Miracle-dz/UniFAR-FTUs huggingface dataset:
Claiming the right to health for women who have sex with women : analysing South Africa's National Strategic Plans on HIV and STIs

Introduction: Evidence has emerged that women who have sex with women (WSW) in South Africa face multiple vulnerabilities to sexually transmitted infections (STIs) including HIV. This health policy analysis seeks to understand why and how interventions to improve sexual health of WSW were initially proposed in the HIV & AIDS and STI Strategic Plan for South Africa 2007-2011, what was implemented and how issues were reframed in the National Strategic Plan (NSP) on HIV, STIs and TB 2012-2016. Methodology: Qualitative methods were used to analyse changes over time in policy discourse around WSW sexual health. A conceptual framework considered four factors determining political priority setting for WSW issues in NSP development processes: actor power, ideas, political context and issue characteristics. 25 semi-structured key informant interviews were conducted in South Africa in 2013 and findings were triangulated through document analysis. Results: Breakthrough in participation in policy making on HIV/AIDS in 2007 enabled the women’s sector of the South African National AIDS Council (SANAC) to present testimony from WSW affected by HIV. Policy content of the 2007-2011 NSP included WSW issues but no activities were implemented in the public health system. Policy actors were mandated to redevelop an evidence based NSP for 2012-2016 and discourse on key populations vulnerable to HIV, including men who have sex with men (MSM), shaped policy content. Data on HIV and STIs among WSW existed but resources to disseminate or undertake further research were limited. The SANAC LGBTI sector, created to represent community interests, became preoccupied with MSM programming. Focus on WSW was not maintained in the 2012-2016 NSP due to limited health metrics, limits on participation and growing social conservatism. Conclusion: In the future advocates must reiterate rights based arguments on the vulnerabilities of WSW and call for a revised research agenda on the epidemiology of WSW sexual health.
Lack of Evidence That Selenium-Yeast Improves Chicken Health and Modulates the Caecal Microbiota in the Context of Colonization by Campylobacter jejuni

Faced with ever-increasing demand, the industrial production of food animals is under pressure to increase its production. In order to keep productivity, quality, and safety standards up while reducing the use of antibiotics, farmers are seeking new feed additives. In chicken production, one of these additives is selenium. This element is expected to confer some advantages in terms of animal health and productivity, but its impact on chicken intestinal microbiota as well as on the carriage of foodborne pathogens is unknown. In this study, chickens raised in a level 2 animal facility were fed or not 0.3 ppm of in-feed selenium-yeast until 35 days of age and were inoculated or not with the foodborne pathogen Campylobacter jejuni at the age of 14 days. At the end of the study, body weight, seric IgY, intestinal IgA, seric gluthatione peroxydase activity, the caecal microbiota (analyzed by MiSeq 16S rRNA gene sequencing), and C. jejuni caecal levels were analyzed. The experiment was completely replicated twice, with two independent batches of chickens. This study revealed that, for healthy chickens raised in very good hygienic conditions, selenium-yeast does not influence the bird’s body weight and lowers their seric gluthatione peroxidase activity as well as their intestinal IgA concentrations. Furthermore, selenium-yeast did not modify the caecal microbiota or the colonization of C. jejuni. The results also showed that C. jejuni colonization does not impact any of the measured chicken health parameters and only slightly impacts the caecal microbiota. This study also clearly illustrated the need for true biological replication (independent animal trials) when assessing the microbiota shifts associated with treatments as the chickens microbiotas clearly clustered according to study replicate.
Crucial Factors in Cooperative Multirobot Learning

Cooperative decentralized multirobot learning refers to the use of multiple learning entities to learn optimal solutions for an overall multirobot system. We demonstrate that traditional single-robot learning theory can be successfully used with multirobot systems, but only under certain conditions. The success and the effectiveness of single-robot learning algorithms in multirobot systems are potentially affected by various factors that we classify into two groups: the nature of the robots and the nature of the learning. Incorrect set-up of these factors may lead to undesirable results. In this paper, we systematically test the effect of varying five common factors (model of the value function, reward scope, delay of global information, diversity of robots’ capabilities, and number of robots) in decentralized multirobot learning experiments, first in simulation and then on real robots. The results show that three of these factors (model of the value function, reward scope, and delay of global information), if set up incorrectly, can prevent robots from learning optimal, cooperative olutions. s K eywords: multirobot learning, distributed reinforcement learning, cooperative robots
History and biomedical applications of digital signal and image processing

