Miracle-dz/UniFAR-FTUs huggingface dataset:
Salmonella and Campylobacter in broilers at slaughter age: a possible source for carcasses contamination in Ecuador

Salmonella and Campylobacter are major foodborne pathogens worldwide and are especially prevalent in the poultry meat chain. Although poultry meat is a principal component of the diet in Ecuador, little is known about the presence of these pathogens in this food chain. The aim of this thesis was to collect data about Campylobacter and Salmonella in the broiler meat chain in Ecuador. To fulfill this objective, we assessed the prevalence and characterized these pathogens in broiler batches at slaughter age and studied the contamination dynamics during the slaughter of Campylobacter positive batches in commercial slaughterhouses. Chapter 1 and Chapter 2 focus on Salmonella and Campylobacter, for which samples from 388 and 379 broiler batches respectively were collected and analyzed by genotypic and phenotypic techniques. Salmonella prevalence at batch level was 16.0%. The most common serotype was S. Infantis (83.9%). S. Infantis isolates showed high resistance rates to 12 antibiotics ranging from 57.7% (kanamycin) up to 98.1% (nalidixic acid and sulfamethoxazole). The prevalence of Campylobacter at batch level was 64.1% and C. coli (68.7%) was the most common species. MIC values showed resistance rates above 67% for tetracycline, ciprofloxacin and nalidixic acid. Genotypic characterization of both pathogens demonstrated that they are widely distributed in farms. In Chapter 3, the dynamics of Campylobacter contamination were studied in three slaughterhouses. The impact of evisceration, final washing and water chilling was evaluated by quantifying Campylobacter contamination. No significant differences were found between Campylobacter counts after evisceration and after final washing, denoting a lack of efficiency of this step. In all slaughterhouses, a significant reduction of Campylobacter counts was found after the chilling step. We reported that S. Infantis and C. coli were the most prevalent ones, which differs from what is reported in other Latin American countries. High resistance rates to antibiotics used in human medicine were found in these pathogens. This could be provoked by the extensive use of antimicrobials in poultry production and might pose a human health concern. The attribution of S. Infantis and C. coli to human infections need further research. Evaluation of Campylobacter counts at slaughterhouses showed that final washing and addition of chlorine in chilling water may be used to decrease Campylobacter numbers on carcasses. This thesis represents the first study on the epidemiology of Campylobacter and Salmonella in the poultry meat chain in Ecuador.
Roles of the Immune Cytokine Environment on Clonal Growth of Murine and Human Tet2 Mutant Bone Marrow Progenitors: Implications for Myelodysplastic Syndromes

ii Acknowledgements.iv Table of contents.v List of Figures.ix List of Tables . xi Lists of Abbreviations . xii Dedication.xviii CHAPTER ONE: INTRODUCTION AND LITERATURE REVIEW 1.1 Clinical Burden of Myelodysplastic Syndromes. 1 1.2 Molecular basis of Cancer 2 1.3 Somatic Mutations in MDS 2 1.4 Epigenetic Regulators-3 1.5 TET Family, Tet2 Structure and Functions-4 1.6 Regulation of Tet2 expression12 1.7 Normal Hematopoiesis13 1.8 Tet2 in Hematopoiesis15 1.9 Tet2 Mutations-16 1.10 Cytokines in Normal Haematopoiesis.19 1.11. Chronic Inflammation in Myeloid Cancers-20
Histamine Level in Fishmeal and Shrimp Feed Marketed in India

Twenty-five samples each of fishmeal and shrimp feed collected from the East and West coasts of India were screened for the level of histamine, total plate count and load of histamine forming bacteria. The average level of histamine in fishmeal samples was 138.2 µg . g -1 and in the shrimp feed samples 191 µg . g -1 . Levels exceeding 200 µg . g -1 were observed in 4/25 samples of fishmeal and 11/25 samples of shrimp feed. The average bacterial load in fishmeal and shrimp feed samples was 1.08 x 10 6 and 1.13 x 10 6 cfu . g -1 respectively. Bacillus, Staphylococcus and Micrococcus were the major genera of bacteria isolated. The effect of feeding Penaeus monodon larvae with a diet containing histamine on the susceptibility to infection by V.alginolyticus was studied. There was no significant difference in the LD 50 between the treated and untreated larvae.
The effects of formoterol on the serum, peritoneal VEGF, MDA, and VEGF levels in the ovaries and endometrium of rats with OHSS

