Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning

Telemetric information is great in size, requiring extra room and transmission time. There is a significant obstruction of storing or sending telemetric information. Lossless data compression (LDC) algorithms have evolved to process telemetric data effectively and efficiently with a high compression ratio and a short processing time. Telemetric information can be packed to control the extra room and association data transmission. In spite of the fact that different examinations on the pressure of telemetric information have been conducted, the idea of telemetric information makes pressure incredibly troublesome. The purpose of this study is to offer a subsampled and balanced recurrent neural lossless data compression (SB-RNLDC) approach for increasing the compression rate while decreasing the compression time. This is accomplished through the development of two models: one for subsampled averaged telemetry data preprocessing and another for BRN-LDC. Subsampling and averaging are conducted at the preprocessing stage using an adjustable sampling factor. A balanced compression interval (BCI) is used to encode the data depending on the probability measurement during the LDC stage. The aim of this research work is to compare differential compression techniques directly. The final output demonstrates that the balancing-based LDC can reduce compression time and finally improve dependability. The final experimental results show that the model proposed can enhance the computing capabilities in data compression compared to the existing methodologies.

Uptake of Screening Mammogram in West-central Illinois During COVID-19 Pandemic: Lessons Learned

Objectives. The study aims to reveal the trend of mammogram uptake in seventeen rural counties in Illinois to understand how the COVID-19 pandemic is influencing breast cancer screening in the area.Methods. Aggregated data on mammography screening for west central Illinois was provided by the Illinois Hospital Association. Data for 2018 and 2019 was used to determine the typical monthly and annual screenings for the two years before the onset of COVID-19. Then, the two years' data was compared to the 2020 data. The monthly mean values for the aggregated 2018 and 2019 data were generated as the base "year" to compare with the monthly value for 2020. Paired T-Test analysis was used to find if there were any statistically significant differences the years and between the base year and 2020.Results. January 2020 revealed an uptick to 2,921, which is more than the uptake for January 2018 (2700) and January 2019 (2488), and 13% greater than the mean value of 2,594 for the previous two years. This was followed by a gradual decrease in uptake in February 2020 by 4% compared to previous years at a mean of 2518 and a further decline in March (44%), with a drastic fall (98%) by April 2020 at 56 screening mammograms in all 17 counties. The lowest uptake in any three months occurred from March through May 2020. Compared to previous years, increase in uptake was noted across the region in 2020 June (8%) and July (4%) after the pandemic restrictions were relaxed. Overall, the total uptake in 2020 was 15% less than the average annual uptake for 2018-2019 with a deficit of 5,537. There was no statistically significant difference in mammogram uptake across the three years.Conclusion. The findings reveal that there was a significant reduction in uptake during the pandemic restriction period. However, increased uptake during the rest of the year effectively mitigated this reduction to such an extent that there was no statistically significant downturn compared to each of the previous two years. A rising trend in total annual uptake noted in preceding years could have continued without the COVID-19 event.

Mammal virus diversity estimates are unstable due to accelerating discovery effort

Host-virus association data underpin research into the distribution and eco-evolutionary correlates of viral diversity and zoonotic risk across host species. However, current knowledge of the wildlife virome is inherently constrained by historical discovery effort, and there are concerns that the reliability of ecological inference from host-virus data may be undermined by taxonomic and geographical sampling biases. Here, we evaluate whether current estimates of host-level viral diversity in wild mammals are stable enough to be considered biologically meaningful, by analysing a comprehensive dataset of discovery dates of 6571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are either constant or accelerating, with little evidence of declines towards viral richness asymptotes, even in highly sampled hosts. Consequently, inference of relative viral richness across host species has been unstable over time, particularly in bats, where intensified surveillance since the early 2000s caused a rapid rearrangement of species' ranked viral richness. Our results illustrate that comparative inference of host-level virus diversity across mammals is highly sensitive to even short-term changes in sampling effort. We advise caution to avoid overinterpreting patterns in current data, since it is feasible that an analysis conducted today could draw quite different conclusions than one conducted only a decade ago.

