Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine Learning-Based Resource Allocation in Satellite Networks Supporting Internet of Remote Things

Satellite networks have been regarded as a promising architecture for supporting the Internet of remote things (IoRT) due to their advantages of wide coverage and high communication capacity in remote areas, which further promotes the development of the satellites for IoRT networks (SIoRTNs). The effectiveness of multi-dimensional resource collaboration has significant impacts on the IoRT data downloading performance. However, the environment ’ s dynamics, e.g., channel conditions and solar infeed process, are unknown in practical scenarios, which poses daunting challenges in making efficient utilization of multi-dimensional resources. Motivated by this fact, we model the joint resource scheduling and IoRT data scheduling problem with the aim of maximizing the amount of the IoRT data of the overall network by applying the model-free reinforcement learning framework. To overcome the limitations of traditional reinforcement learning algorithms, we propose several feature functions by investigating the natural attributes of the multi-dimensional resources of the SIoRTNs, and further exploit the concept of function approximation to approximate the expected downloaded IoRT data given the network state. Furthermore, we propose a state-action-reward-state-action (SARSA) based actor-critic reinforcement learning (SACRL) resource allocation strategy to achieve the optimal resource allocation and IoRT data scheduling with casual information at LEO satellites. Simulations validate the convergence property and the effectiveness of the proposed SACRL algorithm in terms of the amount of the downloaded IoRT data. Particularly, we investigate the impact of typical network parameters on network performance to further provide guidance for future SIoRTN system design.
Mood and Aﬀective Balance of Spaniards Conﬁned by COVID-19: A Cross-Sectional Study

Abstract. The aim of this study was to analyze the mood and aﬀective balance of Spaniards in quarantine and determine the predictive role of sociodemographic variables and mood on the negative aﬀective balance. This cross-sectional study was carried out with a sample of 1014 Spanish adults, 67.2% were women and 32.8% men. The age ranged from 17 to 76. The instruments used were the Mood Assessment Scale and the Aﬀective Balance Scale, which were implemented as a CAWI survey (Computer Aided Web Interviewing). Results showed that age correlated negatively with Sadness-Depression, Anxiety, and Happiness. Women had more Sadness-Depression, Anxiety, and negative aﬀect, while men showed more Happiness and higher positive aﬀect. Thus, the risk of a negative aﬀective balance during conﬁnement was greater for women and those who showed an emotional state marked by sadness-depression and anxiety, while older age and higher scores in happiness were associated with lower risk. In conclusion, knowing which groups are at risk of emotional and aﬀective alteration can facilitate the detection and prevention of later disorders, such as severe stress and posttraumatic stress disorder, avoiding their generalized presence, and becoming a new public health problem derived from COVID-19.
Properties of 2-locus genealogies and linkage disequilibrium in temporally structured samples

Archaeogenetics has been revolutionary, revealing insights into demographic history and recent positive selection in many organisms. However, most studies to date have ignored the non-random association of genetic variants at different loci (i.e., linkage disequilibrium, LD). This may be in part because basic properties of LD in samples from different times are still not well understood. Here, we derive several results for summary statistics of haplotypic variation under a model with time-stratified sampling: 1) The correlation between the number of pairwise differences observed between time-staggered samples (πΔt) in models with and without strict population continuity; 2) The product of the LD coefficient, D, between ancient and modern samples, which is a measure of haplotypic similarity between modern and ancient samples; and 3) The expected switch rate in the Li and Stephens haplotype copying model. The latter has implications for genotype imputation and phasing in ancient samples with modern reference panels. Overall, these results provide a characterization of how haplotype patterns are affected by sample age, recombination rates, and population sizes. We expect these results will help guide the interpretation and analysis of haplotype data from ancient and modern samples.
Enumerating x86-64 – It’s Not as Easy as Counting

