Miracle-dz/UniFAR-FTUs huggingface dataset:
Teaching calm abiding meditation to mental health workers: a descriptive account of valuing subjectivity

Teaching an eight-week calm abiding meditation course to staff in a Child and Youth Mental Health Service located in a regional Australian city presented a curious meeting of Buddhism with Western culture. This meeting highlighted both the potential benefits and challenges of teaching meditation in the workplace and the value of qualitative methods for contributing to the development of meditation research. The thematic analysis of weekly participant responses to emailed reflective questions and follow-up interviews indicated that workplace meditation training can precipitate sustainable changes in attitudes and behaviour beyond the workplace. Participants reported being less reactive and better able to manage emotions, having heightened self-awareness, self-acceptance and acceptance of others and of circumstances; and, in the longer term, were better able to make healthier lifestyle choices. The analysis is contextualized by a rich description of the course and salient concerns and conditions evident in contemporary Buddhist teachings and studies of mindfulness meditation.
Compensation of the Afterglow Phenomenon in 2-D Discrete-Time Simulations

Due to high computational costs, the physics governed by the wave equation in 3-D is often modelled via discrete-time numerical simulations conducted in 2-D scenarios. Results are normally generalized to 3-D rather straightforwardly, overlooking the fact that the propagation of a point-like impulse in 2-D exhibits the so-called afterglow phenomenon, which consists on the fact that non-null field values are measured after the arrival of the first wavefront. This letter analyzes the consequences of this phenomenon, both theoretically and numerically, and presents a simple method to compensate for it. Verification of this method is presented using various discrete-time numerical schemes.
Socioeconomic Disparity in Survival after Breast Cancer in Ireland: Observational Study

We evaluated the relationship between breast cancer survival and deprivation using data from the Irish National Cancer Registry. Cause-specific survival was compared between five area-based socioeconomic deprivation strata using Cox regression. Patient and tumour characteristics and treatment were compared using modified Poisson regression with robust variance estimation. Based on 21356 patients diagnosed 1999–2008, age-standardized five-year survival averaged 80% in the least deprived and 75% in the most deprived stratum. Age-adjusted mortality risk was 33% higher in the most deprived group (hazard ratio 1.33, 95% CI 1.21–1.45, P<0.001). The most deprived groups were more likely to present with advanced stage, high grade or hormone receptor-negative cancer, symptomatically, or with significant comorbidity, and to be smokers or unmarried, and less likely to have breast-conserving surgery. Cox modelling suggested that the available data on patient, tumour and treatment factors could account for only about half of the survival disparity (adjusted hazard ratio 1.18, 95% CI 0.97–1.43, P = 0.093). Survival disparity did not diminish over time, compared with the period 1994–1998. Persistent survival disparities among Irish breast cancer patients suggest unequal use of or access to services and highlight the need for further research to understand and remove the behavioural or other barriers involved.
Assessing kidney function--measured and estimated glomerular filtration rate.

In the coming years, estimates of the glomerular filtration rate (GFR) may replace the measurement of serum creatinine as the primary tool for the assessment of kidney function. Indeed, many clinical laboratories already report estimated GFR values whenever serum creatinine is measured. This review considers current methods of measuring GFR and GFR-estimating equations and their strengths and weaknesses as applied to chronic kidney disease.
Epidemiological profile and genetic diversity of sapoviruses (SaVs) identified in children suffering from acute gastroenteritis in Pune, Maharashtra, Western India, 2007–2011

