Miracle-dz/UniFAR-FTUs huggingface dataset:
Motivationally Significant Self-control: Enhanced Action Withholding Involves the Right Inferior Frontal Junction

In everyday life, people use self-control to withhold actions. This ability is particularly important when the consequences of action withholding have an impact on the individual's well-being. Despite its importance, it is unclear as to how the neural nodes implicated in action withholding contribute to this real-world type of self-control. By modifying an action withholding paradigm, the go/no-go task, we examined how the brain exerts self-control during a scenario in which the implications of withholding an action are meaningful and motivationally significant. A successfully withheld response contributed to long-term monetary rewards, whereas failure to withhold a response incurred an immediate monetary punishment. Compared with neutral action withholding, participants significantly improved their performance when these contingencies were applied. Crucially, although the right IFG and pre-SMA were found to promote overall action withholding, the enhancement in behavioral performance relative to a neutral condition was only reflected by a physiological change in a region encompassing the right inferior frontal junction and precentral gyrus. We speculate that the ability to flexibly modulate attention to goal-relevant stimuli is crucial to enhanced, motivationally driven action withholding and that this ability is subserved by the right inferior frontal junction. These findings suggest that control-modulating factors, rather than action withholding processes per se, can be critical to improving motivationally significant action withholding outcomes.
Collision avoidance with potential fields based on parallel processing of 3D-point cloud data on the GPU

In this paper we present an experimental study on real-time collision avoidance with potential fields that are based on 3D point cloud data and processed on the Graphics Processing Unit (GPU). The virtual forces from the potential fields serve two purposes. First, they are used for changing the reference trajectory. Second they are projected to and applied on torque control level for generating according nullspace behavior together with a Cartesian impedance main control loop. The GPU algorithm creates a map representation that is quickly accessible. In addition, outliers and the robot structure are efficiently removed from the data, and the resolution of the representation can be easily adjusted. Based on the 3D robot representation and the remaining 3D environment data, the virtual forces that are fed to the trajectory planning and torque controller are calculated. The algorithm is experimentally verified with a 7-Degree of Freedom (DoF) torque controlled KUKA/DLR Lightweight Robot for static and dynamic environmental conditions. To the authors knowledge, this is the first time that collision avoidance is demonstrated in real-time on a real robot using parallel GPU processing.
A survey on detection and classification of cotton leaf diseases

Cotton is the most important cash crop in India. It is also known as “White Gold” or “The King of fibers” among all cash crops in the country. About 80-90% of the diseases which occur on the leaves of cotton are Alternaria leaf spot, Cercospora leaf spot, Bacterial blight and Red spot. This paper presents a survey on detection and classification of cotton leaf diseases. It is difficult for human eyes to identify the exact type of leaf disease which occurs on the leaf of plant. Thus, in order to identify the cotton leaf diseases accurately, the use of image processing and machine learning techniques can be helpful. The images used for this work were acquired from the cotton field using digital camera. In pre-processing step, background removal technique is applied on the image in order to remove background from the image. Then, the background removed images are further processed for image segmentation using otsu thresholding technique. Different segmented images will be used for extracting the features such as color, shape and texture from the images. At last, these extracted features will be used as inputs of classifier.
Training high-dimensional neural networks with cooperative particle swarm optimiser

This paper analyses the behaviour of particle swarm optimisation applied to training high-dimensional neural networks. Despite being an established neural network training algorithm, particle swarm optimisation falls short at training high-dimensional neural networks. Reasons for poor performance of PSO are investigated in this paper, and hidden unit saturation is hypothesised to be a cause of the failure of PSO in training high-dimensional neural networks. An analysis of various activation functions and search space boundaries leads to the conclusion that hidden unit saturation can be slowed down by combining activation function choice with appropriate search space boundaries. Bounded search is shown to significantly outperform unbounded search in high-dimensional neural network error search spaces.
Segmentation Strategies to Face Morphology Challenges in Brazilian-Portuguese/English Statistical Machine Translation and Its Integration in Cross-Language Information Retrieval

The use of morphology is particularly inter- esting in the context of statistical machine translation in order to reduce data sparseness and compensate a lack of training corpus. In this work, we propose several approaches to introduce morphology knowledge into a standard phrase-based machine translation sys- tem. We provide word segmentation using two differ- ent tools (COGROO and MORFESSOR) which allow re- ducing the vocabulary and data sparseness. Then, to these segmentations we add the morphological in- formation of a POS language model. We combine all these approaches using a Minimum Bayes Risk strat- egy. Experiments show significant improvements from the enhanced system over the baseline system on the Brazilian-Portuguese/English language pair. Finally, we report a case study of the impact of enhancing the sta- tistical machine translation system with morphology in a cross-language application system such as ONAIR which allows users to look for information in video fragments through queries in natural language.
Association of Processed Meat Intake with Hypertension Risk in Hemodialysis Patients: A Cross-Sectional Study

