Global differences in changes in the numbers of population-adjusted daily test-positive cases (NPDP) and deaths (NPDD) by COVID-19 were analyzed for 49 countries, including developed and developing countries. The changes as a proportion of national population were compared, adjusting by the beginning of test-positive cases increase (BPI) or deaths increase (BDI). Remarkable regional differences of more than 100 fold in NPDP and NPDD were observed. The trajectories of NPDD after BDI increased exponentially within 20 days in most countries. Machine learning analysis suggested that NPDD on 30 days after BDI was the highest in developed Western countries (1180 persons per hundred million), followed by countries in the Middle East (128), Latin America (97), and Asia (7). Furthermore, in Western countries with positive rates of the PCR test of less than 7.0%, the increase in NPDP was slowing-down two weeks after BPI, and subsequent NPDD was only 15% compared with those with higher positive rates, which suggested that the situation of testing might have affected the velocity of COVID-19 spread. The causes behind remarkable differences between regions possibly include genetic factors of inhabitants because distributions of the race and of the observed infection increasing rates were in good agreement globally.

In response to the COVID-19 pandemic, the Philippines placed the majority of the country under enhanced community quarantine, restricting the movement of most of its 100 million plus population. These aggressive measures were initiated on March 15, 2020 and intensified on March 17. According to official data, the number of confirmed COVID-19 cases has exponentially increased during this period, but it is important to note that the number of patients tested also substantially increased during the same period. It is not conclusive that widespread transmission of COVID-19 only started in March and our analysis suggests that community transmission was happening earlier. In discussing extended quarantine measures, it is important to properly understand the trends and recognize the limitations of the data. The unintended consequences on the population, especially in lower-middle income countries with fragile health systems like the Philippines, must be carefully considered.

The COVID-19 pandemic which have affected every part of the world have been deemed a public health concern and classified as a pandemic. The government imposing travel bans and quarantine measures have been found to be effective in preventing and reducing the spread of COVID-19. A reduction in physical activity and increase in the consumption of unhealthy foods have been observed to be some of the major implications of quarantine. Adequate physical activity and increased access to healthy foods would help in improving the psychological wellbeing of individuals thereby preventing the development of cardiovascular diseases.

Decisions affecting the COVID-19 pandemic, by the individual and those with highest authority, are being made on the basis of unreliable data. Data about cases and deaths are collected daily but represent only a sample of reality. Statistics convert sample data into more reliable estimates. However, statistics have no magical powers; reliability requires dependable data. It is futile to rail against this darkness; COVID-19 is not a scientific experiment. However, we must do better both with data collection and data analysis. In this review, I focus on one element of the data, the asymptomatic case of COVID-19. Without reliable information about this number, decision makers are significantly blinded. By its nature, the asymptomatic case is hidden but contaminating to understanding COVID-19. The true case rate and death rate per case are unknowable without knowing the fraction of cases that are asymptomatic. The best estimate of asymptomatic cases is in the CDC document: COVID-19 Pandemic Planning Scenarios. For four different scenarios the estimates range from 10% to 70%, with the best estimate of 40% for asymptomatic cases. However, even the definition of the asymptomatic case is problematic. In simplest terms, two elements are required: an infection and no symptoms. How is “no symptoms” to be usefully defined? It appears to be analogous to pontificating about black swans from studying only white swans. It implies infection, but how is infection defined? Is it presence of the virus, replication of the virus, or presence of antibodies? Is asymptomatic disease an oxymoron? Without extensive, purposeful screening for specifically defined, essential symptoms and appropriate virus and antibody testing over time, the class of asymptomatic cases remains unknown. Current estimates range from <20% to ˃80%. If low, it can be ignored; if high, it dramatically and proportionately lowers the case rate and the death rate per case. Consequentially, the asymptomatic rate dramatically affects our societal and political responses. In this focused review, we assess the limitations of the published estimates, bring attention to the importance of obtaining accurate data, and exhort that high priority be given in the scientific community to understanding the issue, asymptomatic COVID-19 cases.

Reliable methods to confirm the diagnosis of COVID-19 are essential to the successful management and containment of the virus. Current diagnostic options are limited in type, supply, and reliability. This article explores the controversial unreliability of existing diagnostic methods and maintains that more reliable diagnostic methods, combinations, and sequencing are necessary to effectively assist in reducing the occurrence of discharge of the patient on false negative test results. This reduction would in effect reduce transmission of the disease.

Although proposition of “Virtual Reality” (VR) and “Augment Reality” (AR) can be traced back to the 60s, both areas are actually blooming in recent decades. Thanks to the latest deep learning techniques, an enormous advance in computer vision research community has taken place. Since VR and AR are highly related to computer vision tasks, these areas have enjoyed the benefits as well. Yet there is no sufficient survey on such impact and new research areas arising from it. This paper mainly focuses on the latest research progress in ACM Symposium on Eye Tracking Research & Applications (ETRA) 2019, as well as several recent representative paper works. It aims to figure out the influence of deep learning techniques on latest VR/AR research. Meanwhile, new issues have popped up with the development of VR and AR technology, such as privacy and computation efficiency. This paper draws attention to such newly produced topics as well. In addition, this paper also investigates on the effect of latest VR and AR techniques on people, such as level of teamwork in collaborative tasks, assistance and treatment to patients and the disabled, etc.

This study investigates the trend in monthly and annual rainfall, minimum and maximum temperature (T_min and T_max) using the Mann–Kendall (MK) test and Sen’s slope (SS) method and evaluates the significance of their variability for maize, sorghum and millet yields in northern Togo employing multiple regression analysis. The historical data of Kara, Niamtougou, Mango and Dapaong weather stations from 1977 to 2012 were used. Four non-parametric methods—Alexandersson’s Standard Normal Homogeneity Test (SNHT), Buishand’s Range Test (BRT), Pettitt’s Test (PT) and Von Neumann’s Ratio Test (VNRT)—were applied to detect homogeneity in the data. For the data which were serially correlated, a modified version of the MK test (pre-whitening) was utilised. Results showed an increasing trend in the annual rainfall in all four locations. However, this trend was only significant at Dapaong (p < 0.1). There was an increasing trend in T_max at Kara, Mango and Niamtougou, unlike Dapaong where T_max revealed a significant decreasing trend (p < 0.01). Similarly, there was an increasing trend in T_min at Kara, Mango and Dapaong, unlike Niamtougou where T_min showed a non-significant decreasing trend (p > 0.05). Rainfall in Dapaong was found to have increased (7.79 mm/year) more than the other locations such as Kara (2.20 mm/year), Niamtougou (4.57 mm/year) and Mango (0.67 mm). T_max increased by 0.13, 0.13 and 0.32 °C per decade at Kara, Niamtougou and Mango, respectively, and decreased by 0.20 per decade in Dapaong. Likewise, T_min increased by 0.07, 0.20 and 0.02 °C per decade at Kara, Mango and Dapaong, respectively, and decreased by 0.01 °C per decade at Niamtougou. Results of multiple regression analysis revealed nonlinear yield responses to changes in rainfall and temperature. Rainfall and temperature variability affects rainfed cereal crops production, but the effects vary across crops. The temperature has a positive effect on maize yield in Kara, Niamtougou and Mango but a negative effect on sorghum in Niamtougou and millet in Dapaong, while rainfall has a negative effect on maize yield in Niamtougou and Dapaong and millet yield in Mango. In all locations, rainfall and temperature variability has a significant effect on the cereal crop yields. There is, therefore, a need to adopt some adaptation strategies for sustainable agricultural production in northern Togo.

Social distancing policies put in place during COVID-19 epidemic in addition to helping to limit the spread of the disease also contributed to improving urban air quality. Here we show a decrease in air pollutant concentration as a consequence of mobility reduction in São Paulo during the containment measure which began on 22^nd March 2020. When comparing to foregoing weeks to equivalent periods of 2019, the concentration of most air pollutants sharply decreased in the first days of mobility restriction, to then increase again after government officials downplayed the threat of the disease. This trend is also followed by a decrease in hospital admissions by SARS-influenza. Therefore, despite the great economic and social unrest caused by the pandemic, this unique situation shows that large-scale mobility reduction policy had a significant impact on air quality, benefiting, directly and indirectly, the public health system.

Glacier dynamics play an important role in the mass balance of many glaciers, ice caps and ice sheets. In this study we exploit Radarsat-2 (RS-2) Wide Fine (WF) data to determine the surface speed of Svalbard glaciers in the winters of 2012/2013 and 2013/2014 using Synthetic Aperture RADAR (SAR) offset and speckle tracking. The RS-2 WF mode combines the advantages of the large spatial coverage of the Wide mode (150 x 150 km) and the high pixel resolution (9m) of the Fine mode and thus has a major potential for glacier velocity monitoring from space through offset and speckle tracking. Faster flowing glaciers (1.95 m d^-1 - 2.55 m d^-1) which are studied in detail are Nathorstbreen, Kronebreen, Kongsbreen and Monacobreen. Using our Radarsat-2 WF dataset, we compare the performance of two SAR tracking algorithms, namely the GAMMA Remote Sensing Software and a custom written MATLAB script (GRAY method) that has primarily been used in the Canadian Arctic. Both algorithms provide comparable results, especially for the faster flowing glaciers and the termini of slower tidewater glaciers. A comparison of the WF data to RS-2 Ultrafine and Wide mode data reveals the superiority of RS-2 WF data over the Wide mode data.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

In recent years many different deep neural networks were developed, but due to a large number of layers in deep networks, their training requires a long time and a large number of datasets. Today is popular to use trained deep neural networks for various tasks, even for simple ones in which such deep networks are not required. The well-known deep networks such as YoloV3, SSD, etc. are intended for tracking and monitoring various objects, therefore their weights are heavy and the overall accuracy for a specific task is low. Eye-tracking tasks need to detect only one object - an iris in a given area. Therefore, it is logical to use a neural network only for this task. But the problem is the lack of suitable datasets for training the model. In the manuscript, we presented a dataset that is suitable for training custom models of convolutional neural networks for eye-tracking tasks. Using data set data, each user can independently pre-train the convolutional neural network models for eye-tracking tasks. This dataset contains annotated 10,000 eye images in an extension of 416 by 416 pixels. The table with annotation information shows the coordinates and radius of the eye for each image. This manuscript can be considered as a guide for the preparation of datasets for eye-tracking devices.

COVID-19 has affected 212 countries around the world, killing nearly 300,000 and infecting more than 4.4 million by May 14, 2020. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of communicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses. However, the country has just 127,000 hospital beds, 91,000 of them in government-run hospitals. Researchers say, the country’s economy is economy is losing BDT 33 billion every day from its service and agriculture sectors during the nationwide shutdown.

