Miracle-dz/UniFAR-FTUs huggingface dataset:
The long noncoding RNA FEDORA is a cell type– and sex-specific regulator of depression

Women suffer from depression at twice the rate of men, but the underlying molecular mechanisms are poorly understood. Here, we identify marked baseline sex differences in the expression of long noncoding RNAs (lncRNAs), a class of regulatory transcripts, in human postmortem brain tissue that are profoundly lost in depression. One such human lncRNA, RP11-298D21.1 (which we termed FEDORA), is enriched in oligodendrocytes and neurons and up-regulated in the prefrontal cortex (PFC) of depressed females only. We found that virally expressing FEDORA selectively either in neurons or in oligodendrocytes of PFC promoted depression-like behavioral abnormalities in female mice only, changes associated with cell type–specific regulation of synaptic properties, myelin thickness, and gene expression. We also found that blood FEDORA levels have diagnostic implications for depressed women and are associated with clinical response to ketamine. These findings demonstrate the important role played by lncRNAs, and FEDORA in particular, in shaping the sex-specific landscape of the brain and contributing to sex differences in depression.
Impacts Of Fish Meal And Corn Gluten Meal On Performance And Body Tissue Mobilization Of Holstein Fresh Cows

Metabolizable protein (MP) supply and amino acid balance were manipulated through selection of highly digestible rumen-undegradable protein (RUP) sources. Effects on production efficiency and BCS of early postpartum dairy cows were determined. Forty-two multiparous and 16 primiparous Holstein cows were assigned to diets in a completely randomized block design immediately after parturition with three-week experimental periods, and then were fed one ration until 120 days of lactation. Diets were formulated to provide three concentrations of dietary RUP [LRUP 6.65, MRUP 7.72, and HRUP 8.79% of dry matter (DM)] while rumendegraded protein remained constant (11.3% of DM). Diets contained 26.30% of alfalfa hay, 12.60% of corn silage, 9.50% of sugar beet pulp and 51.5% of concentrate (DM basis). Ingredients within diets were equal throughout treatments except for fish meal and corn gluten meal that partially replaced with steam rolled barley and soybean meal. Dry matter intake increased linearly as dietary RUP increasd. Milk yield, FCM and protein content were increased significantly (P<0.05) when cows were fed diets with greater RUP. Body weight changes were lower with the intake of high RUP, whereas BCS changes were significantly different between treatments (P<0.05) and improved by increasing RUP in the diet. Plasma NEFA decreased significantly (P<0.05) although βHBA concentration was not different among treatments.
In Vitro Evaluation of the Effect of Oral Probiotic Weissella cibaria on the Formation of Multi-Species Oral Biofilms on Dental Implant Surfaces

Oral probiotics are beneficial bacteria that can help prevent periodontal disease. However, little is known about the effects of oral probiotics on the formation of implant biofilms. This study aimed to evaluate the effects of oral probiotics Weissella cibaria CMU and CMS1 in an in vitro complex biofilm model on titanium implant surfaces. First, it was identified through colony biofilm assay that W. cibaria CMU and CMS1 inhibit the formation of multi-species biofilms formed by eight types of bacteria. Two types of saliva-coated titanium discs inoculated with early (Streptococcus gordonii, Streptococcus oralis, Streptococcus sanguinis, Actinomyces naeslundii, and Veillonella parvula), secondary (Fusobacterium nucleatum and Prevotella intermedia), and late (Porphyromonas gingivalis) colonizers were treated with the oral probiotics and then incubated anaerobically for three days. The effects of oral probiotics on titanium disc biofilm formation were analyzed using culture methods, quantitative polymerase chain reaction (qPCR), and microscopic analysis. Both probiotics significantly inhibited the formation of biofilm, and all eight bacterial species were significantly reduced. The effectiveness of both probiotic strains was confirmed by all the methods used. Oral probiotics may have dramatically reduced the biofilm formation of secondary colonizers that act as bridges, thus inhibiting biofilm formation on the titanium surface. Our results suggest that the probiotic W. cibaria offers new possibilities for the prevention of peri-implant mucositis.
Three-Stage Least-Squares Analysis of Time and Cost Overruns in Construction Contracts

