Trends, Sociodemographic and Hospital-Level Factors Associated with Palliative Care Utilization Among Metastatic Prostate Cancer Patients.

Background: Several factors are reported to be associated with palliative care utilization among patients with various cancers, but literature is lacking on metastatic prostate cancer (MPC) specific factors. Early integration of palliative care in management of MPC patients could increase their quality of life and overall outcomes. Methods: Retrospective longitudinal analyses were conducted using the National Inpatient Sample (NIS) data (2010 - 2019). Prevalence trends in palliative care utilization were assessed, and sociodemographic and hospital-level factors associated with palliative care utilization in MPC patients were examined. Results: The overall prevalence of palliative care utilization was 13.1% with an increasing trend from 8490 to 15,231 per 100,000 MPC admissions (p-trend <.001). MPC patients aged 65 years and above had similar odds of receiving palliative care compared to younger patients. Relative to non-Hispanic Whites, other racial groups had similar likelihood to utilize palliative care services. Patients in higher median household national income quartiles had greater odds of utilizing palliative care relative to those in the first income quartile. Patients on Medicaid, private insurance and other insurance types had greater odds of palliative care use in comparison to those on Medicare. Other factors identified were hospital region, location and teaching status, patient disposition, admission type, length of stay, and number of comorbidities. Conclusion: Our findings underscore the significance of enhanced government policies and institutional support in improving palliative care use among hospitalized MPC patients. Health systems must be proactive in addressing barriers to optimization of palliative care utilization in this population.

Analysis of land use and land cover change using machine learning algorithm in Yola North Local Government Area of Adamawa State, Nigeria.

The dynamic use of land that results from urbanization has an impact on the urban ecosystem. Yola North Local Government Area (Yola North LGA) of Adamawa state, Nigeria, has experienced tremendous changes in its land use and land cover (LULC) over the past two decades due to the influx of people from rural areas seeking for the benefits of its economic activities. The goal of this research is to develop an efficient and accurate framework for continuous monitoring of land use and land cover (LULC) change and quantify the transformation in land use and land cover pattern over a specific period (between 2002 and 2022). Land sat images of 2002, 2012, and 2022 were obtained, and the Support Vector Machine classification method was utilized to stratify the images. Land Change Modeler (LCM) tool in Idrissi Selva software was then used to analyze the LULC change. SVM produced a good classification result for all three years, with 2022 having the highest overall accuracy of 95.5%, followed by 2002 with 90% and 2012 with 87.7% which indicates the validity of the algorithm for future predictions. The results showed that severe land changes have occurred over the course of two decades in built-up (37.32%), vegetation (forest, scrubland, and grassland) (-3.27%), bare surface (-33.47%), and water bodies (-0.59%). Such changes in LULC could lead to agricultural land lost and reduced food supply. This research develops a robust framework for continuous land use monitoring, utilizing machine learning and geo-spatial data for urban planning, natural resource management, and environmental conservation. In conclusion, this study underscores the efficacy of support vector machine algorithm in analyzing complex land use and land cover changes.

Seroprevalence of SARS-CoV-2 in Niger State: Pilot Cross-Sectional Study.

Background: The COVID-19 pandemic caused by SARS-CoV-2 is causing ongoing human and socioeconomic losses. Objective: To know how far the virus has spread in Niger State, Nigeria, a pilot study was carried out to determine the SARS-CoV-2 seroprevalence, patterns, dynamics, and risk factors in the state. Methods: A cross-sectional study design and clustered, stratified random sampling strategy were used to select 185 test participants across the state. SARS-CoV-2 IgG and IgM rapid test kits (colloidal gold immunochromatography lateral flow system) were used to determine the presence or absence of antibodies to the virus in the blood of sampled participants across Niger State from June 26 to 30, 2020. The test kits were validated using the blood samples of some of the Nigeria Center for Disease Control-confirmed positive and negative COVID-19 cases in the state. SARS-CoV-2 IgG and IgM test results were entered into the Epi Info questionnaire administered simultaneously with each test. Epi Info was then used to calculate the arithmetic mean and percentage, odds ratio, χ2 statistic, and regression at a 95% CI of the data generated. Results: The seroprevalence of SARS-CoV-2 in Niger State was found to be 25.4% (47/185) and 2.2% (4/185) for the positive IgG and IgM results, respectively. Seroprevalence among age groups, genders, and occupations varied widely. The COVID-19 asymptomatic rate in the state was found to be 46.8% (22/47). The risk analyses showed that the chances of infection are almost the same for both urban and rural dwellers in the state. However, health care workers, those who experienced flulike symptoms, and those who had contact with a person who traveled out of Nigeria in the last 6 months (February to June 2020) were at double the risk of being infected with the virus. More than half (101/185, 54.6%) of the participants in this study did not practice social distancing at any time since the pandemic started. Participants' knowledge, attitudes, and practices regarding COVID-19 are also discussed. Conclusions: The observed Niger State SARS-CoV-2 seroprevalence and infection patterns meansuggest that the virus has widely spread, far more SARS-CoV-2 infections have occurred than the reported cases, and there is a high asymptomatic COVID-19 rate across the state.

