Miracle-dz/UniFAR-FTUs huggingface dataset:
The electron microscopic immunohistochemistry of elastase-treated aorta and nuchal ligament of fetal and postnatal sheep.

In conjunction with the immunoperoxidase and the immunoferritin methods, antielastin antibody was used to study the localization of elastin in untreated and elastase-treated elastic fibers of the nuchal ligament and the aorta of fetal and young adult sheep. In tissues not treated with elastase, the staining reaction for antielastin antibody was localized in the outer zones of the amorphous components and along the surfaces of the microfibrils ; the central zones of the amorphous components were unreactive. After mild elastase treatment, incompletely digested amorphous components showed staining both in their central and outer zones, and some of the microfibrils became unreactive. After extensive elastase treatment, small scattered amorphous components were still found in association with bundles of microfibrils. These components were stained diffusely by the antielastin antibody method but were not detectable by staining with uranyl acetate and lead citrate or with Kajikawa 's method for elastin; elastin was not detected on the surfaces of the microfibrils by any of the methods used. These findings were interpreted as indicating that the surfaces of the microfibrils are associated with small amounts of elastin, and that evenly stained amorphous components are composed of elastin, which is loosely arranged and allows the penetration of antielastin antibody. These observations support the concept that microfibrils serve an important role as a scaffold for elastin deposition in elastogenesis. Because of their high sensitivity, immunohistochemical methods for detecting elastin are useful to study partially degraded elastic fibers.
Community annotation experiment for ground truth generation for the i2b2 medication challenge

OBJECTIVE Within the context of the Third i2b2 Workshop on Natural Language Processing Challenges for Clinical Records, the authors (also referred to as 'the i2b2 medication challenge team' or 'the i2b2 team' for short) organized a community annotation experiment. DESIGN For this experiment, the authors released annotation guidelines and a small set of annotated discharge summaries. They asked the participants of the Third i2b2 Workshop to annotate 10 discharge summaries per person; each discharge summary was annotated by two annotators from two different teams, and a third annotator from a third team resolved disagreements. MEASUREMENTS In order to evaluate the reliability of the annotations thus produced, the authors measured community inter-annotator agreement and compared it with the inter-annotator agreement of expert annotators when both the community and the expert annotators generated ground truth based on pooled system outputs. For this purpose, the pool consisted of the three most densely populated automatic annotations of each record. The authors also compared the community inter-annotator agreement with expert inter-annotator agreement when the experts annotated raw records without using the pool. Finally, they measured the quality of the community ground truth by comparing it with the expert ground truth. RESULTS AND CONCLUSIONS The authors found that the community annotators achieved comparable inter-annotator agreement to expert annotators, regardless of whether the experts annotated from the pool. Furthermore, the ground truth generated by the community obtained F-measures above 0.90 against the ground truth of the experts, indicating the value of the community as a source of high-quality ground truth even on intricate and domain-specific annotation tasks.
A CHF detection method based on deep learning with RR intervals

There are extensive studies investigating congestive heart failure (CHF) detection based on heart rate variability. Although a high level of accuracy has been achieved, its robustness under different conditions is not guaranteed. To improve the robustness, we applied sparse auto-encoder-based deep learning algorithm in CHF detection with RR intervals. A total data size of 30,592 (5-min RR interval) was obtained from 72 healthy persons and 44 CHF patients. The deep learning algorithm first extracts unsupervised features using a sparse auto-encoder from raw RR intervals, then constructs a deep neural network model with various hidden nodes combinations. Results showed that the model achieved 72.41% accuracy. This demonstrated that RR intervals have potential in CHF detection but cannot fully reflect dynamic change in 24-h.
Interaction between adolescent obesity and HLA risk genes in the etiology of multiple sclerosis

