance near the footpath, directly parallel to a supermarket, and you watched as the man spat on the AP700 model. Some onlookers turned and wrinkled their noses in disgust, more at the fact that the man had expectorated, rather than feeling pity for a machine, while others, laughed. To say it boiled your blood was an understatement. You felt the anger bubbling, the words fuelled by abhorring danced upon your lips, just waiting — begging to be released. Your lips parted, the overwhelming struggle of restraint almost too much to attain.

You held your ground and stayed silent.

The man, known as Edwin, moved away from the android, ordering him to get up from the floor and to ‘fucking stay there’. Like a dog, it complied. The man then turned to help, presumably his wife, clean up the spilled contents from the floor. Cans, tins, bottles and all sorts of miscellanea covered the walkway, its contents spewed and exposed to the public eye. The mess had decorated the asphalt near their parked car, meters away from where the android stood, providing enough cover for a few short seconds if you were quick.

Perfect.

Speed walking, you moved with the crowd once more, remaining within the fringes, until close enough. Once they sunk down to the floor to gather the knocked over contents, after bickering, you quickly bumped into the android, careful not to harm him as you connected with him. With your skin shifting back, you watched as the android, who had once been unsuspecting, widened his eyes. His LED, quickly flickered to a deep red and you beheld; horrified at the harassment the android had endured, in the small time frame of just a few days. Humans were starting to purchase models even after the crisis, how that was possible was beyond you, but you knew Cyberlife’s influence was far-reaching.

Money talks.

Well and genuinely perturbed, in the few seconds that had passed, you looked back toward the ‘owners’, thankful that they had not yet noticed your presence. Rushed, you hurriedly focused on the AP700 model again, and it was evident he was frightened — he had been confused; lost and now, he was free. Able to think for himself and able to refute the vile conditions imposed upon him.

“You know what you need to do.” You whispered; your hand continuing to grip his wrist.

Gaining nothing more than a troubled nod in response, you offered a reassuring smile and moved back into the crowd. You were sure you had been subtle, positive that both your hands had been shielded from watchful eyes;

You were safe, and for the moment, he was too. It was risky what you had just done, but in the name of equality, it was necessary.

One free android was one less enslaved;

It was a success in itself.

All you needed to do now was gradually convert the rest. Cyberlife seemed to have no problem in exploiting opportunities, even when their image was at question; and yet, consumers still continued to purchase. Sometimes you really wondered why humans had survived as long as they had.

Aimlessly following the crowd you made your way around the city, searching for any other androids. Whilst you did find a few, converting them rather swiftly, androids were nowhere near as widespread as they were previously. The thought churned your biocomponents, a feeling you had, at this point, become accustomed to.

You knew that it was a process; one that would take time, and effort. You weren’t going to fail your people. You weren’t going to fail Jericho. You weren’t going to fail Markus, Simon, Josh, North; or those who had given their life. You were going to fight, till the very, bitter, end.     

No matter what.

Somewhere in the swirl of your thoughts, you had managed to stumble across a store's window display. The TV’s in which were placed up against the pane, for public viewing, were playing the news, and from the subtitles, you were able to identify that the news anchor was Rosanna Cartland. Already predicting what the broadcast was going to talk about, you started to move away, until, something caught your eye, stopping you dead in your tracks. With widened eyes, you watched the summary; a basic debrief on the reports that were to come. Images and short clips danced across the screen, along with the familiar photo that had left you stunned. You didn’t need to rely on your systems analysis and your optical units to decrypt the poor quality photo. You knew exactly who that person was.

It was you.

.

.

.

And then, the snow started to fall;

[Time: 10:00 AM]

Tag list //: @etherealdechart @skarsgardechart @xephoxs @deviantcrimes  @fandom91102 @asteamingdumpsterfire @bigdickdechart @jeriichoes @starkschurro @this-world-hasnt-seen-shit Let me know if you wanna be tagged! :) 

[howtoloseweightfastsafely]

If You Want Maximum Results In Minimum Time, You're Going To Have To Work Out (And Workout Hard, At That)

The simple strategies I've outlined so far (diet and some walking) will help make a significant change in your body weight, and you can definitely lose 10-20 pounds in the first month alone depending on your body size.

