Miracle-dz/UniFAR-FTUs huggingface dataset:
Female mice lacking ERβ display excitatory/inhibitory synaptic imbalance to drive the pathogenesis of temporal lobe epilepsy

Epilepsy is a highly prevalent and drug-refractory neurological disorder characterized by spontaneous recurrent seizures. Estrogen is identified to be proconvulsant and lowers the seizure threshold of female epilepsy. Estrogen receptor β (ERβ) has been proposed to mediate neuroprotection in epilepsy, although the underlying mechanism remains unknown. Rationale: In this study, we investigated the role of ERβ in the epileptogenesis of female temporal lobe epilepsy (TLE). Methods: Immunohistochemistry, immunofluorescence, western blots, Golgi staining, 1H MRS and whole-cell patch-clamp were used to evaluate ERβ expression, pathological changes, and synaptic excitation /inhibition (E/I) balance in female TLE patients and ovariectomized (OVX) chronic epileptic mice. Electroencephalogram (EEG) recordings were recorded to evaluate the epileptic susceptibility in OVX WT and ERβ-/- mice. And high-throughput RNA-sequence was performed to identify differential expression genes (DEGs) which can elucidate the potential mechanism of ERβ regulating the seizure susceptibility. Results: ERβ expression was decreased in the brains of female TLE patients and OVX chronic epileptic mice. ERβ deletion enhanced seizure susceptibility and exacerbated the imbalance of synaptic E/I in hippocampal CA1 area of OVX epileptic mice. In line with these observations, RNA-sequence data further identified glutamine ligase (GLUL) as the target of ERβ involved in regulating synaptic E/I in CA1. Furthermore, ERβ agonist WAY-200070 markedly suppressed epileptic phenotypes and normalized GLUL expression in CA1 region of kainic acid (KA) induced OVX chronic epileptic model. Conclusions: Our data provide novel insight into the pathogenesis of female TLE, and indicate ERβ provides a new therapeutic strategy for female TLE patients.
Impaired activity of circulating EPCs and endothelial function are associated with increased Syntax score in patients with coronary artery disease

It has previously been shown that the number of endothelial progenitor cells (EPCs) is negatively correlated with Syntax score in patients with coronary artery disease (CAD). However, the association between alterations in EPC function and Syntax score is still unknown. The present study evaluated the association between the activity of EPCs as well as endothelial function and Syntax score in patients with CAD and investigated the underlying mechanisms. A total of 60 patients with CAD were enrolled in 3 groups according to Syntax score, and 20 healthy subjects were recruited as the control group. The number and migratory, proliferative and adhesive activities of circulating EPCs were studied. The endothelial function was measured by flow-mediated dilatation (FMD) and the levels of nitric oxide (NO) in plasma or secreted by EPCs were detected. The number and activity of circulating EPCs were lower in patients with a high Syntax score, which was similar to the alteration in FMD. The level of NO in plasma or secreted by EPCs also decreased as Syntax score increased. There was a negative association between FMD or circulating EPCs and Syntax score. A similar association was observed between the levels of NO in plasma or secreted by EPCs and Syntax score. Patients with CAD who had a higher Syntax score exhibited lower EPC numbers or activity and weaker endothelial function, which may be associated with attenuated NO production. These findings provide novel surrogate parameters for evaluation of the severity and complexity of CAD.
Characterization of the DNA‐assisted purification of single‐walled carbon nanotubes

Carbon nanotubes (CNTs) possess outstanding structural, mechanical, and electronic properties. Nevertheless, to achieve their full potential, many problems still need to be solved, including the development of an easy purification procedure, the design of functionalization chemistries that result in increased solubility of the CNTs without altering their properties, and the development of a simple route for the attachment of aligned CNTs on solid substrates. DNA offers a solution to the previous challenges. Recently, DNA‐functionalized single‐walled carbon nanotubes (SWNTs) have been prepared by our group and attached on gold by the self‐assembling technique [1, 2]. We therefore decided to perform an in‐depth study of the DNA‐assisted functionalization of SWNTs, which leads to their purification. The results showed a decrease in the SWNTs impurities after functionalization with DNA and demonstrated that the method used is a straightforward and time‐effective route for the purification of SWNTs at room temperature. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
InFeRno - an Intelligent Platform for Recognizing Pornographic Web Pages

