Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupled Continuum Advection-Diffusion Model for Simulating Parallel Flow Induced Mass Transport in Porous Membranes

: In this paper, convection-diffusion based mass transport model is proposed for parallel flow driven species transport in microporous membranes. An individual membrane is modeled with the help of macroscopic concentration measurements, considering mass transfer effect in a core of residential energy recovery ventilator sandwiched membrane arrangement, utilizing proton transfer reaction mass spectrometry. Isopropyl alcohol (C 3 H 8 ) is used as the trace compound in experimental analysis. Computational model is developed focusing on a local effect occurring at the sandwiched core structure. Through the model, porous membranes exposed to parallel air flows in both sides are studied. Trace compound injection is modeled by creating constant concentration boundary condition at the channel inlet. Fluid-membrane interface mass transfer is represented by source and sink terms proportional to the interface concentration and transfer coefficients (adsorption and desorption). Mass transport in the membrane is attributed to effective diffusion parameter considering both molecular and Knudsen diffusion processes. In addition, membrane pore size distribution is simplified to a lognormal distribution, with a known mean and standard deviation. The proposed model successfully demonstrated the conjugate transport phenomena in microporous membranes demonstrating the development of concentration boundary layers at the interfaces. Also, it is observed that decrease in adsorption coefficients with the increase of adjacent flow velocities near the membrane. In contrary, increase in desorption coefficient is observed at the interface with the increase of flow velocity. The change in adsorption and desorption parameters in the model confirmed previously reported experimental outcomes.
Credit Risk Management Policies and Debt Collection Performance by Registered Security Companies in Kenya

Security has been and continues to be priority for both life and property world over. Due to the limitations of public security services the private sector has supplemented provision of security services. Over time the registered security firms have come to rely more on establishments that acquire services purely on credit which often lead to due debts. This has led to large uncollected debts putting registered security firms into liquidity challenges. If such debts are not efficiently collected, the company’s operations are adversely affected. This study sought to assess the effect of credit risk management policies on debt collection performance by registered security companies in Kenya, for the period 2013 to 2017. The study was grounded on the motive theory of credit, credit risk theory and anticipated income theory. The study used descriptive research design. A census of 38 registered security companies in Kenya was taken. The study used primary data obtained using structured questionnaires and secondary data collected using a secondary data template for complimentary purposes. The study employed multivariate regression model to determine the effect of credit risk management policies on debt collection performance by registered security companies in Kenya. The mediating effect of inflation rate was tested using the stepwise regression technique by employing the logic of Baron and Kenny (1986). The regression results indicated that the credit limit policy had a statistically insignificant positive association with Days Sales Outstanding (DSO), a measure of debt collection performance. The study revealed that credit documentation and review policies improve debt collection performance by registered security companies in Kenya. The study however found that credit approval and scoring policies decreases debt collection performance. The study established that credit limit policy has insignificant effect on debt collection performance of the registered security companies in Kenya. The results of Sobel – Goodman mediation test indicated that inflation had no mediating effect on the relationship between credit risk management policies and debt collection performance by registered security companies in Kenya. The study recommends that managers of registered security companies should review their credit approval and scoring policies in order to improve debt collection performance. Further it recommended that the Government through recently established Private Security Regulatory Authority (PSRA) should come up with minimum documentation requirement for security services acquisition to help improve debt collection performance through complete documentation of credit transactions in the industry.
Extracting localized information from a Twitter corpus for flood prevention

In this paper, we discuss the collection of a corpus associated to tropical storm Harvey, as well as its analysis from both spatial and topical perspectives. From the spatial perspective, our goal here is to get a first estimation of the quality and precision of the geographical information featured in the collected corpus. From a topical perspective, we discuss the representation of Twitter posts, and strategies to process an initially unlabeled corpus of tweets.
Unsupervised Motion Saliency Map Estimation Based On Optical Flow Inpainting

