Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of combined support vector machines in process fault diagnosis

The performance of Combined Support Vector Machines, C-SVM, is examined by comparing it's classification results with k-nearest neighbor and simple SVM classifier. For our experiments we use training and testing data obtained from two benchmark industrial processes. The first set is simulated data generated from Tennessee Eastman process simulator and the second set is the data obtained by running experiment on a Three Tank system. Our results show that the C-SVM classifier gives the lowest classification error compared to other methods. However, the complexity and computation time become issues, which depend on the number of faults in the data and the data dimension. We also examined Principal Component Analysis, using PC scores as input features for the classifiers but the performance was not comparable to other classifiers' results. By selecting appropriate number of variables using contribution charts for classification, the performance of the classifiers on Tennessee Eastman data enhances significantly. Therefore, using contribution charts for selecting the most important variables is necessary when the number of variables is large.
Effects of Variations in Reading Span Task Design on the Relationship Between Working Memory Capacity and Second Language Reading

Relationships between working memory (WM)-measured by reading span tasks (RSTs)-and second language (L2) reading are explored by probing the effects of differences in secondary task design (semantic vs. morphosyntactic) and the language of the task (first or second). Participants were 98 Turkish late adult learners of English as an L2 with moderate proficiency in the language. They completed a reading comprehension test in English and four RSTs (two in Turkish, two in English) whose processing tasks required judging whether there was an anomaly, morphosyntactic or semantic, depending on the RST. Exploratory factor analysis indicated that the storage component of span tasks loaded on the same factor, suggesting that storage is task- and language-independent. By contrast, L2 learners' processing was affected by the linguistic nature of the task and the language in which it was presented. Additionally, findings point to a significant relationship between L2 reading and learners' storage capacity. As for processing, resources underlying L1 and L2 semantic and L2 morphosyntactic processes contribute to L2 reading, unlike those underlying L1 morphosyntactic processes. These findings attenuate the notion of construct equivalency in WM measurement through RSTs, dependent on secondary task type and language used. [ABSTRACT FROM AUTHOR]
Impact of chemotherapy on symptom profile, oxidant-antioxidant balance and nutritional status in non-small cell Lung Cancer

Background: Lung cancer is associated with an oxidant-antioxidant imbalance that is implicated in tumor progression. However, the association of this imbalance on disease burden and treatment response is unclear. The effect of chemotherapy on oxidative stress, antioxidant status, and nutritional profile in patients with advanced nonsmall cell lung cancer (NSCLC) was prospectively evaluated. Subjects and Methods: Patients with confirmed cytological/histological diagnosis of NSCLC were recruited. Performance status was determined using the Eastern Cooperative Oncology Group grading and the Karnofsky Performance Scale. Skin fold anthropometry was done for nutritional assessment. All patients received chemotherapy with intravenous carboplatin and paclitaxel at three-weekly intervals. Response was assessed after four cycles by repeat imaging. Plasma levels of total antioxidant status (TAS), malondialdehyde (MDA), and glutathione peroxidase (GPx) levels were estimated using commercially available kits, and the change was correlated with clinical outcome, response to chemotherapy, performance status, and nutritional profile. Results: Thirty-five cases were studied (92% males), with a mean (SD) age of 56.2 (9.3) years. Following treatment, majority of patients demonstrated stable disease (n = 15 [42%]), followed by partial response (29%), progressive disease (22%), and complete remission (6%). Significant improvement occurred in respiratory symptoms. Body fat declined while subscapular skinfold thickness and 6-min walk distance increased. Spirometric values and performance status remained unchanged. GPx levels declined significantly while no notable change was observed in MDA and TAS levels. Conclusions: Chemotherapy for NSCLC improves symptoms, nutritional status, and exercise capacity but worsens the antioxidant status.
The real taxonomic identity of Trigona latitarsis Friese, 1900, with notes on type specimens (Hymenoptera, Apidae)

Abstract The taxonomic history of Trigona latitarsis Friese, 1900 and its clarification based on the observation of the types and literature data are treated in this study. The paper discusses the validity of the previously proposed lectotype, deposited in the ZMB (Berlin, Germany). Based on the type series deposited in HNHM (Budapest, Hungary) as well as the original description, a new lectotype and 15 paralectotypes from Amazon forest (São Paulo de Olivença, Amazonas) are designated. Data on the geographic distribution of Scaura latitarsis (Friese, 1900) are provided.
CRIM-FCHO: SAR Image Two-Stage Segmentation With Multifeature Ensemble

