Miracle-dz/UniFAR-FTUs huggingface dataset:
Reasons behind current gender imbalances in senior global health roles and the practice and policy changes that can catalyze organizational change

The paper distils results from a review of relevant literature and two gender analyses to highlight reasons for gender imbalances in senior roles in global health and ways to address them. Organizations, leadership, violence and discrimination, research and human resource management are all gendered. Supplementary materials from gender analyses in two African health organizations demonstrate how processes such as hiring, deployment and promotion, and interpersonal relations, are not ‘gender-neutral’ and that gendering processes shape privilege, status and opportunity in these health organizations. Organizational gender analysis, naming stereotypes, substantive equality principles, special measures and enabling conditions to dismantle gendered disadvantage can catalyze changes to improve women's ability to play senior global health roles in gendered organizations. Political strategies and synergies with autonomous feminist movements can increase women's full and effective participation and equal opportunities. The paper also presents organizational development actions to bring about more gender egalitarian global health organizations.
Resource Availability Models Policy Models Rule Learning Mechanism Plan Resourcing Strategy Mechanism Dialogue Manager Dialogical episodes Dialogue strategy

What do I need to say to convince you to do something? This is an important question for an autonomous agent deciding whom to approach for a resource or for an action to be done. Were similar requests granted from similar agents in similar circumstances? What arguments were most persuasive? What are the costs involved in putting certain arguments forward? In this paper we present an agent decision-making mechanism where models of other agents are refined through evidence from past dialogues, and where these models are used to guide future argumentation strategy. We empirically evaluate our approach to demonstrate that decision-theoretic and machine learning techniques can both significantly improve the cumulative utility of dialogical outcomes, and help to reduce communication overhead.
Design of SRAM array using reversible logic for an efficient SoC design

Recently, the power dissipation has become the prime concern with the system-on-chip (SOC) as technology scales. Further, the memory component of the design is as crucial, as it is energy consuming. The conventional approach of circuit designing consumes a lot of power and occupies much area. Thus, the concept of reversible logic in circuit designing is garnering growing attention for low-power applications such as DNA computing, quantum computing and ultra-low power CMOS design. This paper proposes a reversible design of 4-bit 6-T SRAM array at 180nm-1.8V CMOS technology which achieves 8% reduction in energy consumption of the circuit. The designs are simulated on Cadence virtuoso 6.1. 4 schematic editor. The present work also concludes with some insights on the operation of conventional SRAM 6-T cell and the feasibility of reversible logic.
Comparison of alexithymia in schizophrenia and somatic diseases

Somatic diseases, schizophrenia paranoid form the basis of the results of our study examined and established high level alexithymia in both groups. Paranoid schizophrenia patients with higher marks alexithymia level than these somatic diseases. The negative symptoms of schizophrenia patients in weight, compared to about two times more positive signs included. The negative symptoms of schizophrenia, that is a positive correlation with the level of alexithymia. Paranoid schizophrenia, its sense of social isolation is difficult to describe their lack of ability to understand the higher level of relations between individuals, conflicts and patients and when alexithymia and other. The results of these studies show that in future relations and the prospects for the study of schizophrenia and have great relevance in alexithymia. Comparison of alexithymia in schizophrenia and somatic diseases
Two-dimensional distribution of oscillations in a quiescent solar prominence ?

Using time series of two-dimensional Dopplergrams, a temporal and spatial analysis of oscillations in a quiescent prominence has been performed. The presence of an outstanding oscillatory signal in the acquired data has allowed us to study the two-dimensional distribution of wave motions and, in particular, to detect the location of wave generation and the anisotropic propagation of perturbations from that place. Moreover, a strong damping of oscillations has been observed, with damping times between two and three times the wave period. The direction of propagation, wavelength and phase speed, together with the damping time and wave period, have been quantified and their spatial arrangement has been analysed. Thanks to the goodness of the observational data, the image alignment procedure applied during the data reduction stage and the analysis tools employed, it has been possible to carry out a novel and far-reaching observational study of prominence oscillations.
Next‐generation sequencing unravels extensive genetic alteration in recurrent ovarian cancer and unique genetic changes in drug‐resistant recurrent ovarian cancer

