Miracle-dz/UniFAR-FTUs huggingface dataset:
Concurrent Robin Hood Hashing

In this paper we examine the issues involved in adding concurrency to the Robin Hood hash table algorithm. We present a non-blocking obstruction-free K-CAS Robin Hood algorithm which requires only a single word compare-and-swap primitive, thus making it highly portable. The implementation maintains the attractive properties of the original Robin Hood structure, such as a low expected probe length, capability to operate effectively under a high load factor and good cache locality, all of which are essential for high performance on modern computer architectures. We compare our data-structures to various other lock-free and concurrent algorithms, as well as a simple hardware transactional variant, and show that our implementation performs better across a number of contexts.
Association between Functional Dyspepsia and Gastric Depressive Erosions in Japanese Subjects

Objective The association between functional dyspepsia (FD) and endoscopic findings has not been fully elucidated. Helicobacter pylori infection is considered a key factor in the pathophysiology of FD. The Kyoto Classification of Gastritis (KCG) was proposed in 2014 to evaluate endoscopic findings based on the H. pylori status. We investigated the endoscopic findings associated with FD according to the KCG. Methods This cross-sectional study included subjects who underwent esophagogastroduodenoscopy during a medical health check-up. We compared the endoscopic findings between subjects with FD and healthy controls (HCs) according to the KCG. Results A total of 456 subjects were analyzed. Among them, the detection rate of FD was 5.5% (25/456 persons). In a univariate analysis of the endoscopic findings, a significantly lower proportion of subjects with FD had gastric red streak in comparison to HCs (0% vs. 18.6%, respectively; p=0.0124). Subjects with FD were more likely to have gastric depressive erosion (20.0% vs. 7.9%; p=0.0522). A higher proportion of the erosion-positive subjects had FD in comparison to erosion-negative subjects (12.8% vs. 4.8%). There were no significant differences in the other endoscopic findings, including gastric atrophy, intestinal metaplasia, enlarged fold, nodularity, and diffuse redness. A multivariate analysis revealed that gastric depressive erosion was significantly and independently associated with FD (odds ratio, 2.92; 95% confidence interval, 1.03-8.26; p=0.0436). In contrast, gastric red streak was not associated with FD (p=0.989). Conclusion Gastric depressive erosions may be associated with dyspepsia.
Repeated Intrastriatal Botulinum Neurotoxin-A Injection in Hemiparkinsonian Rats Increased the Beneficial Effect on Rotational Behavior

Injection of botulinum neurotoxin-A (BoNT-A) into the striatum of hemiparkinsonian (hemi-PD) rats reduced apomorphine-induced rotation behavior significantly, for at least 3 months. Thereafter, rotation behavior increased again. We injected hemi-PD rats with 1 ng BoNT-A twice, the second injection following 6 months after the first one and tested the rats for apomorphine-induced rotations and spontaneous motor behaviors, i.e., corridor task and stepping test. To test the hypothesis that BoNT-A reduced striatal hypercholinism in hemi-PD rats, the acetylcholinesterase inhibitor donepezil was injected prior to separate apomorphine-induced rotation tests. In hemi-PD rats, the first BoNT-A injection led to a clear reduction of the apomorphine-induced rotations, and the second BoNT-A injection to a more massive and prolonged reaction. In hemi-PD rats whose apomorphine-induced rotation behavior was strongly reduced by an intrastriatal BoNT-A, subsequent donepezil injections led to significant increases of the rotation rate. Concerning corridor task and stepping test, neither first nor second BoNT-A injections changed hemi-PD rats’ behavior significantly. The data give evidence for the possibility of repeated intrastriatal administrations of BoNT-A, for treatment of motor symptoms in experimental hemi-PD over a longer time.
Is together better? Examining scientific collaborations across multiple authors, institutions, and departments