SUMMARY Sapoviruses (SaVs) are responsible for sporadic cases and outbreaks of acute gastroenteritis. Despite this, few studies in India have focused on the epidemiological investigation of SaV in cases of acute gastroenteritis. The aim of this study was to understand the molecular epidemiology, genetic diversity and clinical impact of SaV in diarrhoeic children from Pune, Western India. Between 2007 and 2011, a total of 985 faecal samples from diarrhoeic cases and non-diarrhoeic controls were collected and examined for the presence of SaV by nested RT–PCR. SaV was detected in 2·7% (21/778) of the cases and 1·9% (4/207) of the controls. We observed that the majority of SaV mono-infections caused severe gastroenteritis (67%) with clinical manifestations of diarrhoea (100%), vomiting (73%) and dehydration (80%). All known human SaV genogroups were detected in the study. At least eight genotypes were identified from cases and controls. Genogroups GIV and GV, along with genotypes GI.5, GII.4 and GII.6, were discovered for the first time in India. Two GII.4 study strains were found to be 98·5–99% identical, having a novel intra-genogroup recombinant (GII.1/GII.4) recently reported from the Philippines, suggesting probable evidence of recombination. The circulation pattern of SaV genotypes varied during the study period, with GII.1 being predominant in 2007 and 2009, GIV.1 in 2008, and GV.1 in 2011.
Model Predictive Climate Control of a Swiss Office Building: Implementation, Results, and Cost–Benefit Analysis

This paper reports the final results of the predictive building control project OptiControl-II that encompassed seven months of model predictive control (MPC) of a fully occupied Swiss office building. First, this paper provides a comprehensive literature review of experimental building MPC studies. Second, we describe the chosen control setup and modeling, the main experimental results, as well as simulation-based comparisons of MPC to industry-standard control using the EnergyPlus simulation software. Third, the costs and benefits of building MPC for cases similar to the investigated building are analyzed. In the experiments, MPC controlled the building reliably and achieved a good comfort level. The simulations suggested a significantly improved control performance in terms of energy and comfort compared with the previously installed industry-standard control strategy. However, for similar buildings and with the tools currently available, the required initial investment is likely too high to justify the deployment in everyday building projects on the basis of operating cost savings alone. Nevertheless, development investments in an MPC building automation framework and a tool for modeling building thermal dynamics together with the increasing importance of demand response and rising energy prices may push the technology into the net benefit range.
Space-time OFDM with adaptive beamforming: performance in spatially correlated channels

Space-time block coding (STBC) has proved to be an effective means of exploring diversity branches and improving system performance. In a previous work we proposed an extension to that where the STBC was combined with adaptive eigenbeamforming, an approach that takes an advantage of spatial channel correlation and can provide further improvement for the overall system performance. In this paper, we investigate this new transmission structure for broadband orthogonal frequency division multiplexing (OFDM) systems in frequency-selective channels. Numerical analysis showed that systems employing this scheme would not undergo any diversity losses as it maintains the maximum achievable diversity advantage of space-time (ST) codes in realistic channel conditions. Simulation results showed that the proposed structure has a significant improvement in bit/symbol error rate performance in a spatially correlated channel over systems that utilize only space-time coding.
Large‐scale plant protein subcellular location prediction

Current plant genome sequencing projects have called for development of novel and powerful high throughput tools for timely annotating the subcellular location of uncharacterized plant proteins. In view of this, an ensemble classifier, Plant‐PLoc, formed by fusing many basic individual classifiers, has been developed for large‐scale subcellular location prediction for plant proteins. Each of the basic classifiers was engineered by the K‐Nearest Neighbor (KNN) rule. Plant‐PLoc discriminates plant proteins among the following 11 subcellular locations: (1) cell wall, (2) chloroplast, (3) cytoplasm, (4) endoplasmic reticulum, (5) extracell, (6) mitochondrion, (7) nucleus, (8) peroxisome, (9) plasma membrane, (10) plastid, and (11) vacuole. As a demonstration, predictions were performed on a stringent benchmark dataset in which none of the proteins included has ≥25% sequence identity to any other in a same subcellular location to avoid the homology bias. The overall success rate thus obtained was 32–51% higher than the rates obtained by the previous methods on the same benchmark dataset. The essence of Plant‐PLoc in enhancing the prediction quality and its significance in biological applications are discussed. Plant‐PLoc is accessible to public as a free web‐server at http://202.120. 37.186/bioinf/plant. Furthermore, for public convenience, results predicted by Plant‐PLoc have been provided in a downloadable file at the same website for all plant protein entries in the Swiss‐Prot database that do not have subcellular location annotations, or are annotated as being uncertain. The large‐scale results will be updated twice a year to include new entries of plant proteins and reflect the continuous development of Plant‐PLoc. J. Cell. Biochem. 100: 665–678, 2007. © 2006 Wiley‐Liss, Inc.
Making Structural Sense of Dimerization Interfaces of Delta Opioid Receptor Homodimers

