Miracle-dz/UniFAR-FTUs huggingface dataset:
Crack and fracture theory of liquid crystals and quasicrystals

Liquid crystals and quasicrystals are fascinating phases of modern physics and chemistry, they are also important materials in current and potential applications. The liquid crystals belong to intermediate phase between fluids and solids in macroscopic sense, they present behaviour of anisotropic fluids, i.e., they behave both characters of conventional fluids and anisotropic elastic solids. The quasicrystals present unusual mechanical and physical properties due to the atomic arrangement being quite different from that of conventional crystals. To describe the mechanical behaviour of quasicrystals, one must introduce two different displacement fields, this leads to two different strain tensors and two stress tensors. This paper reports some results in the study on crack and fracture problems of liquid crystals and quasicrystals. The nonlinear fracture analysis is important for the both materials. However there is fundamental difficulty in the analysis due to lack of plastic constitutive equations for them. Some physical models and relevant mathematical methods are developed to overcome the difficulty, and some results have been obtained, which are of a development of fracture theory of conventional structural materials.
Using social data as context for making recommendations: an ontology based approach

Web-based knowledge systems support an impressive and growing amount of information. Among the difficulties faced by these systems is the problem of overwhelming the user with a vast amount of data, often referred to as information overload. The problem has escalated with the ever increasing issues of time constraints and the extensive use of handheld devices. The use of context is one possible way out helping with this situation. To provide a more robust approach to context gathering we propose the use of Social Web technologies alongside the Semantic Web. As the social web is heavily used it could provide a better understanding of a user's interests and intentions. The proposed system gathers information about users from their social web identities and enriches it with ontological knowledge. Thus an interest model for the user can be created which can serve as a good source of contextual knowledge. This work bridges the gap between the user and system searches by analyzing the virtual existence of a user and making interesting recommendations accordingly.
Extracorporeal membrane oxygenation as a rescue measure after thoracic surgery

Background Extracorporeal membrane oxygenation is used for many different conditions including respiratory distress, cardiogenic shock, and trauma. In these patient groups, extracorporeal membrane oxygenation has been extensively studied. Recently, it has been used as a rescue measure in patients experiencing acute respiratory distress after thoracic surgery. The goal of our study was to examine the efficacy and cost-effectiveness of extracorporeal membrane oxygenation as a rescue measure after thoracic surgery at a single center. Methods We conducted a retrospective review of all patients who received extracorporeal membrane oxygenation after thoracic surgery at the University of Kentucky from January 9, 2012 to January 9, 2017. Eight patients were identified. Results The average time on extracorporeal membrane oxygenation was 9.125 days, and the average hospital stay was 65.125 days. Of the 8 patients placed on extracorporeal membrane oxygenation, 3 survived to discharge. Of the 3 patients who survived to discharge, 1 died within 6 months and 2 have been followed up for less than 4 months. The average total charge per patient was calculated to be $1,053,551, and the average charge per day was $16,177. The contribution margin was $109,200 per case. Conclusions Extracorporeal membrane oxygenation is a tool that saves lives in many different patient populations but it does not appear to be as effective in patients experiencing acute respiratory distress syndrome after thoracic surgery. Extracorporeal membrane oxygenation in this group also uses a tremendous amount of hospital resources.
Humor as a Reward Mechanism: Event-Related Potentials in the Healthy and Diseased Brain

Humor processing involves distinct processing stages including incongruity detection, emotional response, and engagement of mesolimbic reward regions. Dysfunctional reward processing and clinical symptoms in response to humor have been previously described in both hypocretin deficient narcolepsy-cataplexy (NC) and in idiopathic Parkinson disease (PD). For NC patients, humor is the strongest trigger for cataplexy, a transient loss of muscle tone, whereas dopamine-deficient PD-patients show blunted emotional responses to humor. To better understand the role of reward system and the various contributions of hypocretinergic and dopaminergic mechanisms to different stages of humor processing we examined the electrophysiological response to humorous and neutral pictures when given as reward feedback in PD, NC and healthy controls. Humor compared to neutral feedback demonstrated modulation of early ERP amplitudes likely corresponding to visual processing stages, with no group differences. At 270 ms post-feedback, conditions showed topographical and amplitudinal differences for frontal and left posterior electrodes, in that humor feedback was absent in PD patients but increased in NC patients. We suggest that this effect relates to a relatively early affective response, reminiscent of increased amygdala response reported in NC patients. Later ERP differences, corresponding to the late positive potential, revealed a lack of sustained activation in PD, likely due to altered dopamine regulation in reward structures in these patients. This research provides new insights into the temporal dynamics and underlying mechanisms of humor detection and appreciation in health and disease.
Discovering Loners and Phantoms in Commit and Issue Data

