What is going on guys welcome back to the channel critical overload here So this would be my spoiler field spoiler field review for Jordan pills Nope movie that comes out this weekend Directed by Jordan Peele written by Jordan Peele starring Danny Kalua Kiki Palmer Steven Young and a few other individuals who make up the cast such as the character of Angel play by Brandon Parea Michael Wing cock who plays antlers host and a few others like Keith David Barbie from euphoria is also in it for those of you who've been wondering about that because there's she wasn't featured in any footage But the movie begins revolving around the Haywoods Emerald in OJ Haywood to be more specific After random objects falling from the sky results in the death of their father ranch owning siblings OJ and emerald Haywood attempt to Capture video evidence of an unidentified flying object with the help of tech salesman Angel Torres and documentarian antlers host now Again, I've had a few days to sit on it. Nope remains the satisfying spectacle I said it was during my spoiler free review again I've had a few days to rest on it consider the other logical flaws that do exist But don't completely destroy the entire narrative like I felt was starting to happen like us with with us his last project And I'm confident in the rating I gave it So jumping into the story after OJ emerald Haywood's father again gets killed by a nickel that falls from the sky They are forced to oversee the company and the ranch since they provide horses to hollywood productions to be used for stunts Emerald is more open and AJ or OJ rather is more is more open and extroverted OJ is more reserved He seemed to be a lot more dedicated to their father's business whereas emerald has side gigs as she called them The relationship between the siblings wasn't explored how I thought it would be or how I wanted it to be But the performances sold me on their banter and the relationship repairs that were happening on screen And it was sold we explored enough to the point for me to be invested in them and their character progressions as it pertains to the Plot that unfolds Kaluya and Palmer again They have wonderful chemistry and I did mention before that the performances across the board are great Although again Barbie who is in this movie from euphoria Cat she felt more like she was just in there for a random cheap jump scare I really wasn't a fan of that she was a nothing character Honestly angel who is the character that comes in to help the siblings as a recently single individual hates his job It fries the tech score and is good with camera installation Honestly, he seemed like he was just searching for something to be a part of more than anything. I think that was his arc He's a good addition to the trio. They're all likable But I'd still call him an underwhelming character as far as just considering how much he ended up being involved with the narrative So what's up with the UFO? Well, we know Stephen Young stars as jupe a former child star that now runs Jupiter's claim that isn't too far from the Haywood ranch jupe was a member of a show involving Gordy the chimp in the late 90s The chimp snapped one day and killed every crew member but jupe now as an adult Jupe has made a discovery that he believes is a spacecraft with aliens on board at some point. I guess Jupe attempted to tame the UFO and those efforts sparked it to consider this area its home so OJ had been selling jupe horses in an effort to save their ranch and Jupe has been feeding the horses to the UFO to gain the alien's trust Jupiter's claim is just a giant is just all a set up a front to profit off his continued efforts to gain the alien's trust by Turning those efforts into a spectacle which again is a big theme in this movie now when considering jupe's Gordy encounter in the 90s I'm guessing that might have left him thinking he had a special bond with animals and taming them or something So in the film's twist is revealed that there aren't really the aliens you were expecting or might be expecting The UFO is actually a creature and that's all I really want to say about that there. It's it's a creature an Unidentified flying creature. I'll call it So the script is riddled with commentary also about film crews and how they don't get the recognition They deserve societies obsession with being first the cycle of the media the dangers of child stardom since that's exactly what you represented exploitation of animals and so much more My thing is I just felt the narrative wasn't always coherent or might have been too vague at certain points And I again definitely will understand those that come out thinking what was the point of that pill is aiming very high here It's again his most ambitious project and he knocks it out for the most part The cinematography is truly breathtaking especially the night shots and the shots that effectively make the sky something terrifying to look at The way Spielberg managed to make the water scary with jaws He is able to accomplish that here with the sky in nope and again It's very much so feels like he's very influenced by Spielberg movies and a little bit of M. Night Shyamalan Kaluya does a really good job selling you on the terror that's established at night with these gazes He does up in the sky and there is a very tense moment that I'm sure will scare a lot of people and the pacing in the scene Is so so amazing. It actually allows it to get under your skin a bit. It has actual aliens in the sense of What you saw in the trailer that moment did involve what appeared to be aliens But yes as many people thought of it's revealed to