Exclusive breastfeeding greater than 50%, success of education in a university hospital in Bogotá: Case-control study

BACKGROUND Maintenance rates of exclusive breastfeeding(EBF)worldwide are low,thus,one of the objectives of the summary of policies on breastfeeding(BF)in world nutrition goals for 2025 are that at least 50%of infants under six months of age receive EBF that year.The Objective of this study is to document the rates of EBF in children born in San Ignacio University Hospital(HUSI)and identify factors associated with maintenance.AIM To document the percentages of EBF in those that were born at HUSI and identify factors associated to their maintenance.METHODS This is a study of cases and controls in an analytic,retrospective cohort that took children born alive between January 2016 and January 2019 at HUSI located in the city of Bogotá,Colombia.RESULTS Receiving information about BF at HUSI was able to maintain EBF up until 4 mo(OR=1.65;95%CI:1.02-2.66).The presence of gynecologic and obstetric comorbidities(OR=0.32;95%CI:0.12-0.83),having mastitis(OR=0.56;95%CI:0.33-0.94),and receiving information from mass media(OR=0.52;95%CI:0.31-0.84)are factors associated with not maintaining EBF.CONCLUSION Receiving education at a Women-and Child-Friendly Institution was the only significant factor to achieve EBF until 4 mo,with a frequency greater than the one reported in the country,which matches multiple studies where counseling and individualized support on BF achieve this purpose.Knowledge about BF and early detection of obstetric/gynecologic complications must be strengthened among the healthcare staff in charge of mothers during post-partum.Additionally,strategies must be promoted to continue BF such as creating milk banks with the objective of increasing BF rates even when mothers return to work.

Sustainability in Higher Education Institutions(HEI):Merging the Study Systematic Review,Analysis Content and Bibliometrics

This study aims to explore how the topic of sustainability in Higher Education Institutions(HEI)has been addressed in the scientific literature.It presents a systematic literature review of peer-reviewed journal articles published between 1975 and 2019.After that,bibliometric and content analyses were performed in order to identify the behavior and evolution of the literature and identify the frequency with which they appear in the text,making it possible to raise replicable and valid inferences to the data.The results of this study indicate that the theme is emerging since the year 2010 and with a strong focus on qualitative studies,focused on critical theory.The results indicate that although studies involve the tripod environment,economy,and society,there is still a gap in studies that deal with specific issues to solve practical problems and that analyze the impacts from a more holistic perspective.The combination of methods made it possible to identify and interpret the articles in the selected sample,but based on results reported by other authors,with little room for quality control and integrity.

Artificial Intelligence Techniques Based Learner Authentication in Cybersecurity Higher Education Institutions

Education 4.0 is being authorized more and more by the design of artificial intelligence(AI)techniques.Higher education institutions(HEI)have started to utilize Internet technologies to improve the quality of the service and boost knowledge.Due to the unavailability of information technology(IT)infrastructures,HEI is vulnerable to cyberattacks.Biometric authentication can be used to authenticate a person based on biological features such as face,fingerprint,iris,and so on.This study designs a novel search and rescue optimization with deep learning based learning authentication technique for cybersecurity in higher education institutions,named SRODLLAC technique.The proposed SRODL-LAC technique aims to authenticate the learner/student in HEI using fingerprint biometrics.Besides,the SRODLLACtechnique designs a median filtering(MF)based preprocessing approach to improving the quality of the image.In addition,the Densely Connected Networks(DenseNet-77)model is applied for the extraction of features.Moreover,search and rescue optimization(SRO)algorithm with deep neural network(DNN)model is utilized for the classification process.Lastly,template matching process is done for fingerprint identification.A wide range of simulation analyses is carried out and the results are inspected under several aspects.The experimental results reported the effective performance of the SRODL-LAC technique over the other methodologies.

