Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic Relations in a Categorical Verbal Fluency Test: An Exploratory Investigation in Mild Cognitive Impairment

Categorical verbal fluency tests (CFT) are commonly used to assess the integrity of semantic memory in individuals with brain damage. Persons with Dementia of the Alzheimer’s Type display a reduced output on CFT, and a similar pattern has been reported in persons with amnesic Mild Cognitive Impairment (aMCI). The aims of the present study were to assess whether the semantic relations between lexical entries produced on a categorical fluency test were different between healthy persons and those with aMCI, and whether this difference was more pronounced in individuals who converted to dementia during a 3-year follow-up period. Methods We recruited 34 individuals with aMCI and 29 matched healthy persons. During the follow-up period, 10 individuals converted to Dementia (aMCI-conv). Two measures assessing semantic relations between consecutively produced word pairs (Path length and Extended Gloss Overlap) were obtained from the Wordnet database. Results The number of word pairs analyzed among the healthy participants (HP) and persons with aMCI were 498 (birds: 262; pieces of furniture: 236) and 395 (birds: 174; pieces of furniture: 221), respectively. Path length was lower in aMCI-conv than in HP (p = 0.035), but no differences were found between stable aMCI and HP, and between aMCI-stable and aMCI-conv. The ANOVA for lexical entries belonging to the “birds” category showed a significant effect of group (F = 5.630; p = 0.004); the post hoc analysis showed a significant difference between HP and aMCI-conv (p = 0.003). The “pieces of furniture” category was significantly affected by group (F = 4.107; p = 0.017); the post hoc test showed significant differences between aMCI-conv and healthy individuals (p = 0.049), and between aMCI-conv and stable aMCI (p = 0.001). Discussion Individuals with aMCI who convert to dementia show a deterioration in the semantic relations between lexical entries, produced on a CFT. This phenomenon may be interpreted as a marker of a very early disruption of semantic memory.
Principles of Neurorehabilitation After Stroke Based on Motor Learning and Brain Plasticity Mechanisms

What are the principles underlying effective neurorehabilitation? The aim of neurorehabilitation is to exploit interventions based on human and animal studies about learning and adaptation, as well as to show that the activation of experience-dependent neuronal plasticity augments functional recovery after stroke. Instead of teaching compensatory strategies that do not reduce impairment but allow the patient to return home as soon as possible, functional recovery might be more sustainable as it ensures a long-term reduction in impairment and an improvement in quality of life. At the same time, neurorehabilitation permits the scientific community to collect valuable data, which allows inferring about the principles of brain organization. Hence neuroscience sheds light on the mechanisms of learning new functions or relearning lost ones. However, current rehabilitation methods lack the exact operationalization of evidence gained from skill learning literature, leading to an urgent need to bridge motor learning theory and present clinical work in order to identify a set of ingredients and practical applications that could guide future interventions. This work aims to unify the neuroscientific literature relevant to the recovery process and rehabilitation practice in order to provide a synthesis of the principles that constitute an effective neurorehabilitation approach. Previous attempts to achieve this goal either focused on a subset of principles or did not link clinical application to the principles of motor learning and recovery. We identified 15 principles of motor learning based on existing literature: massed practice, spaced practice, dosage, task-specific practice, goal-oriented practice, variable practice, increasing difficulty, multisensory stimulation, rhythmic cueing, explicit feedback/knowledge of results, implicit feedback/knowledge of performance, modulate effector selection, action observation/embodied practice, motor imagery, and social interaction. We comment on trials that successfully implemented these principles and report evidence from experiments with healthy individuals as well as clinical work.
The Unique Microbiome and Innate Immunity During Pregnancy

A successful pregnancy depends on not only the tolerance of the fetal immune system by the mother but also resistance against the threat of hazardous microorganisms. Infection with pathogenic microorganisms during pregnancy may lead to premature delivery, miscarriage, growth restriction, neonatal morbidity, and other adverse outcomes. Moreover, the host also has an intact immune system to avoid these adverse outcomes. It is important to note the presence of normal bacteria in the maternal reproductive tract and the principal role of the maternal-placental-fetal interaction in antimicrobial immunity. Previous studies mainly focused on maternal infection during pregnancy. However, this review summarizes the new views on the study of the maternal microbiome and expounds the innate immune defense mechanism of the maternal vagina and decidua as well as how cytotrophoblasts and syncytiotrophoblasts recognize and kill bacteria in the placenta. Fetal immune systems, thought to be weak, also exhibit an immune defense function that is indispensable for maintaining the safety of the fetus. The skin, lungs, and intestines of the fetus during pregnancy constitute the main immune barriers. These findings will provide a new understanding of the effects of normal microbial flora and how the host resists harmful microbes during pregnancy. We believe that it may also contribute to the reference on the clinical prevention and treatment of gestational infection to avoid adverse pregnancy outcomes.
A Urodynamic Comparison of Neural Targets for Transcutaneous Electrical Stimulation to Acutely Suppress Detrusor Contractions Following Spinal Cord Injury