The paper addresses the problem of motion saliency in videos, that is, identifying regions that undergo motion departing from its context. We propose a new unsupervised paradigm to compute motion saliency maps. The key ingredient is the flow inpainting stage. Candidate regions are determined from the optical flow boundaries. The residual flow in these regions is given by the difference between the optical flow and the flow inpainted from the surrounding areas. It provides the cue for motion saliency. The method is flexible and general by relying on motion information only. Experimental results on the DAVIS 2016 benchmark demonstrate that the method compares favourably with state-of-theart video saliency methods.
A Novel Approach for Protection of Accounts' Names against Hackers Combining Cluster Analysis and Chaotic Theory

The last years of the 20 th century and the beginning of the 21 th mark the facilitation trend of our real life due to the big development and progress of the computers and other intelligent devices. Algorithms based on artificial intelligence are basically a part of the software. The transmitted information by Internet or LAN arises continuously and it is expected that the protection of the data has been ensured. The aim of the present paper is to reveal false names of users' accounts as a result of hackers' attacks. The probability a given account to be either false or actual is calculated using a novel approach combining machine learning analysis (especially clusters' analysis) with chaos theory. The suspected account will be used as a pattern and by classification techniques clusters will be formed with a respective probability this name to be false. This investigation puts two main purposes: First, to determine if there exists a trend of appearance of the similar usernames, which arises during the creation of new accounts. Second, to detect the false usernames and to discriminate those from the real ones, independently of that if two types of accounts are generated with the same speed. These security systems are applied in different areas, where the security of the data in users' accounts is strictly required. For example, they can be used in on-line voting for balloting, in studying the social opinion by inquiries, in protection of the information in different user accounts of given system etc.
Reduction of Salmonella Excretion into Drinking Water Following Treatment of Chicks with Nurmi Culture.

Day-old chicks ( Gallus domesticus ) were treated with cultured feces of adult chickens according to the Nurmi concept and were challenged 2 days later with Salmonella typhimurium . Treated chicks were less susceptible to infection than untreated chicks (16% vs. 79% infected). Those treated chicks that did become infected, contaminated their drinking water with fewer Salmonella than the untreated chicks (maximum of 104/ml vs. ⩾ 107/ml). Fecally contaminated water may be a major source for spreading Salmonella infection within a flock.
Duality Bounds on the Cut-Off Rate with Applications to Ricean Fading

We propose to use an expression of Csiszar & Korner's to upper bound Gallager's E/sub 0/(/spl rho/,Q,r) function. We demonstrate this approach by computing the high SNR asymptotic expansion of the computational cut-off rate of the peak-or average-power limited discrete-time memoryless Ricean fading channel with no-or with only partial-side information at the receiver.
Prevalence and clinical significance of regional lymphadenectomy in patients with hepatocellular carcinoma

A limited amount of literature involves the clinical significance of regional lymphadenectomy during operations on hepatocellular carcinoma (HCC) patients. Our study aims to explore regional lymphadenectomy rate and node‐positive rate, as well as their clinicopathological relevance and prognostic values in patients with HCC receiving liver resection (LR) and liver transplantation (LT).
Efficient Tensor Completion for Internet Traffic Data Recovery

In real-world traffic data, missing data is inevitable for traffic collection problem and some other reasons. Therefore, it is increasingly critical to complete the whole traffic data. To make full use of hidden spatial-temporal structures of the Internet traffic data, we extend to traffic matrix (user, server) to a three-way tensor (user, server, time). This paper proposed a novel algorithm to recover the missing data, named TSVT (Tucker decomposition and tensor singular value thresholding). We exploit the proposed the Tucker decomposition and low rank tensor completion (LRTC). Based on LRTC, we extend the known singular value thresholding (SVT) to the tensor case, and combine Tucker decomposition to optimize the performance of the algorithm. Based on Internet traffic data, we model two different tensors, and apply our TSVT to infer the unobserved data of the traffic. Furthermore, we apply TSVT algorithm to our Internet data. Numerical experiments on Synthetic data verify our method and the application for completing DPI traffic data proves the effectiveness of the method.
Combination Treatments of Plasma Exchange and Umbilical Cord-Derived Mesenchymal Stem Cell Transplantation for Patients with Hepatitis B Virus-Related Acute-on-Chronic Liver Failure: A Clinical Trial in China

