Miracle-dz/UniFAR-FTUs huggingface dataset:
The Physcomitrella patens gene atlas project: large-scale RNA-seq based expression data.

High-throughput RNA sequencing (RNA-seq) has recently become the method of choice to define and analyze transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help analyze specific perturbations, no overall reference dataset has yet been established. In the framework of the Gene Atlas project, the Joint Genome Institute selected P. patens as a flagship genome, opening the way to generate the first comprehensive transcriptome dataset for this moss. The first round of sequencing described here is composed of 99 independent libraries spanning 34 different developmental stages and conditions. Upon dataset quality control and processing through read mapping, 28 509 of the 34 361 v3.3 gene models (83%) were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between conditions. The analysis of the three most distinct and abundant P. patens growth stages - protonema, gametophore and sporophyte - allowed us to define both general transcriptional patterns and stage-specific transcripts. As an example of variation of physico-chemical growth conditions, we detail here the impact of ammonium supplementation under standard growth conditions on the protonemal transcriptome. Finally, the cooperative nature of this project allowed us to analyze inter-laboratory variation, as 13 different laboratories around the world provided samples. We compare differences in the replication of experiments in a single laboratory and between different laboratories.
DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension

We propose DuoRC, a novel dataset for Reading Comprehension (RC) that motivates several new challenges for neural approaches in language understanding beyond those offered by existing RC datasets. DuoRC contains 186,089 unique question-answer pairs created from a collection of 7680 pairs of movie plots where each pair in the collection reflects two versions of the same movie - one from Wikipedia and the other from IMDb - written by two different authors. We asked crowdsourced workers to create questions from one version of the plot and a different set of workers to extract or synthesize answers from the other version. This unique characteristic of DuoRC where questions and answers are created from different versions of a document narrating the same underlying story, ensures by design, that there is very little lexical overlap between the questions created from one version and the segments containing the answer in the other version. Further, since the two versions have different levels of plot detail, narration style, vocabulary, etc., answering questions from the second version requires deeper language understanding and incorporating external background knowledge. Additionally, the narrative style of passages arising from movie plots (as opposed to typical descriptive passages in existing datasets) exhibits the need to perform complex reasoning over events across multiple sentences. Indeed, we observe that state-of-the-art neural RC models which have achieved near human performance on the SQuAD dataset, even when coupled with traditional NLP techniques to address the challenges presented in DuoRC exhibit very poor performance (F1 score of 37.42% on DuoRC v/s 86% on SQuAD dataset). This opens up several interesting research avenues wherein DuoRC could complement other RC datasets to explore novel neural approaches for studying language understanding.
Signaling in Effector Lymphocytes: Insights toward Safer Immunotherapy

Receptors on T and NK cells systematically propagate highly complex signaling cascades that direct immune effector functions, leading to protective immunity. While extensive studies have delineated hundreds of signaling events that take place upon receptor engagement, the precise molecular mechanism that differentially regulates the induction or repression of a unique effector function is yet to be fully defined. Such knowledge can potentiate the tailoring of signal transductions and transform cancer immunotherapies. Targeted manipulations of signaling cascades can augment one effector function such as antitumor cytotoxicity while contain the overt generation of pro-inflammatory cytokines that contribute to treatment-related toxicity such as “cytokine storm” and “cytokine-release syndrome” or lead to autoimmune diseases. Here, we summarize how individual signaling molecules or nodes may be optimally targeted to permit selective ablation of toxic immune side effects.
MicroRNA-183 Suppresses Neuropathic Pain and Expression of AMPA Receptors by Targeting mTOR/VEGF Signaling Pathway

Background: Neuropathic pain is a type of chronic pain that results from dysfunctions of the somatosensory nerve system. This study was aimed to investigate the effect of mTOR/VEGF signaling pathway on neuropathic pain and the regulation mechanisms of miR-183 on AMPA Receptors through mTOR/VEGF signaling pathway. Methods: Chronic compress injury (CCI) model was constructed in the current study, we used paw withdrawal mechanic threshold (PWMT) and paw withdrawal thermal latency (PWTL) to observe mTOR and VEGF receptors. Dual luciferase analysis, western blot and qRT-PCR were also applied to complete this experiment. Results: It was observed that the inhibition of mTOR and VEGF receptors could significantly relieve neuropathic pain in the CCI model. Moreover mTOR was confirmed as the direct target of miR-183. Furthermore, miR-183 could modulate VEGF through regulating mTOR expressions. We also found the expressions of AMPA receptors (i.e. GluR1 and GluR2), located in the downstream of mTOR/VEGF signaling pathway, were significantly upregulated when miR-183 was downregulated or when the mTOR/VEGF signaling pathway was activated. Conclusion: The inhibition of mTOR or VEGF receptors can significantly relieve neuropathic pain, and the upregulation of miR-183 can suppress AMPA receptors by inhibiting mTOR/VEGF pathway.
High efficiency counter mode security architecture via prediction and precomputation