Objectives To assess and compare the effect of transcutaneous Dorsal Genital Nerve Stimulation (DGNS), Tibial Nerve Stimulation (TNS), Sacral Nerve Stimulation (SNS), and Spinal Stimulation (SS) on Neurogenic Detrusor Overactivity (NDO) and bladder capacity in people with Spinal Cord Injuries (SCI). Materials and Methods Seven male participants with supra-sacral SCI were tested. Standard cystometry (CMG) was performed to assess bladder activity at baseline and with stimulation applied at each site. This was conducted over four separate sessions. All stimulation was monophasic, 15 Hz, 200 μS pulses and applied at maximum tolerable amplitude. Results were analysed against individual control results from within the same session. Results Dorsal Genital Nerve Stimulation increased bladder capacity by 153 ± 146 ml (p = 0.016) or 117 ± 201%. DGNS, TNS and SNS all increased the volume held following the first reflex contraction, by 161 ± 175, 46 ± 62, and 34 ± 33 ml (p = 0.016, p = 0.031, p = 0.016), respectively. SS results showed small reduction of 33 ± 26 ml (p = 0.063) from baseline bladder capacity in five participants. Maximum Detrusor Pressure before leakage was increased during TNS, by 10 ± 13 cmH2O (p = 0.031) but was unchanged during stimulation of other sites. DGNS only was able to suppress at least one detrusor contraction in five participants and reduced first peak detrusor pressure below 40 cmH2O in these 5. Continuous TNS, SNS, and SS produced non-significant changes in bladder capacity from baseline, comparable to conditional stimulation. Increase in bladder capacity correlated with stimulation amplitude for DGNS but not TNS, SNS or SS. Conclusion In this pilot study DGNS acutely suppressed detrusor contractions and increased bladder capacity whereas TNS, SNS, and SS did not. This is the first within individual comparison of surface stimulation sites for management of NDO in SCI individuals.
Multi-Perspective Hierarchical Deep-Fusion Learning Framework for Lung Nodule Classification

Lung cancer is the leading cancer type that causes mortality in both men and women. Computer-aided detection (CAD) and diagnosis systems can play a very important role for helping physicians with cancer treatments. This study proposes a hierarchical deep-fusion learning scheme in a CAD framework for the detection of nodules from computed tomography (CT) scans. In the proposed hierarchical approach, a decision is made at each level individually employing the decisions from the previous level. Further, individual decisions are computed for several perspectives of a volume of interest. This study explores three different approaches to obtain decisions in a hierarchical fashion. The first model utilizes raw images. The second model uses a single type of feature image having salient content. The last model employs multi-type feature images. All models learn the parameters by means of supervised learning. The proposed CAD frameworks are tested using lung CT scans from the LIDC/IDRI database. The experimental results showed that the proposed multi-perspective hierarchical fusion approach significantly improves the performance of the classification. The proposed hierarchical deep-fusion learning model achieved a sensitivity of 95% with only 0.4 fp/scan.
New Pedestrian Model Based on a Social Force Model with Sub-goals

This article proposes a new pedestrian model that precisely simulates the avoidance behavior so as to realize the pedestrians' walking action. For the design of the facility, the simulation is used as a means for predicting and analyzing the movement of pedestrians. However, most of the simulators focus on the flow of pedestrian but do not consider the movement of each pedestrian. As a result, conventional simulators are useful to simulate the phenomenon of macro level movement of pedestrian but are not useful to simulate the micro-level simulation. Therefore, we aim to implement the pedestrian flow simulator that enables us to observe each pedestrian behavior by using the Multi-Agent System. Research on pedestrian model began in the 1970s, but all models cannot simulate the behavior of the pedestrian individual well. Social Force Model, which is one of the typical pedestrian models, reproduces the behavior using the equation of motion by considering the mass point pedestrian. Accordingly, this model is effective in high-density state. By contrast, there is several problems in low-density state: the avoidance speed and trajectory. Hence, we propose a new model by introducing the concept of sub-goal and new force in order to solve this problem. Furthermore, the evaluation experiment shows that proposal model improves these problems.
Long Short-Term Memory-based Multi-Period Price Prediction for Portfolio Management