be just three kids playing a prank now again a giant part of this film feels Like an homage to jaws So that scene makes a lot more sense if you've seen jaws and remember that prank scene that I'm thinking of Michael Abel's score also factored in combined with that cinematography Just makes this an anxiety inducing experience for the most part at times Especially if you're someone who maybe has a fear related to the sky the pacing again is another highlight I again can admit that maybe it does start out a bit slow But pills still reels you in with a horrifying event at the start like he's done with his previous two movies He definitely enjoys again taking you on this slow This disturbing experience of a movie that just slowly but surely keeps you on the edge keeps you unease and Then kind of just completely immerses you in this third act specifically Which again the entire third act of this movie is a brilliant homage and love later. I would say two jaws I'm literally looking at the movie going that's quint that's chief roadie So on and so forth like I mentioned in my spoiler free review as for the performances again Kiki Palmer She was definitely the highlight here for me. She was the highlight Daniel Kahlua is amazing as his character, but given that this is a more reserved character He was written with he still is doing a brilliant job in the role But someone has a lot more energy to them and gets to shine a lot more because of that and that's Kiki Palmer She is doing she's running laps around her other co-stars. I would say I hope she gets some award recognition I'm not saying she necessarily needs to win But I would appreciate seeing her get some award recognition for what she does in this movie The movie does have some very emotional moments Maybe some moments that you come out saying they don't really feel all that earned The biggest downfall for me. Honestly was just some of the script a little bit incoherent didn't feel too focused at times and Probably a little bit too vague But I think a lot of that might come together for those of you who watch it when you see it as it starts to make sense in The second and third act again beautiful cinematography some of the best I've seen from him while I would still say get out Is his strongest I would put this as a close second I just still think that us and that screenplay kind of unravels a bit too much when everything is revealed there So let me know what you guys think about all this down in the comment section below I'm still giving in a seven and a half out of ten if you haven't already of course make sure you subscribe turn on post If you can never miss a video in the description I have links on my social media accounts on Facebook Twitter and Instagram You can message me there of course to let me know if there is any movies news or reviews You would like me to cover in the future with all that in mind guys. I will see you in the next video


All right. So we've already seen how we select other coordinates for both the enrollment and the event as Pamod mentioned before. So you can select coordinates either through enrollment points, event points, or you can have your enrollment, your data element or attribute type of type coordinate. So that also allows you to select the additional coordinates in addition to enrollment and event. As we saw in the track identity instance layer, the track identity layer you are able to plot in the track entities based on their enrollment coordinates. Similar to that you also have event layer which allows you to create clusters based on the event coordinates added in the program stages. So since it takes into account all the events that are created for that respective period and given that the coordinates are available, it will create these event clusters. So if a person has two events in the selected time period, so both the events become part of the cluster because it is taking events into account, not the unique number of patients. So that's the key difference between the two layers. The track identity layer looks at the unique track identity instances in the program. While the events layer will have a look at the events layer will have a look at the total events added in the selected period which may include repeated events for one track identity instance. So that's the key difference between the two. So let's look at one example where we can see the event clusters. So let's have a look at the favorite which is already created. And we can have a look at the layers that have been used here. So you see here you have organization units the boundary layer is at level three. So that has been set accordingly. Then the important is to look at the event layer which is added here for the lab result stage. So if I click on the edit button, I'll see the selections which are made here. So the program. So whenever you want to create a chart with event layer with grouping the events together basis on the basis of their coordinates. You select a program to select the stage and then you select the coordinate field. Now here in this program the event coordinates are the only field available, which is the event location field shown here. But in case if you were collecting coordinates in the program stage in this program stage through a data element also for example additional sets of coordinates. Then you'll have two fields here one for the event location and one for the data element which is also a coordinate type. So you can create clusters on the basis of both the coordinates that you're collecting either the event coordinates or the coordinates which are collected via data element or a