Typhoid fever is a communicable disease transmitted by the bacteria Salmonella typhi, related to serotype paratyphi A, B and C. The disease is of a significant health concern in most developing countries especially Cameroon. Objectives: The study aimed at determining the prevalence and associated risk factors of typhoid fever in children ( 0-18 years) attending the “Deo Gratias” hospital in Douala. Method: A hospital base cross sectional study from August to September 2018 was carried out in patients’ age 0-18 years suffering from typhoid fever at the Deo gratias Catholic hospital. Widal slide agglutination test was the diagnostic test used. Positive tested patients were administered questionnaires to evaluate the level of knowledge, attitude and practice toward the disease, as well as their self-management abilities. Data obtained from respondents was analysed by descriptive statistics. One-way ANOVA and means comparison using Tukey’s test (α = 0.05) was performed to check whether the population of respondents differed significantly across risk factor practices. Results were finally presented on bar charts, tables and pie chart. Results: Typhoid fever was more prevalent in females (52.3%) than in males (47.7%), with a high proportion in the ages 5-9 years (38.6%). A significant difference was observed in population of respondents across risk factor practices. Conclusion: Water quality have a great impact on the burden of typhoid fever among children. The identification of risk factors associated to the disease is of great importance in the development of rational control strategies of the disease.

The ongoing outbreak of the novel coronavirus pneumonia (also known as COVID-19) has triggered a series of stringent control measures in China, such as city closure, traffic restrictions, contact tracing and household quarantine. These containment efforts often lead to changes in the contact pattern among individuals of the population. Many existing compartmental epidemic models fail to account for the effects of contact structure. In this paper, we devised a pairwise epidemic model to analyze the COVID-19 outbreak in China based on confirmed cases reported during the period February 3rd--17th, 2020. By explicitly incorporating the effects of family clusters and contact tracing followed by household quarantine and isolation, our model provides a good fit to the trajectory of COVID-19 infections and is useful to predict the epidemic trend. We obtained the average of the reproduction number $R=1.494$ ($95\%$ CI: $1.483-1.507$) for Hubei province and $R=1.178$ ($95\%$ CI: $1.145-1.158$) for China (except Hubei), suggesting that some existing studies may have overestimated the reproduction number by neglecting the dynamical correlations and clustering effects. We forecasted that the COVID-19 epidemic would peak on February 13th ($95\%$ CI: February $9-17$th) in Hubei and 6 days eariler in the regions outside Hubei. Moreover the epidemic was expected to last until the middle of March in China (except Hubei) and late April in Hubei. The sensitivity analysis shows that ongoing exposure for the susceptible and population clustering play an important role in the disease propagation. With the enforcement of household quarantine measures, the reproduction number $R$ effectively reduces and epidemic quantities decrease accordingly. Furthermore, we gave an answer to the public concern on how long the stringent containment strategies should maintain. Through numerical analysis, we suggested that the time for the resumption of work and production in China (except Hubei) and Hubei would be the middle of March and the end of April, 2020, respectively. These constructive suggestions may bring some immeasurable social-economic benefits in the long run.

The value of QuantiFERON in the diagnosis of tuberculosis and in the monitoring of the response to anti-tuberculosis treatment is unclear. The aims of this study were to evaluate the accuracy of the QuantiFERON-TB Gold In-Tube (QFT-GIT) test in the diagnosis of tuberculosis and in the monitoring of the response to anti-tuberculosis treatment in patients with active pulmonary tuberculosis (PTB). Between January 2013 and December 2015, 128 cases with active PTB and 128 controls with no mycobacterial infection, matched by age (within 3 years) and by the week that they visited Tainan Chest Hospital, were enrolled in the study. Serial testing by QFT-GIT at baseline and after 2 and 6 months of treatment was performed. At these time points, a comparison of the performance of QFT-GIT with that of sputum culture status among study subjects was conducted. Compared to baseline, 116 (87.2%) cases showed a decreased response, whereas 17 (12.8%) showed persistent or stronger interferon-gamma (IFN-γ) responses at 2 months. Their IFN-γ responses declined significantly from baseline to 2 months (median, 6.32 vs. 4.12; P < 0.005). The sensitivity values of the QFT-GIT test for the detection of pulmonary tuberculosis at cut-off points of 0.35 IU/ml, 0.20 IU/ml, and 0.10 IU/ml were 74.4%, 78.2%, and 80.5%, respectively. The specificity values at cut-off points of 0.35 IU/ml, 0.20 IU/ml, and 0.10 IU/ml were 66.2%, 63.9%, and 57.1%, respectively. Our results support the QFT-GIT assay as a potential tool for diagnosing tuberculosis and for monitoring the efficacy of anti-tuberculosis treatment.

In this work, we designed a MEMS device which allows simultaneous direct measurement of mechanical properties during deformation under external stress and characterization of the evolution of microstructure of nanomaterials within a transmission electron microscope. This MEMS device makes it easy to establish the correlation between microstructure and mechanical properties of nanomaterials. The device uses piezoresistive sensors to qualitatively measure the force and displacement of nanomaterials, e.g., in wire and thin plate forms. The device has a theoretical displacement resolution of 0.19 nm and a force resolution of 2.1 μN. The device has a theoretical displacement range limit of 2.74 μm and a load range limit of 27.75 mN.

We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.

This paper uses panel data to find the determinants of tracking errors in exchange traded funds (ETFs) in the Hong Kong stock market. A comparison of tracking errors between physical and synthetic ETFs also indicates that the synthetic ETFs have higher tracking errors. The magnitude of tracking errors is found to be negatively related to size but positively related to dividend yield, trading volumes of funds, and market risk. However, this study also finds that expense ratio has a negative impact on tracking error, which is not consistent with previous studies, and which this paper addresses.

An on-site, ultra-sensitive, and quantitative sensing method was developed based on quantum dot nanobeads (QDNBs) and test strip for the determination of total aflatoxins (AFTs) in rice and peanut. The monoclonal antibody against AFT (mAbAFT) was home-made and labeled with QDNB. After the pre-coating of the AFT antigen on the test line (T line), the competitive immunoreactions were conducted between AFT and AFT antigen on the T line with QDNBs-mAbAFT. Under optimal conditions, this approach allowed a rapid response towards AFT with a considerable sensitivity of 1.4 pg/mL and 2.9 pg/mL in rice and peanut matrices, respectively. The put-in and put-out duration were within 10 min. The recoveries for AFT in rice and peanut samples matrices were recorded from 86.25–118.0% with the relative deviations (RSD) below 12%. The assay was further validated via the comparison between this QDNB strip and the conventional HPLC method using spiked samples. Thus, the design provided a potential alternative for on-site, ultra-sensitive, and quantitative sensing of AFT that could also be expanded to other chemical contaminants for food safety.

The scratch test consists in pushing a tool across the surface of a material at a given penetration depth or applied load. It has several applications in Science and Engineering including strength testing, damage and quality control of thin films and coatings. Despite numerous attempts in scientific literature, the application of scratch test to characterizations of fracture properties remains a heavily controversial topic. Therefore, this investigation arises as an experimental study in order to assess the fracture toughness using scratch test. A study on the effect of cryogenic treatment, performed after tempering, on fracture toughness, via scratch test experiments, of different tool steels has been made. A laboratory investigation on AISI D2, AISI M2 and X105CrCoMo18 steel confirms the possibility of increasing the fracture toughness by carrying out the cryogenic treatment after the usual heat treatment

We develop an interactive likelihood (ILH) for sequential Monte-Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, AFL, and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (OSPA and CLEAR MOT). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Multiple studies reported a negative relationship between the Honesty-Humility factor of the HEXACO model and psychopathy. The Durand Adaptive Psychopathic Traits Questionnaire (DAPTQ), which was developed to assess adaptive traits known to be related to psychopathic traits, has previously demonstrate positive relationships with all factors of the Big Five Model, at the exception of a negative relationship with neuroticism. The current study aims to validate the previously reported association between the DAPTQ and the five major components of the personality, while also examining its relationship with the Honesty-Humility factor as defined by the HEXACO model. The results (N = 171) support the good internal consistency, two weeks test-retest validity and inter-correlation of the DAPTQ. A Confirmatory Factor Analysis further supports the nine-factor model of the DAPTQ. When compared to the HEXACO, the DAPTQ did not display any relationship with the Honesty-Humility factor, nor the Agreeableness and Openness factors, but kept its similar association to Emotionality, Extroversion, and Conscientiousness as initially reported in its development phase. Overall, the results support the discriminant validity of the DAPTQ to assess adaptive traits related to the psychopathic personality without overlapping with psychopathic personality traits. Results are discussed in terms of implications and further improvements to validate the DAPTQ.

While texturing of workpiece surfaces to promote lubrication in metal forming has been applied for several decades tool surface texturing is rather new. In the present paper tool texturing is studied as a method to prevent galling. Adopting a strip reduction test longitudinal pocket geometries oriented perpendicular to the sliding direction, with shallow pocket depth, small pocket angle to the workpiece surface and varying distance between pockets are investigated. The experiments reveal that the distance between pockets should be larger than the pocket width thereby creating a topography similar to flat table mountains to avoid mechanical interlocking in the valleys; otherwise an increase in drawing load and pick-up on the tools is observed. The textured tool surface lowers friction and improves lubrication performance provided that the distance between pockets is 2-4 times larger than the pocket width. Larger drawing speed facilitates escape of the entrapped lubricant in the pockets. Testing with low to medium viscosity oils leads to a low sheet roughness on the plateaus but also local workpiece material pick-up on the tool plateaus. Large lubricant viscosity results in higher sheet plateau roughness but also prevents pick-up and galling.

We develop a mathematical model to provide epidemic predictions for the 2019-nCov epidemic in Wuhan, China. We use reported case data up to January 31, 2020 from the Chinese Center for Disease Control and Prevention and the Wuhan Municipal Health Commission to parameterize the model. From the parameterized model we identify the number of unreported cases. We then use the model to project the epidemic forward with varying level of public health interventions. The model predictions emphasize the importance of major public health interventions in controlling 2019-nCov epidemics.

The importance of statistics in biological research is inevitable. The appliance of statistics is the most powerful tool to support the scientific hypothesis and to give credibility to biological research methodology, to interpret convoluted explanations and conclusions based on the research findings. The evidences from literatures point the persistent statistical errors, selection of non-proper statistical test with the consequence of misinterpretation of the scientific results which are published in international journals. One of the most extensively used statistical tests in the field of biology (preclinical and clinical) is analysis of variance (ANOVA). ANOVA test is in place of multiple T-tests to compare the means of more than two groups at a time; and there are some important points which biologists should be aware of them to avoid possible misinterpretation of results with the consequence of wrong conclusion. Accordingly, the aim of the current review is to help biologists to understand the basic concepts of ANOVA test and reach to a more valid interpretation of achieved results.

This paper presents a microgrid distributed energy resources (DERs) for a rural standalone system. It is made up of solar photovoltaic (solar PV) system, battery energy storage system (BESS), and wind turbine coupled to permanent magnet synchronous generator (WT-PMSG). The DERs are controlled by maximum power point tracking (MPPT) based proportional intergral (PI) controllers for both maximum power tracking and error feedback compensation. The MPPT uses the perturb and observe (P&O) algorithm for tracking the maximum power point of the DERs. The PI gains are tuned using the Ziegler-Nichol’s method. The developed system was built and simulated in MATLAB/Simulink under two conditions - constant load, and step load changes. The controllers enabled the BESS to charge even during conditions of varying load and other environmental factors such as change of irradiance and wind speed. The reference was tracked very well by the output voltage of the DC grid. This is a useful research for electrifying the rural islanded areas, too far from the grid.