In our work for software watermarking, we have been examining the possibility of executable steganography, hiding intel/AMD x86-64 instructions within the operands of other instructions. Early thoughts about this concept revolved around creating a database of sorts to reflect which x86-64 instructions had large enough operand fields to hold the hidden payload. It was assumed that this database would be easily constructed, but it turns out to be a surprisingly difficult endeavor. Even the question of “how many are there? ” is challenging to answer. Different CPUs support different instruction sets, different instruction decoders or reverse assemblers give different results for the same combination of bytes, and even the number of distinct mnemonics for instructions is blurry. In the process of attempting to construct the x86-64 database we encountered several stumbling blocks along the way and we report on the stumbling blocks here. This white paper is not a traditional research paper, with background, other relevant prior work. Rather, it describes our attempts to answer what we thought was a fairly simple question: for various numbers of bytes, just how many legal x86-64 instructions exist?
Modeling Phytoplankton Blooms and Inorganic Carbon Responses to Sea‐Ice Variability in the West Antarctic Peninsula

The ocean coastal‐shelf‐slope ecosystem west of the Antarctic Peninsula (WAP) is a biologically productive region that could potentially act as a large sink of atmospheric carbon dioxide. The duration of the sea‐ice season in the WAP shows large interannual variability. However, quantifying the mechanisms by which sea ice impacts biological productivity and surface dissolved inorganic carbon (DIC) remains a challenge due to the lack of data early in the phytoplankton growth season. In this study, we implemented a circulation, sea‐ice, and biogeochemistry model (MITgcm‐REcoM2) to study the effect of sea ice on phytoplankton blooms and surface DIC. Results were compared with satellite sea‐ice and ocean color, and research ship surveys from the Palmer Long‐Term Ecological Research (LTER) program. The simulations suggest that the annual sea‐ice cycle has an important role in the seasonal DIC drawdown. In years of early sea‐ice retreat, there is a longer growth season leading to larger seasonally integrated net primary production (NPP). Part of the biological uptake of DIC by phytoplankton, however, is counteracted by increased oceanic uptake of atmospheric CO2. Despite lower seasonal NPP, years of late sea‐ice retreat show larger DIC drawdown, attributed to lower air‐sea CO2 fluxes and increased dilution by sea‐ice melt. The role of dissolved iron and iron limitation on WAP phytoplankton also remains a challenge due to the lack of data. The model results suggest sediments and glacial meltwater are the main sources in the coastal and shelf regions, with sediments being more influential in the northern coast.
The Environment and Climate Change Canada Carbon Assimilation System (EC-CAS v1.0): demonstration with simulated CO observations

Abstract. In this study, we present the development of a new coupled weather and carbon monoxide (CO) data assimilation system based on the Environment and Climate Change Canada (ECCC) operational ensemble Kalman filter (EnKF). The estimated meteorological state is augmented to include CO. Variable localization is used to prevent the direct update of meteorology by the observations of the constituents and vice versa. Physical localization is used to damp spurious analysis increments far from a given observation. Perturbed surface flux fields are used to account for the uncertainty in CO due to errors in the surface fluxes. The system is demonstrated for the estimation of three-dimensional CO states using simulated observations from a variety of networks. First, a hypothetically dense, uniformly distributed observation network is used to demonstrate that the system is working. More realistic observation networks, based on surface hourly observations, and space-based observations provide a demonstration of the complementarity of the different networks and further confirm the reasonable behavior of the coupled assimilation system. Having demonstrated the ability to estimate CO distributions, this system will be extended to estimate surface fluxes in the future.
The effect of autoantibody against M2-muscarinic acetylcholine receptor in peripartum cardiomyopathy patients on digoxin additional to standard treatment