PURPOSE: To investigate the effects of formoterol (a beta2-adrenoreceptor agonist) on serum and peritoneal fluid VEGF, malondialdehyde (MDA) levels, and on VEGF-stained cell counts in the ovaries and endometrium of rats with ovarian hyperstimulation syndrome (OHSS) within the framework of immunohistochemical analysis. MATERIALS AND METHODS: A total of 28 immature female Wistar rats were randomly divided into four groups. Three groups were given ten IU pregnant mare serum gonadotropin/day on days 22-25 of life. They were administered 30 IU hCG on day 26 of life to mimic OHSS. On days 26 and 27 of life, 24 mcg/kg/day formoterol in group 3 and 48 mcg/kg formoterol in group 4 were administered intraperitoneally per animal. RESULTS: Although, there were no statistically significant differences between the groups in terms of serum and peritoneal fluid VEGF or MDA levels (serum VEGF: p = 0.28 1, peritoneal VEGF: p = 0.674, serum MDA: p = 0.543, peritoneal MDA: p = 0.506), there was a significant difference between the control and the OHSS placebo groups (p = 0.013) regarding the VEGF in the ovarian cortex. There was a significant difference between the control and the other groups in terms of ovarian stroma (p = 0.001), and there was also a statistically significant difference between the OHSS placebo and the other groups regarding VEGF in the endometrium (OHSS placebo vs. control group p = 0.002, OHSS placebo vs. the formoterol 24 mcg/kg group, p = 0.008, and OHSS-placebo vs. the formoterol 48 mcg/kg group, p = 0.001). CONCLUSIONS: Formoterol represents a potential novel strategy for the management of OHSS. Further studies, including those examining the dosage of formoterol, are warranted.
Long-term Trends and Influencing Factors of Glomerular Filtration Rate

Purpose: This study assessed chronic kidney disease (CKD) in Pingtung, Taiwan as indicated by the annual changes glomerular filtration rate (GFR) and risk factors of estimated glomerular filtration rate (eGFR). Methods: This study utilized longitudinal data analysis to examine the 2011-2013 medical checkup results for adult at a Pingtung hospital. The participants' general information, physical examination results, and blood test results were analyzed. eGFR was calculated via the abbreviated modification of diet in renal disease (aMDRD) formula and used to determine eFGR stages based on the 2002 Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines. Results: Data from a total of 9,702 participants were analyzed in this study. This study indicated that in Pingtung, from 2011 to 2013, male, aged ≧ 65 years and those who have metabolic syndrome and its components are abnormal have lower eGFR. Multiple linear regression analysis was applied to examine the risk factors influencing eGFR. The results showed lower eGFR in males, participants aged 65 and over, participants with metabolic syndrome, blood pressure, waist 1 Pingtung Christian Hospital, the Division of Nephrology, Pingtung County, Taiwan. 2 Pingtung Christian Hospital, Nursing Department, Pingtung County, Taiwan. 3 Department of Health Business Administration, Meiho University, Pingtung County, Taiwan. 4 Department of Physical Therapy, Tzu Hui Institute of Technology, Taiwan. 5 Department of Nursing, Meiho University, Pingtung County, Taiwan. Article Info: Received: May 29, 2016. Revised: June 16, 2016. Published online : July 15, 2016. 46 HaoHuan Huet al. circumference, and triglyceride level abnormalities. Conclusion: Predictors of eGFR decline included male gender, age of 65 years and over, metabolic syndrome, and abnormal blood pressure, waist circumference, and triglyceride levels.
Modeling and Control of Hybrid Ventilation in a Building With Double Skin Façade