In order to meet the military requirements of the fuze, such as precision strike, efficient mutilates ability and low collateral damages, the microminiaturization is an inevitable trend of secure system. Based on the silicon-based MEMS S&A device designed by our term, the design principles of each module and fabrication process are introduced. The average fracture strength and Young's modulus of the silicon are 726 MPa and 175 GPa from the tensile test, respectively. From Hopkinson impact experiment, we can get the threshold-value judging mechanism being safety under the impact overload of 20526 g, and this value is much more than the standard of the drop overload 12000g; the arming value under the centrifugal overload obtained from theory, simulation and experiment is at the range of 28200 g and 32000 g, it shows that the threshold-value judging mechanism can be arming compared with the value 35951g of design principle. Therefore, the threshold-value judging mechanism can meet the design requirements of overload. Furthermore, the relationship of fracture threshold-values obtained by different theories is found out through parametric design method, as shown in Figure 14, it provides the theory evidence to the follow parametric design.

The stability assessment of aged tunnel linings were mainly evaluated based on the visual inspection, and the Tunnel-lining Crack Index (TCI) is one of the most widely used tunnel lining health assessment indexes in Japan. However, the intersection and distribution of cracks, which can influence the stability of tunnel lining greatly, were not considered in the TCI. A new method was proposed for the health assessment of tunnel lining, which evaluate the lining states according to the fractal dimension of cracks. Based on the machine vision-based method, the crack image can be extracted efficiently. The fractal dimension of lining cracks in one span can be obtained in a few minutes. A series of comparative tests and field tests were conducted to evaluate the validity of this new method. The comparative tests confirmed that fractal dimension can characterize the density, width, and distribution of cracks. The results also certificated that the influence of crack width is larger than the crack density. The intersection of cracks, which will increase the risk of lining collapse, can also increase the fractal dimension, whereas the TCI keep constant. The fractal dimensions of tunnel lining cracks were obtained according to the digital inspection test of Hidake Tunnel in Japan for all the 65 spans. Moreover, the TCI was obtained through statistical methods. The correlation between fractal dimension and TCI of tunnel lining was studied. The significance of the new evaluation index is that it can identify some unusual spans of tunnel lining and provide a basis for further internal testing. As a complement to the conventional visual inspection method, the fractal dimension of the cracks is a promising health assessment index.

Study Objective: This study examined office workstation types’ impact on objective health-related metrics including stress, physical activity (PA), and sleep quality. We propose a sensor-based sleep quality index (SB-SQI) to fill a needed gap for objective sleep quality measurement over short timescales. Methods: We monitored 231 office workers using chest-worn sensors for 72 hours, yielding 11,736 hours of usable data from 163 participants (mean age 43.4, 56% women). SB-SQI was based on a validated algorithm estimating sleep-onset latency, total sleep time, and sleep efficiency, using the scoring method from the Pittsburg Sleep Quality Index (PSQI). We examined the relationships between SB-SQI, office workstation type (open-bench seating, cubicle, and private office), work-hours stress (standard deviation of heart rate variability), and after-work PA (relative duration of moderate-to-vigorous activity). Results: The sensor-derived poor-sleep ratio of the private office workers was higher than with other office workstation types (81% vs. 66.1%, p = 0.023). PSQI revealed a similar but insignificant trend with a lower effect-size. Among good-sleepers, open-bench seating workers had 22% (p = 0.018) less stress during work hours than others. A significant association between work-hours stress and after-work hours PA (r = 0.331, p = 0.000) was observed irrespective of office workstation type, with the highest PA level observed for open-bench seating workers. Conclusions: Office workstation type had a significant impact on work-hours stress, affecting PA after work hours, which influenced sleep quality. SB-SQI could be more sensitive than PSQI in determining the impact of office workstation types on sleep quality.

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named interacting multiple model fifth-degree spherical simplex-radial cubature filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and fifth-degree spherical simplex-radial cubature filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with IMMUKF, IMMCKF and IMM5thCKF.

Autonomous aerial refueling technology is an effective solution to extend flight duration of unmanned aerial vehicles, and also a great challenge due to its high risk. For autonomous probe-and-drogue refueling tasks, relative navigation to provide relative position between the receiver aircraft and the refueling drogue is the first and essential step, and vision-based method is the most frequently used. A new monocular vision navigation sensor with image processing strategy consisting of the drogue detection method and the tracking method is developed for autonomous aerial refueling in this paper. In the drogue detection method, thresholding and mathematical morphology method are adopted to eliminate image interference, and contours extraction method is applied to obtain all contours, which are then subsequently checked to achieve target contour of drogue. In the tracking method, a rectangle of interest (ROI) of current frame image is determined by positioning results of last frame, and then processed by the previous drogue detection method. Finally, the proposed image processing strategy in monocular vision navigation sensor is validated using real flight images, which are captured from an autonomous aerial refueling testbed using a micro six-rotor aircraft as receiver aircraft.

A face serum composed of a combination of biologically active compounds was evaluated for safety and efficacy in vitro, in a repeat insult patch test and in a human clinical efficacy trial. The serum inhibited tyrosinase activity modestly, decreased collagenase activity and exhibited notable free radical scavenging activity in vitro. It is gentle to the skin, as the serum did not irritate the skin or produce symptoms of allergic contact dermatitis in the 55 healthy adults that participated in the repeat insult patch test. In the efficacy trial, daily application of the face serum for 30 days significantly increased skin hydration, with all 35 volunteers experiencing improvement. Substantial improvements in skin elasticity, roughness (fine lines and wrinkles), and brightness also occurred during the trial. Dermatological examination also revealed a trend for reduced comedone count with use of the serum. Self-assessment responses revealed that all volunteers experienced improvements in multiple skin quality parameters and that participant perceptions are consistent with the results of the instrumental analyses. These findings indicated that the measured improvements in skin quality are not only statistically significant but are also clinically relevant as they were great enough for users of the face serum to feel and recognize.

This work combines compressive sensing and short word-length techniques to achieve localization and target tracking in wireless sensor networks with energy-efficient communication between the network anchors and the fusion center. Gradient descent localization is performed using time-of-arrival (TOA) data which are indicative of the distance between anchors and the target thereby achieving range-based localization. The short word-length techniques considered are delta modulation and sigma-delta modulation. The energy efficiency is due to the reduction of the data volume transmitted from anchors to the fusion center by employing any of the two delta modulation variants with compressive sensing techniques. Delta modulation allows the transmission of one bit per TOA sample. The communication energy efficiency is increased by RⱮ, R≥1, where R is the sample reduction ratio of compressive sensing and Ɱ is the number of bits originally present in a TOA-sample word. It is found that the localization system involving sigma-delta modulation has a superior performance to that using delta-modulation or pure compressive sampling alone, in terms of both energy efficiency and localization error in the presence of TOA measurement noise, owing to the noise shaping property of sigma-delta modulation.

In the context of the COVID-19 Pandemic, the use of surgical masks has become the new normal. The use of these devices in exercise and medical situations has been advocated with the purpose of reducing contagions, but some concerns exist regarding its safety. We performed maximal treadmill stress tests in 12 healthy young subjects, with and without surgical mask use, and measured exercise capacity, oxygen saturation (rest, peak exercise and post-exercise) and electrocardiographic changes. Exercise capacity and Oxygen saturation levels decreased in peak exercise vs rest in a statistically significant manner when mask was used. ECG changes, although not significant, were present in 3 subjects when mask was used and disappeared when the test was made unmasked. We conclude that masked exercise has the potential to cause decreased exercise load and oxygen saturation and potentially cause diagnostic errors in medical exams.

Sports video analysis is an interesting and emerging field in the domain of computer vision. It has become a very popular subject among scholars all over the world in the last decade due to the need of automated classification of events such as offsides, in/out situations, goals and so on. The most important problem in sports video analysis is detection and tracking of ball and players. Extraction of court lines is also another important problem since it is necessary in the classification of aforementioned events. In this study, considering some of the previous work on the subject, we develop a method for tracking the ball and players in tennis videos where the camera position and orientation is supposed fixed.

The antioxidant properties and polyphenol content of some selected aromatic plants grown in Greece were studied. Plants were refluxed with 60% methanol after acid hydrolysis. The phenolic substances were quantified by HPLC-DAD. The antioxidant capacity of the extracts was determined with the Rancimat test using sunflower oil as substrate. Free radical scavenging activity was measured using the stable free radical 1, 1-diphenyl-2-picrylhydrazyl (DPPH). Results were compared with standard BHT and ascorbic acid. Total phenol concentration of the extracts was estimated with Folin-Ciocalteu reagent using gallic acid as standard.

Co-integration and Causality was built to conduct studies on causality relation between carbon intensity and coal consumption leading to providing important basis for the transition to a low carbon economy. The EG two-step method was performed to study the relation between carbon intensity and coal consumption of China during 1990-2015 and the co-integration and Granger test was constructed to build up the co-integration and error correction models for analysis of the interaction between carbon intensity and coal consumption. The results showed that in long term there is a stable co-integration relation and a positive correlation between carbon intensity and coal consumption; whereas fluctuations exist in short term and there is a one-way Granger causality of carbon intensity with respect to coal consumption.

The biophysical consequences of nanoscale curvature have been challenging to resolve due to size-dependent membrane behavior and the experimental resolution limits imposed by optical diffraction. Recent advances in nanoengineering and super-resolution techniques have enabled new capabilities for creating and observing curvature. In particular, draping supported lipid bilayers over lithographically patterned substrates provides a model system for endocytic pits. The experiments and simulations presented below describe the possible detection of membrane curvature through fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS), single particle tracking (SPT), and polarized localization microscopy (PLM). FRAP and FCS depend on diffraction-limited illumination and detection. In particular, a simulation of FRAP shows no effects on lipids diffusion due to a 50 nm diameter membrane bud at any stage in the budding process. Simulated FCS demonstrated small effects due to a 50 nm radius membrane bud that was amplified with curvature-dependent lipid mobility changes. However, PLM and SPT achieve sub-diffraction-limited resolution of membrane budding and lipid mobility through the identification of the single-lipid positions with ≤15 nm spatial and ≤20 ms temporal resolution. By mapping the single-lipid step lengths to locations on the membrane, the effects of curvature on lipid behavior have been resolved.

This paper discusses about control of the linear switched reluctance machines (LSRMs) network for the zero phase-difference tracking to a sinusoidal reference. The dynamics of each LSRM is derived by online system identification and modeled as a second-order linear system. Accordingly, based on the coupled harmonic oscillators synchronization manner, a distributed control is proposed to synchronize each LSRM state to a virtual LSRM node representing the external sinusoidal reference for tracking it with zero phase-difference. Subsequently, a simulation scenario and an experimental platform with the identical parameter setup are designed to investigate the tracking performance of the LSRMs network constructed by the proposed distributed control. Finally, the simulation and experimental results verify the effectiveness of the proposed LSRMs network controller, and also prove that the coupled harmonic oscillators synchronization method can improve the synchronization tracking performance and precision.

