Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision Making under uncertainty in Dynamic Multi-stage Attacker-Defender Games

This dissertation presents efficient, on-line, convergent methods to find defense strategies against attacks in dynamic multi-stage attacker-defender games including adaptive learning. This effort culminated in four papers submitted to high quality journals and a book and they are partially published. The first paper presents a novel fictitious play approach to describe the interactions between the attackers and network administrator along a dynamic game. Multi-objective optimization methodology is used to predict the attacker's best actions at each decision node. The administrator also keeps track of the attacker's actions and updates his knowledge on the attacker's behavior and objectives after each detected attack, and uses this information to update the prediction of the attacker's future actions to find its best response strategies. The second paper proposes a Dynamic game tree based Fictitious Play (DFP) approach to describe the repeated interactive decision processes of the players. Each player considers all possibilities in future interactions with their uncertainties, which are based on learning the opponent's decision process (including risk attitude, objectives). Instead of searching the entire game tree, appropriate future time horizons are dynamically selected for both players. The administrator keeps tracking the opponent's actions, predicts the probabilities of future possible attacks, and then chooses its best moves. The third paper introduces an optimization model to maximize the deterministic equivalent of the random payoff function of a computer network administrator in defending the system against random attacks. By introducing new variables the transformed objective function becomes concave. A special optimization algorithm is developed which requires the computation of the unique solution of a single variable monotonic equation. The fourth paper, which is an invited book chapter, proposes a discrete-time stochastic control model to capture the process of finding the best current move of the defender. The defender's payoffs at each stage of the game depend on the attacker's and the defender's accumulative efforts and are considered random variables due to their uncertainty. Their certain equivalents can be approximated based on their first and second moments which is chosen as the cost functions of the dynamic system. An on-line, convergent, Scenarios based Proactive Defense (SPD) algorithm is developed based on Differential Dynamic Programming (DDP) to solve the associated optimal control problem.
Development of object detection software for a mobile robot using an AForce.Net framework

This paper presents a guideline for application development to provide image object detection capability using “Aforge.NET Framework” in conjunction with C# language. In detecting the target object, image processing techniques such as Blob Counter and HSL Color space were used to distinguish the object from the background and determine the position of the target object on the image. This application can be applied to enhance various capabilities on the mobile robot such as object detection, object following and rotation direction control of robot's camera.
Manual material handling advice and assistive devices for preventing and treating back pain in workers: a Cochrane Systematic Review

In many occupations, it is difficult to avoid imposing heavy loads on the back (eg, lifting and moving patients in healthcare). Therefore, it is not surprising that emphasis has been given to optimising lifting techniques and ways to manually handle patients and objects to prevent back pain and injuries. More skilled workers are supposed to cope better with adverse ergonomic conditions, resulting in less strain on the back, less back pain and consequently, less back pain-related disability. This has led to a strong belief that it is useful to advise employees or organise training for them on correct manual material handling (MMH) techniques and to provide them with assistive devices. Therefore, we wanted to determine the effectiveness of MMH advice and training and the provision of assistive devices in preventing and treating back pain. We have updated the previous version of the systematic review with a new search, new studies and improved methods.1 2 We searched CENTRAL ( The Cochrane Library 2011, issue 1), MEDLINE, EMBASE, CINAHL, Nioshtic, CISdoc, Science Citation Index and PsychLIT to February 2011. We included randomised controlled trials (RCT) and, because we thought it would be difficult to find RCTs, cohort studies with a …
Contribution à la radiothérapie adaptative par analyse systématique de la fluence en entrée et de la dose en sortie du patient