Opioid receptors, like other members of the G protein-coupled receptor (GPCR) family, have been shown to associate to form dimers and/or oligomers at the plasma membrane. Whether this association is stable or transient is not known. Recent compelling evidence suggests that at least some GPCRs rapidly associate and dissociate. We have recently calculated binding affinities from free energy estimates to predict transient association between mouse delta opioid receptor (DOR) protomers at a symmetric interface involving the fourth transmembrane (TM4) helix (herein termed “4” dimer). Here we present disulfide cross-linking experiments with DOR constructs with cysteines substituted at the extracellular ends of TM4 or TM5 that confirm the formation of DOR complexes involving these helices. Our results are consistent with the involvement of TM4 and/or TM5 at the DOR homodimer interface, but possibly with differing association propensities. Coarse-grained (CG) well-tempered metadynamics simulations of two different dimeric arrangements of DOR involving TM4 alone or with TM5 (herein termed “4/5” dimer) in an explicit lipid−water environment confirmed the presence of two structurally and energetically similar configurations of the 4 dimer, as previously assessed by umbrella sampling calculations, and revealed a single energetic minimum of the 4/5 dimer. Additional CG umbrella sampling simulations of the 4/5 dimer indicated that the strength of association between DOR protomers varies depending on the protein region at the interface, with the 4 dimer being more stable than the 4/5 dimer.
Mapping of Single-Base Differences between Two DNA Strands in a Single Molecule Using Holliday Junction Nanomechanics

Objective The aim of this work is to demonstrate a novel single-molecule DNA sequence comparison assay that is purely based on DNA mechanics. Methods A molecular construct that contained the two homologous but non-identical DNA sequences that were to be compared was prepared such that a four-way (Holliday) junction could be formed by the formation of heteroduplexes through the inter-recombination of the strands. Magnetic tweezers were used to manipulate the force and the winding applied to this construct for inducing both the formation and the migration of a Holliday junction. The end-to-end distance of the construct was measured as a function of the winding and was used to monitor the behavior of the Holliday junction in different regions of the intra-molecular recombination. Main Results In the appropriate buffer, the magnet rotation induces the migration of the Holliday junction in the regions where there is no sequence difference between the recombining sequences. In contrast, even a single-base difference between the recombining sequences leads to a long-lasting blockage of the migration in the same buffer; this effect was obtained when the junction was positioned near this locus (the site of the single-base difference) and forced toward the formation of heteroduplexes that comprise the locus. The migration blockages were detected through the identification of the formation of plectonemes. The detection of the presence of sequence differences and their respective mappings were obtained from the series of blockages that were detected. Significance This work presents a novel single-molecule sequence comparison assay that is based on the use of a Holliday junction as an ultra-sensitive nanomechanism; the mismatches act as blocking grains of sand in the Holliday “DNA gearbox”. This approach will potentially have future applications in biotechnology.
Linear Off-Policy Actor-Critic

This paper presents the first actor-critic algorithm for off-policy reinforcement learning. Our algorithm is online and incremental, and its per-time-step complexity scales linearly with the number of learned weights. Previous work on actor-critic algorithms is limited to the on-policy setting and does not take advantage of the recent advances in off-policy gradient temporal-difference learning. Off-policy techniques, such as Greedy-GQ, enable a target policy to be learned while following and obtaining data from another (behavior) policy. For many problems, however, actor-critic methods are more practical than action value methods (like Greedy-GQ) because they explicitly represent the policy; consequently, the policy can be stochastic and utilize a large action space. In this paper, we illustrate how to practically combine the generality and learning potential of off-policy learning with the flexibility in action selection given by actor-critic methods. We derive an incremental, linear time and space complexity algorithm that includes eligibility traces, prove convergence under assumptions similar to previous off-policy algorithms, and empirically show better or comparable performance to existing algorithms on standard reinforcement-learning benchmark problems.
A Curcumin Derivative That Inhibits Vinyl Carbamate-Induced Lung Carcinogenesis via Activation of the Nrf2 Protective Response.