We present InFeRno, an intelligent autonomous system to assess and arbitrate pornographic web page acquisition. In the processing pipeline, an adaptive Gamma correction method is applied on each assessed image in order to equalize excessive illumination, and to effectively harness skin segmentation. Based on the contour of each segmented image, a series of low-level features are extracted in the course of discriminating pornographic images. A multi-objective Support Vector Machine scheme for classifying images is proposed, which we evaluate experimentally. Our evaluation of the overall system demonstrates that the proposed system exhibits satisfactory results in discriminating pornographic web pages.
Identification and validation of redox-immune based prognostic signature for hepatocellular carcinoma

The intimate interaction between redox signaling and immunity has been widely revealed. However, the clinical application of relevant therapeutic is unavailable due to the absence of validated markers that stratify patients. Here, we identified novel biomarkers for prognosis prediction in hepatocellular carcinoma (HCC). Prognostic redox-immune-related genes for predicting overall survival (OS) of HCC were identified using datasets from TCGA, LIRI-JP, and GSE14520. LASSO Cox regression was employed to construct the signature model and generate a risk score in the TCGA cohort. The signature contained CDO1, G6PD, LDHA, GPD1L, PPARG, FABP4, CCL20, SPP1, RORC, HDAC1, STC2, HDGF, EPO, and IL18RAP. Patients in the high-risk group had a poor prognosis compared to the low-risk group. Univariate and multivariate Cox regressions identified this signature as an independent factor for predicting OS. Nomogram constructed by multiple clinical parameters showed good performance for predicting OS indicated by the c-index, the calibration curve, and AUC. GSEA showed that oxidoreductase activity and peroxisome-related metabolic pathways were enriched in the low-risk group, while glycolysis activity and hypoxia were higher in the high-risk group. Furthermore, immune profiles analysis showed that the immune score and stromal score were significantly decreased in the high-risk group in the TCGA cohort. There was a considerably lower infiltration of anti-tumor immune cells while a higher proportion of pro-tumor immune cells in silico. Immune markers were distinctly expressed between the subgroups, and redox-sensitive immunoregulatory biomarkers were at higher levels in the high-risk group. Altogether, we identified a redox-immune prognostic signature. A more severe redox perturbation-driven immunosuppressive environment in the high-risk group stratified by the signature may account for poor survival. This may provide a clue to the combined therapy targeting redox and immune in HCC.
Promoter hypermethylation of early B cell factor 1 (EBF1) is associated with cholangiocarcinoma progression

DNA hypermethylation in a promoter region causes gene silencing via epigenetic changes. We have previously reported that early B cell factor 1 (EBF1) was down-regulated in cholangiocarcinoma (CCA) tissues and related to tumor progression. Thus, we hypothesized that the DNA hypermethylation of EBF1 promoter would suppress EBF1 expression in CCA and induce its progression. In this study, the DNA methylation status of EBF1 and mRNA expression levels were analyzed in CCA and normal bile duct (NBD) tissues using a publicly available database of genome-wide association data. The results showed that the DNA methylation of EBF1 promoter region was significantly increased in CCA tissues compared with those of NBD. The degree of methylation was negatively correlated with EBF1 mRNA expression levels. Using methylation-specific PCR technique, the DNA methylation rates of EBF1 promoter region were investigated in CCA tissues (n=72). CCA patients with high methylation rates of EBF1 promoter region in the tumor tissues (54/72) had a poor prognosis. Higher methylation rates of EBF1 promoter region have shown in all CCA cell lines than that of an immortal cholangiocyte cell line (MMNK1). Upon treatment with the DNA methyltransferase inhibitor 5-Aza-dC, increased EBF1 expression levels and reduced DNA methylation rates were observed in CCA cells. Moreover, restoration of EBF1 expression in CCA cells led to inhibition of cell growth, migration and invasion. In addition, RNA sequencing analysis suggested that EBF1 is involved in suppression of numerous pathways in cancer. Taken together, DNA hypermethylation in the EBF1 promoter region suppresses EBF1 expression and induces CCA progression with aggressive clinical outcomes.
Morphological, Molecular and Pollen Grain Investigations of Salix Species in Egypt

