Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Periostin in Angiogenesis and Lymphangiogenesis in Tumors

Simple Summary Cancers are common diseases that affect people of all ages worldwide. For this reason, continuous attempts are being made to improve current therapeutic options. The formation of metastases significantly decreases patient survival. Therefore, understanding the mechanisms that are involved in this process seems to be crucial for effective cancer therapy. Cancer dissemination occurs mainly through blood and lymphatic vessels. As a result, many scientists have conducted a number of studies on the formation of new vessels. Many studies have shown that proangiogenic factors and the extracellular matrix protein, i.e., periostin, may be important in tumor angio- and lymphangiogenesis, thus contributing to metastasis formation and worsening of the prognosis. Abstract Periostin (POSTN) is a protein that is part of the extracellular matrix (ECM) and which significantly affects the control of intracellular signaling pathways (PI3K-AKT, FAK) through binding integrin receptors (αvβ3, αvβ5, α6β4). In addition, increased POSTN expression enhances the expression of VEGF family growth factors and promotes Erk phosphorylation. As a result, this glycoprotein controls the Erk/VEGF pathway. Therefore, it plays a crucial role in the formation of new blood and lymphatic vessels, which may be significant in the process of metastasis. Moreover, POSTN is involved in the proliferation, progression, migration and epithelial-mesenchymal transition (EMT) of tumor cells. Its increased expression has been detected in many cancers, including breast cancer, ovarian cancer, non-small cell lung carcinoma and glioblastoma. Many studies have shown that this protein may be an independent prognostic and predictive factor in many cancers, which may influence the choice of optimal therapy.
Rocuronium versus Cisatracurium for Rapid Sequence Induction of Anesthesia in Morbidly Obese Patients

Introduction and Aim: Obesity is a challenging problem for anesthetists. Difficult airway with risk of aspiration and regurgitation increases with obesity. Therefore, the need for effective and safe drug for rapid induction of anesthesia is crucial to ensure fast good intubation condition. The aim of this study is to assess Rocuronium versus Cisatracurium for rapid sequence induction of anesthesia in morbidly obese patients. Patients and methods: This study included 60 patients with ASA physical status II, aged 21-40 years, BMI 35-40 kg/m 2 and scheduled for elective surgery under general anesthesia. Patients were classified into two equal groups: Group (R): received Rocuronium bromide (Esmeron) in a dose of 0.9 mg/kg (lean body mass) for intubation; Group (C): received Cisatracurium besylate (Nimbex) in a dose of 0.15 mg/kg (LBM) for intubation. Timing of intubation in seconds, intubation score (excellent, good, poor, or inadequate), and hemodynamic variables before induction (baseline), after induction and before injection of Neuro-muscular blocker (NMB), after injection of NMB and before endotracheal intubation and just after intubation were assessed and measured. Results: There was statistically significant decrease in the timing of intubation in R group (84.0 ± 18.50) as compared to C group (96.0 ± 13.29). However, there was no statistically significant difference in the intubation score among the two groups. There was significant decrease in heart rate and mean arterial blood pressure after the induction of anaesthesia as compared to the baseline in both groups; Heart rate and mean arterial blood pressure changes were comparable among the two groups all of the time. Conclusion: Rocuronium for rapid sequence induction in morbidly obese patients is associated with faster onset compared with cisatracurium, with comparable intubation condition and hemodynamic variables. We recommend further studies to be conducted for evaluation of both drugs with different doses.
The effect of housing systems on hoof diseases/disorders and percentage of culling in Holstein dairy cows