The interlinking of commit and issue data has become a de-facto standard in software development. Modern issue tracking systems, such as JIRA, automatically interlink commits and issues by the extraction of identifiers (e.g., Issue key) from commit messages. However, the conventions for the use of interlinking methodologies vary between software projects. For example, some projects enforce the use of identifiers for every commit while others have less restrictive conventions. In this work, we introduce a model called PaLiMod to enable the analysis of interlinking characteristics in commit and issue data. We surveyed 15 Apache projects to investigate differences and commonalities between linked and non-linked commits and issues. Based on the gathered information, we created a set of heuristics to interlink the residual of non-linked commits and issues. We present the characteristics of Loners and Phantoms in commit and issue data. The results of our evaluation indicate that the proposed PaLiMod model and heuristics enable an automatic interlinking and can indeed reduce the residual of non-linked commits and issues in software projects.
Biochemical Characterization of Two Clinically-Relevant Human Fumarase Variants Defective for Oligomerization

Background: Fumarase, a significant enzyme of energy metabolism, catalyzes the reversible hydration of fumarate to L-malate. Mutations in the FH gene, encoding human fumarase, are associated with fumarate hydratase deficiency (FHD) and hereditary leiomyomatosis and renal cell cancer (HLRCC). Fumarase assembles into a homotetramer, with four active sites. Interestingly, residues from three of the four subunits within the homotetramer comprise each active site. Hence, any mutation affecting oligomerization is predicted to disrupt enzyme activity. Methods: We constructed two variants of hexahistidine-tagged human recombinant fumarase, A308T and H318Y, associated with FHD and HLRCC, respectively. Both Ala308 and His318 lie within the fumarase intersubunit interface. We purified unmodified human fumarase and the two variants, and analyzed their enzymatic activities and oligomerization states in vitro. Results: Both variants showed severely diminished fumarase activity. Steady-state kinetic analysis demonstrated that the variants were largely defective due to decreased turnover rate, while displaying Km values for L-malate similar to unmodified human recombinant fumarase. Blue native polyacrylamide gel electrophoresis and gel filtration experiments revealed that each variant had an altered oligomerization state, largely forming homodimers rather than homotetramers. Conclusion: We conclude that A308T and H318Y render human fumarase enzymatically inactive via defective oligomerization. Therefore, some forms of FHD and HLRCC can be linked to improperly folded quaternary structure.
Inducted currents analysis in multiply connected conductors using reluctance-resistance networks

Purpose – The purpose of this paper is to develop a reluctance-resistance network (RRN) formulation for determining the induced current distributions in a 3D space of multiply connected conducting systems. Design/methodology/approach – The proposed RRN method has been applied to solve Problem No. 7 of the International TEAM Workshops. The induced currents in the conductive plate with an asymmetrically situated “hole” have been analysed. The RRN equations have been formed by means of the finite element method using the magnetic vector potential A and the electric vector potentials T and T0. The block relaxation method combined with the Cholesky decomposition procedure has been applied to solve the resultant RRN equations. Findings – Comparison with results published in literature has demonstrated high accuracy of the proposed RRN computational scheme while offering significant savings in computing times. Originality/value – A novel formulation of the RRN approach has been proposed and demonstrated to be computationally efficient.
Wide angle virtual view synthesis using two-by-two Kinect V2

In this paper, we propose a wide-angle view synthesis system based on captured multiple images and depth maps. We use a two-by-two array of Kinect v2 cameras to facilitate virtual camera tilt and zoom-in cases. We integrate two essential components developed by our lab colleagues to form a complete and practical system Two additional elements are designed and implemented in this study. The first element is an improved multi-view blending algorithm that provides a clear improvement on the synthesized image quality even though the warping process induces some artifacts. By using four RGB-D cameras to capture the reference views, we have sufficient information to decide which pixel in the warped views is erroneous and we replace it by choosing the correct virtual color pixel from the other warped views to generate the synthesized pixel. The second element is solving the asynchronization problem among multiple Kinects in capturing images/videos. For simplicity, our first attempt is implementing a clock calibration system based on PC clock synchronization software. We examine the quality of synthesized views for various camera tilt and zoom-in/out cases. Experimental results show that the proposed multi-view blending algorithm achieves good synthesized image subjective quality on the real world images captured by four Kinect v2 sensors.
Human Pancreatic Islet Preparations Release HMGB1: (Ir)Relevance for Graft Engraftment

