Miracle-dz/UniFAR-FTUs huggingface dataset:
A cross sectional study of several diseases in cattle at Chandanaish Upazilla of Chittagong district, Bangladesh.

Prevalence of several diseases is one of the most economically important matters for maintaining a good treatment schedule of an area. This study detects the prevalence of several diseases and to evaluate the disease condition of cattle population in the selected area. Records of 306 clinical cases of cattle (120 dairy cows, 89 bulls and 97 calves) treated at the Chandanaish Upazila Veterinary Hospital during the month from December 2010 to February 2011 were analyzed to assess the importance of existing diseases. The recorded clinical cases were classified into seven major diagnostic groups, of which the highest prevalence was recorded with digestive disorders (47.05%), followed by parasitic infection (26.79%), infectious diseases (7.84%), respiratory disorder (6.2%), surgical affections (5.22%), metabolic disorder (4.24%), ectoparasitic infection (1.96%) and others (0.65%). The percentage of occurrence of major diagnostic groups of disease constituted infectious disease, (cows 41.66%, bulls 33.33%, calves 25%), parasitic disease (cows 37.80%, bulls 19.05% and calves 42.68%), digestive disorders (cows 41.66% , bulls 35.41% and calves 22.91%), respiratory disorders (cows 21.05%, bulls 26.31% and calves 52.63%), ectoparasitic infection (cows 16.66%, bulls 33.33% and calves 50%),metabolic diseases ( cows 46.15%, bulls 38.46% and calves 15.38%) and surgical affections( cows 50%, bulls 12.5% and calves 37.5%). Though each of all the diagnostic groups of diseases is significant but the digestive disorder, parasitic and infectious diseases were the most pressing constraint for improvement of cattle at the Chandanaish Upazila in Bangladesh. Key words: Cattle, diseases, prevalence, Bangladesh.
Salmonella spp. in patients suffering from enteric fever and food poisoning in Thamar city, Yemen.

Salmonella remains a public health concern around the world, including Yemen although data on its incidence are few. This study determined the incidence of Salmonella infection in 250 enteric fever and 210 food poisoning cases attending Thamar general hospital and Dar Alshafaa medical clinic in 2008. In total, 773 clinical specimens were taken: 250 blood, 187 urine and 336 stool samples. Of the patients with enteric fever and food poisoning, 16.4% and 15.2% respectively were infected with Salmonella. The serovars isolated were: Salmonella Typhi (45.6%), Salmonella Enteritidis (24.4%), Salmonella Paratyphi B (14.4%), Salmonella Typhimurium (13.3%) and Salmonella Paratyphi A (2.2%). The distribution of somatic groups was: D (70%), B (27.7%) and A (2.2%). None of the isolates was resistant to ciprofloxacin, sparfloxacin, ceftriaxone or moxifloxacin, while 71.1% were resistant to co-trimoxazole, 62.2% to gentamicin, 56.6% to ampicillin and 35.5% to nalidixic acid.
Modelling the Dynamics of Multiagent Q-Learning in Repeated Symmetric Games: a Mean Field Theoretic Approach

Modelling the dynamics of multi-agent learning has long been an important research topic, but all of the previous works focus on 2-agent settings and mostly use evolutionary game theoretic approaches. In this paper, we study an n-agent setting with n tends to infinity, such that agents learn their policies concurrently over repeated symmetric bimatrix games with some other agents. Using mean field theory, we approximate the effects of other agents on a single agent by an averaged effect. A Fokker-Planck equation that describes the evolution of the probability distribution of Q-values in the agent population is derived. To the best of our knowledge, this is the first time to show the Q-learning dynamics under an n-agent setting can be described by a system of only three equations. We validate our model through comparisons with agent-based simulations on typical symmetric bimatrix games and different initial settings of Q-values.
Classification of malicious process using high‐level activity based dynamic analysis

