Miracle-dz/UniFAR-FTUs huggingface dataset:
Limited knowledge of diabetes in patients attending an outpatient diabetes clinic at a referral hospital in Zimbabwe: a cross-sectional study

Introduction Diabetes mellitus (DM) has increased globally, with a significant increase noted in African communities. Self-care health-related behavior is determined by beliefs about health and illness which are based on the person? s knowledge of diabetes. The present study aimed to assess patients' diabetes awareness and level of diabetes knowledge in Zimbabwean adults with diabetes attending an outpatient diabetes clinic at a main referral hospital. Methods In this cross-sectional descriptive study, the Diabetes Knowledge Test (DKT) was used to measure 96 (71 women and 25 men) patients' knowledge of diabetes and their treatment. Both descriptive and analytic statistical methods were used. Results Most respondents had poor knowledge in all the three knowledge categories, total knowledge of diabetes, general knowledge of diabetes and knowledge of insulin use. Major knowledge gaps were noted related to insulin use, glycemic control and diet. Attending DM classes was significantly associated with general knowledge about diabetes (p 0.026) while the level of education was an independent determinant of Total Knowledge and Insulin use knowledge scores. Conclusion The identified knowledge gaps need to be addressed to control and minimize diabetes mellitus-related complications.
The Rapid Forgetting of Faces

How are faces forgotten? Studies examining forgetting in visual working memory (VWM) typically use simple visual features; however, in ecological scenarios, VWM typically contains complex objects. Given their significance in everyday functioning and their visual complexity, here we investigated how upright and inverted faces are forgotten within a few seconds, focusing on the raw errors that accompany such forgetting and examining their characteristics. In three experiments we found that longer retention intervals increased the size of errors. This effect was mainly accounted for by a larger proportion of random errors - suggesting that forgetting of faces reflects decreased accessibility of the memory representations over time. On the other hand, longer retention intervals did not modulate the precision of recall – suggesting that forgetting does not affect the precision of accessible memory representation. Thus, when upright and inverted faces are forgotten there is a complete failure to access them or a complete collapse of their memory representation. In contrast to the effect of retention interval (i.e., forgetting), face inversion led to larger errors that were mainly associated with decreased precision of recall. This effect was not modulated by the duration of the retention interval, and was observed even when memory was not required in the task. Therefore, upright faces are remembered more precisely compared to inverted ones due to perceptual, rather than mnemonic processes.
Basins of Attraction, Commitment Sets, and Phenotypes of Boolean Networks

The attractors of Boolean networks and their basins have been shown to be highly relevant for model validation and predictive modeling, e.g., in systems biology. Yet, there are currently very few tools available that are able to compute and visualize not only attractors but also their basins. In the realm of asynchronous, non-deterministic modeling not only is the repertoire of software even more limited, but also the formal notions for basins of attraction are often lacking. In this setting, the difficulty both for theory and computation arises from the fact that states may be elements of several distinct basins. In this paper, we address this topic by partitioning the state space into sets that are committed to the same attractors. These commitment sets can easily be generalized to sets that are equivalent w.r. t. the long-term behaviors of pre-selected nodes which leads us to the notions of markers and phenotypes which we illustrate in a case study on bladder tumorigenesis. For every concept, we propose equivalent CTL model checking queries and an extension of the state of the art model checking software NuSMV is made available that is capable of computing the respective sets. All notions are fully integrated as three new modules in our Python package PyBoolNet, including functions for visualizing the basins, commitment sets, and phenotypes as quotient graphs and pie charts.
Improving forecasting accuracy for stock market data using EMD-HW bagging

Many researchers documented that the stock market data are nonstationary and nonlinear time series data. In this study, we use EMD-HW bagging method for nonstationary and nonlinear time series forecasting. The EMD-HW bagging method is based on the empirical mode decomposition (EMD), the moving block bootstrap and the Holt-Winter. The stock market time series of six countries are used to compare EMD-HW bagging method. This comparison is based on five forecasting error measurements. The comparison shows that the forecasting results of EMD-HW bagging are more accurate than the forecasting results of the fourteen selected methods.
A new series- and parallel-feed-network

