Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Glycemic Index of Some Cameroonian Local Meals: A Contribution to the Management of Metabolic Syndrome

Laure.Evaluation of Glycemic Index of Some Cameroonian Local Meals: A Contribution of Management of Metabolic Syndrome. Fortune Journal of Health Sciences 5 (2022): 407-425. Abstract Aim of the study : This study aimed at proposing a strategy of the management of metabolic syndrome through the determination of the glycemic index of some Cameroonian local meals. Methodology : The study was carried out amongsix traditional communities living in Yaounde Haussa, Eton and Dschang communities had GI<55.Meals with the lowest GI were:HLFCo (GI: 1.21) and YCFSFCo (GI 1.51) for Bafia community; YSSC (GI : 3.03) for Dschang community; KM (GI: 4.17) for Mbo community; FLBMFR (GI: 4.17) and DOBMFCo (GI: 2.08) for Haussa community; BSOFCo (GI= 8.33) and YSEPC (GI: 4.17) for Bamougoum community; and YSSCaT (GI: 16.67) for Eton community. Conclusion : Every community is rich in low GI meals whose consumption should be encouraged in the management of metabolic syndrome and its components.
Dominant Processes for Dependence of Boreal Summer Intraseasonal Oscillation on El Niño Phases

Boreal summer intraseasonal oscillation (BSISO) strongly interacts with background mean fields and tends to be stronger and longer in its northward propagation during La Niña than El Niño summers. However, BSISO dependence on El Niño‐Southern Oscillation phase has not been well understood. Here, we show that BSISO‐related convections are stronger and more organized with northward propagation on 30–60‐day timescales during El Niño developing (E‐DV) than decaying (E‐DC) summers over the western Pacific. The easterly vertical shear, responsible for the next vorticity generation north of the BSISO convection, in the E‐DV (E‐DC) remarkably increases (decreases) due to the enhanced (weakened) upper‐level easterly anomaly. The air‐sea interaction in E‐DV gets stronger due to the larger meridional gradient of sea surface temperature, amplifying northward propagation than in E‐DC.
Association of Serum Hepcidin With Preeclampsia: A Systematic Review and Meta-Analysis

The objective of the present systematic review and meta-analysis was to compare the levels of serum hepcidin in women who developed pre-eclampsia with those who did not. The databases PubMed, Embase, Scopus, Cochrane, and references of retrieved articles published till September 2020 were searched with no language restriction. Mean differences in iron regulating protein (hepcidin) were compared using a random-effects model based on the level of heterogeneity. A total of 760 individuals were included in the analysis from seven studies. The pooled estimate showed that mean hepcidin levels were significantly higher in women who developed pre-eclampsia [0.3 ng/ml, 95% confidence interval (CI): 0.01-0.59, p=0.003] as compared to women who did not develop pre-eclampsia. Further research can be done to assess the levels of various iron parameters in different trimesters of pregnancy and their association with pre-eclampsia.
A Novel Hierarchical Detection and Isolation Framework for Quality-Related Multiple Faults in Large-Scale Processes

This paper is devoted to the industrial practices and theoretical approaches for detection and isolation of quality-related multiple faults in large-scale processes. In contrast to the previous schemes, the main innovations are as follows: 1) it is the first time a hierarchical detection and isolation framework for quality-related multiple faults in large-scale processes is developed; 2) a combination method of adaptive kernel canonical variable analysis and Bayesian fusion for real-time and hierarchical detection of varying and unknown quality-related multiple faults is presented; and 3) a robust sparse exponential discriminant analysis algorithm for accurate isolation of multimode quality-related multiple faults is proposed. Finally, the whole framework is applied to a typical large-scale process, i.e., hot strip mill process, where the performance and effectiveness are further demonstrated from real industrial data.
Early Detection of Forest Fire Using Mixed Learning Techniques and UAV

