Morphgear 2.2.5.7 serial

We then designed 2 mathematical modeling approaches to infer the outbreak dynamics in Wuhan by using high-resolution domestic travel and infection data. Results show that the doubling time early in the epidemic in Wuhan was 2. Assuming a serial interval of 6—9 days, we calculated a median R 0 value of 5. We further show that active surveillance, contact tracing, quarantine, and early strong social distancing efforts are needed to stop transmission of the virus.

On January 8, , the pathogen was identified 1 , and human-to-human transmission was reported soon after. In a period of 3 months, an outbreak of apparent idiopathic pneumonia had become the COVID pandemic. Studying dynamics of a newly emerged and rapidly growing infectious disease outbreak, such as COVID, is important but challenging because of the limited amount of data available.

In addition, unavailability of diagnostic reagents early in the outbreak, changes in surveillance intensity and case definitions, and overwhelmed healthcare systems confound estimates of the growth of the outbreak based on data.

Initial estimates of the exponential growth rate of the outbreak were 0. These estimates were based on 2 broad strategies. First, Li et al. However, case count data can be confounded by reservoir spillover events, stochasticities in the initial phase of the outbreak, and low surveillance intensity.

The epidemic curve based on symptom onset after January 4 showed a very different growth rate 6. Second, inference was performed by using international flight data and infected persons reported outside of China 3 — 5.

Because of the low numbers of persons traveling abroad compared with the total population size in Wuhan, this approach leads to substantial uncertainties 7 , 8. Inferences based on a low number of observations are prone to measurement error when data are incomplete or model assumptions are not fully justified; both conditions are common challenges associated with rapid and early outbreak analyses of a new pathogen. We collected an expanded set of case reports across China on the basis of publicly available information, estimated key epidemiologic parameters, and provided a new estimate of the early epidemic growth rate and R 0 in Wuhan.

Our approaches are based on integration of high-resolution domestic travel data and early infection data reported in provinces other than Hubei to infer outbreak dynamics in Wuhan. They are designed to be less sensitive to biases and confounding factors in the data and model assumptions. Without directly using case confirmation data in Wuhan, we avoid the potential biases in reporting and case confirmation in Wuhan, whereas because of the high level of domestic travel before the Lunar New Year in China, inference based on these data minimizes uncertainties and risk for potential misspecifications and biases in data and model assumptions.

We developed 2 modeling approaches to infer the growth rate of the outbreak in Wuhan from data from provinces other than Hubei. In the first model, the first arrival model, we computed the likelihood of the arrival times of the first known cases in provinces outside of Hubei as a function of the exponential growing population of infected persons in Wuhan before late January.

This calculation involved using domestic travel data to compute the probability that an infected person traveled from Wuhan to a given province as a function of the unknown actual number of infected persons in Wuhan and the probability that they traveled.

The timings of the arrivals of the first infected persons in different provinces would reflect the rate of the epidemic growth in Wuhan. In the second model, the case count model, we accounted for the detection of additional persons who were infected in Wuhan and received their diagnoses in other provinces and explicitly modeled those persons by using a hybrid deterministic—stochastic SEIR susceptible-exposed-infectious-recovered model.

We then fitted this model to new daily case count data reported outside Hubei Province during the period before substantial transmission occurred outside of the province. By using data collected outside Hubei Province, we minimized the effect of changes in surveillance intensity. By the time cases were confirmed in provinces outside Hubei, all of the provinces of China had access to diagnostic kits and were engaging in active surveillance of travelers out of Wuhan e.

Furthermore, the healthcare systems outside Hubei were not yet overwhelmed with cases and were actively searching for the first positive case, leading to much lower bias in the reporting in each province compared with the time series of confirmed cases in Wuhan.

These reports include demographic information as well as epidemiologic information, including potential periods of infection, and dates of symptom onset, hospitalization, and case confirmation. Most of the health commissions in provinces and special municipalities documented and published detailed information of the first or the first few patients with confirmed COVID As a result, a unique feature of this dataset includes case reports of many of the first or the first few persons who were confirmed to have SARS-CoV-2 virus infection in each province, where dates of departure from Wuhan were available.

We considered realistic distributions for the latent and infectious periods to calculate R 0. We described the methods we used to calculate R 0 and the effect of intervention strategies on the outbreak Appendix 2. We first translated reports from documents or news reports published daily from the China CDC website and official websites of health commissions across provinces and special municipalities in China during January 15—30, Altogether, we collected individual case reports from China and 3 additional case reports from outside of China Appendix 1 Table 1.