A new design concept of series- and parallel-feed network is presented. The proposed network can solve the significant power-dividing-ratio and amplitude-weighting distributions in low side-lobe level or self-adaptive antenna array. As a proof of concept, a 13-port network, including the power-diving-ratio of 5:1 and −32dB of Taylor's distribution, is given. Measured amplitude errors of the network are within a ripple better than ±0.2dB. The simulated and measured results are well agreed with each other.
Cloud MIMO for Smart Parking System

In this paper a cloud version of distributed reception scenario is analyzed in automated parking system. A parking sensor has a single antenna transmitter sending data to a large number of geographically separated single antenna receive routers. This scenario is applicable in smart parking system (SPS) enabled by Internet of Things (IoT). We propose a new functional split, which enables multiple-input multiple-output (MIMO) detection in cloud server and non-binary low density parity check (LDPC) codes application in SPS. The proposed architecture is intended to increase the uplink performance significantly in shadowed scenario and in strong interference scenario, leading to significant battery power saving in IoT sensor. Among other things, such approach requires less expenses due to reduced routers complexity and fits in future 5G concepts of massive IoT.
Disruption of Inferior Longitudinal Fasciculus Microstructure in Parkinson's Disease: A Systematic Review of Diffusion Tensor Imaging Studies

Parkinson's disease (PD) is a neurodegenerative disorder accompanied by a series of pathological mechanisms which contribute to a variety of motor and non-motor symptoms. Recently, there has been an increasing interest in structural diffusion tensor imaging (DTI) in PD which has shed light on our understanding of structural abnormalities underlying PD symptoms or its associations with pathological mechanisms. One of the white matter tracts shown to be disrupted in PD with a possible contribution to some PD symptoms is the inferior longitudinal fasciculus (ILF). On the whole, lower ILF integrity contributes to thought disorders, impaired visual emotions, cognitive impairments such as semantic fluency deficits, and mood disorders. This review outlines the microstructural changes in ILF associated with systemic inflammation and various PD symptoms like cognitive decline, facial emotion recognition deficit, depression, color discrimination deficit, olfactory dysfunction, and tremor genesis. However, few studies have investigated DTI correlates of each symptom and larger studies with standardized imaging protocols are required to extend these preliminary findings and lead to more promising results.
N,N-Dimethyl-3β-hydroxycholenamide Reduces Retinal Cholesterol via Partial Inhibition of Retinal Cholesterol Biosynthesis Rather Than its Liver X Receptor Transcriptional Activity

N,N-dimethyl-3β-hydroxycholenamide (DMHCA) is an experimental pharmaceutical and a steroidal liver X receptor (LXR) agonist, which does not induce undesired hepatic lipogenesis. Herein, DMHCA was evaluated for its retinal effects on normal C57BL/6J and Cyp27a1−/−Cyp46a1−/− mice; the latter having higher retinal total and esterified cholesterol in addition to retinal vascular abnormalities. Different doses and two formulations were used for DMHCA delivery either via drinking water (C57BL/6J mice) or by oral gavage (Cyp27a1−/−Cyp46a1−/− mice). The duration of treatment was 1 week for C57BL/6J mice and 2 or 4 weeks for Cyp27a1−/−Cyp46a1−/− mice. In both genotypes, the higher DMHCA doses (37–80 mg/kg of body weight/day) neither increased serum triglycerides nor serum cholesterol but altered the levels of retinal sterols. Total retinal cholesterol was decreased in the DMHCA-treated mice, mainly due to a decrease in retinal unesterified cholesterol. In addition, retinal levels of cholesterol precursors lanosterol, zymosterol, desmosterol, and lathosterol were changed in Cyp27a1−/−Cyp46a1−/− mice. In both genotypes, DMHCA effect on retinal expression of the LXR target genes was only moderate and gender-specific. Collectively, the data obtained provide evidence for a decrease in retinal cholesterol as a result of DMHCA acting in the retina as an enzyme inhibitor of cholesterol biosynthesis rather than a LXR transcriptional activator. Specifically, DMHCA appears to partially inhibit the cholesterol biosynthetic enzyme Δ24-dehydrocholesterol reductase rather than upregulate the expression of LXR target genes involved in reverse cholesterol transport. The identified DMHCA dosages, formulations, and routes of delivery as well as the observed effects on the retina should be considered in future studies using DMHCA as a potential therapeutic for age-related macular degeneration and diabetic retinopathy.
Qualitative Analysis of Growth Parameters for PECVD Based Low Temperature Synthesis of Graphene Using Design of Experiments

