Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Management of In-Memory Storage for Efficiently Integrating Compute-and Data-Intensive Computing on HPC Systems

In order to boost the performance of data-intensive computing on HPC systems, in-memory computing frameworks, such as Apache Spark and Flink, use local DRAM for data storage. Optimizing the memory allocation to data storage is critical to delivering performance to traditional HPC compute jobs and throughput to data-intensive applications sharing the HPC resources. Current practices that statically configure in-memory storage may leave inadequate space for compute jobs or miss the opportunity to utilize available space for data-intensive applications. In this paper, we explore techniques to dynamically adjust in-memory storage allocation and provide optimum memory to compute jobs. We have developed a dynamic in-memory storage controller, DynIMS, which monitors memory demands of compute tasks in real time and employs a feedback-based control mechanism to adapt the allocation of in-memory storage. We test DynIMS using HPCC and Spark workloads on a HPC cluster. Experimental results show that DynIMS can achieve up to 5X performance improvement compared to systems with static memory allocations.
Theoretical analysis of fiber motion and loads during flow

A pseudo-analytical model for the forces exerted on fibers during flow that lead to fiber damage is proposed and solved. The fundamental derivations for the forces on fibers moving in suspensions developed by Burgers (1938) were used as a comparison. The cases of the motion of a fiber along its axis and perpendicular to its axis and in shear flow at a −45 degree-angle were investigated for aspect ratios between 10 and 300. The values for the overall forces on the fiber were in good agreement with the results found earlier by Burgers and others. However, the force distribution along the fiber was found to be significantly different from the constant distribution assumed by Burgers. Because of the higher forces on the fiber from the exact solution, the criterion for the onset of buckling in shear flow was revised. The pseudo-analytical solution was also compared to numerical results done with the boundary element method (BEM); the results were in good agreement.
A control theoretic analysis of RED

We use a previously developed nonlinear dynamic model of TCP to analyze and design active queue management (AQM) control systems using random early detection (RED). First, we linearize the interconnection of TCP and a bottlenecked queue and discuss its feedback properties in terms of network parameters such as link capacity, load and round-trip time. Using this model, we next design an AQM control system using the RED scheme by relating its free parameters such as the low-pass filter break point and loss probability profile to the network parameters. We present guidelines for designing linearly stable systems subject to network parameters like propagation delay and load level. Robustness to variations in system loads is a prime objective. We present no simulations to support our analysis.
Preservation of defined phenotypic traits in short-term cultured human breast carcinoma derived epithelial cells.

Interpretation of primary monolayer culture of organs and tissues with different epithelial cell types demands well-defined criteria for distinguishing between such cells. Epithelial components in breast carcinomas comprise, in addition to carcinoma epithelial cells (CEP), at least two epithelial cell types organized in mammary ductules of normal appearance as an inner layer of luminal epithelial cells (LEP) and an outer layer of basal or myoepithelial cells (MEP) resting on a basement membrane. In a previous study (Petersen and van Deurs, Cancer Res., 46: 2013-2020, 1986) we have defined a population of CEP in vivo and in vitro, appearing in about 50% of primary carcinomas, by a cytochemical reaction for reduced nicotinamide adenine dinucleotide phosphate neotetrazolium reductase. Carcinoma derived epithelial cells not showing this cytochemical reaction in culture were believed to originate from either carcinoma cells or from mammary ductules of normal or benign appearance. In the present study we show that carcinoma derived NADPH-NT reductase negative cell islets often exhibit phenotypic traits of apparently normal mammary ductules as defined in vivo. Moreover, it is shown that the reductase positive CEP, apart from the reductase reaction, has preserved several other features in culture distinguishing them from cells of apparently normal origin. Thus, whereas reductase positive CEP often consisted of only one cell type, as revealed by phase contrast microscopy, some reductase negative cell islets showed a distinct two-cell-type composition. One cell type exhibited cobblestone-like appearance and remained in the center of the islets whereas the other was more loosely arranged and rapidly left the central area by migration below the cobblestone-like cells to the periphery of the islets. Cobblestone-like cells and loosely arranged cells were found by immunocytochemistry to express elements of LEP and MEP phenotype, respectively. LEP phenotype was defined in vivo by expression of milk fat globule membrane antigen and cytokeratins, whereas MEP expressed basement membrane-associated type IV collagen. Computerized image analysis revealed mean population doubling times for cells with MEP phenotype of 1 day and for those with LEP phenotype of 2 days. Both cell types showed a diploid DNA pattern as revealed by fluorimetry. Reduced nicotinamide adenine dinucleotide phosphate neotetrazolium reductase positive CEP expressed milk fat globule membrane antigen and cytokeratins, thus resembling the reductase negative LEP. (ABSTRACT TRUNCATED AT 400 WORDS)
6-minute walk testing is more sensitive than maximal incremental cycle testing for detecting oxygen desaturation in patients with COPD.