The development of an accurate control of hybrid ventilation which combines the strengths of natural ventilation and mechanical ventilation relies on better energy efficiency and healthy Indoor Air Quality (IAQ) in buildings. This paper focuses on development of mathematical models for natural ventilation and mechanical ventilation through the use of temperature differences, and on design of a control strategy for hybrid ventilation that switches between control actions for both ventilation modes to optimize energy consumption while maintaining IAQ and thermal comfort at the desired setpoints. These control actions are developed to automatically adjust the position of motorized dampers at the button of the cavity, the position of the motorized windows of the test-cell, and turn on the air-supply fan only when needed. The paper ends with a demonstration and discussion of real experiments on the flexibility and effectiveness of the proposed control strategy for hybrid ventilation in the test-cell building case study.
Comparative Analysis of Multi-Step Time-Series Forecasting for Network Load Dataset

Increased usage of telecommunication networks leads to errors and congestion problems. Prediction of network load well in time can greatly help network operators in avoiding network problems. However, little is known about how different multi-step ahead prediction approaches would perform in predicting long-range variables in telecommunication data sets. In this paper, we use statistical algorithm, auto-regressive integrated moving average (ARIMA) and machine learning algorithms, multi-layer perceptron (MLP) and long short term memory (LSTM) to perform multi-step ahead prediction of network bandwidth utilization. We propose to compare different approaches such as recursive, direct, multiple-in multiple-out (MIMO), and variations of these approaches to perform multi-step ahead prediction of the network bandwidth utilization 1-hour, 2-hour, and 3-hour ahead in time. Results revealed that the direct approach performed better for 1-hour ahead predictions and MIMO for 2 and 3- hours ahead predictions. Also, all three predictive algorithms benefited from the multi-step approaches. We highlight the implication of our results for long-range predictions in telecommunication network.
Estimation of Energy Minimizing Series Elastic Spring Stiffness for an Active Knee Prosthesis

Minimizing the mechanical motor output work or power required to create the desired actuator behavior in a quasi-static manner is a widely used, but incomplete method for actuator design. Here we use a dynamic electric and mechanical motor model combined with constrained output kinematics to find spring parameters for an active knee prosthesis using a series elastic actuator. This simulation was used to examine the landscape of motor torque tracking ability, motor electrical consumption, and the mechanical output of the system to determine spring stiffness ranges that should be further examined in the real device. Even though the task is negative net work, the actuator seems to benefit from having a elastic design, with a range of stiffness that improve energy consumption and torque tracking compared to a stiff device.
Facial Recognition Development to Detect Corporate Employees Stress Level

Technology has developed so well even to the point where machines can recognize our faces. There many APIs and algorithms out there that can recognize human faces. These APIs or algorithms is called Artificial Intelligence or AI. As modern civilian life in modern society, AI has been used so many times and developed into something more. This time, we proposed an idea to recognize motions and emotions on human faces to detect their stress levels. Companies nowadays need to have something that can know how their employees are feeling or think about their work. This program works by taking an image input from mounted cameras on the office’s monitor. However, before that, the program must have been trained first to recognize faces and emotions. For this, the eigenfaces algorithm is used. After the input is received, then the program will process the image received and extract the features from the images such as eyes, nose, mouth, etc. to detect if there are faces and also the emotions of the face. After that, the features extracted will be matched with the features in the database to give an output of the percentage of stress.
Sparsity-Driven ISAR Imaging Based on Two-Dimensional ADMM

