Functional Safety of FPGA Fuzzy Logic Controller

In this paper we describe a methodology to implement a fuzzy logic controller in FPGA. The implementation of fuzzy logic controller (FLC) in FPGA requires a qualitative and a quantitative analysis to define the system safety integrity level (SIL). This level can be defined by the quantification of the probability of failure on demand (PFDavg). We propose to analyze the implementation advance safety architecture of fuzzy logic controllers with 1-out-of-2 controllers (1oo2) in FPGA using the reliability block diagram (RBD) and the Markov model. We demonstrate how from hardware characteristics parameters, such as rate of dangerous detected failure and undetected failure, the diagnostic coverage, proof test interval and other parameters to evaluate the PFDavg

Some new integral inequalities for negative summation parameters

In this paper, we prove some Hardy type and Hardy-Steklov type integral inequalities for two negative summation parameters and we deduce some well-known results with sharp constants

Seroprevalence and risk factors for Coxiella burnetii, the causative agent of Q fever in the dromedary camel (Camelus dromedarius) population in Algeria

Query (Q) fever is a globally distributed zoonotic disease caused by Coxiella burnetii, a bacterial agent for which ruminants are the most prevalent natural reservoir. Data regarding Q fever infection in camels in Algeria are limited. Therefore, a survey to detect seroprevalence of C. burnetii antibodies was conducted among healthy camel populations in a vast area in southeastern Algeria to determine distribution of the Q fever causative organism and to identify risk factors associated with infection. Between January and March 2016, blood samples were collected from 184 camels and serum samples were subsequently analysed using a commercial Enzyme-Linked Immunosorbent Assay (ELISA) kit. At the time of blood collection, a questionnaire investigating 13 potential predisposing factors associated with C. burnetii seropositivity was completed for every dromedary camel and herd. Results were analysed by a chi-square (χ2) test and multivariate logistic regression. The seroprevalence of C. burnetii at the animal level was 71.2% (95% CI: 65.2–78.3) and 85.3% (95% CI: 72.8–97.8) at the herd level. At the animal level, differences in seroprevalence were observed because of herd size, animal age, animal sex, presence of ticks and contact with other herds. A multivariable logistic regression model identified three main risk factors associated with individual seropositivity: (1) age class \u3e 11 years (OR = 8.81, 95% CI: 2.55–30.41), (2) herd size \u3e 50 head (OR = 4.46, 95% CI: 1.01–19.59) and (3) infestation with ticks (OR 2.2; 95% CI: 1.1– 4.5). This study of seroprevalence of C. burnetii infection in camels in Algeria revealed a high seroprevalence of Q fever in camel populations in southeastern Algeria and provided strong evidence that Q fever represents an economic, public health and veterinary concern. Appropriate measures should be taken to prevent the spread of C. burnetii and to reduce the risk of Q fever in farm animals and humans in this agro-ecologically and strategically important region of North Africa

Effect of intrinsic point defects on the catalytic and electronic properties of Cu2WS4 single layer: Ab initio calculations

The challenges imposed by climate change require the continued improvement and identification of materials for the development of green technologies. Point defect engineering is a promising technology for producing green hydrogen by taking advantage of catalytic hydrogen evolution reactions. In this work, we investigate the role of anionic and cationic vacancy point defects, as well as the nature of the active sites, in the catalytic activation of Cu2WS4 single layers. The stability of the pristine and defective structures of Cu2WS4 has been thoroughly investigated using density-functional theory calculations. A deep analysis of the formation enthalpy indicates that the Cu vacancy is the chemically most favorable vacancy. However, the calculated adsorption energy indicates that the presence of such vacancies slightly enhances the hydrogen evolution reaction. In contrast, the formation of an S vacancy considerably magnifies the same reaction in Cu2WS4 single layers

Influence of bonded length of the Carbon Fiber Reinforced Polymer Plates on the behavior of a concrete beam

Sometimes Aged or Damaged Structures need to be reinforced and retrofitted to enhance their performances and structural life, for this reason, the rehabilitation has been the subject of extensive research. The strengthening Reinforced Concrete structures is one of the most difficult and important tasks of civil engineering. Among the ways used to strength the concrete; the reinforcement using Carbon fiber reinforced polymer. This material has proved to be more efficient than other composites because of its high elastics modulus, its durability and this kind of materials are less affected by corrosive environmental conditions. The technique used in this study will be the external bonding of Carbon fiber reinforced polymer (CFRP) to a concrete beam. In this paper, the focus will be on the influence of bonded length of the CFRP Plates on the global behavior of the beam. The study is developed by the finite element program ABAQUS and will contain 11 specimens with a dimension of 100*200*1000mm and the length of the CFRP will be 100 mm, 200 mm, 300 mm, 400 mm, 500 mm, 600 mm, 700 mm, 800 mm, 900 mm, and a fully reinforced beam. Numerical results are presented and discussed herein

Numerical assessment of EMF exposure of a cow to a wireless power transfer system for dairy cattle

