Miracle-dz/UniFAR-FTUs huggingface dataset:
Defending on networks: applying game theory to prevent illegal activities in structured security domains

The past decade witnesses the success of applying game theory to address security issues in domains such as protecting critical infrastructure and wildlife. However, the structured security domains such as interdicting illegal smuggling on networks, combating oil siphoning in international waters and preventing cyber attacks in cyber space are not well investigated. There are many critical challenges in these scenarios such as the scalability of the algorithm to solve realistic-sized problems, the long-term planning ability of the smugglers and the self-interested interdependent behaviors of users in cyber spaces. The previous works cannot be directly applied to solve these problems. Therefore, in this thesis, we provide models and solution approaches to several significant structured security domains. First, we focus on preventing nuclear smuggling on container shipping networks through efficient container inspection. To stop the nuclear smuggling through container shipping networks, the U.S. government launched several initiatives to deploy advanced devices and inspection facilities in ports around the world. However, it is a significant challenge for the government to efficiently allocate the limited inspection resources to combat the nuclear smuggling activities due to the large volume of the containers imported to the U.S. To address this problem, we propose a novel Container Inspection Model (CIM) based on Stackelberg game where the inspector determines her strategy first and the smuggler follows a Markov Decision Process (MDP) to determine his strategy after observing the inspector’s strategy. Several important contributions are made to solve this problem including: i) a linear relaxation approximation which reformulates the problem into a bilinear optimization problem, ii) an algorithm based on the Multipleparametric Disaggregation Technique (MDT) to solve the bilinear program, and iii)
Promoting Military Cultural Competence among Civilian Care Providers: Learning through Program Development

Military veterans and their families belong to a unique subculture. Several studies have identified the need for helping professionals to attain military cultural competence in order to practice more effectively. In order to address this need, a Midwestern state created a military culture certificate program (MCCP). The process of developing this program is described. Eighty-two participants of the MCCP completed a pretest survey assessing their knowledge, awareness, and self-confidence in working with this population. The majority of the participants had experience working with this population already, and their survey scores indicated moderate knowledge and moderate to high levels of overall self-efficacy. Pre-test scores indicated ten areas (six in knowledge and four in self-efficacy) that may deserve increased focus for programs and trainings on military culture. While the MCCP appeared to be generally effective, findings suggest that convenient adjunctive methods of obtaining information to enhance military cultural competence would also be helpful.
Generalized dynamics on the penetration of two phase fuel spray using differential transform method

The penetration of fuel spray as a result of the mixture of fuel droplet and entrained air usually generate nonlinear models whose solutions are normally difficult to realize analytically. This present study presents general approximate analytical solution to such problem by employing Differential transform Method (DTM). At the level of two-phase flow, the spray droplets and the entrained air have the same flow velocity. In order to fully understand the process, the parameters present in the governing equations are carefully studied. The obtained solution employing DTM is verified with Numerical Runge-Kutta (RKF45) and also compared with similar past works. Furthermore, the acquired results for different ambient densities and injection velocities are depicted and discussed. The results illustrate that continuous increase in the initial velocity and orifice diameter cause a corresponding increase in spray penetration while an antonymous effect is noticed for an increased semi cone angle and density. This work will find vital applications in the optimization of systems whose operation are influence by the aforementioned spray penetration processes.
Owner-Manager Competencies and Performance of the Firms: Evidence from Small Restaurant Businesses in Urban Tanzania

This study was set out to examine the influence of owner- manager’s competences on the performance of small restaurant businesses in urban Tanzania since there are patchy empirical evidences on the same. To achieve this, criterion and simple random sampling techniques were employed to obtain a sample of three hundred, ninety two (392) small restaurant businesses from the list of all licensed small restaurants in Ilala and Dodoma district. Information was collected from owner-managers of these entities by using structured questionnaires. Data was analyzed both descriptively and by using structural equation modelling for making inference. Confirmatory Factor Analysis was performed to validate the items measuring the owner-manager entrepreneurial, managerial and functional competencies as latent variables. Performance of small restaurant was measured subjectively by considering the number of customer’s dynamics and changes in lifestyle of the owner-manager as a result of the business undertaken over past three years of operation. It was found that owner-manager’s managerial and functional competencies contribute significantly to the performance of the small restaurant businesses in urban Tanzania. This is true but they cannot be in operation unless entrepreneurial competencies are in place. This implies that, performance relies on base (entrepreneurial) and operational (managerial and functional) that need to be improved. As such, policy makers may not only rely on entrepreneurial aspects but also extend to the managerial and functional aspects of performance.
Dynamic Task Offloading and Resource Allocation for Mobile-Edge Computing in Dense Cloud RAN