The comparison between cyber extension and traditional interaction in the farmers environment during pandemic

Data from the Indonesian Seed and Farmers Technology Association data shows that 22 percent of Indonesian farmers have used smartphones to obtain agricultural information. But many farmers still struggle to get information especially in the pandemic era. This research is to find out how the comparison of information delivery patterns between traditional media and cyber media on farmers in Bangil. Indonesia. This research theory uses the theory of cyber extensions. This research method by, observe online media, interviewing several farmers in Bangil and supported by survey data to 85 farmers in Bangil. The results showed that although cyber media began to enter as one of the sources of information for farmers, only a few were dependent on online, while the rest still relied on information from extension methods. Counselling still needed as a connection between farmers and Internet.

Protective effects of HLA-DRB1*04 subtypes in Parkinson's and Alzheimer's diseases implicate acetylated Tau PHF6 sequences

Using genome-wide association data, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson's (PD) or Alzheimer's (AD) disease versus controls across ancestry groups. A shared genetic association was observed across diseases at rs601945 (PD: odds ratio (OR)=0.84; 95% confidence interval, [0.80; 0.88]; p=2.2x10-13; AD: OR=0.91[0.89; 0.93]; p=1.8x10-22), and with a protective HLA association recently reported in amyotrophic lateral sclerosis (ALS). Hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03, and absent for HLA-DRB1*04:05. The same signal was associated with decreased neurofibrillary tangles (but not neuritic plaque density) in postmortem brain and was more strongly associated with Tau levels than Aβ42 levels in the cerebrospinal fluid. Finally, protective HLA-DRB1*04 subtypes strongly bound aggregation-prone Tau PHF6 sequence, but only when acetylated at K311, a modification central to aggregation. A HLA-DRB1*04-mediated adaptive immune response, potentially against Tau, decreases PD, AD and ALS risk, offering the possibility of new therapeutic avenues.

Crossmodal Correspondence Between Auditory Timbre and Visual Shape

Crossmodal correspondences are defined as associations between crossmodal stimuli based on seemingly irrelevant stimulus features (i.e., bright shapes being associated with high-pitched sounds). There is a large body of research describing auditory crossmodal correspondences involving pitch and volume, but not so much involving auditory timbre, the character or quality of a sound. Adeli and colleagues (2014, Front. Hum. Neurosci. 8, 352) found evidence of correspondences between timbre and visual shape. The present study aimed to replicate Adeli et al.’s findings, as well as identify novel timbre–shape correspondences. Participants were tested using two computerized tasks: an association task, which involved matching shapes to presented sounds based on best perceived fit, and a semantic task, which involved rating shapes and sounds on a number of scales. The analysis of association matches reveals nonrandom selection, with certain stimulus pairs being selected at a much higher frequency. The harsh/jagged and smooth/soft correspondences observed by Adeli et al. were found to be associated with a high level of consistency. Additionally, high matching frequency of sounds with unstudied timbre characteristics suggests the existence of novel correspondences. Finally, the ability of the semantic task to supplement existing crossmodal correspondence assessments was demonstrated. Convergent analysis of the semantic and association data demonstrates that the two datasets are significantly correlated (−0.36) meaning stimulus pairs associated with a high level of consensus were more likely to hold similar perceived meaning. The results of this study are discussed in both theoretical and applied contexts.

Spatio-Temporal Graph Attention Embedding for Joint Crowd Flow and Transition Predictions

Crowd mobility prediction, in particular, forecasting flows at and transitions across different locations, is essential for crowd analytics and management in spacious environments featured with large gathering. We propose GAEFT, a novel crowd mobility analytics system based on the multi-task graph attention neural network to forecast crowd flows (inflows/outflows) and transitions. Specifically, we leverage the collective and sanitized campus Wi-Fi association data provided by our university information technology service and conduct a relatable case study. Our comprehensive data analysis reveals the important challenges of sparsity and skewness, as well as the complex spatio-temporal variations within the crowd mobility data. Therefore, we design a novel spatio-temporal clustering method to group Wi-Fi access points (APs) with similar transition features, and obtain more regular mobility features for model inputs. We then propose an attention-based graph embedding design to capture the correlations among the crowd flows and transitions, and jointly predict the AP-level flows as well as transitions across buildings and clusters through a multi-task formulation. Extensive experimental studies using more than 28 million association records collected during 2020-2021 academic year validate the excellent accuracy of GAEFT in forecasting dynamic and complex crowd mobility.