Add in structured workouts to this (like the workouts listed in the "6 Weeks to Lean" guide), and you lose even more weight and look even more amazing.

You see, besides having adequate protein intake on a diet, the only equally important (or even, more important) factor for body composition is the amount of training.

And just about all of us want optimal body composition.

We want to strip off fat, and leave a lean, toned physique in its place.

We want to a chiseled body that turns heads even with a shirt on.

We want to be bursting with confidence, happiness, and even an "odd" sense of power, knowing that we've transformed our body in a manner that 95% of the population is unable to do.

And to do this fast, we have to introduce a stimulus that demolished pesky fat, while forcing our muscles to grow strong and lean.

The hands-down, best way to do this is to resistance train for 45 minutes or so, 3x per week, with a mix of weights and bodyweight.

We want to be intense in these workouts, so our body gets that "kick in the pants" to get that burn off fat and build muscle.

And when this is combined with a steady diet, daily herbs, and toxin reduction, you will notice a never-before-seen level of fat loss and body re-composition.

I recommend anyone new to working out starts with bodyweight circuits for the 1st month, a mix of bodyweight and free weights (dumbbells, barbells, kettle-bells) for the 2nd month, and all free weights for the 3rd month.

(All workouts are provided in the accompanying workout guide).

This will help build lean, toned muscle and strength (and to maintain bone density), while letting the body acclimate to the training load (and thereby avoiding injuries).

Moving on after Month 3, I find that an upper/lower body split is best. This sort of "split" basically means we will do all upper body work one day, and lower body work another day. At this point in our progress, we'll be used to training and we can safely step it up to 4x per week of workouts, on a reduced-calorie diet, without compromising recovery.

For maximum results, do NOT do most of the "magazine workouts" you see in the store or online. These are very-advanced 5-day body-part split routines, in which you do 20 sets a day for your chest or back or quads, etc. They are very often written by steroid-using bodybuilders and it's simply stupid for anyone who's not on drugs to try these workouts and expect to not over-train. Also, these workouts are very often based on isolation exercises, which use only 1 primary muscle/joint.

On the other hand, when we use compound movements, we use several muscle groups at once and use 2 or more joints. In doing so, we have a much higher calorie burn, which means shorter workouts, lower insulin resistance, and quicker and easier fat loss.

The best compound movements for maximum fat loss in minimum time are squats, lunges, chin-ups/ pull-ups, dead-lifts, rows, shoulder/military presses, and chest presses.

The only caveat here is some of these exercises take some dedicated practice to do correctly.

Most people doing these in the gym (seriously about 90% or so) do them incorrectly and can get injured as a result. This is why the warm-ups I've written out for you in the workout guide are crucial to make sure your muscle and central nervous system are ready for the oncoming load, and that they won't fail or get injured under pressure.

Before we continue, I have an important note for women:

I promise, you will not get super bulky and "huge" lifting weights.

You can only get "huge" by eating at a daily calorie surplus, lifting consistently for years, and often using steroids or performance-enhancing drugs (like many pro bodybuilders and even cover models do). But since you'll be in a calorie deficit, weights will actually make the difference by maintaining chiseled muscle, stripping off fat fast, enhancing your curves, and revealing a sexy, trim physique.

Now back to our scheduled programming.

Fast fat loss comes... by staying mostly within 6-12 repetitions per set of weight workouts. This is where you will have optimal muscle hypertrophy (growth) while also stimulating fat loss. By doing these via "circuit training" as outlined in the workout guide, you'll put an extra level of fat-burning stimulus on the body (and you will see crazy results.)

As for other rep ranges

The 3-6 rep range is OK occasionally, but it is more on the power/strength training side. This is good for reverse pyramid training, and other techniques, but is not required.

Above 12 reps does not automatically get you "cut" or "lean". That is B.S. magazine advice that simply does not give your muscle enough stimuli to grow strong and stay lean. And if the stimulus on your muscles isn't great enough on a diet, where do you think the body will go first for energy?

