Miracle-dz/UniFAR-FTUs huggingface dataset:
Modified multiobjective evolutionary algorithm based on decomposition for low-carbon scheduling of distributed permutation flow-shop

Low-carbon scheduling has raised great interest during recent years under the background of green economy. In this paper, a modified multiobjective evolutionary algorithm based on decomposition (MOEA/D-M) is proposed to solve the distributed permutation flow-shop low-carbon scheduling problem (DPFLCSP) with the criteria of minimizing the makespan and carbon emission. Under the framework of basic MOEA/D, an operator-selection strategy is designed to enhance the exploration ability. This strategy is based on the relative position between solutions and reference point in the normalized objective space. Meanwhile, a local intensification component based on angles of solutions in the normalized objective space is incorporated in the algorithm to improve the quality of the explored solutions. This local intensification consists of some operators specially designed according to the properties of the problem. To balance the convergence and diversity, two different neighborhoods named mating neighborhood and replacement neighborhood are used. Besides, the critical path based carbon saving method is also used. Computational comparisons demonstrate the effectiveness of the operator-selection strategy and the superior quality of the MOEA/D-M to other algorithms.
Production and Biotechnological Potential of Extracellular Polymeric Substances from Sponge-Associated Antarctic Bacteria

ABSTRACT Four sponge-associated Antarctic bacteria (i.e., Winogradskyella sp. strains CAL384 and CAL396, Colwellia sp. strain GW185, and Shewanella sp. strain CAL606) were selected for the highly mucous appearance of their colonies on agar plates. The production of extracellular polymeric substances (EPSs) was enhanced by a step-by-step approach, varying the carbon source, substrate and NaCl concentrations, temperature, and pH. The EPSs produced under optimal conditions were chemically characterized, resulting in a moderate carbohydrate content (range, 15 to 28%) and the presence of proteins (range, 3 to 24%) and uronic acids (range, 3.2 to 11.9%). Chemical hydrolysis of the carbohydrate portion revealed galactose, glucose, galactosamine, and mannose as the principal constituents. The potential biotechnological applications of the EPSs were also investigated. The high protein content in the EPSs from Winogradskyella sp. CAL384 was probably responsible for the excellent emulsifying activity toward tested hydrocarbons, with a stable emulsification index (E24) higher than those recorded for synthetic surfactants. All the EPSs tested in this work improved the freeze-thaw survival ratio of the isolates, suggesting that they may be exploited as cryoprotection agents. The addition of a sugar in the culture medium, by stimulating EPS production, also allowed isolates to grow in the presence of higher concentrations of mercury and cadmium. This finding was probably dependent on the presence of uronic acids and sulfate groups, which can act as ligands for cations, in the extracted EPSs. IMPORTANCE To date, biological matrices have never been employed for the investigation of EPS production by Antarctic psychrotolerant marine bacteria. The biotechnological potential of extracellular polymeric substances produced by Antarctic bacteria is very broad and comprises many advantages, due to their biodegradability, high selectivity, and specific action compared to synthetic molecules. Here, several interesting EPS properties have been highlighted, such as emulsifying activity, cryoprotection, biofilm formation, and heavy metal chelation, suggesting their potential applications in cosmetic, environmental, and food biotechnological fields as valid alternatives to the commercial polymers currently used.
Adult Urology Oncology : Adrenal / Renal / Upper Tract / Bladder Retroperitoneal Lymphadenectomy for High Risk , Nonmetastatic Renal Cell Carcinoma : An Analysis of the ASSURE ( ECOG-ACRIN 2805 ) Adjuvant Trial

From the Fox Chase Cancer Center, Temple Health (BTR, RGU) and Abramson Cancer Center of University of Pennsylvania (NBH), Philadelphia, Pennsylvania, ECOG-ACRIN Biostatistics Center, Dana-Farber Cancer Institute (JM), Boston, Massachusetts, Tom Baker Cancer Center, University of Calgary (DYCH), Calgary, Alberta, Canada, Department of Urology, University of Rochester (EMM), Rochester, New York, University of Texas M. D. Anderson Cancer Center (CGW), Houston, Texas, Moores Cancer Center, University of California-San Diego (CJK), La Jolla, California, and Rutgers Cancer Institute of New Jersey (RSD), New Brunswick, New Jersey
Low Light Image Enhancement Based on Luminance Map and Haze Removal Model

