Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydrogen sulfide‐mediated resistance against water avoidance stress‐induced gastritis by maintenance of gastric microbial homeostasis

Chronic persistent stress is an important cause of gastritis, but the underlying mechanism remains to be further researched, especially the role of the gastric microbiota in this process. Here, we used the water avoidance stress (WAS) test in mouse models for chronic stress‐induced gastritis to investigate the underlying mechanisms of this disease. The effect of stress on the gastric microbiota was analyzed based on 16S rRNA sequencing; the changes in hydrogen sulfide (H2S) and inflammatory cytokine levels in gastric tissues were detected by Western blotting, ELISA, immunofluorescence, and qRT‐PCR. Hematoxylin and eosin staining was used as an indicator of the gastritis histological score. This finding is consistent with previous studies showing that gastric H2S is negatively associated with the inflammatory index and might protect the gastrointestinal tract from inflammation. WAS‐induced gastritis was associated with a reduction in H2S release, which appeared to affect the homeostasis of the gastric microbiota of mice. Inflammation and microbial dysbiosis were partially reversed by sodium hydrosulfide (NaHS) and vitamin B6 (VB6) supplementation, suggesting the therapeutic potential of VB6 supplementation for the treatment of stress‐induced gastritis. Gastritis has a serious impact on health and quality of life. An increasing number of people are suffering from chronic gastritis linked to a high‐stress lifestyle, and our research provides clues for the prevention and treatment of stress‐induced gastritis.
Age- and BMI-Associated Expression of Angiogenic Factors in White Adipose Tissue of Children

The growth of adipose tissue and its vasculature are tightly associated. Angiogenic factors have been linked to obesity, yet little is known about their expression during early childhood. To identify associations of angiogenic factors with characteristics on individual and tissue level, subcutaneous white adipose tissue samples were taken from 45 children aged 0–9 years undergoing elective surgery. We measured the expression of vascular endothelial growth factor A (VEFGA), fibroblast growth factor 1 and 2 (FGF1, FGF2), angiopoietin 1 and 2 (ANGPT1, ANGPT2), TEK receptor tyrosine kinase (TEK), and von Willebrand factor (VWF). In addition, we determined the mean adipocyte size in histologic tissue sections. We found positive correlations of age with FGF1 and FGF2 and a negative correlation with ANGPT2, with pronounced differences in the first two years of life. FGF1, FGF2, and ANGPT1 correlated positively with adipocyte size. Furthermore, we identified a correlation of ANGPT1 and TEK with body mass index-standard deviation score (BMI-SDS), a measure to define childhood obesity. Except for ANGPT2, all angiogenic factors correlated positively with the endothelial marker VWF. In sum, our findings suggest that differences related to BMI-SDS begin early in childhood, and the analyzed angiogenic factors possess distinct roles in adipose tissue biology.
Rich-Club Analysis in Adults With ADHD Connectomes Reveals an Abnormal Structural Core Network

Objective: Whether the abnormal connectome of brain’s rich-club structure in adults with attention-deficit hyperactivity disorder (ADHD) remains unclear. Method: The current study used diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) to compare the performance of 42 adults with ADHD and 59 typical development (TD) adults. Results: A reduced density of rich-clubs among structural hub nodes, including the bilateral precuneus, the insula, the caudate nucleus, the left putamen, and the right calcarine, was found in adults with ADHD. Moreover, lower global efficiency was found in adults with ADHD than in TD, which might be caused by a reduced density of rich-club connections in ADHD patients. Conclusion: Given that adults with ADHD have greater coupling strength between structural and functional connectivity than TD adults, connectome abnormalities with a reduced rich-club connectivity density might be accompanied by altered functional brain dynamics in ADHD patients.
Third Millennium Assisted Reproductive Technologies: The Impact of Oocyte Vitrification