Collaborations are an integral part of scientific research and publishing. In the past, access to large-scale corpora has limited the ways in which questions about collaborations could be investigated. However, with improvements in data/metadata quality and access, it is possible to explore the idea of research collaboration in ways beyond the traditional definition of multiple authorship. In this paper, we examine scientific works through three different lenses of collaboration: across multiple authors, multiple institutions, and multiple departments. We believe this to be a first look at multiple departmental collaborations as we employ extensive data curation to disambiguate authors' departmental affiliations for nearly 70,000 scientific papers. We then compare citation metrics across the different definitions of collaboration and find that papers defined as being collaborative were more frequently cited than their non-collaborative counterparts, regardless of the definition of collaboration used. We also share preliminary results from examining the relationship between co-citation and co-authorship by analyzing the extent to which similar fields (as determined by co-citation) are collaborating on works (as determined by co-authorship). These preliminary results reveal trends of compartmentalization with respect to intra-institutional collaboration and show promise in being expanded.
Feasibility of ALOS2 PALSAR2 Offset-Based Phase Unwrapping of SAR Interferogram in Large and Complex Surface Deformations

The interferometric synthetic aperture radar (InSAR) is a well-known tool for mapping ground surface deformations with centimeter precision, and is much better than that used in the offset tracking method. However, the InSAR method has difficulties in precisely measuring large deformation signals because the phase unwrapping can include severe errors in the case of large and complex deformations. To overcome this drawback, an offset-based unwrapping strategy was proposed. However, this strategy has almost never been used for the unwrapping approach because the accuracy of offset measurement is much lower than that of InSAR measurement. As the spatial resolution of the SAR image becomes more precise, the offset measurement accuracy increases. Specifically, the L-band ALOS2 PALSAR2 sensor has much higher offset measurement accuracy due to its higher spatial resolution. In this paper, the feasibility of the unwrapping of a PALSAR-2 interferometric phase with large surface deformation signals, using an offset map, is proved. This validation of offset-based unwrapping was performed using two ALOS2 PALSAR2 co-seismic pairs in the 2016 Kumamoto earthquake where large deformations of more than 200 cm occurred. The offset-based unwrapping was more successful than traditional unwrapping. The root-mean square errors of offset-based unwrapping using GPS in situ data were about 1.96 and 1.90 cm in the ascending and descending pairs, respectively. The validation results showed that the ALOS2 PALSAR2 offset-based unwrapping enables us to measure complex and large deformation signals accurately. Precise measurements in high-gradient and high-decorrelated deformation areas would be helpful to better understand geological mechanisms.
Risk Factors for Manipulation Under Anesthesia and/or Lysis of Adhesions After Anterior Cruciate Ligament Reconstruction

Background: In the currently published literature, a higher risk for developing arthrofibrosis after anterior cruciate ligament (ACL) reconstruction has been reported for female patients, adolescents, early surgery or concomitant procedures, and the use of a patellar tendon autograft. There is a lack of evidence regarding other graft choices or factors. Hypothesis: Multiple risk factors will play a significant role in the development of arthrofibrosis after ACL reconstruction. Specifically, we hypothesized that the risk of manipulation under anesthesia (MUA) and/or lysis of adhesions (LOA) would be affected by graft choice and patient demographic factors. Study Design: Case-control study; Level of evidence, 3. Methods: The charts of all patients who underwent ACL reconstruction over a 10-year period at a single academic institution were queried from an electronic medical record database and reviewed at a minimum of 6 months after ACL reconstruction, with the collection of demographic and surgical data. The relative risk for undergoing MUA and/or LOA was calculated for each analyzed risk factor. Results: A total of 2424 ACL reconstructions were included, with a chart review at a mean of 56.7 months after surgery (range, 7.6-124.0 months). The rate of MUA and/or LOA for arthrofibrosis was 4.5%. A statistically significantly increased relative risk was found for infection (5.45), hematoma requiring evacuation (3.55), ACL reconstruction with meniscal repair (2.83), use of a quadriceps tendon autograft (2.68), age <18 years (2.39), multiple concomitant procedures (1.69), contact injury (1.62), female sex (1.60), and surgery within 28 days of injury (1.53), and a statistically significantly decreased relative risk was found for revision ACL reconstruction (0.30), age >25 years (0.34), and use of a tibialis anterior allograft (0.36). In the multivariate regression model, the use of a quadriceps tendon autograft (P = .00007), infection (P = .00126), and concomitant meniscal repair (P = .00194) were independent risk factors, whereas revision ACL reconstruction (P = .0024) was an independent protective factor. Conclusion: Graft type, infection, concomitant meniscal repair, and primary reconstruction are significant risk factors for undergoing MUA or LOA after ACL reconstruction.
Comparison of Effects of Melatonin and Gabapentin on Post Operative Anxiety and Pain in Lumbar Spine Surgery: A Randomized Clinical Trial