Determination of key factors and parameters is necessary to design any process when number of factors are large. Design of Experiments technique is an important statistical tool to serve the purpose. This work demonstrates a method to perform qualitative analysis in order to determine cardinal control factors for Graphene growth at low temperature values using Fractional Factorial design. Graphene is synthesized using Plasma Enhanced Chemical Vapor Deposition (PECVD) method in this work. Attribute Response Analysis suggests that Graphene growth temperature, deposition time and RF power are important controlling factors. This is verified by Graphene growth using the predicted recipe.
Compact triplex microstrip slot antenna based on triple feeding types

A novel design of triplex single-layer slot antenna is presented in this paper. By making use of three different types of feed lines and radiating patches, the proposed antenna achieves triplex and wideband features while the port-to-port isolation keeps a high level. The simulation results indicate that the three ports of this antenna work at 2.15–2.8 GHz, 3.1–4.7 GHz, and 4.7–5.95 GHz with the 10-dB return-loss impedance bandwidths of 26.3%, 41%, and 23.5%, respectively. Furthermore, the port isolation of the three ports attains higher than 23dB. Because of the triplex characteristics, this antenna is a good potential in the frequency division duplex systems in future.
Oil Spill Detection in Synthetic Aperture Radar Images Using Lipschitz-Regularity and Multiscale Techniques

This research adapts an effective change detection approach originally applied to mapping fire scar from a stationary synthetic aperture radar (SAR) scene to the problem of oil spills from SAR data. The method presented here combines several advanced image processing techniques to mitigate some of the common performance limitations of SAR-based oil spill detection. Principally among these limitations are the following. First, the radar cross section of the areas affected by an oil spill strongly depends on wind and wave effects, and is, therefore, highly variable. Second, the radar cross section of oil covered water is often indistinguishable from other dark ocean features such as low wind areas, which leads to errors and uncertainties in oil spill detection. In this paper, we introduce a multi-image analysis, the Lipschitz regularity (LR), and wavelet transforms as a combined approach to mitigate these performance limitations. We show that the LR parameter is much less sensitive to variations of wind and waves in an oil spill SAR imagery, lending itself well for normalizing and suppressing ocean background using image ratio processing. We combine LR processing with a multiscale technique based on the wavelet transform to additionally achieve high-quality noise suppression. To describe the performance of this approach under controlled conditions, we applied our method to simulated SAR data of wind-driven oceans with oil spills and low wind areas. We also applied our method to several real-world oil spill data acquired during the 2010 Deep Water Horizon spill in the Gulf of Mexico.
Multi-locus sequence typing of Treponema pallidum subsp. pallidum present in clinical samples from France: Infecting treponemes are genetically diverse and belong to 18 allelic profiles

Treponema pallidum subsp. pallidum, the causative agent of sexually transmitted syphilis, detected in clinical samples from France, was subjected to molecular typing using the recently developed Multilocus Sequence Typing system. The samples (n = 133) used in this study were collected from 2010–2016 from patients with diagnosed primary or secondary syphilis attending outpatient centers or hospitals in several locations in France. Altogether, 18 different allelic profiles were found among the fully typed samples (n = 112). There were five allelic variants identified for TP0136, 12 for TP0548, and eight for TP0705. Out of the identified alleles, one, seven, and three novel alleles were identified in TP0136, TP0548, and TP0705, respectively. Partial allelic profiles were obtained from 6 samples. The majority of samples (n = 110) belonged to the SS14-like cluster of TPA isolates while 7 clustered with Nichols-like isolates. Patients infected with Nichols-like samples were more often older (p = 0.041) and more often diagnosed with secondary syphilis (p = 0.033) compared to patients infected with SS14-like samples. In addition, macrolide resistance caused by the A2058G mutation was found to be associated with allelic profile 1.3. 1 or with strains belonging to the 1.3. 1 lineage (p<0.001). The genetic diversity among TPA strains infecting the European population was surprisingly high, which suggests that additional studies are needed to reveal the full genetic diversity of TPA pathogens infecting humans.
On the MIMO Capacity with Multiple Linear Transmit Covariance Constraints