By using a high‐throughput sequencing technique, we sought to delineate genetic alterations in recurrent ovarian cancer patients and further compare genetic changes in drug‐resistant and ‐sensitive recurrent ovarian cancer patients. We also sought to study the specificity, sensitivity, and consistency of DNA biomarkers in liquid biopsy specimens and ovarian cancer tissue DNA.
Neuroimaging Paradigms to Identify Patients for Reperfusion Therapy in Stroke of Unknown Onset

Despite the proven efficacy of intravenous alteplase or endovascular thrombectomy for the treatment of patients with acute ischemic stroke, only a minority receive these treatments. This low treatment rate is due in large part to delay in hospital arrival or uncertainty as to the exact time of onset of ischemic stroke, which renders patients outside the current guideline-recommended window of eligibility for receiving these therapeutics. However, recent pivotal clinical trials of late-window thrombectomy now force us to rethink the value of a simplistic chronological formulation that “time is brain. ” We must recognize a more nuanced concept that the rate of tissue death as a function of time is not invariant, that still salvageable tissue at risk of infarction may be present up to 24 h after last-known well, and that those patients may strongly benefit from reperfusion. Multiple studies have sought to address this clinical dilemma using neuroimaging methods to identify a radiographic time-stamp of stroke onset or evidence of salvageable ischemic tissue and thereby increase the number of patients eligible for reperfusion therapies. In this review, we provide a critical analysis of the current state of neuroimaging techniques to select patients with unwitnessed stroke for revascularization therapies and speculate on the future direction of this clinically relevant area of stroke research.
Typ-2-Diabetes: Nach Metformin – Verändern neue Studien die Therapie?

Was ist neu? Kardiovaskuläre Endpunktstudien Seit 2013 wurden mehrere auf Nicht-Unterlegenheit angelegte, Placebo-kontrollierte Endpunktstudien zur kardiovaskulären Sicherheit einzelner Substanzen neuer antidiabetischer Wirkstoffklassen publiziert. Während für die Therapie mit den GLP-1-Rezeptoragonisten Liraglutid und Semaglutid sowie für die mit den SGLT-2-Inhibitoren Empagliflozin und Canagliflozin eine Reduktion kardiovaskulärer Endpunkte demonstriert werden konnte, zeigten die bisher abgeschlossenen Studien mit DPP-4-Inhibitoren keine Reduktion kardiovaskulärer Ereignisse. Therapieeskalation nach Metformin Für die notwendige Therapieeskalation bei unzureichender Blutzuckerkontrolle unter Metformin wird bei Patienten mit Diabetes mellitus Typ 2 und hohem Risiko für kardiovaskuläre Erkrankungen vorrangig die Erweiterung der Therapie mit GLP-1-Rezeptoragonisten und SGLT-2-Inhibitoren empfohlen. Auch der Einsatz von DPP-4-Inhibitoren ist für Patienten sinnvoll, bei denen einfache Therapiedurchführung, gute Verträglichkeit und Therapiesicherheit im Vordergrund stehen.
Tolerogenic Dendritic Cells as a Promising Antigen-Specific Therapy in the Treatment of Multiple Sclerosis and Neuromyelitis Optica From Preclinical to Clinical Trials

The identification of activated T-lymphocytes restricted to myelin-derived immunogenic peptides in multiple sclerosis (MS) and aquaporin-4 water channel in neuromyelitis optica (NMO) in the blood of patients opened the possibility for developing highly selective and disease-specific therapeutic approaches. Antigen presenting cells and in particular dendritic cells (DCs) represent a strategy to inhibit pro-inflammatory T helper cells. DCs are located in peripheral and lymphoid tissues and are essential for homeostasis of T cell-dependent immune responses. The expression of a particular set of receptors involved in pathogen recognition confers to DCs the property to initiate immune responses. However, in the absence of danger signals different DC subsets have been revealed to induce active tolerance by inducing regulatory T cells, inhibiting pro-inflammatory T helper cells responses or both. Interestingly, several protocols to generate clinical-grade tolerogenic DC (Tol-DC) in vitro have been described, offering the possibility to restore the homeostasis to central nervous system-related antigens. In this review, we discuss about different DC subsets and their role in tolerance induction, the different protocols to generate Tol-DCs and preclinical studies in animal models as well as describe recent characterization of Tol-DCs for clinical application in autoimmune diseases and in particular in MS and NMO patients. In addition, we discuss the clinical trials ongoing based on Tol-DCs to treat different autoimmune diseases.
Recurrence rate of atrial fibrillation after the first clinical episode: A prospective evaluation using continuous cardiac rhythm monitoring