La radiotherapie moderne combine les techniques complexes et les traitements personnalises, avec le risque que certaines evolutions et erreurs ayant lieu au cours de traitement passent inapercues. Ces aleas peuvent entrainer des consequences graves pour la sante du patient. Dans cette perspective, nous avons etudie le potentiel d'un systeme de dosimetrie in vivo de transit pour le suivi continu du patient et, par consequent, la radiotherapie adaptative. L'experience clinique et des tests de faisabilite ont permis de definir les axes de travail principaux: l'automatisation et la simplification du procede d'analyse des controles. Les developpements incluent la creation d'une bibliotheque de donnees standard et une serie d'analyses de causes racines, permettant ainsi de renforcer la precision du systeme, d'ameliorer l'automatisation de sa mise en place et d'identifier des pistes pour une analyse efficace des resultats et pour la creation d'outils supplementaires facilitant le suivi et l'adaptation du traitement en routine clinique.
Capsaicin‐induced neurogenic inflammation in the skin in patients with symptoms induced by odorous chemicals

Background: Intradermal injection of capsaicin induces the axonal release of neuropeptides, vasodilatation and flare, e.g. neurogenic inflammation. The spatial profile of neurogenic inflammation in the skin has been studied in various experimental models. Polarization spectroscopy imaging introduced recently may be used for the quantitative assessment of the temporal profile of neurogenic inflammation expressed as erythema intensity.
European Collaboration on Low-dose Aspirin in Polycythemia Vera (ECLAP): A Randomized Trial

Thrombotic complications characterize the clinical course of polycythemia vera (PV) and represent the main cause of morbidity and mortality. However, uncertainty still exists as to the benefit/risk ratio of aspirin prophylaxis in this setting. In vivo platelet biosynthesis of thromboxane A2 is enhanced and can be suppressed by low-dose aspirin in PV, thus providing a rationale for assessing the efficacy and safety of a low-dose aspirin regimen in these patients. The Gruppo Italiano Studio Policitemia Vera has recently performed a pilot study on 112 patients randomized to receive aspirin, 40 mg daily, or placebo and followed for 16 +/- 6 months (mean +/- SD). This study showed that low-dose aspirin is well tolerated in PV patients, and that a large-scale efficacy trial is feasible in this setting. In this article we report the protocol of the European Collaboration on Low-dose Aspirin in Polycythemia Vera (ECLAP) study, which is a randomized trial designed to assess the risk/benefit ratio of low-dose aspirin in PV. To estimate the size and the follow-up duration required for the ECLAP trial, a retrospective analysis of the clinical epidemiology of a large PV population has recently been completed by the Gruppo Italiano Studio Policitemia Vera. On this basis, approximately 3500 patients will be enrolled in the ECLAP study with a follow-up of 3 to 4 years. The uncertainty principle will be used as the main eligibility criterion: Polycythemic patients of any age, having no clear indication for or contraindication to aspirin treatment, will be randomized in a double-blind fashion to receive oral aspirin (100 mg daily) or placebo. According to current therapeutic recommendations, the basic treatment of randomized patients should be aimed at maintaining the hematocrit value < or = 45% in subjects aged < or = 50, and hematocrit < 45% as well as platelet count < 400 x 10(9)/L in patients aged > 50. Randomization will be stratified by participating center. The study is funded by the European Union BIOMED 2 program.
Alpha‐motoneurons of the injured cervical spinal cord of the adult rat can reinnervate the biceps brachii muscle by regenerating axons through peripheral nerve bridges: Combined ultrastructural and retrograde axonal tracing study