IVF has been widely used since 1978 (Steptoe & Edwards, 1978) to help infertile couples conceive when nature has failed. The IVF field was improved through embryo freezing/thawing, a technique developed by A. Trounson (Trounson & Mohr, 1983). The next major innovation came with ICSI in 1992, through the work of G.P. Palermo (Palermo et al., 1992). C. Chen was the first to publish work on oocyte freezing (Chen, 1986), but results remained too unreliable for this technique to be adopted in routine ART practice. Oocyte freezing became the focus of experimental efforts when in 1999 the first birth using oocyte vitrification was reported by L. Kuleshova (Kuleshova et al., 1999). M. Kuwayama in a 2005 publication confirmed that this new procedure could be useful in clinical practice (Kuwayama et al., 2005). Within a few years his method for freezing the human oocyte has become the standard for the field. Its clinical application has been widely developed and is now routine, even if other variants have since been proposed. There have been efforts to assess the safety of the procedure (Chian et al., 2008, Noyes et al., 2009). Noteworthy is R. Chian’s report on the health of 200 babies born after having been conceived with vitrified oocytes. The safety of the procedure is also supported by all the data available on the health of children born from vitrified embryos (Takahashi et al., 2005, Mukaida et al., 2009). Use of the technique has reached France (Boyer et al., 2010) with passage of a new bioethics law in the summer of 2011. From Italy we have a good overview of what takes place on a nationwide basis once the technique has become standard practice, thanks to the yearly report of ART results published by the country's ministry of health (Relazione del Ministro della Salute, anno 2009).
A New Type of Anatolian Propolis: Evaluation of Its Chemical Composition, Activity Profile and Botanical Origin

This study was undertaken to analyze the phenolic profiles of 19 propolis samples from Turkey by using a high‐performance thin‐layer chromatographic (HPTLC) method in order to identify their plant origins. Furthermore, their antioxidant and antimicrobial activity profiles were comparatively evaluated. For the appraisal of antioxidant potential, total phenolic (TPC) and total flavonoid contents (TFC) of propolis samples were firstly determined and then their effects on free radicals were evaluated by FRAP, ABTS. +, CUPRAC, DPPH. and HPTLC‐DPPH. methods. Antimicrobial activity of propolis samples against Staphylococcus aureus (ATCC 6538), Pseudomonas aeruginosa (ATCC 15442), Escherichia coli (ATCC 11229) and Candida albicans ATCC 10231 were determined by disc diffusion and broth dilution methods. HPTLC fingerprinting analyses revealed that O‐type (botanical origin from Populus nigra L.) was the primarily available propolis type in Turkey. Moreover, 3‐O‐methylquercetin (3MQ) rich propolis was identified as a new propolis type for the first time. Principal component analysis (PCA) indicated that 3MQ‐type propolis differs from the O‐type. Antioxidant activity studies showed that O‐type of propolis possesses higher antioxidant effect than the other tested propolis types. Quercetin, caffeic acid, caffeic acid phenethyl ester (CAPE) and galangin were determined to contribute significantly to the antioxidant potential of O‐type propolis among others. Propolis extracts exerted moderate antimicrobial activity against the tested microorganisms with MIC values between the ranges of 128–512 μg/mL.
Cadmium and nickel co‐exposure exacerbates genotoxicity and not oxido‐inflammatory stress in liver and kidney of rats: Protective role of omega‐3 fatty acid

The present study examined the influence of co‐exposure to cadmium (Cd) and nickel (Ni) on hepatorenal function as well as the protective role of omega‐3 polyunsaturated fatty acids (ω‐3FA) in rats. The animals were exposed to Cd (5 mg/kg) and Ni (150 μg/L in drinking water) singly or co‐exposed to both metals and ω‐3FA at 20 mg/kg for 14 consecutive days. Results showed that hepatorenal injury resulting from individual exposure to Cd or Ni was not aggravated in the co‐exposure group. Moreover, ω‐3FA markedly abrogated the reduction in the antioxidant enzyme activities, the increase in reactive oxygen and nitrogen species, and lipid peroxidation induced by Cd and Ni co‐exposure. Additionally, ω‐3FA administration markedly suppressed the increase in hepatic and renal myeloperoxidase activity, nitric oxide, tumor necrosis factor alpha, and interleukin‐1 β levels in the co‐exposure group. Genotoxicity resulting from individual exposure to Cd or Ni was intensified in the co‐exposure group. However, ω‐3FA administration markedly ameliorated the genotoxicity and histological lesions in the co‐exposure group. Taken together, co‐exposure to Cd and Ni aggravated genotoxicity and not oxido‐inflammatory stress in the liver and kidney of rats. ω‐3FA abated hepatorenal injury and genotoxicity induced by Cd and Ni co‐exposure in rats.
The homeobox transcription factor HOXC13 upregulates human papillomavirus E1 gene expression and contributes to viral genome maintenance