Figure 1. Epidemiologic characteristics of early dynamics of coronavirus disease outbreak in China. Distributions of key epidemiologic parameters: durations from infection to symptom onset A , from symptom onset to hospitalization B , from hospitalization By using this dataset, we estimated the basic parameter distributions of durations from initial exposure to symptom onset to hospitalization to discharge or death.

Our estimate of the time from initial exposure to symptom onset i. This estimated duration is generally consistent with a recent report by Guan et al. One potential caveat of our estimation is that because most of the case reports we collected were from the first few persons detected in each province, this estimation might be biased toward patients with more severe symptoms if they are more likely to be detected.

The time from symptom onset to hospitalization showed evidence of time dependence Figure 1 , panel B; Appendix 2 Figure 1. Before January 18, the time from symptom onset to hospitalization was 5. The change in the distribution coincides with news reports of potential human-to-human transmission and upgrading of emergency response level to Level 1 by the China CDC.

The emerging consensus about the risk for COVID probably led to substantial behavior changes among symptomatic persons, in terms of seeking more timely medical care during this period. However, because most of the individual reports were collected in provinces other than Hubei, the change in durations might only reflect changes in the rest of China rather than in Hubei.

We also found that the time from initial hospital admittance to discharge was The time from symptom onset to death was estimated to be Figure 2. Extremely high level of travel from Wuhan, Hubei Province, to other provinces during January , as estimated by using high-resolution and real-time travel data, China.

A A modified snapshot of the Moving from empirical estimates of basic epidemiologic parameters to an understanding of the early growth rates of COVID requires model-based inference and data. We first collected real-time travel data during the epidemic by using the Baidu Migration server, which provides real-time travel patterns in China based on mobile-phone positioning services Figure 2 , panel A; Appendix 1 Methods Table 2,. Figure 3. Estimates of the exponential growth rate and the date of exponential growth initiation of the novel coronavirus disease outbreak in China based on 2 different approaches.

A Schematic illustrating the We then integrated spatiotemporal domestic travel data to infer the outbreak dynamics in Wuhan by using two mathematical approaches Appendix 2 ; conceptual framework depicted in Figure 3 , panel A. The first-arrival model uses a unique feature of our case report dataset whereby the dates of departure from Wuhan for many of the first persons who were confirmed with SARS-CoV-2 infection in each province were known Appendix 1 Table 1.

We should expect that t 0 is later than the date of the first infection because multiple spillover events from the animal reservoir might be needed to establish sustained transmission and stochasticity might play a large role in initial dynamics before the onset of exponential growth 12 — We used travel data for each of the provinces Appendix 1 Table 3 and the earliest times that an infected person arrived in a province, across a total of 26 provinces Figure 3 , panel B , to infer r and t 0 Appendix 2.

Model predictions of arrival times in the 26 provinces fitted the actual data well Appendix 2 Figure 2. The growth rate r is estimated to be 0. As we show later, there exist larger uncertainties in the estimation of t 0.

Figure 4. Marginalized likelihoods of growth rate r for 2 inference approaches to estimates the exponential growth rate of the coronavirus disease outbreak in China. An alternative model, the case count approach, used daily new case counts of persons who had COVID diagnosed in other provinces but who had been in Hubei Province within 14 days of becoming symptomatic.

This model uses data beyond the first appearance of an infected person from Wuhan but also accounts for the stochastic nature of the process by using a hybrid model. In this model, the infected population in Wuhan was described with a deterministic model, whereas the infected persons who traveled from Wuhan to other provinces were tracked with a stochastic SEIR susceptible-exposed-infectious-recovered model We restricted the data to the period of January 19—26, when new cases reported were mostly infections imported from Wuhan i.

The transitions of the infected persons from symptom onset to hospitalization and then to case confirmation were assumed to follow the distributions inferred from the case report data Appendix 2. Simulation of the model using best-fit parameters showed that the model described the observed case counts over time well Figure 3 , panel C. These estimates are consistent with estimates in the first arrival approach Figure 4 ; Appendix 2 Figure 4.

In both models, we assumed perfect detection i. However, a certain fraction of cases probably was not reported. To investigate the robustness of our estimates, we performed extensive sensitivity analyses to test 23 different scenarios of surveillance intensity Appendix 2. First, we tested the assumption that a constant fraction of infected persons e.