Healthcare professionals' perceived stigmatization about direct care of COVID-19 Patients: development and validation of the discrimination about COVID-19 (DisCOV-19) instrument

Background: The novel coronavirus disease 2019 (COVID-19) is a public health concern worldwide. Healthcare professionals are among the most vulnerable groups in the fight against COVID-19 because they are directly involved in the care of at-risk persons and patients with Covid-19. Objectives: This study aimed to measure the level to which healthcare workers feel that they can be discriminated due to their involvement in the direct care of COVID-19 patients. Methods: A cross-sectional online survey was conducted among healthcare professionals in Nigeria. A nineteen-item discrimination against COVID-19 (DisCOV-19) questionnaire was developed and validated for the study. Descriptive statistics and OneWay Analysis of Variance were used for data analysis. P<0.05 was considered statistically significant. Results: Out of the 286 healthcare practitioners that participated in the study, 58.4% and 30.1% were pharmacists and physicians, respectively. The majority of the participants were at least "moderately concerned" about disability (60.9%), death (71.7%), unknown complications (65.1%), and risk of infecting family members and friends (83.2%) if asked to provide care for COVID-19 patients. The physicians had a significantly higher mean discrimination score compared to the pharmacists (p=0.041). Pharmacists had a significantly lower mean discrimination score than the nurses (p=0.011). Conclusions: Many of the healthcare professionals reported a certain level of concern and perceived that they could face some forms of discrimination for providing care to COVID-19 patients

Healthcare professionals' perceived stigmatization about direct care of COVID-19 Patients: development and validation of the discrimination about COVID-19 (DisCOV-19) instrument.

Background: The novel coronavirus disease 2019 (COVID-19) is a public health concern worldwide. Healthcare professionals are among the most vulnerable groups in the fight against COVID-19 because they are directly involved in the care of at-risk persons and patients with Covid-19. Objectives: This study aimed to measure the level to which healthcare workers feel that they can be discriminated due to their involvement in the direct care of COVID-19 patients. Methods: A cross-sectional online survey was conducted among healthcare professionals in Nigeria. A nineteen-item discrimination against COVID-19 (DisCOV-19) questionnaire was developed and validated for the study. Descriptive statistics and One-Way Analysis of Variance were used for data analysis. P<0.05 was considered statistically significant. Results: Out of the 286 healthcare practitioners that participated in the study, 58.4% and 30.1% were pharmacists and physicians, respectively. The majority of the participants were at least "moderately concerned" about disability (60.9%), death (71.7%), unknown complications (65.1%), and risk of infecting family members and friends (83.2%) if asked to provide care for COVID-19 patients. The physicians had a significantly higher mean discrimination score compared to the pharmacists (p=0.041). Pharmacists had a significantly lower mean discrimination score than the nurses (p=0.011). Conclusions: Many of the healthcare professionals reported a certain level of concern and perceived that they could face some forms of discrimination for providing care to COVID-19 patients.

Recent Advancements in Emerging Technologies for Healthcare Management Systems: A Survey.