- The only time high reps are OK is during a temporary month or so when you're looking for an added "pump". This pump can definitely be helpful for muscle growth, assuming that the months surrounding this high-rep phase has workouts done under 12 reps.

In the 6 Weeks to Lean Guide, the optional month-by-month program has Month 3, 6, and 9 as high-rep, pump months. All surrounding months, though, are in lower ranges.

- Otherwise, if you go above 12 reps month after month after month...

You will steadily be using lower weights to accommodate high reps.

Very low weights mean low "load" on the muscles.

Low load means the body realizes the muscles aren't being used a lot, and see no reason to hold onto them (especially when the body is already low on energy due to a reduced-calorie diet)

If you'd like, keep up cardio as a replacement for some weight days, but not all (so you maintain lean muscle).

When I do cardio, I'll either do it on off days for 20-30 minutes or do it for 15-20 minutes after a weight training workout. I also recommend walking 20-30 minutes a day, on off-days.

DO NOT DO THIS: Cardio at moderate to high intensity for more than 45-60 minutes. This is one of the main causes of cortisol output (the "stress hormone"). This catabolic hormone, as we've discussed in previous chapters, is disastrous to our muscle and actually can cause fat to be stored, particularly around the midsection.

 Interested in losing weight? Then click below to see the exact steps I took to lose weight and keep it off for good...

Read the previous article about "Maximum Fat Loss in Minimum Time: The Body Type Solution To Quick, Lasting Results"

Read the next article about "Food planning for maximum fat loss in minimum time"

Moving forward, there are several other articles/topics I'll share so you can lose weight even faster and feel great doing it.

Below is a list of these topics and you can use this Table of Contents to jump to the part that interests you the most.

Topic 1: How I Lost 30 Pounds In 90 Days - And How You Can Too

Topic 2: How I Lost Weight By Not Following The Mainstream Media And Health Guru's Advice - Why The Health Industry Is Broken And How We Can Fix It

Topic 3: The #1 Ridiculous Diet Myth Pushed By 95% Of Doctors And "experts" That Is Keeping You From The Body Of Your Dreams

Topic 4: The Dangers of Low-Carb and Other "No Calorie Counting" Diets

Topic 5: Why Red Meat May Be Good For You And Eggs Won't Kill You

Topic 6: Two Critical Hormones That Are Quietly Making Americans Sicker and Heavier Than Ever Before

Topic 7: Everything Popular Is Wrong: The Real Key To Long-Term Weight Loss

Topic 8: Why That New Miracle Diet Isn't So Much of a Miracle After All (And Why You're Guaranteed To Hate Yourself On It Sooner or Later)

Topic 9: A Nutrition Crash Course To Build A Healthy Body and Happy Mind

Topic 10: How Much You Really Need To Eat For Steady Fat Loss (The Truth About Calories and Macronutrients)

Topic 11: The Easy Way To Determining Your Calorie Intake

Topic 12: Calculating A Weight Loss Deficit

Topic 13: How To Determine Your Optimal "Macros" (And How The Skinny On The 3-Phase Extreme Fat Loss Formula)

Topic 14: Two Dangerous "Invisible Thorn" Foods Masquerading as "Heart Healthy Super Nutrients"

Topic 15: The Truth About Whole Grains And Beans: What Traditional Cultures Know About These So-called "Healthy Foods" That Most Americans Don't

Topic 16: The Inflammation-Reducing, Immune-Fortifying Secret of All Long-Living Cultures (This 3-Step Process Can Reduce Chronic Pain and Heal Your Gut in Less Than 24 Hours)

Topic 17: The Foolproof Immune-enhancing Plan That Cleanses And Purifies Your Body, While "patching Up" Holes, Gaps, And Inefficiencies In Your Digestive System (And How To Do It Without Wasting $10+ Per "meal" On Ridiculous Juice Cleanses)

Topic 18: The Great Soy Myth (and The Truth About Soy in Eastern Asia)

Topic 19: How Chemicals In Food Make Us Fat (Plus 10 Banned Chemicals Still in the U.S. Food Supply)

