“Crapo” leaps to freedom

first_imgHamid Latiff also called “Crapo” of Cane Grove, Mahaica, East Coast Demerara, who reportedly stabbed his reputed wife’s brother to death outside a wedding house in 2013 has been freed of murder.Hamid LatiffIn dramatic scenes outside the High Court on Thursday, Latiff leaped to freedom after he was cleared of the November 8, 2013 murder of Mulchand Murilall, 16.Murilall was reportedly defending his sister Bhagmattie “Vashtie” Murilall against Latif with whom she shared a relationship. Latiff’s acquittal for the fatal stabbing followed a unanimous decision by a 12-member mixed jury after a one hour deliberation on Thursday afternoon.Mulchand MurilallThe jury foreman told the court that his team collectively found the defendant not guilty on the charge of murder. On a possibility of the lesser count of manslaughter, the jury was also unanimous in their decision that the accused was not guilty of the indictable crime.After the decision was handed down, Justice Jo-Ann Barlow encouraged the former murder-accused to use the opportunity to avoid trouble, pointing out that sometimes, “trouble comes and finds you”.After being freed, Latiff brushed past his relatives and with great exuberance swiftly proceeded to his waiting car after two years of incarceration for the capital offence.Throughout the week-long trial, a number of discrepancies were found in several witness’ statements. The court took particular note of the lack of credibility in the testimony of Latiff’s reputed wife Vashtie, who attempted to cover up the fact that she shared a relationship and a child with a police officer who was present at her brother’s murder scene.In the summation of tendered evidence in the trial at Thursday morning session, Justice Barlow also stressed the lack of credibility when Vashtie claimed that her relationship with the officer only began in December 2015 when in fact, the police officer had fathered her son over a year ago.During the trial, Vashtie told the court that the child’s birth was never registered but medical records proved otherwise. Under cross-examination by Defence Counsel Bernard De Santos, the woman denied that she had formed a relationship with the officer while she was still with Latiff.The witness had also admitted that she did not see the stabbing of her brother as she was some distance away, hearing tassa drums. However, Bhagmattie “Vashtie” Murilall did claim that she heard someone in the distance say “ow” on that fateful night.It was also revealed that the officer, with whom Vashtie has shared a relationship, was the first police rank to arrive on the scene after her brother had met his demise.  However the jury had to consider the fact White (father of the said child) also “covered up” the relationship with Vashtie as well as the existence of their child.The jurors also considered that while White did not actually conduct investigations of the crime, he preserved the evidence until the police detectives had arrived on the scene.The testimony of Safraz Hussein who was said to be a valid witness also had credibility issues as he withheld the fact that he was using “ganja” on the night he witnessed the stabbing. Hussein who was 18 at that time testified that he actually saw when the deceased teenager was stabbed. However jurors had to consider that in the lower court, he had told the presiding Magistrate that he only smoked cigarettes.Before the jurors were allowed to deliberate, Defence Counsel De Santos reminded the court that his client “did not admit to anything” nor was he bearing any responsibly for Murrilall’s stabbing. This was premised on the unsworn statement that Latiff gave when he had taken the stand. The defendant claimed that he was attacked with “a paling stave affixed with nails” but however declined claiming self-defence. Despite this, Latiif had testified that it was another witness, Rajesh “Alligator Man” Liloutie who had inflicted injures the teenager suffered after “the boy jumped between” the two of them (Latiff and Liloutie).Justice Barlow had reminded the jurors that they would have not been making a determination on whether or not “Alligator Man” caused the boy’s death but that they should focus on the facts surrounding the accused.  Latiff had also alleged that it was Liloutie who threw the young man overboard.However the court learnt that police never investigated that version of events. Rather, the investigators placed prime emphasis on the version that “Crapo” stabbed the boy.Meanwhile Liloutie had earlier testified that he had seen the former murder-accused “shove something” in the deceased’s body after which Latiff had thrown him overboard. The court had however heard that “Alligator Man” had not seen what “Crapo” had shoved into the murdered man’s body.The 12 jurors who freed “Crapo” were told that the pathologist did not find water in the victim’s body.In 2013, it was reported that an argument had ensued between Latiff and Murilall which led to the young man being fatally stabbed to his chest and under his left arm.Sometime after the stabbing, Latiff was nabbed by Police at Springlands while allegedly trying to escape to neighbouring Suriname.last_img read more

