The molten wood’s metal initial velocity variations effect on breaching simulation by MPS method

Series of MPS simulations have been conducted using two-dimensional geometry. The simulation was based on Sudha’s experiment (2018) about initial velocity variations on molten Wood’s Metal (WM). The molten WM would be flowed through nozzle with the diameter was 6 mm. It would impinge to the Woods Metal Plate (WMP) which 270 mm below the nozzle. The WMP diameter was 470 mm. The temperature of molten WM and WMP were set at 573 K and 300 K, respectively. The initial velocity of molten WM was varied at 0.327 m/s, 0.397 m/s, 0.498 m/s in the y-negative direction. The simulation was calculated by using 2D MPS with additional procedures such as heat transfer calculation and defining a new type of wall particle. The results showed some different spread patterns, leading edge and phase fraction change for each initial velocity. It can be concluded that with varying the initial velocity will affect on the radial spread pattern but not so much effect occurs on the phase volume fraction change.

Clover: An anonymous transaction relay protocol for the bitcoin P2P network

The Bitcoin P2P network currently represents a reference benchmark for modern cryptocurrencies. Its underlying protocol defines how transactions and blocks are distributed through all participating nodes. To protect user privacy, the identity of the node originating a message is kept hidden. However, an adversary observing the whole network can analyze the spread pattern of a transaction to trace it back to its source. This is possible thanks to the so-called rumor centrality, which is caused by the symmetry in the spreading of gossip-like protocols. Recent works try to address this issue by breaking the symmetry of the Diffusion protocol, currently used in Bitcoin, and leveraging proxied broadcast. Nonetheless, the complexity of their design can be a barrier to their adoption in real life. In this work, we propose Clover, a novel transaction relay protocol that protects the source of transaction messages with a simple, yet effective, design. Compared to previous solutions, our protocol does not require building propagation graphs, and reduces the ability of the adversary to gain precision by opening multiple connections towards the same node. Experimental results show that the deanonymization accuracy of an eavesdropper adversary against Clover is up to 10 times smaller compared to Diffusion.

Spatio-Temporal Spread Pattern of COVID-19 in Italy

This paper investigates the spatio-temporal spread pattern of COVID-19 in Italy, during the first wave of infections, from February to October 2020. Disease mappings of the virus infections by using the Besag–York–Mollié model and some spatio-temporal extensions are provided. This modeling framework, which includes a temporal component, allows the studying of the time evolution of the spread pattern among the 107 Italian provinces. The focus is on the effect of citizens’ mobility patterns, represented here by the three distinct phases of the Italian virus first wave, identified by the Italian government, also characterized by the lockdown period. Results show the effectiveness of the lockdown action and an inhomogeneous spatial trend that characterizes the virus spread during the first wave. Furthermore, the results suggest that the temporal evolution of each province’s cases is independent of the temporal evolution of the other ones, meaning that the contagions and temporal trend may be caused by some province-specific aspects rather than by the subjects’ spatial movements.

Clustering Analysis Influenza Disease to Identify Spatio-Temporal Spread Pattern in Thailand

The pandemics of influenza in Nonthaburi province was investigated by using autoregression and found the influenza spread pattern by autocorrelation (Moran's I). Population density, temperature, relative humidity, and rainfall are the factors used in the analysis. The influenza quantitative cross-section retrospective research design was employed from 2003-2010. Three seasons are classified as: hot, rainy, and winter season. The study found that influenza outbreaks in the rainy season was R2=0.45 and population density apparently affected the spread of influenza incidence with statistical significance coefficient (p-value <0.05). From the distribution pattern, the highest Moran's I values were related with the highest population density in 4 sub-districts: Suenyai, Taladkhwun, Bangkhen, and Bangkruay sub-district.

Simulating the impacts of interregional mobility restriction on the spatial spread of COVID-19 in Japan

A spatial susceptible–exposed–infectious–recovered (SEIR) model is developed to analyze the effects of restricting interregional mobility on the spatial spread of the coronavirus disease 2019 (COVID-19) infection in Japan. National and local governments have requested that residents refrain from traveling between prefectures during the state of emergency. However, the extent to which restricting interregional mobility prevents infection expansion is unclear. The spatial SEIR model describes the spatial spread pattern of COVID-19 infection when people commute or travel to a prefecture in the daytime and return to their residential prefecture at night. It is assumed that people are exposed to an infection risk during their daytime activities. The spatial spread of COVID-19 infection is simulated by integrating interregional mobility data. According to the simulation results, interregional mobility restrictions can prevent the geographical expansion of the infection. On the other hand, in urban prefectures with many infectious individuals, residents are exposed to higher infection risk when their interregional mobility is restricted. The simulation results also show that interregional mobility restrictions play a limited role in reducing the total number of infected individuals in Japan, suggesting that other non-pharmaceutical interventions should be implemented to reduce the epidemic size.