We introduce PyNTA, a modular instrumentation software for live particle tracking. By using the multiprocessing library of Python and the distributed messaging library pyZMQ, PyNTA allows users to acquire images from a camera at close to maximum readout bandwidth while simultaneously performing computations on each image on a separate processing unit. This publisher/subscriber pattern generates a small overhead and leverages the multi-core capabilities of modern computers. We demonstrate capabilities of the PyNTA package on the featured application of nanoparticle tracking analysis. Real-time particle tracking on megapixel images at a rate of 50 Hz is presented. Reliable live tracking reduces the required storage capacity for particle tracking measurements by a factor of approximately 10³, as compared with raw data storage, allowing for a virtually unlimited duration of measurements

Continuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object’s movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.

Impact characterization of linear resonant actuator (LRA) is studied experimentally by newly developed drop tester, which can control various experimental uncertainty such as rotational moment, air resistance, secondary impact and so on. The feasibility of this test apparatus was verified by comparison with free fall test. By utilizing a high-speed camera and measuring the vibrational displacement of spring material, the impact behavior was captured and the damping ratio of the system was defined. Based on the above processes, the finite element model was established and the experimental and analytical results were successfully correlated. Finally, the damage of the system from impact loading can be expected by developed model and as a result, this research can improve the impact reliability of LRA.

Dietary patterns established during adolescence might play a role in adulthood disease. We examined the stability of dietary patterns (DPs) from childhood through adolescence and into young adulthood (from age 8 to 34 years). Data from 130 participants (53 females) of Saskatchewan Pediatric Bone Mineral Accrual Study (aged 8-15 years, at baseline) were included. Multiple 24-hour recalls were collected annually from 1991 to 1997, 2002 to 2005 and 2010 and 2011. Using principal component analysis, “Vegetarian-style”, “Western-like”, “High-fat, high-protein”, “Mixed” and “Snack” DPs were derived at baseline. Applied DP scores for all annual measurements were calculated using factor loading of baseline DPs and energy-adjusted food group intakes. We analyzed data using generalized estimating equations. The tracking coefficient represents correlation between baseline dietary pattern scores and all other follow-up dietary pattern scores. We found a moderate tracking for the “Vegetarian-style” (ß=0.44, P<0.001) and “High-fat, high-protein” (ß=0.39, P<0.001) DPs in females and “Vegetarian-style” DP (ß=0.30, P<0.001) in males. Remaining DPs showed a poor-to-fair tracking in both sexes. No tracking for “Western-like” DP in females was observed. Assessing overall change in DP scores from childhood to young adulthood showed an increasing trend in adherence to “Vegetarian-style” DP and decreasing trend in adherence to “High-fat, high-protein” DP by age in both sexes (P<0.001). While “Western-like” and “Mixed” DP scores increased only in males (P<0.001). These findings suggest that healthy dietary habits established during childhood and adolescence moderately continue into adulthood.

4-(thiazol-2-yldiazenyl)phenol (L₁) and 2-((4-hydroxyphenyl) diazenyl)-5-nitrophenol (L₂) based on azo phenol were synthesised and used as selective colorimetric sensor for CN^- and AcO⁻ ion in DMSO/H₂O-HEPES (v/v; 1:1, pH–7.3 ± 0.2) and showed good sensitivity with large red shifts and nanomolar detection limit for CN^- and AcO^- ion. The stoichiometry of L₁ with CN⁻/AcO⁻ ion was found to be 1:1 and L₂ with CN⁻/AcO⁻ ion was found to be 1:2. Binding constant for L₁+ CN⁻, L₁ + AcO⁻, L₂ + CN⁻ and L₂ + AcO⁻ were calculated by B-H plot as 1.6 × 10³, 8.0 × 10², 8.4 × 10³ and 1.7 × 10² respectively. L₂ showed high selectivity towards CN⁻ ion with low detection limit of 81 nM and large binding constant. In addition, ¹H NMR titration and DFT studies also supported the deprotonation mechanism of receptors in the presence of selective anions.

Several articles have reported that the low number of COVID-19 cases in Japan is attributed to the small number of diagnostic RT-PCR tests performed. The criticism is based on the low number of the tests performed, and they suspected there would be more potential cases in Japan. The use of pre-test probability among tested subjects is proposed in order to evaluate of the sufficiency of test availability instead of the number of the tests. The pre-test probability means the average probability, i.e., ‘suspicion level’, of having coronavirus among the tested subject in a country. The higher pre-test probability is regarded as less sufficient opportunity of the tests, and the test availability could be evaluated by the pre-test probability. Thus, potential problems of underestimation of COVID-19 cases by insufficient amount of the test would be clear by using pre-test probability. The comparison of the pre-test probability could be replaced with that of the positive rate of the test because of the linear relationship between them under the assumption of common sensitivity and specificity. Japan shows the third lowest rate (8.6%), and is considered that the considerably sufficient number of the tests have been performed. In conclusion, the positive rate of the test as a surrogate index of the pre-test probability is useful to evaluate the sufficiency of test amount instead of the number of the tests performed. In present, the potential problem of underestimation by insufficient test availability would be less serious in Japan.

This paper investigates a distributed, coordinated motion control network based on multiple direct-drive, linear switched reluctance machines (LSRMs). A hierarchical, two-level synchronization control strategy is proposed for the four LSRMs based motion control network. The high-level, reference signals agreement algorithm is first employed to correct the asynchronous behaviors of the position commands. Then, the low-level tracking synchronization method is applied for the collaborative position control of the four LSRMs. The proposed two-level, fault-tolerant control strategy eliminates the asynchrony of the reference signals and it also guarantees the coordinated tracking control performance of the four LSRMs. Experimental results demonstrate that effective coordinated tracking control can be ensured, based on successful agreement of reference signals and an absolute tracking error falling within 2 mm can be achieved.

Full-scale/model test comparison studies to validate the traditional ABL wind tunnel simulation technique are reviewed. According to the literature review, notable discrepancies between full-scale measurement results and model test results were observed by most performed comparison studies, but the causes of the observed discrepancies were not revealed in a scientific way by those studies. In this regard, a new research scheme for future full-scale/model test comparison studies is proposed in this article, which utilizes the multiple-fan actively controlled wind tunnel simulation technique. With the new research scheme, future full-scale/model test comparison studies are expected to reasonably disclose the main problems with the traditional ABL wind tunnel simulation technique, and the technique can be improved correspondingly.

The rapid development of multicopters has led to many security problems. In order to prevent multicopters from invading restricted areas or famous buildings, an Anti-UAV Defense System (AUDS) has been developed and become a research topic of interest. Topics under research in relation to this include electromagnetic interference guns for unmanned aerial vehicles (UAVs), high-energy laser guns, US military net warheads, and AUDSs with net guns. However, these AUDSs use either manual aiming or expensive radar to track UAVs. This paper proposes a dual-axis rotary platform with UAV automatic tracking. The tracking platform uses visual image processing technology to track and lock the dynamic displacement of a UAV. When a target UAV is locked, the system uses a nine-axis attitude meter and laser rangefinders to measure its flight altitude and calculates its longitude and latitude coordinates through sphere coordinates to provide UAV monitoring for further defense or attack missions. Tracking tests of UAV flights in the air were carried out using a DJI MAVIC UAV at a height of 30 meters to 100 meters. It was set up for UAV image capture and visual recognition for tracking under various weather conditions by a thermal imager and a full-color camera respectively. When there was no cloud during the daytime, the images captured by the thermal imager and full-color camera provide a high-quality image recognition result. However, under dark weather, black clouds will emit radiant energy and seriously affect the capture of images by a thermal imager. When there is no cloud at night, the thermal imager performs well in UAV image capture. When the UAV is tracked and locked, the system can effectively obtain the flight altitude and longitude and latitude coordinate values.

In this work, a hybrid component Fault Detection and Diagnosis (FDD) approach for industrial sensor systems is established and analyzed, to provide a hybrid schema that combines the advantages and eliminates the drawbacks of both model-based and data-driven methods of diagnosis. Moreover, it shines the light on a new utilization of Random Forest (RF) together with model-based diagnosis, beyond its ordinary data-driven application. RF is trained and hyperparameter tuned using three-fold cross validation over a random grid of parameters using random search, to finally generate diagnostic graphs as the dynamic, data-driven part of this system. This is followed by translating those graphs into model-based rules in the form of if-else statements, SQL queries or semantic queries such as SPARQL, in order to feed the dynamic rules into a structured model essential for further diagnosis. The RF hyperparameters are consistently updated online using the newly generated sensor data to maintain the dynamicity and accuracy of the generated graphs and rules thereafter. The architecture of the proposed method is demonstrated in a comprehensive manner, and the dynamic rules extraction phase is applied using a case study on condition monitoring of a hydraulic test rig using time-series multivariate sensor readings.

With the outbreak of coronavirus disease 2019 (COVID-19), there is a need for efficient management of patients with mild or no symptoms, which account for the majority. The aim of this study is to introduce the structure and operation protocol of a living and treatment support centre (LTSC) operated by Seoul National University Hospital in South Korea. The existing accommodation facility was converted into a 'patient centre' where patients was isolated. A few Medical staff here performed medical tests and responded to emergencies. Another part of the LTSC was 'remote monitoring centre'. In this center, patients’ self-measured vital signs and symptoms were monitored twice a day, and the medical staff staying here provided video-consultation via a smartphone. During the 3 weeks from March 5 to March 26, 2020, 113 patients were admitted and treated. LTSC could be an efficient alternative to hospital admission in pandemic situation like COVID-19.

In only a few months after initial discovery in Wuhan, China, SARS-CoV-2 and the associated COVID-19 disease has become a global pandemic causing significant mortality and morbidity. In the absence of vaccines and effective therapeutics, reliable serological testing can be a key element of public health policy to control further spread of the disease and gradually ease quarantine measures. However, prior to launch of large-scale seroprevalence studies to assess herd immunity, it is critical to understand the limits and potential of current SARS-CoV-2 serological tests on the market. In this study, we provide an overview of serological testing and conduct a systematic review of independent evaluations of SARS-CoV-2 serological tests performance. Our findings show significant variability in the accuracy of marketed tests and highlight several lab-based and point-of-care rapid diagnostic tests with high performance level in detecting SRAS-CoV-2 specific antibodies. The findings of this review highlight the need for ongoing independent evaluations of commercialized COVID-19 diagnostic tests.

Autonomic dysfunction is an increasingly recognised complication in chronic neurological conditions such as Parkinson’s disease , and other medical conditions, including diabetes mellitus, chronic fatigue syndrome, postural tachycardia syndrome with and without Ehlers-Danlos syndrome, fibromyalgia and recently Long Covid. Despite laboratory-based tests to evaluate normal and abnormal autonomic function, there are no home-based tests to record neuro-cardiovascular autonomic responses to common stimuli in daily life that are dependent on the normal functioning of the autonomic nervous system. We have developed an adapted blood pressure/heart Autonomic Profile (aAP) that can be used by an individual independently and repeatedly in a domiciliary setting to determine the physiological and symptomatic response to standing, food, and physical and mental (cognitive, emotional) activities. The aAP aids separating autonomic failure (often irreversible) from autonomic dysfunction. This helps the individual and attending healthcare professional understand the relationship between symptoms and common triggers in daily life and informs on self-management in debilitating conditions such as the postural tachycardia syndrome (PoTS) and Long Covid.