Human papillomavirus (HPV) infects the basal cells of epithelia and maintains its genome stably as episomes. However, the mechanisms of viral genome maintenance are not fully understood. Here, using normal human immortalized keratinocytes (NIKS), we identified the homeobox transcription factor HOXC13 as a critical host factor for retaining the copy number of HPV genomes in the cell. HOXC13 knockdown in NIKS significantly decreased mRNA levels of the E1 gene, which encodes a DNA helicase required for HPV genome replication, accompanied by a reduction of the viral genome copy number. Chromatin immunoprecipitation assays revealed HOXC13 binding to the long control region that regulates E1 expression. These results indicate that HOXC13 plays invaluable roles in maintaining HPV persistent infection through E1 gene upregulation.
Old friends and friendly fire: Pregnancy, hookworm infection, and anemia among tropical horticulturalists

Despite public health concerns about hookworm infection in pregnancy, little is known about immune profiles associated with hookworm (Necator americanus and Ancylostoma duodenale) infection during pregnancy. Fetal tolerance requirements may constrain maternal immune response to hookworm, thereby increasing susceptibility to new infections or increasing hemoglobin loss. To explore this possibility, we study systemic immune response and hemoglobin levels in a natural fertility population with endemic helminthic infection.
Percepção de enfermeiros sobre condições de trabalho em setor de emergência de um hospital

Objective: To determine the working conditions in the emergency sector in the Hospital da Restauracao, from the perception of nurses working in that sector. Methods: A case study, which used a qualitative and quantitative approach, with triangulation of methods. Data collection was done through open interviews, closed questionnaires and observation. 23 nurses were interviewed. To analyze the data was used the condensation of meanings and the program Excel-version 2003. Results: High number of patients and lack of security for the development of the work were the items most criticized by those interviewed, and confirmed by observation. From the studied group, 47.8% worked in emergency for more than 16 consecutive years, most of them female in the age range of 41 to 50 years. Conclusion: The prevailing perceptions were: poor working conditions, unsatisfactory wages, unhealthy and insecure environment, leading to a feeling of discouragement that influences the quality of care.
Respiratory Muscle Endurance Training in Patients with Chronic Obstructive Pulmonary Disease

Normocapnic hyperpnea has been established as a method of respiratory muscle endurance training. This technique has not been applied on a large scale because complicated and expensive equipment is needed to maintain CO2-homeostasis during hyperpnea. This CO2-homeostasis can be preserved during hyperpnea by enlarging the dead space of the ventilatory system. One of the possibilities to enlarge dead space is breathing through a tube. If tube-breathing is safe and feasible, it may be a new and inexpensive method for respiratory muscle endurance training, enabling its widespread use. The aim of this study was to evaluate the safety of tube-breathing and investigate the effect on CO2-homeostasis in healthy subjects. 20 healthy volunteers performed 10 minutes of tube-breathing (dead space 60% of Vital Capacity). Oxygen-saturation, PaCO2, respiratory muscle function, hypercapnic ventilatory response and dyspnea (Borg-score) were measured. Tube-breathing did not lead to severe complaints, adverse events or oxygen desaturations. 14 out of 20 subjects became hypercapnic (PaCO2 >6,0 kpa) during tube-breathing. There were no significant correlations between PaCO2 and respiratory muscle function or hypercapnic ventilatory responses. The normocapnic versus hypercapnic subjects showed no significant differences between decrease in oxygen saturation (–0,7% versus –0,2% respectively, p=0,6), Borg score (4,3 versus 4,7, p=0,9) , respiratory muscle function nor hypercapnic ventilatory responses. Our results show that tube-breathing is well tolerated amongst healthy subjects. No complaints, nor desaturations occurred. Hypercapnia developed in a substantial number of subjects. When tube-breathing will be applied as respiratory muscle training modality, this potential development of hypercapnia must be considered.
RoboNet: Large-Scale Multi-Robot Learning