THE SPREAD OF COVID-19 OUTBREAK IN AFRICA: A COMPARATIVE ANALYSIS BETWEEN NIGERIA AND NIGER REPUBLIC

The severe acute respiratory syndrome coronavirus 2 (SARSCoV2) outbreak has developed a major public health concern, particularly in northern hemisphere countries. The novel COVID-19 pandemic that broke out in 2019 presented obstacles to the scientific community and healthcare providers. The disparities across Africa highlight the value of assessment that go further than a continent- wide case number, which can distort the true situation on the ground. We wanted to look at epidemiology. In this review using data on confirmed cases and deaths, we attempt to assess the COVID-19 situation in Nigeria and Niger. We also contrasted the patterns of disease transmission and death. The main objective of this research is to address: How do the two countries relate in terms of COVID-19 distribution and mortality. The World Health Organization database, which updates data on the global number of confirmed cases and deaths for the Covid-19 pandemic on a regular basis, was used to get the reported numbers of cases and deaths between the two countries. A Descriptive statistics were used to analyze the average daily reported Covid-19 cases and death and annual cumulative cases and death between the two countries under study. Bivariate correlation analysis was conducted to assess the measure of direction and strength of association that exits between daily new cases and daily new death and also assess the same in terms of annual cumulative cases and death from 1 st April, 2020 to 31st March 2021. In Nigeria, the COVID19 spread pattern was similar to that of Niger. The daily deaths and cases distribution in Niger resembled those of Nigeria, so on daily basis in Niger they record 13.65 covid19 cases on average while Nigeria on average in daily basis they record 445.62 new cases of Covid-19. Then for the new death in Niger the average death on daily basis stand to be 0.50 compare to Nigeria on average which has 5.63 reported new death on daily basis. So for the bivariate correlation re

Social environmental vulnerability approach on the COVID-19 epoch: a case study in Blumenau (SC), Brazil

There is a strong correlation between poverty indicators and the occurrence of diseases associated with environmental inequalities; therefore, it is highly necessary to explore the linkages between these inequalities and COVID- 19. This article describes a research designs made to study aspects of social environmental vulnerability that underlies the linkages between inequalities and COVID-19. This article aims to address this linkage. The objective is to explore aspects of social environmental vulnerability that underlies a case study at Blumenau, Brazil. The analysis is based on the critical question: Is there a relationship between social environmental vulnerability and COVID-19 at Blumenau? In Blumenau, where the study was carry out, the poor people are more likely to be affected from the risks arising out of the location of their homes, and this situation increases their vulnerability to floods, landslides, lack of water and exposure to open sewage. The methodology was divide into two steeps: (i) analysis of multi-temporal spread pattern of COVID-19 around the site; and (ii) analysis of the social environmental vulnerability and COVID-19 relationship. Results have shown that in Blumenau, there is a relationship between social environmental vulnerability and COVID-19. It can be said that COVID-19 emphases’ the social environmental situation in Blumenau. Based on our experience, we contend that an effective way to examine the linkages between inequalities and COVID-19 is to employ concepts and theories drawn from existing research to support guidelines, indicators and methods.

Modeling Mobility Pattern for the Corona-Virus Epidemic Spread Propagation and Death Rate in Nigeria using the Movement-Interaction-Return Model

Modeling the propagation rate of diseases in a society via social interaction has continued to pose its many challenges. The recent spread of the covid-19 epidemic cannot be left out. Thus, social interactions heralds its many benefits and has becomes a vehicle for epidemic outbreaks –which has continually left the world puzzled as the disease itself has come to stay. The nature of its rapid propagation on exposure alongside its migration spread pattern of this contagion (with retrospect of other epidemics) on daily basis, has also left experts rethinking the set protocols. Our study models the spread propagation of the corona-virus contagion using the movement-interaction-return on a social graph. Thus, weseek to measure if the corona-virus (covid-19)spread propagation can be minimized alongside its death rate using movement pattern as a threshold feature and set of protocols. We design a Markovian block model to help minimize targeted propagation with the advent of seed-node(s) using the susceptible-infect structure on a time-varying graph. Study results showed that movement pattern must be employed as an imperative factors when modeling the propagation of contagion(s).

Detecting COVID-19 Related Pneumonia on CT Scans using Hyperdimensional Computing

Pneumonia is a common complication associated with COVID-19 infections. Unlike common versions of pneumonia spread quickly through large lung regions, COVID-19 related pneumonia starts in small localized pockets before spreading over the course of several days. This makes the infection more resilient and with a high probability of developing acute respiratory distress syndrome. Because of the peculiar spread pattern, the use of pulmonary computerized tomography (CT) scans was key in identifying COVID-19 infections. Identifying uncommon pulmonary diseases could be a strong line of defense in early detection of new respiratory infection-causing viruses. In this paper we describe a classification algorithm based on hyperdimensional computing for the detection of COVID-19 pneumonia in CT scans. We test our algorithm using three different datasets. The highest reported accuracy is 95.2\% with an F1 score of 0.90, and all three models had a precision of 1 (0 false positives).

VERIFICATION OF THE HISAB EPHEMERIS SYSTEM AGAINST THE HIJRI CALENDAR LEAP YEAR PATTERN WITH CRITERIA IMKAN AL-RUKYAH MABIMS (Case Study in Kudus District)

The hijri istilahi calendar has a 30-year cycle system, wherein 30 years there are 11 leap years and 19 basithoh years. In history, there are 4 kinds of variants in the placement of the leap year. This research aims to determine the leap year pattern of Kudus district in 30 years and to verify which patterns are close to the 4 kinds of variants. This study uses the Library Research method using a descriptive verification approach. This approach provides a sample of the number of days per month for 30 years using the Ephemeris reckoning system by considering the possibility of seeing the new moon based on the criteria of Imkan al-Rukyah MABIMS. If the hilal meets the MABIMS criteria, then the number of days is 29, but if not, then the number of days will be 30. Then, the number of days each month is accumulated annually and is used to verify the number of days each year on the hijriah istilahi calendar. Based on the analysis of the initial month data at the Kudus district headquarters for a period of 30 years, it turns out that in the period of 1411 H to 1440 H, the spread pattern of leap years is closer to pattern IV. There are 5 years whose leap is the same as the IV pattern, namely 2, 8, 16, 24, and 30.