Miracle-dz/UniFAR-FTUs huggingface dataset:
An Experimental Framework for Wellness Assessment Using the Internet of Things

Everyday wellness assessment is a promising step toward improving the health status of an individual. This article presents an experimental framework to address the growing concern of individual wellness using the advantages of the Internet of Things (IoT). The introduced framework uses an IoT device to read data from five environmental variables and a smartphone application to examine any correlation between environmental parameters and wellness. Ambient temperature, barometric pressure, humidity, luminosity, and audio amplitude data from a mobile IoT device are collected while the user answers three psychological surveys, regarding sleep quality, stress, and distress. The data are forwarded to a server to examine any potential correlation. The feasibility of the framework is examined through experimentation. An experiment with 20 participants is conducted. According to experimental results, parameters such as the luminosity and ambient audio have an effect on individual well being.
Biorefinery perspectives of microbial electrolysis cells (MECs) for hydrogen and valuable chemicals production through wastewater treatment

The degradation of waste organics through microbial electrolysis cell (MEC) generates hydrogen (H2) gas in an economically efficient way. MEC is known as the advanced concept of the microbial fuel cell (MFC) but requires a minor amount of supplementary electrical energy to produce H2 in the cathode microenvironment. Different bio/processes could be integrated to generate additional energy from the substrate used in MECs, which would make the whole process more sustainable. On the other hand, the energy required to drive the MEC mechanism could be harvested from renewable energy sources. These integrations could advance the efficiency and economic feasibility of the whole process. The present review critically discusses all the integrations investigated to date with MECs such as MFCs, anaerobic digestion, microbial desalination cells, membrane bioreactors, solar energy harvesting systems, etc. Energy generating non-biological and eco-friendly processes (such as dye-sensitized solar cells and thermoelectric microconverters) which could also be integrated with MECs, are also presented and reviewed. Achieving a comprehensive understanding about MEC integration could help with developing advanced biorefineries towards more sustainable energy management. Finally, the challenges related to the scaling up of these processes are also scrutinized with the aim to identify the practical hurdles faced in the MEC processes.
Feed Types Driven Differentiation of Microbial Community and Functionality in Marine Integrated Multitrophic Aquaculture System

Integrated multi trophic aquaculture (IMTA) improves the production of aquatic animals by promoting nutrient utilization through different tropical levels. Microorganisms play an important role in elements cycling, energy flow and farmed-species health. The aim of this study was to evaluate how feed types, fresh frozen fish diet (FFD) or formulated diet (FD), influence the microbial community diversity and functionality in both water and sediment in a marine IMTA system. Preferable water quality, higher animal yields and higher cost efficiency were achieved in the FD pond. Feed types changed the pond bacterial community distribution, especially in the rearing water. The FFD pond was dominated with Cyanobacteria in the water, which played an important role in nitrogen fixation through photosynthesis due to the high nitrogen input of the frozen fish diet. The high carbohydrate composition in the formulated diet triggered higher metabolic pathways related to carbon and lipid metabolism in the water of the FD pond. Sediment had significantly higher microbial diversity than the rearing water. In sediment, the dominating genus, Sulfurovum and Desulfobulbus, were found to be positively correlated by network analysis, which had similar functionality in sulfur transformation. The relatively higher rates of antibiotic biosynthesis in the FFD sediment might be related to the pathogenic bacteria introduced by the trash fish diet. The difference in microbial community composition and metabolic pathways may be associated with the different pathways for nutrient cycling and animal growth performance. The formulated diet was determined to be more ecologically and economically sustainable than the frozen fish diet for marine IMTA pond systems.
through Multiple TLRs Innate and Adaptive Immune Responses Microglia Initiate Central Nervous System

Julie K. Olson and Stephen D. Millerhttp://www.jimmunol.org/content/173/6/3916J Immunol€2004; 173:3916-3924; ;Referenceshttp://www.jimmunol.org/content/173/6/3916.full#ref-list-1This article cites 40 articles, 19 of which you can access for free at: Subscriptionshttp://jimmunol.org/subscriptionsInformation about subscribing to The Journal of Immunology is online at: Permissionshttp://www.aai. org/ji/copyright.htmlSubmit copyright permission requests at: Email Alertshttp://jimmunol.org/cgi/alerts/etocReceive free email-alerts when new articles cite this article. Sign up at:
A Summary of the Research on the Judicial Application of Artificial Intelligence