Encrypting data in unprotected memory has gained much interest lately for digital rights protection and security reasons. Counter mode is a well-known encryption scheme. It is a symmetric-key encryption scheme based on any block cipher, e.g. AES. The scheme's encryption algorithm uses a block cipher, a secret key and a counter (or a sequence number) to generate an encryption pad which is XORed with the data stored in memory. Like other memory encryption schemes, this method suffers from the inherent latency of decrypting encrypted data when loading them into the on-chip cache. In this paper, we present a novel technique to hide the latency overhead of decrypting counter mode encrypted memory by predicting the sequence number and pre-computing the encryption pad that we call one-time-pad or OTP. In contrast to the prior techniques of sequence number caching, our mechanism solves the latency issue by using idle decryption engine cycles to speculatively predict and pre-compute OTPs before the corresponding sequence number is loaded. This technique incurs very little area overhead. In addition, a novel adaptive OTP prediction technique is also presented to further improve our regular OTP prediction and precomputation mechanism. This adaptive scheme is not only able to predict encryption pads associated with static and infrequently updated cache lines but also those frequently updated ones as well. Experimental results using SPEC2000 benchmark show an 82% prediction rate. Moreover, we also explore several optimization techniques for improving the prediction accuracy. Two specific techniques, two-level prediction and context-based prediction are presented and evaluated.
Automatic Language Identification in Texts: A Survey

Language identification (“LI”) is the problem of determining the natural language that a document or part thereof is written in. Automatic LI has been extensively researched for over fifty years. Today, LI is a key part of many text processing pipelines, as text processing techniques generally assume that the language of the input text is known. Research in this area has recently been especially active. This article provides a brief history of LI research, and an extensive survey of the features and methods used in the LI literature. We describe the features and methods using a unified notation, to make the relationships between methods clearer. We discuss evaluation methods, applications of LI, as well as off-the-shelfLI systems that do not require training by the end user. Finally, we identify open issues, survey the work to date on each issue, and propose future directions for research in LI.
"I can do everything but see!" -- How People with Vision Impairments Negotiate their Abilities in Social Contexts

This research takes an orientation to visual impairment (VI) that does not regard it as fixed or determined alone in or through the body. Instead, we consider (dis)ability as produced through interactions with the environment and configured by the people and technology within it. Specifically, we explore how abilities become negotiated through video ethnography with six VI athletes and spectators during the Rio 2016 Paralympics. We use generated in-depth examples to identify how technology can be a meaningful part of ability negotiations, emphasizing how these embed into the social interactions and lives of people with VI. In contrast to treating technology as a solution to a 'sensory deficit', we understand it to support the triangulation process of sense-making through provision of appropriate additional information. Further, we suggest that technology should not try and replace human assistance, but instead enable people with VI to better identify and interact with other people in-situ.
Colorectal cancer detection by hyperspectral imaging using fluorescence excitation scanning

Hyperspectral imaging technologies have shown great promise for biomedical applications. These techniques have been especially useful for detection of molecular events and characterization of cell, tissue, and biomaterial composition. Unfortunately, hyperspectral imaging technologies have been slow to translate to clinical devices – likely due to increased cost and complexity of the technology as well as long acquisition times often required to sample a spectral image. We have demonstrated that hyperspectral imaging approaches which scan the fluorescence excitation spectrum can provide increased signal strength and faster imaging, compared to traditional emission-scanning approaches. We have also demonstrated that excitation-scanning approaches may be able to detect spectral differences between colonic adenomas and adenocarcinomas and normal mucosa in flash-frozen tissues. Here, we report feasibility results from using excitation-scanning hyperspectral imaging to screen pairs of fresh tumoral and nontumoral colorectal tissues. Tissues were imaged using a novel hyperspectral imaging fluorescence excitation scanning microscope, sampling a wavelength range of 360-550 nm, at 5 nm increments. Image data were corrected to achieve a NIST-traceable flat spectral response. Image data were then analyzed using a range of supervised and unsupervised classification approaches within ENVI software (Harris Geospatial Solutions). Supervised classification resulted in >99% accuracy for single-patient image data, but only 64% accuracy for multi-patient classification (n=9 to date), with the drop in accuracy due to increased false-positive detection rates. Hence, initial data indicate that this approach may be a viable detection approach, but that larger patient sample sizes need to be evaluated and the effects of inter-patient variability studied.
High proportions of dementia among SLE patients: A big data analysis

