Miracle-dz/UniFAR-FTUs huggingface dataset:
DIFFERENTIAL EXPRESSION OF TFF GENES AND PROTEINS IN BREAST TUMORS

SUMMARY – The objective of this study was to determine differential expression of TFF1, TFF2 and TFF3 genes and proteins in breast tumor subtypes. In addition, we investigated the correlation between TFF genes within tumor subgroups, and TFF genes with clinical and pathologic characteristics of the tumor. Study group included 122 patients with surgically removed breast tumors. Samples were investigated using qRT-PCR and immunohistochemistry. TFF1 and TFF3 genes and proteins were expressed in breast tumors, while the levels of TFF2 gene and protein expression were very low or undetectable. TFF1 was significantly more expressed in benign tumors, while TFF3 was more expressed in malignant tumors. Gene and protein expression of both TFF1 and TFF3 was greater in lymph node-negative tumors, hormone positive tumors, tumors with moderate levels of Ki67 expression, and in grade II tumors. A strong positive correlation was found between TFF1 and TFF3 genes, and the expression of both negatively correlated with Ki67 and the level of tumor histologic differentiation. Our results suggest that TFF1 and TFF3, but not TFF2, may have a role in breast tumor pathogenesis and could be used in the assessment of tumor differentiation and malignancy.
Crowdsourcing-Based Magnetic Map Generation for Indoor Localization

We propose an automatic map construction algorithm that assembles many users' trajectories to a FingerPrinting (FP) map of an indoor environment. Our crowdsourcing approach uses only the inertial sensors of mobile devices, neither dedicated infrastructure nor floor plan information is required. We identify overlapping segments of the trajectories, which are obtained by a simple pedestrian dead reckoning algorithm, by clustering magnetic and heading features. These clusters are used as landmarks in a novel geometric map construction process. Finally, the FP map is derived from the geometric map by exploiting the recorded sensor data of the individual trajectories. Initial results of recordings in a typical office environment show that the algorithm is able to construct a magnetic FP map which closely matches a manually generated magnetic map.
A Meta-Analysis of Context Integration Deficits Across the Schizotypy Spectrum Using AX-CPT and DPX Tasks

Schizotypy and schizophrenia involve disrupted context integration (CI), the ability to assimilate internal and external information into coherent mental representations. Research has primarily examined patients with schizophrenia, with fewer studies assessing CI in schizotypy-spectrum groups. The literature shows overall CI deficits, but mixed results for specific performance patterns and associations with clinical symptoms. Furthermore, conclusions are limited by small samples and heterogeneity across studies. To examine CI deficits across the schizotypy spectrum using AX-Continuous Performance Task (CPT) and Dot Pattern Expectancy task (DPX) performance. Systematic review involved searching 4 databases and 12 journals, examining key references, and contacting 227 researchers for published and unpublished data. Search terms included AX-CPT/DPX/dot pattern expectancy task/CNTRACs/context* integration/context* processing and schizo*/prodromal/high risk/psychosis; context* and ultra high risk. Independent data from studies with diagnostically or psychometrically assessed schizotypy-spectrum groups and AX-CPT/DPX tasks with 10+ trials and 60+% AX trials were included. Articles were independently coded by two authors using predefined coding schemes with good agreement. Meta-analyses pooled outcomes using random-effects models. Forty-one studies met inclusion criteria. CI impairment was present across the schizotypy spectrum. CI deficits in schizophrenia were substantial and associated with disorganized and negative symptoms. Outcomes were comparable between patients with chronic and first-episode schizophrenia. At-risk groups demonstrated moderate CI impairment. Results were robust across task parameters and there was no evidence that reporting biases grossly impacted outcomes. Findings lend support to theories suggesting that CI is a stable vulnerability factor for schizophrenia.
An Analyzer for Program Parallelization and Optimization