Romeo Kumalo: I am an Entrepreneur

first_imgBusiness leader Romeo Kumalo plays his part in promoting entrepreneurship in South Africa, sharing his vast experience in the information and communications technology sector.South African business leader Romeo Kumalo. (Image: M-Net)Brand South Africa’s partnership with the Industrial Development Corporation, Renault, MTN Business and MyStartUp on the ‘I am an Entrepreneur’ programme workshop series is aimed at promoting the spirit of entrepreneurship in South Africa.Mentors and business pioneers present very different but compelling stories about their enterprising journey with budding entrepreneurs in a masterclass set-up.The Bloemfontein chapter of ‘I am an Entrepreneur’ held a workshop on 7 October 2017 with business man Romeo Kumalo. He has more than 20 years of experience in the South African information and communications technology (ICT) sector, 10 years of which were spent with Vodacom. Now Kumalo has struck out on his own and is forging a new path to success.Kumalo says he wants to make his own dent in the universe – and he plans to do this through supporting budding entrepreneurs in South Africa.As a member of M-Net’s Shark Tank, he has been afforded the opportunity to get involved with young entrepreneurs and invest in businesses he believes will help solve societal problems in the country. In Shark Tank, budding entrepreneurs pitch their ideas to five industry leaders who decide whether the idea is worth investing in or not.This was a great platform to amplify the values of Play Your Part as it highlights the goals of the National Development Plan to eliminate poverty and build an inclusive society through, among other things, youth development, skilling and empowering women and entrepreneurship. This ultimately sees South Africa having higher employment rates and a more confident, skilled workforce.Would you like to use this article in your publication or on your website? See Using Brand South Africa material.last_img read more