Background Surgery is one of the stressors that cause physiological and psychological stress. Anxiety and pain and their complications are very important in anesthesiology and many researches have been done to decrease or eliminate them. This training was done to compare the effect of melatonin and gabapentin on pain and anxiety during lumbar surgery. Methods This study was a double-blinded clinical trial conducted on 90 patients undergoing lumbar surgery with general anesthesia in Golestan Academic Hospital in 2017. Patients were randomly assigned into 3 groups: 30 patients received 6 mg melatonin, 30 patients received 600 mg gabapentin, and 30 patients were on placebo (control), 100 minutes preoperatively. All patients were given a fixed method of anesthesia. The pain intensity and patients’ satisfaction from analgesia measured at 1, 2, 6, 12, and 24 h after surgery. The anxiety was measured 15 minutes before surgery and 1, 2, 6, 12, and 24 h after surgery. Results In our study, there was a significant difference between mean Visual Analog Score between melatonin and gabapentin groups in comparison to placebo (P = 0.02). The intensity of anxiety among the groups was lower in melatonin and gabapentin groups in comparison to placebo (P = 0.01). Conclusions The results show that pretreatment with melatonin or gabapentin decreases anxiety and pain in lumbar surgery.
Facebook Social Media for Depression Detection in the Thai Community

Depression is one of the leading mental health problems. It is a cause of psychological disability and economic burden to a country. Around 1.5 Thai people suffer from depression and its prevalence has been growing up fast. Although it is a serious psychological problem, less than a half of those who have this emotional problem gained access to mental health service. This could be a result of many factors including having lack awareness about the disease. One of the solutions would be providing a tool that depression could be easily and early detected. This would help people to be aware of their emotional states and seek help from professional services. Given Facebook is the most popular social network platform in Thailand, it could be a largescale resource to develop a depression detection tool. This research employs Natural Language Processing (NLP) techniques to develop a depression detection algorithm for the Thai language on Facebook where people use it as a tool for sharing opinions, feelings, and life events. Results from 35 Facebook users indicated that Facebook behaviours could predict depression level.
Cuffed Versus Uncuffed Endotracheal Tubes in Pediatrics: A Meta-analysis

Abstract Background Cuffed and uncuffed endotracheal tubes are commonly used for pediatric patients in surgery and emergency situations. It is still controversial which approach should be adopted. The purpose of the study was to compare the application of cuffed and uncuffed endotracheal tubes in pediatric patients. Methods We searched PubMed, Web of Science and Cochrane Library for clinical trials, which compared the two applications in children. The study characteristics and clinical data were summarized by two independent reviewers. Meta-analysis of the data was done using Revman 5.3 software. Results 6 studies with 4141 cases were included in this meta-analysis. The pooling analysis showed that more patients need tube changes in uncuffed than cuffed tubes (OR: 0.07, 95% CI: 0.05-0.10, P < 0.00001). However, there were no differences on intubation duration, reintubation occurrence, accidental extubation rate, croup occurrence and racemic epinephrine use during the intubation process. Also we didn’t find any differences on laryngospasm and stridor occurrence after extubation. Conclusions Our study demonstrated that uncuffed endotracheal tubes increased the need for tube changes. Other incidences or complications between the two groups had no differences. Cuffed tubes may be an optimal option for pediatric patients. But more trials are needed in the future.
Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm

A novel procedure is presented in this paper, for training a deep convolutional and recurrent neural network, taking into account both the available training data set and some information extracted from similar networks trained with other relevant data sets. This information is included in an extended loss function used for the network training, so that the network can have an improved performance when applied to the other data sets, without forgetting the learned knowledge from the original data set. Facial expression and emotion recognition in-the-wild is the test bed application that is used to demonstrate the improved performance achieved using the proposed approach. In this framework, we provide an experimental study on categorical emotion recognition using datasets from a very recent related emotion recognition challenge.
Multi-task Deep Reinforcement Learning with PopArt

The reinforcement learning (RL) community has made great strides in designing algorithms capable of exceeding human performance on specific tasks. These algorithms are mostly trained one task at the time, each new task requiring to train a brand new agent instance. This means the learning algorithm is general, but each solution is not; each agent can only solve the one task it was trained on. In this work, we study the problem of learning to master not one but multiple sequentialdecision tasks at once. A general issue in multi-task learning is that a balance must be found between the needs of multiple tasks competing for the limited resources of a single learning system. Many learning algorithms can get distracted by certain tasks in the set of tasks to solve. Such tasks appear more salient to the learning process, for instance because of the density or magnitude of the in-task rewards. This causes the algorithm to focus on those salient tasks at the expense of generality. We propose to automatically adapt the contribution of each task to the agent’s updates, so that all tasks have a similar impact on the learning dynamics. This resulted in state of the art performance on learning to play all games in a set of 57 diverse Atari games. Excitingly, our method learned a single trained policy - with a single set of weights - that exceeds median human performance. To our knowledge, this was the first time a single agent surpassed human-level performance on this multi-task domain. The same approach also demonstrated state of the art performance on a set of 30 tasks in the 3D reinforcement learning platform DeepMind Lab.
Improving Single Image Haze Removal Based On Cellular Automata Model

Hazy images are the images acquired under bad weather with low contrast and faint color properties. Several algorithms used dichromatic model to remove the haze in the image. This paper proposed a novel technique using cellular automata for the single image haze removal. It aims to improve the dark channel and the transmission map. We proposed the cellular automata rule to refine the intensity of image pixel in a dark channel. Then, the light source is estimated from the dark channel. Finally, we proposed the cellular automata rule to construct the transmission map and restored the haze-free image. The experimental results show that the proposed method improved intensity, color saturation quality, and avoid halo artifact without any post-processing when compared with the state-of-the-art methods.
LRRK2 and its substrate Rab GTPases are sequentially targeted onto stressed lysosomes and maintain their homeostasis

Significance LRRK2, a protein kinase related to Parkinson’s disease, is implicated in the maintenance of lysosomes, and a subset of Rab GTPases has been identified as bona fide substrates of LRRK2. Here, we reveal a key stress-responsive pathway composed of Rab7L1, LRRK2, and phosphorylated Rab8/10 involved in lysosomal homeostasis. Lysosomal overload stress induces translocation of Rab7L1 and LRRK2 to lysosomes, where LRRK2 is activated, and stabilizes Rab8 and Rab10 through phosphorylation. The activation of this machinery protects against lysosomal enlargement and upregulates lysosomal secretion through Rab effectors, EHBP1 and EHBP1L1. These findings elucidate a novel regulatory mechanism of Rab GTPases by phosphorylation by LRRK2 in stressed lysosomes, which may also be involved in the pathomechanism of LRRK2-related disorders. Leucine-rich repeat kinase 2 (LRRK2) has been associated with a variety of human diseases, including Parkinson’s disease and Crohn’s disease, whereas LRRK2 deficiency leads to accumulation of abnormal lysosomes in aged animals. However, the cellular roles and mechanisms of LRRK2-mediated lysosomal regulation have remained elusive. Here, we reveal a mechanism of stress-induced lysosomal response by LRRK2 and its target Rab GTPases. Lysosomal overload stress induced the recruitment of endogenous LRRK2 onto lysosomal membranes and activated LRRK2. An upstream adaptor Rab7L1 (Rab29) promoted the lysosomal recruitment of LRRK2. Subsequent family-wide screening of Rab GTPases that may act downstream of LRRK2 translocation revealed that Rab8a and Rab10 were specifically accumulated on overloaded lysosomes dependent on their phosphorylation by LRRK2. Rab7L1-mediated lysosomal targeting of LRRK2 attenuated the stress-induced lysosomal enlargement and promoted lysosomal secretion, whereas Rab8 stabilized by LRRK2 on stressed lysosomes suppressed lysosomal enlargement and Rab10 promoted lysosomal secretion, respectively. These effects were mediated by the recruitment of Rab8/10 effectors EHBP1 and EHBP1L1. LRRK2 deficiency augmented the chloroquine-induced lysosomal vacuolation of renal tubules in vivo. These results implicate the stress-responsive machinery composed of Rab7L1, LRRK2, phosphorylated Rab8/10, and their downstream effectors in the maintenance of lysosomal homeostasis.
The effect of far infrared radiation therapy on inflammation regulation in lipopolysaccharide-induced peritonitis in mice