With the unprecedented development of smart mobile devices (SMDs), e.g., Internet-of-Things devices and smartphones, various computation-intensive applications are explosively increasing in ultradense networks (UDNs). Mobile-edge computing (MEC) has emerged as a key technology to alleviate the computation workloads of SMDs and decrease service latency for computation-intensive applications. With the benefits of network function virtualization, MEC can be integrated with the cloud radio access network (C-RAN) in UDNs for computation and communication cooperation. However, with stochastic computation task arrivals and time-varying channel states, it is challenging to offload computation tasks online with energy-efficient computation and radio resource management. In this article, we investigate the task offloading and resource allocation problem in MEC-enabled dense C-RAN, aiming at optimizing network energy efficiency. A stochastic mixed-integer nonlinear programming problem is formulated to jointly optimize the task offloading decision, elastic computation resource scheduling, and radio resource allocation. To tackle the problem, the Lyapunov optimization theory is introduced to decompose the original problem into four individual subproblems which are solved by convex decomposition methods and matching game. We theoretically analyze the tradeoff between energy efficiency and service delay. Extensive simulations evaluate the impacts of system parameters on both energy efficiency and service delay. The simulation results also validate the superiority of the proposed task offloading and resource allocation scheme in dense C-RAN.
Contrast-to-noise ratio and lesion-to-liver contrast of low dose and fused images acquisitions with dual-energy CT of hypervascuar liver lesions in patients with HCC

Poster: "ECR 2013 / C-2270 / Contrast-to-noise ratio and lesion-to-liver contrast of low dose and fused images acquisitions with dual-energy CT of hypervascuar liver lesions in patients with HCC" by: "L. Berta1, L. Mascaro2, L. Facchetti2, R. Cuomo2, E. Botturi2, R. Maroldi2; 1Milan/IT, 2Brescia/IT"
Realistic anatomically detailed open-source spinal cord stimulation (RADO-SCS) model

Objective. Computational current flow models of spinal cord stimulation (SCS) are widely used in device development, clinical trial design, and patient programming. Proprietary models of varied sophistication have been developed. An open-source model with state-of-the-art precision would serve as a standard for SCS simulation. Approach. We developed a sophisticated SCS modeling platform, named Realistic Anatomically Detailed Open-Source Spinal Cord Stimulation (RADO-SCS) model. This platform consists of realistic and detailed spinal cord and ancillary tissues anatomy derived based on prior imaging and cadaveric studies. In our finite element model of the T9-T11 spine levels, we represented the following tissues: vertebrae, intervertebral disc, epidural space, epidural space vasculature, dura mater, dural sac, intraforaminal tissue, cerebrospinal fluid (CSF), whitematter, spinal cord vasculature, Lissauer’s tract, gray matter, dorsal and ventral roots and rootlets, dorsal root ganglion (DRG), sympathetic chain (trunk and ganglion), thoracic aorta and its branching, peripheral vasculature, and soft tissues (thorax). As an exemplary application to illustrate the model workflow, we simulated a bipolar SCS montage and calculated the corresponding activation thresholds for individual axons populating the spinal cord. Main results. RADO-SCS provides state-of-the-art precision across 19 tissue compartments. The resulting model calculations of the electric fields generated in the white-matter and gray matter, and the axonal activation thresholds are broadly consistent with prior simulations. Significance. The RADO-SCS can be used to simulate any SCS approach with both unprecedented resolution (precision) and transparency (reproducibility). Freely-available online, the RADO-SCS will be updated continuously with version control.
SmartGov: architecture générique pour la co-construction de politiques urbaines basée sur l'apprentissage par renforcement multi-agent. (Generic architecture for urban policies co-construction using multi-agent reinforcement learning)