Vapor Profiles Help Predict Whether a Wall Can Dry

first_imgToday’s walls, roofs, and floors are better insulated, tighter, and made with a much greater variety of components than they used to be, making them a lot more susceptible to moisture problems when they get wet. Compared to the old days, today’s walls and ceilings are more complicated and can be very slow to dry.Poorly crafted building codes are blamed for many examples of confusion, and the confusion over vapor retarders and vapor barriers is no exception. To design and build energy efficient and durable building assemblies, following the code is not enough. We need a new approach — such as the vapor profile.What is a vapor profile?A vapor profile is an assessment of the vapor permeabilities of each component in a building assembly (a wall, ceiling, or roof). This assessment determines the assembly’s drying potential and its drying direction. The vapor profile shows whether the building assembly protects itself from getting wet and how it dries when it gets wet.“Moisture profile” might be a better term than “vapor profile,” because winning the moisture battle means keeping track of all phases or expressions of water. But vapor profile ties the term to “vapor retarder” and “vapor barrier,” terms that focus on that one layer and whether that layer restricts wetting by vapor diffusion. Vapor profile is about all layers and is as much about drying as it is about wetting.Four steps to a vapor profileExamining the vapor profile is a 4-step process:1. Determine the vapor permeability of each componentThis can be a lot more difficult than it sounds. Various building product manufacturers are not consistent in the ways they measure and report vapor permeability. Different standardized tests are used for different products. Also, the vapor permeability of many building materials is not constant — it can change as the material’s moisture content rises or falls.Make sure that you get numbers for every material or component in your assembly, and obtain the actual test used and units reported. A good start is the Building Materials Property Table from BSC.2. Identify the least vapor permeable component(s)It’s important to identify the component or components that most restricts the wetting and drying potential of the assembly. To understand the robustness or sensitivity of the assembly to moisture accumulation, it’s important to know how many low-permeance materials there are, and where they are located.I suggest following the vapor retarder class system established by Joe Lstiburek of Building Science Corporation:Class I Vapor Retarder (vapor barrier): less than or equal to 0.1 permsClass II Vapor Retarder: less than or equal to 1 perm and greater than 0.1 permsVapor III Vapor Retarder: greater than 1 perm but less than 10 permsThis classification is based on results from ASTM E-96 A (the dessicant or dry cup method). Any material greater than 10 perms is considered vapor permeable.NOTE: The next two steps are not really sequential; you consider them together because they tell you about how to keep things from getting wet and also about letting them dry when they do get wet.3. Assess the extent and direction of vapor driveYou need to consider the following:a. Outdoor conditions, including temperature and relative humidity. It’s important to know how extreme and sustained the expected temperature differences are (with respect to the building interior). For more information, see Climate Consultant 4.b. Indoor conditions — Interior moisture loads, interior setpoints and the type and extent of space conditioning (active heating, cooling, humidification and dehumidification, ventilation).The question you are trying to answer is: Do I need a vapor retarder somewhere in the assembly to restrict the movement of vapor INTO the assembly?4. Assess the moisture storage capacity and drying potential of the assemblyThe next question you are trying to answer is: Do I have at least one way for vapor to GET OUT of the assembly?An assembly with two vapor retarders or barriers on opposite sides of the assembly means that there is little to no drying potential in either direction. That can be a real problem brewing unless you design and detail for extraordinary moisture management protecting this assembly from wetting.Example 1 – an acceptable vapor profileIn this example, we have taken a representative GBA wall construction detail and assigned actual materials for each component of the assembly. [Click to enlarge] This wall can only dry to the outside. It is more risky. Step 1: Assess vapor permeabilitiesHow do you determine the vapor permeability of your building materials?In this example, all of the numbers came from the BSC table mentioned earlier.Note that two numbers are in quotes. In the case of the air space it means that vapor moves so freely in air that it is as vapor permeable as it gets.In the case of wood siding, the quotes indicate an “equivalent” vapor permeability. This means that although the lab test of a piece of wood siding (pine, in this case) may yield a vapor permeability of around 2.5 or so, all the gaps between the installed wood clapboards in a wall assembly permit enough air circulation in between clapboards that the effective permeability is MUCH higher (35).NOTE: If you can’t find the numbers you need in this table, you will have to search the Web or contact the manufacturer and tell them you need this information or you can’t use their product. That should get their attention.Step 2: Identify the least permeable componentAfter you have all the numbers, it is pretty easy to pick the one, or maybe two, most restrictive layers in the wall assembly, in terms of vapor permeability.Note that 1 inch of XPS insulation at 1 perm is NOT vapor impermeable. However, it is the most restrictive, which means that MOST drying will take place to its interior or exterior. Also note that the near vapor impermeability of the oil-based paint is managed or overridden by the air space and the functional or equivalent vapor permeabilty of the wood siding as installed (with lots of little air gaps).Step 3: Assess the vapor drive(s)We don’t know what the interior and exterior temperature/relative humidity regimes for this assembly are; we have not picked a location or interior conditions — but…Step 4: Assess storage and drying capacity…since there is such great drying potential on either side of the XPS, this assembly is well-suited to a wide range of climatic, site, and interior conditions.Example 2 – An unacceptable vapor profileIn this second example, we have another representative GBA wall construction detail and again assigned actual materials for each component of the assembly. [Click to enlarge] This wall can dry in OR out. Step 1: Assess vapor permeabilitiesAgain we have taken vapor permeability numbers from the BSC Building Materials Property Table.Step 2: Identify the least permeable componentWe have two layers that are essentially vapor barriers, stopping all moisture from getting INTO and OUT OF the wall assembly. And the problem is that the two layers encase much of the building assembly.Steps 3 and 4: Assess the vapor drive(s), storage, and drying capacityEven without assessing the vapor drives, this assembly is likely to be a problem in ANY climate or interior conditions. If (or rather when) this assembly gets wet, it has very little drying potential. It would take nearly perfect design and construction details and very little moisture drive to keep this assembly from failing.Let’s look more closely at Step 3 (keeping the assembly from getting wet) and Step 4 (letting it dry when it gets wet). If at all possible, we want to change one of the two restrictive layers to give the assembly more drying potential. But which one?If this building is located in the hot-humid south, where the prevailing vapor drive is from the outside in, it is probably better to keep the foil-faced insulation and lose the vinyl wallpaper.If this building is located in the far north, where the prevailing moisture drive comes during the winter from the inside, we might want to pick a rigid insulation product that is more vapor-permeable.Moisture analysis beyond vapor profilingThe examples look at two extremes; we didn’t really assess the vapor drive and moisture storage capacity of the various assemblies.The vapor profile method is qualitative. It is quite possible that you want a more definitive analysis, because you really don’t know how the assembly will perform in your climate, at your site, with your interior conditions.For a more exacting answer to this question, you have two options: consult with a building scientist who has enough practical experience to review your design and weigh in with an expert opinion; or turn to a more quantitative analytical tool.The tool that many building scientists use is a software program called WUFI (a German acronym based on the Fraunhofer Institute for Building Physics, where the program was first developed). The software allows you to specify your assembly, pick your local climate and interior conditions, and then run a four-year analysis to see how the assembly handles moisture, wetting, and drying.WUFI tends to be a conservative tool (it “fails” assemblies and conditions more often than real-world experience suggests), and so is often more useful in the hands of experienced building scientists than lay folks like builders and architects.A closing noteI am not sure where the term “vapor profile” came from. I learned to use the term during my time at Building Science Corporation when I was trying to document the way in which Dr. Joseph Lstiburek assesses buildings as part of a Building America project.last_img read more