Compressed sensing (CS) can achieve high resolution inverse synthetic aperture radar (ISAR) imaging of moving targets with limited measurements. Recently, alternating direction method of multipliers (ADMM) has been introduced to solve the optimization problem for one dimensional (1D) sparse signal recovery. The main drawback of 1D sparsity-driven algorithms are the high memory usage and the computational complexity. Thus, in this paper a novel two dimensional (2D) ADMM approach is presented which can be directly applied to the ISAR model in matrix form, and needs lower memory and computations compared to the 1D algorithm. Moreover, the performance of the 2D-ADMM method is better than the 2D smoothed L0 (2D-SL0) and 2D gradient projection sequential order one negative exponential (2D-GP-SOONE) algorithms in different signal-to-noise ratio (SNR) conditions and sampling rates. Joint simulations and measured data results based on real data of Yak-42 airplane, validate the superiority of the proposed approach.
Comparative study regarding the integration of photovoltaic sources in agriculture

This article presents a three-year comparative study regarding the amount of energy produced by a photovoltaic park located in an agricultural area of the country. The objective of this article is to make a performance analysis for a photovoltaic power plant that could be used to power the irrigation systems present in the area. The study aims the efficiency of the photovoltaic power plant by comparing the energy performances, obtained in an unfavorable period of the year, during three consecutive years. The results obtained demonstrate the advantage of using photovoltaic panels necessary to supply electricity at affordable prices for farmers.
AI Based Intrusion Detection System Using Self-Adaptive Energy Efficient BAT Algorithm for Software Defined IoT Networks

A software defined IoT network can be considered as global controller managing all the tasks of the network like resource sharing, traffic management and effective utilization of individual IoT devices connected to the network. As the network involves transmission of potential data intrusions and other vulnerabilities may arise. Traditional systems uses a standard dataset and uses evolutionary and population based algorithms for feature selection like BAT and well known classification algorithms to classify traffic as normal or attack. We propose a novel self-adaptive energy efficient BAT algorithm for achieving optimization in BAT Algorithm for Feature selection. Existing system uses swarm division for dataset clustering. But when the network traffic increases the number of features increases and non-continuous features will result. Hence swarm division doesn't works well. So a self-adaptive parallel processing strategy with energy efficiency is proposed which optimizes the existing BAT algorithm. To handle complex batch process loops within BAT algorithms, a fitness based task parallelism is implemented to get the most benefit in terms of scalability and energy efficiency.
A Concentration-Based Drift Calibration Transfer Learning Method for Gas Sensor Array Data

The practical use of electronic nose (e-nose) systems suffers from drift issue, which alters data distribution and reduces the accuracy of classification. This letter proposes a transfer learning method called concentration-based drift calibration (CDC) for calibrating the sensor drift. Based on the sensor characteristic that sensor response is correspondent to gas concentration, transfer samples were collected in the target domain for certain gas concentrations and then used for calibration with a designed concentration-based model and CDC transfer process. This method was evaluated on a complex time-varying drift dataset. The experimental results show that the proposed method for drift calibration is effective and can be used for real-world applications. Moreover, the CDC transfer process can be applied over time with data that has been previously collected to yield a more generalized model.
Motion Planning for Active Prosthetic Knees

A main challenge in the development of active prosthetic knees is how to determine (estimate) the required motion of the missing joint/limb in line with the motion of the remaining biological ones. To do so, a motion planner is required. This study proposes a motion planner for active prosthetic knees. Two inputs (thigh angular velocities and angles obtained from IMU) are used to estimate the corresponding knee joint positions for walking at 0.6, 0.9, 1.2, 1.4 and 1.6 m/s. The motion planner does not require speed estimation, gait percent identification, or switching rules and estimates the outputs (knee joint positions) continuously. This is achieved through a functional (y=f(x)) approach. The strengths and limitations of the proposed motion planner are evaluated at different scenarios.
Taze ve İşlenmiş Gümüş Balığının (Atherina boyeri Risso, 1810) Mikrobiyolojik Kalitesi.