High levels of donor-derived high-mobility group box 1 (HMGB1) protein have been associated with poor islet graft outcome in mouse models. The aim of our work was to determine whether HMGB1 released by human islets had independent proinflammatory effects that influence engraftment in humans. Human islet preparations contained and released HMGB1 in different amounts, as determined by Western blot and ELISA (median 17 pg/ml/IEQ/24 h; min–max 0–211, n = 74). HMGB1 release directly correlated with brain death, donor hyperamilasemia, and factors related to the pancreas digestion procedure (collagenase and digestion time). HMGB1 release was significantly positively associated with the release of other cytokines/chemokines, particularly with the highly released “proinflammatory” CXCL8/IL-8, CXCL1/GRO-α, and the IFN-γ-inducible chemokines CXCL10/IP-10 and CXCL9/MIG. HMGB1 release was not modulated by Toll-like receptor 2, 3, 4, 5, and 9 agonists or by exposure to IL-1β. When evaluated after islet transplantation, pretransplant HMGB1 release was weakly associated with the activation of the coagulation cascade (evaluated as serum cross-linked fibrin products), but not with the immediate posttransplant inflammatory response. Concordantly, HMGB1 did not affect short-term human islet function. Our data show that human islet HMGB1 release is a sign of “damaged” islets, although without any independent direct role in graft failure.
Simultaneous acquisition of gradient echo/spin echo BOLD and perfusion with a separate labeling coil

Arterial spin labeling‐based cerebral blood flow imaging complements blood oxygenation level dependent (BOLD) imaging with a measure that is more quantitative and has better specificity to neuronal activation. Relative to gradient echo BOLD, spin echo BOLD has better spatial specificity because it is less biased to large draining veins. Although there have been many studies comparing simultaneously acquired cerebral blood flow data with gradient echo BOLD data in fMRI, there have been few studies comparing cerebral blood flow with SE BOLD and no study comparing all three. We present a pulse sequence that simultaneously acquires cerebral blood flow data with a separate labeling coil, gradient echo BOLD, and spin echo BOLD images. Simultaneous acquisition avoids interscan variability, allowing more direct assessment and comparison of each contrast's relative specificity and reproducibility. Furthermore, it facilitates studies that may benefit from multiple complementary measures. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.
Hard work at home: musculoskeletal pain among female homemakers

This study explores the relationship between housework and musculoskeletal symptoms among homemakers, adjusting for social, demographic and economic factors. A cross-sectional survey was carried out on 435 women from Nabaa, a low-income community in Lebanon. In total, 77% of women reported having musculoskeletal pain in the previous 12 months. Both psychosocial and physical factors showed significant associations with musculoskeletal symptoms. Related psychosocial factors included feelings of stress associated with homemaking and homemakers' number of children and self-rated health. The physical factors associated with musculoskeletal pain were feeling fatigued at the end of a housework day, working long hours and working in awkward postures or frequently engaging in repetitive hand movements. Ergonomic stressors were also associated with pain in the back and upper and lower extremities. Women from this community engage in a large number of hours of housework that, alongside other factors, were associated with high prevalence of musculoskeletal pain. Practitioner Summary: This study contributes to the literature by studying women's housework activities in association with musculoskeletal pain. The role of women in homemaking activities is explored together with physical exposures leading to reported symptoms. This study adds a perspective of a Middle Eastern context to the literature of women's musculoskeletal health.
Protein S-Nitrosylation Regulates Xylem Vessel Cell Differentiation in Arabidopsis

Post-translational modifications of proteins have important roles in the regulation of protein activity. One such modification, S-nitrosylation, involves the covalent binding of nitric oxide (NO)-related species to a cysteine residue. Recent work showed that protein S-nitrosylation has crucial functions in plant development and environmental responses. In the present study, we investigated the importance of protein S-nitrosylation for xylem vessel cell differentiation using a forward genetics approach. We performed ethyl methanesulfonate mutagenesis of a transgenic Arabidopsis 35S::VND7-VP16-GR line in which the activity of VASCULAR-RELATED NAC-DOMAIN7 (VND7), a key transcription factor involved in xylem vessel cell differentiation, can be induced post-translationally by glucocorticoid treatment, with the goal of obtaining suppressor mutants that failed to differentiate ectopic xylem vessel cells; we named these mutants suppressor of ectopic vessel cell differentiation induced by VND7 (seiv) mutants. We found the seiv1 mutant to be a recessive mutant in which ectopic xylem cell differentiation was inhibited, especially in aboveground organs. In seiv1 mutants, a single nucleic acid substitution (G to A) leading to an amino acid substitution (E36K) was present in the gene encoding S-NITROSOGLUTATHIONE REDUCTASE 1 (GSNOR1), which regulates the turnover of the natural NO donor, S-nitrosoglutathione. An in vitro S-nitrosylation assay revealed that VND7 can be S-nitrosylated at Cys264 and Cys320 located near the transactivation activity-related domains, which were shown to be important for transactivation activity of VND7 by transient reporter assay. Our results suggest crucial roles for GSNOR1-regulated protein S-nitrosylation in xylem vessel cell differentiation, partly through the post-translational modification of VND7.
Optimization Design and Realization of Ceph Storage System Based on Software Defined Network