We found that under this assumption, t 0 would be earlier than our estimate but the estimation of the growth rate remained the same Appendix 1 Table 4. Second, we tested the assumption that the intensity of surveillance increases over the period of data collection, although this scenario is less likely because of the intensive surveillance implemented outside Hubei Province. We found that our data in general do not support this hypothesis on the basis of corrected Akaike Information criterion scores Appendix 1 Table 4.

However, if the intensity of surveillance outside Hubei Province increased over the period of January, we would predict a lower growth rate than the estimate we just described. For the worst-case scenario considered, we estimated the growth rate of the outbreak to be 0.

In addition to using 2 modeling approaches, we looked for other evidence of a high outbreak growth rate to cross-validate our estimations. We found that the time series of reported deaths in Hubei, which is less subject to the biases of the confirmed case counts, is simply not consistent with a growth rate of 0.

As the infected population grows, the number of death cases will grow at the same rate but with a delayed onset corresponding to the time from infection to death. Fitting a simple exponential growth model to the number of reported deaths in Hubei during late January yields an estimate of 0.

Overall, these analyses suggest that although there exist uncertainties depending on the level of surveillance, the exponential growth rate of the outbreak is probably 0.

This estimation is much higher than previous reports, in which the growth rate was estimated to be 0. The basic reproductive number, R 0 , is dependent on the exponential growth rate of an outbreak, as well as additional factors such as the latent period the time from infection to infectiousness and the infectious period 16 , 17 , both of which cannot be estimated directly from the data.

Following the approach by Wearing and Rohani 16 , we found that with a high growth rate of the outbreak, R 0 is in general high and the longer the latent and the infectious periods, the higher the estimated R 0 Appendix 2 Figure 6.

Figure 5. Estimation of the basic reproductive number R 0 , derived by integrating uncertainties in parameter values, during the coronavirus disease outbreak in China. A Changes in R 0 based on different growth rates and More recent data collected in Shenzhen Province, China, suggests that the serial interval is dependent on the time to hospital isolation Q.

Bi et al. When infected persons are isolated after 5 days of symptoms a probable scenario for the early outbreak in Wuhan, where the public was not aware of the virus and few interventions were implemented , the serial interval is estimated to be 8 days Q.

Thus, these results suggest a serial interval of 7—8 days. With this serial interval, we sampled latent and infectious periods within wide biologically plausible ranges Appendix 2 and estimated the median R 0 to be 5. To include a wider range of serial interval i.

The estimated R 0 can be lower if the serial interval is shorter. However, recent studies reported that persons can be infectious for a long period, such as 1—3 weeks after symptom onset 18 ; R. Woelfel et al. The R 0 values we estimated have important implications for predicting the effects of pharmaceutical and nonpharmaceutical interventions.

Starting from August , all my emulators come with a workaround for this bug. So, if you are experiencing this problem, head to Google Play and download the latest version of my app. When scaling pictures, the OpenGLES hardware always adds a bit of blur, to avoid ugly scaling artifacts.

If you do not like the fuzzy picture, disable the "Video Hardware Video Acceleration" option for the crystal clear image, at the cost of lower performance and shorter battery life. When not using hardware video acceleration, the emulator will scale picture with the highly optimized assembler code running on your main CPU. This code is tailored for several different screen resolutions. The emulator will choose the resolution that best matches your screen, but may not completely fill it. If you would like the picture to fill your whole screen, enable the "Video Hardware Video Acceleration" option.

In order to make a custom color palette for a game named Game. If you feel that the sound lags on your device i. Reducing it too much may cause sound distortions though, so be careful.

If your audio becomes distorted, increase the latency. You may also want to try toggling the "Audio Native Audio" option and see if it makes sound better. If you are hearing clicks and pops in the sound, increasing the "Audio Audio Latency" setting should fix your problem, at the cost of some sound lag.

The echo often occurs on slower devices, where emulation cannot keep up with the audio, so the audio repeats, while emulation catches up. You can avoid this problem by optimizing performance to make emulator run faster.

If the sound still echoing, increase the "Audio Audio Latency" setting. A lot of Android devices have limited multitouch that only lets you use two fingers.