Over the last few decades, forest fires are increased due to deforestation and global warming. Many trees and animals in the forest are affected by forest fires. Technology can be efficiently utilized to solve this problem. Forest fire detection is inevitable for forest fire management. The purpose of this work is to propose deep learning techniques to predict forest fires, which would be cost-effective. The mixed learning technique is composed of YOLOv4 tiny and LiDAR techniques. Unmanned aerial vehicles (UAVs) are promising options to patrol the forest by making them fly over the region. The proposed model deployed on an onboard UAV has achieved 1.24 seconds of classification time with an accuracy of 91% and an F1 score of 0.91. The onboard CPU is able to make a 3D model of the forest fire region and can transmit the data in real time to the ground station. The proposed model is trained on both dense and rainforests in detecting and predicting the chances of fire. The proposed model outperforms the traditional methods such as Bayesian classifiers, random forest, and support vector machines.
Regression models and life tables (with discussion

The drum mallets disclosed are adjustable, by the percussion player, as to weight and/or balance and/or head characteristics, so as to vary the "feel" of the mallet, and thus also the tonal effect obtainable when playing upon kettle-drums, snare-drums, and other percussion instruments; and, typically, the mallet has frictionally slidable, removable and replaceable, external balancing mass means, positionable to serve as the striking head of the mallet, whereby the adjustment as to balance, overall weight, head characteristics and tone production may be readily obtained. In some forms, the said mass means regularly serves as a removable and replaceable striking head; while in other forms, the mass means comprises one or more thin elongated tubes having a frictionally-gripping fit on an elongated mallet body, so as to be manually slidable thereon but tight enough to avoid dislodgment under normal playing action; and such a tubular member may be slidable to the head-end of the mallet to serve as a striking head or it may be slidable to a position to serve as a hand grip; and one or more such tubular members may be placed in various positions along the length of the mallet. The mallet body may also have a tapered element at the head-end to assure retention of mass members especially of enlarged-head types; and the disclosure further includes such heads embodying a relatively hard inner portion and a relatively soft outer covering.
ICA of linear and nonlinear mixtures based on mutual information

In independent component analysis (ICA), both linear and nonlinear, one of the best objective functions is the mutual information (MI) of the estimated components. However, use of the MI demands the estimation of the probability densities of those components from a finite number of training samples. Several forms of smoothing have been used to estimate these densities from data, including series expansions and Gaussian kernels. This paper proposes a new way to estimate these densities, simultaneously with the ICA operation. The resulting system is a neural network with a specialized architecture, optimized by a single objective function - the output entropy. The paper includes experimental results, which also illustrate that it is possible to perform nonlinear blind source separation when the mixtures have smooth nonlinearities.
Exploring Teachers’ Lived Experiences on the Integration of Values Education in South African High Schools

Values education has become a necessary tool in response to the rise in moral deterioration in an average South African society today. The school is viewed as one of the key players in nurturing children into adulthood. The teaching of values that can give the growing generation, necessary moral development is one of the responsibilities of the schools. Hence, this study aims at exploring teachers’ experiences on how they integrate values education into South African learners in various high schools. This qualitative study engaged five schools in its case study, where five teachers from each of the schools were purposively selected for semi-structured focus group interviews, to share their experiences on the integration of moral values in schools. Moral development theory was used to underpin the study. Findings from the inductive thematic analysis from the participants from both rural and urban schools indicated a misunderstanding of the concept of values education by some teachers, which affects its effective integration. The study established that role modelling of learners by teachers and parents are inevitable to save the society from moral decadence, while some participants indicted overpopulation, single parenthood, social media as some of the challenges to the integration of value education in schools. The study, therefore, recommends capacitation of teachers through various professional development programmes, to integrate values education and adequate parental support as some of the strategies to promote effective integration of values education in schools.
Modified layer deep convolution neural network for text-independent speaker recognition

