Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional foods as potential therapeutic options for metabolic syndrome

Obesity as part of metabolic syndrome is a major lifestyle disorder throughout the world. Current drug treatments for obesity produce small and usually unsustainable decreases in body weight with the risk of major adverse effects. Surgery has been the only treatment producing successful long‐term weight loss. As a different but complementary approach, lifestyle modification including the use of functional foods could produce a reliable decrease in obesity with decreased comorbidities. Functional foods may include fruits such as berries, vegetables, fibre‐enriched grains and beverages such as tea and coffee. Although health improvements continue to be reported for these functional foods in rodent studies, further evidence showing the translation of these results into humans is required. Thus, the concept that these fruits and vegetables will act as functional foods in humans to reduce obesity and thereby improve health remains intuitive and possible rather than proven.
Relationship Between Cognitive Impairments and Rated Activity Restrictions in Stroke Patients

Objective: To investigate the relationship between cognitive impairments and rated activity restrictions. Design: Comparison of neuropsychological tests and activity questionnaires. Activity ratings were made by staff and stroke patients. Setting: Two neurological rehabilitation hospitals. Participants: Eighty-seven stroke patients. Results: Moderately high correlations were found between cognitive test scores and activity ratings made by staff members. In contrast, correlations between ratings made by patients and cognitive tests were much lower. There was also little agreement between the staffs' ratings and the patients' own ratings. Multiple regression analyses indicate that cognitive impairments account for 28.9% of the variance in the activity rating made by the staff members. The coefficient of determination was slightly higher when age, time since onset of illness, and depression scores were included as predictors. Conclusions: These findings provide partial support for a hierarchical structure of the “International Classification of Impairment, Activities and Participation” model of the World Health Organization.
Water stress in global transboundary river basins: significance of upstream water use on downstream stress

Growing population and water demand have increased pressure on water resources in various parts of the globe, including many transboundary river basins. While the impacts of upstream water use on downstream water availability have been analysed in many of these international river basins, this has not been systematically done at the global scale using coherent and comparable datasets. In this study, we aim to assess the change in downstream water stress due to upstream water use in the world’s transboundary river basins. Water stress was first calculated considering only local water use of each sub-basin based on country-basin mesh, then compared with the situation when upstream water use was subtracted from downstream water availability. We found that water stress was generally already high when considering only local water use, affecting 0.95–1.44 billion people or 33%–51% of the population in transboundary river basins. After accounting for upstream water use, stress level increased by at least 1 percentage-point for 30–65 sub-basins, affecting 0.29–1.13 billion people. Altogether 288 out of 298 middle-stream and downstream sub-basin areas experienced some change in stress level. Further, we assessed whether there is a link between increased water stress due to upstream water use and the number of conflictive and cooperative events in the transboundary river basins, as captured by two prominent databases. No direct relationship was found. This supports the argument that conflicts and cooperation events originate from a combination of different drivers, among which upstream-induced water stress may play a role. Our findings contribute to better understanding of upstream–downstream dynamics in water stress to help address water allocation problems.
Local Costimulation Reinvigorates Tumor-Specific Cytolytic T Lymphocytes for Experimental Therapy in Mice with Large Tumor Burdens1

Cytotoxic T cells recognize tumor Ags and destroy cancer cells in vitro. Adoptive transfer studies with transgenic T cells specific for tumor Ags have demonstrated that CTL are effective only in mice with small tumor burdens and thus appear to have limited potential in cancer immunotherapy. Here we used transgenic mice that express the TCR specific for an unmutated tumor Ag P1A and multiple lineages of P1A-expressing tumors to address this critical issue. We found that local costimulation, either by expression of B7-1 on the tumor cells or by local administration of anti-CD28 mAb 37N, reinvigorated the function of CTL specific for the tumor Ag, as it substantially increased the efficacy of CTL therapy for mice with large tumor burdens. Our study suggests that CTL-based immunotherapy can be manipulated to deal with large tumors.
Invasive pneumococcal disease among infants before and after introduction of pneumococcal conjugate vaccine.