Dans cette these, nous proposons un outil SmartGov, mixant simulation multi-agents et apprentissage multi-agents par renforcement profond, pour permettre la co-construction de politiques urbaines et inscrire les acteurs de la ville dans la boucle de conception. La Smart City permet a l’outil d’integrer les donnees collectees par les capteurs presents dans la ville pour la modeliser de facon realiste. Notre premiere contribution est une architecture generique pour construire une simulation multi-agents representant la ville, et etudier l’emergence de comportement globaux avec des agents realistes capables de reagir aux decisions politiques. Grâce a une modelisation multi-niveaux, et le couplage de differentes dynamiques, le systeme apprend les specificites de l’environnement pour proposer des politiques pertinentes. Notre seconde contribution concerne l'autonomie et l'adaptation de la couche decisionnelle avec un apprentissage par renforcement multi-agents et multi-niveaux. Un ensemble d'agents, regroupes en clusters, est distribue dans le perimetre etudie pour apprendre des specificites locales sans connaissance a priori de son environnement. L’attribution d’un score de confiance et de recompenses individuelles permettent d'attenuer l'impact de la non-stationnarite sur la reutilisation d'experiences necessaire a l'apprentissage profond. Ces contributions conduisent a un systeme complet de co-construction de politiques urbaines dans le contexte de la Smart City. Nous comparons notre modele avec d'autres approches de la litterature sur une politique de tarification du stationnement urbain, afin de mettre en evidence les apports et les limites de nos contributions
High-resolution animal tracking with integration of environmental information in aquatic systems

Acquiring high resolution quantitative behavioural data underwater often involves installation of costly infrastructure, or capture and manipulation animals. Aquatic movement ecology can therefore be limited in scope of taxonomic and ecological coverage. Here we present a novel deep-learning based, multi-individual tracking approach, which incorporates Structure-from-Motion in order to determine the 3D location, body position and the visual environment of every recorded individual. The application is based on low-cost cameras and does not require the animals to be confined or handled in any way. Using this approach, single individuals, small heterospecific groups and schools of fish were tracked in freshwater and marine environments of varying complexity. Further, we established accuracy measures, resulting in positional tracking errors as low as 1.09 ± 0.47 cm (RSME) in underwater areas up to 500 m2. This cost-effective and open-source framework allows the analysis of animal behaviour in aquatic systems at an unprecedented resolution. Implementing this versatile approach, quantitative behavioural analysis can employed in a wide range of natural contexts, vastly expanding our potential for examining non-model systems and species.
Clonagem in vitro de Anredera cordifolia (Ten.) Steenis e análise de exsudados

v Índice de Figuras . vii Abreviaturas . xi 1. Introdução . 1 1.1. Contextualização do trabalho . 1 1.2. Anredera cordifolia . 2 1.2. 1. Taxonomia . 2 1.2. 2. Caracterização da espécie . 3 1.2. 3. Distribuição geográfica . 5 1.2. 4. Propriedades nutricionais e medicinais . 7 1.3. Cultura in vitro . 8 1.3. 1. Clonagem in vitro . 8 1.3. 2. Reguladores de crescimento . 9 1.3. 3. Indução e cultura de calos . 10 1.4. Pigmentos . 12 1.4. 1. Pigmentos nas plantas . 12 1.4. 2. Betalaínas . 14 1.4. 3. Biossíntese das betaínas . 16 1.4. 4. Fontes de betalaínas. 18 1.4. 5. Propriedades das betalaínas . 19 1.5. Objetivos . 20 2. Materiais e Métodos . 21
Infusing the axioms of clinical reasoning while designing clinical anatomy case vignettes teaching for novice medical students: a randomised cross over study

The clinical reasoning skills is often gained when the biomedical knowledge is broadened and deepened alongside exposure to patients. The ‘ideal’ blend of axioms of clinical reasoning and case based learning would establish the pedagogical bridges right from the first year of medical education. So this study aimed to investigate the perceived importance and efficacy of teaching clinical reasoning skills among first year medical students, as this has not previously been described. As a priori, two clinical reasoning skill sessions were conducted using clinico-anatomical case vignettes designed according to the literature regarding clinical reasoning (‘serial cue’ approach and hypothetico-deduction). Students were divided into intervention and control group and crossed over in subsequent sessions. Analysis was done by mixed method approach including measuring proof of benefit using post-test comparison, quantitative survey and qualitative analysis by nominal group discussion. Post test scores were compared using student’s t-test. Feedbacks were analysed using descriptive statistics. The results showed that post test scores were significantly higher in intervention group than the control group in both sessions (P<0.001, 0.016). A total of 66% students felt, diagnostic skills and lateral thinking abilities were improved and It helped in developing problem-solving abilities for 67% students. clinico-anatomical case vignettes helped in understanding anatomical basis of clinical conditions for 61% students. To conclude, introducing clinical reasoning has considerable effect in improving the decision making ability of the students and if incorporated right from the first year, would better prepare the students in successful transition to clinical learning environment.
Prevention and Reversal of Weight Gain Associated with Antipsychotic Treatment

