Help Of Experts Research Articles

Constraints in Organizations of Agricultural Knowledge Creation, Information Management and Technology Delivery System in Bundelkhand Region of Uttar Pradesh, India

The present study was conducted to delineate the various constraints faced by the institutions doing agricultural knowledge, information management, and technology delivery. The Bundelkhand Region of U.P. was purposively chosen for this study because of the presence of major institutes such as the Indian Grassland and Fodder Research Institute (IGFRI), Central Agroforestry Research Institute and agricultural universities located in Banda and Jhansi, ICAR KVKs, state government line departments, ATMA and many related NGOs. Secondary data were collected through the study of extant literature. Identified major constraints were sorted out with the help of experts. Primary data was collected from officials of every organization through direct personal interviews and focussed group discussions. The total sample size was 50. The constraints were grouped into three categories; that is, constraints in knowledge creation, information management, and technology delivery. Rank Based Quotient (RBQ) method was used to quantify the responses, in order to establish the major constraints with severe effects. Findings revealed there is a need for knowledge experts to periodically train the work-force of the sampled organizations to update the skill of the scientists. Such up scaling of employees’ knowledge would increase digitalization, improve effective management of information; enhance coordination among different organizations while reducing duplicative efforts or misplaced efforts.

APPLICATION OF LEGAL RULES RELATED TO DEVIANT SEXUAL BEHAVIOR (EXHIBITIONISM)

This study aims to examine and analyze the phenomenon of the birth of deviant sexual behavior exhibitionism and examine and analyze the application of legal rules related to deviant sexual behavior exhibitionism. The results showed that The application of laws related to exhibitionism may use the offenses of Article 281 of the Criminal Code, Article 10, and Article 36 of the Pornography Law. The judge has the right to determine whether the defendant's actions can be accounted for or not, whether his soul is sick or not, and can be convicted or not. If the panel of judges believes that the defendant is incapable of responsibility and is convicted, then the defendant is free from punishment but is ordered to be treated in a mental hospital. In determining whether the defendant can be responsible or not, the judge usually asks for the help of a psychiatric expert to examine the condition of the defendant, which is commonly referred to as an expert witness in the trial as evidence listed in Article 184 paragraph (1) of the Code of Criminal Procedure.

Feasibility Study on Providing Bibliotherapy Services in Addiction Treatment Camps Affiliated with State Welfare Organization in Tehran Province

Background: The purpose of this study is to evaluate the feasibility of providing bibliotherapy services in addiction treatment camps affiliated with State Welfare Organization (SWO) in Tehran province. The research concerns information resources and manpower, financial resources and technical infrastructure as well as expressing the shortcomings and barriers of this method.
 Methods: The present study was conducted through a descriptive-survey method with an applied purpose in 2020. A questionnaire was developed by the researcher and validated with the help of experts. In order to assess the reliability of the questions, Cronbach's alpha test was used, which was calculated at 0.925. Sampling was performed using Cochran's formula. The sample size included 66 officials in 66 addiction treatment camps. SPSS software version 22 was used for data analysis
 Results: The possibility of providing bibliotherapy services in terms of specialized and committed manpower in the field of bibliotherapy in addiction treatment camps was desirable. These centers were not in a good financial position. There was also the possibility of providing bibliotherapy services in terms of the technical infrastructure and manpower. The most effective methods of implementing bibliotherapy in addiction treatment camps were creative and group methods. Lack of budget and trained staff, staff reluctance to provide bibliotherapy services and lack of support from SWO were obstacles which have hindered the provision of bibliotherapy services in addiction treatment camps in Tehran province.
 Conclusion: The benefits of providing bibliotherapy services in addiction treatment camps include increasing the client's psychological well-being, improving physical condition, preventing the client from returning to drug use, and to some extent, reducing the time of quitting drugs. Assessing and eliminating the shortcomings and barriers of bibliotherapy can play effective roles in the implementation of bibliotherapy.