STUDY OBJECTIVES Some respiratory patients exhibit oxygen desaturation during rehabilitative walking but not during maximal cardiopulmonary exercise testing (CPET). We evaluated exercise-induced desaturation during 6-min walk testing (6MWT) in comparison with CPET in patients with COPD and determined the reproducibility of the phenomenon. PATIENTS We tested 80 consecutive patients with COPD (FEV(1), 62.4 +/- 2% predicted) and 10 patients with supplementary COPD (FEV(1), 59.1 +/- 5% predicted) [mean +/- SEM] to determine the reproducibility. MEASUREMENTS AND RESULTS First, patients with COPD performed cycle CPET (first CPET [CPET-1]). Three days later, they performed two 6MWTs (first 6MWT [6MWT-1] and second 6MWT [6MWT-2]). Pulse oximetric saturation (SpO(2)) was recorded every minute in both tests. Three groups emerged: desaturation at 6MWT not observed at CPET (DND) [n = 23], desaturation in both tests (n = 16), and no desaturation in either test (n = 41). Second, to evaluate reproducibility, 10 additional subjects with COPD who exhibited desaturation during two successive 6MWTs but not in CPET performed a second CPET (CPET-2) and a single-bout 6MWT (6MWT-3) in a supplementary trial. When two CPETs were performed, lack of O(2) desaturation was noted in both. O(2) desaturation was confirmed in 6MWT-2 and 6MWT-3 (7.4 +/- 1% and 7.4 +/- 1.5%, respectively). CONCLUSION Twenty-eight percent of patients with COPD presented DND. The phenomenon was reproducible and not protocol dependent, emphasizing the clinical interest of the 6MWT.
Does the Use of Non-GAAP Earnings Influence Managers ’ Real Activities and Accounting Choices ?

It is now commonplace for managers to emphasize non-GAAP earnings metrics that exclude certain expenses, such as acquisition and restructuring expenses, intangible asset amortization, asset write-downs, and stock compensation expenses. This study hypothesizes that managers become focused on non-GAAP earnings, causing them to underweight excluded expenses when making investment and accounting decisions. Consistent with an underweighting of acquisition-related expenses, firms with a history of reporting non-GAAP earnings overinvest relative to their peers, and to engage in more acquisitions. With respect to accounting choices, excluded expenses such as write-downs and stock option expenses are recorded and measured more conservatively when excluded from non-GAAP earnings. The evidence is consistent with the use of non-GAAP earnings influencing real activities and accounting choices.
Gestational Hypoxia Induces Preeclampsia-Like Symptoms via Heightened Endothelin-1 Signaling in Pregnant Rats