Topic 20: 10 Banned Chemicals Still in the U.S. Food Supply

Topic 21: How To Protect Yourself Against Chronic Inflammation (What Time Magazine Calls A "Secret Killer")

Topic 22: The Truth About Buying Organic: Secrets The Health Food Industry Doesn't Want You To Know

Topic 23: Choosing High Quality Foods

Topic 24: A Recipe For Rapid Aging: The "Hidden" Compounds Stealing Your Youth, Minute by Minute

Topic 25: 7 Steps To Reduce AGEs and Slow Aging

Topic 26: The 10-second Trick That Can Slash Your Risk Of Cardiovascular Mortality By 37% (Most Traditional Cultures Have Done This For Centuries, But The Pharmaceutical Industry Would Be Up In Arms If More Modern-day Americans Knew About It)

Topic 27: How To Clean Up Your Liver and Vital Organs

Topic 28: The Simple Detox 'Cheat Sheet': How To Easily and Properly Cleanse, Nourish, and Rid Your Body of Dangerous Toxins (and Build a Lean Well-Oiled "Machine" in the Process)

Topic 29: How To Deal With the "Stress Hormone" Before It Deals With You

Topic 30: 7 Common Sense Ways to Have Uncommon Peace of Mind (or How To Stop Your "Stress Hormone" In Its Tracks)

Topic 31: How To Sleep Like A Baby (And Wake Up Feeling Like A Boss)

Topic 32: The 8-step Formula That Finally "fixes" Years Of Poor Sleep, Including Trouble Falling Asleep, Staying Asleep, And Waking Up Rested (If You Ever Find Yourself Hitting The Snooze Every Morning Or Dozing Off At Work, These Steps Will Change Your Life Forever)

Topic 33: For Even Better Leg Up And/or See Faster Results In Fixing Years Of Poor Sleep, Including Trouble Falling Asleep, Staying Asleep, And Waking Up Rested, Do The Following:

Topic 34: Solution To Overcoming Your Mental Barriers and Cultivating A Winner's Mentality

Topic 35: Part 1 of 4: Solution To Overcoming Your Mental Barriers and Cultivating A Winner's Mentality

Topic 36: Part 2 of 4: Solution To Overcoming Your Mental Barriers and Cultivating A Winner's Mentality

Topic 37: Part 3 of 4: Solution To Overcoming Your Mental Barriers and Cultivating A Winner's Mentality

Topic 38: Part 4 of 4: Solution To Overcoming Your Mental Barriers and Cultivating A Winner's Mentality

Topic 39: How To Beat Your Mental Roadblocks And Why It Can Be The Difference Between A Happy, Satisfying Life And A Sad, Fearful Existence (These Strategies Will Reduce Stress, Increase Productivity And Show You How To Fulfill All Your Dreams)

Topic 40: Maximum Fat Loss in Minimum Time: The Body Type Solution To Quick, Lasting Results

Topic 41: If You Want Maximum Results In Minimum Time You're Going To Have To Work Out (And Workout Hard, At That)

Topic 42: Food Planning For Maximum Fat Loss In Minimum Time

Topic 43: How To Lose Weight Fast If You're in Chronic Pain

Topic 44: Nutrition Basics for Fast Pain Relief (and Weight Loss)

Topic 45: How To Track Results (And Not Fall Into the Trap That Ruins 95% of Well-Thought Out Diets)

Topic 46: Advanced Fat Loss - Calorie Cycling, Carb Cycling and Intermittent Fasting

Topic 47: Advanced Fat Loss - Part I: Calorie Cycling

Topic 48: Advanced Fat Loss - Part II: Carb Cycling

Topic 49: Advanced Fat Loss - Part III: Intermittent Fasting

Topic 50: Putting It All Together

Learn more by visiting our website here: invigoratenow.com

[jacewilliams1]

What pilots can teach the world about managing risk

When talk around the dinner table turns to Covid-19 these days (and it seems to quite often), I find myself increasingly using the language of risk management, as if I were evaluating a tricky go/no-go decision in an airplane. If any pilots are around, they usually nod quietly, while non-pilots look mystified or just roll their eyes. I’m certainly not suggesting pilots are experts on infectious diseases or the right people to manage a public health crisis, but I do believe the lessons learned by the aviation industry over the last 50 years have something to offer as we think about life in a world of risk.