How Google Is Throwing Sand In Apple’s Face

first_imgRelated Posts What it Takes to Build a Highly Secure FinTech … Role of Mobile App Analytics In-App Engagement Guest author Derek Brown is a technology executive and analyst who blogs at One Blind Squirrel.Yesterday at the playground, Google threw a handful of sand in Apple’s eye.With a subtle, yet powerful update to its Gmail for iOS app, links to YouTube, Google Maps and Chrome now go directly to those relevant apps (if installed), instead of the mobile web.In my view, this is an absolutely brilliant backdoor play through which Google can not only neutralize Apple, but also leverage Apple’s tremendous success to its own benefit, by enhancing the experience of Google’s dedicated users, deepening loyalty to Google’s own products, and driving incremental revenue for Google.Perhaps more important, yesterday’s Gmail for iOS update is a textbook example of why Google will emerge victorious (at Apple’s expense) in the battleground of tomorrow, Web services.As discussed in “Welcome to Google’s Playground, Apple,” mobile hardware and core OS functionality have largely reached a near-term point of peak innovation; as a result, the product itself will become effectively transparent to the end user, with attention, instead, shifting to the Web (or, cloud) services/content that those devices allow easy access to on an anywhere, anytime basis.Unfortunately for Apple, this shift substantially diminishes the value of its closed-loop hardware/software core, while simultaneously highlighting the strengths of Google’s business. To this end, almost everything Google has done since inception has focused on anywhere, anytime cloud services that function like utilities – seamlessly, across all devices, across all operating systems, all the time – at low or no incremental cost, in the face of stiff competition.Moreover, Google absolutely prints money, either directly or indirectly, from use of many of these cloud-based services, even if those services are accessed via an Apple device (e.g., Gmail for iOS). Apple, on the other hand, is almost at ground zero.For Apple to compete broadly on the battleground of tomorrow, it must quickly introduce a broad spectrum of high-impact, high-value, mass-consumption Web services that function seamlessly across all vendors, all OSs, and all devices. And, the only way I see it doing so expeditiously and successfully is through acquisition – buying services that have already proven themselves in the hands of consumers at scale.If Apple doesn’t, it risks seeing its precious hardware turned into little more than access devices for Google’s services, even as it continues losing marketshare to Google’s own Android-based hardware devices, which do an even better job of accessing Google’s services.Seems like a slightly less painful lose-lose to me.Lead image courtesy of Northfoto/Shutterstock derek browncenter_img Why IoT Apps are Eating Device Interfaces Tags:#Apple#Google#iOS The Rise and Rise of Mobile Payment Technologylast_img read more

Kabaddi Masters Dubai: India thrash Iran by 18 points to win title

first_imgPutting up yet another superlative show, India thrashed Iran 44-26 to emerge champions of the six-nation Kabaddi Masters Dubai on Saturday.In a battle between the top-two sides of the world, the three-time world champions did not give Iran any ground to recover with captain Ajay Thakur (nine points) and youngster Monu Goyat (six) leading the raid charts. India inflicted two all-outs on Iran, en route the massive victory.The final had its share of hiccups as lights went off, disrupting the match for 10 minutes in the first half, while in the second half, Iran captain Amirhossein Maleki, who came in as a substitute, claimed “rough play” by the Indians but referee dismissed the protests.Both the teams last met in the World Cup 2016 final in Ahmedabad with Thakur playing a key role in handing them a slender nine-point victory.Having given the captaincy baton in this Asian Games build-up meet, Thakur was all over the mat with his superb raiding skills.India’s defence was also excellent with Surjeet Singh returning with seven tackle points. The captain drew the first blood with a running touch to send Mohammad Naseri to the bench.India, however, lost the early momentum after the power disruption to slip from being 15-5 to 18-11 at the break.The biggest positive for Iran in the closing stage of first-half was when they were able to evict Thakur with Mohammad Maghsoudlou’s fine attempt.But they could not keep Thakur away as India once again forced their way back after the changeover, displaying top-class raiding as well as defensive skills.advertisementIndia coach Srinivas Reddy gave young Goyat a start in place of a lackluster Pardeep Narwal.Iran, however, took a bold decision to keep captain Amirhossein Maleki out of the team as both the teams made one change each.last_img read more