Among all the active confinement techniques, the use of pre-tensioned stainless steel straps has recently gained much attention. The flexibility of the stainless steel straps allows us to bend and pass them through the thickness of the masonry, thus creating a three-dimensional strengthening system between the two opposite facings. The use of the same perforation for the passage of several straps closed in a loop generates a continuous strengthening system that prevents parts of the structure from falling and injuring the occupants during seismic events. However, the perforations can nullify the in-plane strengthening, as they act as cylindrical hinges and make the reinforcement system labile for certain strap arrangements. Diagonal compression tests on square masonry panels performed in the present study show that the straps improve neither strength nor ductility when running along the mortar head and bed joints, arranged in square meshes. Conversely, they improve both strength and ductility when the straps make angles of 45° with the mortar joints. Furthermore, the experimental results show that the straps exert an anisotropic effect that decreases the apparent in-plane Poisson ratio. They also provide new insights into the diagonal compression test and allow formulating a new proposal for the pseudo-ductility factor.

Studies on the structure of economic systems are, most frequently, carried out by the methods of informational statistics. These methods, often accompanied by a wide range of indicators (Shannon entropy, Balassa coefficient, Herfindahl specialty index, Gini coefficient, Theil index etc.) around which a wide literature has been created over time, have a major disadvantage. Such weakness is related to the imposition of the system condition, therefore the need to know all the components of the system (as absolute values or as weights). This restriction is difficult to accomplish in some situations, and in others, this knowledge may be irrelevant, especially when there is an interest in structural changes only in some of the components of the economic system (either we refer to the typology of economic activities - NACE or of territorial units – NUTS). This article presents a procedure for characterizing the structure of a system and for comparing its evolution over time, in the case of incomplete information, thus eliminating the restriction existent in the classical methods. The proposed methodological alternative uses a parametric distribution, with subunit values for the variable. The application refers to Gross Domestic Product values for five of the 28 European Union countries, with annual values of over 1,000 billion Euros (Germany, Spain, France, Italy and United Kingdom) for the years 2003 and 2015. A form of the Wald sequential test is applied to measure changes in the structure of this group of countries, between the years compared. The results of this application validate the proposed method.

Theory of the Thermal Response Testing (TRT) is a well-known part of sizing process of the geothermal exchange system. Multiple parameters influence accuracy of effective ground thermal conductivity measurement; like testing time, variable power, climate interferences, groundwater effect etc. To improve accuracy of the TRT we introduced procedure to additionally analyze falloff temperature decline after power test. Method is based on a premise of analogy between TRT and petroleum well testing, since origin of both procedures lies in diffusivity equation with solutions for heat conduction or pressure analysis during radial flow. Applying pressure build-up test interpretation technique to the borehole heat exchanger testing, greater accuracy could be achieved since ground conductivity could be obtained from this period. Analysis was conducted on coaxial exchanger with five different power steps, and with both direct and reverse flow regime. Each test was set with 96hr of a classical TRT, followed by 96hr of temperature decline, making it almost 2000 hours of cumulative borehole testing. Results showed that ground conductivity value could vary as much as 25% depending on test time, seasonal period and power fluctuations while thermal conductivity obtained from a falloff period gives more stable values with only 10% value variation.

Owing to fascinating applications of ZnO in modern devices, it is interesting to explore its more features for future devices. Hence, herein, we have synthesized the high quality ZnO spherical nanoparticles (SNPs) through a facile green synthesis route and robust structural and biomedical studies are carried out. Hexagonal phase with 93.2% crystallinity was confirmed through XRD analysis. ZnO nanoparticles were tested for their bioactivities both in vivo (acute cytotoxicity test) and in vitro (Anti-cancer activities on liver (HepG2) and cervical (Hela) cancer cell lines, stimulatory/inhibitory effects on normal rat splenic cells and hemolytic effects on red blood cells). Results showed that ZnO SNPs has no cytotoxic effects on vital organ like liver and has no hemolytic action on red blood cells. ZnO SNPs showed inhibitory consequence on normal rat splenic cells growth at all tested concentrations. ZnO nanoparticles showed an inhibitory effect on HepG2 cell line. While showed stimulatory effect on Hela cell line. Current study presents the synthesized ZnO SNPs as highly applicable in bio-optoelectronics.

The performance of ground heat exchangers systems depends on the knowledge of the thermal parameters of the ground like thermal conductivity, thermal capacity and diffusivity. The knowledge of these parameters often requires quite accurate experimental analysis, known under the name of Thermal Response Test (TRT). In this paper, after a general analysis of the various available types of TRT and the study of the theoretical basics of the method, the perspective of the definition of a simplified routine method of analysis based on the combination of a particular version of TRT and the routine geotechnical tests for the characterization of soil stratigraphy and of the ground characteristics, mandatory before the construction of a new buildings, even if limited to quite short drilling depth (lower than 30 m). The idea of developing TRT in connection with geotechnical test activity has the objective of promoting a widespread use of in-situ experimental analysis and of reducing TRT costs and time duration of the experimental analysis. The considerations exposed in the present paper lead to reconsider a particular variety of the TRT in particular the version known as Thermal Response Test while Drilling (TRTWD).

The Combined Elevation Test (CET) is a musculoskeletal screening technique (MST) replicates the streamline position in swimming and is commonly used in various sports. Although the CET is widely used, no normative data exist within an adolescent population. Therefore, the purpose of this study was to develop a normative data set for the CET within an adolescent population and to evaluate the influence various demographic and anthropometric variables. Data was collected for 416 participants aged between 8 and 18 years old. Age and arm span showed a significant correlation with CET scores (arm span r_s (105) = .478, p = .000, age r_s (416) = .238 p = .000). Regression analysis further quantified the influence of arm span and age on CET scores accounting for 23.1% and 5.3% of variability respectively. These results can be used as a reference point for clinicians and coaches who are using the CET within their assessment.

The main objective of this paper is to find a close link between the adaptive level of significance, presented here, and the sample size. We, statisticians, know of the inconsistency, or paradox, in the current classical tests of significance that are based on p-value statistics that is compared to the canonical significance levels (10%, 5% and 1%): "Raise the sample to reject the null hypothesis" is the recommendation of some ill-advised scientists! This paper will show that it is possible to eliminate this problem of significance tests. The Bayesian Lindley's paradox – "increase the sample to accept the hypothesis" – also disappears. Obviously, we present here only the beginning of a possible prominent research. The intention is to extend its use to more complex applications such as survival analysis, reliability tests and other areas. The main tools used here are the Bayes Factor and the extended Neyman-Pearson Lemma.

Organizational skills are a set of cognitive abilities responsible for goal-directed behaviors. While they are moderately studied in clinical settings, the assessment of organizational skills in the general population remains under-studied. This paper presents the new Durand Organizational Skills Questionnaire (DOSQ), which was developed to examine the factors associated with organizational abilities in the general population. Exploratory factor analysis, validated by a confirmatory factor analysis, suggests eight factors: Work Organization, Communication Clarity, Punctuality, Goal-Oriented Behavior, Assiduity, Workspace Organization, Strategies, and Attentiveness. Three studies using samples from the general population provided evidence for the reliability and validity of the DOSQ’s scores. Overall, the results suggest that the DOSQ offers a valid approach to measuring organizational skills in the general population.

The world's growing population is highly dependent on animal agriculture. Animal products provide nutrient-packed meals that help to sustain individuals of all ages in communities across the globe. As the human demand for animal proteins grows, the agricultural industry must continue to advance its efficiency and quality of production. One of the most commonly farmed livestock is poultry and their significance is felt on a global scale. Current poultry farming practices result in the premature death and rejection of billions of chickens on an annual basis before they are processed for meat. This loss of life is concerning regarding animal welfare, agricultural efficiency, and economic impacts. The best way to prevent these losses is through the individualistic and/or group level assessment of animal on a continuous basis. On large-scale farms, such attention to detail was generally considered to be inaccurate and inefficient, but with the integration of Artificial Intelligence (AI) assisted technology individualized and per-herd assessments of livestock are possible and accurate. Various studies have shown cameras linked with specialized systems of AI can properly analyze flocks for health concerns, thus improving the survival rate and product quality of farmed poultry. Building on the recent advancements, this review explores the aspects of AI in the detection, counting and tracking of the poultry in commercial and research-based applications.

The epidemiological situation generated by COVID-19 has highlighted the importance of applying non-pharmacological measures. Among these, mass screening of the asymptomatic general population has been established as a priority strategy by carrying out diagnostic tests to limit the spread of the virus. In this article, we aim to evaluate the economic impact of mass COVID-19 screenings of an asymptomatic population through a Cost-Benefit Analysis based on the estimated total costs of mass screening versus health gains and associated health costs avoided. Excluding the value of monetized health, the Benefit-Cost ratio was estimated at approximately 0.45. However, if monetized health is included in the calculation, the ratio is close to 1.20. The monetization of health is the critical element that tips the scales in favour of the desirability of screening. Screenings with the highest return are those that maximize the percentage of positives detected.

Abstract: This paper is focusing on the stabilisation of soil using jute fibre as soil stabilizer. Stabilisation is the process of modifying the properties of a soil to improve its engineering performance and used it for a variety of engineering works. This study examines the potential of soil stabilization with jute fibre when it is cut into roughly 30mm lengths as stabilizer. The varying percentages like 0.5%, 1%, 1.5 and 2% of pieces of jute fibre were used and mixed it with soil. The laboratory tests such as California Bearing Ratio (CBR) test, modified compaction tests and direct shear strength tests have been conducted to observe the change in engineering properties of soil. On the basis of the experiments performed, it can be concluded that the stabilization of soil using 30mm pieces of jute as stabilizer improves the strength characteristics of the soil so that it becomes usable as one of the reinforcing material for the construction of roadways, parking areas, site development projects, airports and many other situations where sub-soils are not suitable for construction.

Signal-to-noise ratio (SNR) is an important index to evaluate radiation performance and image quality of optical imaging systems under low illumination background. Under the nighttime lighting condition, the illumination of remote sensing objects is low and varies greatly, usually ranging from several lux to tens of thousands of lux. Nighttime light remote sensing imaging requires high sensitivity and large dynamic range of detectors. Luojia 1-01 is the first professional nighttime light remote sensing satellite in the world. In this paper, we took the nighttime light remote sensing camera carried on the satellite as research object, proposed an in-orbit SNR test method based on time series images to overcome the problem of low spatial resolution. We first analyzed the process of luminous flux transmission between objects and satellite and established a radiative transfer model. By combining the parameters of large relative aperture optical system and high sensitivity CMOS device, we established SNR model and specially analyzed the effect of exposure time and quantization bits on SNR. Finally we used the proposed in-orbit test method to calculate SNR of lighting images acquired by satellite. And the measured result is in good agreement with the model predicted data. Under the condition of 10lx illumination, the SNR of typical objects can reach 27.02dB, which is much better than the requirement of 20dB for engineering application.