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease affecting a wide range of systems including the peripheral and central nervous system. Cognitive impairment leading to dementia is one of the harmful central nervous system afflictions of SLE. The aim of this study was to investigate the association of SLE with dementia.
ROBPCA: A New Approach to Robust Principal Component Analysis

We introduce a new method for robust principal component analysis (PCA). Classical PCA is based on the empirical covariance matrix of the data and hence is highly sensitive to outlying observations. Two robust approaches have been developed to date. The first approach is based on the eigenvectors of a robust scatter matrix such as the minimum covariance determinant or an S-estimator and is limited to relatively low-dimensional data. The second approach is based on projection pursuit and can handle high-dimensional data. Here we propose the ROBPCA approach, which combines projection pursuit ideas with robust scatter matrix estimation. ROBPCA yields more accurate estimates at noncontaminated datasets and more robust estimates at contaminated data. ROBPCA can be computed rapidly, and is able to detect exact-fit situations. As a by-product, ROBPCA produces a diagnostic plot that displays and classifies the outliers. We apply the algorithm to several datasets from chemometrics and engineering.
Use of Phenotypic and Molecular Serotype Identification Methods To Characterize Previously Nonserotypeable Group B Streptococci

ABSTRACT Among 1,762 isolates of Streptococcus agalactiae (group B streptococcus [GBS]), 207 (12%) initially nonserotypeable isolates were tested by improved conventional serotyping methods (Lancefield antigen extraction with 0.1 and 0.2 N HCl, latex agglutination assays, and use of antisera against all known serotypes [Ia, Ib, and II to IX]) and a molecular serotype identification system (multiplex PCR-based reverse line blot [mPCR/RLB] assays targeting serotype-specific sites in the region spanning cpsH to cpsM). Serotypes were assigned to 71 (34%) of the 207 isolates by using antisera and to 204 (98.5%) of them by mPCR/RLB. Sequencing of a portion of the cpsE-cpsF-cpsG region of 141 persistently nonserotypeable isolates and 1 with discrepant conventional and molecular serotyping results was attempted. Major mutations were identified in 34 isolates (24%), including 11 (8%) from which no amplicons were obtained and 23 (16%) with sequence variation compared with published sequences; of the latter, 21 (15%) were associated with amino acid changes. By contrast, mutations were identified in only 12 (2.3%) of 516 serotypeable isolates for which this region has been sequenced previously. In summary, an improved serotyping scheme allowed serotype identification of more than one-third of the previously nonserotypeable GBS isolates. Molecular serotypes were assigned to almost all of the isolates by mPCR/RLB. Significant mutations (with no amplicons or with associated amino acid changes) were found in the cpsE-cpsF-cspG region of a higher proportion of nonserotypeable than of serotypeable isolates (32/141 versus 8/516; P < 0.001), but further investigation is needed to determine the genetic basis for most nonserotypeable GBS isolates.
Aero-Thermal Investigations of Tip Leakage Flow In Axial Flow Turbines: Part I — Effect of Tip Geometry and Tip Clearance Gap

A numerical study has been performed to investigate the effect of tip geometry on the tip leakage flow and heat transfer characteristics in unshrouded axial flow turbines. Baseline flat tip geometry and squealer type geometries namely double squealer or cavity and suction side squealer were considered. The performances of the squealer geometries, in terms of the leakage mass flow and heat transfer to the tip, were compared with the flat tip at two different tip clearance gaps. The computations were performed using a single blade with periodic boundary conditions imposed along the boundaries in the pitchwise direction. Turbulence was modelled using three different models namely standard k-e, low Re k-ω and SST k-ω, in order to assess the capability of the models in correctly predicting the blade heat transfer. The heat transfer and static pressure distributions obtained using the SST k-ω model was found to be in close agreement with the experimental data. It was observed that compared to the other two geometries considered, the cavity tip is advantageous both from the aerodynamic and from the heat transfer perspectives by providing a decrease in the amount of leakage, and hence losses, and average heat transfer to the tip. In general, for a given geometry, the leakage mass flow and the heat transfer to the tip increased with increase in tip clearance gap. Part II of this paper examines the effect of relative casing motion on the flow and heat transfer characteristics of tip leakage flow. In Part III of this paper the effect of coolant injection on the flow and heat transfer characteristics of tip leakage flow is presented.Copyright © 2007 by ASME
Kinetics of Photosynthetic Response to Ultraviolet and Photosynthetically Active Radiation in Synechococcus WH8102 (CYANOBACTERIA)