How Resources Combining Expertise and Social Support Help Breastfeeding Women Address Self-Doubt and Increase Breastfeeding Self-Efficacy: A Mixed-Methods Study

ABSTRACT Existing research on parental information literacy focuses on parents’ ability to evaluate information. This approach does not account for conflicting or unwanted information and obscures the emotional impact of unsought information. We aimed to (1) document the sources women use most frequently for accessing breastfeeding information, (2) explore the reasons women choose some sources over others, (3) test the relationship between source characteristics and breastfeeding self-efficacy, and (4) determine the extent to which four source characteristics – competence, trustworthiness, goodwill, and social support – predict breastfeeding self-efficacy. This study was conducted in two phases. The first phase consisted of interviews and focus groups, which we analyzed inductively using a grounded theory approach. In phase two, we conducted a cross-sectional survey of women who were currently breastfeeding, collecting data on the source credibility and social support associated with the source they use most frequently and the participants’ breastfeeding self-efficacy. We used multiple regression to analyze our survey data. The frequency with which our participants encountered conflicting and unsought prompted them to view sources that combine expertise and social support as ideal. However, these sources are often difficult to access, leading to a reliance on online sources. This compromise has implications for breastfeeding tenure, as both competence and social support predicted breastfeeding self-efficacy. This study demonstrates how emotional aspects of information seeking shape women’s preferred sources, how accessibility limits the use of preferred sources, and how source competence and social support influence breastfeeding self-efficacy.

Study of the Traditional Rock Art of the Zo Tribes in Northeast India

Stone engraving or carving also known as petroglyph is an image created by removing part of a rock surface by incising, picking, carving or abrading, as a form of rock art. In the engraving, animals, men, ornaments, instruments, weapons and so on have been depicted which is the material culture of the Zo tribes. This article attempts to give a brief account of the living rock art tradition of the Zo people in the transborder area of Indo-Myanmar. The culture extended to Chin Hills and Mizoram who are the same group of southern Manipur. The periodisation of the studied rock art is beyond the understanding of a mere scholar without the help of experts. This article deals only with the petroglyph or rock art irrespective of megalith, monolith, dolmens or menhir. Efforts have been made to explore how these diverse tendencies can be beneficial within the study of rock art and history.

Neue Forschungen zu Leonardo da Vinci als Ingenieur

Abstract Although the 500th anniversary of Leonardo’s death in 2019 produced a wealth of new publications, including a four-volume monograph by Carmen Bambach, annotated new editions and the first monograph on Leonardo as an engineer, the myriad problems posed by his scientific and technological legacy have by no means been resolved. Much remains to be done on the reconstruction of the numerous writings he announced or intended to write later. As regards major projects such as the drainage of the Pontine Marshes we should consider the extent to which Leonardo could truly have conceived the plans associated with him without the help of other experts. Leonardo’s claimed military ambitions when he left Florence for Milan in 1482 have been accepted in the newly published monographs, although a wealth of material from the following years indicates that he became familiar with military matters only much later. This is particularly true of the military qualifications Leonardo lists in his first letter to Ludovico Sforza. His famous letter dates to the year 1489 and not to Leonardo’s move from Florence to Milan in 1482.

A critical review of multicriteria decision analysis practices in planning of urban green spaces and nature-based solutions

Abstract Green spaces and nature-based solutions (NBS) are increasingly considered by land-use planning policies to respond to the multiple challenges related to sustainable development. The multiple benefits brought by NBS make the use of multicriteria decision analysis (MCDA) essential to optimally balance their use. MCDA offers a catalog of methods allowing to structure problems with multiple objectives and to help adopt the optimal solution. However, NBS planning is a recent discipline and research is still ongoing to make this practice more common. We carried out a critical literature review on MCDA-NBS tools and practices, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method on the Web of Science database. We selected 124 papers on the subject between 2000 and 2022. We present a state-of-the-art MCDA approach for NBS and green space planning by looking at where these practices are applied, why and how this process is conducted, and who is involved in it. We found that studies are usually conducted in the global North on a single case study with the help of experts involved in the criteria weighting phase and the help of GIS MCDA tools often integrating a direct ranking method or the AHP method.