Background Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a common type of liver failure with a high mortality. This study aimed at investigating the safety and efficacy of the combination treatment of plasma exchange (PE) and umbilical cord-derived mesenchymal stem cell (UC-MSCs) transplantation for HBV-ACLF patients. Methods A total of 110 HBV-ACLF patients treated in our hospital from January 2012 to September 2017 were enrolled into this trial and divided into the control group (n = 30), UC-MSC group (n = 30), PE group (n = 30), and UC-MSC + PE group (n = 20) based on their treatments. The hepatic function, coagulation, and virological and immunological markers were assessed at baseline and 30, 60, 90, 180, and 360 days. The endpoint outcomes were death and unfavorable outcome (need for liver transplantation or death). Results The UC-MSC + PE group had the lowest rates of death and unfavorable outcome at 30 days, 60 days, and 90 days posttreatment among the four groups, but the difference did not reach significances. The multivariate logistic regression analysis demonstrated that hemoglobin, prothrombin activity, and MELD (model for end-stage liver disease) score were the independent factors associated with the unfavorable outcome (all P < 0.05). The levels of total bilirubin, alanine aminotransferase, aspartate transaminase, and MELD score were significantly decreased during treatments (all P < 0.05). Conclusion UC-MSCs combined with PE treatment had good safety but cannot significantly improve the short-term prognosis of HBV-ACLF patients with as compared with the single treatment. The long-term efficacy should be further evaluated. This trial is registered with registration no. NCT01724398.
Up-regulation of CKAP2L expression promotes lung adenocarcinoma invasion and is associated with poor prognosis

Aim The purpose of this study is to consider the function of cytoskeleton-associated protein 2-like (CKAP2L) in lung adenocarcinoma (LAD) development and its prognostic value. Methods The mRNA expression of CKAP2L and its correlation with clinical factors in LAD patients were analyzed from the data taken from The Cancer Genome Atlas and The First Affiliated Hospital of Kunming Medical University. We constructed H460 and A549 cell lines with silenced CKAP2L using RNA interference. Cell counting kit-8 assay and colony formation assays were carried out to determine the function of CKAP2L in H460 and A549 cell proliferation. Transwell and wound healing assays were applied to determine the effect of CKAP2L on H460 and A549 cell invasion and migration. The influences of CKAP2L on mitogen-activated protein kinase signaling pathway-related proteins were tested by Western blotting. Results CKAP2L expression is enhanced in LAD tissues and is predictive of poor prognosis in LAD patients. High expression of CKAP2L is associated with stage (P<0.001), lymph node status (P=0.002), and metastasis (P=0.025). Depletion of CKAP2L dramatically suppressed the proliferation, migration, and invasion of H460 and A549 cells. Moreover, the ratio of p-MEK/ MEK and p-ERK/ERK reduced obviously in A549 cells after depleting CKAP2L. Conclusion Our findings implied that CKAP2L might be a promoter of LAD and could serve as a predictor for LAD patients.
Is It Possible to Change from a Linear to a Circular Economy? An Overview of Opportunities and Barriers for European Small and Medium-Sized Enterprise Companies

The Circular Economy is a paradigm shift attempting to replace the end-of-life concept with reducing, reusing, recycling and recovering materials and to slow down, close and narrow material and power loops. This concept is much discussed in the academic literature, but limited progress has been accomplished so far regarding its empirical analysis. The objective of this work is to study circular economy practices and analyze in depth the circular economy behavior in European firms. We find that firms’ circular economy behavior is a gradual process where measures are implemented gradually, starting with activities involving control measures and ending with putting preventive practices in place. We discovered also that the most proactive companies in implementing circular economy measures generally come across certain common barriers such as administrative processes, regulations and a lack of human resources to perform these practices, while firms that have not implemented circular economy measures view financing, investment and cost–benefit barriers as the most significant. Significant efforts need to be undertaken by firms to accomplished circular economy. Also circular economy regulation should be improved to make it easier for companies to implement strategies that will make them more sustainable.
Evaluation of the Bactericidal Activity of Fosfomycin in Combination with Selected Antimicrobial Comparison Agents Tested against Gram-Negative Bacterial Strains by Using Time-Kill Curves