In recent times, the growth of the Internet of Things (IoT), artificial intelligence (AI), and Blockchain technologies have quickly gained pace as a new study niche in numerous collegiate and industrial sectors, notably in the healthcare sector. Recent advancements in healthcare delivery have given many patients access to advanced personalized healthcare, which has improved their well-being. The subsequent phase in healthcare is to seamlessly consolidate these emerging technologies such as IoT-assisted wearable sensor devices, AI, and Blockchain collectively. Surprisingly, owing to the rapid use of smart wearable sensors, IoT and AI-enabled technology are shifting healthcare from a conventional hub-based system to a more personalized healthcare management system (HMS). However, implementing smart sensors, advanced IoT, AI, and Blockchain technologies synchronously in HMS remains a significant challenge. Prominent and reoccurring issues such as scarcity of cost-effective and accurate smart medical sensors, unstandardized IoT system architectures, heterogeneity of connected wearable devices, the multidimensionality of data generated, and high demand for interoperability are vivid problems affecting the advancement of HMS. Hence, this survey paper presents a detailed evaluation of the application of these emerging technologies (Smart Sensor, IoT, AI, Blockchain) in HMS to better understand the progress thus far. Specifically, current studies and findings on the deployment of these emerging technologies in healthcare are investigated, as well as key enabling factors, noteworthy use cases, and successful deployments. This survey also examined essential issues that are frequently encountered by IoT-assisted wearable sensor systems, AI, and Blockchain, as well as the critical concerns that must be addressed to enhance the application of these emerging technologies in the HMS.

Look Beyond the Cataract: A Case Report on Alport Syndrome.

Alport syndrome is an inherited disease with a trio of hearing loss, ocular abnormalities, and progressive renal failure. The most severe form is commonest in males due to the X-linked mutations. We present a 25-year-old male who presented with deterioration of vision over 5 years, further questioning revealed use of hearing aid. Although he had no renal-related complaints, investigation revealed proteinuria. There is a need for proper examination of developmental cataract to avoid missing out on Alport syndrome.

A Novel Rank Aggregation-Based Hybrid Multifilter Wrapper Feature Selection Method in Software Defect Prediction.

The high dimensionality of software metric features has long been noted as a data quality problem that affects the performance of software defect prediction (SDP) models. This drawback makes it necessary to apply feature selection (FS) algorithm(s) in SDP processes. FS approaches can be categorized into three types, namely, filter FS (FFS), wrapper FS (WFS), and hybrid FS (HFS). HFS has been established as superior because it combines the strength of both FFS and WFS methods. However, selecting the most appropriate FFS (filter rank selection problem) for HFS is a challenge because the performance of FFS methods depends on the choice of datasets and classifiers. In addition, the local optima stagnation and high computational costs of WFS due to large search spaces are inherited by the HFS method. Therefore, as a solution, this study proposes a novel rank aggregation-based hybrid multifilter wrapper feature selection (RAHMFWFS) method for the selection of relevant and irredundant features from software defect datasets. The proposed RAHMFWFS is divided into two stepwise stages. The first stage involves a rank aggregation-based multifilter feature selection (RMFFS) method that addresses the filter rank selection problem by aggregating individual rank lists from multiple filter methods, using a novel rank aggregation method to generate a single, robust, and non-disjoint rank list. In the second stage, the aggregated ranked features are further preprocessed by an enhanced wrapper feature selection (EWFS) method based on a dynamic reranking strategy that is used to guide the feature subset selection process of the HFS method. This, in turn, reduces the number of evaluation cycles while amplifying or maintaining its prediction performance. The feasibility of the proposed RAHMFWFS was demonstrated on benchmarked software defect datasets with Naïve Bayes and Decision Tree classifiers, based on accuracy, the area under the curve (AUC), and F-measure values. The experimental results showed the effectiveness of RAHMFWFS in addressing filter rank selection and local optima stagnation problems in HFS, as well as the ability to select optimal features from SDP datasets while maintaining or enhancing the performance of SDP models. To conclude, the proposed RAHMFWFS achieved good performance by improving the prediction performances of SDP models across the selected datasets, compared to existing state-of-the-arts HFS methods.

Design of a FAIR digital data health infrastructure in Africa for COVID-19 reporting and research.

