Miracle-dz/UniFAR-FTUs huggingface dataset:
Adoptive Immunotherapy for Hodgkin’s Lymphoma

Adoptive transfer of tumor-specific T-cells is an attractive strategy for the treatment of patients with refractory or relapsed Hodgkin’s lymphoma. However, Hodgkin’s lymphomas possess a range of tumor-evasion mechanisms, which must be overcome before the full potential of immunotherapies can be achieved. In this article, we discuss the promise of Epstein-Barr virus-specific cytotoxic T-lymphocytes, the roles of cytokines, and other strategies for overcoming the immune-evasion mechanisms in Hodgkin’s lymphoma.
Quotients of unstable subvarieties and moduli spaces of sheaves of fixed Harder–Narasimhan type

When a reductive group G acts linearly on a complex projective scheme X, there is a stratification of X into G‐invariant locally closed subschemes, with an open stratum Xss formed by the semistable points in the sense of Mumford's geometric invariant theory which has a categorical quotient Xss→X // G. In this article, we describe a method for constructing quotients of the unstable strata. As an application, we construct moduli spaces of sheaves of fixed Harder–Narasimhan type with some extra data (an ‘n‐rigidification’) on a projective base.
Analyze the 2-Hop-Neighborhood for Efficient Broadcasting in Wireless Multi Hop Networks

The distribution of broadcast messages in wireless multi hop networks (WMHNs) with a low number of forwardings is a challenge. This paper presents the neighborhood analysis based broadcasting (NABB) protocol for efficient broadcasting in WMHNs. Every node categorizes the 2-hop-neighborhood for each new received broadcast message. Nodes do not forward a message if all nodes of the 1-hop-neighborhood (1HN) already received the broadcast message. Otherwise, a forwarding prob- ability is calculated that considers the nodes, which are able to forward the broadcast message. NABB offers a simple and a dynamic calculation of the forwarding probability. Simple NABB is stateless and dynamic NABB considers the previous behavior of the nodes. Experimental results show that the highest traffic saving is achieved when nodes recognize that there is no other node in the 1HN expecting a forwarding. Properly configured, dynamic NABB is able to reduce the number of forwardings further and keeps the receiving level at around 100%.
Relación entre el estado nutricional y el síndrome metabólico en adultos

El sindrome metabolico constituye una agrupacion de factores como son la obesidad abdominal, dislipidemia, glucemia y presion arterial elevadas, implicados en el desarrollo de la diabetes mellitus y enfermedades cardiovasculares. El estado nutricional refleja la condicion fisica en la que se encuentra un individuo, evaluado comunmente por el Indice de Masa Corporal (IMC) o Indice de Quelet. El objetivo de este estudio fue evaluar la relacion entre el estado nutricional y el sindrome metabolico en adultos de ambos sexos. Estudio transversal analitico con datos secundarios de sujetos que frecuentaron el parque de la salud del Instituto de Prevision Social (Asuncion, Paraguay) en el mes de setiembre del 2.011, realizado en 98 sujetos con rango de edad de 34 a 51 anos. La prevalencia del sindrome metabolico fue del 25,5%. En mujeres con sindrome metabolico fueron mas frecuentes los criterios de circunferencia de cintura (p<0,001) y trigliceridos (p<0,001) aumentados, en hombres el colesterol-HDL bajo (p=0,001), la glucemia (p=0,007) y presion arterial elevadas (p=0,002). El estado nutricional segun indice de masa corporal indico un mayor porcentaje de exceso de peso en hombres (89,6%). Al relacionar el estado nutricional con el sindrome metabolico, en general, la mayoria de los sujetos obesos presentaron sindrome metabolico (p<0,001); por sexo se observo que la mayoria de las mujeres tenian sobrepeso y que los hombres con obesidad presentaron un mayor porcentaje de sindrome metabolico (p=0,001). El estado nutricional y el sindrome metabolico se incrementan de manera proporcional, observandose una mayor prevalencia de sindrome metabolico en mujeres con sobrepeso y en hombres con obesidad. La prevalencia del sindrome metabolico fue del 25,5% siendo menor el sindrome metabolico premorbido (22,4%).
Determinants of Compliance With Iron and Folate Supplementation Among Pregnant Women in West Iran: A Population Based Cross-Sectional Study