In this cross-sectional study, we hypothesized that hemodialysis patients consuming greater processed meat is associated with hypertension risk, which can be partly explained by the high sodium content in processed meat. From September 2013 to May 2014, one hundred and four patients requiring chronic hemodialysis treatment were recruited from hemodialysis centers. Data on systolic blood pressure and diastolic blood pressure before receiving dialysis, and 3-day dietary records of the recruited patients were collected. HD patients with systolic and diastolic blood pressures greater than140 mmHg and higher than 90 mmHg, respectively, were considered hypertension risk. Protein foods were divided into 4 categories: red meat, white meat, soybeans, and processed meat (e.g., sausage and ham). In a model adjusted for energy intake and hypertension history, additional servings of processed meats was positively associated to systolic blood pressure >140 mmHg (odds ratio [95% confidence interval]: 2.1 [1.0–4.3]), and diastolic blood pressure > 90 mmHg (odds ratio: 2.5 [1.2–5.5]). After adjustment for dietary sodium contents or body mass index (BMI), most associations were substantially attenuated and were no longer significant. In systolic blood pressure greater than140 mmHg, one serving per day of red meats (β = -1.22, P < .05) and white meats (β = -0. 75, P = .05) was associated with a reduced risk compared with one serving per day of processed meats. Similarly, compared with one serving per day of processed meat, a reduced risk of diastolic blood pressure higher than 90 mmHg was associated with one serving per day of red meat (β = -1. 59, P < .05), white meat (β = -0. 62, P < .05). Thus, in these hemodialysis patients, intake of processed meat is significantly positively associated with higher blood pressure risk, and both sodium contents in processed meat and BMI significantly contributes to this association.
Business intelligence on complex graph data

Advances in the Internet of Things will provide massive amounts of context-aware information that would need to be ingested and understood by supporting IT infrastructures, influencing running processes that trigger actions. As a result, future Business Intelligence (BI) platforms would need to be able to process and analyze complex data. In this paper, we adapt a generic graph model that may be used to represent data in many applications of interest. We then show how analytical queries over these data can be naturally expressed via an OLAP-like aggregation framework we introduce. We describe how ad-hoc aggregations can be easily decomposed into smaller independent computations via a proper query rewriting mechanism. Our techniques provide the basis for selecting materialized views in order to expedite computation of frequent analytical queries in large datasets, enabling data warehousing of collections consisting of millions of graphs. Our experiments demonstrate the benefits of our methods.
The RNase P family

Ribonuclease P (RNase P) is a ribonucleoprotein comprised of a catalytic RNA subunit and one or several protein subunits. RNase P is best known for its role in 5´-processing of tRNA precursors. RNase P enzymes from almost all forms of life, including protein-synthesizing organelles, contain an RNase P with a conserved, homologous RNA. Five distinct structure classes of RNase P RNAs have been identified in Bacteria and Archaea; eukaryotic RNase P RNAs are not yet sufficiently well surveyed for structure classes to be defined. Here we will examine the structure variations in RNase P RNAs in Bacteria, Archaea, Eukaryotes, plastids, and mitochondria with special emphasis on the functional roles these unique secondary structures perform.
MAINTENANCE OF A MALE‐KILLING WOLBACHIA IN DROSOPHILA INNUBILA BY MALE‐KILLING DEPENDENT AND MALE‐KILLING INDEPENDENT MECHANISMS

Many maternally inherited endosymbionts manipulate their host's reproduction in various ways to enhance their own fitness. One such mechanism is male killing (MK), in which sons of infected mothers are killed by the endosymbiont during development. Several hypotheses have been proposed to explain the advantages of MK, including resource reallocation from sons to daughters of infected females, avoidance of inbreeding by infected females, and, if transmission is not purely maternal, the facilitation of horizontal transmission to uninfected females. We tested these hypotheses in Drosophila innubila, a mycophagous species infected with MK Wolbachia. There was no evidence of horizontal transmission in the wild and no evidence Wolbachia reduced levels of inbreeding. Resource reallocation does appear to be operative, as Wolbachia‐infected females are slightly larger, on average, than uninfected females, although the selective advantage of larger size is insufficient to account for the frequency of infection in natural populations. Wolbachia‐infected females from the wild—although not those from the laboratory—were more fecund than uninfected females. Experimental studies revealed that Wolbachia can boost the fecundity of nutrient‐deprived flies and reduce the adverse effect of RNA virus infection. Thus, this MK endosymbiont can provide direct, MK‐independent fitness benefits to infected female hosts in addition to possible benefits mediated via MK.
“I Was Banging My Head Against a Brick Wall”: Exclusionary Power and the Gendering of Sport Organizations

The under-representation of women in sport management has increasingly been recognized by government and nongovernment organizations, and there has been some attempt to redress the imbalance. Research has indicated, however, that the gendering of sport organizations is not simply a numbers’ game. The purpose of this study was to analyze the exercise of exclusionary power as an aspect of gender relations within a six member volunteer Board of Directors of an Australian local, grass-roots sport organization. Data were gathered using semistructured interviews, participant observation and documentary evidence over a 15-month period. This study identified that, although numerical underrepresentation of men or women on this Board was not an issue for either sex, exclusionary power was exercised in a number of overlapping ways which ultimately limited the participation, input, and influence of its female members.
Learning and Memory.