Construction cost overrun and time overrun (delay) are a significant problem in highway-construction project delivery. Previous research studies have provided insight into the factors that affect overruns; however the findings may have been limited because they do not explicitly consider the simultaneous relationship between cost and time overruns. In this paper, we use data from Indiana highway projects to provide empirical evidence that a simultaneous relationship exists between cost and time overruns and that analysis of these two contractual outputs need to take due cognizance of such simultaneity. Using the three-stage least-squares technique, we identify a number of factors that significantly affect cost overrun and time overrun and we show how the effect of these variables vary by attributes such as project type and results of the bidding process. The models developed in this paper can help agencies enhance the estimation of the expected overruns of final cost and the delay in completion time for their planned projects.
A new strategy to reconcile amyloid cross‐seeding and amyloid prevention in a binary system of α‐synuclein fragmental peptide and hIAPP

Amyloid cross‐seeding and amyloid inhibition are two different research subjects being studied separately for different pathological purposes, in which amyloid cross‐seeding targets to study the co‐aggregation of different amyloid proteins and potential molecular links between different neurodegenerative diseases, while amyloid inhibition aims to design different molecules for preventing amyloid aggregation. While both amyloid cross‐seeding and amyloid inhibition are critical for better understanding the pathological causes of different neurodegenerative diseases including Parkinson disease (PD) and Type 2 diabetes (T2D), less efforts have been made to reconcile the two phenomena. Herein, we proposed a new preventive strategy to demonstrate (a) the cross‐seeding of octapeptide TKEQVTNV from α‐synuclein (associated with PD) with hIAPP (associated with T2D) and (b) the cross‐seeding‐promoted hIAPP fibrillization and cross‐seeding‐reduced hIAPP toxicity. Collective results confirmed that TKEQVTNV can indeed cross‐seed with hIAPP monomers and oligomers, not protofibrils, to form β‐structure‐rich fibrils and to accelerate hIAPP fibrillization. Moreover, such cross‐seeding‐induced promotion effect by TKEQVTNV also rescued the pancreatic cells from hIAPP‐induced cytotoxicity by increasing cell viability and reducing cell apoptosis simultaneously. This work provides a new angle to discover amyloid fragments and use them as amyloid modulators (inhibitors or promotors) to interfere with amyloid aggregation of other amyloid proteins, as well as sequence/structure basis to explore the amyloid cross‐seeding between different amyloid proteins that may help explain a potential molecular talk between different neurodegenerative diseases.
Mobile marketing: a study of attitude and use patterns among mobile phone users