Preeclampsia is a life-threatening pregnancy disorder. However, its pathogenesis remains unclear. We tested the hypothesis that gestational hypoxia induces preeclampsia-like symptoms via heightened endothelin-1 (ET-1) signaling. Time-dated pregnant and nonpregnant rats were divided into normoxic and hypoxic (10.5% O2 from the gestational day 6–21) groups. Chronic hypoxia had no significant effect on blood pressure or proteinuria in nonpregnant rats but significantly increased blood pressure on day 12 (systolic blood pressure, 111.7±6.1 versus 138.5±3.5 mm Hg; P=0.004) and day 20 (systolic blood pressure, 103.4±4.6 versus 125.1±6.1 mm Hg; P=0.02) in pregnant rats and urine protein (&mgr;g/&mgr;L)/creatinine (nmol/&mgr;L) ratio on day 20 (0.10±0.01 versus 0.20±0.04; P=0.04), as compared with the normoxic control group. This was accompanied with asymmetrical fetal growth restriction. Hypoxia resulted in impaired trophoblast invasion and uteroplacental vascular remodeling. In addition, plasma ET-1 levels, as well as the abundance of prepro–ET-1 mRNA, ET-1 type A receptor and angiotensin II type 1 receptor protein in the kidney and placenta were significantly increased in the chronic hypoxic group, as compared with the control animals. Treatment with the ET-1 type A receptor antagonist, BQ123, during the course of hypoxia exposure significantly attenuated the hypoxia-induced hypertension and other preeclampsia-like features. The results demonstrate that chronic hypoxia during gestation induces preeclamptic symptoms in pregnant rats via heightened ET-1 and ET-1 type A receptor–mediated signaling, providing a molecular mechanism linking gestational hypoxia and increased risk of preeclampsia.
Nonlinear Poisson Image Completion using Color Manifold

While most image completion methods focus on filling regions with structures or stationary textures, few are suitable for completing large-scale missing parts on complex background with nonlinearly progressive color changes. In this paper, we propose a novel approach, termed as nonlinear Poisson completion, to solve this problem. The visible parts of the background serve as a training set, from which we learn the embedding nonlinear subspace of progressive colors, namely color manifold. A Poisson image completion procedure, which works efficiently for smoothly linear interpolation, is extended to nonlinearly recover the missing regions with iteration solution confined to the manifold. In some especially challenging cases, a simple post-processing serves to generate more natural-looking results. Experiments on both synthetic and real images verify the effectiveness of the proposed algorithm.
Learning Robot Dynamics for Computed Torque Control Using Local Gaussian Processes Regression

Accurate models of the robot dynamics allow the design of significantly more precise, energy-efficient and more compliant computed torque control for robots. However, in some cases the accuracy of rigid-body models does not suffice for sound control performance due to unmodeled nonlinearities such as hydraulic cables, complex friction, or actuator dynamics. In such cases, learning the models from data poses an interesting alternative and estimating the dynamics model using regression techniques becomes an important problem. However, the most accurate regression methods, e.g. Gaussian processes regression (GPR) and support vector regression (SVR), suffer from exceptional high computational complexity which prevents their usage for large numbers of samples or online learning to date. We proposed an approximation to the standard GPR using local Gaussian processes models inspired by [Vijayakumaf, 2005 and Snelson and Ghahramani, 2007]. Due to reduced computational cost, local Gaussian processes (LGP) is capable for an online learning. Comparisons with other nonparametric regressions, e.g. standard GPR, v-SVR and locally weighted projection regression (LWPR), show that LGP has higher accuracy than LWPR and close to the performance of standard GPR and v-SVR while being sufficiently fast for online learning.
Power Capacitor Temperature Measurement System Using FBG Sensors and Its Validation

It is difficult to accurately measure internal temperature of power capacitor. To accurately measure internal and external temperatures of an operating capacitor, a capacitor temperature measurement system based on fiber Bragg grating (FBG) temperature sensors is developed. First, technical parameters of the sensors and the optical sensing interrogator are determined according to the practical situations. Second, the sensors are calibrated using a highly accurate thermostatic bath, and their reproducibility is checked. Third, in combination with ENLIGHT software, the temperature measurement system based on FBG sensors is set up. Finally, three BAM6.56-556-1W high-voltage film capacitors are manufactured, and the FBG sensors are put into a high-voltage film capacitor and placed on its shell, the temperature distribution of the capacitor in the thermal stability test is measured. The corresponding temperature field model of the capacitor under the same conditions is created and solved in Fluent. The simulation results are consistent with the measured results, which validates the temperature measurement system. This paper fixes the problem of internal temperature measurement for high-voltage film capacitor which can be taken as a reference to online monitoring of power capacitor temperature.
A Panoramic Wireless Endoscope System Design for the Application of Minimally Invasive Surgery