Identifying anti-spike antibodies that exhibit strong neutralizing activity against current dominant circulating variants and antibodies that are escaped by these variants have important implications in the development of therapeutic and diagnostic solutions as well as in improving understanding of the humoral response to SARS-CoV-2 infection. We characterized seven anti-RBD monoclonal antibodies for their binding activity, pairing capability and neutralization activity to SARS-CoV-2 and three variant RBDs (UK, SA and BR P.1) via lateral flow immunoassays. The results allowed us to group these antibodies into three distinct epitope bins. Our studies showed that two antibodies had broadly potent neutralizing activity against SARS-CoV-2 and these variant RBDs and that one antibody did not neutralize the SA and BR P.1 RBDs. The antibody escaped by the SA and BR P.1 RBDs retained binding activity to SA and BR P.1 RBDs but was unable to induce neutralization. Further, we demonstrated that the lateral flow immunoassay can be a rapid and effective tool for antibody characterization, including epitope classification and antibody neutralization kinetics. From these studies, the potential contributions of the mutations (N501Y, E484K and K417N/T) contained in these variants’ RBDs on antibody pairing capability, neutralization activity and therapeutic antibody targeting strategy are discussed.

Thermal stresses belong to the leading factors that influence low-temperature cracking behavior of asphalt pavements. During winter, when temperature drops to significantly low values, tensile thermal stresses develop as a result of pavement contraction. Creep test methods can be suitable for the assessment of low-temperature properties of asphalt mixtures. To evaluate the influence of creep test methods on the obtained low-temperature properties of asphalt mixtures, three point bending and uniaxial tensile creep tests were applied and the master curves of stiffness modulus were analyzed. On the basis of creep test results, rheological parameters describing elastic and viscous properties of the asphalt mixtures were determined. Thermal stresses were calculated and compared to tensile strength of the material to obtain the failure temperature of the analyzed asphalt mixtures. It was noted that lower strain values of creep curves were obtained for the Tensile Creep Test (TCT) than for the Bending Beam Creep Test (BBCT), especially at lower temperatures. Results of thermal stress calculations indicated that higher reliability was obtained for the viscoelastic Monismith method based on the TCT results than for the simple quasi-elastic solution of Hills and Brien. The highest agreement with the TSRST results was also obtained for the Monismith method based on the TCT results. No clear relationships were noted between the predicted failure temperature and different methods of thermal stress calculations.

There is still a lack of a clinical test to reliably identify patients with Parkinson’s disease (PD) being at risk for aspiration. In this prospective, controlled, cross-sectional study we assessed if swallowing speed for water is a useful clinical test to predict aspiration proven by flexible endoscopic evaluation of swallowing (FEES). Due to this we measured the swallowing speed for 90 ml water in 115 consecutive and unselected PD outpatients of all clinical stages and 32 healthy controls. Average swallowing speed was lower in patients compared with controls (6.5 ± 3.9 ml/s vs. 8.5 ± 3.2 ml/s; p < 0.01). The disease-independent widely used threshold of < 10 ml/s showed insufficient sensitivity of 88% and specificity of 19% with unacceptable false-positive rates of 63% for patients and 69% for controls. Receiver operating characteristic (ROC) analysis was carried out to define a suitable cut-off value for detection of aspiration of water (area under the curve 0.72, p < 0.001) in PD patients. The optimized cut-off value was 5.5 ml/s with a sensitivity of 69% and a specificity of 64%. Overall, measuring swallowing speed is prone to methodological errors and not suitable as a screening instrument to predict aspiration in PD patients.

In this research paper, a hybrid Artificial Neural Network (ANN)-Fuzzy Logic Control (FLC) tuned Flower Pollination Algorithm (FPA) as a Maximum Power Point Tracker (MPPT) is employed to emend root mean square error (RMSE) of photovoltaic (PV) modeling. Moreover, Gaussian membership functions have been considered for fuzzy controller design. This paper interprets Luo converter occupied brushless DC motor (BLDC) directed PV water pump application. Experimental responses certify the effectiveness of the suggested motor-pump system supporting diverse operating states. Luo converter is newly developed dc-dc converter has high power density, better voltage gain transfer and superior output waveform and able to track optimal power from PV modules. For BLDC speed controlling there is no extra circuitry and phase current sensors are enforced for this scheme. The recentness of this attempt is adaptive neuro-fuzzy inference system (ANFIS)-FPA operated BLDC directed PV pump with advanced Luo converter has not been formerly conferred.

Abstract: The Inconel 625 is a nickel-based alloy has been widely used in the high-temperature application. The Inconel 625 exhibits unstable plastic flow at elevated temperature characterized by serrated yielding, known as Portevin-Le Chatelier effect. The aim of this work is to evaluate the mechanical properties at high temperatures of the Inconel 625. The tensile tests were performed in the temperature range of room temperature until 1000 °C and strain rate of 2x10^-4 to 2x10^-3 s^-1. The creep tests were performed in the temperature range of 600-700 °C, in the stress range of 500-600 MPa in a constant load mode. The surface fracture was observed by optical and scanning electron microscopy. Serrated stress-strain behavior was observed in the curves obtained at 200 to 700 °C, which was associated with the dynamic strain aging effect. The yield strength and the elongation values show an anomalous behavior as a function of the test temperature. An intergranular cracking was observed specimen tensile tested at 500 °C that can be attributed to the decohesion of the carbides along the grain boundaries. The fracture surface of the specimen tensile tested at 700 °C showed the predominance of transgranular cracking with tear dimples with a parabolic shape.

In this paper a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator. This new family of test statistics will be called Wald-type test statistics. The problem of testing a simple and a composite null hypothesis is considered and the robustness is studied on the basis of a simulation study. Previously, the composite minimum density power divergence estimator is introduced and its asymptotic properties are studied.

Most diagnostic tests for tuberculosis (TB) rely on sputum samples, which are difficult to obtain and have low sensitivity in immunocompromised patients, patients with disseminated TB, and children, delaying treatment initiation. The World Health Organization (WHO) calls for the development of a rapid, biomarker-based, non-sputum test capable of detecting all forms of TB at the point-of-care to enable immediate treatment initiation. Lipoarabinomannan (LAM) is the only WHO-endorsed TB biomarker which can be detected in urine, an easily collected sample. This review discusses the characteristics of LAM as a biomarker, describes the performance of first-generation urine LAM tests and reasons for slow uptake, and presents considerations for developing the next-generation of more sensitive and impactful tests. Next-generation urine LAM tests have the potential to reach adult and pediatric patients regardless of HIV status or site of infection and facilitate global TB control. Implementation and scale-up of existing LAM tests and development of next-generation assays should be prioritized.

Within the field of guilt and shame, two competing perspectives have been advanced. The first, the social-adaptive perspective, proposes that guilt is an inherently adaptive emotion and shame is an inherently maladaptive emotion; thus, those interested in moral character development and psychopathology should work to increase an individual’s guilt-proneness and decrease an individual’s shame-proneness. The functionalist perspective, in contrast, argues that both guilt and shame can serve a person adaptively or maladaptively—depending on the situational appropriateness, duration, intensity, and so forth. This paper reviews the research conducted supporting both positions, critiques some issues with the most widely used guilt- and shame-proneness measure in the social-adaptive research (the TOSCA), and discusses the differences in results found when assessing guilt and shame at the state versus trait level. The conclusion drawn is that although there is broad support for the functionalist perspective across a wide variety of state and trait guilt/shame studies, the functionalist perspective does not yet have the wealth of data supporting it that has been generated by the social-adaptive perspective using the TOSCA. Thus, before a dominant perspective can be identified, researchers need to (1) do more research assessing how the social-adaptive perspective compares to the functionalist perspective at the state level, and (2) do more trait research within the functionalist perspective to compare functionalist guilt- and shame-proneness measures with the TOSCA.

The present novel corona virus (2019-nCoV) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. The infection induced death rate is also very high. There is no vaccine or anti-viral medicine for such infection. So at this moment a major worldwide problem is that how we can control this pandemic. On the other hand, India is a high population density country, where the corona virus disease (COVID-19) has started to spread from $1^{st}$ week of March, 2020 in a significant number of COVID-19 positive cases. Due to this high population density human to human social contact rate is very high in India. So control of the pandemic COVID-19 in early stage is very urgent and challenging problem. Mathematical models are employed in this paper to study the COVID-19 dynamics, to identify the influential parameters and to find the proper prevention strategies to reduce the outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the key model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impacts on the disease dynamics have also been studied. Future trends of the disease transmission has been Predicted from our model with some control measures. Finally, the positive measures to control the disease have been summarized.

Strata and surface movement induced by mining under open-pit final slope is a huge threat to mine safety. Physical model test is an important method to study mining-induced strata and surface movement laws. Because of rock joints predominantly control rock mass deformation and failure, thus physical model test leaving out of consideration of rock joints is difficult to reflect the influence of rock joints on rock mass deformation. Therefore, this paper presents a three-dimensional physical model test considering simplified dominant rock joints. This test process includes the design of testing equipment, the construction of physical model with dominant rock joint sets, conduction of mining and deformation monitoring. And mining under eastern final slope of Yanqianshan iron mine was selected as a case to study the behavior of mining-induced strata and surface movement.

In this paper, an extensive study on the operation, control and performance of a hybrid photovoltaic and wind turbine (PV-WT) system is presented. The study includes the operation of the hybrid systems under different weather conditions which are reflected on a change in the wind speed and irradiance. Various loading conditions are investigated such a change in active and reactive power demands for static and dynamic loads. The performance of the hybrid system is examined via MATLAB/SIMULINK simulations.

Research on bidirectional human-machine interfaces will enable the smooth interaction with robotic platforms in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. We complement the gesture-based control by means of a tactile-feedback strategy grounding on a spiking artificial neuron model. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user’s hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.

Chronic diseases are still known as incurable diseases, and we suspect that the medical research model is unfit for characterizing chronic diseases. In this study, we examined accuracy and reliability required for characterizing chronic diseases, reviewed implied presumptions in clinical trials and assumptions used in statistical analysis, examined sources of variances normally encountered in clinical trials, and conducted numeric simulations by using hypothetical data for several theoretical and hypothetical models. We found that the sources of variances attributable to personal differences in clinical trials can distort hypothesis test outcomes, that clinical trials introduce too many errors and too much inaccuracies that tend to hide weak and slow effects of treatments, and that the means of treatments used in statistical analysis have little or no relevance to specific patients. We further found that a large number of uncontrolled co-causal or interfering factors normally seen in human subjects can greatly enlarge the means and the variances of the experimental errors, and the use of high rejection criteria (e.g., low p values) further raises the chances of failing to find treatment effects. As a whole, we concluded that the research model using clinical trials is wrong on multiple grounds, under any of our realistic theoretical and hypothetical models, and that misuse of statistical analysis is most probably responsible for failure to identify treatment effects for chronic diseases and to detect harmful effects of toxic substances in the environment. We proposed alternative experimental models involving the use of single-person or mini optimization trials for studying low-risk weak treatments.

