Beliefs and practices of young women on utilization of prevention of mother to child transmission of HIV services in Malawi

This study explored beliefs and actual practices of young women on utilization of Prevention of Mother to Child Transmission (PMTCT) of HIV services in Balaka district of Southern Malawi. The study design wascross sectional which utilized qualitative data collection and analysis methods. In-depth interviews were conducted on 12 young mothers of 15 to 24 years old. The respondents were drawn from 6 health centres in the district during their visits to either the under-five clinic, HIV and AIDS support groups or HIV follow up clinics. Data were analyzed using thematic analysis approach. Overall the respondents had positive beliefs on utilization of PMTCT services. They believed that adherence to PMTCT guidelines such as condom use, taking of Nevirapine (NVP) and exclusive breastfeeding protected the baby from contracting the virus. Nevertheless, all respondents believed that HIV testing was mandatory and that early weaning caused malnutrition and death of babies. Actual practice was very low. Very few young mothers breastfed exclusively, weaned their babies abruptly and took NVP as recommended. Not all positive beliefs translated into positive behavior. Lack of male support, inability of the midwives to provide comprehensive care to HIV infected mothers and their infants, and fear of stigma and discrimination were other factors that hindered utilization of PMTCT services. Culture was also a major barrier because traditionally babies are expected to be breastfed and supplements are fed to babies too. Therefore, there is a need to mobilize communities on PMTCT of HIV. Education programmes in HIV should emphasize behavior change interventions and should focus on both men and women and significant others. There is also need to intensify monitoring and evaluation of health workers’ activities to ensure that beliefs translate into positive behavior.

A Health State Prediction Model Based on Belief Rule Base and LSTM for Complex Systems

In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,the Density Peak Clustering(DPC)algorithmis used todetermine referential values of indicators for BRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump.

Evaluation of the effects of health education interventions for hypertensive patients based on the health belief model

BACKGROUND Hypertension is a major risk factor for cardiovascular disease and stroke,and its prevalence is increasing worldwide.Health education interventions based on the health belief model(HBM)can improve the knowledge,attitudes,and behaviors of patients with hypertension and help them control their blood pressure.AIM To evaluate the effects of health education interventions based on the HBM in patients with hypertension in China.METHODS Between 2021 and 2023,140 patients with hypertension were randomly assigned to either the intervention or control group.The intervention group received health education based on the HBM,including lectures,brochures,videos,and counseling sessions,whereas the control group received routine care.Outcomes were measured at baseline,three months,and six months after the intervention and included blood pressure,medication adherence,self-efficacy,and perceived benefits,barriers,susceptibility,and severity.RESULTS The intervention group had significantly lower systolic blood pressure[mean difference(MD):-8.2 mmHg,P<0.001]and diastolic blood pressure(MD:-5.1 mmHg,P=0.002)compared to the control group at six months.The intervention group also had higher medication adherence(MD:1.8,P<0.001),self-efficacy(MD:12.4,P<0.001),perceived benefits(MD:3.2,P<0.001),lower perceived barriers(MD:-2.6,P=0.001),higher perceived susceptibility(MD:2.8,P=0.002),and higher perceived severity(MD:3.1,P<0.001)than the control group at six months.CONCLUSION Health education interventions based on the HBM effectively improve blood pressure control and health beliefs in patients with hypertension and should be implemented in clinical practice and community settings.

Improved Belief Propagation Decoder for LDPC-CRC-Polar Codes with Bit-Freezing

Though belief propagation bit-flip(BPBF)decoding improves the error correction performance of polar codes,it uses the exhaustive flips method to achieve the error correction performance of CA-SCL decoding,thus resulting in high decoding complexity and latency.To alleviate this issue,we incorporate the LDPC-CRC-Polar coding scheme with BPBF and propose an improved belief propagation decoder for LDPC-CRC-Polar codes with bit-freezing(LDPCCRC-Polar codes BPBFz).The proposed LDPCCRC-Polar codes BPBFz employs the LDPC code to ensure the reliability of the flipping set,i.e.,critical set(CS),and dynamically update it.The modified CS is further utilized for the identification of error-prone bits.The proposed LDPC-CRC-Polar codes BPBFz obtains remarkable error correction performance and is comparable to that of the CA-SCL(L=16)decoder under medium-to-high signal-to-noise ratio(SNR)regions.It gains up to 1.2dB and 0.9dB at a fixed BLER=10-4compared with BP and BPBF(CS-1),respectively.In addition,the proposed LDPC-CRC-Polar codes BPBFz has lower decoding latency compared with CA-SCL and BPBF,i.e.,it is 15 times faster than CA-SCL(L=16)at high SNR regions.