This paper investigates the synthetic aperture radar (SAR) image segmentation in terms of feature analysis and fusion and develops a new algorithm based on multifeature ensemble accordingly. This paper is characterized by two aspects. First, multiple heterogeneous features are extracted to accurately describe the objects in SAR images. These features are then integrated in the feature level and the similarity level, respectively, to avoid the mutual influences between different kinds of features and maximize the discriminability of the similarity measure between objects. Second, a two-stage algorithm consisting of a coarse merging stage and a fine classification stage is proposed. In the coarse merging stage, a context-based region iterative merging algorithm is designed to merge most of the unambiguous superpixels in image domain at a high speed. In the fine classification stage, a fuzzy clustering algorithm incorporating hybrid optimization is developed to balance the efficiency and the robustness of the algorithm by simultaneously searching heuristically in the complete high-dimension feature space and searching along the direction of the gradient steepest descent in each feature subspace. The effectiveness of the proposed method has been successfully validated on synthetic and real SAR images.
How to best Automate Intersection Management

Recently there has been increased research interest in developing adaptive control systems for autonomous vehicles. This study presents a comparative evaluation of two distinct approaches to automated intersection management for a multi-agent system of autonomous vehicles. The first is a centralized heuristic control approach using an extension of the Autonomous Intersection Management (AIM) system. The second is a decentralized neuro-evolution approach that adapts vehicle controllers so as they collectively navigate intersections. This study tests both approaches for controlling groups of autonomous vehicles on a network of interconnected intersections, without the constraints of traffic lights or stop signals. These task environments thus simulate potential future scenarios where vehicles must drive autonomously without specific road infrastructure constraints. The capability of each approach to appropriately handle various types of interconnected intersections, while maintaining an efficient throughput of vehicles and minimizing delay is tested. Results indicate that neuro-evolution is an effective method for automating collective driving behaviors that are robust across a broad range of road networks, where evolved controllers yield comparable task performance or out-perform an AIM controller.
The role of organizational culture in retaining nursing workforce.

PURPOSE OF THE STUDY We examined how organizational culture in nursing homes affects staff turnover, because culture is a first step to creating satisfactory work environments. DESIGN AND METHODS Nursing home administrators were asked in 2009 to report on facility culture and staff turnover. We received responses from 419 of 1,056 administrators contacted. Respondents reported the strength of cultural values using scales from a Competing Values Framework and percent of staff leaving annually for Registered Nurse (RN), Licensed Practice Nurse (LPN), and nursing aide (NA) staff. We estimated negative binomial models predicting turnover. RESULTS Turnover rates are lower than found in past but remain significantly higher among NAs than among RNs or LPNs. Facilities with stronger market values had increased turnover among RNs and LPNs, and among NAs when turnover was adjusted for facilities with few staff. Facilities emphasizing hierarchical internal processes had lower RN turnover. Group and developmental values focusing on staff and innovation only lowered LPN turnover. Finally, effects on NA turnover become insignificant when turnover was adjusted if voluntary turnover was reported. IMPLICATIONS Organizational culture had differential effects on the turnover of RN, LPN, and NA staff that should be addressed in developing culture-change strategies. More flexible organizational culture values were important for LPN staff only, whereas unexpectedly, greater emphasis on rigid internal rules helped facilities retain RNs. Facilities with a stronger focus on customer needs had higher turnover among all staff.
Gender Differences at Work: International Variations in Occupational Segregation

Despite the prominence of discussions of gender segregation in explanations of labour market inequalities, there have been relatively few cross-national studies due to a lack of suitably detailed data. A recent ILO initiative obtained suitable data for cross-national analysis of 38 countries, with a much greater number of occupational categories than has usually been available. This paper reports findings from the analysis of these data. The problems and potential of using such data are discussed and a standardisation is introduced to control for the effects of the number of occupations in the segregation measure. There are important differences in the level of segregation in different countries. The highly segregated countries are to be found in Western Europe, and in particular Scandinavia. Several Arab countries also have high levels of segregation. An argument is made suggesting that the context and meaning of segregation patterns may be quite different from what might be inferred from single country studies.
Complementation of Yeast Genes with Human Genes as an Experimental Platform for Functional Testing of Human Genetic Variants

While the pace of discovery of human genetic variants in tumors, patients, and diverse populations has rapidly accelerated, deciphering their functional consequence has become rate-limiting. Using cross-species complementation, model organisms like the budding yeast, Saccharomyces cerevisiae, can be utilized to fill this gap and serve as a platform for testing human genetic variants. To this end, we performed two parallel screens, a one-to-one complementation screen for essential yeast genes implicated in chromosome instability and a pool-to-pool screen that queried all possible essential yeast genes for rescue of lethality by all possible human homologs. Our work identified 65 human cDNAs that can replace the null allele of essential yeast genes, including the nonorthologous pair yRFT1/hSEC61A1. We chose four human cDNAs (hLIG1, hSSRP1, hPPP1CA, and hPPP1CC) for which their yeast gene counterparts function in chromosome stability and assayed in yeast 35 tumor-specific missense mutations for growth defects and sensitivity to DNA-damaging agents. This resulted in a set of human–yeast gene complementation pairs that allow human genetic variants to be readily characterized in yeast, and a prioritized list of somatic mutations that could contribute to chromosome instability in human tumors. These data establish the utility of this cross-species experimental approach.
Changes of bone mineral density and serum pentosidine during a 27-month follow-up of monthly minodronate in osteoporotic patients