Objective: We investigated potential interactions between human leukocyte antigen (HLA) genotype and body mass index (BMI) status in relation to the risk of developing multiple sclerosis (MS). Methods: We used 2 case-control studies, one with incident cases (1,510 cases, 2,017 controls) and one with prevalent cases (937 cases, 609 controls). Subjects with different genotypes and BMI were compared with regard to incidence of MS by calculating odds ratios (ORs) with 95% confidence intervals (CIs) employing logistic regression. Potential interactions between genotypes and BMI were evaluated by calculating the attributable proportion due to interaction. Results: In both cohorts, a significant interaction was observed between HLA-DRB1*15 and obesity, regardless of HLA-A*02 status. Similarly, there was a significant interaction between absence of A*02 and obesity, regardless of DRB1*15 status. In the incident cohort, obese subjects with the most susceptible genotype (carriage of DRB1*15 and absence of A*02) had an OR of 16.2 (95% CI 7.5–35.2) compared to nonobese subjects without the genetic risk factors. The corresponding OR in the prevalent study was 13.8 (95% CI 4.1–46.8). Conclusions: We observed striking interactions between BMI status and HLA genotype with regard to MS risk. Hypothetically, a low-grade inflammatory response inherent to obesity synergizes with the adaptive, HLA molecule–restricted arm of the immune system, causing MS. Prevention of adolescent obesity may thus lower the risk of developing MS, predominantly among people with a genetic susceptibility to the disease.
Fundamentalism or pluralism: Iranian youth’s orientation

Islamic fundamentalism is an extreme perception of Islam that views ‘the “Other” as the enemy demonized’ against the ‘West’, which also views the Muslim ‘enemy within’. In contrast, pluralism perceives ‘others’ as different people, with different values from us. While the fundamentalist seeks to engage in war with the enemy/other, pluralism tolerates difference/conflict with others in peace and in the spirit of mutual acceptance. This article spells out the potential contributions to research regarding fundamentalism stemming from different approaches in Iran. Drawing on data collected from 31 individual in-depth interviews with Tehranian high school students and 206 questionnaires that were filled in by students who were randomly selected from 4 of 19 zones of Education in Tehran, their perceptions about pluralism and fundamentalism will be presented. The aim is to help move debate about fundamentalism beyond the pejorative labelling and to explore the concept of fundamentalism and pluralism in an Iranian context. As a case study, Tehranian pre-university students’ point of view about fundamentalism and pluralism will be discussed, in order to comprehend attitudes to fundamentalism and pluralism on the part of Iranian young people.
Sensors for the CDF Run2b silicon detector

We describe the characteristics of silicon microstrip sensors fabricated by Hamamatsu Photonics for the CDF Run 2b silicon detector. A total of 953 sensors, including 117 sensors from prototyping, have been produced and tested for electrical and mechanical properties. Five sensors were irradiated with neutrons up to 1.4/spl times/10/sup 14/ n/cm/sup 2/, as a part of the sensor quality assurance program. The electrical and mechanical characteristics are found to be superior in all aspects and fulfill our specifications.
Faculteit Economie En Bedrijfskunde Tweekerkenstraat 2 B-9000 Gent Some Thoughts on the Future of Cognitive Style Research

Considerable attention has been devoted to cognitive styles since the beginning of the previous century. Cognitive styles are extensively studied in diverse research domains. This large interest led to a wide diversity of cognitive style theories and studies. The development of the cognitive style field shows some similarity with the story of the 'blind men and the elephant', with researchers tending to study only one part of the whole, but none with full understanding. The aim of this article is to build further on previous suggestions for the advancement of the cognitive style field by focusing on six relevant, critical issues in the area of the theory, the measurement, and the practical relevance of cognitive styles: (1) the need for conceptual clarification to situate cognitive styles in the individual differences field, (2) the need for an overarching, contextualized individual differences model, (3) towards longitudinal, contextual research designs to find the origins of cognitive style, (4) the search for the fundamental cognitive style dimensions in the myriad of cognitive style models, (5) an evolution from self-report questionnaires to multi-source, multi-method approaches, and (6) bridging the relevance gap by different approaches of knowledge creation and knowledge dissemination. On the basis of an overview of past and present cognitive style research, we purport to suggest an agenda for future research in the field of cognitive styles. Ideally, cognitive style research evolves towards a 'pragmatic science', which combines high theoretical rigour with high practical relevance.
BUT SWS 2013 - Massive Parallel Approach