The limited volume of COVID-19 data from Africa raises concerns for global genome research, which requires a diversity of genotypes for accurate disease prediction, including on the provenance of the new SARS-CoV-2 mutations. The Virus Outbreak Data Network (VODAN)-Africa studied the possibility of increasing the production of clinical data, finding concerns about data ownership, and the limited use of health data for quality treatment at point of care. To address this, VODAN Africa developed an architecture to record clinical health data and research data collected on the incidence of COVID-19, producing these as human- and machine-readable data objects in a distributed architecture of locally governed, linked, human- and machine-readable data. This architecture supports analytics at the point of care and-through data visiting, across facilities-for generic analytics. An algorithm was run across FAIR Data Points to visit the distributed data and produce aggregate findings. The FAIR data architecture is deployed in Uganda, Ethiopia, Liberia, Nigeria, Kenya, Somalia, Tanzania, Zimbabwe, and Tunisia.

A Survey of Iranian Retracted Publications Indexed in PubMed.

BACKGROUND: Retraction is a mechanism for correcting the literature and a warning for readers in relation to publications that contain serious flaws or erroneous data. As a result of growth and development of Iranian publications in the last two decades, that brings unethical behavior of researchers led to retraction of their publications. We aimed to investigate Iranian retracted publications indexed in PubMed database. METHODS: All Iranian retracted publications published in PubMed up to Dec 2017 have been retrieved. Bibliographic information of retracted publications, retraction notice, time lag between article publication date and the date of retraction notice, reasons of retraction, Issuer of retraction and acknowledge information of retracted publication were recorded. Additionally, citation data of retracted publications before 2013 were analyzed. RESULTS: Overall, 164 Iranian retracted publications were identified. Meantime lag was 20.8 months. "Islamic Azad University" and "Tehran University of Medical Sciences (TUMS)" were two affiliations that have received highest number of retracted publications. The most issuer of retraction publications was editor-in-chief and the most mentioned reasons for retractions were authorship issues, plagiarism, and redundant publication. Thirty-three (20.12%) publications have received funds from various agencies. Citation study of retracted publications indicates that these publications have received 789 citations (Citation per publication=11.6). CONCLUSION: Although Iranian retracted publications represent small portion of all Iranian publications, but the number of retracted publications has increased. More than half of retracted publications have had authorship issues and plagiarism that requires more attention to research ethics authorities.

Application of the Gaussian Mixture Model to Classify Stages of Electrical Tree Growth in Epoxy Resin.

In high-voltage (HV) insulation, electrical trees are an important degradation phenomenon strongly linked to partial discharge (PD) activity. Their initiation and development have attracted the attention of the research community and better understanding and characterization of the phenomenon are needed. They are very damaging and develop through the insulation material forming a discharge conduction path. Therefore, it is important to adequately measure and characterize tree growth before it can lead to complete failure of the system. In this paper, the Gaussian mixture model (GMM) has been applied to cluster and classify the different growth stages of electrical trees in epoxy resin insulation. First, tree growth experiments were conducted, and PD data captured from the initial to breakdown stage of the tree growth in epoxy resin insulation. Second, the GMM was applied to categorize the different electrical tree stages into clusters. The results show that PD dynamics vary with different stress voltages and tree growth stages. The electrical tree patterns with shorter breakdown times had identical clusters throughout the degradation stages. The breakdown time can be a key factor in determining the degradation levels of PD patterns emanating from trees in epoxy resin. This is important in order to determine the severity of electrical treeing degradation, and, therefore, to perform efficient asset management. The novelty of the work presented in this paper is that for the first time the GMM has been applied for electrical tree growth classification and the optimal values for the hyperparameters, i.e., the number of clusters and the appropriate covariance structure, have been determined for the different electrical tree clusters.

Seroprevalence of Trypanosoma evansi in camels using CATT/T. evansi technique in Borno and Yobe states, Nigeria.

