Miracle-dz/UniFAR-FTUs huggingface dataset:
Tumorous imaginal disc 1 (TID1) inhibits isoproterenol-induced cardiac hypertrophy and apoptosis by regulating c-terminus of hsc70-interacting protein (CHIP) mediated degradation of Gαs

Dilated cardiomyopathy (DCM) is the most common form of non-ischemic cardiomyopathy. It is characterized by ventricular chamber dilation, and myocyte hypertrophy. Human tumorous imaginal disc 1 (Tid1), a chaperone protein and response to regulate number of signaling molecules in the mitochondria or cytosol. Tid1 also plays a major role in preventing DCM; however, the role of Tid1 in isoproterenol (ISO)-induced cardiac apoptosis and hypertrophy remains unclear. H9c2 cells were pretreated Tid1 before ISO-induced hypertrophy and apoptosis and then evaluated by IHC, TUNEL assay, IFC, Co-IP, and Western blot. From the IHC experiment, we found that Tid1 proteins were increased in tissues from different stages of human myocardial infarction. Using H9c2 cardiomyoblast cells we found that Tid1 was decreased by ISO treatment. However, over-expression of Tid1S suppressed NFATc3, BNP and calcineurin protein expression and inhibited NFATc3 nuclear translocation in ISO induced cardiomyoblast cells. On the other hand, Tid1S over-expression activated survival proteins p-AKTser473 and decreased caspase-3 and cytochrome c expression. We also found that overexpression of Tid1 enhanced CHIP expression, and induced CHIP to ubiquitinate Gαs, resulting in increased Gαs degradation. Our study showed that Gαs is a novel substrate of CHIP, and we also found that the Tid1-CHIP complex plays an essential role in inhibiting ISO induced cardiomyoblast hypertrophy and apoptosis.
Forest floor microbial communities in relation to stand composition and timber harvesting in northern Alberta

With the growing interest in silvicultural techniques that more closely emulate natural disturbance regimes, there is a need to better understand how partial harvesting affects the soil microbial community in stands with varying ecological characteristics, e.g., tree species composition. Four and a half and 5.5 years post-harvest, we used phospholipid fatty acid (PLFA) and substrate-induced respiration (SIR) analyses to compare the microbial biomass and microbial community structure of forest floors from stands dominated by white spruce (Picea glauca; SPRUCE) or by trembling aspen (Populus tremuloides; ASPEN) and from mixed-species (MIXED) stands in northern Alberta, Canada, that had been clearcut, partial-cut with 20% retention, partial-cut with 50% retention or left uncut (controls). PLFA and SIR analyses revealed that ASPEN forest floors supported a larger microbial biomass with a very different community structure than MIXED or SPRUCE forest floors. The microbial community structure of these soils appeared to be strongly affected by the presence of white spruce and the composition of the understory vegetation. There were no effects of timber harvesting detected within or across stand types on any of the variables measured, with the exception of the PLFA 16:1o5, which was relatively more abundant in the clearcuts and 50% retention treatments than in the uncut controls, perhaps in response to an increased forest floor pH and grass cover in the disturbed areas. The resilience to timber harvesting of the forest floors from these stands may be the result of efforts to minimize soil disturbance during harvesting and to allow vegetation to regenerate naturally. From the perspective of the forest floor microbial community, partial harvesting does not appear to have any benefit over clearcut harvesting at these boreal forest sites. Crown Copyright r 2006 Published by Elsevier Ltd. All rights reserved.
Quantitative Prediction of Fluorescence Quantum Yields for Tryptophan in Proteins