Detection of malicious program is a critical component in system security. Advanced malware like metamorphic, polymorphic, or evasive malware cannot be detected successfully using the traditional signature‐ and heuristics‐based anti‐malware methods. This paper proposes an approach to detect malicious activity running on the system by leveraging semantics of the behavior of processes to complement the static characteristics of their executable image. Static characteristics are captured from the file header, optional headers, and sections of the executable file. The behavior model of the process is in the form of high‐level activities generated through the runtime tracing of the process. The proposed approach classifies malicious executables on the basis of the higher‐level abstraction of the activity rather than the actual system calls. Experimental results show that the approach supplements the traditional methods toward the improvement of the precision in the overall classification of malicious activity, besides detecting advanced malware which uses obfuscation, polymorphism techniques, etc. for evasion.
The Lipid Profile of Human Immunodeficiency Virus-infected Patients Receiving Antiretroviral Therapy at Mpilo Central Hospital Opportunistic Infections Clinic

Aims: Long term use of antiretroviral therapy subpopulation living with human immunodeficiency virus is associated with disturbances in blood lipids profiles which are not routinely monitored. More data on such disturbances are needed to persuade the country’s program to institute routine monitoring. This study sought to determine the prevalence and timing of dyslipidaemia in HIV/AIDS naïve people on ART at in Zimbabwe. Place and Duration of Study: The study was conducted at Mpilo Central Hospital Opportunistic Infections Clinic in Bulawayo, Zimbabwe over a period of three months. Methods: A cross-sectional study was conducted in HIV-infected persons receiving highly active anti-retroviral treatment at Mpilo Central Hospital Opportunistic Infections Clinic. Lipid assays were determined by Elisa methods. Viral loads and CD4 were measured using the COBAS® TaqMan® and BD FACSCount™ Flow Cytometer, respectively. Results: A total of 149 consenting participants were enrolled and most (63.2%) were females. The median age of the respondents was 43 years and their median CD4 count was 436 cells/μl after a median duration on ART of 36 months. Viral load was <40 in the majority (68.6%) of the participants. More females (63.1%) were on HAART and were aged >35 (60.4%) years. NNRTI (90.6%) were the more commonly prescribed HAART. The prevalence of dyslipidaemia was 70.2%. Hypercholesterolaemia was observed in 72 (48.3%) patients with 26 being male and 46 being female. High levels of LDL-cholesterol (LDL-c ≥ 3.0 mmol/L) were found in 115 patients with 74 of them being female. Hypertriacylglycerolaemia (TAG ≥ 2.0 mmol/L) was present in 8 cases. The proportion of patients with a low HDL-cholesterol (HDL-c < 1.0 mmol/L) was 15.3% while those with a ratio of TC/HDL-c ≥ 4.1 were 87.5%. Conclusion: The study demonstrated a high prevalence of dyslipidaemia in HIV-patients receiving HAART. There is a need for the Country’s HIV program to institute laboratory monitoring of blood lipids in patients over one year on HAART.
THE EXPERIENCE OF RECOVERY AT HOME FOLLOWING AMBULATORY SURGERY PROCEDURE: A SYSTEMATIC LITERATURE REVIEW

Background: Patients’ recovery from surgery differs when they are in a hospital setting or at home. However, an often forgotten aspect of post-operative ambulatory care is the patients' recovery at home following ambulatory surgery.Aim: To explore and describe the patients’ experiences of recovery at home following the ambulatory surgery procedure.Method: A systematic review of 7 qualitative studies in English with pre-specified criteria was conducted. An overview of qualitative evidence derived from the 17 identified main themes across the 7 primary studies was analyzed.Result: Seven thematic analysis themes were identified as being core to the patients’ experience during recovery process at home: physical symptoms, a period of regaining pre-operative functions, psychological effects, the surgical wound, delayed recovery process, social support, and the sick-role condition. These seven themes were described patient's experiences at home following ambulatory surgery from early stage of recovery to the time of getting back to normal life.Conclusion: Recovery at home following ambulatory surgery seemed to be challenging, a quality self-care at home was lacking in the form having full control and knowledge about symptoms; adequate information, education and medication during self-care management; sufficient support by carer and nurses; and enough time-off for recovery.
Analysis of the Selection Factor of Online Transportation in the VIKOR Method in Pematangsiantar City