The article describes new facilities for program optimization and parallelization, work-in-progress modifications of previously implemented program transformations and compiler libraries, and future development of Optimizing parallelizing system (OPS) including opening its source code on GitHub. These new facilities, such as dialog-based optimization and parallelization, user-friendly program dependency visualization (which is needed for high-quality analyzers), parallel code generation for accelerators (GPUs, DSPs, FPGAs, or high performance clusters), are made possible by the fact, that OPS uses high-level intermediate representation as opposed to low-level intermediate representation used in popular compilers.
Measuring Crowd Collectiveness by Macroscopic and Microscopic Motion Consistencies

As a scene-independent descriptor of crowd motions, crowd collectiveness quantifies the degree of constituent individuals moving as a union in a crowd scene. An effective measurement on crowd collectiveness is of great importance for applications in surveillance of public safety, human dynamics, and other areas. To this end, we propose a novel framework to measure crowd collectiveness by combining macroscopic and microscopic motion consistencies and define quantitatively the global and local consistency of crowd motions. The defined global consistency represents the likelihood of pairwise individuals belonging to the same collective group, whereas the local consistency reflects the degree of conformity in a local region. Based on the proposed collectiveness measure, a new algorithm, named group mining, is proposed to detect collective groups from a crowd. We validate the effectiveness of the proposed method on several synthetic particle systems and a real-world crowd database with human-labeled collectiveness. Experimental results show that, compared with the previous approaches, our collectiveness measure is more consistent with human perception, and the collective groups detected by our group mining algorithm are more accurate and robust.
Superhero's Other Power: Motivate Students with Difficulties

Superhero's science project can be an interesting mode to change the students' attitudes that are unmotivated in studies for different reasons. In this paper we present a project called "Superhero's Science", carried out with a special group of Secondary School last year students, in "Sciences Applied to Professional Activity" subject. These scholars with learning difficulties are part of "Programs for the Improvement of the Learning and the Performance". Using the methodology of work in collaborative groups, this project was very useful to motivate these students in their science lessons. In addition, it improved their learning and their autonomy at class work, allowing them to learn how to do a research project, how to redact a paper, how to make graphs, and how to design posters.
Addressing Health-Related Misinformation on Social Media.

The ubiquitous social media landscape has created an information ecosystem populated by a cacophony of opinion, true and false information, and an unprecedented quantity of data on many topics. Policy makers and the social media industry grapple with the challenge of curbing fake news, disinformation, and hate speech; and the field of medicine is similarly confronted with the spread of false, inaccurate, or incomplete health information.1 From the discourse on the latest tobacco products, alcohol, and alternative therapies to skepticism about medical guidelines, misinformation on social media can have adverse effects on public health. For example, the social media rumors circulating during the Ebola outbreak in 2014 created hostility toward health workers, posing challenges to efforts to control the epidemic.2 Another example is the increasingly prevalent antivaccine social media posts that seemingly legitimize debate about vaccine safety and could be contributing to reductions in vaccination rates and increases in vaccine-preventable disease.3 The spread of health-related misinformation is exacerbated by information silos and echo chamber effects. Social media feeds are personally curated and tailored to individual beliefs, partisan bias, and identity. Consequently, information silos are created in which the likelihood for exchange of differing viewpoints
Input Method for Human Translators

Computer-aided translation (CAT) systems are the most popular tool for helping human translators efficiently perform language translation. To further improve the translation efficiency, there is an increasing interest in applying machine translation (MT) technology to upgrade CAT. To thoroughly integrate MT into CAT systems, in this article, we propose a novel approach: a new input method that makes full use of the knowledge adopted by MT systems, such as translation rules, decoding hypotheses, and n-best translation lists. The proposed input method contains two parts: a phrase generation model, allowing human translators to type target sentences quickly, and an n-gram prediction model, helping users choose perfect MT fragments smoothly. In addition, to tune the underlying MT system to generate the input method preferable results, we design a new evaluation metric for the MT system. The proposed input method integrates MT effectively and imperceptibly, and it is particularly suitable for many target languages with complex characters, such as Chinese and Japanese. The extensive experiments demonstrate that our method saves more than 23% in time and over 42% in keystrokes, and it also improves the translation quality by more than 5 absolute BLEU scores compared with the strong baseline, i.e., post-editing using Google Pinyin.
Efficacy of tasquinimod in men with metastatic castration-resistant prostate cancer