The paper presents in its initial part historical notes to the development of digital signal and image processing methods. The following case studies are devoted to their application in biomedicine and they include the use of computational intelligence in EEG and EMG signal processing, image segmentation and registration in orthodontia, the human-machine interaction and the three-dimensional modelling using MS Kinect in diagnostics and treatment of human motion disorders and neurological diseases. Associated comments include remarks and references to the development of modern computational tools, biosensors, wireless communication and data fusion used in assistive technologies and robotic systems. Mathematical tools common to all these applications form the next part of the paper that includes notes to spectral analysis, functional transforms, digital filtering, image enhancement, classification of multi-dimensional signal components and optimization using neural networks. Final remarks emphasize the interdisciplinary significance of the digital signal processing forming the integrating basis of many diverse research areas.
MPI-based parallel for bees optimization algorithm

In this paper, the Artificial Bee Colony algorithm is implemented using Message Passing Interface (MPI) in a parallel form. Bees Algorithm was emerged to solve optimization problems. Randomly generated initial solutions and obtaining the optimal solution among all the possible solutions are the cases which optimize Speedup of the algorithm in a parallel basis. In this paper, using the capabilities of MPI including making connections among various processes, a method was used for paralleling this optimization algorithm. In this method, for further optimization of the responses at the end of each loop, master process is specified to collect the best solutions for each processor. Master process finds the best solutions and replaces the worst ones to the processor which has not the optimal solution.
Approaches on Detecting Domain Errors – A Survey

The past decades of research in software testing has foreseen the development of n number of techniques for assessing the domain correctness of software units. A method of programming and debugging causes many types of errors. Types of errors would have some classifications based on the nature of the program. One of those is the occurrence of domain errors in programs. The major challenge in this area is to generate a set of test cases automatically and test it with various techniques. Main goal of this survey is to allow the software testers and developers to become aware of where the error origins and how it would be tested? The following steps are elucidated in detail of how a program should be tested by test case generation, by test case tools and by test case algorithms with the presence of some correct behavior in programs. This paper presents a short survey of past decades on how the errors have been handled by the testers. Keywords— Domain Errors, Test Case Generation, Tools, Algorithms, Approaches and Methods.
Visual Detection, Tracking and Pose Estimation of a Robotic Arm End Effector

In this work we present a robust tracking and pose estimation of an end effector of a 7 DoF robotic arm under a binocular stand-alone configuration. The proposed method is composed of sequence of three processes. The first one is a fast segmentation in HSV color space of a planar patch placed at the end effector. This step considers the segmentation using pixels classification and Euclidean distance a similarity measure. The second step is the selection of a region of interest, feature point extraction and tracking over that region. Finally, the feature points can be used to estimate the homography between world reference frame and image frame. The proposed methodology runs in real time and it is applicable for visual servoing and the grasping.
PowerViP: SoC power estimation framework at transaction level

In this work, we propose a SoC power estimation framework built on our system-level simulation environment. Our framework provides designers with the system-level power profile in a cycle-accurate manner. We target the framework to run fast and accurately, which is enabled by adopting different modeling techniques depending on the power characteristics of various IP blocks. The framework can be applied to any target SoC design
A Method of Analysis to Uncover Artefact-Communication Relationships

This paper introduces a method of analysis to uncover artefact communication relationships in real world settings. This method is based on learning and communication theory, together with situated cognition. It was developed in the context of agile software development practice. Using this method, we found evidence that physical artefacts help team members to define contexts within their practice, which in turn become part of their contingency plan for communicating during specific contexts of communication. A contingency plan is a set of communicative actions that members take in future events that are possible but not intended, including the unanticipated.
Preventative Effects of Caffeic Acid Phenyl Ester on Cadmium Intoxication Induced Hematological and Blood Coagulation Disturbances and Hepatorenal Damage in Rats

The preventative effect of caffeic acid phenyl ester (CAPE) against hematological, blood coagulation, and hepatorenal disturbances in cadmium (Cd) intoxication was investigated in rats. Male Wistar rats were randomly assigned into control group, Cd-group, and Cd + CAPE group. Cd intoxication was induced by intraperitoneal injection (i.p.) of CdCl2 (1 mg/kg/day) for 21 days, and CAPE was daily given (10 micromol/kg; i.p.) for also 21 days. The results showed that Cd intoxication impaired hepatorenal function and significantly prolonged prothrombin time and activated partial thromboplastin time and decreased fibrinogen level, red blood cells and platelets counts, hemoglobin concentration, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration. Interestingly, all these hematological, blood coagulation, and hepatorenal deteriorations of Cd toxicity were significantly prevented by CAPE. Additionally, CAPE significantly reversed the significant decreases in levels of total reduced glutathione and superoxide dismutase and increases in levels of thiobarbituric acid reactive substances that were observed in the sera and liver and kidney homogenates of Cd group. It is concluded that CAPE is a promising compound that can counteract the hematological and blood coagulation disturbances, oxidative stress, and hepatorenal damages in Cd intoxication. However, further studies are crucially needed to improve this treatment in patients.
Non-causal computation avoiding the grandfather and information antinomies