ABSTRACT Speaker recognition is the task of identifying the spokesman automatically using speaker-specific features. It has been a popular and most involved topic in the field of speech technology. This field opens a wide opportunity for research and finds its application in the areas such as forensics, authentication, security, etc. In this work, a modified deep-convolutional neural network structure has been proposed for speaker identification that has improved convolution, activation, and pooling layers along with Adam’s optimiser. The proposed architecture yielded the increase of prediction accuracy and reduction of Loss function when compared to the generic Convolutional Neural Network scheme. The execution of the proposed architecture is validated by various datasets and the outcomes show that the modified CNN performs better than the other state-of-the-art models regarding both accuracy (avg 99%) and loss function (avg 1%). From the analysis, it is found that the Modified-CNN suits the best for real-time speaker identification applications as the efficacy of the model does not degrade due to the effects of noise and interferences that are caused in the recording environment. Relevance of the work: Speaker Recognition is an area of interest in which ML and DL schemes, when combined, have the potential to make history in the areas of Automation and Authentication. Using a modified CNN can enhance the process by ignoring many issues such as false positives, background noise, and so on. This process can be expanded to create a Raga Identification and Therapy mechanism that can be used to treat diseases.
A retrospective and regional approach assessing the genomic diversity of Salmonella Dublin

Abstract From a historically rare serotype, Salmonella enterica subsp. enterica Dublin slowly became one of the most prevalent Salmonella in cattle and raw milk cheese in some regions of France. We present a retrospective genomic analysis of 480 S. Dublin isolates to address the context, evolutionary dynamics, local diversity and the genesis processes of regional S. Dublin outbreaks events between 2015 and 2017. Samples were clustered and assessed for correlation against metadata including isolation date, isolation matrices, geographical origin and epidemiological hypotheses. Significant findings can be drawn from this work. We found that the geographical distance was a major factor explaining genetic groups in the early stages of the cheese production processes (animals, farms) while down-the-line transformation steps were more likely to host genomic diversity. This supports the hypothesis of a generalised local persistence of strains from animal to finished products, with occasional migration. We also observed that the bacterial surveillance is representative of diversity, while targeted investigations without genomics evidence often included unrelated isolates. Combining both approaches in phylogeography methods allows a better representation of the dynamics, of outbreaks.
Research on a hybrid controller combining RBF neural network supervisory control and expert PID in motor load system control

Considering the contradiction among the response speed, overshoot and stability of system when the motor load system adopts PID control, a control strategy combining RBF (Radial Basis Function) neural network supervisory control and expert PID control is designed to effectively improve this problem in this paper. First of all, the related algorithms of RBF neural network supervisory control composed of RBF neural network and PID control (RSC-PID) is introduced. This method can make the motor load system reach a steady state faster than simple PID control. But RSC-PID is also unsatisfactory in terms of overshoot. Based on the RSC-PID control method, a hybrid controller combining RBF neural network supervisory control and expert PID control (RSC-EPID) is proposed. This method combines RSC-PID control theory with expert PID control ideas, further improves the stability and rapidity of the system, reduces the overshoot. Moreover, when the input signal is a time-varying signal with interference, the motor load system shows better anti-interference performance after using RSC-EPID. The simulation results show that RSC-EPID control improves the tracking effect of the output signal of the motor load system, ensures the stability of the system, and improves the performance of the system.
Association between Blood Donation and Malignant and Benign Tumour Risk: A Population-Based Study of 3.4 Million Participants in China