Background: Tasquinimod is an oral quinoline-3-carboxamide derivative for the treatment of metastatic castration-resistant prostate cancer (mCRPC). Tasquinimod has antiangiogenic, immunomodulatory, and antimetastatic properties, but it is also associated with toxicities, including skeletal pain, digestive disorders, fatigue, insomnia, and mental disorders. We aimed to perform a meta-analysis to evaluate the efficacy, safety, and long-term survival for tasquinimod in patients with mCRPC. Methods: Searches were carried out in PubMed, Embase, and the Cochrane Library. Eligible articles included randomized clinical trials (RCTs) comparing systemic or combination therapy (excluding primary or secondary androgen deprivation therapy, bone protective agents, or radionuclides) with placebo in men with mCRPC. Results: Three RCTs were selected for final evaluation. The pooled results from the 3 studies indicated that tasquinimod was associated with good radiologic progression-free survival (rPFS) in mCRPC. For adverse effects (AEs), the results of meta-analysis indicated that patients with mCRPC who received tasquinimod had obvious anemia (risk ratio (RR) 1.35, 95% confidence interval (CI) 1.06–1.73, P = . 02), back pain (RR: 1.57, 95% CI: 1.01–2.47, P = .05), pain in the extremities (RR: 1.90, 95% CI: 1.14–3.17, P = .01), insomnia (RR: 1.50, 95% CI: 1.03–2.17, P = .03), vomiting (RR: 1.52, 95% CI: 1.04–2.21, P = .03), and peripheral edema (RR: 1.52, 95% CI: 1.03–2.23, P = .03). Conclusions: Tasquinimod is associated with better rPFS in mCRPC. The toxicity of tasquinimod requires further investigation, it is not recommended for routine clinical use.
Secure Energy Efficiency for NOMA Based Cognitive Radio Networks With Nonlinear Energy Harvesting

In order to improve the spectrum efficiency and secrecy energy efficiency, in this paper, we propose a non-orthogonal multiple access (NOMA)-based secure scheme for cognitive radio networks. In the proposed scheme, the secondary users harvest energy from the radio-frequency signals to securely transmit the secondary privacy information with the NOMA technique. Unlike the conventional ideal linear energy harvesting, we employ the practical nonlinear energy harvesting model for energy harvesting. To implement the proposed scheme, the energy transmitter first broadcasts radio-frequency signals to power the secondary users. Then, the secondary users employ the NOMA technique to transmit the uplink privacy information, which is threatened by the eavesdropper. Considering two scenarios: two secondary users and more than two secondary users, we first provide comprehensive analysis of the secondary secrecy performances and derive the closed-form expressions of the secrecy outage probability for both scenarios. Following the above analysis, we develop the optimization problems to optimally allocate the time slot and the secondary transmit power such that the minimum secrecy energy efficiency is maximized under the constraints of the transmission security and reliability requirements. A two-stage algorithm is proposed to efficiently solve the above optimization problems. Numerical results are presented to verify the analysis in terms of the secrecy rate and secrecy energy efficiency.
On-Die Decoupling Capacitor Optimization for DDR IO Interface Power Rail

In the early stages of DDR memory interface design for SOCs (system on chip), the SOC designer needs to estimate the necessary amount of on-die decoupling capacitance for die floorplanning to meet power rail noise limits. Power rail noise is determined by the DDR interface current profile and the power delivery network (PDN) impedance, which is dominated by the on-die decoupling in the frequency range of interest. Using an example case of DDR4 at 3200Mb/s, this paper demonstrates an on-die decap optimization method to meet the target power rail noise. In particular, it demonstrates the interaction between the decap value and its associated ESR (effective series resistance) by solution space analysis.
A story of levels