Background: To evaluate the effects of autoantibodies against the M2-muscarinic receptor (anti-M2-R) on digoxin additional to standard treatment in peripartum cardiomyopathy (PPCM) patients.Methods: 86 PPCM patients were separated into anti-M2-R negative or positive group according to the anti-M2-R reactivity. All the patients received digoxin additional to standard treatment regimen. Echocardiography was performed at baseline and after 5 years treatment. Serum digoxin concentration (SDC) were performed every 3 to 6 months. All-cause mortality, cardiovascular mortality and re-hospitalization for heart failure were compared after 5 years of follow-up.Results: There were 82 patients completed the final data analysis, including 38 in the anti-M2-R (+) group and 44 in the anti-M2-R (-) group. The heart rate of the positive group was higher than that of the negative group at baseline (102.3 ± 6.3 vs. 95.9 ± 6.8, p < 0.001). The initial SDC of patients in the positive group was higher than that of patients in the negative group with the same dose of digoxin (1.21 ± 0.41 vs. 0.73 ± 0.16 ng/mL, p < 0.001). Patients in the anti-M2-R (-) group had better tolerance to metoprolol and digoxin (p < 0.05). All the PPCM patients showed prominent improvement in cardiac function, especially in the anti-M2-R (-) group. Re-hospitalization for heart failure was decreased in the negative group, but not of all-cause or cardiovascular mortality. Conclusions: Patients negative for anti-M2-R showed better tolerance to metoprolol and digoxin. Anti-M2-R maybe a predictor for vagus nerve overactivation and is associated with poor response to digoxin treatment in PPCM patients.
Development of Problem-Oriented Mathematics Learning Videos on Scale Material for the Fifth-Grade Elementary School Students

This research was conducted based on an analysis of the needs and problems that occur in the learning process. The occurrence of the Covid-19 pandemic made learning less than optimal so that students had difficulty in understanding the teaching materials. To optimize mathematics learning, it is necessary to develop learning media according to the needs of students. This research aimed to produce problem-oriented mathematics learning videos on scale material for the fifth-grade students at Public Elementary School No. 2 Ketewel, and to find out its validity. The type of research is a development research using the ADDIE model (Analyze, Design, Development, Implementation, Evaluation). The subjects of this study were subject content experts, instructional design experts, instructional media experts, and three fifth-grade elementary school students. The data collection instrument used was a questionnaire. The research data were collected using the method of observation, interviews and questionnaires. Data were analyzed using quantitative descriptive analysis and qualitative descriptive analysis. The results of this study indicated the process of developing problem-oriented mathematics learning videos on scale material for the fifth-grade elementary school students through the analysis, design, development, and evaluation stages. The results of the validity test of the instructional videos by instructional design experts obtained a percentage score of 85.41% with good qualifications. The results of the validity test of the instructional videos by instructional media experts obtained a percentage score of 85% with good qualifications. The results of the validity test of the instructional videos by subject content experts obtained a percentage score of 87.5% with good qualifications. The results of the validity test of the instructional video by individual trial subjects obtained a percentage score of 95.66% with very good qualifications. Therefore, the problem-oriented mathematics learning on scale material for the fifth-grade elementary school students is valid for use in the learning
Enhancement of water and organic solvent resistances of a waterborne polyurethane film by incorporating liquid polysulfide

Environmentally friendly, waterborne polysulfide-based polyurethane (WSPU) films have been successfully synthesized from liquid polysulfide (PSF), polytetramethylene ether glycol (PTMG), isophorone diisocyanate (IPDI) and dimethylolpropionic acid (DMPA). The chemical structures, mechanical and thermal properties of the chemically modified films have been carefully investigated using ATR-IR, gel permeation chromatography (GPC), tensile tests, dynamic mechanical analysis (DMA) and a thermogravimetric analyzer (TGA). As the PSF content increases from 0 to 20%, after an immersion in deionized water for 96 h, the water absorption decreases from 6.2% to 3.4% and the tensile strength retention increases from 74.3% to 91.7%. The chemical resistance to organic solvents is also improved significantly. The enhanced water and organic solvent resistances of waterborne polyurethanes (WPUs) are primarily attributed to the addition of a PSF containing sulfur group. However, the tensile strength and thermal performance are weakened to some extent. This study produces a new composite derived from polysulfide, and its high water and solvent resistance performance could contribute to surface material research.
Translation and Validation of Adolescents’ Self-Concept Short Scale