Objective: To assess the compliance with iron and folate supplementation, and the possibly causally associated factors, among pregnant women in western Iran. Materials and methods: A cross-sectional study of 433 pregnant women, selected randomly amongst those (n = 8,500) attending 40 primary health care centers (PHCCs) in west Iran in 2017. A validated questionnaire was used to gather data, including demographic characteristics, the compliance with iron/folate supplementation and reasons for non-compliance. Results: The participants’ mean age and the duration of their pregnancies when commencing supplementation were (27.86 ± 5.54y [µ ± SD]) and (23.29 ± 9.86w), respectively. The compliance was 71.6% / 28% for iron, and 81.5% / 40% for folate. The commonest causes of poor compliance were forgetfulness and side-effects. Educational status, age, and history of anemia were significantly positively associated with folate compliance. The compliance with iron was associated only with the level of education. Conclusion: Although the compliance with iron and folate was relatively high, most women had not started taking the supplements regularly or at the correct time, usually due to forgetting and/or experiencing adverse side-effects.
Realtime Video Based Water Surface Approximation

This paper describes an approach for automatically producing convincing water surfaces from video data in real time. Fluids simulation has long been studied in the Computer Graphics literature, but the methods developed are expensive and require input from highly trained artists. In contrast our method is a low cost Computer Vision based solution which requires only a single video as a source. Our output consists of an animated mesh of the water surface captured together with surface velocities and texture maps from the video data. As an example of what can be done with this data, a modified form of video textures is used to create naturalistic infinite transition loops of the captured water surface. We demonstrate our approach over a wide range of inputs, including quiescent lakes, breaking sea waves, and waterfalls. All source video we use are taken from a third-party publicly available database.
Effects of Panose on Glucan Synthesis and Cellular Adherence by Streptococcus mutans

The effects of panose on glucan synthesis and sucrose‐dependent cellular adherence by Streptococcus mutans were investigated. Panose effectively inhibited glucan synthesis from sucrose by glucosyltransferases from S. mutans strain 6715, but increasing amounts of panose increased the release of fructose from sucrose by the enzymes. On the other hand, production of a series of oligosaccharides of increasing size by the enzymes was markedly enhanced in the presence of panose. These results indicate that panose activates the enzymes and that the inhibition of glucan synthesis by panose is due to the transfer of the glucosyl group of sucrose to panose. Sucrose‐dependent adherence of cells of various S. mutans strains to a glass surface was also inhibited by panose.
Production of volatile sesquiterpenes by Fusarium sambucinum strains with different abilities to synthesize trichothecenes

Twenty-five strains of Fusarium sambucinum grown on wheat kernels were examined for trichothecene production and the synthesis of volatile sesquiterpenes. The volatiles were purged with air and collected on Tenax traps. Adsorbed compounds were eluted from the traps and injected into a gas chromatograph coupled with a mass spectrometer. Ten strains isolated from potato tubers produced high amounts of diacetoxyscirpenol and its derivatives. These strains were characterized by the production of high amounts of diverse sesquiterpenes. In 10 cultures, 19 compounds were detected, of which 6 were predominant and composed as much as 82% of the volatile sesquiterpene fraction (e.g., beta-farnesene, beta-chamigrene, beta-bisabolene, alpha-farnesene, trichodiene, and an unidentified compound). Fifteen strains isolated from various sources that did not produce trichothecenes produced much less volatile sesquiterpenes, with less chemical diversity. No more than six compounds were present in cultures. Two of these compounds were present in the toxigenic strains isolated from potatoes (beta-farnesene and acoradiene), but four were unique to the strains not producing trichothecenes (longifolene, isocaryophyllene, delta-elemene, and an unidentified one). The pattern of volatile sesquiterpenes was characteristic and distinctive for both toxic and nontoxic strains.
Facial emotion recognition using a combining AAM with DBN