Indian Mobile market is one of the largest in the world and mobile advertising in India is growing rapidly with 35% growth in number of available impressions between quarters 2 and 3 of the year 2011. Surge of smartphones has changed consumer disposition towards mobile phones with consumers growing more comfortable with m-commerce as indicated by earlier research. Objective of this research is to study uses of mobile phones by Indian consumers as differentiated for ‘Smart Phone’ users and ‘Ordinary Handset’ users. Usage patterns and attitude towards uses of mobile phone based on usage rate are also studied. Research outcome indicates that type of handset used does not impact usage pattern and uses that a consumer obtains from his device. Differentiation between Smart Phones and Ordinary Handsets both by features and attributes of the handsets as also by nature of use by handset owners is not very much. Light and Heavy users are more positive in their attitude towards entertainment value derived out of mobile phones. Medium users are more concerned with functional values offered by their instruments. This research offers insights to Smartphone handset manufacturers and mobile service providers to enhance and differentiate their products and services. This research paper addresses issues of mobile usage in India, which is not a well-studied market. Key Findings:  Smartphones are not differentiated from ordinary handsets in terms of attributes and features  Usage rates for Smartphones and Ordinary Handsets remains almost similar  Medium users of mobile phones are more serious about their use.
Gut Microbial Metabolite-Mediated Regulation of the Intestinal Barrier in the Pathogenesis of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a chronic inflammatory disease. The disease has a multifactorial aetiology, involving genetic, microbial as well as environmental factors. The disease pathogenesis operates at the host–microbe interface in the gut. The intestinal epithelium plays a central role in IBD disease pathogenesis. Apart from being a physical barrier, the epithelium acts as a node that integrates environmental, dietary, and microbial cues to calibrate host immune response and maintain homeostasis in the gut. IBD patients display microbial dysbiosis in the gut, combined with an increased barrier permeability that contributes to disease pathogenesis. Metabolites produced by microbes in the gut are dynamic indicators of diet, host, and microbial interplay in the gut. Microbial metabolites are actively absorbed or diffused across the intestinal lining to affect the host response in the intestine as well as at systemic sites via the engagement of cognate receptors. In this review, we summarize insights from metabolomics studies, uncovering the dynamic changes in gut metabolite profiles in IBD and their importance as potential diagnostic and prognostic biomarkers of disease. We focus on gut microbial metabolites as key regulators of the intestinal barrier and their role in the pathogenesis of IBD.
Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations

The pandemic crisis has forced the development of teaching and evaluation activities exclusively online. In this context, the emergency remote teaching (ERT) process, which raised a multitude of problems for institutions, teachers, and students, led the authors to consider it important to design a model for evaluating teaching and evaluation processes. The study objective presented in this paper was to develop a model for the evaluation system called the learning analytics and evaluation model (LAEM). We also validated a software instrument we designed called the EvalMathI system, which is to be used in the evaluation system and was developed and tested during the pandemic. The optimization of the evaluation process was accomplished by including and integrating the dashboard model in a responsive panel. With the dashboard from EvalMathI, six online courses were monitored in the 2019/2020 and 2020/2021 academic years, and for each of the six monitored courses, the evaluation of the curricula was performed through the analyzed parameters by highlighting the percentage achieved by each course on various components, such as content, adaptability, skills, and involvement. In addition, after collecting the data through interview guides, the authors were able to determine the extent to which online education during the COVID 19 pandemic has influenced the educational process. Through the developed model, the authors also found software tools to solve some of the problems raised by teaching and evaluation in the ERT environment.
ERROR PROPAGATION OF HHT-α METHOD FOR PSEUDODYNAMIC TESTS

Error propagation for the direct and improved implementations of the subfamily of HHT-α method with favourable numerical dissipation is studied herein for a pseudo-dynamic test. Analytical results show that the direct implementation of the subfamily of HHT-α method is inappropriate for the pseudodynamic testing although it possesses desired numerical dissipation. However, it is found that the error propagation of high frequency responses can be effectively suppressed by numerical dissipation for the improved implementation of this subfamily of integration methods. Furthermore, the error amplification factor for the improved implementation highly depends on the number of remaining time steps to be performed and the spectral radius of the amplification matrix. In fact, a small spectral radius and/or a large number of remaining time steps will lead to a small error amplification factor. This means an error introduced in an early time step will contribute less to the cumulative error at the end of the test as compared to an error introduced in a later time step.
Detection and Classification of Human Stool Using Deep Convolutional Neural Networks