CONTEXT Streptococcus pneumoniae is a serious infection in young infants. A heptavalent pneumococcal conjugate vaccine (PCV7) was licensed in 2000 and recommended for all children aged 2 to 23 months. OBJECTIVE To determine the rates of invasive pneumococcal disease (IPD) in young infants before and after PCV7 was incorporated into the childhood immunization schedule in June 2000. DESIGN, SETTING, AND PARTICIPANTS A prospective, population-based study of infants aged 0 to 90 days who resided in areas in 8 US states with active laboratory surveillance for invasive S pneumoniae infections from July 1, 1997, to June 30, 2004. MAIN OUTCOME MEASURES Rates of laboratory-confirmed IPD before (July 1, 1997-June 30, 2000) and after (July 1, 2001-June 30, 2004) PCV7 introduction, excluding a transition year (July 1, 2000-June 30, 2001). RESULTS There were 146 cases of IPD, 89 before and 57 after PCV7 introduction. Isolated bacteremia occurred in 94 cases (64%), pneumonia in 27 (18%), meningitis in 22 (15%), and septic arthritis and/or osteomyelitis in 3 (2%). Mean rates of IPD for infants aged 0 to 90 days decreased 40% from 11.8 (95% confidence interval [CI], 9.6-14.5) to 7.2 (95% CI, 5.6-9.4; P = .004) per 100 000 live births following PCV7 introduction. Among black infants, mean rates of IPD decreased significantly from 17.1 (95% CI, 11.9-24.6) to 5.3 (95% CI, 2.8-10.1; P = .001) per 100,000 live births, with a nonsignificant decrease from 9.6 (95% CI, 7.3-12.7) to 6.8 (95% CI, 4.9-9.4) per 100,000 live births for white infants. Rates of PCV7-serotype isolates decreased significantly from 7.3 (95% CI, 5.3-10.1) to 2.4 (95% CI, 1.6-3.8; P<.001) per 100,000 live births, while rates of non-PCV7 serotypes remained stable (P = .55). CONCLUSIONS Since PCV7 introduction, rates of IPD in young infants have decreased significantly, providing evidence that vaccinating children aged 2 to 23 months has led to changes in pneumococcal carriage in infants too young to receive PCV7. With a significant decrease in rates of IPD among black infants, the previous racial difference has been eliminated.
Diseño y elaboración de un prototipo para un sistema inteligente de prevención de accidentes de tránsito por exceso de velocidad aplicado al transporte interprovincial

En el siguiente documento se detalla el desarrollo de una herramienta de software y hardware para el monitoreo de la velocidad y ubicacion geografica aplicado al transporte interprovincial, el cual permite obtener datos que al ser analizados puedan contribuir a mitigar el indice de accidentes de transito. Siendo el exceso de velocidad el segundo causal de accidentes, se propuso como solucion un sistema de monitoreo en linea que engloba conceptos de Internet de las Cosas enfocados hoy en dia al desarrollo de Ciudades Inteligentes, permitiendo mejorar el resguardo de los usuarios que hagan uso de estos medios de transporte. El prototipo consta de sensores que monitorean la velocidad (km/h), la posicion geografica y el estado de la puerta (abierta/cerrada). Todos estos datos son enviados a la plataforma web para luego ser procesados y de esta manera bajo un analisis tomar futuras decisiones correctivas con el fin de combatir este problema. Todo esto se despliega sobre un escenario real sobre el que se realizaron las pruebas.
A Brief Introduction to the Basics of Game Theory

Game theory is a set of mathematical tools that are used to represent and study social interactions. This is a very brief (and not comprehensive) introduction to some of the basic ideas of game theory. In many ways, game theory is an extension of decision theory which is the study of rational choice when we are faced with uncertainty. For this reason, some of the basic concepts from decision theory (e.g. probability and utility) are important for understanding the basics of game theory. The first section covers some central ideas from decision theory and the discussion of game theory begins in section two.
Microendodontie guidée : étude de faisabilité montrant l'économie tissulaire potentielle sur les cavités d'accès des incisives calcifiées

Introduction : la gestion des calcifications pulpaires est un challenge en endodontie. La microendodontie guidee pourrait ameliorer le succes de ces therapeutiques. Le but de cette etude de faisabilite ex-vivo est d'evaluer la perte tissulaire des trepanations au cours de microendodonties guidees sur dents a endodonte calcifie. Materiel et methodes : un simulateur d'arcade est realise avec l'incorporation de dents a pulpe calcifiee. Une planification endodontique, a l'image d'une planification implantaire, est realisee. Un guide est dessine puis imprime, une douille lui est incorporee. Les trepanations guidees sont realisees dans un simulateur clinique. Des radiographies de controle post-operatoire sont realisees. Resultats : le succes de permeabilisation canalaire sans complication est de 75%. Apres gestion des complications, aucune dent ne s'avere perdue. Discussion : cette therapeutique semble prometteuse mais doit etre encore etudiee et amelioree.
Ultrasonido en el procesamiento (homogenización, extracción y secado) de alimentos