Assessment of Gender Policy in Selected Tertiary Agricultural Education Institutions in Africa

The paper assesses the existing gender policy document in fourteen (14) selected agricultural faculties and colleges in tertiary institutions in Africa. This paper is an output of research report on Programme of Strengthening Africa’s Strategic Agricultural Capacity for Impact on Development (SASACID) implemented by the African Network for Agriculture, Agroforestry and Natural Resources Education (ANAFE). Data for the study were collected from 207 respondents (8 deans of ANAFE SASACID pilot institutions, 36 academic staff/lecturers of SASACID pilot institutions and 163 students of SASACID pilot institutions) through the use of online survey. Data collected were analysed and presented using frequency, percentage and charts. Results of the survey revealed that 25.0% of the institutions studied indicated that they had a formal gender policy document in place in their institutions with regards to staff recruitment and students’ admission, while about 25.0% had an informal gender practices on staff recruitment and students’ admission. Higher proportion (60.0%) of the institution had neither a formal policy document nor informal practices as regards staff recruitment and students admission. Some of the constraints faced by the Institutions with a gender policy were insufficient female applicants in agricultural courses, societal norms and remote location of some of the faculties/colleges of agriculture. To encourage both males and females to study agriculture in higher institutions of learning and to create and sustain a fair and just academic environment where both have equal opportunities, there is a need to have a gender policy document and the need to create awareness.

Enhanced Artificial Intelligence-based Cybersecurity Intrusion Detection for Higher Education Institutions

As higher education institutions(HEIs)go online,several benefits are attained,and also it is vulnerable to several kinds of attacks.To accomplish security,this paper presents artificial intelligence based cybersecurity intrusion detection models to accomplish security.The incorporation of the strategies into business is a tendency among several distinct industries,comprising education,have recognized as game changer.Consequently,the HEIs are highly related to the requirement and knowledge of the learner,making the education procedure highly effective.Thus,artificial intelligence(AI)and machine learning(ML)models have shown significant interest in HEIs.This study designs a novel Artificial Intelligence based Cybersecurity Intrusion Detection Model for Higher Education Institutions named AICIDHEI technique.The goal of the AICID-HEI technique is to determine the occurrence of distinct kinds of intrusions in higher education institutes.The AICID-HEI technique encompassesmin-max normalization approach to preprocess the data.Besides,the AICID-HEI technique involves the design of improved differential evolution algorithm based feature selection(IDEA-FS)technique is applied to choose the feature subsets.Moreover,the bidirectional long short-term memory(BiLSTM)model is utilized for the detection and classification of intrusions in the network.Furthermore,the Adam optimizer is applied for hyperparameter tuning to properly adjust the hyperparameters in higher educational institutions.In order to validate the experimental results of the proposed AICID-HEI technique,the simulation results of the AICIDHEI technique take place by the use of benchmark dataset.The experimental results reported the betterment of the AICID-HEI technique over the other methods interms of different measures.

A Survey on the Continuing Education Status and Demand of Nurses in Chongqing Grass-Root Medical Institutions

Background: With the increased aging of population, the continuous increase in the morbidity of chronic diseases, and the issuance of universal two-child policy, the grass-root medical teams become more and more important. Objective: To investigate the continuing education status and demand of nurses in the grass-root medical institutions and thus provide a reference for optimizing the continuing education plan. Methods: From October 2018 to May 2019, a survey of 270 nurses from 28 grass-root medical institutions in Tongliang District of Chongqing was performed using a self-designed questionnaire. Results: In the grass-root medical institutions, the major continuing education pattern of nurses was hospital training and distance education;the continuing education focused on new basic theoretical knowledge and new nursing techniques, and its satisfaction was 67.8%. About 20.6% questionnaire answerers never had received continuing nursing education. As shown by one-way analysis of variance (ANOVA) and binary logistic regression analysis, the following factors were associated with the continuing education participation in the past three years: work unit, organizational affiliation, age, professional title and hospital policies. There were 93.0% questionnaire answerers reflecting that it was necessary to participate in the continuing education and wishing the conformance between the pattern and contents of continuing nursing education and the actual implementation status. Conclusion: The continuing education demand of nurses in the grass-root medical institutions is basic but diverse, and the organizations shall provide effective policy support for continuing education and make the diversified training plan by combining Internet technology, so as to realize the maximization of continuing education participation and keep improving the overall service quality of gross-root nurses.