Following our previous studies related to brachial plexus injury and repair, the present experimentation was designed to examine the ultrastructural features of those motoneurons of the locally injured cervical spinal cord of adult rats that were seen to regenerate into peripheral nerve (PN) bridges and to reinnervate nearby skeletal muscles. Here, the peripheral connection of the PN bridge was made with the biceps brachii (BB) muscle. Three months postsurgery, the spinal motoneurons labelled by retrograde axonal transport of horseradish peroxidase (HRP), after its injection into the BB, were selected on thick sections, using light microscopy, for the presence of dark amorphous granules of the HRP reaction product. Serial ultrathin sections were then made from the selected material. For the 10 labelled neurons studied, we examined the synaptic boutons present on the membrane of the neuronal soma. For five of them, we could observe three of the six types of synaptic boutons described for the alpha‐motoneurons of the cat (S‐type with spherical vesicles, F‐types with flattened vesicles, and C‐type with subsynaptic cistern). The largest boutons (type C) are specific to alpha‐motoneurons. In comparison to normal material, we noticed a decrease in the number of boutons and an increase in the number of glial processes. After a transient phase of trophic changes, the reinnervated BB muscles showed a return of their fibers to nearly normal diameters as well as evidence of fiber type grouping. Simultaneous staining with silver and cholinesterase also revealed the presence of new motor endplates frequently contacted by several motoneurons. The present study indicates that, after a local spinal injury, typical alpha‐motoneurons can reinnervate a skeletal muscle by regenerating axons into the permissive microenvironment provided by a PN graft. These data offer prospects for clinical reconstruction of the brachial plexus after avulsion of one or several nerve roots. J. Neurosci. Res. 64:476–486, 2001. © 2001 Wiley‐Liss, Inc.
Cellular Watersheds: A Parallel Implementation of the Watershed Transform on the CNN Universal Machine

The watershed transform has been used as a powerful morphological segmentation tool in a variety of image processing applications. This is because it gives a good segmentation result if a topographical relief and markers are suitably chosen for different type of images. This paper proposes a parallel implementation of the watershed transform on the cellular neural network (CNN) universal machine, called cellular watersheds. Owing to its fine grain architecture, the watershed transform can be parallelized using local information. Our parallel implementation is based on a simulated immersion process. To evaluate our implementation, we have experimented on the CNN universal chip, ACE16k, for synthetic and real images.
A transfer learning framework for energy efficient Wi-Fi networks and performance analysis using real data

In the recent past, there has been an exponential increase in data intensive services over the communication networks. This trend would sustain in future communication networks as well, especially in the Wi-Fi networks. This could be attributed to rapid growth of business and institutional entities and the need for cellular data off-loading for which localized Wi-Fi networks are preferred due to higher offered data rate. In such networks, a major portion of energy consumption occurs at the access network entities making energy efficient operation of Wi-Fi access points (APs) extremely crucial. In this paper, an actor-critic (AC) reinforcement learning (RL) framework is designed to enable traffic based ON/OFF switching of APs in Wi-Fi network. Furthermore, previously estimated traffic statistics is exploited in future scenarios which speeds up the learning process and provide additional improvement in energy saving. The important feature of the present study is the validation of the proposed framework on real data collected from an institute's Wi-Fi network. The simulation results for 20 APs of a Wi-Fi network shows that the proposed framework can lead to around 75% saving in energy consumption as compared to the case when AP switching is not considered.
The Benchmark Dose Method—Review of Available Models, and Recommendations for Application in Health Risk Assessment

The benchmark dose method has been proposed as an alternative to the no-observed-adverse-effect level (NOAEL) approach for assessing noncancer risks associated with hazardous compounds. The benchmark dose method is a more powerful statistical tool than the traditional NOAEL approach and represents a step in the right direction for a more accurate risk assessment. The benchmark dose method involves fitting a mathematical model to all the dose-response data within a study, and thus more biological information is incorporated in the resulting estimates of guidance values (e.g., acceptable daily intakes, ADIs). Although there is an increasing interest in the benchmark dose approach, it has not yet found its way into the regulatory toxicology in Europe, while in the United States the U.S. Environmental Protection Agency (EPA) already uses the benchmark dose in health risk assessment. Several software packages are today available for benchmark dose calculations. The availability of software to facilitate the analysis can make modeling appear simple, but often the interpretation of the results is not trivial, and it is recommended that benchmark dose modeling be performed in collaboration with a toxicologist and someone familiar with this type of statistical analysis. The procedure does not replace expert judgments of toxicologists and others addressing the hazard characterization issues in risk assessment. The aim of this article is to make risk assessors familiar with the concept, to show how the method can be used, and to describe some possibilities, limitations, and extensions of the benchmark dose approach. In this article the benchmark dose approach is presented in detail and compared to the traditional NOAEL approach. Statistical methods essential for the benchmark dose method are presented in Appendix A, and different mathematical models used in the U.S. EPA's BMD software, the Crump software, and the Kalliomaa software are described in the text and in Appendix B. For replacement of NOAEL in health risk assessment it is considered important that consensus is reached on the crucial parts of the benchmark dose method, that is, selection of risk types and the determination of a response level corresponding to the BMD, especially for continuous data. It is suggested that the BMD method is used as a first choice and that in cases where it is not possible to fit a model to the data the traditional NOAEL approach should be used instead. The possibilities to make benchmark dose calculations on continuous data need to be further investigated. In addition, it is of importance to study whether it would be appropriate to increase the number of dose levels by decreasing the number of animals in each dose group.
Automatic Emotional State Detection using Facial Expression Dynamic in Videos