In this paper, we present a novel, machine learning-based approach for price prediction to portfolio construction in the context of multi-period trading. We use a combination of recurrent neural network (RNN) and a long short-term memory (LSTM) network for predicting the future prices and to perform constrained optimization on the portfolio update. Evaluation using a series of back-test on a number of datasets obtained from Shanghai Stock Exchange (SSE) and National Association of Securities Deal Automated Quotations (NASDAQ) sources show that our proposed approach outperforms the most common conventional portfolio management technique, namely Robust Median Reversion strategy, on a number of diﬀerent metrics. In back-test experiment, our proposed method oﬀers an average of 148% returns over 360 trading periods with 100 stocks, compared to 124% returns using conventional technique, over the same period and number of stocks.
Death Anxiety and Meaning of Life in the Three Groups of Nurses: Obstetrics and Gynecology and CCU Nurses and Housewives

The aim of this study is to compare the anxiety of death and the meaning of life in three groups of nurses: obstetrics and gynecology and CCU nurses and housewives. Documentary and survey methodologies were used. The purpose of this research was applied in terms of objective and used a descriptive-comparative research design. 30 nurses of CCU ward, 30 nurses in the maternity ward, as well as 30 housewives were analyzed in three groups on a scale of meaning of life and death anxiety. For data analysis, two-way ANOVA was used, and the results of the study showed that there was a significant difference between ICU nurses, maternity nurses and housewives in terms of death anxiety and meaning of life. DOI: 10.5901/mjss.2016. v7n2s2p18
Identification of key genes in non-small cell lung cancer by bioinformatics analysis

Background Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors in the world, and it has become the leading cause of death of malignant tumors. However, its mechanisms are not fully clear. The aim of this study is to investigate the key genes and explore their potential mechanisms involving in NSCLC. Methods We downloaded gene expression profiles GSE33532, GSE30219 and GSE19804 from the Gene Expression Omnibus (GEO) database and analyzed them by using GEO2R. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were used for the functional and pathway enrichment analysis. We constructed the protein-protein interaction (PPI) network by STRING and visualized it by Cytoscape. Further, we performed module analysis and centrality analysis to find the potential key genes. Finally, we carried on survival analysis of key genes by GEPIA. Results In total, we obtained 685 DEGs. Moreover, GO analysis showed that they were mainly enriched in cell adhesion, proteinaceous extracellular region, heparin binding. KEGG pathway analysis revealed that transcriptional misregulation in cancer, ECM-receptor interaction, cell cycle and p53 signaling pathway were involved in. Furthermore, PPI network was constructed including 249 nodes and 1,027 edges. Additionally, a significant module was found, which included eight candidate genes with high centrality features. Further, among the eight candidate genes, the survival of NSCLC patients with the seven high expression genes were significantly worse, including CDK1, CCNB1, CCNA2, BIRC5, CCNB2, KIAA0101 and MELK. In summary, these identified genes should play an important role in NSCLC, which can provide new insight for NSCLC research.
Clinical Electroencephalography for Anesthesiologists: Part I Background and Basic Signatures

The widely used electroencephalogram-based indices for depth-of-anesthesia monitoring assume that the same index value defines the same level of unconsciousness for all anesthetics. In contrast, we show that different anesthetics act at different molecular targets and neural circuits to produce distinct brain states that are readily visible in the electroencephalogram. We present a two-part review to educate anesthesiologists on use of the unprocessed electroencephalogram and its spectrogram to track the brain states of patients receiving anesthesia care. Here in part I, we review the biophysics of the electroencephalogram and the neurophysiology of the electroencephalogram signatures of three intravenous anesthetics: propofol, dexmedetomidine, and ketamine, and four inhaled anesthetics: sevoflurane, isoflurane, desflurane, and nitrous oxide. Later in part II, we discuss patient management using these electroencephalogram signatures. Use of these electroencephalogram signatures suggests a neurophysiologically based paradigm for brain state monitoring of patients receiving anesthesia care.
The Effectiveness of Online Course Intervention to Improve Knowledge of Antimicrobial Resistance among Dental Students, in Comparison to Reference Group Using a Randomized Controlled Trial

AIM: This study aimed to assess the effectiveness of a recognised antimicrobial resistance (AMR) online module on knowledge and perception among dental students, using a randomised controlled trial study design. METHODS: Dental students (n = 64, aged 21-25 years) in clinical years agreed to participate in this triple-blinded, parallel, randomised controlled trial. There were 34 students in the study group and 30 students in the control group. The study group participated in an online course covering information about AMR, while students in the control group received another online course about microorganisms in dentistry. Both groups were assessed three times using online questionnaires: before the intervention (T1), after the intervention (T2), and two months later (T3). Each one of T1, T2 and T3 had 22 questions. The questions were repeated each time in T1, T2, and T3 asking about AMR but with different question format, to avoid the possibility of students to memorise the answers. RESULTS: The mean (m) of correct answers for all students on T1 was 12.56, with standard deviation (SD) of 3.2. On T2, m = 14.03 and SD = 3.85, and on T3, m = 14.36 and SD = 3.71. Scores ranged from 0 to 22. The participants in the study and control groups showed significant score improvements from T1 to T2, immediately after the intervention, but there was no significant difference between T2 and T3. The study group students’ scores did not improve significantly from T1 to T3, in contrast to the control group students’ scores. More importantly, there was no significant difference in improvement from T1 to T2 when comparing the study and control groups. CONCLUSION: Online courses might not be reliable learning methods for ensuring the optimal levels of AMR knowledge that are needed by dental practitioners.
Overeducation or Undereducation, Discrimination and Wages of Young Immigrants in Denmark