The objectives of this research were to investigate the effect of the housing system (tie-stall and free-stall barns) on the prevalence of hoof diseases/disorders, as well as on the percentage of culling in 6,348 Holstein dairy cows from 5 farms. During the three months of research the hoof care service on all farms collected records of causes of lameness, diagnoses and treatments. Functional and corrective hoof trimming was conducted by a professional farm trimmer. When all the registered diseases/disorders were observed as a percentage (all diseases = 100%), it was noticed that both housing systems were similarly affected by the same diseases/disorders. In this regard, White Line Disease occurred in both systems in prevalence of 0.5% - 1%, Toe Ulcer and Necrosis in 3% - 6%, Rusterholz Ulcer / Sole Ulcer in 20% - 23%, Digital Dermatitis in 18% - 20%, Interdigital Hyperplasia / Tyloma in 10% - 12%, Panaritium / Interdigital Phlegmon in 0.7% - 0.77%, while the prevalence of Mechanical Injury was negligible and in similar amounts - 0.2% - 0.5%. Cows in the free-stall barns were much more burdened with Dermatitis Interdigitalis / Heel Erosion Disease (39.11%) compared to cows in the bound housing system (20.40%). In contrast, diagnosed acute, chronic and haemorrhagic Laminitis was significantly more pronounced in the tie-stall barns (18.61%) than in the free-stall barns (0.88%). In the statistical analysis conducted, statistically significantly more diseases/disorders were registered in the tie-stall system than in the free housing system (P<0.01). During the three months of the study, the average percentage of culling in the free system was 5.4%, while in the tie-stall system it was 4.9%. This difference was not statistically significant (P>0.05).
Whole-exome sequencing using the xGen ™ DNA Library Preparation Kit family enables customizable workflows returning quality in consistent results

The xGen DNA Library Preparation Kit family provides flexibility by utilizing enzymatic fragmentation (EZ) or mechanical shearing (MC) methods that support multiple indexing strategies and generates libraries suitable for PCR-free or PCR-amplified workflows. Here, we show that use of both xGen DNA Library Preparation kit workflows maintains sequencing performance when used with xGen Exome Hybridization Panel v2 while offering additional flexibility in multiplexing. These results demonstrate that versatile whole exome capture workflows provide high on-target and low duplication rates, and deep, uniform coverage across all regions, regardless of GC-content. Exome sequencing is invaluable for sequencing only the protein-coding regions of the human genome. This method is performed using hybridization capture —a technique that uses biotin-modified oligonucleotide probes to “capture” the region of interest for sequencing. Exome capture provides significant sequencing advantages over whole-genome sequencing. Focusing only on the protein-coding exons lowers the cost and time of sequencing, as exons make up approximately 1% of the genome. In contrast to their small size contribution to the genome, exons contain 85% of variants associated with disease [ 1 ]. Whole exome sequencing (WES) is a practical method for mapping variants that are in the to better understand complex disorders [ 2 ]. It is a feasible option for population genetics and discovery science, or data mining, when searching for associations, or linking genes to phenotypes 3 ]. WES is also particularly useful in oncology studies, researchers to identify germline and somatic variants within coding regions of results assessed with key NGS performance metrics.
Synthesis and Photocatalytic Properties of Au-ZnSe Hybrid Nanorods for H 2 Generation

Hybrid nanocrystals which integrate multiple component into a single nanoparticle at nanoscale has attracted much research interest in recent years 1-6. The combination of several material enables the hybrid nanocrystals with synergetic optical and chemical properties2. Hybrid semiconductor-metal nanostructures, especially platinum (Pt) or gold (Au) nanoparticles decorated semiconductor nanocrystals, such as Au-CdSe7, Pt-CdSe8 AuCdS9, CdS-Pt, CdSe/CdS-Pt10, Au-Cu3P, and Au-Cu2O gained much attention because of the special property of these hybrid nanocrystals, such as the located surface Plasmon resonance effect (LSPR) of noble metals and outstanding charge separation ability12. Nobel semiconductor-metal hybrid nanoparticles like Au-CdSe, Pt-CdS work as co-catalyst by providing the active sites for reaction with lower activation barrier than semiconductors. The lifetime of charge carriers is also extended because of the enhanced rate of electronhole separation.12
Customized deep learning for precipitation bias correction and downscaling