Effects of Inter-Parental Conflict on Children’s Social Well-Being and the Mediation Role of Parenting Behavior

Inter-parental conflicts can have devastating effects on children’s well-being and social behavior. This study explores the association between an increased frequency of inter-parental conflict and peer problems and prosocial behavior in children, and whether parents’ emotional warmth and negative communication with their children mediates this association. Data for a total of 1,157 children between the ages of 7 and 16 (4,016 observations) was drawn from the eighth to the twelfth waves of the German Family Panel so as to perform fixed-effects regressions and mediation analyses. The analyses reveal that increased inter-parental conflict is strongly related to decreased emotional warmth and increased negative communication in parents, and to increased peer problems and decreased prosocial behavior in children. The results also suggest that the association between inter-parental conflict and children’s social well-being is mediated by the parenting behavior of mothers and fathers, indicating that increased inter-parental conflict leads to less warm parenting and more negative communication in parents, which ultimately reduces children’s social well-being.

Flexibility in the social structure of male chimpanzees (Pan troglodytes schweinfurthii) in the Budongo Forest, Uganda

ABSTRACTIndividuals of social species face a trade-off between the competitive costs and social benefits of group living. Species show a range of social strategies to deal with this trade-off, for example atomistic fission-fusion dynamics in which temporary social groups of varying size and membership form and re-form; or molecular fission-fusion dynamics which contain stable sets of multilevel nested subgroups. Chimpanzees are considered an archetypical atomistic fission-fusion species, using dynamic changes in day-to-day association to moderate the costs of within-group competition. It has been argued that humans’ highly flexible social organisation allows us to live in extremely large groups. Using four years of association data from two neighbouring communities of East African chimpanzees (Pan troglodytes schweinfurthii), we describe new levels of flexibility in chimpanzee social organisation and confirm the presence of subgrouping in a second, large community of chimpanzees. We show that males from the larger Waibira community (N males 24-31) exhibited additional levels of semi-stable subgrouping, while males from the smaller Sonso community (N males 10-13) did not. Subgroup membership showed stability across some years, but flexibility across others. Our data support the hypothesis that chimpanzees can incorporate strategies other than fission-fusion to overcome costs of social living, and that their social organisation may be closer to that of modern humans than previously described.SIGNIFICANCE STATEMENTSocial living offers benefits and costs; groups can more easily locate and defend resources, but experience increased individual competition. Many species, or individuals, flexibly adjust their social organization when faced with different competitive pressures. It is argued that humans are unique among primates in combining multigroup social organisation with fission-fusion dynamics flexibly within and across groups, and that doing so allows us to live in extremely large groups. Using four-years of association data we show new levels of flexibility in chimpanzee social organization. Males from a typically-sized community employed atomistic fission-fusion dynamics, but males in an unusually large community incorporated additional semi-stable levels of subgrouping. Our data support the hypothesis that chimpanzee males combine social organization strategies, and that doing so may allow them, like humans, to mitigate individual costs at larger community sizes.

Associations Between Comorbidity and Depressive Symptoms During COVID-19: Variation by Social Isolation?

Adults with comorbidities are at high COVID-19 risk and may experience elevated depressive symptoms during the pandemic. We aimed to investigate the associations between comorbidity at pandemic onset and subsequent depressive symptoms and whether social isolation modified this association. Data were from monthly online questionnaires in the COVID-19 Coping Study of US adults aged ≥55 from April/May-September/October 2020 (n=4,383). Depressive symptoms were measured by the 8-item CES-D, and social isolation as “high” vs. “low” based on contact with family, friends, social organizations, and living alone. In multivariable mixed-effects models, comorbidity (≥2 vs. <2 chronic conditions) was associated with greater depressive symptoms at baseline (β=0.50; 95% CI: 0.36-0.64), this association varied negligibly by social isolation. Differences in depressive symptoms by comorbidity status at pandemic onset were consistent over the six-month follow-up. This study indicates that middle-aged and older US adults with comorbidities experienced persistently elevated depressive symptoms during the COVID-19 pandemic.