© 2018 CEUR-WS. All rights reserved. Despite being one of the fundamental concepts of multi-level modeling - to the extent of occurring in the name of the discipline - the concept of “level” has no universally agreed upon meaning among multi-level modeling researchers. There is no consensus on what the nature of a level is nor on how levels should be used to organize modeling elements. In this paper, I aim to initiate a discussion on what the options for defining levels in multi-level modeling are and how they could be systematically characterized.
Progressive treadmill cognitive dual-task gait training on the gait ability in patients with chronic stroke

The purpose of this study was to investigate the effects of progressive treadmill cognitive dual-task training on gait performance in individuals with chronic stroke patients. Twenty-six participants with chronic hemiparesis were recruited to this study and randomly distributed into two groups: progressive treadmill cognitive dual-task gait training (PTCDG group, 13 patients), conventional treadmill gait training (CTG group, 13 patients). All patients underwent 20 sessions of treadmill gait training with a harness (5 times per week, for a total of 4 weeks). The GAITRite was used to analyze gait kinematics, and 10-m walking test (10MWT) wear used as the clinical evaluation indicators. After training, PTCDG group showed significant improvement in gait velocity, cadence, single support time, and 10MWT compared to the control group. However there was no significant difference between the groups in the stride lengths in the affected and unaffected sides. The study verified that progressive treadmill cognitive dual-task gait training had a positive influence on the gait and clinical gait index in chronic stroke patients.
Multiple paternity and number of offspring in mammals

Many cooperative social attributes are being linked to characteristics of mating systems, particularly to the rate of multiple paternity that typifies a population. Under the logic that greater offspring production by females should engender greater competition among males to mate with females, it is predicted that multiple paternity should increase with litter sizes. We tested the predicted positive association of multiple paternity and litter size with a meta-analysis of 59 species of mammals. The probability of multiple paternity and mean litter size were positively correlated, but not significantly (Zr = 0.202). Also, the mean number of sires of litters increased with mean litter size, but not significantly (Zr = 0.235). We developed a combinatorial formula for the influence of number of male mates and litter size on the probability of multiple paternity. We used Bayesian Markov chain Monte Carlo simulations to generate an expectation for the form of the relationship between the probability of multiple paternity and mean litter size. Under the assumption of random samplings of numbers of mates, the expected association of the probability of multiple paternity and mean litter sizes among species was positive, curvilinear and relatively high. However, the empirical probabilities of multiple paternities were much less than expected, suggesting that behavioural factors (such as mating-associated behaviours) or ecological characteristics (such as population density) probably limit the number of male mates for reproductive females. The probability of multiple paternity in a population is an estimate of mating patterns that does not closely reflect the number of sires of individual litters. We suggest use of the estimated probability of mating success for males as an alternative measure of their contribution to the mating system.
Aspect Detection in Book Reviews: Experimentations

Aspect Based Sentiment Analysis (ABSA) aims at identifying the aspects of entities and the sentiment expressed towards each aspect. Substantial work already exists in English language and in domains where aspects are easy to define such as restaurants, hotels, laptops, etc. This paper investigates detection of aspects in French language and in the books reviews domain where expression is more complex and aspects are less easy to characterize. On the basis of a corpus that we annotated , 21 aspects were defined and categorized into eight main classes including a catch-all class, General, which was found to be absorbent. Several methods were carried out to address this difficulty, with varying efficiency: Random Forest and SVM provided better results than kNN and Neural Net. Combining these methods with voting rules helped to improve noticeably the results. On another side, the difficulty of the task and the limits of a lexical approach were further explored with a qualitative analysis of errors and a topological mapping of the data using Self Organising Maps.
A Semantic Similarity Computing Model based on Siamese Network for Duplicate Questions Identification