Belief reliability:a scientific exploration of reliability engineering

This paper systematically introduces and reviews a scientific exploration of reliability called the belief reliability.Beginning with the origin of reliability engineering,the problems of present theories for reliability engineering are summarized as a query,a dilemma,and a puzzle.Then,through philosophical reflection,we introduce the theoretical solutions given by belief reliability theory,including scientific principles,basic equations,reliability science experiments,and mathematical measures.The basic methods and technologies of belief reliability,namely,belief reliability analysis,function-oriented belief reliability design,belief reliability evaluation,and several newly developed methods and technologies are sequentially elaborated and overviewed.Based on the above investigations,we summarize the significance of belief reliability theory and make some prospects about future research,aiming to promote the development of reliability science and engineering.

Integrating the health belief model into health education programs in a clinical setting

The article demonstrates that health belief model(HBM)-based health education in hypertensive patients effectively improves blood pressure control and medication adherence at 3 months and 6 months.The HBM addresses perceived barriers,benefits,susceptibility,severity,and self-efficacy,leading to better health behaviors.HBM-based education has been effective in various contexts,including managing chronic diseases,promoting cancer screenings,and preventing infectious diseases.However,the model has limitations,such as cultural applicability and addressing complex health behaviors influenced by environmental factors.Future research should integrate HBM with other theories and conduct longitudinal studies to assess long-term impacts.Despite these limitations,HBM-based education significantly improves patient outcomes,highlighting its potential in health education and promotion when appropriately adapted and implemented.This reinforces the model's value in designing effective health interventions and advancing public health.

Exploring the Intersection of Spirituality and Religion:Transcendence,Secularism,and Personal Beliefs in Contemporary Society

This paper explores the intersection of spirituality and religion,focusing on how transcendence,secularism,and personal beliefs shape contemporary spiritual practices.It examines the philosophical foundations of transcendence,the rise of existentialism,and the distinction between spirituality and religion.Secularism's role in fostering personal spirituality and reducing religious authority is discussed,alongside the psychological and societal impacts of spiritual transcendence.The paper also critiques the limitations of spirituality,emphasizing the need for a balanced approach that integrates cognitive development and mental health perspectives.

A study on the cognitive status of human papillomavirus among adult males in Tianjin based on the health belief model

Background:To understand the health beliefs and knowledge of human papillomavirus among adult males in Tianjin.Methods:An online questionnaire survey was conducted from 18 January 2023 to 6 March 2023 using snowball sampling method.Analyze the health belief scores and human papillomavirus(HPV)and HPV vaccine knowledge scores of adult males in Tianjin,and analyze their influencing factors.Results:A total of 388 adult males in Tianjin were surveyed,with an average total score of 3.23±0.04 for their health beliefs.Among them,the average scores for perceived severity,perceived susceptibility,perceived impairment,perceived benefit,and self-efficacy were 3.41±1.05,2.37±1.20,2.96±1.00,3.51±0.90,and 3.36±1.08,respectively.Multiple linear regression analyses showed education was a factor influencing health beliefs.The average total score of knowledge is 64.09±15.62,with 277 people scoring above 60,and a pass rate of 71.4%.Through multiple linear regression analysis,education level,emotional status,whether disease testing has been done,and whether family and friends have been diagnosed with HPV positive are the main influencing factors.Conclusion:The awareness rate of HPV among adult males in Tianjin is still acceptable,but there are still misconceptions.The overall level of health beliefs is moderate,and the perceived susceptibility level is low.It is necessary to strengthen health education on HPV related knowledge for males and improve their cognitive level.

