Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Text Summarization Using Intenal and Extemal Information

Sentence ranking is an important step of an extractive text summarization process. Traditionally, sentences are ranked using the information internal to the specified document, that is, they only use the data that is self-contained in the document. External methods use the information that is not necessarily contained in the document, such as manual annotation, labeling, etc. In this paper, we propose a hybrid summarization method that combines the internal methods and the external methods for improving text summarization performance. Comparisons of our proposed summarization system with some state-of-the art summarization systems reveal that our proposed approach is effective.
Handwritten Digit Recognition using DAISY Descriptor: A Study

Handwritten digit recognition is a highly evolved research domain. The major issues that make this domain challenging are different photometric discrepancies, along with computation complexity. A script invariant feature vector is designed here based on the concept of the DAISY descriptor which has previously been applied in different research domains. We have applied this feature descriptor after suitable customization to fit it into the aforesaid classification problem. We have tested the same on handwritten digits written in four different scripts namely Arabic, Bangla, Devanagari and Roman. Bangla dataset is in-house, while the remaining are the standard databases. Experimental results demonstrate the effectiveness of the said feature descriptor for digit recognition. It is a computationally inexpensive approach when compared to other state-of-the-art prevalent architectures like LSTM or CNN.
A 130 nm CMOS Power Management Unit With a Multi-Ratio Core SC DC–DC Converter for a Supercapacitor Power Supply

In recent years, switched capacitor (SC) DC–DC converters have been gaining interest as an attractive solution for implementing power management solutions in small scale low power systems, such as Internet of Things remote sensor nodes. Since switch capacitor circuits can be fully integrated in bulk CMOS technology, the number of external components is reduced, thus decreasing both the production costs and the volume of the system. This brief presents a power management unit using a multi-ratio SC DC–DC converter, and its controlling circuits, designed in a 130 nm bulk CMOS technology occupying an area of 0.138 mm2. It provides a constant supply voltage of 0.9 V for a maximum output power of 1 mW, from an input supercapacitor voltage ranging from 1.2 to 2.3 V. The measured results show a conversion efficiency peak of 80.4%.
Primary Hyperparathyroidism due to Parathyroid Adenoma Originated from Supernumerary Gland

Introduction The variability of the location of the parathyroid glands is directly related to the events that occur during embryonic development. The impact that an individual submits more than four parathyroid glands is close to 13%. However the presentation of a parathyroid adenoma in a supernumerary gland is an uncommon event. Case report A 30-year-old man diagnosed with primary hyperparathyroidism with matching findings on ultrasonography and scintigraphy for parathyroid adenoma localization lower left regarding the thyroid gland. A cervicotomy explorer showed four orthotopic parathyroid glands. The biopsy of the inferior left gland was normal. No signs of adenoma were seen in the biopsy. Following mobilization of the ipsilateral thyroid lobe, fifth parathyroid gland was found increased significantly in size than proceeded to remove, confirming the diagnosis of adenoma. After the excision, the levels of serum calcium and parathyroid hormone were normalized. Conclusions The presentation of a parathyroid adenoma in a supernumerary gland is a challenge for the surgeon. The high sensitivity having different imaging techniques has been a key to locate preoperatively the pathological parathyroid gland. Analytical or clinical persistence of primary hyperparathyroidism after parathyroid surgery can occur if the location of the adenoma is a supernumerary or ectopic gland location.
Congenital Adrenal Hyperplasia Due to Steroid 21-Hydroxylase Deficiency: An Endocrine Society Clinical Practice Guideline.