Factors Influencing Students Decisions to Enrollment in Sudanese Higher Education Institutions

There is a growing body of literature that recognizes the importance of data mining in educational systems. This recognition makes educational data mining a new growing research community. One way to achieve the highest level of quality in a higher education system is by discovering knowledge from educational data such as students’ enrollment data. Many mining tools that aim to discover exciting correlations, frequent patterns, associations, or casual structures among sets of items in educational data sets have been proposed. One of the widely used tools is association rules. In this paper, the Apriori algorithm is used to generate association rules to discover the importance and correlation between factors that influence student’s decision to enroll in higher education institutions in Sudan. The algorithm is applied using a student’s enrollment data set that was created using a questionnaire and 800 students enrolled in governmental and private sector universities as a sample. This paper classifies factors that influence enrollment into: student’s demographic factors and four categories of enrollment related factors (Student and Society, Educational Institution, Admission, and Employment related factors), and determines the most influential factors in determining student’s decision to enroll in Sudanese universities. The analysis result shows that the Educational Institution related factors (50%) and Admission related factors (40%) are strongly influencing students’ enrollment decision, while the Employment related factors (10%) and Student and Society related factors (0%) have weak influence. The factors out of the 14 Educational Institution related factors that have a high impact are: reputation, diversity of study, quality of education, education facilities, and feasibility.

Threefold Optimized Forecasting of Electricity Consumption in Higher Education Institutions

Energy management benefits both consumers and utility companiesalike. Utility companies remain interested in identifying and reducing energywaste and theft, whereas consumers’ interest remain in lowering their energyexpenses. A large supply-demand gap of over 6 GW exists in Pakistan asreported in 2018. Reducing this gap from the supply side is an expensiveand complex task. However, efficient energy management and distributionon demand side has potential to reduce this gap economically. Electricityload forecasting models are increasingly used by energy managers in takingreal-time tactical decisions to ensure efficient use of resources. Advancementin Machine-learning (ML) technology has enabled accurate forecasting ofelectricity consumption. However, the impact of computation cost affordedby these ML models is often ignored in favour of accuracy. This studyconsiders both accuracy and computation cost as concurrently significantfactors because together they shape the technology environment as well ascreate economic impact. Thus, a three-fold optimized load forecasting modelis proposed which includes (1) application specific parameters selection, (2)impact of different dataset granularities and (3) implementation of specificdata preparation. It deploys and compares the widely used back-propagationArtificial Neural Network (ANN) and Random Forest (RF) models for theprediction of electricity consumption of buildings within a university. In addition to the temporal and historical power consumption date as input parameters, the study also embeds weather data as well as university operationalcalendars resulting in improved performance. The outcomes are indicativethat the granularity i.e. the scale of details in data, and set of reduced and fullinput parameters impact performance accuracies differently for ANN and RFmodels. Experimental results show that overall RF model performed betterboth in terms of accuracy as well as computational time for a 1-min, 15-minand 1-h dataset granularities with the mean absolute percentage error (MAPE)of 2.42, 3.70 and 4.62 in 11.1 s, 1.14 s and 0.3 s respectively, thus well suitedfor a real-time energy monitoring application.