What Our NBA Projections Got Right And Wrong Last Season

CARMELO is back! As my colleague Nate Silver detailed Thursday, we’re issuing our second set of NBA player career forecasts; you can find the latest batch of projections here. For those unfamiliar with CARMELO,1Which, as a complete coincidence, stands for Career-Arc Regression Model Estimator with Local Optimization. it’s an algorithm that uses the career arcs of similar historical players to predict what’s in store for today’s stars, journeymen and scrubs.I want to dig into what CARMELO predicts for 2016-17, but first let’s look back at the best — and worst — moments of the projection’s rookie season. To help isolate its biggest hits and misses, I gathered wins above replacement2WAR can be calculated by multiplying a player’s Box Plus/Minus by the percentage of his team’s minutes he played and then multiplying that by 2.2. data for the 435 players who both played in the NBA in 2015-16 and were issued a CARMELO forecast last fall. Here’s a simple histogram of the differences in WAR between what was predicted and what transpired on the court: Kawhi LeonardSF2515.810.55.010.8 Marcus SmartPG229.95.10.59.3 R. Westbrook27OKC2449+7.312.72750+10.018.3+5.6 Kyle LowryPG3014.59.43.810.8 Anthony Davis22NO2568+6.311.82164+2.25.1-6.7 What CARMELO got wrong in 2015-16 K. Towns20MIN1859-0.21.82627+2.86.8+5.0 James HardenSG2719.514.28.011.6 M. Smart2.55.1+2.6K. Durant14.110.9-3.2 Russell WestbrookPG2819.215.29.49.8 Paul George25IND2074+2.45.12819+4.510.1+5.0 Marcin Gortat31WSH1889+1.63.82256+1.24.0+0.2 Chris PaulPG3114.910.33.411.5 T. Evans1.63.8+2.2C. Paul13.110.3-2.9 Anthony DavisPF2313.58.83.79.8 That’s a pretty good list! Nic Batum, for instance, was coming off of a down year by the conventional metrics, but CARMELO predicted he’d bounce back to something more like his old form. It also predicted that Tim Duncan, at age 39, would play at a high level, and that lottery pick Frank Kaminsky would underwhelm.So, now that we’ve assessed CARMELO’s debut season, what can it tell us going forward? Here are the players our system thinks will see the biggest improvements (or declines) by WAR in 2016-17: PLAYERAGETMMINUTES+/-WARMINUTES+/-WARDIFF Draymond GreenPF2614.69.64.410.2 Nicolas Batum27CHA2435+2.05.42448+2.05.5+0.1 Patrick Patterson26TOR1841+1.53.62020+1.03.3-0.3 DeAndre JordanC2813.98.02.911.0 Draymond Green25GS2189+4.68.02808+5.812.1+4.1 Lavoy Allen26IND1201+0.31.51599-0.61.3-0.2 Among players who were issued a forecast and played in the NBA in 2015-16.Source: Basketball-Reference.com Luis Scola35TOR1052-1.30.41636-1.20.7+0.3 Stephen CurryPG2820.516.111.39.2 Marvin Williams29CHA1568+0.01.82338+2.75.9+4.2 Kemba WalkerPG2611.67.22.19.6 FORECASTACTUAL What CARMELO got less wrong in 2015-16 Arron Afflalo30NY1952-2.5-0.52371-2.4-0.4+0.1 By WAR, the biggest miss on CARMELO’s résumé was also the game’s biggest star: Stephen Curry. It wasn’t that the algorithm thought Curry would be bad — CARMELO predicted that he’d be the game’s most valuable player in 2015-16 — but the projection didn’t foresee the quantum leap his game would take the season after he’d already established himself as league MVP. Outlier performances are outliers for a reason; most players would regress to the mean after posting one of the top 50 seasons in modern NBA history, not one-up themselves with a campaign ranking in the top 10. Obviously, Curry isn’t “most players.”Similarly, CARMELO knew Kyle Lowry and Russell Westbrook were good, but it didn’t bank on them being quite so good. The numbers also didn’t see Kemba Walker’s breakout performance coming, or that Karl-Anthony Towns would be one of the best rookies in modern history. And it was taken completely by surprise when Anthony Davis — CARMELO’s pick as the game’s most valuable franchise player — turned in a historically disappointing season.Davis, who was less than 100 percent for much of the season, brings us to the bumps and bruises — or worse — that players have to deal with. Injuries are notoriously difficult to predict, and since playing time and performance are so fundamentally intertwined, many of the players on the list above saw various ailments rob them of both minutes and per-minute production. Joakim Noah and Michael Kidd-Gilchrist, for instance, missed most of the season with injuries, and they weren’t themselves when they did suit up.And it goes without saying that CARMELO knows little about the personal-life problems of mere humans. That’s why it — like me — was so utterly, woefully wrong about Ty Lawson’s disastrous 2015-16 season.Things weren’t all bad for CARMELO’s inaugural season, though. Here are the players — among those who played at least 1,500 minutes — for whom the projected WAR totals most closely matched the player’s output in 2015-16: Frank