Faith and Belief in Autism in Cote d’Ivoire: About Judith, God’s Strange Gift

Faced with autism, motherhood and parenthood are turned upside down in many ways. Coping with stress and mental health problems, continuing to assume a rewarding parental role and finding suitable care are the trials and tribulations that mark out the journey of African parents. Faith and belief have been described as providing meaning and coping mechanisms in the frightening ordeal of disability. An encounter with a young girl and her parents provided an opportunity to analyse the mother’s experience and the impact of beliefs and discourses on her commitment to care. Based on this clinical story, we discuss the place of other-actors (parents and carers) and the Other-God in relation to the psychopathological dynamics of the mother.

Optimal Insurance with Background Risk under the Ambiguity and Belief Heterogeneity Structure

In this paper, we discuss the optimal insurance in the presence of background risk while the insured is ambiguity averse and there exists belief heterogeneity between the insured and the insurer. We give the optimal insurance contract when maxing the insured’s expected utility of his/her remaining wealth under the smooth ambiguity model and the heterogeneous belief form satisfying the MHR condition. We calculate the insurance premium by using generalized Wang’s premium and also introduce a series of stochastic orders proposed by [1] to describe the relationships among the insurable risk, background risk and ambiguity parameter. We obtain the deductible insurance is the optimal insurance while they meet specific dependence structures.

A Real-Time and Ubiquitous Network Attack Detection Based on Deep Belief Network and Support Vector Machine

In recent years, network traffic data have become larger and more complex, leading to higher possibilities of network intrusion. Traditional intrusion detection methods face difficulty in processing high-speed network data and cannot detect currently unknown attacks. Therefore, this paper proposes a network attack detection method combining a flow calculation and deep learning. The method consists of two parts: a real-time detection algorithm based on flow calculations and frequent patterns and a classification algorithm based on the deep belief network and support vector machine(DBN-SVM). Sliding window(SW) stream data processing enables real-time detection, and the DBN-SVM algorithm can improve classification accuracy. Finally, to verify the proposed method, a system is implemented.Based on the CICIDS2017 open source data set, a series of comparative experiments are conducted. The method's real-time detection efficiency is higher than that of traditional machine learning algorithms. The attack classification accuracy is 0.7 percentage points higher than that of a DBN, which is 2 percentage points higher than that of the integrated algorithm boosting and bagging methods. Hence, it is suitable for the real-time detection of high-speed network intrusions.

Heterogeneous information fusion recognition method based on belief rule structure

To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on belief rule structure is proposed.By defining the continuous probabilistic hesitation fuzzy linguistic term sets(CPHFLTS)and establishing CPHFLTS distance measure,the belief rule base of the relationship between feature space and category space is constructed through information integration,and the evidence reasoning of the input samples is carried out.The experimental results show that the proposed method can make full use of sensor data and expert knowledge for recognition.Compared with the other methods,the proposed method has a higher correct recognition rate under different noise levels.

Improved Segmented Belief Propagation List Decoding for Polar Codes with Bit-Flipping

Belief propagation list(BPL) decoding for polar codes has attracted more attention due to its inherent parallel nature. However, a large gap still exists with CRC-aided SCL(CA-SCL) decoding.In this work, an improved segmented belief propagation list decoding based on bit flipping(SBPL-BF) is proposed. On the one hand, the proposed algorithm makes use of the cooperative characteristic in BPL decoding such that the codeword is decoded in different BP decoders. Based on this characteristic, the unreliable bits for flipping could be split into multiple subblocks and could be flipped in different decoders simultaneously. On the other hand, a more flexible and effective processing strategy for the priori information of the unfrozen bits that do not need to be flipped is designed to improve the decoding convergence. In addition, this is the first proposal in BPL decoding which jointly optimizes the bit flipping of the information bits and the code bits. In particular, for bit flipping of the code bits, a H-matrix aided bit-flipping algorithm is designed to enhance the accuracy in identifying erroneous code bits. The simulation results show that the proposed algorithm significantly improves the errorcorrection performance of BPL decoding for medium and long codes. It is more than 0.25 d B better than the state-of-the-art BPL decoding at a block error rate(BLER) of 10^(-5), and outperforms CA-SCL decoding in the low signal-to-noise(SNR) region for(1024, 0.5)polar codes.