This study aims to identify the relationship between blood donation and malignant and benign tumour hospitalization risk. The cohort study was constructed in Shaanxi, China, to include blood donors and match nonblood donors one-to-one by gender, age, and county of residence. The study compared the hospitalization records of two groups from 2012 to 2018. A log-binomial regression model was used to estimate the relative risk (RR) of tumour risk between donors and nonblood donors among different age groups. A total of 1,625,599 donors were recruited (including 968,823 males) and compared with the matched nonblood donor group. Significantly lower risk of malignancy in males was found among donors (adjusted RR: 0.82, 95% CI: 0.75–0.92). Lower risks for specific types of tumours among donors were observed, including liver (0.42, [0.28–0.67]), lung (0.74, [0.59–0.87]), lymphoma (0.75, [0.62–0.85]), and oesophagus (0.55, [0.41–0.72]). However, the risk of brain cancer was higher among male donors (RR 1.19 [1.06–1.29]). Among female donors, lower risk of liver (0.57, [0.42–0.79]) and oesophagus malignancy (0.73, [0.62–0.88]) was observed. For benign tumours, male donors have a lower risk of benign skin tumour (0.79, [0.62–0.94]) and hemangioma and lymphangioma (0.75, [0.51–0.89]), while female donors have a lower risk in hemangioma and lymphangioma (0.65, [0.44–0.83]). We also found that the risk decreased with age among donors in the prevalence of tumours compared to that in nonblood donors (p < 0.05). Blood donation appears to be significantly associated with various tumour risks among both males and females. Overall, the risk of tumours decreased more substantially with age in blood donors compared with nonblood donors. Further research is warranted to investigate the impact of ‘health donor effects' on these findings.
Differential Quadrature Method to Examine the Dynamical Behavior of Soliton Solutions to the Korteweg-de Vries Equation

Nonlinear evolution equations are crucial for understanding the phenomena in science and technology. One such equation with periodic solutions that has applications in various fields of physics is the Korteweg-de Vries (KdV) equation. In the present work, we are concerned with the implementation of a newly defined quintic B-spline basis function in the differential quadrature method for solving the Korteweg-de Vries (KdV) equation. The results are presented using four experiments involving a single soliton and the interaction of solitons. The accuracy and efficiency of the method are presented by computing the L 2 and L ∞ norms along with the conservational quantities in the forms of tables. The results show that the proposed scheme not only gives acceptable results but also consumes less time, as shown by the CPU for the elapsed time in two examples. The graphical representations of the obtained numerical solutions are compared with the exact solution to discuss the nature of solitons and their interactions for more than one soliton.
E-learning from the Perspective of University of Zakho Students During Covid-19

The study investigates the impressions of students at University of Zakho, Kurdistan Region of Iraq, about e-learning during the Covid-19, highlighting some problems resulted from using this e-learning system. Also, the statistical significance of correlations according to gender is calculated. Using qualitative and quantitative methods for data collection, a questionnaire of seven items is utilized via google document and sent to nearly 1000 participants (males and females) via social media and online platforms. Only 752 responses returned. The data were interpreted and analyzed by Excel sheets and SPSS software. As there was statistical significance in gender differences, the results showed that the majority of the participants do not view e-learning as a fun process for their education and they have no willingness to use it for their future studies. In addition, more than half of the participants agree that (1) e-learning is costly; (2) lectures are better understood in classrooms; (3) e-learning is not adequate because of the internet and electricity outage; and (4) e-learning leads to some eye problems and headaches. Generally, knowing the students’ impressions about using e-learning for their education will be helpful for the university administrators, educational policy makers, teachers to determine the students’ genuine needs, motivation or challenges. This will be helpful to gain an understanding of e-learning in Kurdistan Region of Iraq, to cope with challenges involved in the process of e-learning, and develop approaches to solve the problems resulted from.
Effectiveness of ABA on supporting children with ASD

This review article starts with broad categories of ASD interventions and identifies the need to study effectiveness of ABA therapy. It establishes ABA to be gold standard based on research done in the past. Further, it defines ABA and then deep dives into the advantages and limitations of ABA therapy. Finally, it concludes by strongly vouching for ABA as the treatment of choice on the premise that advantages certainly outweigh its limitations
Long Noncoding RNA LINC01554 Inhibits the Progression of NSCLC Progression by Functioning as a ceRNA for miR-1267 and Regulating ING3/Akt/mTOR Pathway