Transportation plays an important role in helping every community activity and also has an important function in economic, social and developmental development. Online transportation provides alternative transportation solutions in the middle of the density of vehicles to be fast and able to reach places that are likely to be inaccessible to other public vehicles. People who usually use public transport or conventional taxi services have begun to switch to online-based taxis that are considered cheaper and more practical. Market research institutes in Southeast Asia show that 250 million Indonesians are quickly adapting the growth of application-based transportation (taxis and ojek online) to facilitate their lives. Various factors that influence people prefer online transportation compared to public transport or conventional taxis. The purpose of the study is to determine the main factors that people prefer to use Oline transportation. The study used the VIKOR method system which obtained the results based on the VIKOR index value where alternative A1: Easy and Safe (VIKOR index value 0) as a rank one and alternative A2: Price (VIKOR index value 0.1809520) as the second rank.
Fault Diagnosis Method for Hydraulic Directional Valves Integrating PCA and XGBoost

A novel fault diagnosis method is proposed, depending on a cloud service, for the typical faults in the hydraulic directional valve. The method, based on the Machine Learning Service (MLS) HUAWEI CLOUD, achieves accurate diagnosis of hydraulic valve faults by combining both the advantages of Principal Component Analysis (PCA) in dimensionality reduction and the eXtreme Gradient Boosting (XGBoost) algorithm. First, to obtain the principal component feature set of the pressure signal, PCA was utilized to reduce the dimension of the measured inlet and outlet pressure signals of the hydraulic directional valve. Second, a machine learning sample was constructed by replacing the original fault set with the principal component feature set. Third, the MLS was employed to create an XGBoost model to diagnose valve faults. Lastly, based on model evaluation indicators such as precision, the recall rate, and the F1 score, a test set was used to compare the XGBoost model with the Classification And Regression Trees (CART) model and the Random Forests (RFs) model, respectively. The research results indicate that the proposed method can effectively identify valve faults in the hydraulic directional valve and have higher fault diagnosis accuracy.
Reduced Order Modelling and Uncertainty Propagation Applied to Water Distribution Networks

Water distribution systems are large, spatially distributed infrastructures that ensure the distribution of potable water of sufficient quantity and quality. Mathematical models of these systems are characterized by a large number of state variables and parameter. Two major challenges are given by the time constraints for the solution and the uncertain character of the model parameters. The main objectives of this thesis are thus the investigation of projection based reduced order modelling techniques for the time efficient solution of the hydraulic system as well as the spectral propagation of parameter uncertainties for the improved quantification of uncertainties. The thesis gives an overview of the mathematical methods that are being used. This is followed by the definition and discussion of the hydraulic network model, for which a new method for the derivation of the sensitivities is presented based on the adjoint method. The specific objectives for the development of reduced order models are the application of projection based methods, the development of more efficient adaptive sampling strategies and the use of hyper-reduction methods for the fast evaluation of non-linear residual terms. For the propagation of uncertainties spectral methods are introduced to the hydraulic model and an intrusive hydraulic model is formulated. With the objective of a more efficient analysis of the parameter uncertainties, the spectral propagation is then evaluated on the basis of the reduced model. The results show that projection based reduced order models give a considerable benefit with respect to the computational effort. While the use of adaptive sampling resulted in a more efficient use of pre-calculated system states, the use of hyper-reduction methods could not improve the computational burden and has to be explored further. The propagation of the parameter uncertainties on the basis of the spectral methods is shown to be comparable to Monte Carlo simulations in accuracy, while significantly reducing the computational effort.
Medical Care of the Liver Transplant Patient