In this paper, a novel and effective algorithm is proposed for noise reduction and contrast enhancement in low light images based on luminance map and haze removal model. The proposed method is divided into two steps: i) A combined denoising method using the improved guided filtering based on gradient information and median filtering is proposed to obtain the initial denoised image. ii) Considering that an inverted low light image presents quite similar to a haze image, the haze removal model is used to enhance the denoised low light image.The luminance component L is extracted to obtain the transmission map with the adaptive weight from the inverted denoised image which is applied to Lab color space. Then the classical quad-tree subdivision is utilized to estimate the atmospheric light, and then the de-hazed image is recovered by the haze removal model. At last, we can get the final enhanced image by inverting the de-hazed image back. The experimental results show that the proposed algorithm reduces the noise and enhances the contrast of the low light image more effectively and robustly than the conventional and the state-of-the-art algorithms
Enriching the “Senso Comune” Platform with Automatically Acquired Data

This paper reports on research activities on automatic methods for the enrichment of the Senso Comune platform. At this stage of development, we will report on two tasks, namely word sense alignment with MultiWordNet and automatic acquisition of Verb Shallow Frames from sense annotated data in the MultiSemCor corpus. The results obtained are satisfying. We achieved a final F-measure of 0.64 for noun sense alignment and a F-measure of 0.47 for verb sense alignment, and an accuracy of 68\% on the acquisition of Verb Shallow Frames.
Physical forces aware aging simulation on cultural heritage artifacts

Cultural heritage objects tend to change in appearance over time due to weathering phenomena and physical force effects, such as gravity or wind. Simulating such phenomena can be a useful guide for conservators and restorers. In this direction, the current paper proposes an aging simulation method which models the impact of physical forces using a particle-based approach. The proposed simulation method enhances the realism of the aging simulation through the creation of realistically shaped geometry regions for the decay formation under the effect of physical forces. Particularly, the case of gravitational accelerations effect was examined. The method is general and its application can be extended to different kinds of materials and weathering phenomena. A metallic sculpture has been used as a case study and the qualitative results presented in each intermediate processing step, demonstrate the overall functionality and the promising potential of the suggested approach in comparison with other existing methods and the decayed appearance of cultural heritage objects in their natural environment.
The complete mitochondrial genome of Stump-tailed Macaques (Macaca arctoides)

Abstract Stump-tailed macaque (Macaca arctoides) has been enlisted as the Near Threatened species in the IUCN Red List. In this study, the complete mitochondial genome of M. arctoides was determined. The mitogenome was 16,559 bp in length with an A + T content of 56.8%, containing 2 ribosomal RNA genes (rRNA), 22 transfer RNA genes (tRNA), 13 protein-coding genes (PCGs) and a control region (D-loop). Ten protein-coding genes (ND1, COX1, COX2, ND4, COX3, ND4L, ATP8, ATP6, CYTB, ND6) started with ATG codons, while ND2, ND3 and ND5 initiated with ATT, ATC and ATA, respectively. Eight PCGs ended with complete termination codons except for COX3, ND3, ND4, and CYTB terminated with incompleted codon T.
Death in the intestinal epithelium—basic biology and implications for inflammatory bowel disease