The effects of combining fosfomycin with various antimicrobial agents were evaluated in vitro by broth microdilution checkerboard and time-kill kinetic studies. Checkerboard analyses were used to evaluate the following 30 Gram-negative isolates: 5 Pseudomonas aeruginosa, 5 Acinetobacter baumannii-Acinetobacter calcoaceticus species complex, and 20 Enterobacteriaceae isolates. ABSTRACT The effects of combining fosfomycin with various antimicrobial agents were evaluated in vitro by broth microdilution checkerboard and time-kill kinetic studies. Checkerboard analyses were used to evaluate the following 30 Gram-negative isolates: 5 Pseudomonas aeruginosa, 5 Acinetobacter baumannii-Acinetobacter calcoaceticus species complex, and 20 Enterobacteriaceae isolates. No isolate exhibited antagonism when fosfomycin was tested in combination, and synergy was observed in more than 25% of the drug combinations tested. The most frequent instances of synergy occurred when testing fosfomycin with β-lactams. Two isolates of Pseudomonas aeruginosa, 2 of Klebsiella pneumoniae, and 1 of the A. baumannii-A. calcoaceticus species complex that exhibited synergy when fosfomycin was tested in combination were subjected to time-kill kinetic analyses for confirmation. Time-kill assays confirmed synergistic activity. These data indicated that combination therapy with fosfomycin may be beneficial.
Estimating PM2.5 Concentrations Based on MODIS AOD and NAQPMS Data over Beijing–Tianjin–Hebei

Accurately estimating fine ambient particulate matter (PM2.5) is important to assess air quality and to support epidemiological studies. To analyze the spatiotemporal variation of PM2.5 concentrations, previous studies used different methodologies, such as statistical models or neural networks, to estimate PM2.5. However, there is little research on full-coverage PM2.5 estimation using a combination of ground-measured, satellite-estimated, and atmospheric chemical model data. In this study, the linear mixed effect (LME) model, which used the aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), meteorological data, normalized difference vegetation index (NDVI), and elevation data as predictors, was fitted for 2017 over Beijing–Tianjin–Hebei (BTH). The LME model was used to calibrate the PM2.5 concentration using the nested air-quality prediction modeling system (NAQPMS) simulated with ground measurements. The inverse variance weighting (IVW) method was used to fuse satellite-estimated and model-calibrated PM2.5. The results showed a strong agreement with ground measurements, with an overall coefficient (R2) of 0.78 and a root-mean-square error (RMSE) of 26.44 μg/m3 in cross-validation (CV). The seasonal R2 values were 0.75, 0.62, 0.80, and 0.78 in the spring, summer, autumn, and winter, respectively. The fusion results supplement the lack of satellite estimates and can capture more detailed information than the NAQPMS model. Therefore, the results will be helpful for pollution process analyses and health-related studies.
Evaluation of Supervised Machine Learning Algorithms for Detecting Anomalies in Vehicle’s Off- Board Sensor Data

A diesel particulate filter (DPF) is designed to physically remove diesel particulate matter or soot from the exhaust gas of a diesel engine. Frequently replacing DPF is a waste of resource and waiting for full utilization is risky and very costly, so, what is the optimal time/milage to change DPF? Answering this question is very difficult without knowing when the DPF is changed in a vehicle. We are finding the answer with supervised machine learning algorithms for detecting anomalies in vehicles off-board sensor data (operational data of vehicles). Filter change is considered an anomaly because it is rare as compared to normal data. Non-sequential machine learning algorithms for anomaly detection like oneclass support vector machine (OC-SVM), k-nearest neighbor (K-NN), and random forest (RF) are applied for the first time on DPF dataset. The dataset is unbalanced, and accuracy is found misleading as a performance measure for the algorithms. Precision, recall, and F1-score are found good measure for the performance of the machine learning algorithms when the data is unbalanced. RF gave highest F1-score of 0.55 than K-NN (0.52) and OCSVM (0.51). It means that RF perform better than K-NN and OC-SVM but after further investigation it is concluded that the results are not satisfactory. However, a sequential approach should have been tried which could yield better result.
Effects of landscapes, pesticide toxicity and host plant-herbivore phenological synchrony on the abundance of true bugs (Heteroptera) in apple orchards Táji környezet, peszticid terhelés és tápnövény- fitofág fenológiai szinkronitás hatása almaültetvények poloska (Heteroptera) együttes