Under the traditional network architecture, Ceph, a hybrid distributed file system, uses storage capacity as the unique constraint condition to select storage node in replication scheme. In addition, considering network conditions and the load status can improve the performance of the cloud storage system when facing complex network environment and node high load. Software-defined network architecture, which applied to Ceph to obtain the node network and load status in the real time, can be used as weight factor to select storage node and optimize cluster performance. Read and write operation tests show that in a real environment, the prototype design is not obvious for the performance improvement of the write operation, but in read operations, the throughput of the small file and the response time of the large file are significantly improved.
Lightweight Aggregate Self-Compacting Concrete: State-of-the-Art & Pumice Application

The scope of this study is twofold: first to present the current state-of-knowledge on lightweight aggregate self-compacting concrete (LWASCC) and second to discuss the development of pumice aggregate self-compacting concrete (PASCC) falling in the LC20/22 strength class and D1.4 density class (as per EN 206-1). Former studies have showed that the commonly accepted range of values derived from fresh-state tests on normal weight self-compacting concrete (NWSCC) is also attainable for LWASCC, the majority of which is produced using artificial lightweight aggregates. The second part of the paper presents the findings of an experimental program that aimed to assess the effect of coarse-to-fine pumice aggregates ratio on the rheological and mechanical properties of PASCC. Based on the results of this study it is verified that properly designed PASCC mixtures with a dry density in the order of 1400 kg/m3 may be evaluated while in fresh state using the same test methods applicable for normal weight self-compacting concrete (NWSCC) and yield scores that lie within the commonly accepted ranges. If pumice aggregates are introduced in the mix in a saturated state, PASCC exhibits self-compactness similar to the one typically characterizing most NWSCC mixtures. Surface coating of fine and coarse pumice aggregates - though difficult in practice - improves workability and prolongs its retention.
SozRank: A new approach for localizing the epileptic seizure onset zone

Epilepsy is one of the most common neurological disorders affecting about 1% of the world population. For patients with focal seizures that cannot be treated with antiepileptic drugs, the common treatment is a surgical procedure for removal of the seizure onset zone (SOZ). In this work we introduce an algorithm for automatic localization of the seizure onset zone (SOZ) in epileptic patients based on electrocorticography (ECoG) recordings. The proposed algorithm builds upon the hypothesis that the abnormal excessive (or synchronous) neuronal activity in the brain leading to seizures starts in the SOZ and then spreads to other areas in the brain. Thus, when this abnormal activity starts, signals recorded at electrodes close to the SOZ should have a relatively large causal influence on the rest of the recorded signals. The SOZ localization is executed in two steps. First, the algorithm represents the set of electrodes using a directed graph in which nodes correspond to recording electrodes and the edges’ weights quantify the pair-wise causal influence between the recorded signals. Then, the algorithm infers the SOZ from the estimated graph using a variant of the PageRank algorithm followed by a novel post-processing phase. Inference results for 19 patients show a close match between the SOZ inferred by the proposed approach and the SOZ estimated by expert neurologists (success rate of 17 out of 19).
Safety Biomarkers in Preclinical Development

The identification, application, and qualification of safety biomarkers are becoming increasingly critical to successful drug discovery and development as companies are striving to develop drugs for difficult targets and for novel disease indications in a risk-adverse environment. Translational safety biomarkers that are minimally invasive and monitor drug-induced toxicity during human clinical trials are urgently needed to assess whether toxicities observed in preclinical toxicology studies are relevant to humans at therapeutic doses. The interpretation of data during the biomarker qualification phase should include careful consideration of the analytic method used, the biology, pharmacokinetic and pharmacodynamic properties of the biomarker, and the pathophysiology of the process studied. The purpose of this review is to summarize commonly employed technologies in the development of fluid- and tissue-based safety biomarkers in drug discovery and development and to highlight areas of ongoing novel assay development.
Learning Invariance with Compact Transforms

The problem of building machine learning models that admit efficient representations and also capture an appropriate inductive bias for the domain has recently attracted significant interest. Existing work for compressing deep learning pipelines has explored classes of structured matrices that exhibit forms of shift-invariance akin to convolutions. We leverage the displacement rank framework to automatically learn the structured class, allowing for adaptation to the invariances required for a given dataset while preserving asymptotically efficient multiplication and storage. In a setting with a small fixed parameter budget, our broad classes of structured matrices improve final accuracy by 5–7% on standard image classification datasets compared to conventional parameter constraining methods.