If we want to recognize the emotion via the face-to face interaction, first of all, we need to extract the emotional features from the facial image by using a feature extraction method. The active appearance model (AAM) is a well-known method that can represent a non-rigid object, such as face, facial expression regions as emotional features. And then we need to classify the emotional status reliably, robustly. Bayesian Network is a probability based classifier that can represent the probabilistic relationships between sets of facial features. So, in this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with Facial Action Coding System (FACS) for automatically modeling and extracting the facial emotional features. To recognize the facial expression, we use the Dynamic Bayesian Networks (DBNs) for modeling and understanding the temporal phases of facial expressions in image sequences.
Réduction des risques de catastrophes naturellesImpact des phénomènes de météorologie spatiale sur la gestion des tremblements de terre

108 REE N°5/2014 QUELQUES APPROCHES INNOVANTES DANS LA PREVENTION ET LA GESTION DES RISQUES DOSSIER 2 Introduction La necessite de prendre des mesures pour limiter les risques associes aux ca- tastrophes (Disaster Risk Reduction), et en particulier aux catastrophes natu- relles (inondations, activites volcaniques, seismes, ouragans, tsunamis etc.), est apparue au cours des annees 70 [1]. Si, depuis ce temps, des initiatives sont re- gulierement prises pour renforcer les sys- temes d'alertes, mettre rapidement en place les cellules de crise, les equipes de sauvetage, la restauration des systemes de communication affectes par ces ca- tastrophes, etc. il reste indispensable de veiller a l'amelioration de nos connais- sances des facteurs de reduction des risques afin de diminuer a la fois le nombre de pertes humaines et le cout des pertes economiques. Dans son rapport 2013 [2], l’United Nations Office for Disaster Reduction (UNISDR), met l'accent sur deux fac- teurs de reduction des risques : (I) l'identification et l'analyse des causes de catastrophes, et (II) la necessite d'inte- grer la science aussi bien dans l'elabora- tion des politiques a suivre que d
HYPERTENSION 2020: CONFRONTING TOMORROW'S PROBLEM TODAY

1. In developed countries, the major burden of disease is due to chronic diseases, such as heart disease and stroke. In contrast, the major burden of disease among people in developing countries has been due largely to diseases caused by malnutrition, poor sanitation and infection. In recent years, with increasing economic and demographic development, there has been a shift in developing countries from diseases caused by poverty towards chronic, non‐communicable, lifestyle‐related diseases. The rapid emergence of these chronic diseases has not occurred with a similarly rapid decline in infectious diseases. Therefore, these developing countries are experiencing high rates of both infectious and chronic diseases.
A Privacy Preserving Selective Authorization Enforcement Approach in Daas

Database as a Service(DaaS) is a practical and useful paradigm, in which the Database Service Provider(DSP) hosts the delegated database generated from the Source DB of Data Owner(DO). Due to the untrusted DSP, most of the proposed approaches were concentrated on using encryption to guarantee the privacy of delegated database and using partition based index to speed up the query. However, few papers were proposed to guarantee the privacy of delegated access control policies. Therefore in order to improve the usability of delegated database and guarantee the privacy of delegated access control policies, a critical problem to be addressed in DaaS is to make the DSP enforce the delegated selective authorization policies correctly, but know nothing about the privacy of users or the privacy of delegated authorization policies. In this paper, we present a privacy preserving selective authorization enforcement approach to resolve the critical problem above. By using selective encryption, Pedersen commitment and access control policy polynomial, the privacy of delegated access control policies and the privacy of users can be efficiently guaranteed. Finally we analyze the security properties of our approach from different aspects.
Understanding the structure of terrorist networks

