Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Different Rheological Models on the Distress Prediction of Composite Pavement

In this paper, three different rheological models including a newly developed formulation based on the current Christensen Anderson and Marateanu (CAM) model, named sigmoidal CAM model (SCM), are used to estimate the evolution of roughness, rutting, and reflective cracking in a typical composite pavement structure currently widely adopted in South Korea. Three different asphalt mixtures were prepared and dynamic modulus tests were performed. Then, the mechanistic-empirical pavement design guide (MEPDG) was used for predicting the progression of the pavement distress and to estimate the effect of the three different models on such phenomena. It is found that the three different mathematical models provide lower and upper limits for roughness, rutting, and reflective cracking. While the CAM model may not be entirely reliable due to its inability in fitting the data in the high-temperature domain, SCM might result in moderately more conservative pavement design.
Prevalence and Characteristics of Pain in Patients of Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study in China

Abstract The purposes of this study were to: (1) study the prevalence of pain in patients with mild-to-very severe chronic obstructive pulmonary disease (COPD) in China; (2) compare the differences in pain characteristics between stable COPD and acute exacerbation of COPD (AECOPD); (3) explore the clinical associations with pain in those with COPD. This cross-sectional study was conducted in China from October 24, 2017, to January 11, 2019. A face-to-face interview was conducted to collect data. The Chinese version of the brief pain inventory (BPI-C) was applied to investigate the pain characteristics in patients with COPD. Of the 901 patients in this study, 226 (25.1%) patients reported pain problems. The prevalence of pain in patients with mild to very severe COPD was 32.9%, 23.9%, 25.2%, and 23.5%, respectively (p = 0.447). According to the BPI-C results, 31.3% (31/99) of patients reported pain of AECOPD, compared to 24.3% (195/802) of stable COPD (p = 0.13). Reported pain intensity and pain interference evaluated by the BPI-C were significantly higher in AECOPD than stable COPD (p < 0.001, p < 0.05, respectively). Those with body mass index (BMI) ≥ 24kg/m2 or COPD assessment test (CAT) score > 20 were significantly more likely to have pain problems than BMI < 24kg/m2 (aOR = 1.568, a95IC = 1.132–2.170, p = 0.007) or CAT ≤ 20 (aOR= 1.754, a95IC = 1.213–2.536, p = 0.003). Pain was common in patients with both stable COPD and AECOPD. AECOPD patients had a significantly higher pain intensity than stable COPD. Overweight and CAT > 20 were significantly related to higher prevalence of pain.
Two‐pore channels regulate Tat endolysosome escape and Tat‐mediated HIV‐1 LTR transactivation

HIV‐1 Tat is essential for HIV‐1 replication and appears to play an important role in the pathogenesis of HIV‐associated neurological complications. Secreted from infected or transfected cells, Tat has the extraordinary ability to cross the plasma membrane. In the brain, Tat can be taken up by CNS cells via receptor‐mediated endocytosis. Following endocytosis and its internalization into endolysosomes, Tat must be released in order for it to activate the HIV‐1 LTR promoter and facilitate HIV‐1 viral replication in the nucleus. However, the underlying mechanisms whereby Tat escapes endolysosomes remain unclear. Because Tat disrupts intracellular calcium homeostasis, we investigated the involvement of calcium in Tat endolysosome escape and subsequent LTR transactivation. We demonstrated that chelating endolysosome calcium with high‐affinity rhodamine‐dextran or chelating cytosolic calcium with BAPTA‐AM attenuated Tat endolysosome escape and LTR transactivation. Significantly, we demonstrated that pharmacologically blocking and knocking down the endolysosome‐resident two‐pore channels (TPCs) attenuated Tat endolysosome escape and LTR transactivation. This calcium‐mediated effect appears to be selective for TPCs because knocking down TRPML1 calcium channels was without effect. Our findings suggest that calcium released from TPCs is involved in Tat endolysosome escape and subsequent LTR transactivation. TPCs might represent a novel therapeutic target against HIV‐1 infection and HIV‐associated neurological complications.
The Expression of Potato Expansin A3 (StEXPA3) and Extensin4 (StEXT4) Genes with Distribution of StEXPAs and HRGPs-Extensin Changes as an Effect of Cell Wall Rebuilding in Two Types of PVYNTN–Solanum tuberosum Interactions