Adolescents’ Self-Concept Short Scale (Veiga& Leite, 2016) was devised to measure self-concept among adolescents. Present study was aimed to translate the scale into Urdu language and validate the underlying factors among adolescents of Pakistan. It comprised of three main phases. Phase-I underlies the translation through forward-back translation method, followed by the cross-language validation study. The translated and the original version were administered on bilingual secondary school students (N=100) and reliability was estimated that ranges from . 39 to . 71 for translated version. Phase-II aimed to establish the construct validity by using Exploratory Factor Analysis on adolescent students (N=150) with age range of 13 to 16 years (M=14.53; SD=1.02). Results showed four main factors, instead of six factors of original scale. Finally, Phase-III of the research aimed to confirm the factorial validity through Confirmatory Factor Analysis (CFA) on sample of secondary school adolescent students (N=300) age ranges from 13 to 18 years (M= 15.46; SD=1.23). Findings thus suggested that Adolescents’ Self-Concept Short Scale - Urdu version can be utilized as a valid and reliable measure for the assessment of self-concept among adolescent students with understandability of Urdu language.
An algorithm for characterizing skin moles using image processing and machine learning

Melanoma, the most serious type of skin cancer, forms in cells (melanocytes) that produce melanin, the pigment that gives color to the skin. There are low-income regions that lack specialized dermatologists, causing skin cancer to be diagnosed in advanced stages. In Peru, in high Andean communities with low resources, the problem is aggravated by the high incidence of ultraviolet radiation and lack of medical resources to make the diagnosis. Normally, mole images are obtained from dermatoscopes. The present work seeks to use mole images obtained from smartphones to make the classification of them as suspected or not suspected of being melanoma, by means of a feature extraction algorithm. The first step is to make color and lighting corrections. After this, the image is segmented using the K-Means algorithm, and we obtain the areas of the mole and skin. With the segmented mole we proceed to extract the main visual characteristics and then use classification algorithms such as support vector machine (SVM), random forest and naive bayes, which obtained an accuracy of 0.9473, 0.7368 and 0.6842, respectively. These results show that it is possible to use images obtained from smartphones to develop a classification algorithm with 94.73% accuracy to detect melanoma in skin moles.
Time series activity classification using gated recurrent units

The population of elderly is growing and is projected to outnumber the youth in the future. Many researches on elderly assisted living technology were carried out. One of the focus areas is activity monitoring of the elderly. AReM dataset is a time series activity recognition dataset for seven different types of activities, which are bending 1, bending 2, cycling, lying, sitting, standing and walking. In the original paper, the author used a many-to-many Recurrent Neural Network for activity recognition. Here, we introduced a time series classification method where Gated Recurrent Units with many-to-one architecture were used for activity classification. The experimental results obtained showed an excellent accuracy of 97.14%.
Grape Yield and Quality Response to Cover Crops and Amendments in a Vineyard in Nova Scotia, Canada