Kaminsky22CHA1272-1.40.41708-1.20.7+0.2 FORECASTACTUAL Jimmy Butler26CHI2688+3.68.32474+4.08.1-0.2 Goran Dragic29MIA2169+1.13.72363+0.73.5-0.2 About 55 percent of the players finished with a WAR total within a win (plus or minus) of what CARMELO predicted; that grows to 80 percent if we look for players who fell within two wins of their WAR forecast. It’s tough to say how that compares to other projection systems, since there aren’t many alternatives available in the public domain, but in a vacuum that doesn’t seem like an awful rookie showing, particularly since CARMELO’s errors appear to be roughly symmetrical along the shape of a bell curve — meaning it isn’t systematically biased toward over- or undervaluing players.CARMELO wasn’t perfect, though. Here were its biggest misses, high and low, of 2015-16: BIGGEST IMPROVEMENTSBIGGEST DECLINES D. Russell0.32.7+2.5R. Westbrook18.315.2-3.1 Jae Crowder25BOS1364+0.51.92308+2.86.2+4.3 Since CARMELO uses previous seasons to inform its projections, along with a heavy dose of regression to the mean, there’s some crossover between the lists of its 2015-16 misses and its 2016-17 improvements or declines. Curry, Lowry and company can’t possibly be that dominant two years in a row, right? We’ll see; projection systems are conservative by nature, always abiding by the law of averages, and an explosive individual performance represents a rebellion against that law. Maybe some of the names on the right-hand list will buck the odds and make history again; maybe they won’t. The left-hand list, however, is the one to keep an eye on — these are largely young players the projection expects to make big improvements, as well as a few veterans (Davis, Blake Griffin, Tyreke Evans) that it expects to bounce back.On that note, here’s a list based on pure volatility — the players for whom CARMELO projects the biggest range between what could reasonably be termed their best-case (90th percentile) and worst-case (10th percentile) outcomes next season: Karl-Anthony TownsC2114.38.83.910.4 Kemba Walker25CHA2452+1.34.42885+4.09.7+5.2 Blake Griffin26LAC2581+3.98.51170+3.33.5-5.0 D. Cunningham28NO1360-1.20.61971-1.20.9+0.2 CARMELO’s most volatile players of 2016-17 WAR CARMELO’s most (and least) improved players for 2016-17 Tim Duncan39SA1652+3.55.11536+4.15.3+0.2 Among players who were issued a forecast and played 1,500 NBA minutes in 2015-16.Source: Basketball-Reference.com Tyson Chandler33PHX2045+3.25.91618-0.51.3-4.6 Kyle Lowry29TOR2307+3.57.02851+6.813.9+6.8 Kyrie Irving23CLE2743+3.38.01667+1.63.3-4.7 Jeff Teague27ATL2072+0.52.82255+0.32.9+0.0 A. Davis5.08.8+3.7S. Curry21.716.1-5.6 Kristaps PorzingisPF2110.25.50.79.5 Brandon Knight24PHX2337-0.61.81870-0.31.8-0.1 Dwight Howard30HOU1920+1.13.32280+0.63.3+0.0 PLAYERPOSITIONAGEBEST CASEMEANWORST CASERANGE (+/-) B. Griffin3.45.9+2.4K. Leonard13.610.5-3.1 Andre Iguodala32GS1735+1.93.71732+1.63.5-0.2 PLAYER2016 WAR2017 WARCHANGEPLAYER2016 WAR2017 WARCHANGE Among players who will not be rookies in 2016-17. E. Mudiay-2.6-0.3+2.4P. George10.17.2-2.9 E. Payton0.83.4+2.6A. Horford8.95.7-3.2 Damian LillardPG2613.48.22.311.1 Shane Larkin23BKN1654-2.1-0.11751-2.2-0.2-0.2 Joakim Noah30CHI2160+3.06.0635+1.91.3-4.7 K. Irving3.36.2+2.8K. Lowry13.99.4-4.5 Naturally, young players such as Towns, Davis, Kristaps Porzingis and No. 1 draft pick Ben Simmons will have wider variation in potential outcomes because we have less of a sample from which to draw their projections. But some veterans are also highly volatile because their comparable-player lists contain both stars and duds. From here out, James Harden could have the career arc of a Kobe Bryant (who stuck around in the league forever) or a Steve Francis (who was great early in his career but was out of the league by age 31).That’s the beauty of the NBA — we never truly know what will happen. But with CARMELO’s help, we have a slightly better idea than we would otherwise.Check out FiveThirtyEight’s CARMELO NBA player projections. John WallPG2613.28.02.610.7 M. Kidd-Gilchrist22CHA2260+1.54.4205-1.40.0-4.4 Jerami Grant21PHI1656-0.71.22066-1.30.9-0.3 A. Wiggins-0.22.6+2.8P. Millsap10.77.3-3.4 Gordon HaywardSF2611.26.82.09.2 T.J. McConnell23PHI387-2.8-0.21606-2.10.0+0.2 Jimmy ButlerSG2711.87.62.69.2 LeBron JamesSF3216.311.56.210.1 K. Porzingis2.45.5+3.1L. James16.711.5-5.2 Elfrid Payton21ORL2404+2.35.72145-1.30.9-4.8 PLAYERAGETEAMMINUTES+/-WARMINUTES+/-WARDIFF Ty Lawson28—2442+1.34.41411-4.6-2.0-6.4 Al Horford29ATL2063+2.34.92631+4.19.0+4.1 Enes Kanter23OKC1824-2.00.01721-1.70.2+0.2 Paul Millsap30ATL2149+3.26.22647+5.310.8+4.6 Markieff Morris26—2073+1.13.61629-2.8-0.7-4.3 Ben SimmonsPF209.14.1-0.19.2 Paul MillsapPF3112.27.33.09.1 Derrick Favors24UTA2195+2.35.31983+2.75.1-0.2 Stephen Curry27GS2608+8.214.72700+12.521.6+6.8 read more