Trypanosoma evansi is an important camel pathogen with dissimilar mammalian hosts and is the most widely distributed pathogenic animals' trypanosomes worldwide that affects domesticated animals. Four hundred and six blood samples were collected using homogeneous purposive sampling techniques from camels of all age groups (206 from Borno State and 200 from Yobe State, Nigeria). Each animal was examined and information on age and gender were recorded. The card agglutination test for T. evansi (CATT/T. evansi) was used to estimate the seroprevalence of T. evansi infection. The seroprevalence of T. evansi based on age and sex in Borno State, Nigeria was 38.83% (95% CI = 32.44%, 45.63%) in adult camels, whereas, the seroprevalence of T. evansi in young camels was significantly lower 2.91%, (95% CI = 1.34%, 6.20%), p < 0.05). The seroprevalence of T. evansi in male camels was estimated at 14.08% (95% CI = 9.99, 19.49) whereas, in female camels the seroprevalence was estimated at 27.67% (95% CI = 22.01%, 34.15%, p < 0.05). Furthermore, the seroprevalence of T. evansi in Yobe State, Nigeria in the adult camels was 27.50% (95% CI = 21.78%, 34.07%) whereas, the seroprevalence of T. evansi in young camels was 19.00%, (95% CI = 14.17%, 25.00%). The seroprevalence of T. evansi in male camels was 30.0% (95% CI = 24.07%, 36.68%), whereas, the seroprevalence of T. evansi in female camels was 16.5% (95% CI = 12.00%, 22.27%). Therefore, the present study aimed to provide information on the seroprevalence of T. evansi and the related risk factors in camels in Borno and Yobe States, Nigeria using CATT/T. evansi technique.

Seroprevalence of COVID-19 in Niger State

BackgroundCoronavirus Disease 2019 (COVID-19) Pandemic caused by SARS-CoV-2 is ongoing causing human and socioeconomic losses. ObjectiveTo know how far the virus has spread in Niger State, Nigeria, a pilot study was carried out to determine the SARS-CoV-2 seroprevalence, patterns, dynamics, and risk factors in the state. MethodsA cross sectional study design and Clustered-Stratified-Random sampling strategy were used to select 185 test participants across the state. SARS-CoV-2 IgG and IgM Rapid Test Kits (Colloidal gold immunochromatography lateral flow system) were used to determine the presence or absence of the antibodies to the virus in the blood of sampled participants across Niger State as from 26th June 2020 to 30th June 2020. The test kits were validated using the blood samples of some of the Nigeria Center for Disease Control (NCDC) confirmed positive and negative COVID-19 cases in the State. SARS-CoV-2 IgG and IgM Test results were entered into the EPIINFO questionnaire administered simultaneously with each test. EPIINFO was then used for to calculate arithmetic mean and percentage, odd ratio, chi-square, and regression at 95% Confidence Interval of the data generated. ResultsThe seroprevalence of SARS-CoV-2 in Niger State was found to be 25.41% and 2.16% for the positive IgG and IgM respectively. Seroprevalence among age groups, gender and by occupation varied widely. COVID-19 asymptomatic rate in the state was found to be 46.81%. The risk analyses showed that the chances of infection are almost the same for both urban and rural dwellers in the state. However, health care workers, those that experienced flu-like symptoms and those that have had contact with person (s) that travelled out of Nigeria in the last six (6) months (February -June 2020) are twice (2 times) at risk of being infected with the virus. More than half (54.59%) of the participants in this study did not practice social distancing at any time since the pandemic started. Discussions about knowledge, practice and attitude of the participants are included. ConclusionThe observed Niger State SARS-CoV-2 seroprevalence and infection patterns means that the virus is widely spread, far more SARS CoV-2 infections occurred than the reported cases and high asymptomatic COVID-19 across the state.

Personality and Subjective Well-Being: Towards Personalized Persuasive Interventions for Health and Well-Being.

Subjective well-being (SWB) is an individual's judgment about their overall well-being. Research has shown that activities that elevate people's sense of SWB have a significant effect on their overall health. There are two dimensions of SWB: Affective and Cognitive dimensions. However, studies on SWB usually focus more on one dimension, ignoring the other dimension. Also, most existing studies on SWB focused on individuals from Western cultures. Research has shown that the influence of personality on subjective well-being is moderated by culture. Thus, to advance research in personalizing persuasive health interventions, this study focuses on Africans (n=732). Specifically, we investigate the relationship between the Big-Five personality traits and both dimensions of SWB using the constructs: Happiness, Satisfaction with Life, Social, Psychological and Emotional well-being. Our results reveal that health informatics designers who design persuasive technologies to promote SWB would need to tailor designs along personality traits and SWB constructs. Accordingly, for users high in Agreeableness, the design should be focus on promoting their feelings of Happiness and Social Well-being. For users who exhibit Neuroticism, designers should focus on designing to promote Psychological well-being and Emotional well-being. Based on our findings, we offer guidelines for tailoring persuasive health interventions to promote individuals' SWB based on their personality. We thus highlight areas personal health informatics design can benefit. CCS CONCEPTS: • Human-centered computing → Personalization → HCI design and evaluation methods → User models.