The plant cell wall acts not only as a physical barrier, but also as a complex and dynamic structure that actively changes under different biotic and abiotic stress conditions. The question is, how are the different cell wall compounds modified during different interactions with exogenous stimuli such as pathogens? Plants exposed to viral pathogens respond to unfavorable conditions on multiple levels. One challenge that plants face under viral stress is the number of processes required for differential cell wall remodeling. The key players in these conditions are the cell wall genes and proteins, which can be regulated in specific ways during the interactions and have direct influences on the rebuilding of the cell wall structure. The cell wall modifications occurring in plants during viral infection remain poorly described. Therefore, this study focuses on cell wall dynamics as an effect of incompatible interactions between the potato virus Y (PVYNTN) and resistant potatoes (hypersensitive plant), as well as compatible (susceptible plant) interactions. Our analysis describes, for the first time, the expression of the potato expansin A3 (StEXPA3) and potato extensin 4 (StEXT4) genes in PVYNTN-susceptible and -resistant potato plant interactions. The results indicated a statistically significant induction of the StEXPA3 gene during a susceptible response. By contrast, we demonstrated the predominantly gradual activation of the StEXT4 gene during the hypersensitive response to PVYNTN inoculation. Moreover, the in situ distributions of expansins (StEXPAs), which are essential cell wall-associated proteins, and the hydroxyproline-rich glycoprotein (HRGP) extensin were investigated in two types of interactions. Furthermore, cell wall loosening was accompanied by an increase in StEXPA deposition in a PVYNTN-susceptible potato, whereas the HRGP content dynamically increased during the hypersensitive response, when the cell wall was reinforced. Ultrastructural localization and quantification revealed that the HRGP extensin was preferably located in the apoplast, but deposition in the symplast was also observed in resistant plants. Interestingly, during the hypersensitive response, StEXPA proteins were mainly located in the symplast area, in contrast to the susceptible potato where StEXPA proteins were mainly observed in the cell wall. These findings revealed that changes in the intracellular distribution and abundance of StEXPAs and HRGPs can be differentially regulated, depending on different types of PVYNTN–potato plant interactions, and confirmed the involvement of apoplast and symplast activation as a defense response mechanism.
Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decisions

A fundamental question for companies with large amount of logged data is: How to use such logged data together with incoming streaming data to make good decisions? Many companies currently make decisions via online A/B tests, but wrong decisions during testing hurt users' experiences and cause irreversible damage. A typical alternative is offline causal inference, which analyzes logged data alone to make decisions. However, these decisions are not adaptive to the new incoming data, and so a wrong decision will continuously hurt users' experiences. To overcome the aforementioned limitations, we propose a framework to unify offline causal inference algorithms (e.g., weighting, matching) and online learning algorithms (e.g., UCB, LinUCB). We propose novel algorithms and derive bounds on the decision accuracy via the notion of "regret". We derive the first upper regret bound for forest-based online bandit algorithms. Experiments on two real datasets show that our algorithms outperform other algorithms that use only logged data or online feedbacks, or algorithms that do not use the data properly.
Genomic dissection of gastrointestinal and lung neuroendocrine neoplasm