In this paper, we assessed the exposure of a cow to the electromagnetic fields (EMFs) induced by a wireless power transfer (WPT) system working at 92 kHz in a dairy barn. Cow exposure to the radiated EMFs was evaluated and compared to safety guidelines. We modeled a realistic WPT system for dairy cows in Sim4Life, a 3D electromagnetic simulation tool. We validated the model with electric field measurements; simulated fields deviated on average 6% from measured fields. We used the proposed WPT model to evaluate the stimulation and thermal effects based on the internal electric field and the specific absorption rate (SAR), respectively. Results showed that the exposure mainly varied with the distance of the transmitter to the body: variation of 5 dB of the induced electric field when the transmitter was set at 20 cm and 10 cm from the body. The distance of the receiver to the body influenced the exposure less (10%). We also compared the exposure with the limits provided by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The internal electric fields were more conservative than SAR, which showed values far below exposure limits

Automatic inference of hypoglycemia causes in type 1 diabetes: a feasibility study

BackgroundHypoglycemia is the most common adverse consequence of treating diabetes, and is often due to suboptimal patient self-care. Behavioral interventions by health professionals and self-care education helps avoid recurrent hypoglycemic episodes by targeting problematic patient behaviors. This relies on time-consuming investigation of reasons behind the observed episodes, which involves manual interpretation of personal diabetes diaries and communication with patients. Therefore, there is a clear motivation to automate this process using a supervised machine learning paradigm. This manuscript presents a feasibility study of automatic identification of hypoglycemia causes.MethodsReasons for 1885 hypoglycemia events were labeled by 54 participants with type 1 diabetes over a 21 months period. A broad range of possible predictors were extracted describing a hypoglycemic episode and the subject’s general self-care from participants’ routinely collected data on the Glucollector, their diabetes management platform. Thereafter, the possible hypoglycemia reasons were categorized for two major analysis sections - statistical analysis of relationships between the data features of self-care and hypoglycemia reasons, and classification analysis investigating the design of an automated system to determine the reason for hypoglycemia.ResultsPhysical activity contributed to 45% of hypoglycemia reasons on the real world collected data. The statistical analysis provided a number of interpretable predictors of different hypoglycemia reasons based on self-care behaviors. The classification analysis showed the performance of a reasoning system in practical settings with different objectives under F1-score, recall and precision metrics.ConclusionThe data acquisition characterized the incidence distribution of the various hypoglycemia reasons. The analyses highlighted many interpretable predictors of the various hypoglycemia types. Also, the feasibility study presented a number of concerns valuable in the design of the decision support system for automatic hypoglycemia reason classification. Therefore, automating the identification of the causes of hypoglycemia may help objectively to target behavioral and therapeutic changes in patients' care

Evaluation des connaissances et pratiques du personnel du laboratoire central vis-à-vis des risques infectieux au niveau du Centre Hospitalier Universitaire Mohammed VI d’Oujda

Introduction : Nos objectifs à travers ce travail sont d’une part l’évaluation des connaissances et des bonnes pratiques des laborantins du Centre Hospitalier Universitaire Mohammed VI d’Oujda, et d’autre part, de proposer des actions d’information, d’éducation et de communication dans le cadre d’une politique de prévention des risques dans notre pays.Matériels et méthodes : Nous avons réalisé une étude épidémiologique descriptive de type transversale menée sur deux mois (septembre et novembre 2022), auprès du personnel du laboratoire au sein du CHU Mohammed VI d’Oujda. Les données ont été collectées à l’aide d’un questionnaire anonyme concernant les risques infectieux et les mesures préventifs.Résultats : Notre population cible était représentée par des médecins (48%). Seulement 6% de notre population affirmait avoir eu une formation sur les risques au laboratoire et presque la totalité (98%) était intéressée par des formations continues et régulières. La majorité du personnel (84%) confirmait la disponibilité des produits d’hygiène des mains mais il remarquait l’irrespect des règles d’utilisation de ces produits (37%). Presque 70% étaient satisfaits de la gestion des déchets. Concernant les accidents d’exposition au sang, 33% du personnel était victime et 67% ne déclarait pas l’accident du travail, tandis que la plupart savait les premiers soins après l’accident d’exposition au sang. Seulement la moitié était vacciné contre l’hépatite B.Conclusion : les résultats de cette étude ont montré qu’une réorganisation de la formation profonde et continue en matière des risques biologiques s’avère nécessaire pour améliorer les connaissances et les attitudes du personnel de laboratoire

Local linear embedded regression in the quantitative analysis of glucose in near infrared spectra

This paper investigates the use of Local Linear Embedded Regression (LLER) for the quantitative analysis of glucose from near infrared spectra. The performance of the LLER model is evaluated and compared with the regression techniques Principal Component Regression (PCR), Partial Least Squares Regression (PLSR) and Support Vector Regression (SVR) both with and without pre-processing. The prediction capability of the proposed model has been validated to predict the glucose concentration in an aqueous solution composed of three components (urea, triacetin and glucose). The results show that the LLER method offers improvements in comparison to PCR, PLSR and SVR

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century