Variation of intrinsic tryptophan (Trp) fluorescence intensity and lifetime in proteins is widely exploited to follow changes in protein structure such as folding/unfolding, substrate or ligand binding, and protein−protein interactions. Although a credible candidate for the source of weak Trp fluorescence in some proteins has long been believed to be electron transfer from excited Trp to an amide carbonyl group, recognition of when such a process should be exceptionally efficient has not been possible. Here we propose a reasonable basis for the 30-fold variation by the use of quantum mechanics−molecular mechanics simulations in which the energy of the lowest Trp ring-to-amide backbone charge transfer (CT) state is monitored during dynamics trajectories for 24 Trps in 17 proteins. The energy, fluctuations, and relaxation of high lying CT states are extremely sensitive to protein environment (local electric field direction and strength). Application of basic electron transfer theory with a single empirical .
ambient air with laser spectroscopy: method development and first intercomparison results

In situ and simultaneous measurement of the three most abundant isotopologues of methane using midinfrared laser absorption spectroscopy is demonstrated. A field-deployable, autonomous platform is realized by coupling a compact quantum cascade laser absorption spectrometer (QCLAS) to a preconcentration unit, called trace gas extractor (TREX). This unit enhances CH4 mole fractions by a factor of up to 500 above ambient levels and quantitatively separates interfering trace gases such as N2O and CO2. The analytical precision of the QCLAS isotope measurement on the preconcentrated (750 ppm, parts-per-million, μmole mole) methane is 0.1 and 0.5 ‰ for δCand δDCH4 at 10 min averaging time. Based on repeated measurements of compressed air during a 2-week intercomparison campaign, the repeatability of the TREX–QCLAS was determined to be 0.19 and 1.9 ‰ for δC and δD-CH4, respectively. In this intercomparison campaign the new in situ technique is compared to isotoperatio mass spectrometry (IRMS) based on glass flask and bag sampling and real time CH4 isotope analysis by two commercially available laser spectrometers. Both laser-based analyzers were limited to methane mole fraction and δC-CH4 analysis, and only one of them, a cavity ring down spectrometer, was capable to deliver meaningful data for the isotopic composition. After correcting for scale offsets, the average difference between TREX–QCLAS data and bag/flask sampling–IRMS values are within the extended WMO compatibility goals of 0.2 and 5 ‰ for δCand δD-CH4, respectively. This also displays the potential to improve the interlaboratory compatibility based on the analysis of a reference air sample with accurately determined isotopic composition.
Evolving into a remnant: optical observations of SN 1978K at three decades

Ministry of Economy, Development, and Tourism's Millennium Science Initiative IC120009 CONICYT through FONDECYT 3140563 3140566 Japan Society for the Promotion of Science (JSPS) KAKENHI 26800100 World Premier International Research Center Initiative (WPI Initiative), MEXT, Japan JSPS JSPS, Japan 23224004 26400222
Parallelization of Extracting Binary Program Execution Trace Offline

This paper studied the technology to extract program execution trace which is fine-grained in parallel through an open source platform - Platform for Architecture-Neutral Dynamic Analysis. In binary program analysis, analyzing operations in the OS kernel and interactions between multiple processes are enabling only in whole-system mode, and precise analysis is provided in fine-grained mode. To meet the above two conditions, this paper proposes to extract binary program execution trace offline. But whole system analysis and fine-grained instrumentation will reduce the execution speed of programs seriously, so, in this paper, the execution trace extraction has been parallelized. The experiment results indicate that the required extracting time is greatly reduced in ensuring the integrity of the execution trace. Compared with other execution trace extracting technology, this method not only has the characteristic of "record and replay", but also takes the library functions, kernel, and driver and CPU architecture into consideration through whole-system view.
A Review Paper on Improvised Method for Tweet Segmentation Using Named Entity Recognition

: Twitter has become one of the most important channels of communication with its ability to provide the latest and latest information. Given the extensive use of Twitter as a source of information, touching an interesting tweet for users among a bunch of tweets is a challenge. In this paper, we propose a new framework for batch tweet segmentation, called EnhancedSeg, by dividing the tweets into meaningful segments. Semantic or contextual information is well preserved and easily extracted by downstream applications. Enhance Segmentation finds the optimal segmentation of a tweet by maximizing the sum of the membership scores of its candidate segments. The sticky score considers the probability that a segment is an English expression (ie, a global context) and the probability that a segment is an expression in the tweets batch (that is, The local context). For the latter, we propose and evaluate two models to derive the local context by considering the linguistic characteristics and the temporal dependence in a batch of tweets, respectively.
Protective Effects of DHEA and AED against Viral, Bacterial and Parasitic Infections