Genus Salix is among family Salicaceae, distributing in the northern hemisphere. It is represented in Egypt by two species (Salix mucronata and Salix tetrasperma). The classification of Salix at the generic and infra-generic levels is still outstanding. We have agreed to list the Egyptian species of this genus. We collected them during field trips to most Egyptian habitats; fresh and herbarium specimens were subjected to taxonomic revision based on morphological characters; scanning electron microscope (SEM) for pollen grains; isozyme analysis using esterase and peroxidase enzymes and genetic diversity using random amplified polymorphic DNA (RAPD). We recorded that both sexes of S. mucronata existed but there were only male trees from S. tetrasperma. SEM of pollen grain revealed that there were many differences between them. Also, the application of isozyme analysis giving 12 sex indicating bands. In addition, ten RAPD primers retrieved a total of 227 amplified bands (77 for female S. mucronata, 74 for male S. mucronata and 76 for male S. tetrasperma).
Shape Optimization of conductive-media interfaces that maximize heat transfer using a BEM-Isogeometric solver

In this paper, we present a method that combines the Boundary Element Method (BEM) with IsoGeometric Analysis (IGA) for numerically solving the system of Boundary Integral Equations (BIE) arising in the context of a 2-D steady-state heat conduction problem across a periodic interface separating two conducting and conforming media. Our approach leads to a fast converging solver that achieves the same level of accuracy for fewer degrees of freedom, when compared with low-order BEM. Additionally, an optimization procedure is developed and test cases of interface’s shape optimization, with the aim of heat transfer maximization under given constraints, are demonstrated.
Microstructure and chemical wet etching characteristics of AlN films deposited by ac reactive magnetron sputtering

The influence of the surface morphology of a molybdenum underlayer on the crystallinity and etchability of reactively sputtered c-axis oriented aluminum nitride thin films was investigated. Atomic force microscopy, scanning electron microscopy, transmission electron microscopy, high resolution x-ray diffraction, and defect selective chemical etching were used to characterize the microstructure of the Mo and AlN films. 1000nm thick films of AlN with a full width at half maximum (FWHM) of the x-ray rocking curve ranging from 1.1° to 1.9° were deposited on 300nm thick Mo underlayers with a FWHM of around 1.5°. The Ar pressure during the Mo deposition had a critical effect on the Mo film surface morphology, affecting the structure of the subsequently deposited AlN films and, hence, their wet etching characteristics. AlN films deposited on Mo sputtered at a relatively high pressure could not be etched completely, while AlN films deposited on low pressure Mo etched more easily. Postdeposition etching of the Mo .
Ultrahigh Photoresponse of Few‐Layer TiS3 Nanoribbon Transistors

Here, we isolate thin TiS3 ribbons, a layered direct band gap semiconductor (1.1 eV, well suited for detection all across the visible spectrum), thus far almost unexplored. We fabricate field effect transistors and study their electrical characteristics and optoelectronic properties. The measured FET characteristics show mobilities up to 2.6 cm^2/Vs and ON/OFF ratios up to 10^4. Under illumination, the TiS3 NR-FETs present an ultrahigh photoresponse of 2910 A/W and fast rise/fall times of ~4 ms. In addition, we measure cutoff frequencies (f3dB) up to 1000 Hz. The strong combination of ultrahigh sensitivity all along the visible spectrum and fast time response of TiS3 nanoribbon transistors put them among the best nanoscale photodetectors to date.
The Presence of Pyrrolo Quinoline Quinone (PQQ) in Eukaryotic Tissue Extracts