There is growing concern about weight gain and related health problems associated with treatment with antipsychotic medications [1]. These medications are firstline treatments for psychotic disorders, including schizophrenia and schizoaffective disorder. Such disorders affect 1% to 2% of the general population and can be quite disabling [2]. Antipsychotic agents are also a key element in the treatment of bipolar disorders and to a lesser extent other psychiatric disorders. Psychotic disorders typically present with symptoms grouped into 5 clusters: positive symptoms (hallucinations, delusions), disorganized speech and/or behavior, negative symptoms (flat affect, alogia, avolition, social indifference), cognitive symptoms, and mood symptoms [3]. These symptoms can often interfere with work, interpersonal relationships, and self-care. All antipsychotic medications can be effective in reducing positive symptoms and disorganization; however, newer agents may uniquely improve symptoms in the other 3 clusters. In order for a medication to be maximally effective, however, it must be well accepted by the patient. Weight gain may adversely affect patients’ adherence to their medication regimens, undermining the success of pharmacologic treatment for schizophrenia [4,5]. Potential health problems related to weight gain include obesity, diabetes mellitus, hyperlipidemia, hypertension, osteoarthritis, and sleep apnea [6]. Providers must educate patients about weight gain as a potential side effect at the outset of treatment with antipsychotics, assess for changes in appetite and weight throughout treatment, teach patients the skills necessary to manage the process, and if needed, consider pharmacologic interventions. All of these interventions must take place in the larger context of treating the primary presenting psychiatric disorder. Taking modest steps to prevent and, if necessary, reverse weight gain can lead to better adherence to treatment regimens and fewer health problems, ultimately enhancing patients’ quality of life.
A systematic review of targeted social and emotional learning interventions in early childhood education and care settings

ABSTRACT A growing body of research evidence suggests universal (Tier 1) Social and Emotional Learning (SEL) interventions in early childhood education and care settings can improve children’s social and emotional development. Less is known however about the effectiveness of targeted (Tier 2) programmes for preschoolers experiencing social, emotional or behavioural challenges. A systematic literature review was conducted to examine the outcomes associated with targeted (Tier 2) SEL interventions; 19 studies were captured in the review. Findings revealed that while evidence for targeted SEL programming is still emerging, it may offer a promising early intervention approach to strengthen aspects of children’s social and behavioural functioning. Based on the evidence reviewed, the impact of targeted SEL intervention on emotional competencies could not be established. Programmes were predominately directed to preschoolers with externalizing problems and there appears to be a dearth of approaches focused on internalizing behaviour. Implications for practice and research are discussed.
Evaluation of Flight Parameters During Approach and Landing Phases by Applying Principal Component Analysis

This paper adopts an unsupervised learning technique, Principal Component Analysis (PCA) to analyze flight data. While the flight parameters for a stable approach have been established for a while, the paper reevaluates these flight parameters using PCA for a set of airports across the United States of America. Some flight parameters were found to be more sensitive to some airports. The parameters have been cross-checked with experts in the industry to better interpret their significance
Investigation of the relationship between professional maturity and hope levels with test anxiety of twelfth-grade high school students

The essential objectives of the present research was to investigate the association between the professional maturity and hope levels with test anxiety of twelfth-grade students in high schools. A total of 700 twelfth class high school students who attend eight different types of high school in Trabzon province throughout the academic year (2016-2017) was recruited for this study. Relational and causal study methods were utilised in the study. Regarding data collection, the Professional Maturity Scale (PMS), State Hope Scale (SHS) and Test Anxiety Inventory (TAI) were selected. In order to analyze the gathered data, the SPSS 23.0 program was used. The relationships between the variables were evaluated by Pearson Moments Multiplication correlation coefficient and the predictive level of the variables was examined by hierarchical regression analysis. The results reveal that the students' test anxiety levels are related to professional maturity and hope, and these variables are important factors explaining the students' test anxiety.