ABSTRACT Purpose: Monthly regimen of minodronate for osteoporosis more than two years has not been reported yet. The aim of this study is to elucidate the effect of monthly minodronate (M-MIN) on bone mineral density (BMD) and serum pentosidine (Pen) during 27 months. Materials and methods: The study consisted of 52 newly treated patients (73.3 ± 8.8 years) (new group) and 47 patients (75.9 ± 9.5 years) who were switched from either alendronate or risedronate (switch group). Monthly minodronate (50 mg/every 4 weeks) was administered for 27 months. Lumbar, femoral neck, and total hip BMDs and serum pentosidine were monitored at baseline and after 9, 18, and 27 months of treatment. Results: In the new condition, lumbar, neck, and total hip BMDs increased significantly by 9.07%, 3.15%, and 3.06%, respectively. Only the lumbar BMD significantly increased in the switch condition. Serum Pen increased in both groups in a time-dependent manner. In the group switch, multivariate logistic regression analysis revealed that the initial change in serum intact procollagen type I N-terminal propeptide (P1NP) at 9 months was an independent predictor of changes in neck and total hip BMDs at 27 months (OR = 1.039, 95% CI 1.003–1.077, p = 0.032 for neck and OR = 1.055, 95% CI 1.009–1.104, p = 0.020 for total hip). Conclusions: Monthly minodronate treatment increased BMDs in newly treated patients over 27 months. Serum Pen increased with M-MIN therapy, possibly indicating prolonged bone turnover. The initial 9-month changes in serum P1NP predicted the 27-month changes in hip BMDs when M-MIN replaced alendronate or risedronate.
Murine Cytomegalovirus m38.5 Protein Inhibits Bax-Mediated Cell Death

ABSTRACT Many viruses encode proteins that inhibit the induction of programmed cell death at the mitochondrial checkpoint. Murine cytomegalovirus (MCMV) encodes the m38.5 protein, which localizes to mitochondria and protects human HeLa cells and fibroblasts from apoptosis triggered by proteasome inhibitors but not from Fas-induced apoptosis. However, the ability of this protein to suppress the apoptosis of murine cells and its role during MCMV infection have not been investigated previously. Here we show that m38.5 is expressed at early time points during MCMV infection. Cells infected with MCMVs lacking m38.5 showed increased sensitivity to cell death induced by staurosporine, MG132, or the viral infection itself compared to the sensitivity of cells infected with wild-type MCMV. This defect was eliminated when an m38.5 or Bcl-XL gene was inserted into the genome of a deletion mutant. Using fibroblasts deficient in the proapoptotic Bcl-2 family proteins Bak and/or Bax, we further demonstrated that m38.5 protected from Bax- but not Bak-mediated apoptosis and interacted with Bax in infected cells. These results consolidate the role of m38.5 as a viral mitochondrion-localized inhibitor of apoptosis and its functional similarity to the human cytomegalovirus UL37x1 gene product. Although the m38.5 gene is not homologous to the UL37x1 gene at the sequence level, m38.5 is conserved among rodent cytomegaloviruses. Moreover, the fact that MCMV-infected cells are protected from both Bak- and Bax-mediated cell death suggests that MCMV possesses an additional, as-yet-unidentified mechanism to block Bak-mediated apoptosis.
28 GHz Millimeter-Wave Ultrawideband Small-Scale Fading Models in Wireless Channels

This paper presents small-scale fading measurements for 28 GHz outdoor millimeter-wave ultrawideband channels using directional horn antennas at the transmitter and receiver. Power delay profiles were measured at half-wavelength spatial increments over a local area (33 wavelengths) on a linear track in two orthogonal receiver directions in a typical base-to-mobile scenario with fixed transmitter and receiver antenna beam pointing directions. The voltage path amplitudes are shown to follow a Rician distribution, with K-factor ranging from 9 - 15 dB and 5 - 8 dB in line of sight (LOS) and non-line of sight (NLOS) for a vertical-to-vertical co- polarized antenna scenario, respectively, and from 3 - 7 dB in both LOS and NLOS vertical-to- horizontal cross-polarized antenna scenario. The average spatial autocorrelation functions of individual multipath components reveal that signal amplitudes reach a correlation of 0 after 2 and 5 wavelengths in LOS and NLOS co-polarized V-V antenna scenarios. The models provided are useful for recreating path gain statistics of millimeter- wave wideband channel impulse responses over local areas, for the study of multi-element antenna simulations and channel estimation algorithms.
Behavior Analysis of Parent-Child Interactions from Text