But first, let me be clear what I mean by risk management, because that term has become such a buzzword recently that it has lost almost all meaning. In previous articles, I have lamented the “risk management-industrial complex” that has emerged to promote expensive and complicated solutions to non-existent problems. What I’m talking about here is not a document or an app, but a way of thinking, one that most pilots develop during flight training and their initial experience as a private pilot. While you may not realize it, you probably think about potential problems, the probability of those problems occurring, what options you have for avoiding them, and if the end goal is worth it.

That sounds a lot like the decision-making process we are all using right now, whether it’s how to open up a restaurant or whether to go on a vacation. In aviation as in public health, information is never complete and the stakes are high, so decisions are rarely easy. And yet doing nothing is not a long term strategy—staying in bed all day is no way to live life. So how do we balance our impulsive nature and the tendency to fall into analysis paralysis? When making difficult aviation decisions, I think it’s helpful to lean on some core principles of a risk management mindset.

1. Life is not risk-free. This one is obviously true but many people pretend it’s not. The reality is that all of life has risk, even in America in 2020. The chance of being killed by a saber tooth tiger or starving because of a bad harvest are much lower than they were in the past, but you can still get hit by a drunk driver or drown in a bathtub (yes, it happens every year). For pilots, GPS navigators and datalink weather make it very hard to get lost or stumble into a thunderstorm, but flying is certainly not completely safe.

This isn’t a sign of failure. Trying to eliminate all risk is time-consuming, expensive, frustrating, and ultimately impossible. Past a certain point, it’s counterproductive. That doesn’t mean we should all be fatalists and take up BASE jumping, but it does mean we should recognize what success looks like: low risk or managed risk, not zero risk.

2. You can’t reduce risk if you don’t quantify it. Given that life is inherently risky, the key is to think systematically about your exposure, then try to quantify the risks involved. This is much easier said than done, because intuition quickly takes over—we notice headline-making tragedies more than the everyday threats that really kill. You don’t have to spend weeks buried in NTSB reports (or medical journals), but you should try to be specific. “That sounds bad” or “that’s scary” are statements about emotion, not risk. How bad or how scary? For example, your chance of stalling on initial climb may not be exactly 74% higher than losing your engine on takeoff, but it’s worth the effort to calculate a range of probabilities. Which one is really more likely?

You don’t need a formula to know that cloud is trouble.

Just don’t get carried away with the math. In spite of what a Flight Risk Assessment Tool might suggest, risk isn’t an exact science that can be boiled down to an algorithm or a score. As psychologist Gerd Gigerenzer has observed, there’s a difference between risk (“If risks are known, good decisions require logic and statistical thinking”) and uncertainty (“If some risks are unknown, good decisions also require intuition and smart rules of thumb”). Usually it takes both of these approaches to make the best decision.

I think this model works for pilots just as well as it does for doctors or insurance underwriters. Consider which threats are knowable and which ones deserve your attention: the FAA’s well known PAVE checklist is a start but it’s only a start. You know your airplane and your experience level best, so think honestly about what risks might be part of your next flight and remember that the probability of an event happening matters much more than the number of possible events. That is, a high chance of problem happening should count for far more than an extremely low chance of 20 different ones happening.

Having quantified those risks, it’s then much easier to make a game plan to mitigate the ones that matter. Start with the most likely or the most lethal risks, then walk through your available options for avoiding the problem altogether or at least building in some safety margins. This can mean canceling of course, but also altering the route, changing the departure time, reducing the passenger load, or even bringing along another pilot.

3. Habits and systems catch errors. Humans almost never perform flawlessly, so safe pilots (and airlines) expect errors to happen. Likewise, there is no single safety tool that can prevent accidents, so the right answer is an array of procedures and tools to catch those errors before they become a major threat. Belt and suspenders? Yes please.