En los ultimos anos el uso del ultrasonido en el procesamiento de los alimentos se ha incrementado debido a las ventajas que presenta sobre los procesos convencionales por la reduccion de tiempos y temperatura, mezclado efectivo, aumento de la transferencia de masa y energia, la reduccion de los gradientes termicos y de concentracion, extraccion selectiva, una respuesta mas rapida al control de procesos de extraccion, aumento de la tasa de produccion, eliminacion de microorganismos y enzimas sin destruir los nutrientes de los alimentos. Ademas, de considerarse una tecnologia limpia, aplicable en las diferentes fases del procesamiento de alimentos como: secado, homogeneizacion y extraccion. El ultrasonido de baja potencia (alta frecuencia) se utiliza para el seguimiento de la composicion y propiedades fisicoquimicas de los componentes del alimento y el de alta potencia (baja frecuencia) induce cambios mecanicos, fisicos quimicos y bioquimicos por accion de la cavitacion, que soporta muchas operaciones de procesamiento de alimentos. Esta revision resume la aplicacion del ultrasonido en el procesamiento de homogenizacion, extraccion y secado en alimentos, con el fin de conocer los aspectos generales: definicion, mecanismos, efectos; aplicaciones y futuras tendencias de aplicacion en la industria alimentaria.
Petri Net Modeling Dynamic Context of Ambient Systems

An ambient System is a network of tools and equipment that interacts to fulfill someone needs. This equipment should respect the context in which they act. In order to correctly fulfill their functions, we need to specify these contexts. In this paper, we propose a new approach that allows 1) to model the ambient systems as a multi agent systems, and 2) to model both local context of each component and the global context of the ambient systems. The context is modeled using petri nets to formally verify and validate the system operations.
Distinctive effects of arachidonic acid and docosahexaenoic acid on neural stem/progenitor cells

Arachidonic acid (ARA) and docosahexaenoic acid (DHA), which are the dominant polyunsaturated fatty acids in the brain, have crucial roles in brain development and function. Recent studies have shown that ARA and DHA promote postnatal neurogenesis. However, the direct effects of ARA on neural stem/progenitor cells (NSPCs) and the effects of ARA and DHA on NSPCs at the neurogenic and subsequent gliogenic stages are still unknown. Here, we analyzed the effects of ARA and DHA on neurogenesis, specifically maintenance and differentiation, using neurosphere assays. We confirmed that primary neurospheres are neurogenic NSPCs and that tertiary neurospheres are gliogenic NSPCs. Regarding the effects of ARA and DHA on neurogenic NSPCs, ARA and DHA increased the number of neurospheres, whereas neither ARA nor DHA had a detectable effect on NSPCs in the differentiation condition. In gliogenic NSPCs, DHA increased the number of neurospheres, whereas ARA had no such effect. In contrast, ARA increased the number of astrocytes, whereas DHA increased the number of neurons in the differentiation condition. These results suggest that ARA promotes the maintenance of neurogenic NSPCs and might induce the glial differentiation of gliogenic NSPCs and that DHA promotes the maintenance of both neurogenic and gliogenic NSPCs and might lead to the neuronal differentiation of gliogenic NSPCs.
Weighted Local Naive Bayes Link Prediction

Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model—local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.
A Covariate Shift Minimisation Method to Alleviate Non-stationarity Effects for an Adaptive Brain-Computer Interface

The non-stationary nature of the electroencephalogram (EEG) poses a major challenge for the successful operation of a brain-computer interface (BCI) when deployed over multiple sessions. The changes between the early training measurements and the proceeding multiple sessions can originate as a result of alterations in the subject's brain process, new cortical activities, change of recording conditions and/or change of operation strategies by the subject. These differences and alterations over multiple sessions cause deterioration in BCI system performance if periodic or continuous adaptation to the signal processing is not carried out. In this work, the covariate shift is analyzed over multiple sessions to determine the non-stationarity effects and an unsupervised adaptation approach is employed to account for the degrading effects this might have on performance. To improve the system's online performance, we propose a covariate shift minimization (CSM) method, which takes into account the distribution shift in the feature set domain to reduce the feature set overlap and unbalance for different classes. The analysis and the results demonstrate the importance of CSM, as this method not only improves the accuracy of the system, but also reduces the classification unbalance for different classes by a significant amount.
Étude théorique et numérique de tissus biologiques en hyperélasticité anisotrope

Pour determiner les deformations et les contraintes au sein de tissus biologiques tels que les ligaments, les tendons ou les parois arterielles, les lois de comportements hyperelastiques anisotropes sont souvent utilisees dans le cadre de la methode des elements finis. Dans cet article, on se propose de realiser une telle etude en parallele avec une analyse theorique portant sur l'angle entre les fibres de collagene et la direction circonferentielle. En particulier, l'importance d'un angle critique egal a 54.73° est discutee.
Uma abordagem computacional para identificação de indício de preconceito em textos baseada em análise de sentimentos