Let’s Talk LMCC (S01E04): Legal, Ethical and Organizational Aspects of Medicine - Confidentiality and Legal Systems

Welcome to the McGill Journal of Medicine (MJM) Let’s Talk LMCC Review. This podcast series was created to aid medical students studying for the Canadian Medical Council (MCC)’s licensing exam. Each episode is created based on specific LMCC objectives and is divided into two sections. In Section 1 we provide an overview of the topic with the help of experts in the field, followed by Section 2 where we review LMCC styled questions to help consolidate knowledge. In this episode, we welcome our expert advisor, Prof. Lara Khoury, an Associate Professor in the McGil Faculty of Law and Associate Member of McGill’s Institute for Health & Social Policy and Biomedical Ethics Unit, to speak on LMCC Objectives 121-4 Confidentiality and 121-5 Legal Systems. This episode was written by MJM Podcast Team members, Esther Kang, Sarah Grech, and Professor Lara Khoury.

Let’s Talk LMCC (S01E03): Legal, Ethical and Organizational Aspects of Medicine - Consent, Truth Telling and Negligence

Welcome to the McGill Journal of Medicine (MJM) Let’s Talk LMCC Review. This podcast series was created to aid medical students studying for the Canadian Medical Council (MCC)’s licensing exam. Each episode is created based on specific LMCC objectives and is divided into two sections. In Section 1 we provide an overview of the topic with the help of experts in the field, followed by Section 2 where we review LMCC styled questions to help consolidate knowledge. In this episode, we welcome our expert advisor, Dr. Carolyn Ells, a recently retired Associate Professor in the Department of Medicine at McGill, based at the Biomedical Ethics Unit, to speak on LMCC Objectives 121-1 Consent, 121-2 Truth Telling, and 121-3 Negligence. This episode was written by MJM Podcast Team members Amanda Sears and Esther Kang and Dr. Carolyn Ells.

Design of teaching aids in STEAM education and fuzzy hierarchical analysis of their educational effect

Focusing on problem-based learning (PBL) and the multi-disciplinary teaching of science, technology, engineering, arts, and mathematics (STEAM), we developed the evaluation tool of teaching aids in STEAM education to help students practice creative thinking and solution-finding. The fuzzy theory and the analytical hierarchy process were integrated for the evaluation of the acceptance of using robots in STEAM education. The fuzzy analytical hierarchy process (FAHP) was developed with the help of experts in education and industry who defined the goal, criteria, and alternatives (factors) of using teaching aids in STEAM education. FAHP was applied to the evaluation of three robots designed for STEAM education in this study. The result of the evaluation showed that the use of the designed robots in STEAM education was important in five criteria (structure, function, economy, aesthetic, and creativity). Among the alternatives, logic, creativity, simpleness, Avant-garde, and innovation were important for robots to be used for STEAM education. This indicated that artistic elements were important in the integration of them in STEAM education. The developed FAHP and questionnaire were useful in evaluating the acceptance of teaching aids in STEAM education. For the evaluation of the use of other teaching aids, the result of this study provides a basis and a reference for how teaching aids can be used for STEAM education.

APPLICATION OF HYBRID DIBR-FUCOM-LMAW-BONFERRONI-GREY-EDAS MODEL IN MULTICRITERIA DECISION-MAKING

The selection of unmanned aerial vehicles for different purposes is a frequent topic of research. This paper presents a hybrid model of an unmanned aerial vehicle (UAV) selection using the Defining Interrelationships Between Ranked criteria (DIBR), Full Consistency Method (FUCOM), Logarithm Methodology of Additive Weights (LMAW) and grey - Evaluation based on Distance from Average Solution (G-EDAS) methods. The above-mentioned model is tested and confirmed in a case study. First of all, in the paper are defined the criteria conditioning the selection, and then with the help of experts and by applying the DIBR, FUCOM and LMAW methods, the weight coefficients of the criteria are determined. The final values of the weight coefficients are obtained by aggregating the values of the criteria weights from all the three methods using the Bonferroni aggregator. Ranking and selection of the optimal UAV from twenty-three defined alternatives is carried out using the G-EDAS method. Sensitivity analysis confirmed a high degree of consistency of the solutions obtained using other MCDM methods, as well as changing the criteria weight coefficients. The proposed model has proved to be stable; its application is also possible in other areas and it is a reliable tool for decision-makers during the selection process.

