Miracle-dz/UniFAR-FTUs huggingface dataset:
Telomere length: lights and shadows on their role in human reproduction

Abstract Telomeres are repeated DNA sequences whose main function is to preserve genome stability, protecting chromosomes ends from shortening caused by progressive loss during each cell replication or DNA damage. Telomere length regulation is normally achieved by telomerase enzyme, whose activity is progressively shut off during embryonic differentiation in somatic tissues, whereas it is maintained in germ cells, activated lymphocytes, and certain types of stem cell populations. The maintenance of telomerase activity for a longer time is necessary for germ cells to delay telomere erosion, thus avoiding chromosome segregation defects that could contribute to aneuploid or unbalanced gametes. Over the last few years, telomere biology has become an important topic in the field of human reproduction, encouraging several studies to focus on the relation between telomere length and spermatogenesis and male fertility, embryo development and quality during assisted reproductive treatment, and female pathologies as polycystic ovary, premature ovarian insufficiency, and endometriosis. This review analyzes whether telomere length in germ cells is related to reproduction fitness, whether telomere length is related to pathologies associated with male and female fertility, and whether measurement of telomere length could represent a biomarker of germ cell and embryo quality. Telomere length could be considered a molecular marker of spermatogenesis and sperm quality and is somewhat related to male fertility potential. Fewer evidence, although promising, is available for oocytes, female (in)fertility, and embryo quality. The increasing evidence for a role of telomeres and telomere length in human reproduction, indeed, has expanded the historical view of considering them just a marker of aging. Telomere length might have in the future a prognostic potential in couple infertility, especially useful to select best germ cells with the greatest potential of fertilization. Summary Sentence Telomere length could be considered a molecular marker of spermatogenesis and sperm quality and is somewhat related tomale fertility potential. Fewer evidence, although promising, is available for oocytes, female (in)fertility, and embryo quality.
Pharmacogenetic variation influences sensory neuropathy occurrence in Southern Africans treated with stavudine-containing antiretroviral therapy

Background The use of the HIV antiretroviral drug stavudine (d4T), a thymidine analogue, is associated with the development of mitochondrial toxicities such as sensory neuropathy (SN). Genetic variation in genes relating to d4T transport and metabolism, as well as genetic variation in the thymidine synthesis pathway, could influence occurrence of d4T-related toxicity. Methods We examined this hypothesis in a cohort of HIV-positive South African adults exposed to d4T, including 143 cases with SN and 120 controls without SN. Ten SNPs in four genes associated with stavudine transport, and 16 SNPs in seven genes of the thymidine synthesis / phosphorylation pathway were genotyped using Agena mass spectrometry methods. Associations between sensory neuropathy and genetic variants were evaluated using PLINK by univariate and multivariable analyses. Results Age and height were significantly associated with SN occurrence. Using logistic regression with age and height as covariates, and uncorrected empirical p-values, genetic variation in SLC28A1, SAMHD1, MTHFR and RRM2B was associated with SN in South Africans using d4T. Conclusion Variation in genes relating to d4T transport and metabolism, as well as genetic variation in the thymidine synthesis pathway may influence occurrence of d4T-related SN. These data contribute to the characterisation of African pharmacogenetic variation and its role in adverse response to antiretroviral therapy.
Central control of glucose homeostasis.

Type 2 diabetes is a complex disease mainly characterized by impaired insulin action and insulin secretion [1, 2]. A major breakthrough in the understanding of mechanisms leading to type 2 diabetes has recently come from studies on the central nervous system (CNS) dependent regulation of glucose and fat metabolism. The concept that the CNS has an essential role in glucose homeostasis and insulin action is not new. In 1849, Claude Bernard reported that pricking the floor of the fourth ventricle in rabbits produced hyperglycemia [3]. The past decade has greatly increased knowledge about the ability of the CNS to regulate food intake, body weight and glucose homeostasis. It is now clear that the CNS, and in particular the hypothalamus, plays a pivotal role in regulating glucose homeostasis independently of its effects on body weight. Therefore, some of the molecular defects underlying type 2 diabetes may reside in the CNS, supporting the concept that type 2 diabetes is, at least in part, a hypothalamic disorder.
Dynamic Swarm Attestation With Malicious Devices Identification