AIMS Lung cancer has a high worldwide morbidity and mortality. The employment of chemopreventive agents is effective to reduce lung cancer. Nuclear factor erythroid 2-related factor 2 (Nrf2) mitigates insults from both exogenous and endogenous sources and thus has been verified as a target for chemoprevention. Curcumin has long been recognized as a chemopreventive agent, but poor bioavailability and weak Nrf2 induction have prohibited clinical application. Thus, we have developed new curcumin derivatives and tested their Nrf2 induction. RESULTS Based on curcumin, we synthesized curcumin analogs with five carbon linkages and established a structure-activity relationship for Nrf2 induction. Among these derivatives, bis[2-hydroxybenzylidene]acetone (BHBA) was one of the most potent Nrf2 inducers with minimal toxicity and improved pharmacological properties and was thus selected for further investigation. BHBA activated the Nrf2 pathway in the canonical Keap1-Cys151-dependent manner. Furthermore, BHBA was able to protect human lung epithelial cells against sodium arsenite [As(III)]-induced cytotoxicity. More importantly, in an in vivo vinyl carbamate-induced lung cancer model in A/J mice, preadministration of BHBA significantly reduced lung adenocarcinoma, while curcumin failed to show any effects even at high doses. INNOVATION The curcumin derivative, BHBA, is a potent inducer of Nrf2. It was demonstrated to protect against As(III) toxicity in lung epithelial cells in an Nrf2-dependent manner. Furthermore, compared with curcumin, BHBA displayed improved chemopreventive activities in a carcinogen-induced lung cancer model. CONCLUSION Taken together, our results demonstrate that BHBA, a curcumin analog with improved Nrf2-activating and chemopreventive activities both in vitro and in vivo, could be developed into a chemoprotective pharmacological agent.
PE File Features in Detection of Packed Executables

— Portable executable or PE file features play a key role in detection of packed executables. Packing performs a lot of changes to the internal structure of PE files in such a way that it makes it very difficult for any Reverse Engineering Technique, Anti-Virus (AV) scanner or similar kind of programs to figure out whether the executable is malware or benign. Therefore, it is very important to figure out whether a given executable is packed or non-packed before detecting it as malicious or benign. Once a binary is detected as packed, it can be unpacked and can be given to AV or similar kind of programs. In this paper we have included a brief description of Portable Executable file format as we need to know the internal structure of PE before figuring out Packed Portable Executables. We have considered the packed executable by UPX packer only, and hence mentioned the functioning of UPX packer very briefly. Our approach basically works in two phases. In the first phase, it extracts various features of portable executables and in the second phase it analyses the extracted features and comes up with best set of features, which can be used to identify whether a given binary is packed or not by UPX Packer. Experimental results are shown to the end of this paper. We figure out the key feature set with proper justifications to show differences between packed and non-packed executable by UPX packer.
Serum microRNA signatures and metabolomics have high diagnostic value in hepatocellular carcinoma