Computation models such as circuits describe sequences of computation steps that are carried out one after the other. In other words, algorithm design is traditionally subject to the restriction imposed by a fixed causal order. We address a novel computing paradigm, replacing this assumption by mere logical consistency: We study non-causal circuits, where a fixed time structure within a gate is locally assumed whilst the global causal structure between the gates is dropped. We present examples of logically consistent non-causal circuits outperforming all causal ones; they imply that suppressing loops entirely is more restrictive than just avoiding the contradictions they can give rise to. That fact is already known for correlations as well as for communication, and we here extend it to computation.
Send Orders of Reprints at Reprints@benthamscience.net Cnto 530 Increases Expression of Hba and Hbf in Murine Models of -thalassemia and Sickle Cell Anemia

CNTO 530 is an erythropoietin receptor agonist MIMETIBODY TM construct. CNTO 530 has been shown to be active in a number of rodent models of acquired anemia (e.g. renal insufficiency and chemotherapy induced anemia). We investigated the efficacy of CNTO 530 in murine models of-thalassemia and sickle cell anemia (Berkeley mice). -thalassemic mice are deficient in expression of-globin chain and heterozygous mice are characterized by a clinical syndrome similar to the human-thalassemia intermedia. Berkeley mice are knocked out for murine alpha and beta globin and are transgenic for human alpha, beta (sickle) and gamma globin genes. Berkeley mice thus express human sickle he-moglobin A (HbS) and can also express human fetal hemoglobin. These mice express a severe compensated hypochromic microcytic anemia and display the sickle cell phenotype. To test the effectiveness of CNTO 530, mice from both genotypes received a single subcutaneous (s.c.) dose of CNTO 530 or darbepoetin-(as a comparator) at 10,000 U/kg, a dose shown to cause a similar increase in reticulocytes and hemoglobin in normal mice. Hematologic parameters were evaluated over time. CNTO 530, but not darbepoetin-, increased reticulocytes, red blood cells and total hemoglobin in-thalassemic mice. In Berkeley mice CNTO 530 showed an increase in reticulocytes, red blood cells, F-cells, total hemo-globin and fetal hemoglobin. In conclusion, CNTO 530 is effective in murine models of-thalassemia and sickle cell anemia. These data suggest that CNTO 530 may have beneficial effects in patients with genetically mediated hemoglobi-nopathies.
Robust Support Vector Machines for Anomaly Detection in Computer Security

Using the 1998 DARPA BSM data set collected at MIT’s Lincoln Labs to study intrusion detection systems, the performance of robust support vector machines (RVSMs) was compared with that of conventional support vector machines and nearest neighbor classifiers in separating normal usage profiles from intrusive profiles of computer programs. The results indicate the superiority of RSVMs not only in terms of high intrusion detection accuracy and low false positives but also in terms of their generalization ability in the presence of noise and running time. Keywords—Intrusion detection, computer security, robust support vector machines, noisy data.
Using machine learning to predict if a profiled lay rescuer can successfully deliver a shock using a public access automated external defibrillator?

A public access automated external defibrillator (AED) is a device that is intended to be used by lay rescuers in an event where a member of the public experiences a sudden cardiac arrest due to a severe ventricular arrhythmia. Therefore, it is imperative that the human-machine interface of an AED is optimized in terms of its usability and intuitive design. This study involved the recruitment of362 subjects (lay people) in a shopping mall to undertake the task of using an AED in a simulated environment as facilitated by a ‘sensorised’ manikin and an AED that was developed by HeartSine Technologies. We found that a large proportion (91.44%) of lay people can successfully use an AED in a simulated emergency scenario to deliver a successful shock. We also found that CPR training did not provide greater likelihood for shock success whilst those with AED training did. Exploratory data analysis and machine learning were used to determine if demographics and other variables are potential predictors for delivering a successful shock using an AED. We found that user demographics and educational attainment were not predictive for AED ‘usage’ success, which is reassuring since the objective of the medical industry is to develop AEDs that are intuitive to any member of the public.
Ranitidine modifies myeloid cell populations and inhibits breast tumor development and spread in mice

ABSTRACT Histamine receptor 2 (H2) antagonists are widely used clinically for the control of gastrointestinal symptoms, but also impact immune function. They have been reported to reduce tumor growth in established colon and lung cancer models. Histamine has also been reported to modify populations of myeloid-derived suppressor cells (MDSCs). We have examined the impact of the widely used H2 antagonist ranitidine, on both myeloid cell populations and tumor development and spread, in three distinct models of breast cancer that highlight different stages of cancer progression. Oral ranitidine treatment significantly decreased the monocytic MDSC population in the spleen and bone marrow both alone and in the context of an orthotopic breast tumor model. H2 antagonists ranitidine and famotidine, but not H1 or H4 antagonists, significantly inhibited lung metastasis in the 4T1 model. In the E0771 model, ranitidine decreased primary tumor growth while omeprazole treatment had no impact on tumor development. Gemcitabine treatment prevented the tumor growth inhibition associated with ranitidine treatment. In keeping with ranitidine-induced changes in myeloid cell populations in non-tumor-bearing mice, ranitidine also delayed the onset of spontaneous tumor development, and decreased the number of tumors that developed in LKB1−/−/NIC mice. These results indicate that ranitidine alters monocyte populations associated with MDSC activity, and subsequently impacts breast tumor development and outcome. Ranitidine has potential as an adjuvant therapy or preventative agent in breast cancer and provides a novel and safe approach to the long-term reduction of tumor-associated immune suppression.
Map segmentation based SLAM using embodied data