Nowadays, there is a rapid development of smart sensor network solutions. To prevent potential malicious attacks and make sure that the activities of devices are correct, there is a pressing need to ensure the software integrity of devices in the large-scale, dynamic, and self-organization swarm. Different from those single device attestation studies, Asokan et al. are the first to consider the secure swarm attestation problem and provide implementations based on two remote attestation architectures for embedded systems. However, their scheme could not provide a correct attestation result with dynamic swarm topology. Also, their scheme could not prevent a malicious device from launching a new attestation, and the adversary can use this weakness to conduct energy exhausting attack. In this paper, we mainly focus on secure and efficient identity attestation of compromised devices over swarm with dynamic topology and design an interactive swarm attestation scheme. Furthermore, we introduce multi-hop attestation security in swarm attestation and provide a verifiable solution for new attestation launching solution based on the one-way hash chain. Moreover, theoretical and practical analyses prove that our scheme is secure and efficient in attestation security and energy saving for dynamic swarm topology.
Framework to Enhance Nurses’ Use of EMR

Abstract The ability of nurses to adopt and successfully use EMR is expected to have a significant impact on achieving benefits such as reduction in healthcare costs and improvement in healthcare quality. A review of the current research literature reveals issues and concerns relating to the adoption and use of EMR by nurses in hospital environments. This article presents a literature review of such issues and concerns, and suggests a framework for enhancing the adoption and use of EMR by nurses and hospitals.
Metal-Cased Oil Well Inspection Using Near-Field UWB Radar Imaging

In this paper, monitoring of metal-cased oil wells using the ultrawideband (UWB) radar is proposed. The inspection includes the detection and imaging of perforations and corroded areas in a metal pipe. Detection of small anomalies/ perforations on the surface of a narrow metal pipe is very challenging. Here, we present a method for imaging such small anomalies based on the extra time delay of the reflected pulse due to the effect of perforation in the radar near field. In this paper, the necessary concepts for the use of UWB radar specified for this application are developed and proved based on different measurement and simulation scenarios. We have experimentally demonstrated the effect of the perforations’ size on the time delay of reflected pulses. The distance between the perforation and the radar, for the near-field phenomenon, is critical for an effective detection and imaging. Therefore, we also studied the optimal distance between the radar and the perforation. Perforations with a size range of 1–3 cm are considered for the experiments and simulations. The experiments are done both in air and diesel. Synthetic aperture radar processing is used to reconstruct the images of the perforations and corroded area. Measurement and simulation results demonstrate the potential of UWB radar systems for oil well monitoring applications.
A 0.9-V 33.7-ppm/°C 85-nW Sub-Bandgap Voltage Reference Consisting of Subthreshold MOSFETs and Single BJT

A low temperature coefficient (TC) and high power supply ripple rejection (PSRR) CMOS sub-bandgap voltage reference (sub-BGR) circuit using subthreshold MOS transistors and a single BJT is presented in this brief. The proposed sub-BGR consists of a novel complementary-to-absolute-temperature (CTAT) voltage generator based on a scaled emitter-base voltage of a BJT, and an improved proportional-to-absolute-temperature (PTAT) voltage generator based on stacking of <inline-formula> <tex-math notation="LaTeX">$\Delta V_{\mathbf {GS}}$ </tex-math></inline-formula> of sub-<inline-formula> <tex-math notation="LaTeX">$V_{\mathbf {TH}}$ </tex-math></inline-formula> MOSFETs. As the CTAT circuit achieves a reduced absolute value of the negative TC, the PTAT circuit achieves reduced power consumption without consuming a large chip area. The proposed sub-BGR circuit is implemented in a standard 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process. Measured results show that the sub-BGR circuit can run with a supply voltage down to 0.9 V while the power consumption is only 85 nW. An average TC of 33.7 ppm/°C and a PSRR of better than −40 dB over the full frequency range are achieved.
Deep Gaussian Process-Based Bayesian Inference for Contaminant Source Localization