Objective To update the congenital adrenal hyperplasia due to steroid 21-hydroxylase deficiency clinical practice guideline published by the Endocrine Society in 2010. Conclusions The writing committee presents updated best practice guidelines for the clinical management of congenital adrenal hyperplasia based on published evidence and expert opinion with added considerations for patient safety, quality of life, cost, and utilization.
Nanostructured p-TiO2/n-GaN heterostructure as a potential photoelectrode for efficient charge separation

This work proposes p-TiO2/n-GaN as a new semiconductor heterostructure, which holds great promise as a photoelectrode material. To fabricate p-TiO2/n-GaN heterostructures, wurtzite GaN is grown in two different morphologies by molecular beam epitaxy, and a TiO2 overlayer is formed by atomic layer deposition. The XRD and Raman experiments confirm the anatase crystal structure of TiO2 and SEM shows the conformal coating of TiO2 on GaN. The system with GaN nanowall network morphology (TiO2/GaN NWN, calls as TGN) showed better photoelectrochemical response with a photocurrent density of ∼0.65 mA cm−2 and an IPCE of 17% compared to 0.24 mA cm−2 and 6% of the planar heterostructure (TiO2/GaN epilayer, called TGE), at an applied bias of 1.24 V and at an incident power of only 13 mW cm−2. Chronoamperometric analysis show that electrodes are highly stable. The p–n diagram derived by using the data from cathodoluminescence (CL) and valence band (VB) spectra showed higher barrier height for the TGN structure due to interfacial band bending, and thus, favoring photogenerated charge separation. The evolution of hydrogen in the form of bubbles is visually evident at an applied bias of −0.56V for TGN. The enhanced photocurrent density, cathodic shift in the onset potential and the stability show the superiority of TGN to TGE in charge separation as well as in the photoelectrochemical performance.
Giant Bilateral Calvarial Hyperostosis Secondary to Small Unilateral Frontal Meningioma

ABSTRACT A 28-year-old male patient presented to us with bilateral frontal hyperostosis associated with a small unilateral frontal intracranial meningioma. He underwent successful excision of the involved bone and repair of the large cranial defect using a titanium mesh. Histological examination revealed tumor infiltration of the overlying bone. Surgical challenges in the management of such a case are also discussed.
Research on Software Testing Technology Under the Background of Big Data

With the progress of science and technology, computer technology continues to improve, the Internet has produced a large amount of data information, mankind has entered the era of “big data”, has great influence in this era of complex software industry development, the software product has penetrated into various industries in various fields of society. Under such a background, one of the problems that people need to solve is the quality, stability and reliability of software products. The key to solve this problem is software testing. This paper describes the current situation of the software testing technology under the background of big data, the purpose of the test, the testing principles, the testing methods, the development process of software testing technology based on the UML model, and the prospect of the development.
Altered DNA Methylation Sites in Peripheral Blood Leukocytes from Patients with Simple Steatosis and Nonalcoholic Steatohepatitis (NASH)

Background The aim of this study was to identify DNA methylation sites in peripheral blood leukocytes from patients with histologically confirmed nonalcoholic fatty liver disease (NAFLD) that included simple hepatic steatosis and nonalcoholic steatohepatitis (NASH). Material/Methods DNA was isolated from peripheral blood leukocytes from patients with histologically diagnosed NAFLD (n=35), including simple hepatic steatosis (n=18) and NASH (n=17). Healthy controls included individuals without liver disease (n=30). DNA was hybridized, and DNA methylation was interrogated in an epigenome-wide association study (EWAS). DNA methylation levels (β-values) were correlated with serum lipid profiles, liver enzymes, and liver histology. Results Circulating blood leukocytes from 35 patients with NAFLD (simple steatosis and NASH) contained 65 CpG sites, which represented 60 genes that were differentially methylated when compared with healthy controls. In the simple hepatic steatosis group (n=18), 42 methylated CpG sites were found to be associated with increased levels of serum alanine aminotransferase (ALT), and 32 methylated CpG sites were associated with increased serum lipid profiles. In the NASH group (n=17), when compared with the simple hepatic steatosis group, methylated CpG sites showed significant correlations with the presence of lobular inflammation compared with hepatic steatosis and fibrosis. Six differentially methylated CpG sites were identified in the ACSL4, CRLS1, CTP1A, SIGIRR, SSBP1 and ZNF622 genes, which were associated with histologically confirmed simple hepatic steatosis and NASH. Conclusions The study identified some key methylated CpG sites from peripheral blood leukocytes, which might be used as serum biomarkers to stratify NAFLD patients into simple hepatic steatosis and NASH.
Influence of moisture and filler surface properties on the dielectric spectrum of epoxy-based nanocomposites