ATTs 5G E network helps it take crown as fastest US carrier

first_img AT&T makes the first transcontinental call, 100 years ago (pictures) Now playing: Watch this: 5G AT&T Sprint T-Mobile Verizon 8 Originally published April 3, 6:30 a.m. PT.Update, April 5:50 a.m. PT: Adds comment from T-Mobile. AT&T tries tricking customers with 5G E logo Tags AT&T’s wireless network has become the fastest in the nation, according to Speedtest. Roberto Machado Noa/LightRocket via Getty Images) Maybe it really is evolving?AT&T’s wireless network was named the fastest in the US, it announced Wednesday, based on an analysis of speeds over the first quarter of 2019 by Ookla’s Speedtest. It noted that AT&T’s speeds improved by more than 15% during that period, while the other carriers plateaued.AT&T’s speeds jumped from 34.3 megabytes per second (MBPS) to 40.7 MBPS, according to the data it presented. By comparison, T-Mobile hit 35.4 MBPS, Sprint reached 34.9 MBPS and Verizon was at 33.3 MBPS.Keep in mind that different tests have yielded different results. Last month, OpenSignal, another firm that tests wireless speeds, said it found that AT&T’s controversial  5G E (short for 5G Evolution) clocked in slower than services from Verizon and T-Mobile. However, AT&T dismissed Opensignal’s method as flawed.center_img Internet Services Tech Industry 1:58 Comments In its announcement  Wednesday, AT&T highlighted its 5G E service — which is really just fancy branding for its advanced 4G LTE network — as a major factor in its speed growth, saying it laid the foundation for the upgrade to 5G next-generation cellular technology.”We are thrilled Ookla has confirmed that we are the fastest wireless network nationwide,” said Andre Fuetsch, president of AT&T Labs and chief technology officer. “This is further proof that our wireless network strategy and build are benefiting our customers in ways that other carriers cannot match.” Responding to results from Speedtest, Verizon asserted that its wireless network is the fastest and most reliable.”The evidence is overwhelming that the Verizon wireless network is best, fastest and most reliable,” said spokesperson Howie Waterman in an emailed statement. “We focus on deploying the best technologies for our customers, at scale.”T-Mobile made a similar claim, noting that that people use their phones for upload as well as download.”When you look at the overall customer experience, there’s only one fastest LTE network: T-Mobile,” said Neville Ray, its chief technology officer. “We’ve led the industry on LTE speed for five years (20 straight quarters), all without lying to customers or pretending LTE is 5G.”Sprint didn’t responded to a request for comment. Share your voice 15 Photoslast_img read more