The use of artificial intelligence technology in the field of judicial trials is becoming more widespread. Intelligent software includes functional modules, such as guidance, prompting, and deviation warning, which can assist trials judges in sentencing, case push, and automatic document generation throughout the litigation process, thereby helping to save litigation costs and improve trial efficiency. However, in the application process, intelligent auxiliary software has displayed essential, prerequisite, procedural, and result defects and thus poses ethical risks and challenges. Therefore, we should clarify such technology’s auxiliary trial status, determine the scope of specific applications, and formulate ethical norms for judicial artificial intelligence. Additionally, differential trials and post hoc monitoring should be used to standardize the application of such technology.
Spatiotemporal bycatch analysis of the Atlantic halibut (Hippoglossus hippoglossus) longline fishery survey indicates hotspots for species of conservation concern

The Atlantic halibut (Hippoglossus hippoglossus) longline fishery is the second most valuable groundfish fishery in Atlantic Canada and received Marine Stewardship Council certification in 2013. The bottom longline fishery accounts for most halibut landings but incidentally catches nontargeted species (bycatch). Since 1998, Fisheries and Oceans Canada and the halibut fishing industry performed annual longline surveys across the Scotian Shelf and Southern Grand Banks stock management area to monitor halibut abundance, and at‐sea observers also recorded bycatch information. We examined the species composition and proportion of the survey bycatch and analyzed temporal and spatial trends in standardized weight of (a) halibut catch, (b) total bycatch, and (c) bycatch of species of conservation concern. From 1998 to 2016, 70% of the total catch by weight and 85% by number of individuals were bycatch. Over 100 identified species of finfish, sharks, skates, benthic invertebrates, marine mammals, and seabirds were caught as bycatch in the survey. This included four species listed under the Species at Risk Act (Northern wolffish, Anarhichas denticulatus; spotted wolffish, A. minor; Atlantic wolffish, A. lupus; Atlantic cod, Gadus morhua), and another 14 species awaiting a listing decision based on assessments by the Committee on the Status of Endangered Wildlife in Canada. Generally, the standardized weight of halibut and barndoor skate (Dipturus laevis) increased over time, while Atlantic cod, spiny dogfish (Squalus acanthias), white hake (Urophycis tenuis), and thorny skate (Amblyraja radiata) decreased. Spatial patterns indicated high bycatch levels on the southern Scotian Shelf and southern edge of the Southern Grand Banks, with hotspots for certain species of conservation concern. Our results identify temporal trends in threatened species and areas where they are susceptible to the Atlantic halibut longline fishery which can inform recovery strategies, bycatch levels and spatial zoning in fisheries management and marine conservation.
Application of characteristic modes to design the platform-mounted inverted-F antenna

Abstract: Many high-frequency antennas have significantly smaller dimensions than the operating wavelength, causing a narrow bandwidths. This paper examines characteristic modes (CMs) of platformmounted antennas to increase the overall bandwidth of the system. We use the theory of CMs to identify the appropriate platform modes and determine the practical feeding circuits. We fabricate a prototype platform antenna using a scaled model at 860 MHz to verify the simulation results.
AB0632 Association between Interstitial Pulmonary Involvement and Microvaculature Changes in Systemic Sclerosis