The diagnosis of functional gastrointestinal disorders and chronic digestive system diseases such as irritable bowel syndrome relies heavily on macroscopic examination of human stool specimens. However, traditional manual stool analysis processes are time-consuming and prone to human subjectivity errors that may lead to incorrect judgments. In this study, we employed deep convolutional neural networks (CNN) to automatically recognize and classify stools in macroscopic images. This approach is advantageous because it reduces the amount of direct interaction required by patients or medical staff, lowers the risk of cross-infection, and removes subjectivity in stool analysis. The U-Net segmentation model is applied to define the region of stools by generating a mask image. After combining the mask and the corresponding original image, the ResNeXt-50 classifies the pre-processed stool image according to the modified Bristol Stool Form Scale (BSFS). Overall, the U-Net model yielded a mean intersection-over-union (mIoU) of 93.75% and an F-score of 0.9570, as the ResNeXt-50 classifier had a classification accuracy of 94.35% and showed decent performance in terms of predictive power. Our study may help to improve the quality of diagnosis and monitoring of diseases associated with bowel movement habits by providing reliable measurements in terms of stool form and consistency.
A distribution line model for lightning overvoltage studies

Recently, the focus of lightning protection measures for distribution lines has moved from a nearby lightning stroke to a direct lightning stroke. Studies of direct lightning stroke countermeasures are generally carried out by digital simulations using the EMTP (Electro‐Magnetic Transients Program). Thus, components of a distribution line must be modeled appropriately in the EMTP for accurate simulations.
In Vitro Antimalarial Activity and Toxicity of Helianthus annuus L. Leaf Extract against Plasmodium falciparum

Background: Malaria is one of the public health problems in Indonesia. The morbidity rate is still quite high, especially in the eastern part of Indonesia. Objective: This study aimed to determine the inhibitory activity of the leaf extracts of Helianthus annuus L. against Plasmodium falciparum strain 3D7 as well as the cytotoxicity of the extracts. Methods: The leaves of H. annuus were extracted by the maceration method with n-hexane, chloroform, and ethanol 96% to increase polarity. The antimalarial assay was performed by using Trager and Jensen method, and the cytotoxicity test was carried out by the MTT method. Results: The results of antimalarial study showed that the chloroform extract had IC50 value of 0.002 µg/mL and CC50value of 138.03 µg/mL, 96% ethanol extract had an IC50 value of 0.02 µg/mL and CC50 value of 617.81 µg/mL, and n-hexane extract had an IC50 value of 1.29 µg/mL and CC50 value of 104.89 µg/mL. The selectivity index (SI) values of the chloroform, ethanolic, and n-hexane extracts were calculated and obtained 69,015.00, 30,890.50, and 81.31, respectively. Conclusion: To conclude, the chloroform extract of H. annuus L. leaf gave strong antimalarial activity against P. falciparum strain 3D7 without any cytotoxicity; therefore, H. annuus L. leaf can be a good candidate for the development of an antimalarial drug.
Laser Enrichment Device Stimulates Broiler Laser-Following Behavior While Increasing Individual Bird Locomotion and Pen-Wide Movement

Genetic selection for fast growth rate and high breast muscle yield in modern broilers has unintended effects on animal welfare and behavior, namely in terms of inactivity and leg disorders. We hypothesized that exercise stimulated through environmental enrichment could positively stimulate pen-wide activity and improve bird welfare. The study objectives were to implement a laser enrichment device to motivate active and feeding behaviors throughout the pen. Twelve hundred Ross 708 broilers were randomly assigned to enrichment (LASER; laser enrichment, or CON; no laser enrichment) for 49 d. Seventy focal birds were randomly assigned to 14 video-recorded pens for behavioral analysis, including focal bird home pen behavior and walking distance. Pen-wide activity was also measured during the 4-min laser periods, four times daily, d0–8, and 1 day weekly, wk 1–6. Focal birds were gait scored wk 1–6, and were euthanized on d42 for tibia bone mineral content, density, and bone breaking strength analysis. Time spent active was increased in LASER-enriched birds compared to CON on wk 3–5 by up to 214% (wk 4), and percent of time at the feeder was increased in LASER-enriched birds by 761% on wk 4 (P < 0.05). Peak percent of birds following the laser (LASER-enriched pens only) was observed on d0 (8.52%). Over wk 1–6, peak laser-following behavior was observed on wk 3 (3.07% of birds). Percent of birds moving during laser periods was increased in LASER-enriched pens on d0, 1, 2, 6, 7, and 8, with a percent increase of 68.7% observed on d1 (P < 0.05). Percent of birds moving (laser-following or not) was increased on wk 1, 3, and 4 in LASER-enriched pens, with an increase of 69.7% observed on wk 4 (P < 0.05). No differences were found in tibia measures. These data indicate that laser enrichment stimulated voluntary locomotion through wk 5 and laser-following behavior through wk 6, and that the relatively small percent of birds actively following the laser stimulated pen-wide movement above the level of the CON through wk 4 on study.
Fabrication and characterization of heterojunction diodes with HVPE-grown GaN on 4H-SiC