Decision making regarding a patient who has experienced a first clinical episode of atrial fibrillation (AF) is challenging, and the AF recurrences should be a significant consideration. Continuous long‐term rhythm monitoring via implantable loop recorders (ILRs) has enabled us to evaluate the AF recurrence profile after the first clinical episode and to investigate clinical parameters associated with the course of the arrhythmia.
Antihyperglycemic and Antihyperlipidemic Effects of Ferula duranii in Experimental Type 2 Diabetic Rats

A B S T R A C T In the present study, DPPH radical scavenging assay and ferric-reducing antioxidant assay were used to evaluate in vitro antioxidant potential of the methanol extract of Ferula duranii (F. duranii). The antihyperglycemic and antihyperlipidemic activities of F. duranii extract were evaluated in streptozotocin (STZ)-induced diabetic rats. F. duranii showed considerable antioxidant potential in the DPPH radical scavenging assay and minimum reducing power in ferric-reducing antioxidant power assay. A meaningful reduction in the concentrations of Fasting Blood Glucose (FBG), glycosylated hemoglobin (Hb A1c), triglycerides (TG), Total Cholesterol (TC) and Low Density Lipoprotein (LDL-C) in plasma and an elevation in the activity of superoxide dismutase (SOD), glutathione peroxidase (GPx), catalase (CAT) in hepatic and pancreas homogenates were observed in diabetic animals medicated with F. duranii extract in comparison with diabetic control rats. The level of insulin raised significantly in plasma of diabetic groups received F. duranii in respect to diabetic control one. Levels of alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), bilirubin, total protein and High Density Lipoprotein (HDL-C) in plasma and malondialdehyde (MDA) in liver and pancreas homogenates were recovered significantly in F. duranii-medicated diabetic rats in comparison with diabetic controls. The present data suggest that F. duranii has both antidiabetic and antihyperlipidemic effects.
Uncertainty Gated Network for Land Cover Segmentation

The production of thematic maps depicting land cover is one of the most common applications of remote sensing. To this end, several semantic segmentation approaches, based on deep learning, have been proposed in the literature, but land cover segmentation is still considered an open problem due to some specific problems related to remote sensing imaging. In this paper we propose a novel approach to deal with the problem of modelling multiscale contexts surrounding pixels of different land cover categories. The approach leverages the computation of a heteroscedastic measure of uncertainty when classifying individual pixels in an image. This classification uncertainty measure is used to define a set of memory gates between layers that allow a principled method to select the optimal decision for each pixel
Body composition and the monitoring of non-communicable chronic disease risk

There is a need for simple proxies of health status, in order to improve monitoring of chronic disease risk within and between populations, and to assess the efficacy of public health interventions as well as clinical management. This review discusses how, building on recent research findings, body composition outcomes may contribute to this effort. Traditionally, body mass index has been widely used as the primary index of nutritional status in children and adults, but it has several limitations. We propose that combining information on two generic traits, indexing both the ‘metabolic load’ that increases chronic non-communicable disease risk, and the homeostatic ‘metabolic capacity’ that protects against these diseases, offers a new opportunity to improve assessment of disease risk. Importantly, this approach may improve the ability to take into account ethnic variability in chronic disease risk. This approach could be applied using simple measurements readily carried out in the home or community, making it ideal for M-health and E-health monitoring strategies.
The Big Entity of New RNA World: Long Non-Coding RNAs in Microvascular Complications of Diabetes