Background Pulmonary disease is the leading cause of mortality in patients with systemic sclerosis (SSc). Baseline gas transfer (DLCO) and FVC levels have traditionally been used as measures of disease severity and reductions in both parameters have been associated with increased mortality in the interstitial lung disease of SSc. In SSc the reduced capillary density leads to a reduced blood flow, to tissue ischemia. Tissue hypoxia usually initiates the formation of new blood vessels from the pre-existing microvasculature. Nailfold capillaroscopy is a safe, noninvasive routine way for the microvascular investigation Objectives The aim of this study is to assess the association between capillaroscopic abnormalities and parameters of interstitial lung involvement in patients with SSc. Methods All patients underwent routine clinical examination (dyspnea, cough, crepitus), pulmonary function tests, DLCO (alveolitis grade and fibrosis), blood gases and HRCT scan of chest (1). Microvasculature changes were assessed using nailfold videocapillaroscopy (NVC) which was performed by two independent examiners. The obtained images were analysed anonymously by two investigators blinded for the clinical and serum status of SSc patients and classified as early, active and late pattern, non specific or normal picture (2). For statistical evaluation Poisson's correlation coefficient and T-test were used. Results Total 42 patients (38 females) were investigated: 30 individuals with limited form, 7 with diffuse, 3 patients with scleroderma sine scleroderma, 1 with overlap syndrome and 1 with undifferentiated connective tissue disease. The mean age ± standard deviation (SD) of the whole cohort was 51±22 years and the mean disease duration ± SD was 10±7 years. 3 patients (7.5%) had early NVC pattern, 12 patients (30%) had active, 10 (58%) late pattern, and 17 (37.5%) had nonspecific changes or normal picture. The patients with late NVC pattern exhibited more often mild to moderate alveolitis, decreased FEV1 and FVC and DLCO. When correlating NVC patterns with clinical findings, pulmonary function test and HRCT scans we found only an association of low significance with dyspnea and alveolitis grade (both p<0.1). Conclusions In our study NVC patterns did not seem to correlate with severity of interstitial lung disease in SSc patients References Corrado A et al. Joint Bone Spine. 2010, Cutolo M et al. J Rheumatol. 2000 Acknowledgement This study was performed with support of CMH Research Projects No 00000023728. Disclosure of Interest R. Bečvář Consultant for: Actelion, M. Tomcik: None declared, S. Skacelova: None declared, J. Stork: None declared, A. Slovakova: None declared
Advanced Methods for Photovoltaic Output Power Forecasting: A Review

Forecasting is a crucial task for successfully integrating photovoltaic (PV) output power into the grid. The design of accurate photovoltaic output forecasters remains a challenging issue, particularly for multistep-ahead prediction. Accurate PV output power forecasting is critical in a number of applications, such as micro-grids (MGs), energy optimization and management, PV integrated in smart buildings, and electrical vehicle chartering. Over the last decade, a vast literature has been produced on this topic, investigating numerical and probabilistic methods, physical models, and artificial intelligence (AI) techniques. This paper aims at providing a complete and critical review on the recent applications of AI techniques; we will focus particularly on machine learning (ML), deep learning (DL), and hybrid methods, as these branches of AI are becoming increasingly attractive. Special attention will be paid to the recent development of the application of DL, as well as to the future trends in this topic.
Facial Expressions of Comprehension (FEC)

While the relationship between facial expressions and emotion has been a productive area of inquiry, research is only recently exploring whether a link exists between facial expressions and cognitive processes. Using findings from psychology and neuroscience to guide predictions of affectation during a cognitive task, this article aimed to study facial dynamics as a mean to understand comprehension. We present a new multimodal facial expression database, named Facial Expressions of Comprehension (FEC), consisting of the videos recorded during a computer-mediated task in which each trial consisted of reading, answering, and feedback to general knowledge true and false statements. To identify the level of engagement with the corresponding stimuli, we present a new methodology using animation units (AnUs) from the Kinect v2 device to explore the changes in facial configuration caused by an event: Event-Related Intensities (ERIs). To identify dynamic facial configurations, we used ERIs in statistical analyses with generalized additive models. To identify differential facial dynamics linked to knowing vs. guessing and true vs. false responses, we employed an SVM classifier with facial appearance information extracted using LPQ-TOP. Results of ERIs in sentence comprehension show that facial dynamics are promising to help understand affective and cognitive states of the mind.
GENETIC CHARACTERIZATION OF ANAEROBIC MICRO-ORGANISMS APPLIED TO WASTEWATER TREATMENT: AN ALTERNATIVE IN AREAS OF HEIGHT