Objective: Far infrared radiation has been widely used in a variety of healthcare institutions and clinical research. Previous studies have shown that far infrared radiation can promote blood circulation and enhance the functioning of the immune system. Many patients receiving peritoneal dialysis have been co-treated with far infrared radiation to reduce the occurrence of inflammation. This study seeks to evaluate the effects of far infrared radiation therapy on inflammation. Method: We used the lipopolysaccharide-induced peritonitis mouse model to study the effect of far infrared radiation treatment. Sixteen mice were randomly divided into two groups, a far infrared radiation treatment group (n = 8) and a non-far infrared radiation treatment group (n = 8). Collected blood samples were studied by analyzing the RNA level of peripheral blood mononuclear cells and the plasma protein levels of interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and endothelial nitric oxide synthase (eNOS). Results: The administration of far infrared radiation inhibited the RNA levels of interleukin-6 and TNF-α after stimulation by lipopolysaccharide. The far infrared radiation treatment inhibited the endothelial nitric oxide synthase RNA levels at 1 h, but the RNA levels returned close to the baseline level after 2 h. In the control group, the endothelial nitric oxide synthase RNA levels were continuously decreasing. The interleukin-6 concentration in the plasma of the far infrared radiation group showed significant inhibition 30 min after lipopolysaccharide stimulation. The tumor necrosis factor alpha RNA concentration in plasma of the far infrared radiation group was significantly reduced 2 h after lipopolysaccharide stimulation. Conclusion: Far infrared radiation therapy can inhibit interleukin-6 and tumor necrosis factor alpha RNA levels of peripheral blood mononuclear cells and recover endothelial nitric oxide synthase expression. These results demonstrate that far infrared radiation therapy might aid in reducing the level of inflammation experienced by patients going through peritoneal dialysis treatment.
Analysis and Comparison of Live Virtual Machine Migration Methods

With the huge development of servers' virtualization technology, the importance of live virtual machines (VM) migration has increased in order to improve hardware utilization, increase the power efficiency of data centers, and to decrease the effect of data centers failures and service downtime during the maintenance period. Live VM migration is the process of copying the CPU state and the memory and disk states of a VM from a hosting physical server to another destination server at the same data center, or to another data center connected to the hosting data center over LAN or WAN networks, with the least service downtime, in order not to affect the Quality of Experience (QoE) of virtualization service users. After the VM is transferred to the destination host and before it resumes running there, network traffic should be redirected to the new VM's location. In this paper, we analyze and compare the three migration methods: the Pre-copy, the Post-copy, and the Hybrid-copy method. We explain the mathematical model of the Pre-copy method as available in the literature. We present our mathematical models for Post-copy and Hybrid-copy methods for the migration downtime, total migration time, and total transferred data during the migration process. We implement the three models using MATLAB and evaluate the performance of these migration methods for different experimental parameters. Based on the performance we propose which method is suitable for live migration of virtual machines.