Chapter 1: Selection of Patients and Timing of Liver Transplantation Don C. Rockey Chapter 2: Evaluation of Potential Liver Transplant Recipients Mark W. Swaim Chapter 3: Fulminant Hepatic Failure Michael A. Heneghan Chapter 4: Management of Portal Hypertension and Biliary Disease Prior to Transplantation Nazia Malekkiani, Janet E. Tuttle-Newhall, and Pierre-Alain Clavien Chapter 5: Transplantation in Patients with Alcoholic Liver Disease Jeff M. Georgi Chapter 6: Psychiatric Evaluation and Care of the Liver Transplant Patient Valerie F. Holmes Chapter 7: Financial Considerations in Liver Transplantation Syvil S. Burke and Donald W. Witten, Jr. Chapter 8: Procurement and Allocation of Donor Livers R. Randal Bollinger and Michael Heneghan Chapter 9: The Transplant Operation Pierre-Alain Clavien Chapter 10: Adult-to-Adult Living Related Liver Transplantation Markus Selzner, Zakiyah Kadry, Pierre-Alain Clavien Chapter 11: Anesthesia for the Liver Transplant Patient Kerri Robertson Chapter 12: Recovery Following Liver Transplant Julie S. Tart and Judith W. Gentile Chapter 13: Rejection of the Liver Graft Bradley H. Collins Chapter 14: Vascular Aspects of Liver Transplantation Paul Suhocki, Ravi Chari, Richard McCann, and Pierre A. Clavien Chapter 15: Biliary Complications Following Liver TransplantationM. Stanley Branch Chapter 16: The Role of Histopathology in the Evaluation of the Liver Transplant Recipient Mary K. Washington and David N. Howell Chapter 17: Research in Liver Transplantation: A Cooperative Endeavor Pierre-Alain Clavien Chapter 18: Medical Problems after Liver Transplantation Paul G. Killenberg Chapter 19: Recurrence of the Original Liver Disease After Transplantation Jeffrey D. Bornstein Chapter 20: Infectious Complications and Considerations in the Liver Transplant Recipeint Barbara M. Alexander Chapter 21: Renal Function in the Liver Transplant Patient Stephen R. Smith Chapter 22: Cutaneous Problems in Liver Transplant Patients Sarah A. Myers Chapter 23: Social Rehabilitation of the Liver Transplant Patient Z. Elaine Dowdy and R. Scott Pollard Chapter 24: Pharmacology of the Immunosuppressive Drugs Used in Liver Transplantation Andrew Muir Chapter 25: Drug Interactions with Commonly Used Immunosuppressive Agents Paul G. Killenberg Chapter 26: Liver Transplantation in Children William Treem
Sculptures as the Trademark of Sovereignty in the Hoysaḷa Kingdom

Among the various sculptures created by Hoysaḷa artists between the 12th and 13th centuries emerges a curious iconographic couple: a man wearing a long robe and an unusual headdress, accompanied by a woman, completely naked, with sandals on her feet, surrounded by snakes. Both these figures have a stick. The recurrence of this subject in many temples and the important position in the register of sculptures suggest that this iconography was already codified in the early 12th century, that is during the rise of the dynasty. The focus of my study is to analyze the development of these representations in correlation with the religious and political context: at the beginning the two iconographies were sculpted together, while in the course of time they began to be carved separately. This new exploration adds to the iconographic analysis and the study of the epigraphic sources and it aims at relating the artistic production with the construction and legitimation of the dynasty. Controversial interpretations of the meaning of these representations open up a lively debate about local cults in medieval Karnataka and the versatile royalty of the Hoysaḷa dynasty.
Investigating Capsule Network and Semantic Feature on Hyperplanes for Text Classification

As an essential component of natural language processing, text classification relies on deep learning in recent years. Various neural networks are designed for text classification on the basis of word embedding. However, polysemy is a fundamental feature of the natural language, which brings challenges to text classification. One polysemic word contains more than one sense, while the word embedding procedure conflates different senses of a polysemic word into a single vector. Extracting the distinct representation for the specific sense could thus lead to fine-grained models with strong generalization ability. It has been demonstrated that multiple senses of a word actually reside in linear superposition within the word embedding so that specific senses can be extracted from the original word embedding. Therefore, we propose to use capsule networks to construct the vectorized representation of semantics and utilize hyperplanes to decompose each capsule to acquire the specific senses. A novel dynamic routing mechanism named ‘routing-on-hyperplane’ will select the proper sense for the downstream classification task. Our model is evaluated on 6 different datasets, and the experimental results show that our model is capable of extracting more discriminative semantic features and yields a significant performance gain compared to other baseline methods.
Utilization of the Modified Tanahashi Model for Assessing Universal Effective Health Coverage: The Nigeria Bottleneck Instrument and its’ Implications for Planning