Objective Neuroendocrine neoplasms (NENs) are relatively rare and heterogeneous malignancies with two major subtypes: low-grade neuroendocrine tumor (NET) and high-grade neuroendocrine carcinoma (NEC). Comprehensive molecular characterization of NENs is needed to refine our understanding of the biological underpinnings of different NEN subtypes and to predict disease progression more accurately. Methods We performed whole-exome sequencing (WES) of NEN samples from 49 patients (25 NETs and 24 NECs) arising from the stomach, intestines or lung. Clinicopathologic features were assessed and associated with molecular events. Results NENs generally harbor a low mutation burden, with TP53 being the top mutated gene found in 31% of patients. Consistent with other studies, p53 signaling pathway dysfunction is significantly enriched in NECs compared to NETs (P<0.01). Other thanTP53, tissue type-specific mutation profiles of NENs were observed in our cohort compared to those reported in pancreatic NETs. Importantly, we observed significant genomic instability, with increased copy number alterations observed across the NEN genome, which was more profound in NECs and independently correlated with poor overall survival (OS) (P<0.001). NECs could be further stratified into two molecular subtypes based on OS (P<0.001) and the chromosomal instability score (CIS). Interestingly, we discovered that the gain of whole chromosome 5 occurred at the early stage of NEN development, followed by the loss of 5q exclusively in NECs (P<0.001). Conclusions These findings provide novel insights into the molecular characteristics of NENs and highlight the association of genomic stability with clinical outcomes.
The negative effect of desflurane on reproductive capacity in female rats.

AIM The aim of this study was to determine the effect of desflurane on reproductive capacity in female rats through a study of biochemical evaluations. METHOD After experimental procedure, the blood samples of female rats were collected, and the malondialdehyde, interleukin‑1‑beta, total glutathione and superoxide dismutase levels were measured to evaluate oxidative stress. In addition to biochemical evaluations, the reproductive performance of the experimental groups was also examined. RESULTS The results of our study demonstrated that in blood samples of desflurane‑treated groups of rats, the parameters indicating oxidative stress and inflammation increased, and antioxidant parameters decreased (p < 0.05). It was also proven that repeated desflurane doses caused infertility in female rats, prolonged the gestation period and reduced the number of offspring. CONCLUSIONS This study showed that recurrent desflurane application can cause infertility problems through oxidative stress in female rats (Tab. 3, Fig. 1, Ref. 25).
A Sample Selection Approach for Universal Domain Adaptation

We study the problem of unsupervised domain adaption in the universal scenario, in which only some of the classes are shared between the source and target domains. We present a scoring scheme that is effective in identifying the samples of the shared classes. The score is used to select which samples in the target domain to pseudo-label during training. Another loss term encourages diversity of labels within each batch. Taken together, our method is shown to outperform, by a sizable margin, the current state of the art on the literature benchmarks.
Faster Regret Matching

The regret matching algorithm proposed by Sergiu Hart is one of the most powerful iterative methods in finding correlated equilibrium. However, it is possibly not efficient enough, especially in large scale problems. We first rewrite the algorithm in a computationally practical way based on the idea of the regret matrix. Moreover, the rewriting makes the original algorithm more easy to understand. Then by some modification to the original algorithm, we introduce a novel variant, namely faster regret matching. The experiment result shows that the novel algorithm has a speed advantage comparing to the original one.
Optimization of Convolutional Neural Network Using the Linearly Decreasing Weight Particle Swarm Optimization

Convolutional neural network (CNN) is one of the most frequently used deep learning techniques. Various forms of models have been proposed and improved for learning at CNN. When learning with CNN, it is necessary to determine the optimal hyperparameters. However, the number of hyperparameters is so large that it is difficult to do it manually, so much research has been done on automation. A method that uses metaheuristic algorithms is attracting attention in research on hyperparameter optimization. Metaheuristic algorithms are naturally inspired and include evolution strategies, genetic algorithms, antcolony optimization and particle swarm optimization. In particular, particle swarm optimization converges faster than genetic algorithms, and various models have been proposed. In this paper, we propose CNN hyperparameter optimization with linearly decreasing weight particle swarm optimization (LDWPSO). In the experiment, the MNIST data set and CIFAR-10 data set, which are often used as benchmark data sets, are used. By optimizing CNN hyperparameters with LDWPSO, learning the MNIST and CIFAR-10 datasets, we compare the accuracy with a standard CNN based on LeNet-5. As a result, when using the MNIST dataset, the baseline CNN is 94.02% at the 5th epoch, compared to 98.95% for LDWPSO CNN, which improves accuracy. When using the CIFAR-10 dataset, the Baseline CNN is 28.07% at the 10th epoch, compared to 69.37% for the LDWPSO CNN, which greatly improves accuracy.
3-(6-Phenylimidazo [2,1-b][1,3,4]thiadiazol-2-yl)-1H-Indole Derivatives as New Anticancer Agents in the Treatment of Pancreatic Ductal Adenocarcinoma