The use of agents that can boost host immunity to combat infections may be of considerable benefit in the treatment of animals’ infectious outbreaks and complement the available modes of various treatments. This report deals with the role of beta androstenes as agents that up-regulate host immune response to a level that enables the host to resist lethal infection by viruses, bacteria, and parasites. The agents reviewed consist of a specific subgroup of androstene steroids that increase the levels of the TH1 cytokines such as, IL-2, IL3, and IFNγ. Similarly to hydrocortisone, they suppress inflammation, but do not suppress immunity and function in the maintenance of the TH1/TH2 balance and immune homeostasis. We report that DHEA, and AED up-regulate immune resistance and protect the host from lethal infection by RNA and DNA viruses, Gram positive and Gram negative bacteria, parasitic infections, and stress mediated immune suppression. These agents provide a unique new avenue for the control, mitigation, and prevention of animal diseases by viral, bacterial and parasitic infections. Moreover, immune up-regulation may have a significant role in limiting antibiotic resistant and stress mediated infection.
The Effect Of Focused Extracorporeal Shock Wave (ESW) On Calvaria Bone Ex Vivo

THE EFFECT OF FOCUSED EXTRACORPOREAL SHOCK WAVE (ESW) ON CALVARIA BONE EX VIVO Syrah Quraishi, DDS Marquette University, 2013 Introduction: Extracorporeal shock wave (ESW) is low frequency high-pressure wave, regularly used to destroy calcifications e.g. kidney stone. Recent evidence shows that ESW produces micro-cracks in the bones of horse legs. As micro-cracks in bone can lead to an increased rate of bone turnover (remodeling), we hypothesize that proper application of ESW will increase bone turnover rate through generating micro-cracks in bone. Materials and Methods: To test our hypothesis, we used a mouse calvaria bone organ culture model and explored the effects of ESW on bone tissues ex vivo. The calvaria bone pieces were collected from 3 days old C57BL/6 neonatal mice and cultured in 10% FBS supplemented DMEM. After dissection, each quadrant (1/4) of calvaria was randomly assigned into one control and three experimental groups which were subjected to a single dose of 2000 shocks of 3 energy levels of ESW i.e. low (0.1mJ/mm2, 6 Hz), medium (0.25mJ/mm2, 4 Hz), and high (0.5mJ/mm2, 3 Hz,) doses, respectively. After ESW stimulation, the bone tissues were further cultured for 1 week and fixed in 10% formalin. The same experiment was repeated three times (n=3). The bone samples were (1) examined by using a customized radiographic analysis program to measure the bone microdensity, and (2) demineralized and processed to undergo H&E staining to observe the cellular changes histologically. Results: Radiographically the mid dose group exhibited a higher microdensity but not statistically significant (P > 0.05) compared to the other two ESW and the control groups. Histologically, some empty osteocytic lacunae exhibited in all the three dose ESW groups, with nearly all osteocytes disappeared in the high dose group. Hypertrophy of osteoblasts was mainly found in the low dose group. No microcracks were observed on all the H&E staining tissue slides. Histological differences cannot be calculated statistically mainly due to the high heterogeneity of the samples. Conclusion: Although not statistically significant, the mid dose ESW group seems to gain bone microdensity. Due to the lack of statistical differences, definite conclusions cannot be drawn, leaving further endeavors be put on this topic.
Methods for Analysis of Naturalistic Driving Data in Driver Behavior Research