Autonomous mobile robots offer the prospect of extending our knowledge of remote places in the solar system or in the ocean. They also have the potential to improve everyday life with ever increasing adaptability to a large variety of environments. One of the key technological elements is the ability to navigate unknown and uncooperative environments. A range of solutions for the simultaneous localisation and mapping (SLAM) problem have emerged in the last decade. One factor which is often neglected is the fact that the robot has a body which interacts with the environment. In this paper a method is presented, which utilises this information and uses visual and non-visual correlations to generate accurate local map segments. Further, a method is presented to combine particle filter based local map segments and constraint graph based global pose optimization to a single coherent map representation. The method is evaluated on a Leg/Wheel hybrid mobile robot and the resulting maps compared against high resolution environment models generated with a commercial laser scanner.
Predictors of Prolonged Stay in the Intensive Care Unit following Cardiac Surgery

The prediction of intensive care unit length of stay (ICU-LOS) could contribute to more efficient ICU resources' allocation and better planning of care among cardiac surgery patients. The aim of this study was to identify the preoperative and intraoperative predictors for prolonged cardiac surgery ICU-LOS. An observational cohort study was conducted among 150 consecutive patients, who were admitted to the cardiac surgery ICU of a tertiary hospital of Athens, Greece from September 2010 to January 2011. Multivariate regression analysis revealed that patients with increased creatinine levels preoperatively (odds ratio (OR) 3.0, P = 0.049), history of atrial fibrillation (AF) (OR 6.3, P = 0.012) and high EuroSCORE values (OR 2.6, P = 0.017) had a significant greater probability to stay in the ICU for more than 2 days. In addition, intraoperative hyperglycemia (OR 3.0, P = 0.004) was strongly associated with longer ICU-LOS. In conclusion, the high perioperative risk, the history of AF and renal dysfunction, and the intraoperative hyperglycemia are significant predictors of prolonged ICU stay. The early identification of patients at risk could allow the efficient ICU resources' allocation and the reduction of healthcare costs. This would contribute to nursing care planning depending on the availability of healthcare personnel and ICU bed capacity.
EXPLAINING CROSS-COUNTRY DIFFERENCES IN JOB -RELATED TRAINING: MACROECONOMIC EVIDENCE FROM OECD COUNTRIES

This paper presents an empirical analysis on the macroeconomic determinants of aggregate job-related training activity across fourteen OECD countries. Training data comes from the International Adult Literacy Survey. We find that compression at the bottom of the wage distribution has a positive effect on aggregate training across countries and age-groups while compression at the top has the opposite effect. Consistent with microeconomic evidence on education and training, average literacy skills in each country and age-group have a positive effect on the proportion of workers trained. The analysis controls for unemployment rates, R&D levels, unionization rates, and industrial structures.
Advanced recognition techniques for human computer interaction

Hand gestures are an important modality for human computer interaction (HCI) [1]. Compared to many existing interfaces, hand gestures have the advantages of being easy to use, natural, and intuitive. Successful applications of hand gesture recognition include computer games control [2], human-robot interaction [3], and sign language recognition [4], to name a few. Vision-based recognition systems can give computers the capability of understanding and responding to hand gestures. The aim of this technique is the proposal of a real time vision system for its application within visual interaction environments through hand gesture recognition, using general-purpose hardware and low cost sensors, like a simple personal computer and an USB web cam, so any user could make use of it in his office or home. The basis of our approach is a fast segmentation process to obtain the moving hand from the whole image, which is able to deal with a large number of hand shapes against different backgrounds and lighting conditions, and a recognition process that identifies the hand posture from the temporal sequence of segmented hands. The use of a visual memory (Stored database) allows the system to handle variations within a gesture and speed up the recognition process through the storage of different variables related to each gesture. A hierarchical gesture recognition algorithm is introduced to recognize a large number of gestures. Three stages of the proposed algorithm are based on a new hand tracking technique to recognize the actual beginning of a gesture using a Kalman filtering process, hidden Markov models and graph matching. Processing time is important in working with large databases. Therefore, special cares are taken to deal with the large number of gestures.