Mice were subjected to a taste aversion conditioning procedure in which they drank water, familiar saccharin, or novel saccharin, followed by injection of either NaCl or the emetic agent LiCl. Immunohistochemistry was used to localize phosphorylated MAP kinase (ppERK) and phosphoCREB (pCREB) in the brain shortly after conditioning. An examination of insular cortex and amygdala revealed speci®c phosphorylation of MAP kinase by novel saccharin and LiCl, and CREB by LiCl. Pairing of novel saccharin with LiCl was the only stimulus suf®cient to increase ppERK and pCREB immunoreactivity in the lateral amygdala, suggesting this as a site of CS±US convergence. ppERK immunoreactivity was localized to both nuclear and non-nuclear compartments, suggesting multiple functional roles of MAP kinase during learning. NeuroReport 11:1625±1630 & 2000 Lippincott Williams & Wilkins.
On-line data registration in OUTDOOR environment

In the paper an algorithm of 3D data registration based on CUDA implementation is shown. The research is related to the problem of collecting 3D data with laser measurement system mounted on rotated head, to be used in mobile robot applications. Assumed performance of data registration algorithm is achieved, therefore it can used as On-line. The ICP (Iterative Closest Point) approach is chosen as registration method. Computation is based on massively parallel architecture of NVIDIA CUDA. The presented concept of 3D data matching is based on parallel computation used for fast nearest neighbor search. Nearest neighbor search procedure is using 3D space decomposition into cubic buckets, therefore the time of matching is deterministic.
INTERVIEWERS' VERBAL IDIOSYNCRASIES AS A SOURCE OF BIAS

Interviewer effects in recording can bias survey data in two ways: (i) unsystematically, by increasing random error; and (2) systematically, by suppressing natural respondent variability. Many studies have dealt with random error, but few with systematic error. This study investigates the problem of systematic bias from recording in survey data. Unsystematic error is typically related to "incompetence," or the interviewer's lack of the clerical and critical skills needed for recording. Guest and Nuckols, Sheatsley and others have identified certain personality and demographic correlates of competent recording (i.e., recording with relatively few clerical errors); e.g., intelligence, sex, marital status, education, and experience in interviewing appear to be good predictors. ' These unsystematic effects are generally considered endemic to survey research. Random error is a calculated risk, taken as the better part of the implicit trade-off with unsatisfactory features of other datacollection methods. Generally, the hope is that instances of random error will balance out over many interviews. Systematic effects cannot be so hopefully dismissed. Typically, they result from consistent interviewer behaviors, or idiosyncrasies. These create less variability within one interviewer's production than between sets of schedules submitted by several different interviewers. By contrast, in the ideal situation where each interviewer's quota of respondents represents a random subsample, the between and within variances should be approximately the same. For example, an individual interviewer can be expected to use words in a systematic way. If she does not record her respondents' words verbatim, then neces-
Neural-electronic inhibition simulated with a neuron model implemented in SPICE

There have been numerous studies presented in the literature related to the simulation of the interaction between biological neurons and electronic devices. A complicating factor associated with these simulations is the algebraic complexity involved in implementation. This complication has impeded simulation of more involved neural-electronic circuitry and consequently has limited potential advancements in the integration of biological neurons with synthetic electronics. In this paper, we describe a modification to a previously proposed SPICE based Hodgkin-Huxley neuron model that demonstrates more physiologically relevant electrical behavior. We utilize this SPICE based neuron model in conjunction with an external circuit that allows for artificial selective inhibition of neural spiking. The neural firing control scheme proposed herein would allow for action potential frequency modulation of neural activity that, if developed further, could potentially be applied to suppress undesirable neural activity that manifests symptomatically as the tremors or seizures associated with specific pathologies of the nervous system.
Uterine Anomalies: Frequency of Diagnosis and Associated Obstetric Complications

Uterine anomalies are associated with an increase in cases of breech presentation, premature labor, abnormal presentation with dystocia, and the necessity for cesarean section. The yearly frequency of diagnosis of an anomaly has varied from 1.06 to 0.48 at this medical center depending on the physician's clinical suspicion. Thus, if the true incidence and the decrease of obstetric complications are to be accomplished, an increased interest in diagnosing uterine anomalies is essential.
Antibacterial Activity of Metabolites Products of Vibrio Alginolyticus Isolated from Sponge Haliclona sp. Against Staphylococcus Aureus