Minimally Invasive Surgery (MIS) is the current trend in surgery. Compared to traditional surgery, MIS can substantially decrease recovery time and expenses needed by patients after surgeries, reduce pain during surgical procedures, and is highly regarded by physicians and patients. An endoscope is widely used in the diagnosis and treatments of various medical disciplines, such as hysteroscopy, laparoscopy, and colonoscopy, and have been adopted by many branches of medicine. However, the limited image field of MIS is often the most difficult obstacles faced by surgeons and medical students, especially to less experienced physicians and difficult surgical procedures; the limited field of view of endoscopic imaging does not provide a whole picture of the surgery area, making the procedures difficult and full of uncertainty. In light of this problem, we proposed a “Panoramic Wireless Endoscope System design”, hoping to provide physicians with a wide field of view of the endoscopic image. We combine images captured from two parallel-mounted endoscope lenses into a single, wide-angle image, giving physicians a wider field of view and easier access to the surgical area. In addition, we developed a wireless transmission system so the image can be transmitted to various display platforms, eliminating the needs for excessive cabling on surgical tools and enable physicians to better operate on the patient. Finally, our system allows surgical assistants a better view of the operation process, and enables other physicians and nurses to remotely observe the process. Our experiment results have shown that we can increase the image to 152% of its original size. We used the PandaBoard ES platform with an ARM9 processor and 1G of onboard RAM, and continuously implementing animal trials to verify the reliability of our system.
Measuring the Chaplygin Gas Equation of State from Angular and Luminosity Distances

An exotic dark component, called generalized Chaplygin gas (Cg) and parameterized by an equation of state p = -A/ρ, where A and α are arbitrary constants, is one of the possible candidates for dark energy as well as for a unified scenario of dark matter and dark energy. In this paper we investigate qualitative and quantitative aspects of the angular size-redshift test in cosmological models driven by such a dark component. We discuss the prospects for constraining the Cg equation of state from measurements of the angular size at low- and high-redshift radio sources and also from a joint analysis involving angular size and supernova data. A detailed discussion about the influence of the Cg on the minimal redshift at which the angular size of an extragalactic source takes its minimal value is also presented.
Preparation and Characterization of Polypropylene/Superfine Down Powder Blend Films

To develop a novel hygroscopic PP film available for functional application, superfine down powder (SDP) was blended with polypropylene (PP) to produce blend pellets, and the extruded pellets were hot-pressed into blend films. Scanning electron microscopy (SEM) photos showed the interface between SDP and PP matrix. X-ray diffraction (XRD) results showed that the crystallinity of PP/SDP blend films decreased with increasing SDP content. Compared to pure PP film, PP/SDP blend films showed higher moisture regain, improved thermal stability and more residues at 600°C according to thermo-gravimetric analysis (TGA). Differential scanning calorimetry (DSC) curves showed that the addition of SDP accelerated the crystallization process of PP matrix. The water absorption of PP/SDP blend films with 50 wt% SDP achieved an increase of 11.9%. It was worth noting that the water absorption and mechanical properties of PP/SDP blend films depended on SDP content.
Bridging the gap between research and practice in a clinical and training network: Aigle's Program

Abstract The aim of this article is to share our experience at the Aiglé Foundation in fostering research that can conducted by (or in collaboration with) clinicians within a specific type of naturalistic setting—one that not only provides psychological services but also trains psychotherapists. After presenting the structure of Aiglé and the implementation of its scientific-practitioner philosophy, we describe some of the research that has been conducted with our network of clinicians and the benefits of connecting clinical practice and academic work. We then discuss some of the obstacles that we have encountered in conducting such studies, as well as a number of strategies that we adopted in attempting to address these challenges. We end this article by briefly describing the current state of our practice-research network, and by offering some recommendations to facilitate the conduct of research by and for clinicians.
Putting bandits into context: How function learning supports decision making