In this paper, an automatic emotion detection system is built for a computer or machine to detect the emotional state from facial expressions in human computer communication. Firstly, dynamic motion features are extracted from facial expression videos and then advanced machine learning methods for classification and regression are used to predict the emotional states. The system is evaluated on two publicly available datasets, i.e. GEMEP_FERA and AVEC2013, and satisfied performances are achieved in comparison with the baseline results provided. With this emotional state detection capability, a machine can read the facial expression of its user automatically. This technique can be integrated into applications such as smart robots, interactive games and smart surveillance systems.
Variability in Measurement of Swimming Forces

An analysis was conducted to identify sources of true and error variance in measuring swimming drag force to draw valid conclusions about performance factor effects. Passive drag studies were grouped according to methodological differences: tow line in pool, tow line in flume, and carriage in tow tank. Active drag studies were grouped according to the theoretical basis: added and/or subtracted drag (AAS), added drag with equal power assumption (AAE), and no added drag (ANA). Data from 36 studies were examined using frequency distributions and meta-analytic procedures. It was concluded that two active methods (AAE and ANA) had sources of systematic error and that one active method (AAS) measured an effect that was different from that measured by passive methods. Consistency in drag coefficient (Cd) values across all three passive methods made it possible to determine the effects of performance factors.
Loss of Luteinizing Hormone Surges Induced by Chronic Estradiol Is Associated with Decreased Activation of Gonadotropin-Releasing Hormone Neurons1

Abstract Chronic exposure of young ovariectomized rats to elevated circulating estradiol causes loss of steroid-induced LH surges. Such LH surges are associated with cFos-induced activation of GnRH neurons; therefore, we hypothesized that chronic estradiol treatment abolishes LH surges by decreasing activation of GnRH neurons. Regularly cycling rats were ovariectomized and immediately received an estradiol implant or remained untreated. Three days or 2 or 4 wk later, the estradiol-treated rats received vehicle or progesterone at 1200 h, and 7 hourly blood samples were collected for RIA of LH. Thereafter, all rats were perfused, and the brains were examined for immunocytochemical localization of cFos and GnRH. The GnRH neurons from untreated ovariectomized rats rarely expressed cFos. As reported, LH surges induced by 3 days of estradiol treatment were associated with a 30% increase in cFos-containing GnRH neurons, and progesterone enhanced both the amplitude of LH surges and the proportion of cFos-immunopositive GnRH neurons. As hypothesized, the abolition of LH surges caused by 2 or more weeks of estradiol was paralleled by a reduction in the percentage of cFos-containing GnRH neurons, and this effect was delayed by progesterone. These results suggest that chronic estradiol abolishes steroid-induced LH surges in part by inactivating GnRH neurons.
Modelo de deslizamento para escoamento gás-líquido em bomba centrífuga submersa operando com líquido de baixa viscosidade