Since the interfacial area between nanoparticles and a polymer matrix can influence the overall characteristics of a nanocomposite, it is the aim to understand the nature and properties of such interfaces. In the present study, epoxy-based nanocomposites with different materials and weight percentages of nanoscale fillers (SiO2, Al2O3 and TiO2) were investigated with respect to the impact of water content on their dielectric spectrum. In general, the permittivity of the bulk material increases with increasing moisture and filler content. In particular, moisture in nanocomposites with hydrophilic particles leads to an additional maximum in the spectra of the imaginary part of permittivity.
Embedded-State Latent Conditional Random Fields for Sequence Labeling

Complex textual information extraction tasks are often posed as sequence labeling or shallow parsing, where fields are extracted using local labels made consistent through probabilistic inference in a graphical model with constrained transitions. Recently, it has become common to locally parametrize these models using rich features extracted by recurrent neural networks (such as LSTM), while enforcing consistent outputs through a simple linear-chain model, representing Markovian dependencies between successive labels. However, the simple graphical model structure belies the often complex non-local constraints between output labels. For example, many fields, such as a first name, can only occur a fixed number of times, or in the presence of other fields. While RNNs have provided increasingly powerful context-aware local features for sequence tagging, they have yet to be integrated with a global graphical model of similar expressivity in the output distribution. Our model goes beyond the linear chain CRF to incorporate multiple hidden states per output label, but parametrizes them parsimoniously with low-rank log-potential scoring matrices, effectively learning an embedding space for hidden states. This augmented latent space of inference variables complements the rich feature representation of the RNN, and allows exact global inference obeying complex, learned non-local output constraints. We experiment with several datasets and show that the model outperforms baseline CRF+RNN models when global output constraints are necessary at inference-time, and explore the interpretable latent structure.
Development of a programmable partial discharge generator for the evaluation of partial discharge measuring devices

Partial discharges (PD) measurement provide valuable information for assessing the condition of the insulation elements in high voltage (HV) electrical grids. During the last three decades, several instruments integrated with specific technical functionalities have been developed in order to perform accurate diagnostics when temporary or monitoring measurements are carried out on-site and on-line. Some electrical utilities, maintenance companies and large electricity consumers have defined technical specifications trying to select the most appropriate PD measuring systems, but in general, no tests are performed to check their capability to perform appropriate and accurate diagnostics. Furthermore, no standard exists to define what type of evaluation should be required to assess the efficacy of this type of instrumentation. In this paper, a reference PD generator developed for the evaluation of the functional features of PD measuring and diagnostic instruments is presented. This PD generator enables the characterization of the technical functionalities of commercial PD instruments in a controlled and homogenous way and without the requirement of apply HV in a test facility. Reference analogue PD time series with superimposed electrical noise time sequences are generated simulating real acquisitions of on-line PD measurements.
Sailfish: A Cooperative Data Retrieving Scheme in the Distributed Cloud for Interactive Applications

I378 applications on mobile devices are attracting more users nowadays. Unfortunately, mobile devices have limited resources while interactive applications run compute-intensive algorithms with extreme latency needs. Cloud offloading is proposed to compensate for the computing capacity. However, how to retrieve data efficiently in distributed clouds remains to be a significant open problem. In this paper, we propose Sailfish, a cooperative parallel-flow data retrieving framework which can reduce the latency of all users to support interactive applications. We further formulate the Data Retrieving Minimization (DRM) problem to minimize the sum of all users' data retrieving latency under bandwidth constraints. To solve large scale problems efficiently, we design a high-efficient Parallel-Flow Greedy Algorithm (PFGA) that leverages parallel flows to retrieve data from multiple cloud storage servers. We implement PFGA and evaluate it with extensive trace-based simulation. Evaluation results demonstrate all users' data retrieving latency of PFGA outperforms that of the state of the art by up to 68.3%.
Gray Box Modeling of Power Transformer Windings Based on Design Geometry and Particle Swarm Optimization Algorithm