The picoplanktonic cyanobacteria, Synechococcus spp. , (Nägeli) are important contributors to global ocean primary production that can be stressed by solar radiation, both in the photosynthetically active (PAR) and ultraviolet (UV) range. We studied the responses of PSII quantum yield (active fluorescence), carbon fixation (14C assimilation) and oxygen evolution (membrane inlet mass spectrometry) in Synechococcus WH8102 under moderate UV and PAR. PSII quantum yield decreased during exposure to moderate UV and UV+PAR, with response to the latter being faster (6.4 versus 2.8 min, respectively). Repair processes were also faster when UV+PAR exposure was followed by moderate PAR (1.68 min response time) than when UV was followed by very low PAR (10.5 min response time). For the UV+PAR treatment, the initial decrease in quantum yield was followed by a 50% increase (“rebound”) after 7 min exposure, showing an apparent photoprotection induction. While oxygen uptake increased with PAR, it did not change under UV, suggesting that this oxygen‐dependent mechanism of photoprotection, which may be acting as an electron sink, is not an important strategy against UV. We used propyl gallate, an antioxidant, to test for plastid terminal oxidase (ptox) or ptox‐like enzymes activity, but it caused nonspecific and toxic effects on Synechococcus WH8102.
The Different Effects of Motivational Messages and Monetary Incentives on Fostering Walking Behavior

While motivational messages and monetary incentives are all useful intervention strategies to promote people's physical activity, it remains unclear how these strategies work together to increase people's steps day and whether the effect will continue after the intervention period. Here, we investigate how these two interventions affect how adult office workers with sedentary jobs set their goals and achieve these daily step goals. We found that motivational messages can improve people's walking behavior only when their behavior is first influenced by motivational messages, not through money. Although monetary incentives increase people's comMassachusetts Institute of Technologyment to goals, it makes those who with low self-efficacy tend to set easier goals. Monetary incentives may have adversely affect the walking behavior of people who have low self-efficacy. These findings help to shed some lights on how to design persuasive mechanisms for mobile health and fitness applications.
Can Word Puzzles be Tailored to Improve Different Dimensions of Verbal Fluency? A Report of an Intervention Study

ABSTRACT Verbal fluency is commonly used as a proxy measure of executive functioning, as it involves cognitive flexibility, working memory, and inhibitory control. Previous research has demonstrated that crosswords can be a useful means of improving verbal fluency, results consistent with the cognitive reserve hypothesis; the form of verbal fluency affected has, however, differed across studies. The present study sought to assess the extent to which it was possible to target phonemic (PVF) and semantic verbal fluency (SVF) separately through word puzzles designed to focus on semantic/thematic and structural clues respectively. Fifty-three university students were randomly assigned to one of three groups: semantic/thematic, structural, or a daily diary control group. They were assessed on PVF and SVF at baseline, and immediately following a four-week intervention. Age, sex, and depression scores were controlled for. A 2 × 3 mixed ANCOVA showed that the structural group improved significantly more in PVF during the intervention period than did the semantic/thematic or control groups, with the improvement linked to improved switching performance. The effect size was large. No significant difference in improvement in SVF emerged, although the effect size was moderate. The findings support the notion that it is possible to improve specific forms of verbal fluency through tailored brief word-puzzle interventions.
Experimental Study on the Flow Characteristics of ￢-Type Groyne

A hydraulic model test for ￢-type groynes (with “￢” shape) was conducted to analyze the flow characteristics around these groynes. The results of the model tests are expected to be used as fundamental information in designing the ￢-type groyne constructed in the field. Main hydraulic factors such as velocity and thalweg line changes in the main channel and separation area were analyzed in this study. The thalweg line is a stream line where the maximum velocity occurs, whereas the separation area is the boundary between the main flow and the recirculation zone. Model tests with 5 different arm lengths of the ￢-type groynes were conducted by changing the velocity. The LSPIV (Large-Scale Particle Image Velocimetry) technique was used to measure and analyze flow variation around the ￢-type groynes. The velocity in the main channel measured to be increased by 1.5 times. The velocity variation on groyne arm length is little. The width of the thalweg lines (TCL) was changed to 55 - 57% of the channel width. The Froude number did not affect the thalweg line (TCL) and separation line (Sh) changes, however.