program or a or a So both these options are supported. Then you can filter by the event status where they want to see all you want to see active completed so depending upon the status of the event the results will get filtered accordingly. Once you selected the data in the period you can either select relative periods. So in the list of all relative periods are given here. Or if you want to select start in dates then you can select fixed period as well but then the period should be based on two dates start and end date because it will count the events which lie between the dates that you've given. Okay, so for this example we had chosen this year as a relative period. For units, you can in order to keep this chart dynamic, you can select the levels from here. So we want to see all the levels. That is the grand children level at which the all data is collected so you selected two weeks below. So depending upon how your hierarchy is set up you can select the organization units from here. So if you want to keep this chart relative and be flexible enough to meet the requirements for all the users working at different organization units province and districts. For example, then you can select two weeks below because both these kind of users will have access to these are units so they will be able to see the clusters based on their designated districts and provinces. So now we've seen we selected the data we selected the period we selected the organization units. In while creating your clusters, you can put filters and other filters could be of data elements or they could be program attributes as well identity attributes as well. So here's the example you have we have added the data element lab test result. And then we have added the since this had an options that associated to it so we selected that we only want to see the grouping of events where the lab test result came out to be positive. You can select these filters and you can add more than one filter also for example if you're only looking at the mail cases then you can select mail from here. So then it will get revised automatically for now I'll just remove this filter. Then in styling you can style your clusters by different data elements. If you want if your data element has different options associated, then you can select a data element and then the options for that data element will be shown automatically here. Okay, so for example, if I'd selected this then I see all the options associated here, but we want to see the the positive cases by the agenda. So gender has two options male and female so you can choose the color which you want to give to female and which you want to give to male. Okay, so once you make all these selections, you if you want to group these events together then you select group events if you want to see individual events, one event, each event individually then you can select view all events. Okay, if you do grouping then it will automatically create these donut clusters for you why this is being shown as donut because you've done additional styling and have used data element that you want to style by data element which has certain options and then to those options you have assigned two colors. So hence it shows you the result as a donut where you have total three cases so based on the proportion we see here probably two cases are male and one is female so likewise you can design your clusters accordingly. If you wanted to see data for individual events, then you can go to view all events and click on update layer. So you'll see individual events by different colors, but the they will no longer be grouped together. Okay, so these are the individual events which are there. So for each event you can see the gender, the type of test in the lab result which is positive what was the facility, the date time of event or the date of event and the event location. If you want to switch it over back to group events then you can group events and it will again turn into a cluster. So what we'll do now is let us revise this and see from scratch how we can create this one. Okay, so let's try to recreate this one. So I'll go to file, click as new. So I'll start by adding my boundary layer. So I'll go to the boundary layer or the organization units layer, select level three and add layer. So it will automatically add the district boundaries or the boundaries against the level three organization units which are there. Next I'll go and I'll add an event layer. We're into select the variables. So I'll select the program and select lab results. This is the only coordinate field available. So this will automatically be selected. Then I'll go to period. I'll select last one year. Just like this year. Organics, we want to keep it relative and dynamic. So we select the lowest level available. So we select two X below. Now we can add some filters. So from these events, so lab result event will be of all types. You will have lab result event for positive cases, negative cases, inconclusive cases, but you only want to see data for positive cases. So we'll select the data element as lab test result. And since it has options associated. So you, and we only want to see positive cases. So we select as positive. But you can add multiple filters also if you want to. Next you move to style. Now here we want to see donut clusters, which are disaggregated by gender. So we'll select sex as our attribute. And then you have female and male as your options. You can change the color. So you can make the female as pink and male you can select as blue. And you can click on add layer. So by default, you'll always see group event