Robot learning has emerged as a promising tool for taming the complexity and diversity of the real world. Methods based on high-capacity models, such as deep networks, hold the promise of providing effective generalization to a wide range of open-world environments. However, these same methods typically require large amounts of diverse training data to generalize effectively. In contrast, most robotic learning experiments are small-scale, single-domain, and single-robot. This leads to a frequent tension in robotic learning: how can we learn generalizable robotic controllers without having to collect impractically large amounts of data for each separate experiment? In this paper, we propose RoboNet, an open database for sharing robotic experience, which provides an initial pool of 15 million video frames, from 7 different robot platforms, and study how it can be used to learn generalizable models for vision-based robotic manipulation. We combine the dataset with two different learning algorithms: visual foresight, which uses forward video prediction models, and supervised inverse models. Our experiments test the learned algorithms' ability to work across new objects, new tasks, new scenes, new camera viewpoints, new grippers, or even entirely new robots. In our final experiment, we find that by pre-training on RoboNet and fine-tuning on data from a held-out Franka or Kuka robot, we can exceed the performance of a robot-specific training approach that uses 4x-20x more data. For videos and data, see the project webpage: https://www.robonet. wiki/
(111)-oriented, single crystal diamond tips for nanoscale scanning probe imaging of out-of-plane magnetic fields

We present an implementation of all-diamond scanning probes for scanning nitrogen-vacancy (NV) magnetometry fabricated from (111)-oriented diamond material. The realized scanning probe tips on average contain single NV spins, a quarter of which have their spin quantization axis aligned parallel to the tip direction. Such tips enable single-axis vector magnetic field imaging with nanoscale resolution, where the measurement axis is oriented normal to the scan plane. We discuss how these tips bring multiple practical advantages for NV magnetometry, in particular regarding quantitative analysis of the resulting data. We further demonstrate the beneficial optical properties of NVs oriented along the tip direction, such as polarization-insensitive excitation, which simplifies optical setups needed for NV magnetometry. Our results will be impactful for scanning NV magnetometry in general and for applications in spintronics and the investigation of thin film magnets in particular.
Malware Classification using Deep Learning based Feature Extraction and Wrapper based Feature Selection Technique

In case of behavior analysis of a malware, categorization of malicious files is an essential part after malware detection. Numerous static and dynamic techniques have been reported so far for categorizing malwares. This research work presents a deep learning based malware detection (DLMD) technique based on static methods for classifying different malware families. The proposed DLMD technique uses both the byte and ASM files for feature engineering and thus classifying malwares families. First, features are extracted from byte files using two different types of Deep Convolutional Neural Networks (CNN). After that, important and discriminative opcode features are selected using a wrapper-based mechanism, where Support Vector Machine (SVM) is used as a classifier. The idea is to construct a hybrid feature space by combining the different feature spaces in order that the shortcoming of a particular feature space may be overcome by another feature space. And consequently to reduce the chances of missing a malware. Finally, the hybrid feature space is then used to train a Multilayer Perceptron, which classifies all the nine different malware families. Experimental results show that proposed DLMD technique achieves log-loss of 0.09 for ten independent runs. Moreover, the performance of the proposed DLMD technique is compared against different classifiers and shows its effectiveness in categorizing malwares. The relevant code and database can be found at this https URL.
Facial Emotion Recognition Using Deep Learning