A new series of imidazo[2,1-b][1,3,4]thiadiazole derivatives was efficiently synthesized and screened for their in vitro antiproliferative activity on a panel of pancreatic ductal adenocarcinoma (PDAC) cells, including SUIT-2, Capan-1 and Panc-1. Compounds 9c and 9l, showed relevant in vitro antiproliferative activity on all three pre-clinical models with half maximal inhibitory concentration (IC50) ranging from 5.11 to 10.8 µM, while the compounds 9e and 9n were active in at least one cell line. In addition, compound 9c significantly inhibited the migration rate of SUIT-2 and Capan-1 cells in the scratch wound-healing assay. In conclusion, our results will support further studies to increase the library of imidazo [2,1-b][1,3,4] thiadiazole derivatives for deeper understanding of the relationship between biological activity of the compounds and their structures in the development of new antitumor compounds against pancreatic diseases.
Reappraising the neurosurgical significance of the pterion location, morphology, and its relationship to optic canal and sphenoid ridge and neurosurgical implications

Frontolateral craniotomy procedures have advanced from conventional craniotomy to mini-craniotomy, and to contemporary keyhole surgery. In this context, it is important for the neurosurgeon to precisely locate the pterion. The distance of the pterion center from midpoint of zygomatic arch and posterolateral margin of frontozygomatic suture was studied bilaterally in 50 whole adult skulls in Indian ethnic group. The depth of optic canal and sphenoid ridge from the pterion was recorded bilaterally in fifty cut adult skulls and fifteen three-dimensional computed tomography scans. The suture length, thickness, and morphology were studied. The data were analyzed using SPSS software, two-tailed Student's t test, binary logistic regression and receiver operating characteristic curve for sexual dimorphism. The pterion center was located at a mean distance of 37.02 mm above the midpoint of zygomatic arch, 28.20 mm behind the posterolateral margin of frontozygomatic suture, 42.73 mm lateral to the optic canal and 10.59 mm from the sphenoid ridge. The location did not exhibit sexual dimorphism. In 20% cases the pterion center was 40 mm or more above the midpoint of the zygomatic arch and in 5% cases 35 mm or more posterior to the posterolateral margin of frontozygomatic suture. The mean suture length was 10±3 mm. The mean thickness at the center of the pterion was 3.52±1.45 mm. The commonest variety was sphenoparietal followed by frontotemporal, epipteric, and stellate types. A thorough knowledge of these dimensions has innumerable neurosurgical implications in resection of sellar, parasellar, and paraclinoid tumors and circulatory aneurysms.
A Sub-Clone of RAW264.7-Cells Form Osteoclast-Like Cells Capable of Bone Resorption Faster than Parental RAW264.7 through Increased De Novo Expression and Nuclear Translocation of NFATc1

The murine macrophage cell line RAW264.7 is extensively used as a progenitor to study osteoclast (OC) differentiation. RAW264.7 is a heterogeneous cell line, containing sub-clones with different abilities to form OCs. The aim of this study was to identify characteristics within the heterogeneous RAW264.7 cells that define sub-clones with an augmented ability to form bone-resorbing OCs (H9), as well as sub-clones representing non-OCs (J8). RAW264.7 sub-clones were isolated by single cell cloning. Selection was based on TRAP/cathepsin K expression in sub-clone cultures without added RANKL. Sub-clones before and after differentiation with RANKL were assayed for multiple OC-characteristics. Sub-clone H9 cells presented a higher expression of OC-markers in cultures without added RANKL compared to the parental RAW264.7. After 6 days of RANKL stimulation, sub-clone H9 cells had equal expression levels of OC-markers with RAW264.7 and formed OCs able to demineralize hydroxyapatite. However, sub-clone H9 cells displayed rapid differentiation of OC already at Day 2 compared to Day 4 from parental RAW264.7, and when cultured on plastic and on bone they were more efficient in resorption. This rapid differentiation was likely due to high initial expression/nuclear translocation of OC master transcription factor, NFATc1. In contrast to H9, J8 cells expressed initially very low levels of OC-markers, and they did not respond to RANKL-stimulation by developing OC-characteristics/OC-marker expression. Hence, H9 is an additional clone suitable for experimental setup requiring rapid differentiation of large numbers of OCs.
Usefulness Analysis of Urine Samples for Early Screening of Human Papilloma Virus Infection