The Comparison of Ten Biggest Distance Education Institutions in the World

The 1995 International Council of Distance Education（ICDE）In Blrmingham，Britain selected ten（llstance education mstltutlons with an enrollment of over 100，000Inthe world． Theyrespectively belong to China，阶ance，India，Indonesia，

A Study on the Management of Career Development of Young Teachers in Higher Education Institutions from the Perspective of Career Anchors

In January 2021,six departments in China,including the Ministry of Education jointly issued the Guiding Opinions on Strengthening Reform in HEI Teacher Capacity Building for the New Era which emphasizes support for career development of young teachers.From the perspective of the career anchor theory,this paper takes human resource management as a tool to analyze organizational environment at the macro and micro levels to find out how to facilitate career development of young teachers in higher education institutions.

Total Quality Management at Algerian Higher Education Institutions to Promote Our Roles in Comprehensive Development

The aims this study to know the reality of the role for Total Quality Management(TQM)to need of Algerian Higher Education Institutions(AHEI)in apply the Total Quality Management(TQM)to promote the Comprehensive Development(CD),and this approach to enhance their roles in the comprehensive development,the efficiency of the training process,global changes and their needs to adopt a new educational policy in line with the global transformation competition,and the requirements of sustainable development,in this study was used a questionnaire composed of(75)items distributed on(08)areas,This is for confirmation the need to adopt philosophy of Total Quality Management(TQM)as a strategy imposed by the nature and the stage experienced for Algerian Higher Education Institutions(AHEI),And deal with the nature of the changes and challenges imposed by certain factors such as Globalization and the knowledge revolution,through all this inevitably to apply the Total Quality Management(TQM)in our Algerian Higher Education Institutions(AHEI).

Empirical Research on the Status Quo of Teachers of Common Required Courses in Vocational Higher Education Institutions

In order to build a high-quality team of teachers in vocational higher education institutions, and investigate the current situation of teachers of common required courses in vocational higher education institutions of Hainan Province, an empirical research is conducted. A questionnaire survey was carried out in aspects of satisfaction of teaching and scientific research, professional quality, work saturation and teacher’s job satisfaction. The research results shows that the professional quality of teachers of common required courses cannot significantly influence the satisfaction of teaching and scientific research;Job saturation can positively influence teaching and research satisfaction;teaching and research satisfaction can positively influence teachers’ job satisfaction.

Coping Strategies of Nigeria Higher Education Institutions during COVID-19 Lockdown

Beginning at the end of the year 2019,the novel coronavirus(COVID-19)has drowned the world into uncertainty and has threatened the continuity of traditional classroom learning that is the backbone and,in many cases,the main method of learning in most countries.This paper seeks to ascertain how Higher Institutions of learning in Nigeria have thrived during the lockdown period,based on the National policy document that spells out the guidelines for school reopening.Official documents such as newspaper reports university bulletins are used to corroborate in order to ascertain the implementation of the provisions of the policy guideline document as well as assess the efficacy of the measures on students’quality of learning.

A Sentiment Analysis Based Model for Recruitment by Higher Institutions

The traditional roles of a university are teaching and research with the aim of developing society and contributing positively to the national economic development by producing skilled and well-tutored graduates. However, recruitments by these higher institutions are too reliant on the eligibility provided by Resumes of candidates, while neglecting their suitability drawn from their research activity and publications online. This study identifies insights in recruitment trends in higher institutions of learning and uses Artificial Intelligence to produce a more rounded and balanced decision-making process that caters for both eligibility and suitability. The methodology employs the machine learning process using the Multinomial Naïve Bayes for training the model as well as the Vader sentiment analyzer for accuracy and testing. The datasets used contained Resume instances as well as author publication information. The results show a score of 83.9% for the model as well as a sentiment analysis score of 1, indicating an overall positive score. The results show that sentiment analysis can help educational institutions in improving their recruitment models and attracting more suitable candidates for such roles.

Coordinating rural-urban education and institution innovation

In order to implement the spirit of the Sixteenth National People＇s Congress to accelerate development of rural education, deepen reform of rural education, guarantee a well-off society, and harmonize rural and urban development, coordinating ruralurban education is the key to China＇s development. At present, the rural-urban coordinating education is influenced by many factors, including rural-urban income difference, rural-urban educational resources difference, rural-urban background difference, and rural- urban institutional difference. In order to realize the coordinating development of rural-urban education, we need innovation in ＂Hukou＂ institution, land institution, financial institution and rural education institution. Institution innovation would be the guarantee to the coordinating rural-urban education.