i ACKNOWLEDGEMENTS . iii ABBREVIATIONS . vi CHAPTER 1 . 1 Background . 1 Problem Statement . 6 CHAPTER 2 . 8 Study Setting and Design . 8 Measures . 10 Analytical Approach . 11 Ethical Approval . 12 CHAPTER 3 . 14 Characteristics of the Sample . 14 Correlations between the Determinants in the NBNA Instrument . 15 Diminishing Relationship between Demand Side Variables . 16 Multivariate Results . 17 CHAPTER 4 . 20 Recommendations for Leadership . 23 Limitations . 24 Conclusion . 24 REFERENCES . 26 APPENDICES . 32 Table A: Adapted Coverage Indicators for Routine Immunization . 32 Table B: Adapted Coverage Indicators for Integrated Management of Childhood Illnesses . 33 Table C: Adapted Coverage Indicators for Antenatal Care (ANC). 34 Table D: Adapted Coverage Indicators for Skilled Birth Attendance & Neonatal Care. 35 Table E: Correlation Matrices . 36 Table F: Ordinary Least Squares Models . 37
Machine learning prediction of defect types for electroluminescence images of photovoltaic panels

Despite recent technological advances for Photovoltaic panels maintenance (Electroluminescence imaging, drone inspection), only few large-scale studies achieve identification of the precise category of defects or faults. In this work, Electroluminescence imaged modules are automatically split into cells using projections on the x and y axes to detect cell boundaries. Regions containing potential defects or faults are then detected using Hough transform combined with mathematical morphology. Care is taken to remove most of the bus bars or cell boundaries. Afterwards, 25 features are computed, focusing on both the geometry of the regions (e.g. area, perimeter, circularity) and the statistical characteristics of their pixel values (e.g. median, standard deviation, skewness). Finally, features are mapped to the ground truth labels with Support Vector Machine (RBF kernel) and Random Forest algorithms, coupled with undersampling and SMOTE oversampling, with a stratified 5- folds approach for cross validation. A dataset of 982 Electroluminescence images of installed multi-crystalline photovoltaic modules was acquired in outdoor conditions (evening) with a CMOS sensor. After automatic blur detection, 753 images or 47244 cells remain to evaluate faults. All images were evaluated by experts in PV fault detection that labelled: Finger failures, and three types of cracks based on their respective severity levels (A, B and C). Our results based on 6 data series, yield using Support Vector Machine an accuracy of 0.997 and a recall of 0.274. Improving the region detection process will most likely allow improving the performance.
MODELING AND CONVERGENCE ANALYSIS OF DIRECTED ENERGY DEPOSITION SIMULATIONS WITH HYBRID IMPLICIT / EXPLICIT AND IMPLICIT SOLUTIONS

Conventional metal manufacturing techniques are suitable for mass production. However, cheaper and faster alternatives are preferred for small batch sizes and individualized components. Directed energy deposition (DED) processes allow depositing metallic material in almost arbitrary shapes. They are characterized by cyclic heat input, hence heating and cooling every point in the workpiece several times. This temperature history leads to distribution of mechanical properties, distortions, residual stresses or even fatigue properties in the part. To avoid experimental trial-and-error optimization, different methods are available to simulate DED processes. Currently, the wire arc additive manufacturing (WAAM) is the most competitive DED process. In this work, a simulation method for the WAAM process is established and validated, which should be capable to calculate global effects (e.g. distortions, residual stresses) of real WAAM-processes with duration of hours and thousands of weld beads. The addition of beads and layers is simulated by the element birth and death technique. The elements are activated according to the movements of the heat source (arc). In this paper, the influence of the time step, the mesh size and the material properties of the inactive elements in hybrid implicit / explicit and fully implicit solutions are evaluated with respect to the computation time and stability. This investigation concludes several recommendations for AM-modelling. For example, a low Young’s modulus (100 N/mm²) for the inactive elements show nearly no influences on the welding simulation, but introduces numerical instabilities in case of multiple welding beads. The Young’s modulus should be increased to 1.000 N/mm² for small mesh-sizes, small step-sizes and many beads, even when it introduces unwanted stresses.