Markets cautious ahead of election results Hero MotoCorp declares 2750 interim dividend

first_imgA man looks at a screen displaying news of markets update inside the Bombay Stock Exchange (BSE) building in Mumbai, India, February 11, 2016.Reuters fileHero MotoCorp rewarded shareholders with a bonanza: 2,750 percent interim dividend or Rs 55 per share. However, the news did not have any impact on the share price of the two-wheeler maker. The share, which has a face value of Rs 2, actually closed in the red at Rs 3,299, down 0.65 percent.The company has fixed March 8 as the record date for determining entitlement of members for the purpose of paying the bonanza.Hero MotoCorp sold 5.24 lakh units in February, down 4.75 percent in comparison to 5.50 lakh two-wheelers sold in February 2016.The BSE Sensex closed 49 points lower at 28,999 on Tuesday while the NSE Nifty closed 16 points lower at 8,947. Investors are apparently cautious ahead of the outcome of the Assembly polls, particularly in Uttar Pradesh.”The markets are keenly awaiting the outcome of the exit poll announcements that are expected in the next few days and the street has already factored in a BJP win in the key state of Uttar Pradesh,” Mayuresh Joshi, fund manager at Angel Broking, said in a note.”Any disappointment however on this front can cause significant volatility and disruption in the positive momentum that has been created and can have a short term negative impact in the way the markets react,” he added.Top Sensex losers included Tata Steel, Lupin, Infosys and Axis Bank. Adani Power closed 4.8 percent higher at Rs 40.The rupee gained 4 paise to end at 66.67 to the US dollar. Gold and silver prices also fell on Tuesday, with the yellow metal losing Rs 200 to close at Rs 29,550 per 10 gm while silver ended Rs 300 lower at Rs 42,500 per kg.last_img read more

9 killed in Turkey train crash

first_imgRescue workers search at the wreckage after a high speed train crash in Ankara, Turkey on 13 December 2018. Photo: ReutersNine people were killed and nearly 50 injured after a high-speed train crashed into a locomotive in the Turkish capital on Thursday, officials said.Transport Minister Cahit Turhan told reporters in televised remarks that three of those killed were operators of the train.One of the victims died in hospital, he added.Turhan added that 47 people were injured and were in hospital for treatment.The fast train had been on its way from Ankara’s main station to the central province of Konya and according to Hurriyet daily, there were 206 passengers on board.Earlier, the Ankara governor’s office said three out of a total of 46 people had been seriously injured.The death toll was rising fast. Ankara governor Vasip Sahin said earlier on Thursday morning that four people had been killed.- Debris scattered on the tracks -“This morning there was an accident after the 6.30 high-speed train to Konya hit a locomotive tasked with checking rails on the same route,” Sahin told reporters in televised remarks.Turhan said the accident took place six minutes after the train left Ankara as it entered the Marsandiz station.The governor said search and rescue efforts continued as “technical investigations” were underway to find out exactly what caused the crash in Yenimahalle district.He said information about the cause of the crash would be shared with the public when it is known.Images published by Turkish media showed some wagons had derailed and debris from the train scattered on the rail track, which was covered in snow.The windows of one wagon were completely broken while another wagon had been smashed after hitting the footbridge, which also collapsed, an AFP correspondent at the scene said.The Ankara public prosecutor launched an investigation into the crash, state news agency Anadolu reported.The Ankara to Konya high-speed route was launched in 2011 and was followed in 2014 with a high-speed link between Ankara and Istanbul.The accident comes after another rail disaster in July this year when 24 people were killed and hundreds more injured after a train derailed in Tekirdag province, northwest Turkey, due to ground erosion following heavy rains.Turkey’s rail network has been hit by several fatal accidents in recent years.In March 2014, a commuter train smashed into a minibus on a railway track in the southern Turkish province of Mersin, which left 10 dead.In January 2008, nine people were killed when a train derailed in the Kutahya region south of Istanbul because of faulty tracks.Turkey’s worst rail disaster in recent history was in July 2004 when 41 people were killed and 80 injured after a high-speed train derailed in the northwestern province of Sakarya.last_img read more