Every 4–5 days, intestinal epithelial cells (IEC) are terminated as they reach the end of their life. This process ensures that the epithelium is comprised of the fittest cells that maintain an impermeable barrier to luminal contents and the gut microbiota, as well as the most metabolically able cells that conduct functions in nutrient absorption, digestion, and secretion of antimicrobial peptides. IEC are terminated by apical extrusion—or shedding—from the intestinal epithelial monolayer into the gut lumen. Whether death by apoptosis signals extrusion or death follows expulsion by younger IEC has been a matter of debate. Seemingly a minor detail, IEC death before or after apical extrusion bears weight on the potential contribution of apoptotic IEC to intestinal homeostasis as a consequence of their recognition by intestinal lamina propria phagocytes. In inflammatory bowel disease (IBD), excessive death is observed in the ileal and colonic epithelium. The precise mode of IEC death in IBD is not defined. A highly inflammatory milieu within the intestinal lamina propria, rich in the proinflammatory cytokine, TNF‐α, increases IEC shedding and compromises barrier integrity fueling more inflammation. A milestone in the treatment of IBD, anti‐TNF‐α therapy, may promote mucosal healing by reversing increased and inflammation‐associated IEC death. Understanding the biology and consequences of cell death in the intestinal epithelium is critical to the design of new avenues for IBD therapy.
Machine learning techniques to predict sensitive patterns to fault attack in the Java Card application

Abstract Fault attack represents one of the serious threats against Java Card security. It consists of physical perturbation of chip components to introduce faults in the code execution. A fault may be induced using a laser beam to impact opcodes and operands of instructions. This could lead to a mutation of the application code in such a way that it becomes hostile. Any successful attack may reveal a secret information stored in the card or grant an undesired authorisation. We propose a methodology to recognise, during the development step, the sensitive patterns to the fault attack in the Java Card applications. It is based on the concepts from text categorisation and machine learning. In fact, in this method, we represented the patterns using opcodes n-grams as features, and we evaluated different machine learning classifiers. The results show that the classifiers performed poorly when classifying dangerous sensitive patterns, due to the imbalance of our data-set. The number of dangerous sensitive patterns is much lower than the number of not dangerous patterns. We used resampling techniques to balance the class distribution in our data-set. The experimental results indicated that the resampling techniques improved the accuracy of the classifiers. In addition, our proposed method reduces the execution time of sensitive patterns classification in comparison to the SmartCM tool. This tool is used in our study to evaluate the effect of faults on Java Card applications.
斯丕曼Charles Edward Spearman

以二因素论著称于世的英国心理学家斯丕曼生于1863年殁于1945年。 死后,泰晤士报以一句极为恰当的评语作为悼文的结论:"由于他对心理学问题应用了崭新的统计方法,和他结合深邃理论解释精确实验的非凡才能,他在心理科学的伟大人物中,占有一席不朽的地位。 "斯丕曼是一个传奇式的人物。 青年时代消磨在
Simultaneous determination of 29 pharmaceuticals in fish muscle and plasma by ultrasonic extraction followed by SPE-UHPLC-MS/MS.

A confirmatory method for the simultaneous detection of 29 pharmaceuticals in fish muscle and plasma was developed by using solid-phase extraction combined with ultra-high performance liquid chromatography and tandem mass spectrometry. Fish samples were extracted with methanol and enriched using Oasis HLB solid-phase extraction columns in one step. Twenty-nine target pharmaceuticals were quantified by the internal standard method and the calibration curves showed good linearity in a wide range with determination coefficients of greater than 0.913. The detection limits of the pharmaceuticals ranged from 0.01 to 2.00 μg/kg (μg/L). The applicability of the method was checked by precision and recovery experiments. The average recoveries of the 29 pharmaceuticals were between 61 and 111%, and all the relative standard deviations were below 25%. Our reported method has been demonstrated to be sensitive, convenient, rapid, and reliable for the simultaneous determination of 29 pharmaceuticals in fish muscle and plasma. Real sample determination showed that 25 and 9 of the 29 compounds were detected in fish muscle and plasma, respectively.
Insecticidal efficacy of silica nanoparticles against Rhyzopertha dominica F. and Tribolium confusum Jacquelin du Val