Reliable models to predict the fast transient response of transformer windings are categorized into three groups: 1) white box; 2) black box; and 3) gray box models. Each group is applicable to solve a certain problem and includes its own advantages, hardly replacable by another group. The gray box methodology is a compromise between black and white box approaches which is investigated profoundly in this paper. A new method based on design geometry estimation is applied to accomplish transient simulation. The introduced procedure is probed on a noninterleaved double disk winding. Simulation and experimental results confirm that the gray box approach is applicable to both terminal and internal response estimation of a transformer when there is no knowledge of the transformer's internal specifications. The parameter identification of the model is performed by the particle swarm optimization algorithm.
Disability Adjusted Life Years due to Ischaemic Stroke Preventable by Real-Time Stroke Detection—A Cost-Utility Analysis of Hypothetical Stroke Detection Devices

Background: Ischaemic stroke remains a significant contributor to permanent disability world-wide. Therapeutic interventions for acute ischaemic stroke (AIS) are available, but need to be administered early after symptom onset in order to be effective. Currently, one of the main factors responsible for poor clinical outcome is an unnecessary long time between symptom onset and arrival at a hospital (pre-hospital delay). In the future, technological devices with the capability of real-time detection of AIS may become available. The health economic implications of such devices have not been explored. Methods: We developed a novel probabilistic model to estimate the maximally allowable annual costs of different hypothetical real-time AIS detection devices in different populations given currently accepted willingness-to-pay thresholds. Distributions of model parameters were extracted from the literature. Effectiveness of the intervention was quantified as reduction in disability-adjusted life-years associated with faster access to thrombolysis and mechanical thrombectomy. Incremental costs were calculated from a societal perspective including acute treatment costs and long-term costs for nursing care, home help, and loss of production. The impact of individual model parameters was explored in one-way and multi-way sensitivity analyses. Results: The model yields significantly shorter prehospital delays and a higher proportion of acute ischaemic patients that fulfill the time-based eligibility criteria for thrombolysis or mechanical thrombectomy in the scenario with a real-time stroke detection device as compared to the control scenario. Depending on the sociodemographic and geographic characteristics of the study population and operating characteristics of the device, the maximally allowable annual cost for the device to operate in a cost-effective manner assuming a willingness-to-pay threshold of GBP 30.000 ranges from GBP 22.00 to GBP 9,952.00. Considering the results of multiway sensitivity analyses, the upper bound increases to GBP 29,449.10 in the subgroup of young patients with a very high annual risk of ischaemic stroke (50 years/20% annual risk). Conclusion: Data from probabilistic modeling suggest that real-time AIS detection devices can be expected to be cost-effective only for a small group of highly selected individuals.
A Technique of Forced Expiratory Noise Time Evaluation Provides Distinguishing Human Pulmonary Ventilation Dynamics During Long-Term Head-Down and Head-Up Tilt Bed Rest Tests Simulating Micro and Lunar Gravity

Estimating the effect of microgravity/hypogravity on pulmonary ventilation function remains topical. Recently developed acoustic techniques based on the evaluation of the forced expiratory noise time (FETa) were hypothesized to be a promising tool for this aim. The aim of the protocol is to study the effect of two different modalities of bed rest space simulations (microgravity and lunar gravity) on FETa and spirometric indices. The FETa in the frequency band of 200–2000 Hz, recorded above human trachea, was evaluated. The 21st-day exposure to 6 degree head-down tilt (HDT) bed rest, simulating microgravity, and 9.6 degree head-up tilt (HUT) bed rest with head-zero tilt (HZT) rest intervals (HUT + HZT), simulating lunar gravity, in statistically identical subgroups of five and six healthy male volunteers, was studied. In the course of HDT bed rest, a significant elongation of FETa was found in relation to background measurements in “sitting” position (p = 0.016). The effect corresponded to a significant decrease of basic spirometric indices (p < 0.02). Moreover, FETa provided reliable discrimination of HDT and HUT + HZT bed rest tests (p = 0.018), while spirometric indices did not (p > 0.05). Based on previously found correlations (Korenbaum and Pochekutova, 2008; Malaeva et al., 2017), a FETa elongation in response to HDT bed rest was attributed to an increase of aerodynamic resistance of the respiratory tract. The technique seems promising to monitor human pulmonary ventilation dynamics in long-term space missions; however, new studies are welcome to verify it in real spaceflight.
The sympathetic nervous system regulates skeletal muscle motor innervation and acetylcholine receptor stability