This paper presents the study of structural cohesion which is discussed in Social Network Analysis, but can also useful in other important application areas including investigative data mining for destabilising terrorist networks. Structural cohesion is defined as the number of actors who, if removed from a group, would disconnect it. We discuss structural cohesion concepts, such as cliques, n-cliques, n-clans and k-plexes to determine familiarity, robustness and reachability within subgroups of the 9/11 terrorist network. We also propose a methodology of detecting critical regions in covert networks; and then compare them to the topological characteristics of those networks.
Interactive cybersecurity defense training inspired by web-based learning theory

As cybersecurity has become a huge problem of today's society, the demand for cybersecurity experts is increasing. Therefore, many researchers and organizations create training environments for professionals to have hands-on activities. However, in most cases, they are created manually and only focus on features, without a pedagogic point of view. This research proposes an interactive training interface aiming to bring a better interaction inspired by the web-based learning theory. Moreover, it runs on top of a system that can setup the training environment automatically and perform unmanned cyber attacks. In this paper, we first define requirements for a modern elearning system for cybersecurity training. We then describe how a defense training system is designed and implemented in this research. After that, a comparison of the implemented interface with the theory of interaction in web-based learning is presented. Based on this theory, a survey is conducted on participants with various cybersecurity background levels to evaluate the effectiveness of the training, and what participants expect from hands-on cybersecurity defense training programs. The time for environment creation is also evaluated.
Dynamic Parameter Identification of Secondary Mass Dampers Based on Full‐Scale Tests

Abstract: For a secondary mass damper such as tuned liquid damper (TLD) or tuned liquid column damper (TLCD), whose moving mass is liquid, it is impossible to prefabricate the damper in a factory for the identification of dynamic properties. Also, it is not easy to prefabricate a concrete tuned mass damper (TMD), whose moving mass is made of concrete, in a factory. In this article, an identification method for finding dynamic properties of secondary mass dampers based on the full‐scale field test is presented. Decoupled equations of motion are derived from a coupled equation of motion of building and damper. The decoupled equations of motion are then used for system identification using the response of the damper as an input and the response of the building as an output. The proposed method is applied to numerical examples and an actual TMD and TLCD installed in buildings.
Direct power control of a DFIG-based WECS with active filter capabilities

This paper presents an integrated control strategy for a DFIG-based wind energy conversion system (WECS) with power quality enhancement capabilities. The proposed control scheme performs independent active and reactive power control of the DFIG by means of a robust direct power control (DPC) approach acting through the rotor side converter (RSC). Likewise, active filtering functionality is achieved through the grid side converter (GSC) along with a synchronous reference frame based scheme for the extraction of the compensating current components. Experimental results are presented and discussed. The implemented test rig comprises a DFIG driven by a DC motor which in turn is controlled to emulate the behavior of a wind turbine following a given wind speed profile. A back-to-back PWM-controlled power converter and C-programmed DSP control cards make-up the control system. Full control of active and reactive power is obtained and a remarkable active filtering operation is achieved even for highly unbalanced and non-linear loads.
Fuzzy multiple model tracking algorithm for manoeuvring target

This paper develops a tracking algorithm for maneuvering target based on fuzzy logic inference (FMMTA). In place of the model probability computed intricately in the IMM, filtering measurement innovations are tackled with the innovation covariance, and the results are used as the input to a fuzzy inference system to get the matched degrees for each filtering model in the model set designed. With the matched degrees, the estimation from each filtering is weighted to obtain the maneuvering target's overall estimation and its covariance. The performance of FMMTA is tested via Monte Carlo simulation, and the result expresses its validity and its promise.
A Meta-Analysis of Cohort Studies Describing Mortality and Cancer Incidence among Chemical Workers in the United States and Western Europe