Bu calismada, bir tatli su baligi olan ve yogun olarak ihracati yapilan gumus baliginin (Atherina boyeri Risso,1810) mikrobiyolojik kalitesi incelenmistir. Taze, donmus ve panelenerek dondurulmus uc urune ait numunelerde, hijyenik kalite adina toplam aerobik bakteri sayisi, Koliform grubu ve fekal Streptococcus bakterileri arastirilmistir. Elde edilen sonuclarda, urunler arasinda Koliform grubu ve fekal Streptococcus bakteri iceriginde farkliliklar tespit edilmis, toplam aerobik bakteri sayisinda ise urunler arasinda bariz bir farkliliga rastlanmamistir. Taze, donmus ve panelenerek dondurulmus gumus baligi urunlerinde toplam aerobik bakteri sayisi 4,1x104 – 9,8x104 kob/g arasinda tespit edilmistir. Koliform grubu bakteri icerigi donmus urunlerde
Do fruit morphology and scarification affect germination and predation rates of Babassu seeds

Seed predation is a natural phenomenon that can occur either before or after dispersal and can significantly reduce the economic value and reproductive potential of plants. The babassu palm (Attalea vitrivir, Arecaceae) is important to rural communities that extract oil from its fruits for a wide variety of uses. We evaluated the predation and germination of A. vitrivirseeds in Pandeiros River Environmental Protection Area (EPA-Pandeiros) in Minas Gerais State, Brazil. Sixty individual plants were evaluated to determine their fruiting patterns. Seed predation and germination were evaluated in the natural environment for eight months for fruits divided into two treatments: scarified and intact. Germination of fruits submitted to these same treatments was also evaluated under greenhouse conditions. Our results indicated that fruiting is continuous in this species and that fruit morphology does not influence either germination or predation. Likewise, fruit scarification did not influence seed germination. Pachymerus cardo (Coleoptera: Chrysomelidae) preferentially oviposited on scarified fruits, but only after their dispersal. The predation rate in the natural environment was 14.6%. Germination was not observed under natural conditions, but reached 33.05% under greenhouse conditions.
Optimization and Validation of Dual Element Ultrasound Transducers for Improved Pulse-Echo Measurements of Material Nonlinearity

In nonlinearity parameter (<inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>) measurements of solids, the pulse-echo method is more desirable than the through-transmission method. Dual element transducers consisting of an outer ring transmitter and an inner disk receiver have been found to be an efficient alternative to single element transducers because such configuration provides an improved second harmonic generation and dependence on the total correction in the pulse-echo mode. For accurate and reliable measurements of <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> for relatively thin samples, further improvement is needed by optimizing the transmitter and receiver size of dual element transducers for a given sample thickness and frequency. The optimized transducer should provide the largest possible second harmonic reception and a total correction value close to one. In this paper, optimization of the dual element transducer is performed for 1 cm thick Al specimen at 5 MHz fundamental frequency, and the results are presented for the received second harmonic amplitude and the total correction. The optimized dual element transducer is fabricated and experimentally characterized to be applied to determine the absolute <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> of Al specimens whose microstructure changes due to precipitation heat treatment. The experimental results validate the transducer optimized for pulse-echo <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> measurements on 1 cm specimens, and provide a quantitative correlation between the <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> and the microstructural change.
Examining the usage of and access to online databases for academic purposes: A study at an engineering- and technology-based university in Malaysia

In higher learning processes, information and reference sources are considered significant to both students and staff of higher education institutions (HEIs) in gathering references and reviewing literatures. Currently, students and staff tend to obtain or access references from the online databases and electronic resources provided by their university’s libraries. In this study, we examine the number and titles of online databases that are most frequently searched, viewed and downloaded by students and staff for academic purposes. Data were obtained from the annual reports published by the university’s library between 2014 and 2017. Findings revealed a high percentage of usage and access per year, which clearly indicates that the students and staff of the university are aware of the online databases provided by the university’s library. It was also found that the five titles accessed most frequently by the university’s students and staff were: IEEE Xplore Digital Library, ScienceDirect, EdITLib, Datastream and Scopus. In light of these findings, it is recommended that librarians should continuously encourage active and efficient usage of online databases among the students and staff, especially for academic purposes.