Symptoms of autonomic failure are frequently the presentation of advanced age and neurodegenerative diseases that impair adaptation to common physiologic stressors. The aim of this work was to examine the interaction between the sympathetic and motor nervous system, the involvement of the sympathetic nervous system (SNS) in neuromuscular junction (NMJ) presynaptic motor function, the stability of postsynaptic molecular organization, and the skeletal muscle composition and function.
Therapeutic Potential of Fulvic Acid in Chronic Inflammatory Diseases and Diabetes

Chronic inflammatory diseases like diabetes are on a rise in the Western world. Based on the tsunami of new cases every year, new therapeutic measures must be considered. A promising avenue might involve the attenuation of underlying inflammation through natural health products (NHPs). This is because most NHPs have a rich history in traditional medicine and might be considered safer under appropriate doses and conditions. However, the biggest impediment in NHP research is that rarely do these products come with verified health benefits or dosing schedules established through modern scientific research. Fulvic acid (FvA), one such NHP, comes from humic substances produced by microorganisms in soil. Traditional medicine and modern research claim FvA can modulate the immune system, influence the oxidative state of cells, and improve gastrointestinal function; all of which are hallmarks of diabetes. This minireview outlines the available peer-reviewed research on FvA and examines its anecdotal health claims. We show that although available research has been minimal, there is substantial evidence to pursue FvA research in preventing chronic inflammatory diseases, including diabetes.
Switched-Capacitor Power Management Integrated Circuit for Autonomous Internet of Things Node

A power management integrated circuit for an energy autonomous device is presented. It is based on a configurable 2:1 switched capacitor converter that is capable of delivering a maximum current to always-on and duty-cycled loads equal to 5 <inline-formula> <tex-math notation="LaTeX">$ \mu \text{A}$ </tex-math></inline-formula> and 2 mA, respectively, from a thin-film 4.2-V lithium battery. The circuit is designed and implemented using the 0.8-<inline-formula> <tex-math notation="LaTeX">$ \mu \text{m}$ </tex-math></inline-formula> CMOS transistors of a BCD technology and exploits off-chip ceramic capacitors. Power conversion efficiency as high as 93% in the active mode and 80% in the sleep mode, despite the large variation range of the output current, is achieved.
A Combined Fully Convolutional Networks and Deformable Model for Automatic Left Ventricle Segmentation Based on 3D Echocardiography

Segmentation of the left ventricle (LV) from three-dimensional echocardiography (3DE) plays a key role in the clinical diagnosis of the LV function. In this work, we proposed a new automatic method for the segmentation of LV, based on the fully convolutional networks (FCN) and deformable model. This method implemented a coarse-to-fine framework. Firstly, a new deep fusion network based on feature fusion and transfer learning, combining the residual modules, was proposed to achieve coarse segmentation of LV on 3DE. Secondly, we proposed a method of geometrical model initialization for a deformable model based on the results of coarse segmentation. Thirdly, the deformable model was implemented to further optimize the segmentation results with a regularization item to avoid the leakage between left atria and left ventricle to achieve the goal of fine segmentation of LV. Numerical experiments have demonstrated that the proposed method outperforms the state-of-the-art methods on the challenging CETUS benchmark in the segmentation accuracy and has a potential for practical applications.