This paper presents an efficient approach to computing the capacity of multiple-input multiple-output (MIMO) channels under multiple linear transmit covariance constraints (LTCCs). LTCCs are general enough to include several special types of power constraints as special cases such as the sum power constraint (SPC), per-antenna power constraint (PAPC), or a combination thereof. Despite its importance and generality, most of the existing literature considers either SPC or PAPC independently. Efficient solutions to the computation of the MIMO capacity with a combination of SPC and PAPC have been recently reported, but were only dedicated to multiple-input single-output (MISO) systems. For the general case of LTCCs, we propose a low-complexity semi-closed-form approach to the computation of the MIMO capacity. Specifically, a modified minimax duality is first invoked to transform the considered problem in the broadcast channel into an equivalent minimax problem in the dual multiple access channel. Then alternating optimization and concave-convex procedure are utilized to derive water-filling-based algorithms to find a saddle point of the minimax problem. This is different from the state-of-the-art solutions to the considered problem, which are based on interior-point or subgradient methods. Analytical and numerical results are provided to demonstrate the effectiveness of the proposed low-complexity solution under various MIMO scenarios.
Differential roles of sleep spindles and sleep slow oscillations in memory consolidation

Sleep plays an important role in consolidation of recent memories. However, the mechanisms of consolidation remain poorly understood. In this study, using a realistic computational model of the thalamocortical network, we demonstrated that sleep spindles (the hallmark of N2 stage sleep) and slow oscillations (the hallmark of N3 stage sleep) both facilitate spike sequence replay as necessary for consolidation. When multiple memories were trained, the local nature of spike sequence replay during spindles allowed replay of the memories independently, while during slow oscillations replay of the weak memory was competing to the strong memory replay. This led to the weak memory extinction unless when sleep spindles (N2 sleep) preceded slow oscillations (N3 sleep), as observed during natural sleep. Our study presents a mechanistic explanation for the role of sleep rhythms in memory consolidation and proposes a testable hypothesis how the natural structure of sleep stages provides an optimal environment to consolidate memories. Significant Statement Numerous studies suggest importance of NREM sleep rhythms – spindles and slow oscillations - in sleep related memory consolidation. However, synaptic mechanisms behind the role of these rhythms in memory and learning are still unknown. Our new study predicts that sleep replay - the neuronal substrate of memory consolidation - is organized within the sleep spindles and coordinated by the Down to Up state transitions of the slow oscillation. For multiple competing memories, slow oscillations facilitated only strongest memory replay, while sleep spindles allowed a consolidation of the multiple competing memories independently. Our study predicts how the basic structure of the natural sleep stages provides an optimal environment for consolidation of multiple memories.
The effects of auditory enrichment on zebrafish behavior and physiology

Environmental enrichment is widely used to improve welfare and behavioral performance of animal species. It ensures housing of laboratory animals in environments with space and complexity that enable the expression of their normal behavioral repertoire. Auditory enrichment by exposure to classical music decreases abnormal behaviors and endocrine stress responses in humans, non-humans primates, and rodents. However, little is known about the role of auditory enrichment in laboratory zebrafish. Given the growing importance of zebrafish for neuroscience research, such studies become critical. To examine whether auditory enrichment by classical music can affect fish behavior and physiology, we exposed adult zebrafish to 2 h of Vivaldi’s music (65–75 dB) twice daily, for 15 days. Overall, zebrafish exposed to such auditory stimuli were less anxious in the novel tank test and less active, calmer in the light-dark test, also affecting zebrafish physiological (immune) biomarkers, decreasing peripheral levels of pro-inflammatory cytokines and increasing the activity of some CNS genes, without overt effects on whole-body cortisol levels. In summary, we report that twice-daily exposure to continuous musical sounds may provide benefits over the ongoing 50–55 dB background noise of equipment in the laboratory setting. Overall, our results support utilizing auditory enrichment in laboratory zebrafish to reduce stress and improve welfare in this experimental aquatic organism.
Hepatitis C virus enters liver cells using the CD81 receptor complex proteins calpain-5 and CBLB