selected. If you want to see individual events, then you can click on the second option as well. Okay, so now I see the clusters are created. So you can do the selections and create your own event layers on the on the on the maps application. So once you have created the the clusters, you can drill down and reach till the individual case. So this is an individual case, and all the data elements which are marked as display in reports in your program stage, they will show they will be shown here in this pop up. Okay, so depending upon what data elements you marked as display and reports and configuring your program stage, you'll have the information for those data elements here. Now, using this layer we are looking at the event data. So this will display all events within that program, and you can filter the events by the data element values, which are there in those events. So if a person was tested twice within the gap of this year, then it will show that person twice because the event happened twice. So this is not unique count of positive cases. These are the count of events where the test result was positive not not for the same person you can have more than one event so you can use events there only when you want to even your focus analysis focus is the number of events for the count of events total events, not unique tracked entity instances. So we have given this requirement to the code developers at Oslo to give us a functionality to also create clusters for unique cases, where we want to see based on say the latest value of the events for example I want to create clusters of ART positive cases who are on treatment. So only want to see those cases who are on treatment. So if I have made three visits in this quarter, then if I do quarterly analysis I should see the patient count unique patient count not the total count of events. So that requirement has come up from any implementation so we already are in the process of sharing the documentation which is required for submitting the feature request so that is under consideration. So once you have created your map with the event layer, you can go to file and click on save. So it's similar to like you do in all analytics model you're saving favorites you can just select positive. Ovid cases, general application and you can save this one. Okay. Then after saving you can use this on the dashboard and you can even use this for your analysis here. Then you can download this map from the maps application.  So it'll give you four positions. Left, left top corner, left bottom corner, right top corner, right bottom corner. So depending upon what's the most convenient you can select that and it will show the filters that you're filtering cases by lab test result which is positive. So you are styling the results by the sex data element. Okay. So once you've selected your, your legend location you can download this image so you will have this image downloaded on your device. And then you can use this for your presentations. So just to ensure that you capture the entire image so ensure that you have you have the clusters within your image size. So that is a concentration which you need to make that when you're downloading this ensure that you are not in because then it will take up only the area which is shown on the map but not the default size that it shows. So this is how you can create a map on using the event layer. So please one in your learners guide. So please proceed with doing that exercise if there any questions please feel free to unmute and ask a question or put in this chat I'll try to answer that. Now, once I sort of assume the map zoom in the map so I found that the cluster sub in detach and it gives me a values, whereas if I zoom out it so sort of a merge and gives a value. So what is the sort of a fundamental does it have some sort of a sort of methodical way or does it any sort of algorithm or can we sort of make changes to this one. So this is happening based on the coordinates which are there. So when your group when you're zooming in zooming out you're basically drill down on the coordinates so the polygon expands or the cluster expands as you click on the the zoom in feature so then if so basically the coordinates are splitting up into different clusters so if by default if you see you'll have 1259 cases which belong to a group of coordinates which has formed a polygon. If you keep drilling down then the coordinates are keep splitting up so as the coordinates split up the clusters become less and less the in terms of the radius.  So it kind of forms a cluster of patients who share coordinates within the same parameters which just combines and breaks them together based on the purely on the coordinates. There is no specific algorithm working so this is based on the coordinates which have been selected. So if these coordinates are coming in from one single location or polygon or an area, then it just combines those into one bigger cluster and when you break them it splits into specific coordinates of that location or those events which share that same location in terms of the coordinates selected while data entry is done. Okay, so we can do the exercise one from the learners guide. If there any questions please let us know. If not now then you can put it on the Slack channel we'll answer those. Yesterday you have your grid assignments for event visualizer and the event analytics in the maps. So please don't forget to do the grid exercises and also fill the feedback for today so that your attendance can be mapped. We can check if the feedback is open on modules or if not, we can open that with me.