Objective: To use mathematical models to predict the epidemiological impact of lifting the lockdown in London, UK, and alternative strategies to help inform policy in the UK. Methods: A mathematical model for the transmission of SARS-CoV2 in London. The model was parametrised using data on notified cases, deaths, contacts, and mobility to analyse the epidemic in the UK capital. We investigated the impact of multiple non pharmaceutical interventions (NPIs) and combinations of these measures on future incidence of COVID-19. Results: Immediate action at the early stages of an epidemic in the affected districts would have tackled spread. While an extended lockdown is highly effective, other measures such as shielding older populations, universal testing and facemasks can all potentially contribute to a reduction of infections and deaths. However, based on current evidence it seems unlikely they will be as effective as continued lockdown. In order to achieve elimination and lift lockdown within 5 months, the best strategy seems to be a combination of weekly universal testing, contact tracing and use of facemasks, with concurrent lockdown. This approach could potentially reduce deaths by 48% compared with continued lockdown alone. Conclusions: A combination of NPIs such as universal testing, contact tracing and mask use while under lockdown would be associated with least deaths and infections. This approach would require high uptake and sustained local effort but it is potentially feasible as may lead to elimination in a relatively short time scale.

The Baculoviridae, a family of insect-specific large DNA viruses, is widely used in both biotechnology and biological control. Its applied value stems from millions of years of evolution influenced by interactions with their hosts and the environment. To understand how ecological interactions, have shaped baculovirus diversification, we reconstructed a robust molecular phylogeny using 217 complete genomes and ~580 isolates for which at least one of four lepidopteran core genes was available. We then used a phylogenetic-concept-based approach (mPTP) to delimit 165 baculovirus species, including 38 species derived from new genetic data. Phylogenetic optimization of ecological characters revealed a general pattern of host conservatism punctuated by occasional shifts between closely related hosts and major shifts between lepidopteran superfamilies. Moreover, we found significant phylogenetic conservatism between baculoviruses and the type of plant growth (woody or herbaceous) associated with their insect hosts. In addition, we found that colonization of new ecological niches sometimes led to viral radiation. These macroevolutionary patterns show that besides selection during the infection process, baculovirus diversification was influenced by tritrophic interactions, explained by their persistence on plants and interactions in the midgut during horizontal transmission. This complete eco-evolutionary framework highlights the potential innovations that could still be harnessed from the diversity of baculoviruses.

This paper presents a new adaptive and optimal algorithm for the trajectory tracking control of a quadrotor using iterative learning algorithm (ILA) and enumerative learning algorithm. Ordinarily the ILA, as an adaptive method, can perform well with PID control to improve the controller’s performance for a nonlinear system. Quadrotors are considered as non-linear and unstable systems which the use of an adaptive and optimal controller can increase its stability and decrease error level. In this method, a PID controller is proposed for the outer and inner control loops of a quadrotor and the ILA is used to adapt PID control gains. Subsequently, an enumerative learning algorithm is used to optimize the learning rates of the ILA. For this purpose, at first, the dynamic model of the quadrotor is acquired. After that, the structure of the inner and outer control loops is defined. In the end, the simulation results for the trajectory tracking control of a quadrotor are demonstrated. Through simulation, it is concluded that as time increases, the performance of the suggested control method in trajectory tracking control becomes better and better and error signals convergence to zero.

Oriented strand board (OSB) panels are widely marketed for several applications, from building to packaging. The manufacturing of poplar OSB started recently in Northern Italy representing a relevant innovation in the sector since this product is usually made of coniferous wood. The thermal treatment is widely used for reducing the hygroscopicity of wood-based products, nonetheless it influences the mechanical behavior and degrades the main components of wood, which can affect their finishing. Therefore, it is important to know the properties of the treated surfaces. To this purpose, in this study a lot of OSB panels, made of poplar wood, 15 mm thick and with a density of 590 kg/m³, were thermally treated under vacuum conditions at 190 °C for 2 h and then subjected to accelerated weathering. The changes in color and in wettability due to treatment and accelerated weathering were studied. The thermal treatment determined a significant darkening of the color; the accelerated weathering darkened the untreated surfaces and, on the opposite, lightened the thermo-treated surfaces. The wettability decreased after thermal treatment and increased after weathering, more evidently in treated panels. Overall, this study improves the knowledge about the behavior of the surface of thermo-treated poplar OSB, which is relevant for the industrial coating of this product.

A cross-sectional study was carried out to determine the prevalence of subclinical mastitis (SCM) among medium to large scale household dairy farms in southwestern district, Jhenaidah, Bangladesh during July to December 2019. A total of 78 (n=100) lactating cows from household dairy farms (N=32) having three or more dairy cows were selected randomly as sampled populations. Milk samples were screened for SCM by using Surf Field Mastitis Test (SFMT). The prevalence of SCM varied among farm level [71.9% (95% CI: 53.3-86.3)], individual animal level [67.9% (95% CI: 56.4-86.3)] and quarter level [29.5% (95% CI: 24.5-34.9)]. Descriptive statistics represented the farmers and farm demography, characteristics of the sampled population, and overall management feature. Random Effect Logistic Regression identified, Body Condition Score (BCS) [OR=3.8 and 2.9, at cows level and quarter level respectively (BCS-2 vs. BCS-≥3)], and breed [OR=5.1 and 2.9, at cows level and quarter level respectively (HF× Sahiwal vs. HF × Local)] as potential risk factors. This study shows that SCM is highly prevalent in the study area, which is a major threat to the dairy industry's production performance. Regular screening by SFMT, proper hygiene, improve the management system, and farmer’s awareness is required to control the disease.

Shear connectors are used in steel beam–concrete slabs of composite frame and bridge structures to transfer shear force according to design loads. The existing Y-type perfobond rib shear connectors are designed for girder slabs of composite bridges. Therefore, the rib and transverse rebars of the conventional Y-type perfobond rib shear connectors are extremely large for the composite frames of building structures. We performed push-out tests of stubby Y-type perfobond rib shear connectors for composite frames. These shear connectors have relatively small ribs than conventional Y-type perfobond rib shear connectors. To confirm the shear resistance of these stubby shear connectors, we performed an experiment by using transverse rebars D13 and D16. The results indicate that these shear connectors have suitable shear strength and ductility for application in composite frame structures. The shear strengths obtained using D13 and D16 were not significantly different. However, the ductility of the shear connectors with D16 was 45.1% higher than that of the shear connectors with D13.

The role of vitamin D in the prevention and treatment of non-skeletal health issues has received significant media and research attention in recent years. Costs associated with clinical management of low vitamin D (LVD) have increased exponentially. However, no clear evidence supports vitamin D screening to improve health outcomes. Authoritative bodies and professional societies recommend against population-wide vitamin D screening in community-dwelling adults who are asymptomatic or at low risk of LVD. In order to assess patterns of physician management of LVD in this conflicting environment, we conducted a scoping review of three electronic databases and gray literature. Thirty-eight records met inclusion criteria and were summarized in an evidence table. Results from seven countries showed a consistent increase in vitamin D lab tests and related costs. Many vitamin D testing patterns reflected screening rather than targeted testing for individuals at high risk of vitamin D deficiency or insufficiency. Interventions aimed at managing inappropriate clinical practices related to LVD were effective in the short term. Variability and controversy were pervasive in many aspects of vitamin D management, shining light on physician practices in the face of uncertainty. Future research is needed is needed to inform better clinical guidelines and to assess implementation practices that encourage evidence-based management of LVD in adult populations.

Disposable absorbent hygiene products have evolved for superior performance, enhancing the convenience of daily lives. Yet the use of disposable hygiene pads has brought safety concerns on chemical exposure, and significant efforts have been made to assess the potential risks associated with use of hygiene pads. This article intends to overview the safety assessment framework of diapers and feminine pads, which includes hazard identification, hazard characterization, exposure assessment, risk characterization, and postmarket risk management. Risk assessment of various constituents are reviewed for quantification methods and conservative estimation of exposure parameters. By reviewing the up-to-date considerations in risk assessment, we aim to provide insightful discussion on safety evaluation of current versions of disposable absorbent products. More clinical testing and postmarket surveillance are needed for continuous monitoring of potential health impacts of advanced products and constituents.

The concept of using eye-tracking in virtual reality for education has been researched in various fields over the past years. With this review, we aim to discuss the recent advancements and applications in this area, explain the technological aspects, highlight the advantages of this approach and inspire interest in the field. Eye-tracking has already been used in science for many decades and now has been substantially reinforced by the addition of virtual and augmented reality technologies. The first part of the review is a general overview of eye-tracking concepts and its applications. In the second part, the focus shifted towards application of eye-tracking in virtual reality. The third part is the description of the recently emerged concept of eye-tracking in virtual reality when applied to education and studying, which has not been thoroughly described before. We describe the main findings, technological aspects and advantages of this approach.

We characterize the performance of a system based on a magnetoresistor array. This instrument is developed to map the magnetic field, and to track a dipolar magnetic source in the presence of a static homogeneous field. The position and orientation of the magnetic source with respect to the sensor frame is retrieved together with the orientation of the frame with respect to the environmental field. A nonlinear best-fit procedure is used, and its precision, time performance, and reliability are analyzed. This analysis is performed in view of the practical application for which the system is designed that is an eye-tracking diagnostics and rehabilitative tool for medical purposes, which require high speed ($\ge 100$~Sa/s) and sub-millimetric spatial resolution. A throughout investigation on the results makes it possible to list several observations, suggestions, and hints, which will be useful in the design of similar setups.

The prolonged lockdown imposed to contain the COVID-19 pandemic prevented many people from direct contact with nature and greenspaces, raising alarms for a possible worsening of mental health. This study investigates the effectiveness of a simple and affordable remedy for improving psychological well-being, based on audio-visual stimuli brought by a short computer video showing forest environments, with an urban video as a control. Randomly selected participants were assigned the forest or urban video, to look at and listen early in the morning, and filled questionnaires. In particular, the State-Trait Anxiety Inventory (STAI) Form Y, collected in baseline condition and at the end of the study, and the Part II of the Sheehan Patient Rated Anxiety Scale (SPRAS), collected every day immediately before and after watching the video. The virtual exposure to forest environments showed effective to reduce perceived anxiety levels in in people forced by lockdown in limited spaces and environmental deprivation. Although significant, the effects were observed only in the short term, highlighting the limitation of the virtual experiences. The reported effects might also represent a benchmark to disentangle the determinants of health effects due to real forest experiences, for example, the inhalation of biogenic volatile organic compounds (BVOC).

In this paper we describe many important aspects connected with lubricants, namely: the most cheapest organic lubricant in the word, how effectively save lubricant between pairs of friction, what kind of rational shapes for the lubricant must be, what it will be connected with wear and tear using the new organic lubricant (for this purpose formulas and curves are shown in computer program MathCad with calculation). Moreover, there is one physical model which helps to catch car exhausted gases. In conclusion, some recommendations will be given to realize them into the practice during the operation for the different mechanisms including ecology.

Rainfall variability has resulted in extreme events like devastating floods and droughts which is the main cause of human vulnerability to precipitation in West Africa. Attempts have been made by previous studies to understand rainfall variability over Ghana but these have mostly focused on the major rainy season of April-July, leaving a gap in our understanding of the variability in the September-November season which is a very important aspect of the Ghanaian climate system. The current study seeks to close this knowledge gap by employing statistical tools to quantify variabilities in rainfall amounts, rain days, and extreme precipitation indices in the minor rainfall season over Ghana. We find extremely high variability in rainfall with a Coefficient of variation (CV) between 25.3% and 70.8%, and moderate to high variability in rain days (CV=14.0% - 48.8%). Rainfall amount was found to be higher over the middle sector (262.7 mm – 400.2 mm) but lowest over the east coast (125.2 mm – 181.8 mm). Analysis of the second rainfall season using the Mankandell Test presents a non-significant trend of rainfall amount and extreme indices (R10, R20, R99p, and R99p) for many places in southern Ghana. Rainfall Anomaly Indices show that the middle sector recorded above normal precipitation which is the opposite for areas in the transition zone. The result of this work provides a good understanding of rainfall in the minor rainfall season and may be used for planning purposes.