We evaluated the mortality and cancer experience of employees of the chemical industry in the United States and western Europe, as reported in the peer-reviewed literature between 1966 and 1997 (>1 million workers and >15 million person-years). Cohort studies (N = 461) were grouped (N = 181) so that specific populations could be traced from the earliest to the most recently published report, and we extracted observed and expected numbers of cases for each of 35 mortality and 23 cancer incidence endpoints. We then generated standardized mortality ratios or standardized incidence ratios and 95% confidence intervals, and undertook meta-analyses of subcohorts (for example, gender, latency, or duration of employment), as well as the entire cohort. With few exceptions, the observed cause-specific mortality and site-specific cancer incidences were reassuring: overall, 10% fewer deaths were observed than expected. Fewer than expected deaths from all causes, cardiovascular disease, noncancer respiratory disease, cirrhosis of the liver, and external causes were observed, some or all of which may be attributed to a “healthy worker effect. ” Meta-analyses revealed weak to moderate excesses of lung and bladder cancers likely caused by occupational exposure to known human carcinogens. We also observed a 10–15% increase in lymphatic and hematopoietic cancers. Additional research is required to gain a more complete understanding of the potential role that methodology and environmental or occupational influences may play in these associations.
Sanitation in self-service automatic washers

The potential for microbial transfer in self-service laundry washing machines was investigated by obtaining swab samples from the interior surfaces of commercial machines and wash water samples before and after disinfectant treatment. Three disinfectants (chlorine, a quaternary ammonium product, and a phenolic disinfectant) were used. Four self-service laundry facilities were sampled, with 10 replications of the procedure for each treatment at each location. Although washers were set on a warmwater setting, the wash water temperatures ranged from 24 to 51 degrees C. The quaternary ammonium product seemed most effective, averaging a 97% microbial kill; chlorine was the second most effective, with a 58% kill, and the phenolic disinfectant was least effective, with only a 25% kill. The efficacies of the chlorine and phenolic disinfectants were reduced at low water temperatures commonly experienced in self-service laundries. Interfamily cross-contamination in self-service facilities is a potential public health problem, which is aggravated by environmental conditions, such as water temperature and the practices of the previous users of the equipment. Procedural changes in laundering are recommended, including the use of a disinfectant to maintain adequate levels of sanitation.
A novel approach to trace time-domain trajectories of power systems in multiple time scales

This work presents a novel approach for multitime-scale power system dynamic simulation based on differential and algebraic equations (DAEs). By properly selecting the continuation (local) parameter, the approach can avoid the numerical divergence encountered by a conventional approach, due to the singularity of the algebraic part of the equations. Meanwhile, by setting step size in a local parameterization, the approach varies its time step size according to the first- or second-order sensitivity of the solution to the variation of local parameter. It employs larger time step sizes for slow dynamics and smaller ones for fast dynamics. The approach presents an advanced tool to study voltage dynamics in multiple time scales and is easily adaptable for quasisteady-state analysis (QSS). The applicability of the approach to multiple time scales and QSS is demonstrated through a 39-bus New England system.
JUNLG-MSR: A Machine Learning Approach of Main Subject Reference Selection with Rule Based Improvement

The GREC-MSR task is to generate appropriate references to an entity in the context of a piece of discourse longer than a sentence. In MSR '09 run of this task, the main aim is to select the actual main subject reference (MSR) from a list of given referential expressions that is appropriate in context. We used a machine learning approach augmented with some rules to select the most appropriate referential expression. Our approach uses the training set for learning and then combines some of the rules found by observation to improve the system.
Subcortical Vascular Dementia

Vascular dementia (VaD) incorporates different vascular mechanisms and changes in the brain, and has different causes and clinical manifestations. Current criteria for VaD select an aetiologically and clinically heterogeneous group and this definitional heterogeneity has affected clinical trial results. Focus on a more homogeneous group, such as that with subcortical (ischaemic) VaD, could be an alternative in clinical drug trials. This subtype incorporates two small vessel clinical entities – ‘Binswanger’s disease’ and ‘the lacunar state’. It comprises small vessel disease as the primary vascular aetiology, lacunar infarct(s) and ischaemic white matter lesions as the primary type of brain lesions, subcortical location as the primary location of lesions, and the subcortical clinical syndrome as the primary clinical manifestation. Subcortical VaD is expected to show a more predictable clinical picture, natural history, outcome and treatment responses.