This paper proposes a Bayesian framework for localization of multiple sources in the event of accidental hazardous contaminant release. The framework assimilates sensor measurements of the contaminant concentration with the integrated multizone computational fluid dynamics (multizone-CFD)-based contaminant fate and transport model. To ensure online tractability, we build deep Gaussian process-based emulators approximating multizone-CFD model. To effectively represent the transient response of the multizone-CFD model, the deep Gaussian processes are extended to matrix-variate architecture by adopting Kronecker products to the output covariance for each GP layer. The resultant deep matrix-variate Gaussian process emulators are used to define the likelihood of the Bayesian framework, while Markov chain Monte Carlo approach is used to sample from the posterior distribution. The proposed method is evaluated for single and multiple contaminant sources localization tasks modeled by CONTAM simulator in a single-story building of 30 zones, demonstrating that proposed approach accurately perform inference on locations of contaminant sources. Moreover, the proposed model not only shows outstanding regression performance but speed up training.
Knowledge Points Extraction of Junior High School English Exercises Based on SVM Method

In the process of learning English, students need to do a lot of exercises to improve English performance. The knowledge points of exercises are important to students, yet how to extract the knowledge points from exercises automatically is difficult, which is the foundation of the knowledge graph construction for students learning. In this paper, we use SVM to realize the knowledge points extraction of junior high school English exercises. Firstly, this paper obtains amounts of question data through analyzing electronic documents, and uses NLP tools to segment, POS tagging and named entity recognition. Secondly, we extract the knowledge points based on SVM model, which involves building multi-class feature vectors and constructing a hierarchical classification for question data. Finally, the experimental results prove the method is effective.
A Label-Free Fluorescent AND Logic Gate Aptasensor for Sensitive ATP Detection

In this study, a label-free fluorescent, enzyme-free, simple, highly sensitive AND logic gate aptasensor was developed for the detection of adenosine triphosphate (ATP). Double-stranded deoxyribonucleic acid (DNA) with cohesive ends was attached to graphene oxide (GO) to form an aptasensor probe. ATP and single-stranded DNA were used as input signals. Fluorescence intensity of PicoGreen dye was used as an output signal. The biosensor-related performances, including the logic gate construction, reaction time, linearity, sensitivity, and specificity, were investigated and the results showed that an AND logic gate was successfully constructed. The ATP detection range was found to be 20 to 400 nM (R2 = 0.9943) with limit of detection (LOD) of 142.6 pM, and the sensitivity range was 1.846 × 106 to 2.988 × 106 M−1. This method for the detection of ATP has the characteristics of being simple, low cost, and highly sensitive.
Investigation into Impulsive Noise Techniques for a G.FAST System

This paper focuses on impulsive noise (IN) mitigation techniques for the fourth generation broadband (4GBB) access network technology, known as G.fast. G.fast has demonstrated data rates up to 1 Gbps over lengths of copper loop up to 250 meters. The copper wire channel is subject to IN and our aim is to study its effect on the G.fast broadband system by modeling a copper wire channel combined with Middleton Class A IN is usually mitigated using simple non-linear techniques such as clipping and blanking, but these become less effective when working with high order QAM constellation, such as those used in G.fast. Therefore, we propose the use of the iterative Zhidkov algorithm to mitigate impulsive noise, for several noise index values. Simulation results show that Zhidkov’s algorithm outperforms the blanking and clipping methods, achieving a significant performance gain, and demonstrating that it is very suitable for use in a G.fast system.
Preferential Colonization of Osteoblasts Over Co-cultured Bacteria on a Bifunctional Biomaterial Surface