The increasing cost of synthetic fertilizers, combined with their associated environmental impacts and yield instability, has promoted the use of local waste products and cover crops in vineyards. We assessed the effects of cover crop mixtures combined with organic and industrial wastes on grape yield and quality over two full growing seasons in a vineyard (Vitis vinifera) in Eastern Canada. The experimental treatments were arranged in a nested design with three replicates. Four cover crop mixtures: (i) oats + pea + hairy vetch (OPV), (ii) oats mixed with red clover (ORCl), (iii) timothy + alsike + red clover (TM), and (iv) control with no cover crop (CONT) were applied to main plots and five fertility treatments (fertilizer without N [NDEF], full synthetic fertilizer [FERT], wood ash [WA], municipal solid food waste [MSFW], and mussel sediment [MS]) were applied to subplots. During the second growing season, only half of the subplots received fertility treatments. Grape yield for the most productive cover crop and amendment combinations were ORCl × MS (9.52 mg/ha) > OPV × MSFW (9.49 mg/ha) > TM × WA (8.81 mg/ha) > ORCl × MSFW (8.28 mg/ha). The lowest grape yields were obtained with combinations of CONT with either NDEF (3.86 mg/ha) or WA (3.61 mg/ha). The highest berry sugar concentrations among the cover crops were obtained under TM floor management combined with NDEF (16.43 Brix), MS (16.03 Brix), and MSFW (15.98 Brix). Grape yield was affected by cover crop only during the second growing season, but berry sugar was not. Cover crop floor management strategies and organic or industrial wastes can be used as sources of nutrients or soil conditioners for vineyards in the cool humid climate of Eastern Canada.
Graphene-Based Plasmonic Absorber for Biosensing Applications Using Gold Split Ring Resonator Metasurfaces

We propose a novel graphene-based metasurface plasmonic biosensor. The gold split-ring resonator is used as a metasurface element in the biosensor. Split Ring Resonator structures are used to localize and increase electromagnetic field incidents. Two types of split-ring resonator based metasurface (Single split-ring resonator and Double split-ring resonator) designs are analyzed to observe its effect on biosensing. The proposed biosensor is used to sense hemoglobin and urine biomolecules for their different concentrations. The design results in the form of absorption, electric field, and magnetic field are presented. The sensitivity for hemoglobin biomolecules and urine biomolecules are calculated from their absorption peak difference and refractive index difference. The sensitivity results are compared with previously published designs. The proposed single split ring resonator metasurface design has the highest sensitivity for hemoglobin-urine concentrations. The proposed biosensor can become a building block for future medical biosensing devices.
HIGH RISK OF POSTPARTUM HAEMORRHAGE AT BOUAKÉ UNIVERSITY HOSPITAL (NORTH-CENTRAL CÔTE D’IVOIRE)

Objectives. Postpartum haemorrhage is one of several direct causes of maternal death in Côte d’Ivoire. It is recurrent in the department of gynaecology and obstetrics at Bouaké University Hospital (CHU de Bouaké), but little is known to date about the underlying risk factors. The present study aims to describe the levels and trends displayed by the risk factors of postpartum haemorrhage before determining the contributing social factors in the aforesaid department. Material and methods. This study is retrospective in nature, concerning the period from 2014 to 2016. Data was obtained from delivery records and through individual interviews. The overall approach adopted is an anthropological one. Results. Postpartum haemorrhage is significant in light of its very high and increasing incidence (22.31%) among multiparous mothers. Within the latter category, fatal complications are a critical problem, with an annual average estimated at 35.98% and on the rise. The overall situation is alarming in view of this progressive deterioration. The persistence of the reproductive morbidity is attributable to various economic, social, cultural, and infrastructural factors. Conclusions. Communicational strategies are proposed as a type of community intervention conducive to social and behavioural change, with multiparous mothers as a priority target group, followed by older mothers in the medium term and by adolescent mothers in the long term. This should raise awareness about high-risk reproductive behaviours and practices as well as the environmental, economic, social, cultural, and infrastructural factors correlated to postpartum haemorrhage, with the ultimate goal of improving the quality and safety of reproductive practices. Keywords: postpartum haemorrhage, reproductive behaviour, high risk, obstetric emergency, maternal morbidity, Côte d’Ivoire.
Help through demonstration and automation for interactive computing systems: A survey of recent works

Usability is very important however, it is still difficult to develop interactive computing systems that meet all user’s specificities. Help systems should be a way of bridging this gap. This paper presents a general survey on recent works (building upon previous surveys) related to improving applications’ help through demonstration and automation and, identifies which technologies are acting as enablers. The main contributions are, identifying (i) which are the recent existing solutions; (ii) which aspects must be investigated further; and (iii) which are the main difficulties that are preventing a faster progress.