The degradation of organic matter in wastewater from livestock stables is analyzed with the use of anaerobic micro-organisms obtained from wastewater samples from the study area. The research is divided into three phases. In the first, wastewater samples are taken from three farms in the area; in the second phase the samples are taken to the laboratory and three replicates of each collected sample are prepared to be analyzed and identified and the methanogenic bacteria that are responsible for degrading organic matter in anaerobic processes are isolated. In the last phase, two experiments are carried out with three repetitions each; in the first one, the contaminated water is placed without a previous dilution process. In the second experiment, a 75% dilution is carried out to recreate the real conditions in the treatment plants where the micro-organisms are going to be applied, which suffer dilutions due to the presence of constant precipitations in the analysis area. The results show a high elimination of organic matter and fecal coliforms in the wastewater treated with the identified micro-organisms, producing degradation kinetics of order 1 (exponential) with particular constants for each process.
Background selection does not mimic the patterns of genetic diversity produced by selective sweeps

It is increasingly evident that natural selection plays a prominent role in shaping patterns of diversity across the genome. The most commonly studied modes of natural selection are positive selection and negative selection, which refer to directional selection for and against derived mutations, respectively. Positive selection can result in hitchhiking events, in which a beneficial allele rapidly replaces all others in the population, creating a valley of diversity around the selected site along with characteristic skews in allele frequencies and linkage disequilibrium (LD) among linked neutral polymorphisms. Similarly, negative selection reduces variation not only at selected sites but also at linked sites—a phenomenon called background selection (BGS). Thus, discriminating between these two forces may be difficult, and one might expect efforts to detect hitchhiking to produce an excess of false positives in regions affected by BGS. Here, we examine the similarity between BGS and hitchhiking models via simulation. First, we show that BGS may somewhat resemble hitchhiking in simplistic scenarios in which a region constrained by negative selection is flanked by large stretches of unconstrained sites, echoing previous results. However, this scenario does not mirror the actual spatial arrangement of selected sites across the genome. By performing forward simulations under more realistic scenarios of BGS, modeling the locations of protein-coding and conserved noncoding DNA in real genomes, we show that the spatial patterns of variation produced by BGS rarely mimic those of hitchhiking events. Indeed, BGS is not substantially more likely than neutrality to produce false signatures of hitchhiking. This holds for simulations modeled after both humans and Drosophila, and for several different demographic histories. These results demonstrate that appropriately designed scans for hitchhiking need not consider background selection’s impact on false positive rates. However, we do find evidence that BGS increases the false negative rate for hitchhiking—an observation that demands further investigation.
Genetic Variation and Geographical Differentiation of Elymus nutans (Poaceae: Triticeae) from West China

Part of the Plant Sciences Commons, and the Soil Science Commons This document is available at https://uknowledge.uky. edu/igc/22/1-4/9 The 22nd International Grassland Congress (Revitalising Grasslands to Sustain Our Communities) took place in Sydney, Australia from September 15 through September 19, 2013. Proceedings Editors: David L. Michalk, Geoffrey D. Millar, Warwick B. Badgery, and Kim M. Broadfoot Publisher: New South Wales Department of Primary Industry, Kite St., Orange New South Wales, Australia
Study of voltage stability on photovoltaic integration into Lombok power system

Photovoltaic (PV) is known as an intermittent energy source so that the impacts need to be calculated by the developer. In order to ensure the presence of PV does not cause the reliability of the system interrupted, developers are required to perform the stability study before the integration. In this paper, voltage stability study is done by using various PV capacities ranging from 5 MWp to 15 MWp in systems with a capable capacity of 90.79 MW using software ETAP 12.6. 0. PV generation is set at the maximum site irradiance where power drop due to weather condition. The analysis shows the system stabilized in less than 50 seconds where the voltage disturbance does not exceed 10% for PV with a capacity of 5 and 10 MWp which is connected to a distribution network. Meanwhile, PV with a capacity of 15 MWp requires load release in order to regain stability.
Psychosocial Support and Emergency Education: An Explorative Study of Perceptions among Adult Stakeholders in Sudan and South Sudan