Traditional semantic similarity computing methods mostly regard the text as a set of words, by calculating the number of words occurred in the text to build the feature vector, then using the metrics such as cosine distance between the vectors to calculate the text similarity. However, these methods only consider the word level of the sentence, not the semantic level, which may ignore many important information, including syntax and word order. This paper proposes a new deep learning method, which combines the attention mechanism with BiLSTM based on Siamese network to achieve the semantic similarity matching for given question pairs. Experimental results show that our models can make full use of the semantic information of the text, and the F1 value in the dataset provided by the CCKS2018 question-intention matching task is 0.84586, achieving fourth place in the final test.
COX5B and COX2 gene expressions in Multiple Sclerosis

Multiple Sclerosis (MS) is an autoimmune inflammatory disease which affects the Central Nervous System (CNS) and leads to the destruction of myelin and atrophy of the axons. Genetic factors, in addition to environmental ones, seem to play a role in MS. Numerous studies have reported mitochondrial defects including a reduction in COX complex function related to the decrease of mitochondrial gene expression in the cortex tissue of MS patients. This study aimed to assess COX5B and COX2 gene expression in MS patients and controls. By using Real-Time PCR method, expression levels of the COX5B and COX2 were determined, with reference to s-actin and GAPDH. The results showed that COX5B gene expression is significantly reduced in MS patients compared to control (P<0.05), whereas there was no significant difference in the COX2 gene expression. Thus, it can be claimed that down-regulation of mitochondrial electron transport chain genes supported the hypothesis that hypoxia-like tissue injury in MS may be due to mitochondrial gene expression impairments.
Three Dimensional Convolutional Neural Network Pruning with Regularization-Based Method

In recent years, three-dimensional convolutional neural network (3D CNN) is intensively applied in video analysis and receives good performance. However, 3D CNN leads to massive computation and storage consumption, which hinders its deployment on mobile and embedded devices. In this paper, we propose a three-dimensional regularization-based pruning method to assign different regularization parameters to different weight groups based on their importance to the network. Experiments show that the proposed method outperforms other popular methods in this area.
Survey on housing, management and welfare of dairy cattle in tie-stalls in western Italian Alps

In the Alps, the traditional breeding system for dairy cattle is based on the alternation between a free-ranging period on mountain ranges during the summer, and an indoor period in tie-stalls in the winter. Several welfare issues may arise in tie-stall housing systems. We describe the situation in 47 farms in three villages in western Italy, trying to identify possible relationships among structural and management characteristics, animal health and behaviour traits. A long duration of the grazing period, associated with frequent manure removal during the housing period, are probably key factors for limiting the occurrence of lameness. Teat trauma is more common in narrower stalls. Getting-up behaviour is unnatural in most of the visited farms. Some lack in the farmers’ knowledge of animal behaviour was noted. Some structural and management characteristics are strictly related to geographical constraints. However, circumstances permitting, some expedients may be achieved for improving welfare levels.
An Improved Chemical Reaction-Based Approach for Multiple Sequence Alignment

In bioinformatics, multiple sequence alignment (MSA) is an NP-hard problem. Nature-inspired approaches can provide an approximate solution compared to conventional approaches. In this article, the MSA problem is dealt with using chemical reaction optimization (CRO). The limitations of CRO are slow convergence and low population diversity. Therefore, the initialization process is improved by pairwise alignment technique which maintains diversity. In the performance analysis, we have taken benchmark datasets from Bali base version 2.0. The Bali score of the proposed approach is compared with those of the existing approaches such as SB-PIMA, SAGA, RBT-GA and GAPAM, HMMT. Simulation results confirm the superiority of the proposed approach over others.
Causal Learning

room that had gotten warm, but my body. Catharsis in this case does not involve the acting out of anger, the mistake of the systematic studies of anger “catharsis. ” It is rather an internal process: heat seems to metabolize the adrenaline for bodily preparation to fight. Body heat signals the internal orgasm of anger. These comments on catharsis were brief. For further discussion, see my book (1979), article, Catharsis and Other Heresies (2007), or my video on emotions, backed up by two Swedish rock stars (Scheff 2009).