We submitted a system composed of 26 subsystems as the required run. 13 subsystems are based on Acoustic Keyword Spotting and 13 on DTW. All of them were using three state phoneme posteriors as input. The underlaying phoneme posterior estimators were both in-language (Czech, English) and out-of-language (other 12 languages). We also performed unsupervised adaptation of the artificial neural network (ANN) on the target data and fusion based on binary logistic regression. 1. MOTIVATION Our motivation was to use many (mostly) out-of-targetlanguages systems which can be combined by fusion at the detection level. The goal was to re-use as many trained systems available at BUT as possible. Please bear in mind that reusing all these systems (so-called Atomic Systems) lead to several inconsistencies among them — for example feature extraction and sizes of the ANN. We performed unsupervised adaptation of ANN on the target data (utterances). Our goal was also to test combination two approaches in the query-by-example task – Acoustic Keyword Spotting (AKWS) and Dynamic Time Warping (DTW). We also explored system calibration with respect to the TWV metric.
Modified Elite Chaotic Immune Clonal Selection Algorithm for sever resource allocation in cloud computing systems

Cloud computing is a promising technology to improve computational efficiency for both IT enterprise and individuals. Resource allocation in cloud computing is very challenging as both server computing power and network bandwidth are limited. The computational efficiency of cloud computing system can be significantly improved if the resources are allocated in a balanced fashion. However, resource allocation in cloud computing is a multi-constrained nonlinear optimization problem. The computational complexity for an exhaustive search over all combinations of resource allocations is too high for practical implementation. In this paper, we develop a Modified Elite Chaotic Immune Clonal Selection Algorithm to increase the overall efficiency of the system. An elite strategy and chaotic approaches are designed to improve population diversity and escape from local optima. Performance comparisons are made with simulated annealing algorithm (SA) and three other heuristic algorithms. Simulation results show that the Modified Elite Chaotic Immune Clonal Selection Algorithm solves the resource allocation problem with higher system resource efficiency than all other heuristic algorithms.
Shear stress activates monovalent cation channel transient receptor potential melastatin subfamily 4 in rat atrial myocytes via type 2 inositol 1,4,5‐trisphosphate receptors and Ca2+ release

During each contraction and haemodynamic disturbance, cardiac myocytes are subjected to fluid shear stress as a result of blood flow and the relative movement of sheets of myocytes. The present study aimed to characterize the shear stress‐sensitive membrane current in atrial myocytes using the whole‐cell patch clamp technique, combined with pressurized fluid flow, as well as pharmacological and genetic interventions of specific proteins. The data obtained suggest that shear stress indirectly activates the monovalent cation current carried by transient receptor potential melastatin subfamily 4 channels via type 2 inositol 1,4,5‐trisphosphate receptor‐mediated Ca2+ release in subsarcolemmal domains of atrial myocytes. Ca2+‐mediated interactions between these two proteins under shear stress may be an important mechanism by which atrial cells measure mechanical stress and translate it to alter their excitability.
P-Code: a new RAID-6 code with optimal properties