Parent-Child Interaction Therapy (PCIT) is a ther-apeutic approach designed to enhance the interaction between parents and their children. Parent-child interaction quality may be assessed via observations of free-play or structured tasks between parents and young children. Based on these assess-ments, interventionists provide therapy designed to support more optimal parent-child interactions and promote children's developmental outcomes. While conducting these assessments is vital for children's men-tal health development, manual assessments are time-consuming and resource intensive. This work aims to make PCIT accessible by using Artificial Intelligence (AI) to analyze interaction quality, based on linguistic features in an interactive dialogue. We propose a solution to classify the main behavioral classes in the Dyadic Parent-Child Interaction Coding System (DPICS). To the best of our knowledge, our work is the first model that uses a Transformer-based architecture to analyze the emotions and the psychology integral to the parent-child interactions. The proposed model could understand and detect grammatical, syntactic, and emotional characteristics of the language in parent-child interactions. We categorized Natural Language Processing (NLP) strategies in parent-child interaction quality into three categories: deep learning-based, ML-based, and transfer learning-based. The proposed model is followed by a transfer learning strategy that is fine-tuned over a RoBERTa model and considers text in order to produce comparable results without the use of audio. Our results showed that our proposed model can detect behav-ioral aspects of parent-child interaction without the use of further feature engineering or incorporating additional modalities. We achieved a validation accuracy of 90 %, a significant improvement of 11 % compared to the most successful results reported in similar studies, and therapist agreement rates of 80 %.
On the strength of weak ties in mobile social networks

Weak ties, introduced in the seminal paper by Granovetter [6], refer to people's relationships with acquaintances outside their social circle (i.e., acquaintances with which they interact infrequently). We show that weak ties play an important role on the dissemination of content updates over a mobile social network. From a practical perspective, weak ties can be used to design strategies for limiting the bandwidth usage on such a network, without severely impacting the speed with which the content is disseminated. Moreover, the importance of weak ties can be traced on the effect they have on the edge expansion of the social network. By identifying this relationship, we extend and validate earlier work [7], that characterizes the speed of content dissemination in terms of the network's edge expansion.
Probabilistic Inference for Cold Start Knowledge Base Population with Prior World Knowledge

Building knowledge bases (KB) automatically from text corpora is crucial for many applications such as question answering and web search. The problem is very challenging and has been divided into sub-problems such as mention and named entity recognition, entity linking and relation extraction. However, combining these components has shown to be under-constrained and often produces KBs with supersize entities and common-sense errors in relations (a person has multiple birthdates). The errors are difficult to resolve solely with IE tools but become obvious with world knowledge at the corpus level. By analyzing Freebase and a large text collection, we found that per-relation cardinality and the popularity of entities follow the power-law distribution favoring flat long tails with low-frequency instances. We present a probabilistic joint inference algorithm to incorporate this world knowledge during KB construction. Our approach yields state-of-the-art performance on the TAC Cold Start task, and 42% and 19.4% relative improvements in F1 over our baseline on Cold Start hop-1 and all-hop queries respectively.
Changes in household, transport and recreational physical activity and television viewing time across the transition to retirement: longitudinal evidence from the EPIC-Norfolk cohort

Background Retirement is associated with an increase in recreational physical activity but its impact on other domains of activity (at home, for transport) and sedentary behaviour, such as time spent watching television (TV) is unknown. We examined the association between retirement and changes in domain-specific and overall activity and TV viewing. Methods Data were derived from the population-based EPIC (European Prospective Investigation into Cancer)–Norfolk cohort. Physical activity and TV viewing time were self-reported at baseline (1997–2000) and follow-up 2 (2006–2007) by 3334 participants employed at baseline, of whom 785 (24%) were retired at follow-up 1 (2002–2006). Multivariable regression models were fitted to estimate the association between retirement and changes in physical activity and weekly TV viewing time. Results Compared with continued employment, retirement was associated with a decline in overall activity (men: non-manual, −40.9 MET h/wk; manual, −49.6 MET h/wk; women: non-manual, −26.9 MET h/wk; manual, −31.6 MET h/wk; all p<0.001 (MET, metabolic equivalent of task)). Domain-specific activity declined for transport and occupational (p<0.001) and increased for recreational (p<0.02) and household (p≤0.002) activity. We observed significant interaction between retirement and social class in respect of overall and domain-specific activity apart from household activity. Retirement was associated with a mean increase in TV viewing time, with the largest increase among manual social classes (men: +3.9 h/wk; women: +2.8 h/wk; both p<0.001). Conclusions Interventions should aim to promote household and transport as well as recreational activity. Further research on the impact of retirement on sedentary behaviour is needed.