Blood of African Hedgehog Atelerix albiventris Contains 115-kDa Trypanolytic Protein that Kills Trypanosoma congolense.

INTRODUCTION: Protozoan parasites of the Order Trypanosomatida infect a wide range of multicellular plants and animals, causing devastating and potentially fatal diseases. Trypanosomes are the most relevant members of the order in sub-Saharan Africa because of mortalities and morbidities caused to humans and livestock. PURPOSE: There are growing concerns that trypanosomes are expanding their reservoirs among wild animals, which habours the parasites, withstand the infection, and from which tsetse flies transmit the parasites back to humans and livestock. This study was designed to investigate the potentials of the African hedgehog serving as reservoir for African animal trypanosomes. METHODS: Five adult hedgehogs alongside five laboratory mice were intraperitoneally inoculated with 106 and 104 of Trypanosoma congolense cells, respectively, and monitored for parasitemia and survival. Serum from twenty hedgehogs was subjected to trypanocidal activity-guided fractionation by successive ion-exchange and gel-filtration chromatographies, followed by characterization with Sodium Dodecyl Sulphate Polyacrylamide Gel Electrophoresis (SDS-PAGE). RESULTS: Hedgehogs were resistant to the infection as no parasite was detected and none died even after 60 days, while all the mice died within 12 days. Both the serum and plasma prepared from hedgehogs demonstrated trypanocidal activity- rapidly killed trypanosomes even when diluted 1000 times. The trypanolytic factor was identified to be proteinaceous with an estimated molecular weight of 115-kDa. CONCLUSION: For the first time, it is here demonstrated that hedgehog blood has significant trypanolytic activity against T. congolense. The potential application of the hedgehog protein for the breeding of trypanosomosis-resistant livestock in tsetse fly belt is discussed.

Structural Shielding Evaluation: A Case Study of the Radiography Room of a Rural Hospital in Jos, Nigeria.

INTRODUCTION: Most Nigerian rural hospitals constructed before the publication of the 2005 National Council on Radiation Protection and Measurements Report No. 147 did not undergo a performance assessment at the time of construction. To avoid overexposure to ionizing radiation and to ensure adequate protection of patients, workers, and the public, the shielding barriers need to be evaluated to ascertain that they conform to this standard. METHODS: This study evaluates the shielding barriers for the general radiography room in a rural hospital in Jos, Nigeria. The workload information, generator voltage waveform, anode material, filtration, and anode angle with XRAYBARR calculation model were used to estimate the thickness of lead, concrete, gypsum, steel, plate glass, and wood required to shield the X-ray facility installed in the hospital. The design dose limit was compared to the estimated shielded dose, and the calculated shielded barrier thickness to the design shielded barrier thickness was also compared. RESULTS: The unshielded radiation doses inside the X-ray room were high, indicating that the radiological department of the study area is not minimizing radiation doses to patients. The calculated doses beyond the barriers were greater than the design dose limit, indicating that the shielded barriers in place were not adequate and did not comply with the international standard. DISCUSSION: Hospitals must understand the type of shielding materials that can provide adequate protection and to what extent they can protect their radiography rooms. Management and radiation protection agencies need to ascertain whether these barriers are still adequate or require reinforcement through regular quality assurance testing. Due to an increase in workload associated with an increase in population and urbanization, proper policies are needed more than ever in this and other rural hospitals in Nigeria. CONCLUSION: The tested X-ray rooms did not comply with international recommendations for shielding thickness. Except for the door, console, and changing room, a 0.5 mm-thick lead reinforcement is required. It is also recommended that quality assurance testing occur on an annual basis.

Animal health professionals' knowledge,risk perceptions and preventive practices towards zoonotic infections in Nigeria: any challenging gap?