GaN/SiC heterojunctions can improve the performance considerably for BJTs and FETs. In this work, heterojunction diodes have been manufactured and characterized. The fabricated diodes have a GaN n-type cathode region on top of a 4H-SiC p-type epi layer. The GaN layer was grown with HVPE directly on off-axis SIC without a buffer layer. Mesa structures were formed and a Ti metallization was used as cathode contact to GaN, and the anode contact was deposited on the backside using sputtered Al. Both current-voltage (I-V) and capacitance-voltage (C-V) measurements were performed on the diode structures. The ideality factor of the measured diodes was 1.1 and was constant with temperature. A built in potential of 2.06 V was extracted from I-V measurements and agrees well with the built in potential from C-V measurements. The conduction band offset was extracted to 1.1 eV and the heterojunction was of type II. The turn on voltage for the diodes is about 1 V lower than expected and a suggested mechanism for this effect is discussed.
Comprehensive Evaluation of Urban Integrated Transportation Network with Multivariate Statistical Analysis: a case study of Haimen

This paper proposed a comprehensive evaluation (CE) framework concerning multivariate statistical analysis to provide a systematic assessment and a hierarchical analysis for the urban integrated transportation network (UITN). Specifically, this research contributed the following technical approaches: Firstly, 4 criteria (scale, structure, level of service (LOS), layout) was adopted and indexes were screened from heterogeneous aspects to establish the hierarchical model using correlation coefficient method (CCM). Built upon that, fuzzy comprehensive evaluation method (FCEM) and linear dimensionless (LD) were applied to quantify and nondimensionalize the qualitative and quantitative indexes. In order to improve accuracy and guarantee rationality, this paper then integrated analytic hierarchy process (AHP) with entropy weight method (EWM) to get the index weight. At last, the combination of value analysis (VA) and grey relational analysis (GRA) was used to calculate the CE value. The experimental study shows that our introduced CE framework can offer a thorough evaluation of the UITN, the CE value of UITN in Haimen city is 0.740 and its grade level is "Medium". Pros and cons of the structural layout of each transport mode can also be judged through the hierarchical analysis of different indexes. In view of this, corresponding suggestions were given for future improved transportation planning.
Resilience against Adversarial Examples: Data-Augmentation Exploiting Generative Adversarial Networks

Recently, malware classification based on Deep Neural Networks (DNN) has gained significant attention due to the rise in popularity of artificial intelligence (AI). DNN-based malware classifiers are a novel solution to combat never-before-seen malware families because this approach is able to classify malwares based on structural characteristics rather than requiring particular signatures like traditional malware classifiers. However, these DNN-based classifiers have been found to lack robustness against malwares that are carefully crafted to evade detection. These specially crafted pieces of malware are referred to as adversarial examples . We consider a clever adversary who has a thorough knowledge of DNN-based malware classifiers and will exploit it to generate a crafty malware to fool DNN-based classifiers. In this paper, we propose a DNN-based malware classifier that becomes resilient to these kinds of attacks by exploiting Generative Adversarial Network (GAN) based data augmentation. The experimental results show that the proposed scheme classifies malware, including AEs, with a false positive rate (FPR) of 3.0% and a balanced accuracy of 70.16%. These are respective 26.1% and 18.5% enhancements when compared to a traditional DNN-based classifier that does not exploit GAN.