The objective of this study was to investigate the antibacterial activity of primary and secondary metabolites from Vibrio alginoliticus isolated from sponge Haliclona sp. against Staphylococcus aureus. A descriptive method was used in this research. The antibacterial activity was analysed by paper disk method. The results showed that the primary metabolites produced by Vibrio alginoliticus that is in symbiosis with sponge Haliclona sp. were able to effectively inhibit Staphylococcus aureus growth with an inhibition zone diameter of 12.9 mm, while the secondary metabolites of 9.9 mm. Electrophoresis analysis of the primary metabolites showed that there were 11 protein bands which were not found in secondary metabolites. Protein bands with low molecular weights presumably had an inhibiting effect on the growth of Staphylococcus aureus.
Multi-Antenna Downlink Broadcast Using Compressed-Sensed Medium Access

In this paper, we propose a method for user selection and channel estimation using compressed sensing. In particular, we consider a multiple-input multiple-output (MIMO) downlink broadcast scenario. We establish that full channel state information (and not just channel quality) for each self-selecting user can be obtained at the basestation via compressed sensing with no increase in overhead for the uplink feedback channel. We demonstrate the new method as a medium access technique for MIMO downlink broadcast with transmitter precoding and linear receiver processing.
SABIO: A BIOLOGICALLY PLAUSIBLE CONNECTIONIST APPROACH TO AUTOMATIC TEXT SUMMARIZATION

An implementation of a computational tool to generate new summaries from new source texts is presented, by means of the connectionist approach (artificial neural networks). Among other contributions that this work intends to bring to natural language processing research, the use of a more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expectation that it may bring an increase in computational efficiency when compared to the so-called biologically implausible algorithms.
Novel scheme for ultrafast all-optical XOR operation

A novel scheme for all-optical exclusive-OR (XOR) operating at 160 Gb/s is proposed and analyzed by means of numerical simulations. It consists of a Mach-Zehnder interferometer (MZI) where a semiconductor optical amplifier (SOA) is placed in each of its arms. This SOA-MZI setup is coupled to a delay interferometer, which acts as a signal regenerator. It is shown that error-free operation can be achieved at a data rate of 160 Gb/s, indicating that the proposed scheme is not limited by the SOA recovery time.
Surface acting and distress tolerance as predictors of workplace deviance among Nigerian commercial bank workers

This study examined surface acting and distress tolerance as predictors of workplace deviance. Three hundred and thirty-two (332) workers (176 males and 156 females) drawn from selected banks in Nsukka, Enugu State, Nigeria participated in the study. The participants responded to validated measures of surface acting and distress tolerance. The result of regression analyses indicated that surface acting significantly predicted workplace deviance. The result also revealed that distress tolerance was significantly related to workplace deviance. The standardized regression coefficients showed that surface acting was a stronger predictor of workplace deviance than distress tolerance. It was suggested that positive behaviours that are consistent with the organizational work ethics should be adequately reinforced to alleviate the negative emotions felt as a result of surface acting. It was also concluded that Nigeria bank employees who persist in the face of emotional distress may be less likely to engage in workplace deviant behaviours. Key words: Surfacing acting, distress tolerance, workplace deviance and Nigerian bank workers.
Association between PD-L1 expression combined with tumor-infiltrating lymphocytes and the prognosis of patients with advanced hypopharyngeal squamous cell carcinoma

Limited information is available regarding the immune-related prognostic factors of patients with advanced hypopharyngeal squamous cell carcinoma (HPSCC). The expression of programmed cell death-ligand 1 (PD-L1) in tumor cells contributes to a mechanism that allows cancer cells to escape immune surveillance. We investigated whether PD-L1 or human leukocyte antigen (HLA) class I expression in tumor cells and the tumor-infiltrating lymphocyte (TIL) density were associated with the tumor response to neoadjuvant chemotherapy (NAC) and survival in patients with advanced HPSCC. We retrospectively reviewed 83 consecutive patients with stage III or IV HPSCC who received NAC. We evaluated PD-L1 and HLA class I expression and TIL density using immunohistochemistry. Univariate and multivariate analyses demonstrated that CD8+ TIL density was an independent and significant predictive factor for the response to NAC, progression-free survival (PFS) and overall survival (OS), whereas PD-L1 or HLA class I expression did not significantly correlate. The subgroup analysis revealed that a higher CD8+ TIL density without detectable PD-L1 expression tended to be associated with longer patient survival. These results suggest that PD-L1 expression levels combined with CD8+ TIL density may serve as a predictive biomarker for patients with stage III or IV HPSCC receiving NAC.