Abstract. Systematic biases and coarse resolutions are major limitations of current precipitation datasets. Many deep learning (DL)-based studies have been conducted for precipitation bias correction and downscaling. However, it is still challenging for the current approaches to handle complex features of hourly precipitation, resulting in the incapability of reproducing small-scale features, such as extreme events. This study developed a customized DL model by incorporating customized loss functions, multitask learning and physically relevant covariates to bias correct and downscale hourly precipitation data. We designed six scenarios to systematically evaluate the added values of weighted loss functions, multitask learning, and atmospheric covariates compared to the regular DL and statistical approaches. The models were trained and tested using the Modern-era Retrospective Analysis for Research and Applications version 2 (MERRA2) reanalysis and the Stage IV radar observations over the northern coastal region of the Gulf of Mexico on an hourly time scale. We found that all the scenarios with weighted loss functions performed notably better than the other scenarios with conventional loss functions and a quantile mapping-based approach at hourly, daily, and monthly time scales as well as extremes. Multitask learning showed improved performance on capturing fine features of extreme events and accounting for atmospheric covariates highly improved model performance at hourly and aggregated time scales, while the improvement is not as large as from weighted loss functions. We show that the customized DL model can better downscale and bias correct hourly precipitation datasets and provide improved precipitation estimates at fine spatial and temporal resolutions where regular DL and statistical methods experience challenges.
DeepCon: An End-to-End Multilingual Toolkit for Automatic Minuting of Multi-Party Dialogues

In this paper, we present our minuting tool DeepCon, an end-to-end toolkit for minuting the multiparty dialogues of meetings. It provides technological support for (multilingual) communication and collaboration, with a specific focus on Natural Language Processing (NLP) technologies: Automatic Speech Recognition (ASR), Machine Translation (MT), Automatic Minuting (AM), Topic Modelling (TM) and Named Entity Recognition (NER). To the best of our knowledge, there is no such tool available. Further, this tool follows a microservice architecture, and we release the tool as open-source, deployed on Amazon Web Services (AWS). We release our tool open-source here http://www.deepcon. in.
Price Derivatives in Commodity Market

This article presents a new approach for pricing commodity derivatives. The key to this approach is the model calibration that makes the model prices of vanilla options match the market prices and the implied model dynamics be in good agreement with the characteristics of the historical data series. Our theoretical results show that the model can better capture the price and volatility dynamics. Empirical study shows that the model performs quite well.
and the Macroeconomy

This book originates from a set of notes I wrote in support of graduate and advanced undergraduate lectures in financial economics, macroeconomic dynamics, financial econometrics, and financial engineering. These notes have circulated for about 20 years under the title Lectures on Financial Economics. Unifying these notes into a coherent book was tantamount to engaging in a long and patient journey into historical intellectual developments as well as the interactions of ideas and theories with actual markets behaviors. I have attempted to synthesize the state of knowledge accumulated during 70 years of initially intermittent, and later incessant contributions to this very important field of economics.1 Finance has the potential to oil the wheels of the real economy. While economists still debate about the benefits of finance for our society, more than a dozen scholars researching this field may be counted as Nobel Prize laureates in economic sciences. Progress was sometimes faster than any attempts at organizing our thoughts. Initially, efforts at synthesis were focused on the mathematical structures of the pioneering work underlying the foundations of finance. Later, synthesis became more problematic as research work proliferated through such disparate domains including, among others, the evaluation of derivatives instruments, the behavior of markets over the business cycle, information problems in corporate finance and asset markets, and last but not least, the then-nascent econometrics of financial markets. The initial classics would often cover nonoverlapping spaces, as reviewed in section C of this introduction. We are still struggling with the creation of a comprehensive treatment of financial economics. This book is an attempt at such a treatment, an attempt at linking various theories and ideas to empirical puzzles and, sometimes, established market practice. Financial economics relies on sophisticated methods that have already received a comprehensive textbook treatment since at least the early classics. While this book still aims
Development of a concept for cybersecurity metrics classification