On these devices, you simply cannot press more than two virtual buttons at once. My emulators offer a workaround of sorts though. Go into the "Input Edit Layout" setting and drag buttons so that they overlap a little bit. Now, you can press both buttons by touching the overlapped spot. To resize joystick buttons, open the "Input Virtual Joystick Size" setting and choose any size you like.

To move buttons, open the "Input Edit Layout" setting and drag buttons around the screen to the most comfortable spots. Keep in mind that when you rotate your device, each button will "stick" to the closest screen edges. Normally, you will see transparent controls overlaid on top of the display. You can also control the joystick by physically tilting your device, if your device has an accelerometer and you enable the "Input Tilt Joystick" option. In my apps, released after August 14 , you can supply your own virtual joystick skin.

Make a Controls. See the "Input Auto Fire Settings" setting. It lets you choose what buttons are going to have auto-fire. Of course you can use your generic keyboard, gamepad, or joystick with any of my emulators. If your gamepad has a mode switch, make sure it is set to the "generic gamepad" position. You may also want to visit the "Input Assign Keys" setting in order to make a comfortable button layout for yourself.

By default, your keys are going to be assigned as follows:. Simply turn it on, and once you see the "MOGA controller connected" message on the screen, it is ready to play with.

This little app should let you use the MOGA with many applications that do not normally support it. Starting Apr 5 , all my emulators support iCade joysticks. To enable iCade support, toggle the "Input iCade Support" option. You may also want to customize the button layout via the "Input Assign Keys" setting. If you have got a Sony Sixaxis gamepad and a rooted Android device, you can use the gamepad over Bluetooth, with the help of the Sixaxis Controller app from Dancing Pixel.

See the application web site for instructions. For Nintendo Wiimote users, here is a short tutorial on using Wiimote with my applications, provided by Robert McCurdy. Most of my emulators now support the NetPlay feature that lets you play with other users over your local WiFi network or the Internet. The first player should select "NetPlay" from the menu and then choose "Become Server" option. The second player should select "NetPlay" from the menu and then choose first player's name from the list of available servers.

Once you are done playing, uncheck "NetPlay" on both devices to disconnect the NetPlay. In order to use network play, both players must be running the same game and have mutually visible IP addresses. It is only possible if You and your friend are on the same local network, such as same WiFi. You and your friend have globally visible Internet addresses.

You will not see each other in the NetPlay dialog, unless these conditions are met. Unlike stationary consoles which came with a pair of gamepads, the GameBoy and GameBoy Advance handhelds had a special serial cable that let users connect handhelds together, for cooperative play.

The GameLink connection works exactly the same way as a regular NetPlay connection. When using NetPlay , each player must send a lot of data over the network and wait for the other player to acknowledge every packet they send. This wait time slows down the gameplay speed for both players. While this slowdown is unavoidable and depends on your network speed, I am working to reduce it in the upcoming versions of my products. Many games are available in different versions, in different languages, or with bugfixes.

In order for a cheat code to work, you need to be running exactly the same version of the game that this cheat code has been discovered for. The codes will not work for a different game version, even on the real GameShark or ActionReplay hardware. Besides, many cheat codes found on the Internet contain errors and will not work on any game version. Given how unreliable cheats are to begin with, I usually can't answer the question why your cheat does not work.

The easiest way to use cheat codes is by going to Android menu and choosing "Cheats Cheatopedia" there. Cheatopedia contains premade cheats for many popular games. Use the cheat editing interface to add, delete, or edit cheat codes. Please note that emulators will only accept cheat codes in the above formats whatever ones are relevant. They will not accept codes in any other formats.

So, if you cannot enter a code, carefully check its format. Finally, be aware that not all cheats you find on the Internet work, even on the real hardware. Never mix cheats from different sources and try to use cheats that are known to work on at least some other emulator. If you are not sure that your cheats are saved, select the "Save" from the Android menu before returning to the emulator. After exiting and reentering the emulator, you have to toggle cheats on again. The cheats are always off at startup.

Most of my emulators include the Cheat Hunter tool letting you search for your own cheats in any game. Enter the value to search for money amount, ammo count, lives , how it changes, and the replacement value like Play the game to make the watched value change.

Repeat previous two steps several times, to minimize false positives. To browse and edit newly found cheats, use "Cheats Edit Cheats". Yes, you can extend Cheatopedia with your own cheats. In order to do that, you will have to place a text file called custom. Follow GarageResearch Tweet. Fast-Forwarding The fast-forwarding feature lets you quickly skip through long dialogs and demo sequences.