Implant-related infection is a devastating complication in clinical trauma and orthopedics. The aim of this study is to use a bifunctional biomaterial surface in order to investigate the competitive colonization between osteoblasts and bacteria, which is the cause of implant-related infection. A bone-engineering material capable of simultaneously facilitating osteoblast adhesion and inhibiting the growth of Staphylococcus aureus (S. aureus) was prepared. Then, three different co-cultured systems were developed in order to investigate the competitive colonization between the two cohorts on the surface. The results suggested that while the pre-culturing of either cohort compromised the subsequent adhesion of the other according to the ‘race for the surface’ theory, the synergistic effect of preferential cell adhesion and antibacterial activity of the bifunctional surface led to the predominant colonization and survival of osteoblasts, effectively inhibiting the bacterial adhesion and biofilm formation of S. aureus in the co-culture systems with both cohorts. This research offers new insight into the investigation of competitive surface-colonization between osteoblasts and bacteria for implant-related infection.
Enteric Fever Cases in the Two Largest Pediatric Hospitals of Bangladesh: 2013–2014

Abstract Background Enteric fever predominantly affects children in low- and middle-income countries. This study examines the burden of enteric fever at the 2 pediatric hospitals in Dhaka, Bangladesh and assesses their capacity for inclusion in a prospective cohort study to support enteric fever prevention and control. Methods A descriptive study of enteric fever was conducted among children admitted in 2013–2014 to inpatient departments of Dhaka Shishu and Shishu Shashthya Foundation Hospitals, sentinel hospitals of the World Health Organization-supported Invasive Bacterial Vaccine Preventable Disease surveillance platform. Results Of 15917 children with blood specimens received by laboratories, 2.8% (443 of 15917) were culture positive for significant bacterial growth. Sixty-three percent (279 of 443) of these isolates were confirmed as the cases of enteric fever (241 Salmonella Typhi and 38 Salmonella Paratyphi A). In addition, 1591 children had suspected enteric fever. Overall, 3.6% (1870 of 51923) were laboratory confirmed or suspected enteric fever cases (55% male, median age 2 years, 86% from Dhaka district, median hospital stay 5 days). Conclusions The burden of enteric fever among inpatients at 2 pediatric hospitals in Dhaka, Bangladesh is substantial. Therefore, inclusion of these hospitals in a prospective cohort study will be useful for the generation of credible disease burden estimates of enteric fever in Bangladesh.
Web-Based Mindfulness Interventions for Mental Health Treatment: Systematic Review and Meta-Analysis

Background Web-based mindfulness interventions are increasingly delivered through the internet to treat mental health conditions. Objective The objective of this study was to determine the effectiveness of web-based mindfulness interventions in clinical mental health populations. Secondary aims were to explore the impact of study variables on the effectiveness of web-based mindfulness interventions. Methods We performed a systematic review and meta-analysis of studies investigating the effects of web-based mindfulness interventions on clinical populations. Results The search strategy yielded 12 eligible studies. Web-based mindfulness interventions were effective in reducing depression in the total clinical sample (n=656 g=−0.609, P=.004) and in the anxiety disorder subgroup (n=313, g=−0.651, P<.001), but not in the depression disorder subgroup (n=251, P=.18). Similarly, web-based mindfulness interventions significantly reduced anxiety in the total clinical sample (n=756, g=−0.433, P=.004) and the anxiety disorder subgroup (n=413, g=−0.719, P<.001), but not in the depression disorder group (n=251, g=−0.213, P=.28). Finally, web-based mindfulness interventions improved quality of life and functioning in the total sample (n=591, g=0.362, P=.02) in the anxiety disorder subgroup (n=370, g=0.550, P=.02) and mindfulness skills in the total clinical sample (n=251, g=0.724, P<.001). Conclusions Results support the effectiveness of web-based mindfulness interventions in reducing depression and anxiety and in enhancing quality of life and mindfulness skills, particularly in those with clinical anxiety. Results should be interpreted with caution given the high heterogeneity of web-based mindfulness interventions and the low number of studies included.
The Profiling Machine: Active Generalization over Knowledge