Bioassays were conducted to assess the effects of two silicon dioxide nanoparticles of Aerosil® and Nanosav against adults of Rhyzopertha dominica F. and Tribolium confusum Jacquelin du Val. Silica nanoparticles were applied at the rates of 50, 100, 200 and 300 mg · kg–1 on wheat and peeled barley. The mortality was counted after 1, 2, 3, and 7 days of exposure. Another experiment was carried out to evaluate the effect of food source on the survival of beetles after exposure to silica nanoparticles. Adults were exposed to silica nanoparticles at the rate of 0.2 mg · cm–2 for 1 and 2 days on filter paper inside plastic Petri dishes, respectively. After exposure, the initial mortality was counted and live individuals of both species were held for a week in empty glass vials or vials containing wheat and wheat flour, respectively. Silica nanoparticles have high toxicity on R. dominica and T. confusum adults. Rhyzopertha dominica was more susceptible than T. confusum. However, the mortality of both species increased with increasing concentrations and time exposed to each concentration. At low concentrations, Aerosil® was more effective than Nanosav. Silica nanoparticles were more effective in wheat grains than barley. Results indicated that the initial mortality was so high that the impact of food source on delay mortality was unclear in most cases. Silica nanoparticles were efficient against tested species and can be used effectively in a stored grain integrated pest management program.
Video saliency detection using the propagation of image saliency between frames

Recently, the saliency detection of image and video has attracted more and more attention due to its wide application. In this paper, we propose an image registration method based on SLIC image segmentation algorithm, which is used to realize the saliency information propagate between frame and frame. First, we use SLIC algorithm to divide each image in video into many regions, obtain the brightness and color information of each frame through LAB color space. Then, use the optical flow method to get the motion information of each frame. At the same time, the saliency information of the first frame is calculated by the method of Li et al [1]. Then, the following procedure is iterated from the first frame: first of all, we perform the registration with the divided regions as processing units, after that, saliency map of this frame is weighted according to the criterion of motion and color and brightness changes, and the result becomes saliency information of the next frame. The salience information obtained by each iteration is generated as a new frame, and the salience result of the video is obtained. The proposed method has been tested in two sets of video sequences and obtained good results.
Identifying characteristic miRNAs-genes and risk pathways of multiple sclerosis based on bioinformatics analysis

Multiple sclerosis is a chronic autoimmune disorder of the central nervous system. In MS, the genetic susceptibility is high and currently there is no effective treatment. MicroRNA, a small non-coding RNA, plays a vital role in immune responses. Aberrant or dysfunctional miRNAs may cause several diseases, including MS, thus miRNAs and miRNA related genes may be therapeutic weapons against MS. Here, we identified 21 miRNAs in peripheral blood mono-nuclear cells from over 600 persons, including healthy controls. By using informatics databases, 1637 susceptibility genes were evaluated and Cytoscape was used to integrate and visualize the relation between the miRNA identified and susceptibility genes. By using the cluster Profile package, a total of 10 risk pathways were discovered. Top pathways included: hsa05200 (pathway in cancer), hsa04010 (MAPK signaling pathway), and hsa04060 (cytokine-cytokine receptor interaction). By using the STRING database, a protein-protein interaction network was conducted to identify highly susceptibility genes. Moreover, the GSE21942 dataset was used to indicate the gene expression profiles and to correct prediction results, thereby identifying the most pivotal genes. The MiRSystem database provided information on both pivotal miRNAs and genes. In conclusion, miR-199a and miR-142-3p may be crucial for MS by targeting pivotal susceptibility genes, in particular KRAS and IL7R.
Studies on the effects of thyristor dynamic extinction angle on HVDC commutation failure

This paper focuses on the key technology of ultra high voltage direct current (UHVDC) converter valve equipment which is resistant to commutation failures. The simulation model is established, which can reflect the whole turn-off process of thyristor. The paper also offers the simulation models of converter valve model and of the double-fed high voltage direct current (HVDC) system. The transient fault and the failure mechanism of commutation failure are studied. The internal and external factors that affect commutation failure are analyzed in depth and the impact of operating conditions on commutation failure is quantified. The calculation method of the thyristor dynamic turn-off time and the related key technical indexes are proposed to optimize the commutation characteristics of the high power thyristor. This paper presents the method of intelligent trigger detection, such as forward voltage monitoring method, turn-off angle direct measurement method and minimum turn-off angle estimation method, together with their application approach in multi-infeed HVDC system (MIDC). The intelligent trigger monitoring device and the converter valve module prototype which is resistant to commutation failure are developed, and then verified by functional test.
Application of Digital Diagnosis and Treatment Technique in Benign Mandibular Diseases