In the last several years, the focus of traffic safety research—especially when performed in association with the automotive industry—has shifted from preventing injury during a crash to avoiding the crash altogether or mitigating its effects. Pre-crash safety measures include intelligent safety systems (e.g., different levels of automated driving), infrastructure design, behavior-based safety, and policy-making. Understanding driver behavior is crucial in the development and evaluation of such measures. Naturalistic driving data (NDD) can facilitate this understanding by providing information about crash causation and contribute to the evaluation of pre-crash safety measures and the effects of driver behavior on safety. However, NDD’s complexity calls for new and better methods to fully exploit its advantages. This thesis, together with the five included papers, addresses several gaps in current scientific knowledge by presenting novel methods for analyzing NDD that address multiple aspects of the development process for pre-crash safety measures. The chunking method (Paper I) helps to identify and overcome common biases in analysis of everyday-driving time-series data, while the expert-assessment-based crash-causation analysis method (Paper II, supported by Paper III) is a novel approach to studying crash causation through the analysis of NDD with video. Product and prototype development can be improved by utilizing counterfactual simulations, for which the choice of driver behavior model is shown to be crucial (Paper IV)—an awareness that was previously lacking. Being able to compare the effects of drivers’ specific behaviors (e.g., driver-vehicle interactions or in-vehicle secondary tasks) on safety could both speed up development of safety measures and improve vehicle designs and design guidelines. Methods to perform such comparisons through the combination of counterfactual glance behavior and pre-crash kinematics have been missing (they are provided in Paper V). This thesis further improves the evaluation of pre-crash safety measures by providing more robust analyses of everyday driving data (Paper I) and by demonstrating the importance of good mathematical models of driver behavior in virtual evaluation (Paper IV). In summary, these new methods fill important research gaps and have the potential to improve the design of pre-crash safety measures through the use of NDD. Using NDD can augment our understanding of driver behavior and crash causation, important aspects of improving traffic safety and fulfilling Sweden’s Vision Zero.
Distinctive Features of a Saudi Genome

We have fully sequenced the genome of an individual from the region of Saudi Arabia. In order to facilitate comparative analysis, an initial characterization of the new genome was undertaken based on single nucleotide polymorphism (SNP). The SNP data having associated population statistics, essentially the HapMap, served to identify features that were rare by comparison. Methods were developed and applied to tag observed SNPs as different and were extended to identify strings or clusters of difference in the individual relative to comparison populations to effectively increase the significance over single SNP comparison. Difference strings identified in the individual relative to each comparison population showed a genome location pattern with various levels of overlap between the comparison populations. The SNP frequencies from the HapMap population samples Ceu and Yri showed a difference inversion relative to the sample genome. The total SNP difference count was greatest between the individual and the Yri population sample while the number and total span of SNP difference clusters was greatest in comparison with the Ceu population sample. The final pattern of difference clusters has served to define distinctive features in the individual genome toward preliminary characterization.
Scene Detection using Convolutional Neural Networks

Computer vision is widely adopted to support the elderly and people with disabilities to improve their quality of life. As such a wide range of research has been carried out to help people benefit from the latest developments in computer vision in the field of ambient assisted living. We present the application of a deep machine learning approach to image classification with the aim of classifying nine different points of interest in the local environment. Our work uses convolutional layers to reduce image dimensions whilst extracting features to be used in a classification process. We then use the transformed data to train a Multi Layer Perceptron. The work also explored the applications of Locally Linear Embedding (LLE) to visualise the data both before and after the classification process to help evaluate the performance. The results show an Area Under the Curve of 0.96 and 0.97 for training and test data. It is also shown that the convolutional process is able to produce a good representation of the original image. Our work concludes that convolution neural networks are able to generalise to a very good standard. The work also concludes that the use of LLE can be used to help evaluate the classification process.
Deep Learning Models for Large-Scale Collaboration