The development of the IT industry and computing resources allows the formation of cyberphysical social systems (CPSS), which are the integration of wireless mobile and Internet technologies and the combination of the Internet of things with the technologies of cyberphysical systems. To build protection systems, while minimizing both computing and economic costs, various sets of security profiles are used, ensuring the continuity of critical business processes. To assess/compare the level of CPSS security, various assessment methods based on a set of metrics are generally used. Security metrics are tools for providing up-to-date information about the state of the security level, cost characteristics/parameters from both the defense and attack sides. However, the choice of such sets is not always the same/understandable to the average person. This, firstly, leads to the absence of a generally accepted and unambiguous definition, which means that one system is more secure than another. Secondly, it does not take into account the signs of synergy and hybridity of modern targeted attacks. Without this knowledge, it is impossible to show that the metric measures the security level objectively. Thirdly, there is no universal formal model for all metrics that could be used for rigorous analysis. The paper explores the possibility of defining a basic formal model (classifier) for analyzing security metrics. The proposed security assessment model takes into account not only the level of secrecy of information resources, the level of provision of security services, but also allows, based on the requirements put forward, forming the necessary set of security assessment metrics, taking into account the requirements for the continuity of business processes. The average value of the provision of security services to CPSS information resources is 0.99, with an average value of the security level of information resources of 0.8
Evolutionary and temporal dynamics of emerging influenza D virus in Europe (2009–22)

Abstract Influenza D virus (IDV) is an emerging influenza virus that was isolated for the first time in 2011 in the USA from swine with respiratory illness. Since then, IDV has been detected worldwide in different animal species, and it was also reported in humans. Molecular epidemiological studies revealed the circulation of two major clades, named D/OK and D/660. Additional divergent clades have been described but have been limited to specific geographic areas (i.e. Japan and California). In Europe, IDV was detected for the first time in France in 2012 and subsequently also in Italy, Luxembourg, Ireland, the UK, Switzerland, and Denmark. To understand the time of introduction and the evolutionary dynamics of IDV on the continent, molecular screening of bovine and swine clinical samples was carried out in different European countries, and phylogenetic analyses were performed on all available and newly generated sequences. Until recently, D/OK was the only clade detected in this area. Starting from 2019, an increase in D/660 clade detections was observed, accompanied by an increase in the overall viral genetic diversity and genetic reassortments. The time to the most recent common ancestor (tMRCA) of all existing IDV sequences was estimated as 1995—16 years before its discovery, indicating that the virus could have started its global spread in this time frame. Despite the D/OK and D/660 clades having a similar mean tMRCA (2007), the mean tMRCA for European D/OK sequences was estimated as January 2013 compared to July 2014 for European D/660 sequences. This indicated that the two clades were likely introduced on the European continent at different time points, as confirmed by virological screening findings. The mean nucleotide substitution rate of the hemagglutinin-esterase-fusion (HEF) glycoprotein segment was estimated as 1.403 × 10−3 substitutions/site/year, which is significantly higher than the one of the HEF of human influenza C virus (P < 0.0001). IDV genetic drift, the introduction of new clades on the continent, and multiple reassortment patterns shape the increasing viral diversity observed in the last years. Its elevated substitution rate, diffusion in various animal species, and the growing evidence pointing towards zoonotic potential justify continuous surveillance of this emerging influenza virus.
Relevance of CMV DNA Detection in Symptomatic Children up to 3 Months of Age