The human mind is a powerful multifunctional knowledge storage and management system that performs generalization, type inference, anomaly detection, stereotyping, and other tasks. A dynamic KR system that appropriately profiles over sparse inputs to provide complete expectations for unknown facets can help with all these tasks. In this paper, we introduce the task of profiling, inspired by theories and findings in social psychology about the potential of profiles for reasoning and information processing. We describe two generic state-of-the-art neural architectures that can be easily instantiated as profiling machines to generate expectations and applied to any kind of knowledge to fill gaps. We evaluate these methods against Wikidata and crowd expectations, and compare the results to gain insight in the nature of knowledge captured by various profiling methods. We make all code and data available to facilitate future research.
User-Centric Evaluation of Recommender Systems in Social Learning Platforms: Accuracy is Just the Tip of the Iceberg

Recommender systems provide users with content they might be interested in. Conventionally, recommender systems are evaluated mostly by using prediction accuracy metrics only. But, the ultimate goal of a recommender system is to increase user satisfaction. Therefore, evaluations that measure user satisfaction should also be performed before deploying a recommender system in a real target environment. Such evaluations are laborious and complicated compared to the traditional, data-centric evaluations, though. In this study, we carried out a user-centric evaluation of state-of-the-art recommender systems as well as a graph-based approach in the ecologically valid setting of an authentic social learning platform. We also conducted a data-centric evaluation on the same data to investigate the added value of user-centric evaluations and how user satisfaction of a recommender system is related to its performance in terms of accuracy metrics. Our findings suggest that user-centric evaluation results are not necessarily in line with data-centric evaluation results. We conclude that the traditional evaluation of recommender systems in terms of prediction accuracy only does not suffice to judge performance of recommender systems on the user side. Moreover, the user-centric evaluation provides valuable insights in how candidate algorithms perform on each of the five quality metrics for recommendations: usefulness, accuracy, novelty, diversity, and serendipity.
Privado: Practical and Secure DNN Inference

Recently, cloud providers have extended support for trusted hardware primitives such as Intel SGX. Simultaneously, the field of deep learning is seeing enormous innovation and increase in adoption. In this paper, we therefore ask the question: "Can third-party cloud services use SGX to provide practical, yet secure DNN Inference-as-a-service? " Our work addresses the three main challenges that SGX-based DNN inferencing faces, namely, security, ease-of-use, and performance. We first demonstrate that side-channel based attacks on DNN models are indeed possible. We show that, by observing access patterns, we can recover inputs to the DNN model. This motivates the need for Privado, a system we have designed for secure inference-as-a-service. Privado is input-oblivious: it transforms any deep learning framework written in C/C++ to be free of input-dependent access patterns. Privado is fully-automated and has a low TCB: with zero developer effort, given an ONNX description, it generates compact C code for the model which can run within SGX-enclaves. Privado has low performance overhead: we have used Privado with Torch, and have shown its overhead to be 20.77\% on average on 10 contemporary networks.
A 2.4 GHz Rectifier Insensitive to the Angle of Incidence of Incoming Waves

In this paper a high efficiency, low-cost and low-complexity RF-DC converter was designed at 2.4 GHz that maintains increased efficiency range for a wide range of incident angles. The circuit of converter is based on a Wilkinson power combiner with two single-diode rectifiers. The proof of concept prototype uses a single-diode rectifier instead of the isolation resistor for recycling the wasted power when the input signals do not have the same phase. The modified Wilkinson power combiner was fabricated and measured using commercially available components. The measured rectifier RF-to-DC efficiency was 19.7% for in-phase input signals with power −20 dBm. Measurement results also showed that when the relative phase of input signals varied from 90 to 360 degrees, a variation in efficiency between 15% and 20.7% was observed.