I'm sure you know that yogurt comes from milk but did you know that bacteria are also a key ingredient? Yes, bacteria! But don't worry, these are good bacteria and are often called probiotics. Your gut has thousands of types of bacteria happily living inside whose job it is to aid digestion. Yogurt is thought to be a good vehicle to bring more of these good bacteria in. So in this video we're going to learn a bit more about how yogurt is made. First we need milk. Before we start the next steps all of our equipment needs to be sterilized to kill any unwanted bacteria and other microorganisms. Now we're ready to start. The milk is heated to somewhere between 85 and 95 degrees Celsius for between 15 and 30 minutes. This is a process called pasteurization and is also done to kill any bacteria and other microorganisms that are naturally found in the milk. The milk is then homogenized. This breaks down the fat droplets in milk to make them smaller so that they stay suspended in the yogurt, rather than sinking and making it all lumpy. So we've sterilized our equipment, then pasteurized and homogenized the milk. Now the mixture is cooled to 40 to 45 degrees Celsius and we add our special yogurt making bacteria. The mixture needs to be cooled first so that the bacteria aren't killed by the high temperature. You might be wondering why on earth are we adding bacteria when we've gone to all the effort so far of killing all the bacteria. We're adding lactic acid bacteria, which are also used in cheese manufacturing. The two species used to make yogurt are lactobacilli and streptococci. But don't worry you don't need to learn these names. Just remember that lactic acid bacteria are added. These lactic acid bacteria are known as the starter culture. The bacteria ferment the milk and change it into yogurt. Lactose is the main sugar in milk and during fermentation the bacteria turn the lactose into lactic acid. The bacteria also start to digest the milk proteins. Fermentation takes many hours and during this time the mixture skipped at the optimum temperature of 40 to 45 degrees Celsius so that the bacteria can work its fastest. As fermentation produces lactic acid type of acid the pH of the milk drops to about pH 4.4. This is why natural yogurt has a sharp tangy taste. As the pH levels drop the milk solidifies to become raw yogurt. Once the pH drops to a low the lactic acid bacteria that make the yogurt also stop working so the yogurt doesn't become too solid. The pH drop also stops any bad bacteria growing. The solidification happens because the proteins begin to coagulate. Coagulation is when something which is liquid turns into a more solid state. So we've sterilized our equipment, then pasteurized and homogenized the milk. Add lactic acid bacteria so fermentation happens and then coagulation. The mixture is now stirred and cooled to 5 degrees Celsius and we've made natural unflavored yogurt. At this stage we can add flavorings and fruit. Now it's ready to be packaged and sold delicious. Can you match the words to the definitions of the different stages of the yogurt making process? Pause the video and give it a go. Did you get them right? Now what about completing the missing words? Again pause the video and work them out. Did you get them right? So there we have the process of yogurt making, from milk to a tasty strawberry flavored yogurt. If you like the video give it a thumbs up and don't forget to subscribe, comment below if you have any questions. Why not check out our few school app as well. Until next time.


Hi guys. Welcome to another episode of Sugar MD. Today we are talking about sweet potatoes. Now you're going to be like, oh, he's going to say don't eat, but no, I have some good news for you this time. And I will tell you a few secrets about how to eat sweet potatoes and still get away with it. I'm Dr. Ahmed Ergin. I'm an endocrinologist and a diabetes education specialist. We will start right now. Okay guys, so a lot of you love potatoes. We have videos about potatoes. Recently we talked about the parsnips, how parsnips can be a good addition to or alternative to, not addition, alternative to your potato. And a lot of you are concerned about also how about the sweet potato story, right? So sweet potato is people think it is much healthier, which I agree that healthier than potato, but it can still spark your blood sugar unless you do something when you are cooking those sweet, sweet, sweet potatoes. Now, sweet potatoes are interesting vegetables because depending on how you cook, it really changes the glycemic index of the sweet potato. That's interesting, because normally glycemic index doesn't change with cooking. Sometimes it does, but not as drastically like the sweet potato. Now you can roast sweet potato, you can fry sweet potato, you can bake sweet potato, you are still going to have a blood sugar spike. You're still going to have at least 70 to 80 of glycemic index, which is high in the glycemic index chart, and it will spike your blood sugar. And if you boil the sweet potato, it will depend on how much you boil. If you boil only eight to 10 minutes, you will still have a blood sugar spike. So what is the key? The key is to boil your sweet potato 30 minutes or more. Now, what happens is when you do boiling, it changes the structure of the sweet potato and retains the resistant starches, and it will prevent the blood sugar spike after a long process of boiling. So if you like that approach, if you're going to like that taste, if you're going to do a meshed sweet potatoes, for example, or casseroles or whatever, you can definitely try to do that, and you can see the difference. Now, I want you to try that. I want you to write comments about what happened with the different type of sweet potato, your experience with it. Again, you know, one experience may be different than the other experience, what you're eating with sweet potato also makes a difference. We always say, for example, if you are having some fatty food with it or fat content or the amount of the portion that you're consuming makes a difference in terms of how much spike you're going to get in your blood sugar. But if you are making an experiment yourself where you are roasting and frying whatever compared to boiling 30 minutes, and I want you to tell me what difference you have seen yourself. So anyways, guys, thank you for watching.  We'll see you in the next one.