Members of loosely-coupled teams are often unaware of the work done by other team members. As such, identifying and sharing relevant information with a user about their teammates’ activity can enhance collaborative success. Determining the relevance of information becomes more di ﬃ cult as teams grow large and users dispersed. In this work, we introduce a model to predict information relevance in large-scale collaboration that addresses these di ﬃ culties. Our model also captures a one-to-many relationship between users and projects and allows for multiple types of user interaction. Using data from the GitHub Archive, we demonstrate that our approach can predict both user-repository interaction sequences and the likelihood of success for a given repository. Speciﬁcally, we show that our model predicts all types of user interactions at 65% precision and active user interactions at above 80%. It also predicts a repository’s stars and forks, two important metrics of success, within 5 . 7 of the true value. These ﬁndings bode well for the creation of large-scale information sharing systems that facilitate successful teamwork at scale.
The Body Mass Index: the Good, the Bad, and the Horrid

Summary The Body Mass Index (BMI) was developed to estimate the risk for overweight in large samples of people from the wealthy, heavily industrialized nations of Western Europe and North America. When used for this purpose the BMI is, generally, a good tool to estimate overweight. The BMI is a bad tool when used to estimate fatness prior to the onset of the obesity epidemic in 1980 because BMI cannot distinguish between fat and lean tissue and there was, generally, lower levels of fatness in the general population before that date. The BMI is also a bad tool when used to estimate fatness for individuals in any nation or in any group of people. The BMI was never intended to be used for individual diagnosis. The BMI becomes a horrid tool to estimate fatness or health risk when used in some groups of people, such as high-level athletes, body building enthusiasts, people engaged in jobs with strenuous physical activity, and in groups suffering from the nutritional double-burden of very short stature with high body fatness.
Research of Financial Early Warning on Enterprises Listed on the New Third Board Based on KLR Model

In the multi-level capital market in our country, enterprises listed on the New Third Board market are the most promising development enterprises and face the broadest financial risk, but the analysis of available literature on their financial crisis warning is scarce. By referencing KLR model which analyzes financial crisis, selecting a sample of enterprises listed on the New Third Board and adopting the method of comparative analysis, this article makes early warning on the enterprise’s financial crisis from five aspects: the state of profitability, asset quality, debt risk situation, business growth and supplementary material. The empirical results show that the KLR model can be used in financial early warning analysis on enterprises listed on the New Third Board and it distinguishes enterprises with financial crisis from healthy ones with 100 percent accuracy.
Study of the effect of “FARADARMANI” on patients in waiting list for liver transplantation: a double-blinded randomized controlled clinical trial

1Research Center for Traditional Medicine and History of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran 2Essence of Parsiyan Wisdom Institute, Phytopharmaceutical Technology and Traditional Medicine Incubator, Shiraz University of Medical Sciences, Shiraz, Iran 3Department of Traditional Persian Medicine, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran 4Gastroentrohepatology Research Center, Namazee Hospital, Shiraz University of Medical Sciences, Shiraz, Iran 5Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran
Antibacterial Activities of Mentha piperita L. Extracts Against Bacteria Isolated from Soccer Player’s Shoes and its Antioxidant Activities

Objective: Microorganisms have an easier entry into the sportsman’s epidermis, and these make diseases on athletes. The main scope of the study is to search the lack of information about the biological activities of Mentha piperita extracts against bacteria isolated from soccer player’s shoes. Materials and Methods: The bacteria were isolated from soccer player’s shoes from Balikesir Spor soccer team after the competition. The plant extracts were tested by disc diffusion assay for antibacterial activity. In addition, the different extracts of plant were screened by ABTS decolorization assay for antioxidant activity. Results: The highest inhibition zone in bacteria were determined on Staphylococcus sp. BFT12 (21 mm). MIC value was determined as 3250 μg/mL. The highest antioxidant activity of the plant was determined from aqueous extract of plant. This scavenging activity is about 88%. Discussion/Conclusion: The extracts of the plant have high antibacterial and antioxidant potential.