Perceived Barriers to Asthma Therapy in Ethno-Cultural Communities: The Role of Culture, Beliefs and Social Support

Background : Adherence to therapy is integral to successfully managing asthma, which requires comprehension of what, when, and how to use medication and diligence in following management plan. Asthma patients from ethnic minority groups have more morbidity and reported filling their prescriptions less often. Limited information is available in Canadian literature on ethnic differences in their perceptions of asthma management. We aimed to document patient perceived adherence to asthma therapy among targeted ethno-cultural groups. Methods : We evaluated perceived barriers to therapy adherence, including: cultural beliefs and practices, patient/care-provider communication, self-management knowledge, and medication costs. We conducted a cross sectional study and interviewed 85 Chinese or Punjabispeaking adult asthma patients. Results : Lack of sufficient instructions from physicians, language/communication barriers, lack of skills on how to use inhalers, and high medication costs and medication side effects were most reported barriers to proper self-management practices. Most participants lived with others in the same household and reported high social support from home caregivers. The influence of family on self-management practices was obvious. Conclusion: Better understanding of patient needs, provision of culturally and linguistically appropriate education, and inclusion of home caregivers into the management practices are necessary to improve asthma outcomes in Chinese and Punjabi communities.

Beliefs and Clinical Practice for Complex Regional Pain Syndrome (CRPS) Managed by Physiotherapists on the South Island of New Zealand

On the South Island of New Zealand, Anaesthetists and other Medical Professionals, frequently refer their patients with Complex Regional Pain Syndrome (CRPS) for physiotherapy management. Beliefs about what is important for the management of patients with CRPS are lacking across all medical and allied health disciplines. Difficulties are no gold standard for diagnosis and evidence for intervention methods is moderate or can be conflicting. This paper explores what Physiotherapists believe to be important in a clinical setting for their management of CRPS, as well as documenting and evaluating their interventional methods used in everyday clinical practice across the region of the South Island of New Zealand. This has not been recorded before. Eighty-one Physiotherapists replied to questions on their usual treatment interventions for the management of CRPS, their frequency of use of these treatment interventions, and what they believed to be important in the management of pain and improvement of function. The results demonstrated that CRPS is not a common condition seen regularly by Physiotherapists;that there is a high level of variation between the physiotherapy interventions used and that Physiotherapists’ beliefs regarding interventions used for pain management and functional restoration differ. Education was reported as the most frequently used intervention method. Those physiotherapists seeing CRPS patients more frequently are more likely to use evidence based intervention methods like graded motor imagery or sensory motor training.

Comparison of Urban Growth Modeling Using Deep Belief and Neural Network Based Cellular Automata Model—A Case Study of Chennai Metropolitan Area, Tamil Nadu, India

Urban Growth Models (UGMs) are very essential for a sustainable development of a city as they predict the future urbanization based on the present scenario. Neural Network based Cellular Automata models have proved to predict the urban growth more close to reality. Recently, deep learning based techniques are being used for the prediction of urban growth. In this current study, urban growth of Chennai Metropolitan Area (CMA) of 2017 was predicted using Neural Network based Cellular Automata (NN-CA) model and Deep belief based Cellular Automata (DB-CA) model using 2010 and 2013 urban maps. Since the study area experienced congested type of urban growth, “Existing Built-Up” of 2013 alone was used as the agent of urbanization to predict urban growth in 2017. Upon validating, DB-CA model proved to be the better model, as it predicted 524.14 km2 of the study area as urban with higher accuracy (kappa co-efficient: 0.73) when compared to NN-CA model which predicted only 502.42 km2 as urban (kappa co-efficient: 0.71), while the observed urban cover of CMA in 2017 was 572.11 km2. This study also aimed at analyzing the effects of different types of neighbourhood configurations (Rectangular: 3 × 3, 5 × 5, 7 × 7 and Circular: 3 × 3) on the prediction output based on DB-CA model. To understand the direction and type of the urban growth, the study area was divided into five distance based zones with the State Secretariat as the center and entropy values were calculated for the zones. Results reveal that Chennai Corporation and its periphery experience congested urbanization whereas areas away from the Corporation boundary follow dispersed type of urban growth in 2017.