Background Many new diagnostic biomarkers have been developed for hepatocellular carcinoma (HCC). We selected two methods with high diagnostic value, the detection of serum microRNAs and metabolomics based on gas chromatography/mass spectrometry (GC/MS), and attempted to establish appropriate models. Methods We reviewed the diagnostic efficiencies of all microRNAs identified by previous diagnostic tests. Then we chose appropriate microRNAs to validate the diagnostic efficiencies, and determined the optimal combination. We included 66 patients with HCC and 82 healthy controls (HCs) and detected the expression of the microRNAs. GC/MS analysis was performed, and we used three multivariate statistical methods to establish diagnostic models. The concentration of alpha feto-protein (AFP) was determined for comparison with the novel models. Results 82 published studies and 92 microRNAs were ultimately included in this systematic review. Seven microRNAs were selected for further validation of their diagnostic efficiencies. Among which, miR-21, miR-106b, miR-125b, miR-182 and miR-224 had a significantly different expression in HCC patients. The combination of miR-21, miR-106b and miR-224 had the highest area under the curve (AUC) at 0.950 with a sensitivity of 80.3% and a specificity of 92.7%. The GC/MS analysis exhibited an excellent diagnostic value and the AUC reached 1.0. In comparison, the AUC of the traditional biomarker, AFP, was 0.755. Conclusion MicroRNAs and metabolomics shows promising potential as new diagnostic methods due to their high diagnostic value compared with traditional biomarkers.
The central nervous system as target for antihypertensive actions of a proline‐rich peptide from Bothrops jararaca venom

Pyroglutamyl proline‐rich oligopeptides, present in the venom of the pit viper Bothrops jararaca (Bj‐PROs), are the first described naturally occurring inhibitors of the angiotensin I‐converting enzyme (ACE). The inhibition of ACE by the decapeptide Bj‐PRO‐10c (
Regulation of meiotic gene expression in plants

With the recent advances in genomics and sequencing technologies, databases of transcriptomes representing many cellular processes have been assembled. Meiotic transcriptomes in plants have been studied in Arabidopsis thaliana, rice (Oryza sativa), wheat (Triticum aestivum), petunia (Petunia hybrida), sunflower (Helianthus annuus), and maize (Zea mays). Studies in all organisms, but particularly in plants, indicate that a very large number of genes are expressed during meiosis, though relatively few of them seem to be required for the completion of meiosis. In this review, we focus on gene expression at the RNA level and analyze the meiotic transcriptome datasets and explore expression patterns of known meiotic genes to elucidate how gene expression could be regulated during meiosis. We also discuss mechanisms, such as chromatin organization and non-coding RNAs that might be involved in the regulation of meiotic transcription patterns.
Doppler time-of-flight imaging

Over the last few years, depth cameras have become increasingly popular for a range of applications, including human-computer interaction and gaming, augmented reality, machine vision, and medical imaging. Many of the commercially-available devices use the time-of-flight principle, where active illumination is temporally coded and analyzed in the camera to estimate a per-pixel depth map of the scene. In this paper, we propose a fundamentally new imaging modality for all time-of-flight (ToF) cameras: per-pixel radial velocity measurement. The proposed technique exploits the Doppler effect of objects in motion, which shifts the temporal illumination frequency before it reaches the camera. Using carefully coded illumination and modulation frequencies of the ToF camera, object velocities directly map to measured pixel intensities. We show that a slight modification of our imaging system allows for color, depth, and velocity information to be captured simultaneously. Combining the optical flow computed on the RGB frames with the measured metric radial velocity allows us to further estimate the full 3D metric velocity field of the scene. The proposed technique has applications in many computer graphics and vision problems, for example motion tracking, segmentation, recognition, and motion deblurring.
GoalBit: a free and open source peer-to-peer streaming network

This paper presents the GoalBit Starter platform. GoalBit is an open source peer-to-peer distribution system of real-time video streams over Internet. The main advantage of a P2P architecture is the possibility of using available upload bandwidth in the hosts connected. The main difficulty is that these hosts are typically highly dynamic, they continuously enter and leave the network. To deal with this problem a mesh connectivity approach is used (Bittorrent-like) where the stream is decomposed into several pieces and shared between different peers. Nowadays, the GoalBit platform is used by operators and by final users to broadcast their live contents. To illustrate its potential, we present some empirical results measured in an emulation of a GoalBit P2P streaming, with more than 300 peers concurrently connected.