I've been working reclamation for a little over a year.  I work for CLK, one of the largest property owners in the southeast. Chuck L. Chuckles Landry bought hundreds of distressed properties for pennies on the dollar during the recession and built an empire renting them back to the same poor people the banks had just evicted. I started working there after my sister kicked me out. Before she died, our mother had made me promise to make good grades in school and made my sister, Carla, promise to let me stay with her so long as I did. College didn't agree with me. I could pick up the facts just fine, but put a sheet of paper in front of me and called a test and my mind would become a complete blank. I made it through two years of community college, but I just couldn't handle my junior year. Carla seemed relieved, sitting there at mom's old scarred kitchen table, telling me that I had to go. I couched her for a few weeks and found the reclamation job cheerfully through luck. Trenton, a friend of mine who was a part-time bartender, told me a tale of his cousin who got bit by a rat at work. You seen hoarders? Trenton asked.   Workers' comp paid for all that. But when he got back to work, the place chit-shatted him for not wearing appropriate safety gear. A few questions later, and I had the name of the company, Barry's manager, now my manager hired me on the spot. I dressed in nice slacks on an Oxford shirt, the only nice clothes I owned. I think he smelled my desperation. The pay was truly lousy. You're going to mess up them britches, boy. He said, you start today. People are filthy. I'm no neat freak, but the way some of these people live is worse than animals and pens, year's worth of dishes stacked in sinks, counters, the floor, junky needles, rusted tips stuck everywhere, waiting to snag an arm or a hand.  I'm dead serious about my safety gear.  You don't go into these places without a lot of something between you and everything else. Most of the houses I worked in weren't disaster zones. They were just houses that for some reason, usually foreclosure, had sat empty for a long time. Houses aren't made to sit empty, a tiny problem that would be instantly noticed and repaired by an occupant like a dripping faucet, a bit of missing weather stripping around a door or an animal scratching around in the attic would turn into a full blown disaster after six months of neglect. I would back up a dump truck to the house and my partner and I would haul out broken furniture, cracked toilets, sodden carpet, rune drywall. The people who lived in those houses usually left when they didn't want a leaf and some left mad. I'd seen entire plumbing stacks filled with concrete, wiring pulled from walls and fixtures smashed with hammers. My partner on the job, Hank, opened a kitchen cabinet only to discover it was full of baby raccoons. Mama raccoon tried to eat Hank's face. Some days were luckier than others though. In one place I realized the strange odor I'd been smelling was kerosene.  The cop said the whole place was rigged. The tripwire and several others had been tied to crude nail filled claymores and pipe bombs were wired into the light switches. Since then, I always cut power to a place first thing and I always smelled the air. The air told me something was wrong with the killing house. At first glance from the street, the house seems small, a modest bungalow shrouded by trees and overgrown shrubs. When we back the truck down the cramped, curving drive, I could see the house was very large verging towards mansion. It appeared to have three distinct wings. Three floors rose over the porch, the topmost crowned with a row of small windows. I just forced my way through the large heavy front door with a pry bar, past no less than three dead bolts. The air was warm and wet, like the exhalation from the mouth of a carnivore.  He was 19, stood about six foot three, weighed about 300 pounds and had a rosy child's face framed by ringlets of curly blonde hair. He looked like a giant, oversized baby, belly straining against his rip proof environment suit. This was his first real job. I doubted I would see him after Friday. Put your respirator on. I said pulling mine into place stinks like mold in here.  