We aim to construct a system that captures real-world facial images through the front camera on a laptop. The system is capable of processing/recognizing the captured image and predict a result in real-time. In this system, we exploit the power of deep learning technique to learn a facial emotion recognition (FER) model based on a set of labeled facial images. Finally, experiments are conducted to evaluate our model using largely used public database.
UniGrasp: Learning a Unified Model to Grasp with N-Fingered Robotic Hands

To achieve a successful grasp, gripper attributes including geometry and kinematics play a role equally important to the target object geometry. The majority of previous work has focused on developing grasp methods that generalize over novel object geometry but are specific to a certain robot hand. We propose UniGrasp, an efficient data-driven grasp synthesis method that considers both the object geometry and gripper attributes as inputs. UniGrasp is based on a novel deep neural network architecture that selects sets of contact points from the input point cloud of the object. The proposed model is trained on a large dataset to produce contact points that are in force closure and reachable by the robot hand. By using contact points as output, we can transfer between a diverse set of N-fingered robotic hands. Our model produces over 90 percent valid contact points in Top10 predictions in simulation and more than 90 percent successful grasps in the real world experiments for various known two-fingered and three-fingered grippers. Our model also achieves 93 percent and 83 percent successful grasps in the real world experiments for a novel two-fingered and five-fingered anthropomorphic robotic hand, respectively.
Keeping Them Honest: a Trustless Multi-Agent Algorithm to Validate Transactions Cleared on Blockchain using Physical Sensors.

In recent years, many Blockchain based frameworks for transacting commodities on a congestible network have been proposed. In particular, as the number of controllable grid connected assets increases, there is a need for a decentralized, coupled economic and control mechanism to dynamically balance the entire electric grid. Blockchain based Transactive Energy (TE) systems have gained significant momentum as an approach to sustain the reliability and security of the power grid in order to support the flexibility of electricity demand. What is lacking in these designs, however, is a mechanism that physically verifies all the energy transactions, to keep the various inherently selfish players honest. In this paper, we introduce a secure peer-to-peer network mechanism for the physical validation of economic transactions cleared over a distributed ledger. The framework is $\textit{secure}$ in the sense that selfish and malicious agents that are trying to inject false data into the network are prevented from adversely affecting the optimal functionality of the verification process by detecting and isolating them from the communication network. Preliminary simulations focusing on TE show the workings of this framework.
Taxonomy of Real Faults in Deep Learning Systems

The growing application of deep neural networks in safety-critical domains makes the analysis of faults that occur in such systems of enormous importance. In this paper we introduce a large taxonomy of faults in deep learning (DL) systems. We have manually analysed 1059 artefacts gathered from GitHub commits and issues of projects that use the most popular DL frameworks (TensorFlow, Keras and PyTorch) and from related Stack Overflow posts. Structured interviews with 20 researchers and practitioners describing the problems they have encountered in their experience have enriched our taxonomy with a variety of additional faults that did not emerge from the other two sources. Our final taxonomy was validated with a survey involving an additional set of 21 developers, confirming that almost all fault categories (13/15) were experienced by at least 50% of the survey participants.
Toward Co-existing Database Schemas based on Bidirectional Transformation

According to strong demands for rapid and reliable software delivery, co-existing database schema versions with multiple application versions are reality to contribute them. Current database management systems do not support co-existing schema versions in one database. Although a design of co-existing schema based on updatable view tables was previously proposed, its flexibility is limited due to pre-defined several restrictions to achieve data synchronization among schemas and handling independent unsynchronized data in each schema. In this preliminary report, we present a new approach for co-existing schemas based on bidirectional transformation. We explain the required properties to realize co-existing schemas, bidirectionality and totality. We show that the co-existing schemas can be implemented systematically by applying putback-based bidirectional transformation to satisfy both the bidirectionality and the totality. While the bidirectionality can be satisfied by applying bidirectional transformation, to satisfy the totality, extra functions need to be introduced. How to derive these extra functions is presented.