The pyrroloquinoline quinone (PQQ) is a novel cofactor of certain bacterial enzymes. It was described for the first time in Methylobacterium extorquens associated to ethanol dehydrogenase (FloresEncarnación et al., 2004; Misra et al., 2012; Shen et al., 2012). So, PQQ has been reported to be associated with dehydrogenases and oxidases, functioning as an enzymatic cofactor in some Gramnegative bacteria (Flores-Encarnación et al., 2014). For example, PQQ-glucose dehydrogenase was isolated from Gluconobacter suboxydans and Klebsiella aerogenes. This enzyme was found to be associated to the cytoplasmic membrane and functionally linked to respiratory chain (Meyer et al., 2013). In more recent years, in animal cells it has been reported that PQQ has a protector effect in cardiac lesions; it also prevents liver injury eliminating free radicals due to its antioxidant potent properties (50-100 times more effective than ascorbic acid) (Akagawa et al., 2016; Feng et al., 2014; Jia et al., 2015; Rucker et al., 2009; Tao et al., 2007). PQQ is a polyphenolic compound found in plants, various foods and biological fluids (Flores-Encarnación et al., 2017; Noji et al., 2007). The present study aimed to seek evidence the presence of PQQ in eukaryotic tissue extracts.
WireGuard Linux Kernel Integration Techniques

WireGuard is a formally veriﬁed secure tunneling protocol written and designed with the Linux Kernel as its primary operating context. Several design considerations at the protocol layer were considered in order to make it safe and simple to implement into an operating system kernel. In implementing WireGuard for Linux, several techniques are used for achieving performance and for doing cryptographic operations at the struct net_device level. This paper describes those techniques and protocol considerations, including a discussion of GSO, queueing, zero-copy, crypto API, FPU batching, multi-core algorithms, and socket routing semantics.
Movie Sound, Part 2: Preference and Attribute Ratings of Six Listening Environments

In this study, the assessors evaluated the alterations in the sound field of six movie listening environments. The sound fields of the listening environments were auralized to an anechoic listening room with 45 loudspeakers so that assessors could compare the rooms with each other directly. 31 experienced listeners evaluated five descriptive attributes on a continuous scale for each room with two program material items, dialogue and music. The preference ratings for the rooms were also collected. The perceptual evaluations were compared to the objective electroacoustic data of the rooms. The sense of space, clarity, and distance match the measured clarity C 50 at the middle frequencies, while the brightness matches the level of the high frequencies in the electroacoustic response above 4 kHz. No psychoacoustical support was found for the current standards, according to which the high frequencies should be attenuated more in large cinemas with longer reverberation than in small cinemas. It turned out that the movie sound professionals do not prefer either too dead or too live listening environments.
The Societal Implications of Deep Reinforcement Learning

Deep Reinforcement Learning (DRL) is an avenue of research in Artificial Intelligence (AI) that has received increasing attention within the research community in recent years, and is beginning to show potential for real-world application. DRL is one of the most promising routes towards developing more autonomous AI systems that interact with and take actions in complex real-world environments, and can more flexibly solve a range of problems for which we may not be able to precisely specify a correct ‘answer’. This could have substantial implications for people’s lives: for example by speeding up automation in various sectors, changing the nature and potential harms of online influence, or introducing new safety risks in physical infrastructure. In this paper, we review recent progress in DRL, discuss how this may introduce novel and pressing issues for society, ethics, and governance, and highlight important avenues for future research to better understand DRL’s societal implications. This article appears in the special track on AI and Society.
Arsenic occurrence in Europe: emphasis in Greece and description of the applied full-scale treatment plants