The link between education and psychosocial wellbeing is important, but complex. This study seeks to explore stakeholder’s views on the role of school education in the psychosocial support and wellbeing of children in the context of Sudan and South Sudan. Qualitative interviews were conducted among teachers, parents, counsellors, and NGO staff who were stakeholders in terms of providing education and psychosocial support for refugee children or children living in another kind of emergency situation. Even though no integrated psychosocial support was reported, teachers and schools were seen as having important roles to play, especially in terms of material and practical help, as well as for emotional needs. There was a clear motivation for providing more systematic help and access to methods and tools to serve this purpose. The development of helping strategies targeted for use in schools by teachers, which build on and strengthens existing ideas and practices, were explored. The potential for integrated psychosocial support is discussed based on these findings.
Reinforcement Learning-Based Distributed BESS Management for Mitigating Overvoltage Issues in Systems With High PV Penetration

High levels of penetration of distributed photovoltaic generators can cause serious overvoltage issues, especially during periods of high power generation and light loads. There have been many solutions proposed to mitigate the voltage problems, some of them using battery energy storage systems (BESS) at the PV generation sites. In addition to their ability to absorb extra power during the light load periods, BESS can also supply additional power under high load conditions. However, their capacity may not be sufficient to allow charging every time when power absorption is desired. Therefore, typical PV/BESS may not fully prevent over-voltage problems in power distribution grids. This work develops a cooperative state of charge control scheme to alleviate the BESS capacity problem through Monte Carlo tree search based reinforcement learning (MCTS-RL). The proposed intelligent method coordinates the distributed batteries from other regions to provide voltage regulation in a distribution network. Furthermore, the energy optimization process during the day hours and the simultaneous state of charge control are achieved using model predictive control (MPC). The proposed approach is demonstrated on two test cases, the IEEE 33 bus system and a practical medium size distribution system in Alberta Canada.
3D printing of composites: design parameters and flexural performance

3D printing of composites has a high degree of design freedom, which allows for the manufacture of complex shapes that cannot be achieved with conventional manufacturing processes. This paper aims to assess the design variables that might affect the mechanical properties of 3D-printed fibre-reinforced composites. ,Markforged Mark-Two printers were used to manufacture samples using nylon 6 and carbon fibres. The effect of fibre volume fraction, fibre layer location and fibre orientation has been studied using three-point flexural testing. ,The flexural strength and stiffness of the 3D-printed composites increased with increasing the fibre volume fraction. The flexural properties were altered by the position of the fibre layers. The highest strength and stiffness were observed with the reinforcement evenly distributed about the neutral axis of the sample. Moreover, unidirectional fibres provided the best flexural performance compared to the other orientations. 3D printed composites also showed various failure modes under bending loads. ,Despite multiple studies available on 3D-printed composites, there does not seem to be a clear understanding and consensus on how the location of the fibre layers can affect the mechanical properties and printing versatility. Therefore, this study covered this design parameter and evaluated different locations in terms of mechanical properties and printing characteristics. This is to draw final conclusions on how 3D printing may be used to manufacture cost-effective, high-quality parts with excellent mechanical performance.
Dynamic Deep Squat: Lower-Body Kinematics and Considerations Regarding Squat Technique, Load Position, and Heel Height

ABSTRACT THE DYNAMIC DEEP SQUAT IS AN IMPORTANT AND WIDELY USED EXERCISE BY STRENGTH AND CONDITIONING, REHABILITATION, AND HEALTH CARE PROFESSIONALS. THIS ARTICLE EXPLORES LUMBAR SPINE AND LOWER EXTREMITY KINEMATICS DURING THE DYNAMIC DEEP SQUAT AND CONSIDERS SQUAT TECHNIQUE, LOAD POSITION, AND HEEL HEIGHT INFLUENCES. BETTER UNDERSTANDING OF DYNAMIC DEEP SQUAT KINEMATICS MAY HELP TO PREVENT LUMBAR SPINE INJURIES RELATED TO SQUATTING.