Students'Political Belief Education in Agricultural and Forestry Colleges and Universities in Network Environment:Taking Northwest A&F University as an Example

The influence of the network environment on the education of political beliefs of college students in China cannot be ignored.Taking Northwest A&F University as an example,starting from the current situation of students'political belief education in agricultural and forestry colleges and universities,the impact of network environment on the education of political beliefs of students in agricultural and forestry colleges and universities was analyzed,and the implementation path of improving political belief education in the network environment was explored,in order to provide a reference for improving the effectiveness of ideological and political education of students in agricultural and forestry colleges and universities.

Multimodal Belief Fusion for Face and Ear Biometrics

This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor responses and the proposed fusion is accomplished by Dempster-Shafer (DS) decision theory. Face and ear images are convolved with Gabor wavelet filters to extracts spatially enhanced Gabor facial features and Gabor ear features. Further, GMM is applied to the high-dimensional Gabor face and Gabor ear responses separately for quantitive measurements. Expectation Maximization (EM) algorithm is used to estimate density parameters in GMM. This produces two sets of feature vectors which are then fused using Dempster-Shafer theory. Experiments are conducted on two multimodal databases, namely, IIT Kanpur database and virtual database. Former contains face and ear images of 400 individuals while later consist of both images of 17 subjects taken from BANCA face database and TUM ear database. It is found that use of Gabor wavelet filters along with GMM and DS theory can provide robust and efficient multimodal fusion strategy.

Accountable capability improvement based on interpretable capability evaluation using belief rule base

A new approach is proposed in this study for accountable capability improvement based on interpretable capability evaluation using the belief rule base(BRB).Firstly,a capability evaluation model is constructed and optimized.Then,the key sub-capabilities are identified by quantitatively calculating the contributions made by each sub-capability to the overall capability.Finally,the overall capability is improved by optimizing the identified key sub-capabilities.The theoretical contributions of the proposed approach are as follows.(i)An interpretable capability evaluation model is constructed by employing BRB which can provide complete access to decision-makers.(ii)Key sub-capabilities are identified according to the quantitative contribution analysis results.(iii)Accountable capability improvement is carried out by only optimizing the identified key sub-capabilities.Case study results show that“Surveillance”,“Positioning”,and“Identification”are identified as key sub-capabilities with a summed contribution of 75.55%in an analytical and deducible fashion based on the interpretable capability evaluation model.As a result,the overall capability is improved by optimizing only the identified key sub-capabilities.The overall capability can be greatly improved from 59.20%to 81.80%with a minimum cost of 397.Furthermore,this paper also investigates how optimizing the BRB with more collected data would affect the evaluation results:only optimizing“Surveillance”and“Positioning”can also improve the overall capability to 81.34%with a cost of 370,which thus validates the efficiency of the proposed approach.

Chinese Adaptation and Psychometric Properties of the Belief in a Just World Scale for College Students

This study aims to revise the Belief in a Just World Scale(BJWS)for Chinese college students and test its reliability and validity(construct validity,convergent and divergent validity).Two samples of 546 and 595 college students were selected,respectively,using stratified cluster random sampling.Item analysis,exploratory factor analysis(EFA),confirmatory factor analysis(CFA),reliability analysis and convergent and divergent validity tests were carried out.The results showed that the 13 items of the BJWS have good item discrimination.The corrected item–total correlation in the general belief in a just world subscale was found to range from 0.464 to 0.655,and that in the personal belief in a just world subscale was 0.553 to 0.715.The internal consistency coefficients of the revised version of the BJWS and its subscales are good.The EFA and CFA results show that the structure and items of the revised scale are the same as those of the original scale.Belief in a just world was found to have significant positive correlations with gratitude and empathy,and has a significant negative correlation with anxiety,thereby exhibiting good convergent and divergent validity.Therefore,the Chinese revised version of the BJWS has good reliability and validity.