s Markó V. , Elek Z. , Kovács-Hostyánszki A. , Kőrösi Á. , Somay L. , Földesi R. , Varga Á. , Iván Á. és Báldi A. (2016): Coleoptera assemblages in apple orchards along pesticide disturbance and landscape gradients. XXV. International Congress of Entomology, USA, Orlando, 2016. szeptember 25–30. Abstracts Markó V. , Somay L. , Kovács-Hostyánszki A. , Elek Z. , Iván Á. , Varga Á. és Báldi A. (2014): Tájszerkezet és pesztidicd terhelés hatása almaültetvények Coleoptera együtteseire. 60. Növényvédelmi Tudományos Napok, Budapest, 2014. február 18–19. Összefoglaló kiadvány: 41. Somay L. , Kovács-Hostyánszki A. , Elek Z. , Földesi R. , Kőrösi Á. , Markó V. , Nyisztor K. , Sárospataki M. , Varga Á. , Báldi A. (2013): Tájszerkezet heterogenitásának hatása almaültetvények ökoszisztéma szolgáltatásaira – Projektbemutatás. 5. Szünzoológiai Szimpózium, Vácrátót, 2013. március 22. Előadások összefoglalói.
Clinical Data on Daptomycin plus Ceftaroline versus Standard of Care Monotherapy in the Treatment of Methicillin-Resistant Staphylococcus aureus Bacteremia

Vancomycin (VAN) and daptomycin (DAP) are approved as a monotherapy for methicillin-resistant Staphylococcus aureus (MRSA) bacteremia. A regimen of daptomycin plus ceftaroline (DAP+CPT) has shown promise in published case series of MRSA salvage therapy, but no comparative data exist to compare up-front DAP+CPT head-to-head therapy versus standard monotherapy as an initial treatment. ABSTRACT Vancomycin (VAN) and daptomycin (DAP) are approved as a monotherapy for methicillin-resistant Staphylococcus aureus (MRSA) bacteremia. A regimen of daptomycin plus ceftaroline (DAP+CPT) has shown promise in published case series of MRSA salvage therapy, but no comparative data exist to compare up-front DAP+CPT head-to-head therapy versus standard monotherapy as an initial treatment. In a pilot study, we evaluated 40 adult patients who were randomized to receive 6 to 8 mg/kg of body weight per day of DAP and 600 mg intravenous (i.v.) CPT every 8 h (q8h) (n = 17) or standard monotherapy (n = 23) with vancomycin (VAN; dosed to achieve serum trough concentrations of 15 to 20 mg/liter; n = 21) or 6 to 8 mg/kg/day DAP (n = 2). Serum drawn on the first day of bacteremia was sent to a reference laboratory post hoc for measurement of interleukin-10 (IL-10) concentrations and correlation to in-hospital mortality. Sources of bacteremia, median Pitt bacteremia scores, Charlson comorbidity indices, and median IL-10 serum concentrations were similar in both groups. Although the study was initially designed to examine bacteremia duration, we observed an unanticipated in-hospital mortality difference of 0% (0/17) for combination therapy and 26% (6/23) for monotherapy (P = 0.029), causing us to halt the study. Among patients with an IL-10 concentration of >5 pg/ml, 0% (0/14) died in the DAP+CPT group versus 26% (5/19) in the monotherapy group (P = 0.057). Here, we share the full results of this preliminary (but aborted) assessment of early DAP+CPT therapy versus standard monotherapy in MRSA bacteremia, hoping to encourage a more definitive clinical trial of its potential benefits against this leading cause of infection-associated mortality. (The clinical study discussed in this paper has been registered at ClinicalTrials.gov under identifier NCT02660346.)