Beach sand may act as a reservoir for numerous micro-organisms, including enteric pathogens. Several of these pathogens originate in human or animal feces, which may pose a public health risk. In August 2019, high levels of fecal indicator bacteria (FIB) were detected in the sand of the Azorean beach Prainha, Terceira Island, Portugal. Remediation measures were promptly implemented, including sand removal and the spraying of chlorine to restore the beach sand quality. To determine the biological source of the contamination, during the first campaign, supratidal sand samples were collected from several sites along the beach, followed by microbial source tracking (MST) analyses of Bacteroides markers for five animal species, including humans. Some of the sampling sites revealed the presence of marker genes from dogs, seagulls, and ruminants. Making use of the information on biological sources originating partially from dogs, the municipality enforced restrictive measures for dog-walking at the beach. Subsequent sampling campaigns detected low FIB contamination due to the mitigation and remediation measures that were undertaken, thereby no longer requiring MST marker-gene analysis. This is the first case study where the MST approach was used to determine the contamination sources in the supratidal sand of a coastal beach. Our results show that MST can be an essential approach to determine sources of fecal contamination in the sand. This study shows the importance of holistic management of beaches that should go beyond water quality monitoring for FIB, putting forth evidence for the need for sands also to be monitored.

The study focused on two climatic variables i.e. precipitation and stream flow for analysing change in trend of rainfall for the River Ssezibwa Catchment area and stream flow of River Ssezibwa. This Catchment is found in the districts of Mukono and Buikwe in Uganda. In this area agriculture is majorly dependent on rainfall and irrigation on a small scale. However, rainfall occurrence has become unpredictable over the past few years as result of the changes in patterns of weather. This has caused severe effects on the agricultural cropping system as well as caused negative effects on the natural water resources. Stream flow data of 57 years (1960 – 2017) and rainfall data for 35 years (1982 – 2017) on a daily basis was analysed to find out the trend and detect change point. Trend analysis was done by using the non-parametric analysis while the change point detection was carried out by using the Pettit test (1979).Magnitude of trend for the time series data was carried out using Sen’s Slope estimator and Mann – Kendall test was done to determine the trend. Results from the statistical analysis highlighted that; for stream flow the trend was generally positive and change point detected to be in the year 2000 while for rainfall data analysis indicated that the trend was predominantly negative and change point was in the year 1998.

Land Surface Temperature (LST) is a basic parameter in energy exchange between the land and atmosphere and is frequently used in many sciences such as climatology, hydrology, agriculture, ecology, etc. LST time series data have usually deficient, missing and unacceptable data caused by the presence of clouds in images, presence of dust in atmosphere and sensor failure. In this study, Singular Spectrum Analysis (SSA) algorithm was used to resolve the problem of missing and outlier data caused by cloud cover. The region studied in the present research included an image frame of MODIS with horizontal number 22 and vertical number 05 (h22v05). This image involved a large part of Iran and Turkmenistan and Caspian Sea. In this study, MODIS LST sensor (MOD11A1) was used during 2015 with 1×1 Km spatial resolution and day/night LST data (daily temporal resolution). The results of the data quality showed that cloud cover caused 36.37% of missing data in the studied time series with 730 day/night LST images. Further, the results of SSA algorithm in reconstruction of LST images indicated the Root Mean Square Error (RMSE) of 2.95 K between the original and reconstructed data in LST time series in the study region. In general, the findings showed that SSA algorithm using spatio-temporal interpolation in LST time series can be effectively used to resolve the problem of missing data caused by cloud cover.

Simultaneous measurement of different substances from a single sample is an emerging issue to achieve efficient and high-throughput detection in several fields of application. Although immunoanalytical techniques have well-established and prevailing advantages over alternative screening analytical platforms, one of the incoming challenges for immunoassay is exactly multiplexing. The Lateral Flow Immunoassay (LFIA) is a leading immunoanalytical technique for onsite analysis thanks to its simplicity, rapidity and cost-effectiveness. Moreover, LFIA architecture is adaptable to multiplexing and therefore candidates as a possible answer to the pressing demand of multiplexing point-of-need analysis. The review present an overview of diverse approaches for multiplex LFIA, with a special focus on strategies based on new types of magnetic, fluorescent and colored labels

Muon radiography is an imaging technique based on the measurement of the absorption of cosmic ray muons. This technique has recently been used successfully to investigate the presence of unknown cavities in the Bourbon Gallery in Naples and in the Cheops Pyramid at Cairo. The MIMA detector (Muon Imaging for Mining and Archaeology) is a muon tracker prototype for the application of muon radiography in the Archaeological and Mining fields. It is made of three couples of X-Y planes each consisting of 21 scintillator bars with silicon photomultiplier read-out. The detector is compact, robust, easily transportable and has a low power consumption: all of that makes the detector ideal for measurements in narrow and isolated environments. With this detector we have performed a measurement from inside the Temperino mine in the San Silvestro archaeo-mining park in Tuscany. The park includes about 25 km of mining tunnels arranged on several levels that have been excavated since the Etruscan time. The measured muon absorption was compared to the simulated one, obtained from the information provided by 3D laser scanner measurements and the cartographic maps of the mountain above the mine, in order to obtain information on the average density of the rock. This allowed to confirm the presence of a partially accessible exploitation opening and gave some hints on the presence of a high density body within the rock.

Natural calamities observation, study and simulation has always been a prime concern for disaster management agencies. Billions of dollars are spent annually to explore geo-seismic movements especially earthquakes but it has always been a unique accident. The real-time study of seismic waves, ground motions, and earthquakes always needed a programmable mechanical structure capable of physically producing the identical geo-seismic motions with seismology domain definitions. A programmable multi-parametric five degrees of freedom electromechanical seismic wave events simulation platform to study and experiment seismic waves and earthquakes realization in the form of geo-mechanic ground motions is exhibited in this work. The proposed platform was programmed and interfaced through an IoT cloud-based Web application. The geo-mechanics was tested in the range of i) frequencies of extreme seismic waves from 0.1Hz to 178Hz; ii) terrestrial inclinations from -10.000° to 10.000°; iii) velocities of 1km/s to 25km/s iv) variable arrival times 1us to 3000ms; v) magnitudes M1.0 to M10.0 earthquake; vi) epi-central and hypo-central distances of 290+ and 350+ kilometers. Wadati and triangulation methods have been used for entire platform dynamics design and implementation as one of key contributions in this work. This platform is as an enabler for a variety of applications such as training self-balancing and calibrating seismic-resistant designs and structures in addition to studying and testing seismic detection devices as well as motion detection sensors. Nevertheless, it serves as an adequate training colossus for machine learning algorithms and event management expert systems.

The ongoing pandemic of COVID-19 has not only commenced a global health emergency but agitated various aspects of humanity. During this period of crisis researchers over the world have ramped their efforts to constrain the disease in all possible ways whether it is vaccination, therapy, or diagnosis. Since the spread of the disease has not yet elapsed sharing the ongoing research findings could be the key to disease control and management. An early and efficient diagnosis could leverage the outcome until a successful vaccine is developed. Molecular tests both in-house and commercial kits are preferably being used worldwide in the COVID-19 diagnosis. However, the limitation of high prices and lengthy procedures impede their use for mass testing. Keeping the constant rise of infection in mind search for an alternative test that should be cost-effective, simple, and suitable for large scale testing and surveillance is a need of an hour. One such alternative could be the immunological tests. Therefore, in the last few months deluge of immunological rapid tests has been developed and validated across the globe. The objective of the present review is to share the diagnostic performance of various immunological assays reported so far in SARS-CoV-2 case detection. The article consolidated the studies (published and preprints) related to the serological tests such as chemiluminescence, enzyme-linked and lateral flow-based point-of-care tests in COVID-19 diagnosis and updated the current scenario. This review will hopefully be an add-on in COVID-19 research and will contribute to congregate the evidence for decision-making.

This research aims to estimate the micro-motion (m-m) of ships. The problem of motion and m-m detection of targets is usually solved using synthetic aperture radar (SAR) along-track interferometry (ATI) which is observed employing two radars spatially distanced by a baseline extended in the azimuth direction. This paper is proposing a new approach where the m-m estimation of ships, occupying thousands of pixels, is measured processing the information given by sub-pixel tracking generated during the coregistration process of several re-synthesized time-domain and overlapped sub-apertures. The SAR products are generated splitting the raw data, according to a small-temporal baseline strategy, observed by one single wide-band staring spotlight (ST) SAR image. The predominant vibrational modes of different ships are estimated and results are promising to extend this application in performing surveillance also of land-based industries activities. Experiments are performed processing one ST SAR image observed by the COSMO-SkyMed satellite system.

Background: Flow-through dot-blot assay (FT-DBA) for SARS-CoV-2 specific IgG detection will provide a reliable and affordable immunoassay for the rapid serosurveillance against COVID-19. Method: SARS-CoV-2 antigens were immobilized on nitrocellulose membrane to capture IgG immunoglobulins, which were then detected with AuNP anti-human IgG. A total of 181 samples were characterized with in-house and commercial immunoassay. The positive panel consisted of RT-PCR positive samples from patients with both <14 days and >14 days from the onset of symptoms, while the negative panel contained samples collected either from the pre-pandemic era dengue patients from healthy donors during the pandemic period. Results: In-house ELISA selected a total of 79 true seropositive and 100 seronegative samples. The sensitivity of samples with <14 days using FT-DBA was 94.7% which increased to 100% for samples >14 days. The overall detection sensitivity and specificity were 98.8% and 98%, respectively, whereas the overall PPV and NPV were 97.6% and 99%. Moreover, comparative analysis between ELISA and FT-DBA revealed clinical agreement of Cohen’s Kappa value of 0.944. Conclusion: The assay can confirm past SARS-CoV-2 infection with high accuracy within 2 minutes compared to ELISA. It can help track SARS-CoV-2 disease progression, population screening, and vaccination response.

This paper introduces an approach that chooses the fault detection by calculating probabilities using probability mass function (pmf) and cumulative distribution function (CDF). This work used a method for multiple stuck-at faults by producing a new test pattern in combinational circuits. We assumed that existence of all multiple faults is only because of one single component that is faulty. A complete test set can be created by all possible single stuck-at faults in a combinational circuit using some combination of gates. The test set generation fault detection method is applied on two different 3-bit input variable and 4-bit input variable circuits. The probability of error occurrence is calculated at both 3-bit and 4-bit input variable circuits. The resulting feature is used to obtain maximum error occurrence probability to detect faults by the logic used that the complexity of the circuit is inversely proportional to the fault occurrence probability. Then again, undetectability is directly proportional to the complexity of the circuit. Therefore, finest feasible circuit should have large input variable components with less complexity to reduce the fault occurrence probability.