I pushed the front door open and stepped into the hallway. The heat inside the house was oppressive. It was early October, cool outside, so the heater must have been running. Light from beyond the low slung front porch showed a hallway packed floor to ceiling with stacks of papers with only a narrow path between them. Gray dust or mold coated everything piled into small drifts in the corners and floated in the sunlight. Great. A hoarder house. Like on TV. Jacob asked. Yeah, like on TV. I flicked on my flashlight. Look, be really careful near these stacks. If you bump into one, the whole pile can fall on you. Jacob had been watching long legged centipedes scurry for cover from the beam of his light. He gave a nervous laugh and shrank back from the stacks of papers. Jacob reached for the old two button style light switch near the front door. I blocked his hand. No, no, use your light. There's no telling how bad the wiring is in this place. I motioned at the papers. I don't want to be stuck in here with a fire. We made our way farther down the hallway between the teetering stacks of dust covered in cobwebbed papers. The light faded as the killing house swallowed us. Jacob and I entered what once would have been a grand foyer off the front hallway. Our lights picked out beautiful woodwork and glinted off an elaborate chandelier hanging three stories overhead. Dust covered shelves lined the walls, floor to the ceilings high overhead, each crammed to overflowing with junk and papers. Galaxies of dust swirled in the thick air, disturbed by our intrusion. In the gloom, the room was dizzying. The mind recoiled from so many details, from having to track an account for so many things. Jacob's respirator whistled faster and faster. I lay a hand on his shoulder. Calm down, man. Breathe. Sorry, it's just so much. His eyes were shocked huge behind his face mask. We need to find the main breaker panel and cut the power.  From the looks of it, we'll be living here until then. Stepping over scattered papers, I walked through an archway into a new hallway opposite the entry hallway. This one was more narrow and only had crudely assembled wooden shelves on one side. I checked each door along the way. These old houses, the panels in the kitchen half the time, I said. The kitchen was as bad as I feared. The food hadn't simply rotted. It had disintegrated and merged into a sheet of decaying matter that glued the layers of plates and dishes into a near solid mat. A mottled Amana refrigerator, once yellow or even white, slumped in a corner like a murder victim. Its door open to display ancient furred food crushed beneath broken wire shelves. Every level surface had been stacked with dishes, as if whoever had brought them into the kitchen had dropped them off, expecting them to be cleaned by a servant who was no longer there or who'd never been. Jacob and I picked our way across and around the heaps that may have been tables or chairs are lights aimed at the walls where we hoped to find a breaker panel. We found none. And what about the other half of the time? Jacob asked, though the resignation in his voice meant he knew the answer. Yeah, it's in the basement. The other door leading out of the kitchen was stuck firm. Even Jacob, who had nearly 100 pounds on me, couldn't get it to shift in its frame. We backtracked to the foyer. Look, we got to split up. You take this hallway and I'll take the other one. You walk the right side edge the whole time. I punched his arm. Hear me. Right side the whole time. I'm following the left side. I need to make sure you're checking every wall and every single room. This is a big house. There's trash all over and it's dark. We've already burned two hours and we only have until the end of the week. We don't have time to waste checking the same room twice. If you find it, text me. You got your phone on you. Is it turned up loud? He nodded. You got a signal.  I know.   He wants it cleaned out by the end of the week. If we do a good job, haul a bunch of loads, he'll give us a bonus. Well, he'd give me a bonus. Jacob would get a pat on the back and he wouldn't show up to work on Monday morning. Let's go. Keep that mask on. As Jacob stumbled down his hallway, clumsy in his environmental suit, motes of gray dust sparkled in his flashlight beam until the darkness closed upon him. An hour later, I had to admit, I was lost. I was furious. It was a big house and yes, there was trash everywhere and yes, it was dark, but it was still just a house. I'd spotted a promising doorway at the end of a hallway, but the hallway was blocked by an impenetrable stack of furniture and oddly, garden implements. I backtracked to a narrow spiral staircase and climbed it. My plan was to go up one floor, go down the length of an upper hallway and find a way down on the other side. At the top of the staircase was another long hallway, but this one was empty of both trash and doorways. Gray mold or dust lay thick across carpet that might once have been red. I walked the length of the hallway without finding another staircase. Instead, the hallway turned sharply left. The first door on the right was slightly open. I pushed the door open and walked into a dusty but otherwise clean bedroom. Large bay windows looked down upon the driveway. I could see the front of the truck, except I was too high up. Now instead of climbing up one floor, I'd climbed to the topmost level of the house. When my phone rang, I nearly wet myself. Yeah? I said, I don't hear. Jacob said the connection was terrible. I can't hear