We introduce the contextual multi-armed bandit task as a framework to investigate learning and decision making in uncertain environments. In this novel paradigm, participants repeatedly choose between multiple options in order to maximise their rewards. The options are described by a number of contextual features which are predictive of the rewards through initially unknown functions. From their experience with choosing options and observing the consequences of their decisions, participants can learn about the functional relation between contexts and rewards and improve their decision strategy over time. In three experiments, we explore participants’ behaviour in such learning environments. We predict participants’ behaviour by context-blind (mean-tracking, Kalman filter) and contextual (Gaussian process and linear regression) learning approaches combined with different choice strategies. Participants are mostly able to learn about the context-reward functions and their behaviour is best described by a Gaussian process learning strategy which generalizes previous experience to similar instances. In a relatively simple task with binary features, they seem to combine this learning with a “probability of improvement” decision strategy which focuses on alternatives that are expected to lead to an improvement upon a current favourite option. In a task with continuous features that are linearly related to the rewards, participants seem to more explicitly balance exploration and exploitation. Finally, in a difficult learning environment where the relation between features and rewards is non-linear, some participants are again well-described by a Gaussian process learning strategy, whereas others revert to context-blind strategies.
Mining the Banking Customer Behavior Using Clustering and Association Rules Methods

The unprecedented growth of competition in the banking technology has raised the importance of retaining current customers and acquires new customers so that is important analyzing Customer behavior, which is base on bank databases. Analyzing bank databases for analyzing customer behavior is difficult since bank databases are multi-dimensional, comprised of monthly account records and daily transaction records. Few works have focused on analyzing of bank databases from the viewpoint of customer behavioral analyze. This study presents a new two-stage frame-work of customer behavior analysis that integrated a K-means algorithm and Apriori association rule inducer. The K-means algorithm was used to identify groups of customers based on recency, frequency, monetary behavioral scoring predicators; it also divides customers into three major profitable groups of customers. Apriori association rule inducer was used to characterize the groups of customers by creating customer profiles. Identifying customers by a customer behavior analysis model is helpful characteristics of customer and facilitates marketing strategy development .
Semantic Data Models

A semantic data model describes the concepts that are important to an organization along Description: with their meanings and relationships to other important concepts. It is something like an authoritative Glossary of Terms along with diagrams or other ways of showing the relationships between different data. A semantic model has an emphasis on relationships and meaning and how the data relate to the real world. Ideally, the highest level semantic data model for an organization should be able to fit on one page, and provide the ability to drill down for more detail.
Impact of titanium dioxide on androgen receptors, seminal vesicles and thyroid hormones of male rats: possible protective trial with aged garlic extract

The aim of this study was to evaluate the effect of titanium dioxide (TiO2), a widely produced and consumed pigment in various food products, on the post‐natal development of male albino rat seminal vesicle and thyroid hormones, as well as to evaluate the ameliorative effect of aged garlic extract (AGE) on TiO2‐induced alterations. Forty male rat pups (3 weeks old) were divided into four equal groups. The 1st group received distilled water orally (control group), 2nd group was given 2 ml kg−1 AGE, 3rd group was administered TiO2 (5 g kg−1 BW) day after day for 65 days, and the 4th group administered AGE 6 hr prior to TiO2 gavage. TiO2‐exposed rats showed nonsignificant changes in the serum testosterone, TSH, T3 and T4, while serum glucose showed a significant decrease. Androgen receptor (AR) mRNA expression was significantly down‐regulated and weak signal of AR immune labelling. Histopathologically, the epithelium cell lining of seminal vesicles showed focal areas of necrosis and fibrous tissue with the prominent fibrous stroma of the atrophied glands. Meanwhile, AGE supplementation ameliorated the deleterious effects of TiO2 intoxication through protecting the tissues from oxidative stress caused by TiO2. In summary, oral administration of TiO2 resulted in abnormal developmental events in male rat seminal vesicle and AGE able to reduce TiO2 toxicity.