There is a growing interest in detecting abusive language, hate speech, cyber bullying in recent years. Web sites and social networks have also been under increasing pressure to address these issues. Hate speech is usually defined as any communication that disparages a person or group based on some characteristics, such as race, color, ethnicity, gender, sexual orientation, nationality, religion, or other characteristic. In the area of Artificial Intelligence, text mining can be defined as a set of techniques and processes for discovering innovative knowledge from textual data. Among the text mining techniques is Sentiment Analysis, or also known as opinion mining, act with the study of opinions, feelings, evaluations, attitudes and emotions of people in relation to entities such as products, services, organizations, individuals, problems. This paper proposes a possible solution for the discovery of evidence of prejudice in texts in Brazilian Portuguese, where a hybrid approach was developed combining approaches based on machine learning and lexical dictionaries. In addition, the approach was used in a pilot study to identify biased comments in essays.
SEROTONIN‐LSD INTERACTIONS

About 5 years ago various workers in my laboratory started to look for drugs that would antagonize the actions of 5-hydroxytryptamine (5-HT, enteramine, serotonin). Many indole compounds depressed the responses of plain muscles, but this effect was generally unspecific, since the effects of other stimulant drugs were also depressed. The action of 5-HT on the rat’s uterus was depressed by gamine, however, and this effect was specific because the action of acetylcholine was not depressed, so that this organ was chosen for screening tests. Tests were made with a long series of indole compounds, some of which were very active, and it was eventually found that LSD was more active than any of our synthetic compounds and more active than any of the other ergot derivatives with which we had been working (Fingl and Gaddum, 1953; Gaddum, 1953). It had some effect in a concentration of lW9, and a given dose of LSD antagonized 20 times its own weight of 5-HT. The effect was specific, since the effects of oxytocin and acetylcholine were not depressed by these concentrations. Since we already knew that 5-HT was normally present in the brain, this result immediately suggested that the effects of LSD on the brain might be due to interference with the actions of this physiological 5-HT, but it has been difficult to find evidence for or against this theory, and little has been said about it (Gaddum, 1954; Woolley and Shaw, 1954). In the hands of Hameed the rat’s uterus gave very regular results (Gaddum and Hameed, 1954; Gaddum, Hameed, Hathway, and Stephens, 1954), and when the effects were measured and plotted, smooth curves could be drawn showing the relation between the effect and the log dose. When LSD was present in the bath the effects diminished, and the dose of 5-HT was increased. By comparing the effects of these larger doses with the original curves, estimates were made of the dose ratio, which is equal to the ratio between the dose that causes a given effect in the presence of the antagonist and the dose that caused the same effect in the absence of the antagonist. This provided a satisfactory method of measuring the effect of an antagonist and allowed us to show that the effect of LSD, in a concentration of 10-8, continued to increase for a t least 45 minutes, during which the dose ratio rose to about 50. The effects of low concentrations of LSD could always be surmounted by increasing the dose of 5-HT in this way, and reversed by washing the muscle with drug-free solutions. The effects of higher concentrations, however, were insurmountable (in the sense that enormous amounts of 5-HT still had no effect) and irreversible. The tryptamine receptors appeared to have been completely destroyed by these high concentrations. Ergometrine is also an active antagonist, although earlier experiments failed to detect this effect. Various other ergot alkaloids are also active-more active as antagonists of 5-HT than as antagonists of adrenaline. Dibenamine is a very active antagonist of 5-HT on this tissue.
Using Data-Driven Subword Units in Language Model of Highly Inflective Slovenian Language

This paper presents the results of a study on modeling the highly inflective Slovenian language. We focus on creating a language model for a large vocabulary speech recognition system. A new data-driven method is proposed for the induction of inflectional morphology into language modeling. The research focus is on data sparsity, which results from the complex morphology of the language. The idea of using subword units is examined. An attempt is made to figure out the segmentation of words into two subword units: stems and endings. No prior knowledge of the language is used. The subword units should fit into the frameworks of the probabilistic language models. A morphologically correct decomposition of words is not being sought, but searching for a decomposition which yields the minimum entropy of the training corpus. This entropy is approximated by using N-gram models. Despite some seemingly over-simplified assumption, the subword models improve the applicability of the language models for a sparse training corpus. The experiments were performed using the VECER newswire text corpus as a training corpus. The test set was taken from the SNABI speech database, because the final models were evaluated in speech recognition experiments on SNABI speech database. Two different subword-based models are proposed and examined experimentally. The experiments demonstrate that subword-based models, which considerably reduce OOV rate, improve speech recognition WER when compared with standard word-based models, even though they increase test set perplexity. Subword-based models with improved perplexity, but which reduce the OOV rate much less than the previous ones, do not improve speech recognition results.