A major part of the genome is known to be transcribed into non-protein coding RNAs (ncRNAs), such as microRNA and long non-coding RNA (lncRNA). The importance of ncRNAs is being increasingly recognized in physiological and pathological processes. lncRNAs are a novel class of ncRNAs that do not code for proteins and are important regulators of gene expression. In the past, these molecules were thought to be transcriptional “noise” with low levels of evolutionary conservation. However, recent studies provide strong evidence indicating that lncRNAs are (i) regulated during various cellular processes, (ii) exhibit cell type-specific expression, (iii) localize to specific organelles, and (iv) associated with human diseases. Emerging evidence indicates an aberrant expression of lncRNAs in diabetes and diabetes-related microvascular complications. In the present review, we discuss the current state of knowledge of lncRNAs, their genesis from genome, and the mechanism of action of individual lncRNAs in the pathogenesis of microvascular complications of diabetes and therapeutic approaches.
Effective Features to Classify Big Data Using Social Internet of Things

Social Internet of Things (SIoT) supports many novel applications and networking services for the IoT in a more powerful and productive way. In this paper, we have introduced a hierarchical framework for feature extraction in SIoT big data using map-reduced framework along with a supervised classifier model. Moreover, a Gabor filter is used to reduce noise and unwanted data from the database, and Hadoop Map Reduce has been used for mapping and reducing big databases, to improve the efficiency of the proposed work. Furthermore, the feature selection has been performed on a filtered data set by using Elephant Herd Optimization. The proposed system architecture has been implemented using Linear Kernel Support Vector Machine-based classifier to classify the data and for predicting the efficiency of the proposed work. From the results, the maximum accuracy, specificity, and sensitivity of our work is 98.2%, 85.88%, and 80%, moreover analyzed time and memory, and these results have been compared with the existing literature.
Zur Lage der gesellschaftlichen Mitte in Deutschland

In den vergangenen Jahren waren von Massenentlassungen groserer Firmen nicht mehr weit uberwiegend Geringqualifizierte, sondern zunehmend auch Personen mit abgeschlossener beruflicher Ausbildung, einschlieslich solcher mit Hochschulabschluss, und nicht mehr nur Arbeitnehmer im produzierenden Gewerbe, sondern auch Arbeitnehmer im Dienstleistungssektor betroffen. Diese Meldungen haben unter den weiterhin Beschaftigten ein betrachtliches Mas an Unsicherheit erzeugt. Auch der Einstieg ins Erwerbsleben erscheint, selbst im Bereich qualifizierter Beschaftigung, heute schwieriger als in der Vergangenheit. Trotzdem ist offen, ob und in welchem Mase die Wahrnehmung eines gestiegenen Entlassungsrisikos bzw. einer zunehmenden Instabilitat von Erwerbsverlaufen auch im Bereich der gesellschaftlichen Mitte der Realitat entspricht. Der Beitrag untersucht, inwieweit innerhalb der "gesellschaftlichen Mitte" bestimmte Konvergenz- oder Divergenztendenzen sichtbar werden.
Memory for melodies in unfamiliar tuning systems: Investigating effects of recency and number of intervening items

In a continuous recognition paradigm, most stimuli elicit superior recognition performance when the item to be recognized is the most recent stimulus (a recency-in-memory effect). Furthermore, increasing the number of intervening items cumulatively disrupts memory in most domains. Memory for melodies composed in familiar tuning systems also shows superior recognition for the most recent melody, but no disruptive effects from the number of intervening melodies. A possible explanation has been offered in a novel regenerative multiple representations (RMR) conjecture. The RMR assumes that prior knowledge informs perception and perception influences memory representations. It postulates that melodies are perceived, thus also represented, simultaneously as integrated entities and also as their components (such as pitches, pitch intervals, short phrases and rhythm). Multiple representations of the melody components and melody as a whole can restore one another, thus providing resilience against disruptive effects from intervening items. The conjecture predicts that melodies in an unfamiliar tuning system are not perceived as integrated melodies and should (a) disrupt recency-in-memory advantages and (b) facilitate disruptive effects from the number of intervening items. We test these two predictions in three experiments. Experiments 1 and 2 show that no recency-in-memory effects emerge for melodies in an unfamiliar tuning system. In Experiment 3, disruptive effects occurred as the number of intervening items and unfamiliarity of the stimuli increased. Overall, results are coherent with the predictions of the RMR conjecture. Further investigation of the conjecture’s predictions may lead to greater understanding of the fundamental relationships between memory, perception and behavior.
Expression profile of circular RNAs in infantile hemangioma detected by RNA-Seq