This study was aimed to assess zoonotic disease knowledge, risk perceptions, and preventive practices of animal health professionals in Nigeria. Cross-sectional questionnaire survey was conducted on 582 participants and 529 responded. Collected data were analyzed by descriptive statistics and multivariate logistic regression models. The proportion of veterinarians (92.0%) which knowledge about zoonosis was much higher (P < 0.001) than that of para-veterinarians (32.4%). In contrast to para-veterinarians (46.2%), the majority of veterinarians (76.7%) perceived high risk of zoonotic infections during necropsy/tissue collections. Similarly, a much higher (P < 0.001) proportion of veterinarians (54.0%) considered hand washing before eating at work as effective way of risk mitigation, compared to para-veterinarians (25.0%). Professionals in large animal practice were less likely (OR 0.35; 95% CI: 0.16, 0.77) not to be engaged in satisfactory protective measures. These results constitute public health contributions to the risk mitigation information that may support measures for zoonosis prevention in Nigeria.

Behavior of an Inductive Loop Sensor in the Measurement of Partial Discharge Pulses with Variations in Its Separation from the Primary Conductor.

Ideally, an insulation system must be capable of electrically insulating the active components of a machine or device subjected to high voltages. However, due to the presence of polluting agents or imperfections inside or on the surface of the insulation, small current pulses called partial discharges (PDs) are common, which partially short-circuit the insulation and cause it to lose its insulating properties, and thus its insulation capacity, over time. In some cases, measurements of this phenomenon are limited by the type of sensor used; if it is not adequate, it can distort the obtained results, which can lead to a misdiagnosis of the state of the device. The inductive loop sensor has experimentally been demonstrated to be capable of properly measuring different types of PDs. However, because of its current design, there are several practical limitations on its use in real devices or environments. An example is the presence of a primary conductor located at a fixed distance from the sensor, through which PD pulses must flow for the sensor to capture them. In this article, the sensor's behavior is studied at different separation distances from the line through which the PD pulses flow. In addition, the measuring capacity of the sensor is tested by removing the presence of the primary conductor and placing the sensor directly over the line through which the PD pulses of a real device flow.

Polymeric Materials for Conversion of Electromagnetic Waves from the Sun to Electric Power.

Solar photoelectric energy converted into electricity requires large surface areas with incident light and flexible materials to capture these light emissions. Currently, sunlight rays are converted to electrical energy using silicon polymeric material with efficiency up to 22%. The majority of the energy is lost during conversion due to an energy gap between sunlight photons and polymer energy transformation. This energy conversion also depends on the morphology of present polymeric materials. Therefore, it is very important to construct mechanisms of highest energy occupied molecular orbitals (HOMO)s and the lowest energy unoccupied molecular orbitals (LUMO)s to increase the efficiency of conversion. The organic and inorganic solar cells used as dyes can absorb more photons from sunlight and the energy gap will be less for better conversion of energy to electricity than the conventional solar cells. This paper provides an up-to-date review on the performance, characterization, and reliability of different composite polymeric materials for energy conversion. Specific attention has been given to organic solar cells because of their several advantages over others, such as their low-energy payback time, conversion efficiency and greenhouse emissions. Finally, this paper provides the recent progress on the application of both organic and inorganic solar cells for electric power generations together with several challenges that are currently faced.

On the Use of Monopole Antennas for Determining the Effect of the Enclosure of a Power Transformer Tank in Partial Discharges Electromagnetic Propagation.

A well-defined condition-monitoring for power transformers is key to implementing a correct condition-based maintenance (CBM). In this regard, partial discharges (PD) measurement and its analysis allows to carry out on-line maintenance following the standards IEC-60270 and IEC-60076. However, new PD measurements techniques, such as acoustics or electromagnetic (EM) acquisitions using ultra-high-frequency (UHF) sensors are being taken into account, IEC-62478. PD measurements with antennas and the effect of their EM propagation in power transformer tanks is an open research topic that is considered in this paper. In this sense, an empty tank model is studied as a rectangular cavity and their resonances are calculated and compared with their measurement with a network analyser. Besides, two low cost improved monopole antennas deployed inside and outside of the tank model capture background noise and PD pulses in three different test objects (Nomex, twisted pair and insulator). The average spectrum of them are compared and can be found that mainly, the antenna frequency response, the frequency content distribution depending on the PD source and the enclosure resonances modes are the main factors to be considered in PD acquisitions with these sensors. Finally, with this set-up, it is possible to measure PD activity inside the tank from outside.