RAID-6 significantly outperforms the other RAID levels in disk-failure tolerance due to its ability to tolerate arbitrary two concurrent disk failures in a disk array. The underlying parity array codes have a significant impact on RAID-6's performance. In this paper, we propose a new XOR-based RAID-6 code, called the Partition Code (P-Code). P-Code is a very simple and flexible vertical code, making it easy to understand and implement. It works on a group of (prime-1) or (prime) disks, and its coding scheme is based on an equal partition of a specified two-integer-tuple set. P-Code has the following properties: (1) it is a Maximum-Distance-Separable (MDS) code, with optimal storage efficiency; (2) it has optimal construction and reconstruction computational complexity; (3) it has optimal update complexity (i.e., the number of parity blocks affected by a single data-block update is minimal). These optimal properties of P-Code are proven mathematically in this paper. While X-Code is provably optimal and RDP is proven optimal in computational complexity and storage efficiency, the latter in its current form is not optimal in update complexity. We propose a row-parity placement strategy for RDP to help it attain optimal update complexity. P-Code complements the other two optimal RAID-6 codes, X-code and the tweaked RDP, to provide a near-full set of optimal RAID-6 configurations of typical disk-array size (e.g., 4-20 disks). That is, for any prime in a typical array size range, P-code can be deployed for (prime-1) disks optimally, while X-code (or P-Code) and the tweaked RDP can be respectively deployed for (prime) and (prime+1) disks optimally. Moreover, P-code's potentially beneficial properties such as the flexible association between the blocks and their labels may find useful applications in distributed environments.
Hubs of Anticorrelation in High-Resolution Resting-State Functional Connectivity Network Architecture

A major focus of brain research recently has been to map the resting-state functional connectivity (rsFC) network architecture of the normal brain and pathology through functional magnetic resonance imaging. However, the phenomenon of anticorrelations in resting-state signals between different brain regions has not been adequately examined. The preponderance of studies on resting-state fMRI (rsFMRI) have either ignored anticorrelations in rsFC networks or adopted methods in data analysis, which have rendered anticorrelations in rsFC networks uninterpretable. The few studies that have examined anticorrelations in rsFC networks using conventional methods have found anticorrelations to be weak in strength and not very reproducible across subjects. Anticorrelations in rsFC network architecture could reflect mechanisms that subserve a number of important brain processes. In this preliminary study, we examined the properties of anticorrelated rsFC networks by systematically focusing on negative cross-correlation coefficients (CCs) among rsFMRI voxel time series across the brain with graph theory-based network analysis. A number of methods were implemented to enhance the neuronal specificity of resting-state functional connections that yield negative CCs, although at the cost of decreased sensitivity. Hubs of anticorrelation were seen in a number of cortical and subcortical brain regions. Examination of the anticorrelation maps of these hubs indicated that negative CCs in rsFC network architecture highlight a number of regulatory interactions between brain networks and regions, including reciprocal modulations, suppression, inhibition, and neurofeedback.
Quantization in the presence of large amplitude threshold noise

Signal quantization in the presence of independent, identically distributed, large amplitude threshold noise is examined. It has previously been shown that when all quantization thresholds are set to the same value, this situation exhibits a form of stochastic resonance known as suprathreshold stochastic resonance. This means the optimal quantizer performance occurs for a small input signal-to-noise ratio. Here we examine the performance of this stochastic quantization in terms of both mutual information and mean square error distortion. It is also shown that for low input signal-to-noise ratios that the case of all thresholds being identical provides the optimal mean square error distortion performance for the given noise conditions.
Caching incentive design in wireless D2D networks: A Stackelberg game approach

Caching in wireless device-to-device (D2D) networks can be utilized to offload data traffic during peak times. However, the design of incentive mechanisms is challenging due to the heterogeneous preference and selfish nature of user terminals (UTs). In this paper, we propose an incentive mechanism in which the base station (BS) rewards those UTs that share contents with others using D2D communication. We study the cost minimization problem for the BS and the utility maximization problem for each UT. In particular, the BS determines the rewarding policy to minimize his total cost, while each UT aims to maximize his utility by choosing his caching policy. We formulate the conflict among UTs and the tension between the BS and the UTs as a Stackelberg game. We show the existence of the equilibrium and propose an iterative gradient algorithm (IGA) to obtain the Stackelberg Equilibrium. Extensive simulations are carried out to evaluate the performance of the proposed caching scheme and comparisons are drawn with several baseline caching schemes with no incentives. Numerical results show that the caching scheme under our incentive mechanism outperforms other schemes in terms of the BS serving cost and the utilities of the UTs.
The Divided University: The impact of budget cuts on faculty in two disciplines