Cytomegalovirus (CMV) is the most frequent cause of congenital infection worldwide. The burden of disease related to congenital CMV (cCMV) is substantial, as it is the leading cause of sensorineural hearing loss and an important cause of neurodevelopmental disabilities in children. Despite its clinical significance, cCMV infection often goes undetected because the majority of infected infants are asymptomatic at birth and screening programmes have not been implemented in any country. The aim of this study is to define the role of CMV in congenital and early postnatal morbidity in clinically relevant symptomatic children up to 3 months of age in Varna region, comparatively in ELISA (anti CMV IgM/IgG) and PCR. We found CMV DNA in 12 out of 50 tested children (24%, 95% CI: 12.16–35.84%). The viral load ranged in 65–1 628 879 IU/ml, average viral load 144 707.2 IU/ml. It is important to note that only half of the PCR positive children 6/12 (50%) had an anti CMV IgM positive result. Our data demonstrate that serological tests defining active CMV infection with CMV IgM detection are not sufficiently indicative in all newborns, and it is therefore mandatory to conduct modern PCR for all relevant infants after birth.
Direct Transfer Manufacturing of Flexible Silicon Carbide Nanowire-Network Prototype Device

Flexible and transparent devices are expected to meet increasing consumer demands for upgrades in wearable devices, smart electronic and photonic applications. In this work, nano-manufacturing of a flexible and powerless silicon carbide nanowire network ultraviolet photodetector (SiCNW-network UVPD) prototype was investigated by a very cost-effective direct transfer method. Indeed, the powerless device exhibited a photo-to-dark current ratio (PDCR) of 15 with a responsivity of 5.92 mA/W at 254 nm wavelength exposure. The reliability and durability of the device was evaluated by bending tests. In fact, the PDCR of the device was still very good even after seventy-five bending cycles (~ 96 % of the rest state). In brief, our flexible, powerless SiCNW-network UVPD device with cost-effectiveness, good performance, and durability can provide feasible alternatives for new generation wearable optoelectronic products.
Tensile Strength Enhancement of the Bamboo Fiber Hand Sheet by Fiber Arrangement

In order to improve the tensile strength of bamboo hand sheets used as reinforcement in bio composite materials, bamboo fibers have to be arranged roughly in the same direction. However, the classical method for forming the bamboo hand sheet (using L’HOMARGY machine) is not efficient to align the fibers. The objective of this work is to improve the method for forming the suitable arranged direction of the bamboo hand sheets. The bamboo strips were treated with a 6% NaOH solution at 120oc for 2 hours before extracting as individual bamboo fibers. These bamboo fibers were then formed as bamboo hand sheet by a dynamic laboratory sheet former (Mecaform, EP MECA, France). The given hand sheets were then cut along different angles (0, 45, and 90 degrees), and ten samples of each unidirectional and classical bamboo hand sheet were tested for the tensile strength according to ISO 1924-1. It was found that the tensile strength and the tensile modulus of bamboo hand sheets are correlated. The tensile strength and the tensile modulus of the 0-degree arranged bamboo hand sheets are double improved compare with the classical bamboo hand sheets.
Quality of Service-Aware Resource Selection in Healthcare IoT Using Deep Autoencoder Neural Networks

Heterogeneous network and device-to-device communication are two possible solutions for improving wireless network spectral efficiency. Techniques based on the Internet of Things (IoT) can interact between a large number of smart devices as well as heterogeneous networks. The goal of this study is to investigate proposed quality of service-aware resource selection in an IoT network for healthcare data using a deep auto encoder neural network with spectrum reuse utilizing mixed integer nonlinear programming (MINLP). The suggested MINLP spectrum reuse was used to address the optimization problem, and the spectrum allocation was done using fast Fourier transform based reinforcement Q-learning. Increased transmission repetitions have been identified as a promising strategy for improving IoT coverage by up to 164 dB in terms of maximum coupling loss for uplink transmissions, which is a significant improvement over traditional LTE technology, particularly for serving customers in deep coverage. Based on a comparison of existing methodologies, the experimental study is performed using parameters such as bit error rate of 40%, signal-to-interference plus noise ratio of 72%, sum rate of 88%, and spectral efficiency of 98%.