Human papilloma virus (HPV) is known to be a major cause of cervical cancer. In Korea, although the mortality of cervical cancer has decreased, HPV infection rates are increasing rapidly in young women. One of the reasons for a high rate of human immunodeficiency virus (HIV) infection appears to be associated with a low frequency to visit gynecology clinics because of the uncomfortable sampling process for HPV testing. Therefore, it is necessary to develop a non-invasive method, such as urine testing to diagnose cervical cancer rather than use of the existing invasive method. This study aimed to test validity of HPV DNA detection in urine specimens that can be easily collected from women. Paired vaginal discharge and urine samples were collected prospectively from 203 women who visited the local hospital between January and August 2018 in Busan, Korea. By using the Virocheck® assay kit (Optipharm), we found that 17.2% (35/203) of vaginal discharge samples were HPV positive and 82.8% (168/203) were HPV negative. In urine samples, 15.8% (32/203) were HPV positive and 84.2% (171/203) were HPV negative. The co-incident rate for HPV DNA detection was 84.8% in both vaginal discharge and urine samples. These results suggest that the HPV DNA detection using urine samples might be an alternative way to diagnose HPV infection in a non-invasive way. This analytical approach can be utilized as a screening test to identify HIV-infected patients who need a follow-up process by using urine samples.
Can advanced glycation end‐products and their receptors be affected by weight loss? A systematic review

Advanced glycation end products (AGEs) have been implicated in the pathogenesis of most chronic diseases. Therefore, identification of treatments that can attenuate the effects of these compounds and prevent cardiometabolic complications is of extreme public health interest. Recently, body weight management interventions showed positive results on reducing serum AGE concentrations. Moreover, the soluble receptor for advanced glycation end products (sRAGE) is considered to be a novel biomarker to identify patients with obesity most likely to benefit from weight management interventions. This systematic review aimed to critically analyze papers evaluating the effects of weight loss on serum AGEs and its receptors in adults with excess body weight. MEDLINE, Cochrane, Scopus, and Lilacs databases were searched. Three studies evaluating the response of AGEs to energy‐restricted diets and six assessing sRAGE as the primary outcome were included. Energy‐restricted diets and bariatric surgery reduced serum AGE concentrations, but effects on endogenous secretory RAGE (esRAGE) and sRAGE concentrations are conflicting. These results may be associated with mechanisms related to changes in dietary intake and limiting endogenous AGE formation. Therefore, the role of energy‐restricted diets and bariatric surgery on lowering serum AGE concentrations, as well as its effects on AGEs receptors, deserves further investigation.
A Markerless Deep Learning-based 6 Degrees of Freedom Pose Estimation for Mobile Robots using RGB Data

Augmented Reality has been subject to various integration efforts within industries due to its ability to enhance human machine interaction and understanding. Neural networks have achieved remarkable results in areas of computer vision, which bear great potential to assist and facilitate an enhanced Augmented Reality experience. However, most neural networks are computationally intensive and demand huge processing power, thus are not suitable for deployment on Augmented Reality devices. In this work, we propose a method to deploy state of the art neural networks for real time 3D object localization on augmented reality devices. As a result, we provide a more automated method of calibrating the AR devices with mobile robotic systems. To accelerate the calibration process and enhance user experience, we focus on fast 2D detection approaches which are extracting the 3D pose of the object fast and accurately by using only 2D input. The results are implemented into an Augmented Reality application for intuitive robot control and sensor data visualization. For the 6D annotation of 2D images, we developed an annotation tool, which is, to our knowledge, the first open source tool to be available. We achieve feasible results which are generally applicable to any AR device, thus making this work promising for further research in combining high demanding neural networks with Internet of Things devices.