A bomba centrifuga submersa (BCS) e uma bomba de multiplos estagios que tem recebido muita atencao nos ultimos anos, devido a sua importância para a elevacao artificial de petroleo em altas vazoes. Como uma parte do sistema de Elevacao Artificial, a BCS e geralmente instalada no interior do poco, a fim de aumentar a vazao ou ate mesmo viabilizar a producao. A presenca de gas livre no fluido na entrada da bomba provoca uma diminuicao do ganho de pressao fornecido pela BCS e pode conduzir a instabilidades na curva de ganho de pressao versus vazao. O objetivo deste trabalho e desenvolver e avaliar o desempenho de um modelo de deslizamento para representar o ganho de pressao em uma ampla faixa de vazao de liquido de uma BCS. Para este proposito foram realizados testes experimentais em laboratorio para tres BCS diferentes que operam com misturas ar - agua. Especificamente, o ganho de pressao e a potencia de eixo foram medidos em diferentes vazoes de liquido, de gas, de pressoes de entrada e rotacao. Os resultados dos testes de agua monofasicos foram interpretados por ajuste dos dados com um modelo de correlacao generico para o ganho de pressao e potencia, tentando descrever todos os fenomenos fisicos envolvidos no escoamento nos canais rotativos. Os resultados dos testes bifasicos foram discutidos em termos dos efeitos da fracao de vazio, da pressao de admissao, da velocidade de rotacao e da geometria da bomba. Um modelo de deslizamento para escoamento em bolhas foi proposto para representar o ganho de pressao e tambem foi utilizado para expressar a potencia de eixo. Os dois parâmetros envolvidos no modelo, ou seja, C0 e kb? , foram ajustados aos dados e mostrou a capacidade desta abordagem em capturar as principais tendencias das curvas experimentais. O parâmetro de distribuicao C0 foi, em todos os casos, significativamente menor do que um, confirmando os resultados de outros autores, em escoamento bifasico descendente em tubos. Alem disso, este resultado indica que os perfis de velocidade e de distribuicao de fase sao distorcidos pelo campo centrifugo e de Coriolis. O parâmetro kb? foi significativo apenas para a bomba radial de menor vazao, o que confirma a ideia de que para altas vazoes de liquido, as bolhas de gas sao dispersadas atraves do liquido e o deslizamento torna-se insignificante. Abstract
Predictors for Starting Depot Administration of Risperidone in Chronic Users of Antipsychotics

Background: Risperidone long-acting injectable (RLAI), the first second-generation depot antipsychotic, has extensively been studied before introduction. Thereafter, questions about the type of patients actually treated with RLAI in daily practice remain to be answered for making valid antipsychotic treatment comparisons involving RLAI in observational studies. Objective: We aimed to determine in chronic antipsychotic users who switched treatment, predictors for the prescription of (1) depot versus oral antipsychotics and (2) RLAI versus first-generation antipsychotics (FGAs) depot. Methods: We used pharmacy dispensing data from 53 community pharmacies in the northeast of the Netherlands containing approximately 500,000 persons. Chronic antipsychotic users were defined and followed up for a switch in antipsychotic treatment within the first period that RLAI was on the market. Multivariable analysis was performed to relate patient, prescriber, and medication characteristics to prescription of a new antipsychotic drug. Results: Predictors for switching to depot versus oral antipsychotics were male sex, previous use of depot antipsychotics, recent anticholinergic drug use, and a gap in antipsychotic dispensation history. Predictors for switching to RLAI versus FGA depot were previous use of depot and consulting a specialist. Conclusions: The results suggest that, compared with oral antipsychotics, patients receiving a depot are less compliant users, with more extrapyramidal side effects. Compared with FGA depot, patients receiving RLAI tend to be more severely ill patients. We conclude that RLAI may be partly channeled to patients as a last resort, which may have important consequences for the interpretation of observational effectiveness comparisons between RLAI and other antipsychotics in daily practice.