The presence of arsenic in groundwater comprises a worldwide problem and is recognized as a human health threat. The present work summarizes the arsenic contamination in Europe, where many countries are affected by elevated arsenic concentrations (i.e. Greece, Hungary, Romania, Croatia, Serbia, Turkey, and Spain). In particular, in Greece, several groundwater resources contain arsenic at increased concentrations, which render these water sources as non-potable. Arsenic-affected regions in Greece are classified mainly in three categories, namely, the geothermal-affected waters, the alluvial deposits of rivers and aquifers, and those influenced by mineralization and are typically close to mining activities. In Greece, arsenic concentrations in geothermal waters vary from 30 to 4,500 μg/L, in the regions close to alluvial deposits from 15 to 100 μg/L and in areas affected by mining activities from 20 to 60 μg/L. Arsenic-removal plants have been installed in several towns in Greece. The applied removal technologies are mainly based on chemical precipitation with FeClSO4 or adsorption onto iron oxide materials, such as Bayoxide, granular ferric hydroxide or AquAsZero. In the cases where As(III) is present, biological oxidation or ozonation is applied to convert As(III) to the less mobile forms of As(V). Specific arsenic removal capacity at an equilibrium concentration equal to the regulation limit of 10 μg/L was between 1.7 and 4.2 mg As/g of adsorbent for adsorption processes and between 18 and 59 mg As/g Fe for chemical precipitation.
Automatic Unit Test Generation for Machine Learning Libraries: How Far Are We?

Automatic unit test generation that explores the input space and produces effective test cases for given programs have been studied for decades. Many unit test generation tools that can help generate unit test cases with high structural coverage over a program have been examined. However, the fact that existing test generation tools are mainly evaluated on general software programs calls into question about its practical effectiveness and usefulness for machine learning libraries, which are statistically orientated and have fundamentally different nature and construction from general software projects. In this paper, we set out to investigate the effectiveness of existing unit test generation techniques on machine learning libraries. To investigate this issue, we conducted an empirical study on five widely used machine learning libraries with two popular unit testcase generation tools, i.e., EVOSUITE and Randoop. We find that (1) most of the machine learning libraries do not maintain a high-quality unit test suite regarding commonly applied quality metrics such as code coverage (on average is 34.1%) and mutation score (on average is 21.3%), (2) unit test case generation tools, i.e., EVOSUITE and Randoop, lead to clear improvements in code coverage and mutation score, however, the improvement is limited, and (3) there exist common patterns in the uncovered code across the five machine learning libraries that can be used to improve unit test case generation tasks.
Deep Learning Methodologies for UWB Ranging Error Compensation

Ultra-Wideband is becoming extensively used in many kinds of robot and human positioning systems. From industrial robotic tasks to drones used for search and rescue operations, this high-accuracy technology allows to locate a target with an error of a few centimeters, outperforming other existing low-cost ranging methods like Bluetooth and Wi-Fi. This fact also lead Apple to equip the latest IPhone 11 with an UWB module specifically for precise localization applications. Unfortunately, this technology is very accurate only in Line-Of-Sight. Indeed, performances degrade significantly in Non-Line-Of-Sight scenarios, in which walls, furniture or people obstruct the direct path between the antennas. Moreover, reflections constitute another source of error, causing the receiver to detect multiple signals with different delays. The aim of this thesis is to compensate NLOS and multi-path errors and obtain a precise and reliable positioning system, that could allow to develop several service robotics applications that are now limited by unsatisfactory accuracies. Another fundamental goal is to guarantee a good scalability of the system to unseen scenarios, that is where even modern mitigation methods still fail. For this scope, a large dataset is built taking both LOS and NLOS measurements in different environments and experimenting on different types of obstacles. Then, modern deep learning methods are used to design a Convolutional Neural Network that estimates the error of the range estimates directly from raw Channel Impulse Response samples. Finally, a positioning test is conducted to verify the effectiveness of the method in a real scenario. The rest of the work is organized as follows. Chapter 1 introduces the theoretical bases that are needed to understand the context and the development of the thesis: UWB definition and features, main ranging methods, positioning algorithms, machine learning and deep neural networks. In Chapter 2, an overview of the state of the art is addressed, highlighting strenghts and limits of each of the existing methods. Chapter 3 describes the experimental set adopted for the range measurements and the building of the dataset, also comprehending the characteristics of low-cost sensors and all the employed hardware and software. Chapter 4 addresses the design of the Deep Learning models used to perform the correction of the range estimate and the strategy adopted to optimally train and test different variants. Chapter 5 shows and comments the results reached after the training of the models, highlighting the effect of environment and obstacles on the prediction accuracy. It also presents the final positioning test conducted in real-time. Finally, Chapter