Joystick Emulation The joystick is emulated with hardware keys, virtual joypad, or accelerometer. Emulators will also save state on exit, letting you restart where you have left off. Mouse Emulation For the old software that requires a mouse, it is emulated with the touch screen.

Compressed Files The emulators will automatically process files with. You do not need to unpack these files. Built-in Debugger Many emulators include a built-in debugger for hacking or developing your own retro software. Cheats Cheatopedia offers hundreds of cheats for popular games, or you can enter your own cheat codes.

Screenshots The emulators will save stamp-sized screenshots for each game you play, and show them in the file selection dialog. State Exchange State Exchange lets you swap gameplay states with other users playing the same game.

Normal Display The picture fills the center of your device screen, while retaining the original display ratio. Stretched Display The picture is stretched horizontally to fill the entire device screen, for the biggest possible size.

Softened Display The picture is softened, hiding individual pixels, as if it were shown on an old analog TV. Keyboard Emulation The keyboard is naturally emulated with the hardware keyboard or the on-screen virtual keyboard, in case your Android device lacks a real one.

Frame Rate Display The frame rate counter shows how fast your emulation is running. Google Play Market. All my products are published on the Google Play Market. Free iNES available here! Download it here , spread it wide, let other people know. You both have to be playing the same game and be on the same WiFi network, or have Internet-visible IP addresses. You can reenable these features yourself, by downloading this file to the Downloads folder on your Android device.

Speccy will automatically unzip and use that file once you start the app. Cheats support Since Mar 21 , I had to disable Cheatopedia, Cheat Editor, and Cheat Hunter features in Speccy , since Google Play no longer allows them and bans any apps that come with game cheating features. To change joystick type or enable mouse Go to the built-in menu, select "Input devices" and set whatever input device s you want. Believe it or not, but that is how original k Spectrum did it.

To load program from a tape i. Press the on-screen MENU button to go to the built-in menu and toggle the "Tape running" option to start the tape. There are also options to rewind and browse tape contents. Wait for the program to load, which may take a while, just like on a real ZX Spectrum. To enable mouse or joystick Go to the built-in menu, select "Input devices" and set mouse or joystick in joystick port 1.

Same goes for the second joystick port. ColEm will automatically unzip and use that file once you start the app. ROM The names can be in upper or lower case. You can always repeat the search by clicking on the "Scan Files" menu option or the magnifier icon in the action bar. Free VGB available here! To establish connection, check "NetPlay" in the Android menu. Note that both of your devices have to have valid IP addresses. This feature will not work if one of you is behind NAT.

Your phone will vibrate every time a game uses the "rumble" feature. VGBAnext will automatically unzip and use that file once you start the app. For NES games, the second gamepad can be emulated over the network. If you are having trouble saving games Use the gameplay freezing feature instead.

Later on, select the same option to restore your game back to where you have frozen it. If you are still having trouble saving games If you cannot save games, even with the freezing feature, and the games won't even save state when you exit and restart VGBAnext , you may be low on the disk space.

Check how much free space you have got in the folder where your games are. There should be at least kB of free space for saving and freezing to work.

If nothing works, games do not save, cheats do not work Aside from using a pirated version that is known to fail randomly, on different features and low disk space, this problem may sometimes be caused by a package upgrade.

SAV made by other emulators. As of Aug 7 , VGBAnext will also store in-game saves in a format compatible with other emulators. Prior VGBAnext versions used their own. SAV files. FRZ files to other emulators Unfortunately, the gameplay state files are in proprietary format and cannot be exported to other emulators. Nor can VGBAnext load proprietary state files such as. SGM from other emulators. General I want to report a bug or make a suggestion! I want games! I need games! Where do I find games?

Nothing works, saves fail, everything hangs or crashes! I have bought the app, but now it says I do not have a valid license! I cannot save games and screenshots do not show up either. Do your emulators work on rooted devices?

Emulator is too slow. How do I make it faster? How can I make fast-forward stay on all the time? Video How do I remove the title bar from the top of my screen? When I rotate my Gingerbread device, the picture disappears! When I use video acceleration, the picture becomes fuzzy.

The picture does not fill the screen. Colors look wrong. I want to change them. Audio Sound lags. How do I prevent it from lagging? Sound clicks and pops. How do I clean it up?