Valorization of Solid Waste Recovery in an Institution of Higher Education

One of the biggest challenges for organizations, cities and countries is waste management. Currently, 1.3 million tons of solid wastes are generated in the cities and by 2025 it is estimated that this volume will increase up to 2.2 billion tons. Considering this, it is clear that strategies for the reduction of waste generation are needed. In order to achieve this arduous and critic task changes in education, culture and public policy are required and one of the strategies that emerge as one of the most effective is the “zero waste” programs. This paper shows the foundation of a zero waste program based on previous and successful experiences in institutions of higher education. It presents the characterization and quantification of waste, as well as the valorization of it and potential environmental and economic benefits of the implementation of this kind of programs in higher education institutions. Results show that reduction and valorization of waste generation is possible in academic sectors while other outcomes emerge, such as the generation of human capital for the implementation of this kind of programs in different sectors of society and, in that way, contribute in the transition towards sustainable development.

The Department of Otolaryngology Head and Neck Surgery,PLA General Hospital (national key academic unit) The PLA Institute of Otolaryngology (PLA key laboratory for acoustic trauma) The PLA Medical College Department of Deafness Education Key Laboratory

Led by four generations of leadership from late Prof.JIANG Sichang(academician,Chinese Academy of Engineering),Prof.YANG Weiyan(Honorary President,Division of Otolaryngology Head and Neck Surgery,Chinese Medical Association),Prof.HAN Dongyi(President Elected,Division of Otolaryngology Head and Neck Surgery,Chinese Medical Association)to now Prof.YANG Shiming(President,Division of Otolaryngologists,

Effects of Peer Health Education on Sexual Health Knowledge and Attitudes of Tertiary Institution Students in Imo State, Nigeria

This study was designed to determine effects of peer-health-education on sexual health knowledge and attitudes of tertiary institution students in Imo State Nigeria by determining the mean gain scores of sexual health knowledge and attitudes after peer health education. Quasi-experimental (pre-test-post-test) research design was employed. Two hundred students drawn from the University, Polytechnic and College of Education, using a multi-stage sampling technique participated in the peer sessions which were facilitated by trained peer educators. Data were analyzed using ANCOVA and Z-test. Findings revealed improved knowledge and attitudes on sexual health, as depicted by positive mean gain scores. Age group 16 - 20 years had the highest mean gain score (<img src="Edit_8e8f0539-e2c6-47bc-80f1-ccaee4c06df5.png" alt="" /> = 22.31) of sexual health knowledge than the rest, while age group 26 - 30 years had the highest mean gain score (<img src="Edit_dec53aa0-f549-425f-baf4-08f39aaf05fd.png" alt="" /> = 10.59) of sexual health attitudes. Males had higher mean gain score (<img src="Edit_e767bc6a-c1f3-4f0a-8b31-814581d9dd64.png" alt="" /> = 26.05) of sexual health knowledge, while females had higher mean gain score (<img src="Edit_79f87968-38f8-4873-8516-f5370ba691df.png" alt="" /> = 9.77) of sexual health attitudes. The first years (100 level students) had the highest mean gain score (<img src="Edit_3f417e44-7627-4d69-860e-94c94ae7db0e.png" alt="" /> = 25.71) of sexual health knowledge and also had the highest mean gain score (<img src="Edit_2a60fbc7-0a2c-49fe-b9a2-1cea354966a3.png" alt="" /> = 14.12) of sexual health attitudes. Level of study was significant both for knowledge and attitudes (P < 0.01). It is recommended that peer-health-education be explored further as a method of communicating sexual health issues to tertiary institution students and youths generally.