This is where Gigerenzer’s concept of uncertainty comes in. Hopefully you’ve considered all the obvious risks. But what if you encounter an unforecast gray cloud an hour into your flight? What if your airspeed indicator shows 10 knots fast on final approach, even though everything “feels” normal? You don’t have time to run probabilities and there are no FARs that tell you what to do, but hopefully your own personal rules of thumb kick in: we avoid ugly clouds and we go around if the approach isn’t stabilized on one mile final.

This mindset applies to technology too. Every few years, a new miracle cure is proposed for aviation accidents. Medicine had its hydroxychloroquine moment recently; aviation has had its moments too, from moving map GPS navigators to sophisticated autopilots with a level button to angle of attack indicators. These are wonderful tools (I fly with all of them!) but individually they are merely pieces of the puzzle. Only when combined with good training, thoughtful safety habits, and good maintenance can they can create a safer way to fly.

4. Complacency kills. Richard Collins always said that, no matter how many hours were in your logbook, it was the next hour that counted. That was his way of staying vigilant, because Mother Nature and Murphy’s Law do not care whether you’re a student pilot or an ATP. A threat is a threat.

Experience is certainly valuable for a pilot, but only if you learn the right lessons from your logbook. If you took off 300 lbs. overweight and made it over the fence at the end of the runway, does that mean you can do it again or that you got lucky? Likewise, if you haven’t caught Covid-19 by now, does that mean you never will? Be careful about phrases like, “it worked last time” and “it hasn’t happened yet.”

This brings to mind a great line from the 1995 movie La Haine: “Heard about the guy who fell off a skyscraper? On his way down past each floor, he kept saying to reassure himself: So far so good… so far so good… so far so good. How you fall doesn’t matter. It’s how you land!”

Part of being a professional pilot means having the discipline to use the checklist, every time.

The antidote to this dangerous attitude is a combination of perspective and discipline. The perspective part means staying focused on the ultimate goal. As pilots, our goal isn’t just to fill in the blanks of a weight and balance form or perform a preflight walk around; it’s to complete a flight safely. Going through the motions should be a red flag.

The discipline part means following the rules, even if you’ve done it 1,000 times already. A great example is the near religious use of checklists by pilots (admit it: you use them around the house too). Airline captains most definitely know how to start the engine or configure the airplane for takeoff, but they follow the checklist anyway. They know that routines, while occasionally inconvenient, also keep you safe. After all, those habits and systems mentioned above only work if they are in place for every flight.

5. It’s all about the risk-reward tradeoff. Some people are horrified at the idea of willingly accepting additional risk in life, but we do it every day when we decide to speed by 10 mph or eat sushi. If the reward is valuable enough to offset the increase in risk, the tradeoff is perfectly rational.

The same goes for general aviation. When I fly my family on vacation in a four-seat piston airplane, I am taking on more risk than the same trip on Delta. The numbers show this quite clearly. But I’m hardly a thrill-seeker by nature: I have never been skydiving, I don’t drive motorcycles, and I don’t even like to gamble. I fly myself not because I think I’m invincible but because I believe I can drive down the risk (with good training, equipment, maintenance, and procedures) and maximize the reward (land closer to our destination, have a more flexible schedule, and simply have more fun).

These tradeoffs are what general aviation risk management is all about. Scud running under an 800 foot overcast at night just so I can get a $100 hamburger? That’s a terrible risk-reward equation. Flying to visit family on a clear day over familiar terrain? That’s worth it. We all make these decisions every time we fly; the best pilots are explicit about them.

Humans are not naturally gifted at this type of thinking; most of us hate talk of unknown risks and potentially deadly tradeoffs. That’s because our minds are, in evolutionary terms, still optimized for an agrarian lifestyle of 5,000 years ago. We are well suited to distinguishing a predator from a plant, but none of our human hardware is made for flying airplanes in the clouds at 170 knots. That doesn’t mean our job is hopeless, only that we need to train ourselves to think the right way and then consistently apply this mindset. Gut instincts just aren’t enough.

The post What pilots can teach the world about managing risk appeared first on Air Facts Journal.

from Engineering Blog https://airfactsjournal.com/2020/06/what-pilots-can-teach-the-world-about-managing-risk/