Hepatitis C virus (HCV) and the malaria parasite Plasmodium use the membrane protein CD81 to invade human liver cells. Here we mapped 33 host protein interactions of CD81 in primary human liver and hepatoma cells using high-resolution quantitative proteomics. In the CD81 protein network, we identified five proteins which are HCV entry factors or facilitators including epidermal growth factor receptor (EGFR). Notably, we discovered calpain-5 (CAPN5) and the ubiquitin ligase Casitas B-lineage lymphoma proto-oncogene B (CBLB) to form a complex with CD81 and support HCV entry. CAPN5 and CBLB were required for a post-binding and pre-replication step in the HCV life cycle. Knockout of CAPN5 and CBLB reduced susceptibility to all tested HCV genotypes, but not to other enveloped viruses such as vesicular stomatitis virus and human coronavirus. Furthermore, Plasmodium sporozoites relied on a distinct set of CD81 interaction partners for liver cell entry. Our findings reveal a comprehensive CD81 network in human liver cells and show that HCV and Plasmodium highjack selective CD81 interactions, including CAPN5 and CBLB for HCV, to invade cells.
Impact of chlorine dioxide disinfection of irrigation water on the epiphytic bacterial community of baby spinach and underlying soil

The contamination of pathogenic bacteria through irrigation water is a recognized risk factor for fresh produce. Irrigation water disinfection is an intervention strategy that could be applied to reduce the probability of microbiological contamination of crops. Disinfection treatments should be applied ensuring minimum effective doses, which are efficient in inhibiting the microbial contamination while avoiding formation and accumulation of chemical residues. Among disinfection technologies available for growers, chlorine dioxide (ClO2) represents, after sodium hypochlorite, an alternative disinfection treatment, which is commercially applied by growers in the USA and Spain. However, in most of the cases, the suitability of this treatment has been tested against pathogenic bacteria and low attention have been given to the impact of chemical residues on the bacterial community of the vegetable tissue. The aim of this study was to (i) to evaluate the continual application of chlorine dioxide (ClO2) as a water disinfection treatment of irrigation water during baby spinach growth in commercial production open fields, and (ii) to determine the subsequent impact of these treatments on the bacterial communities in water, soil, and baby spinach. To gain insight into the changes in the bacterial community elicited by ClO2, samples of treated and untreated irrigation water as well as the irrigated soil and baby spinach were analyzed using Miseq® Illumina sequencing platform. Next generation sequencing and multivariate statistical analysis revealed that ClO2 treatment of irrigation water did not affect the diversity of the bacterial community of water, soil and crop, but significant differences were observed in the relative abundance of specific bacterial genera. This demonstrates the different susceptibility of the bacteria genera to the ClO2 treatment. Based on the obtained results it can be concluded that the phyllosphere bacterial community of baby spinach was more influenced by the soil bacteria community rather than that of irrigation water. In the case of baby spinach, the use of low residual ClO2 concentrations (approx. 0.25 mg/L) to treat irrigation water decreased the relative abundance of Pseudomonaceae (2.28-fold) and Enterobacteriaceae (2.5-fold) when comparing treated versus untreated baby spinach. Members of these two bacterial families are responsible for food spoilage and foodborne illnesses. Therefore, a reduction of these bacterial families might be beneficial for the crop and for food safety. In general it can be concluded that the constant application of ClO2 as a disinfection treatment for irrigation water only caused changes in two bacterial families of the baby spinach and soil microbiota, without affecting the major phyla and classes. The significance of these changes in the bacterial community should be further evaluated.