Purpose: To explore the feasibility of preoperative planning for treatment of benign mandibular lesions (BML) using digital technologies such as three-dimensional (3D) reconstruction, measurement, visualization as well as image contrast and design of neural positioning protection template (NPPT) in combination with 3D printing technology in the BML diagnosis and treatment. Methods: The 3D models of BML and inferior alveolar nerves (IAN) of 10 BML patients were reconstructed based on their digital imaging and communications in medicine (DICOM) data using MIMICS16.0 software. The models were used to visualize lesions and nerve contrast measurement and guide design of personalized NPPT and osteotomy after operation modality was determined in order to achieve accurate, minimally invasive operation with shortened intraoperative time. Results: Intraoperative NPPT application could accurately locate lesions and their scope and assist osteotomy. The measurement results were consistent with those of preoperative reconstruction and measurement. The BML were curetted completely without damage IAN. The 10 BML patients had no numbness and other discomforts in the lower lip and mandibular teeth after operation. Conclusions: The digital diagnosis and treatment technology is an effective method for functional treatment of BML patients and its application could achieve personalized, minimally invasive and precise treatment and save intraoperation time.
Recursive Power Allocation with Interference Minimization for Time Varying Massive MIMO

Among the emerging breakthroughs for future wireless communications, massive multiple-input multiple-output (MIMO) has attracted a lot of interest. To harvest its potential, however, accurate channel state information (CSI) is required at the base station. Unfortunately, the accurate CSI is hard to be obtained when Doppler spread occurs. The mismatch between the precoder and the actual channel causes the signal to be phase-shifted, and the interuser interference arises. To overcome this problem, we propose a power allocation technique based on the predicted interference level of all users. First, we extract the Doppler shift information from the pilots sent by the mobile station (MS) to create predicted channel matrix. Based on this matrix, we conduct a recursive power allocation to minimize the interuser interference at the MSs. Computer simulation shows that our proposed technique enables the time varying massive MIMO transmission even when the precoder matrix is not frequently updated.
Intraclass Correlation for Measures from a Worksite Health Promotion Study: Estimates, Correlates, and Applications

Objectives. Investigators planning studies employing group-randomized designs need good estimates of the extra variation introduced as a result of correlated observations within units of assignment. We report intraclass correlation coefficients (ICCs) for a wide range of outcomes commonly employed in worksite studies and demonstrate analysis methods that can limit their deleterious impact. Methods. A sample of 11, 711 employees of 24 firms recruited from the Minneapolis/St. Paul metropolitan area completed a mailed survey in the SUCCESS study, reporting on a broad array of outcomes. Applying mixed-model regression, we provide both crude and adjusted estimates of ICCs for 27 outcomes. Results. The crude ICCs were generally small, with a mean of . 0163 and values ranging from 0 to . 0650. Adjustment for demographics reduced the ICCs for 25 of the 27 outcomes, and adjustment for additional individual-level covariates further reduced the ICCs for 23 of the 27 outcomes. Conclusions. Our results suggest that worksite-level ICCs for a variety of outcomes are generally small and can generally be reduced by adjustment for individual-level characteristics. Incorporating this information in planning worksite studies can improve sample size calculations to avoid underpowered studies.
Network modeling using optimal transmission switching

The aim of this paper is to identify an optimized network in an existing system which has minimized active power loss and generation cost obtainable through change in topology by reorganizing the switch status and remodeling the production schedules. The transmission system is made to participate with and function in coordination with the generating system schedules. The control variables required to get such optimal transmission switching (OTS) model are of both binary and continuous type. Present work solves the non-commensurate multi-objective problem by creating a weighted sum method to form a single fitness function model including constraints where the binary variables are created as a function of the continuous ones reducing it to a single variable type. Multiple objectives of OTS problem has been designed as an effective analysis and decision-making tool for the operator for choosing the best configuration and generation patterns that can be operated by considering a given set of load certainties. To check the robustness of the proposed method simulation has been done on IEEE-57 bus system successfully with a range of optimal solutions obtained by changing the weight factors for the decision maker to choose from.