Objectives This study focused on the biological functions and mechanisms of action of LINC01554 in nonsmall cell lung cancer (NSCLC). Methods The expression and prognostic values of LINC01554 in NSCLC were evaluated using The Cancer Genome Atlas datasets. MTT, colony formation, wound healing, transwell, and in vivo assays were performed to investigate the role of LINC01554 in NSCLC. The related protein expression levels were measured via western blotting. Bioinformatic analysis was conducted to predict targeted genes. The relationship between LINC01554, microRNA- (miR-) 1267, miR-1267, and inhibitor of growth family member 3 (ING3) was analysed via a dual-luciferase reporter assay. Results LINC01554 expression was downregulated in NSCLC and associated with NSCLC prognosis. LINC01554 overexpression suppressed NSCLC cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT). Bioinformatic and dual-luciferase reporter assays demonstrated that LINC01554 expression directly targeted miR-1267 expression, which in turn directly acted on ING3. An miR-1267 mimic significantly reduced ING3 expression, whereas an miR-1267 inhibitor observably elevated its expression. LINC01554 overexpression increased ING3 expression, whereas this effect was counteracted by the miR-1267 mimic. LINC01554 overexpression also significantly suppressed the expression of phosphorylated protein kinase B (Akt) and phosphorylated mammalian target of rapamycin (mTOR) expression; this effect was abrogated by the miR-1267 mimic. Mechanistically, LINC01554 overexpression repressed the growth, migration, invasion, and epithelial-mesenchymal transition (EMT) of NSCLC cells through the regulation of the miR-1267/ING3 axis via regulation of the Akt/mTOR signalling pathway. Conclusions We provide the first evidence of the involvement of the LINC01554/miR-1267 axis in NSCLC proliferation and metastasis through the ING3Akt/mTOR pathway. Thus, LINC01554 may serve as a novel therapeutic target for NSCLC.
Younger Age and Albuminuria are Associated with Proliferative Diabetic Retinopathy and Diabetic Macular Edema in the South Indian GeNetics of DiAbeTic Retinopathy (SIGNATR) Study

Abstract Purpose: The purpose of the South Indian GeNetics of DiAbeTic Retinopathy (SIGNATR) Study is to identify non-genetic and genetic risk factors associated with diabetic retinopathy (DR). This report examines the non-genetic risk factors for DR in South Indian patients. Methods: Participants with South Indian ancestry and type 2 diabetes (T2D) were included from two sources: the Sankara Nethralaya Diabetic Retinopathy and Molecular Genetics Study (SN-DREAMS) and prospective recruitment at Sankara Nethralaya affiliates. Fundus photography and optical coherence tomography (OCT) were obtained on participants. Fundus images were graded for DR severity and OCTs were graded for center-involved diabetic macular edema (ciDME). Multivariate analyses were performed using stepwise logistic regression to assess effects of the demographic and clinical factors on proliferative DR (PDR) and DME. Results: Among the 2941 participants with DR grading, participants with PDR were more likely to be younger [odds ratio (OR)=0.95], men (OR = 1.83), have a longer duration of diabetes (OR = 1.10), have a higher hemoglobin A1c (OR = 1.12), have albuminuria (OR = 5.83), have hypertension (OR = 1.69), have a higher HDL (OR = 1.02) and a lower total cholesterol (OR = 0.99) (all p < 0.05). Among the 483 participants with gradable OCT scans, participants who had ciDME were more likely to be younger (OR = 0.97), men (OR = 2.80), have a longer duration of diabetes (OR = 1.06), have lower triglycerides (OR = 0.99), and have albuminuria (OR = 3.12) (all p < 0.05). Conclusions: Younger age, male sex, longer duration of diabetes, higher HbA1c, and presence of albuminuria were identified as risk factors for PDR and DME in a South Indian population with T2D.
Behavioural science applied to risk-based decision processes: a case study for earthquake prone buildings in New Zealand

ABSTRACT Policy and technical guidance are only as good as their implementation. Often well-meaning legislation has unintended consequences, as individuals and organisations overlay their own risk perceptions and understanding to an issue. This paper illustrates how behavioural science can be applied to risk-based engineering decisions to improve decision outcomes. It is framed around an analysis of the management of earthquake prone public buildings in New Zealand. It demonstrates how the individual, social and cultural contexts can influence how risks and impacts are perceived, evaluated, and communicated. The framing of the decision, unconscious biases, cognitive limitations, trust, and other social influences are all critical factors in translation of technical policy to effective outcomes.