you. Move towards a window. Oh, go me. I looked at my phone call feature call failed. I'm not sure how that's a feature. I sent him a text meet at truck. I was hot thirsty and I really had to pee so I was ready to kick down a door and climb out a window just to get to the truck. I left the bedroom thinking to retrace my steps. After that, I'm not sure what happened. I'd always felt like I had a good sense of direction, especially inside a building. But the killing house was different. I know I went left out of the bedroom, then right down the long empty hallway and down the spiral staircase. But when I reached the bottom, the pile of rakes and garden shears shoved through decaying chest of drawers was missing. It seemed to be the same hallway at first. I hurried down to the end of the hallway toward what I had earlier thought must be the door to the basement.  I backtracked again, opening doors. Another was piled high with books. A brief look revealed them to all be molded, water swollen paperback romance novels. Not one had a breaker panel on the wall. Worse, the windows in each room had been boarded up, then painted. After the third room, I noticed the carpet pattern in the hallway, once sparsely visible beneath molding papers and dust, had changed from a red grid to green with yellow flowers. I checked my phone again, no signal and no text messages. I tried calling Jacob anyway, but of course the call didn't go through. I started walking back to find the spiral staircase. Preoccupied as I was, I nearly missed the door to the basement. It was made to look like the walls of the hallway in which I stood with dark wood trim and covered in yellowing plaster, lathe. As I walked past, I noticed something near the floor, a light. The door opened easily to reveal a short set of wooden stairs dimly lit by an ancient naked incandescent bulb. The steps ended at another door. This door was not wood, but metal and was much larger. A wheel was set in the center of the door. I turned the wheel and pulled open the hatch. Hot air, hot enough to feel through the tyvek of my suit rushed past me. That white blue light spilled around the edges of the doorway, blinding my gloom accustomed eyes. I hissed involuntarily, shading my eyes from the harshness of the glare. After my eyes adjusted, I stepped through the doorway onto a white painted metal landing. A long series of white metal strips descended from the platform. The walls, also white, were spotlessly clean as were the floor and steps. My phone dinged and vibrated. It claimed it had a bars worth of signal. Three missed calls all from Jacob. Several text messages. Where are you? Not funny. I quit. Joking. You at the truck? I called Jacob. The call connected, but it went to voicemail. I texted him found basement, meet you a truck and hit send. In the dry stillness of the stairway, I could have sworn I heard the text tone sound off in the distance. Floodlights cleared overhead as I climbed down the steps to the sterile white basement floor. There was no dirt, no dust, row upon row of steel shelves silently receded into the brightly lit immaculate distance. The shelves gleamed under the lights and on each shelf laid dozens of white cardboard boxes. I picked a box near me. A small elegantly hand printed label was affixed to the front. 623 I read aloud. The box was light, but something was inside. I removed the lid. Inside the box lay a woman's dress, a pink fabric that was polyester or maybe acrylic. Under it were a pair of buckled pink shoes and a purse.  I said to myself as I replaced the box upon the shelf. Deep down I didn't believe it. Deep down I needed to leave. But then, but I didn't. I heard a ping loud and echoing against the concrete and steel, Jacob's phone, reminding him of my text. I looked around, but did not see him in the bright cavernous room. I walked towards where I thought I heard the sound and picked up another box, 898.  I flicked open the wallet, but it was empty. In the corner of the box I noticed a gold ring, a wedding band. Though the room was sweltering hot, I was suddenly cold. I put the lid back on the box and the box back on the shelf. The humming was louder here, more of a throb, so I continued my way down the corridor of shelves toward its source. At a certain point, the shelves emptied of boxes, their steel racks gleaming in the floods. At the far corner of the room, taking up nearly the entire wall, crouched in enormous furnace. No. It was an oven. Its surface, vast and black iron, was studded with rivets. Across its dark face were five large doors, and in those doors were portholes, and in those portholes fire danced and played. Next to the oven was a cart, it was small and steel and very clean. On the cart was a single white box, its label read 1248. The box pinged, loudly. I opened its lid. Inside it held a respirator, a Tyvek environment suit, and Jacob's phone.