This article explores how budget cuts affected faculty in two departments—a physical sciences department and a humanities department—at one research university in the United States. Using theories of academic capitalism as a guide, the author focuses in particular on changes in governance structures and increasing competition between disciplines for resources and prestige. The article suggests that the physical sciences department was relatively spared, due to its ability to bring in external grants and the role played by the department head while the humanities department suffered from a mass exodus of faculty. Both departmental and institutional operations signal the ways in which universities are increasingly adopting market-like behaviours to survive.
Porcine LMNA Is a Positional Candidate Gene Associated with Growth and Fat Deposition

Crosses between Korean and Landrace pigs have revealed a large quantitative trait loci (QTL) region for fat deposition in a region (89 cM) of porcine chromosome 4 (SSC4). To more finely map this QTL region and identify candidate genes for this trait, comparative mapping of pig and human chromosomes was performed in the present study. A region in the human genome that corresponds to the porcine QTL region was identified in HSA1q21. Furthermore, the LMNA gene, which is tightly associated with fat augmentation in humans, was localized to this region. Radiation hybrid (RH) mapping using a Sus scrofa RH panel localized LMNA to a region of 90.3 cM in the porcine genome, distinct from microsatellite marker S0214 (87.3 cM). Two-point analysis showed that LMNA was linked to S0214, SW1996, and S0073 on SSC4 with logarithm (base 10) of odds scores of 20.98, 17.78, and 16.73, respectively. To clone the porcine LMNA gene and to delineate the genomic structure and sequences, including the 3′untranslated region (UTR), rapid amplification of cDNA ends was performed. The coding sequence of porcine LMNA consisted of 1,719 bp, flanked by a 5’UTR and a 3’UTR. Two synonymous single nucleotide polymorphisms (SNPs) were identified in exons 3 and 7. Association tests showed that the SNP located in exon 3 (A193A) was significantly associated with weight at 30 wks (p<0.01) and crude fat content (p<0.05). This association suggests that SNPs located in LMNA could be used for marker-assisted selection in pigs.
G(-2548)A leptin gene polymorphism in obese subjects is associated with serum leptin concentration and bone mass.

INTRODUCTION Clinical studies have shown either positive or in some other cases negative correlations between leptinemia and bone mineral density (BMD) or bone mineral content (BMC). OBJECTIVES The aim of the present study was to assess whether these discrepancies might be associated with the effect of G(-2548)A leptin or A326G and A668G leptin receptor gene polymorphisms on serum leptin concentrations or BMD and BMC. PATIENTS AND METHODS The study included 72 obese patients (39 women and 33 men, aged 46 +/-8.8 years; body mass index [BMI] >30 kg/m2). In all subjects, serum creatinine, glucose, lipids, leptin, and insulin were determined. Total fat mass (TFM), BMC, and BMD were assessed using dual energy X-ray absorptiometry (Lunar DPX-L). RESULTS No significant correlations were observed between body mass composition parameters (TFM, lean mass, BMC) or BMD in relation to genotypes. A positive correlation was found between serum leptin concentration and BMI. An inverse association was observed between leptin concentrations and BMC. Multiple regression analysis showed independent correlations of leptinemia with sex (P <0.001), TFM (P <0.000 001), BMC (P = 0.0001), and the presence of (-2548)A allele of the leptin gene (P <0.05). These parameters together accounted for 83% of variability in serum leptin concentrations. CONCLUSIONS In obese patients, serum leptin concentration shows an independent inverse correlation with BMD and male sex, but positively with TFM and the presence of -2548A allele of leptin gene. These parameters are responsible for 83% of leptin concentration variability. No correlations between the examined polymorphisms and BMC or BMD were found.