Background: Circular RNAs (circRNAs) have emerged as a novel class of widespread non-coding RNAs, and they play crucial roles in various biological processes. However, the characterization and function of circRNAs in infantile hemangioma (IH) remain elusive. Methods: In this study, we used RNA-Seq and circRNA prediction to study and characterize the circRNAs in IH tissue and a matched normal skin control. Specific circRNAs were verified using real-time polymerase chain reaction. Results and Conclusion: We found that of the 9811 identified circRNAs, 249 candidates were differentially expressed, including 124 upregulated and 125 downregulated circRNAs in the IH group compared with the matched normal skin control group. A set of differentially expressed circRNAs (in particular, hsa_circRNA001885 and hsa_circRNA006612 expression) were confirmed using qRT-PCR. Gene ontology and pathway analysis revealed that compared to matched normal skin tissues, many processes that were over-represented in IH group were related to the binding, protein binding, gap junction, and focal adhesion. Specific circRNAs were associated with several micro-RNAs (miRNAs) predicted using miRanda. Altogether, our findings highlight the potential importance of circRNAs in the biology of IH and its response to treatment.
Cross-layer resource allocation for mixed tactile Internet and traditional data in SCMA based wireless networks

The tactile internet requires an ultra short end-to-end (E2E) latency of about 1 ms and is proposed as one of the fifth-generation (5G) wireless cellular network applications. In a typical 5G framework, inclusion of tactile data that imposes different delay requirements than traditional data to the system, makes the system implementation more challenging. This paper is concerned with resource allocation to maximize the uplink sum rate of traditional data while satisfying the delay requirements for tactile data. To do so, we propose a practical model for delay in which the queuing delay both at the source and the base station is considered. We use sparse code multiple access (SCMA), one of the candidate multiple access techniques in 5G cellular network, in our system model. Consequently, for a given number of traditional data streams, we can quantify the reduction in the traditional data sum rate caused by increasing the number of tactile data streams. In addition, we investigate the effect of quality of service coefficient, referred to as θ on the uplink sum rate of traditional data and show that there is a threshold behavior such that if θ gets larger than a certain value, the sum rate of traditional data drastically decreases toward zero.
MITRE at SemEval-2018 Task 11: Commonsense Reasoning without Commonsense Knowledge

This paper describes MITRE’s participation in SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge. The techniques explored range from simple bag-of-ngrams classifiers to neural architectures with varied attention and alignment mechanisms. Logistic regression ties the systems together into an ensemble submitted for evaluation. The resulting system answers reading comprehension questions with 82.27% accuracy.
Clustered miRNAs and their role in biological functions and diseases

MicroRNAs (miRNAs) are endogenous, small non‐coding RNAs known to regulate expression of protein‐coding genes. A large proportion of miRNAs are highly conserved, localized as clusters in the genome, transcribed together from physically adjacent miRNAs and show similar expression profiles. Since a single miRNA can target multiple genes and miRNA clusters contain multiple miRNAs, it is important to understand their regulation, effects and various biological functions. Like protein‐coding genes, miRNA clusters are also regulated by genetic and epigenetic events. These clusters can potentially regulate every aspect of cellular function including growth, proliferation, differentiation, development, metabolism, infection, immunity, cell death, organellar biogenesis, messenger signalling, DNA repair and self‐renewal, among others. Dysregulation of miRNA clusters leading to altered biological functions is key to the pathogenesis of many diseases including carcinogenesis. Here, we review recent advances in miRNA cluster research and discuss their regulation and biological functions in pathological conditions.