The purpose of this paper is to analyse whether young immigrants to a greater extent than ethnic Danes in the same age group are overeducated or undereducated and the effect of this on the wage differential between ethnic Danes and immigrants. This is done using a decomposition method originally applied to analyse differences between men and women with regard to distribution on occupational status and wage level. The immigrants focused on in this paper are young first generation immigrants from Turkey, Pakistan and the former Yugoslavia, who came to Denmark as children in the 1970s. The analyses are based on administrative register data supported by Statistics Denmark. The analysis of the occupational distribution indicates that immigrants are not in general overeducated in the jobs they hold. On the contrary, at the top level immigrants seem to be undereducated, while at the lowest levels we found evidence of overeducation. The decomposition analysis shows that the major part of the wage gap between immigrants is explained by differences in individual characteristics. The undereducation among immigrants contributes to reduce the wage gap between young ethnic Danes and young immigrants and dominates the effect of overeducation.
Four new Caribbean Sigambra species (Annelida, Pilargidae), and clarifications of three other Sigambra species

Abstract Sigambra grubii Müller, 1858 has been reported from many different coastal environments in Brazil and the Grand Caribbean. However, more than one species was thought to be included under this species group name. After the study of several subtle and consistent differences in specimens fitting the description S. grubii, a new Grand Caribbean species is herein recognized and described as S. hernandezisp. nov. Further, the study of other Sigambra specimens prompted the examination of type specimens of S. bassi (Hartman, 1947), and of S. wassi Pettibone, 1966 to clarify some morphological features, and three other new species are recognized and newly described: S. diazisp. nov. and S. ligneroisp. nov. from the southeastern Caribbean (Venezuela), and S. olivaisp. nov. from the northwestern Caribbean (México). Morphological features are also clarified for S. grubii by comparison with specimens from the type locality, Florianópolis, Brazil, and with type specimens of S. bassi from Florida (U.S.A.), and non-type specimens of S. wassi from Virginia (USA). A key to identify all species of Sigambra is also included.
Digital transformation trends reshaping companies

Abstract Nowadays, the ubiquity of the digital technology and the transformation it brings both within the societies and economies around the globe has become a well-accepted fact. For business is no longer a matter of whether or not to incorporate technology in their daily activity, but a matter how to change their way of approaching, and doing when adapting to digital. The digital transformation has enabled the emergence of new business models, as well as many other changes when it comes to satisfying the customer’s needs and expectations, by creating opportunities for value and sustainability. The present paper highlights all these aspects, emphasizing on how businesses can think about the digital transformation to achieve the highest benefits and create competitive advantage.
Higher Education Policies and Employability of University Graduates in the EU-28

Abstract Objective: The main purpose of this research is to analyze and reveal if the recent policy measures in higher education carried in European Union member countries have had a significant impact on the labour market integration of university graduates. Methodology: We selected a set of indicators that were common in the 2015 and 2016 editions of Structural Indicators for Monitoring Education and Training Systems in Europe and could offer an image of intensity of higher education policies in relation with labour market at European level. We further used these measures to test for any significant effects of the policies on the integration of graduates in the labour market. Findings: We found significant effects of various policy measures in high education in the European countries. We estimate a positive role for factors like monitoring of completion rates, requirements for the staff to have higher education, presence of educational guidelines, and recognition of formal and informal learning for entry in higher education. Value Added: This is the first study to address the impact of high education policies carried in European countries on the integration of college graduates. The study is distinct through both the design of new measures of higher education policy in Europe as well through testing whether the intensity of policies carried for higher education has affected the employability of young graduates or not. Recommendations: The results of this empirical research allow us to make some recommendations for improving the insertion of young graduates on European labour market.
The Management of Non-Verbal Signs in Disagreements

Abstract Gesture, outlined in terms of physical activity, philosophical theory and linguistics are strongly connected in the course of human interaction. Utterances are accompanied by facial expressions, shifts of gaze, movements, posture, etc. Therefore, we support the thesis that a gestural approach to analyzing communicative events is appropriate, since non-verbal components communicate attitudes and emotions and complete the verbal interchange in numerous ways. Disagreements are especially prone to such an analysis.