Decision-making Support System for Predicting and Eliminating Malnutrition and Anemia

Aims: This study investigates predicting and eliminating malnutrition and anemia using ML Algorithms and comparing all the methods with various malnutrition-based parameters. Background: The health of the nation is more important than the wealth of the nation. Malnutrition and anemia are serious health issues but the least importance is given to eradicate them. Objective: Proper nutrition is an essential component for the survival, growth, and development of infants, children, and women who in turn give birth to infants. Methods: In the proposed system, machine learning approaches are utilized to predict the malnutrition status of children under five years of age and anemia in men and women using old datasets and further providing a suitable diet recommendation to overcome the disease. Classification techniques are being used for malnutrition as well as anemia prediction. Results: Algorithms such as Naïve Bayes classifier (NBC), Decision Tree (DT) algorithm, Random Forest (RF) algorithm, and K-Nearest Neighbor (k-NN) algorithm are utilized for prediction. The results obtained by these algorithms are 94.47%, 85%, 95.49%, and 63.15%. When compared, Naïve Bayes and random forest algorithm provided efficient results for malnutrition and anemia, respectively. Conclusion: By testing and validating, preventive actions can be taken with the help of medical experts and dieticians to reduce malnutrition and anemia conditions among children and elders, respectively.

Pharmaceutical humanitarian assistance in the establishment of a drug compounding laboratory in a refugee camp

In 1992 Medicus Mundi Mediterrània and the Sahrawi Arab Democratic Republic spearheaded a cooperation project to set up a small drug compounding laboratory in the Sahrawi refugee camps located in the desert town of Rabouni (Algeria's Tindouf province). The goal of the project was to build a drug compounding facility, create a training center for local staff, and ensure local production of medicines in cases of inadequate supply.With the help of external experts and of multiple public and private organizations and institutions, a small compounding laboratory was established with separate work areas, similar to the lines of the laboratories found in Spanish hospitals. The laboratory now has a stable team of 10-12 pharmacy technicians led by a pharmacist. In the last 25 years, 40 Sahrawis have been trained through internships in hospital pharmacy departments abroad, visits to drug compounding labs in other countries, tutoring, and ongoing training programs. Products that can be compounded in the laboratory include capsules, oral solutions, creams and ointments, topical solutions, eye drops, and sterile irrigation and lavage solutions. Over fifty different formulations of varying degrees of complexity have been prepared. One of the most significant challenges, given the political situation and the geographical environment, has been the procurement and transportation of the active ingredients and the packaging materials/equipment required for the compounding process. After 25 years of continuous work, this project is now a reality thanks to the effort and direct involvement of the Sahrawi people. The experience gained in the last few years has shown the importance of coordinating drug preparation with local prescribing physicians, as well as having quality standards and facilities with homologated low complexity basic equipment that allows, in other areas that is required, the replication of this model.

Outcome of radical cystectomy in remote area of Pakistan: Recep Tayyip Erdogan Hospital, Muzaffargarh (IHHN)

Background: Radical cystectomy with bilateral pelvic lymphadenectomy is the standard treatment for high grade/ muscle invasive urinary bladder tumor. Continent or incontinent urinary diversion is the part of this major operation. High volume centers perform routinely but low volume centers do less frequent. It might be because of availability of equipment and trained surgeon in remote area of Pakistan. Objectives: to assess the results of radical cystectomy at a low-volume center for high-grade muscle-invasive bladder tumours. For patients aged 50 to 75, this involves evaluating surgical complications, overall survival, and the absence of tumour recurrence throughout a one-year follow-up period. Study design: A Retrospective StudyDuration and place of study: Recep Tayyip Erdogan hospital, Muzaffargarh from October 2018 to August 2022 Methods: total Cases from both genders and 50 to 75 years old with High grade/ Muscle invasive urinary bladder carcinoma, incomplete resection during TURBT due to high volume of mass (irresistible) included. Performa designed for collection of information. All the patients underwent same procedure by same urologist. Patients were followed for one year after surgery. Results: All participants were followed for one year. 33.3% patients had paralytic ileus (CDC I), 13.3% had wound infection (CDC I) and 6.7% had urinary leakage (CDC IIIb). There was 86.6% overall survival rate. 6.7% lost to follow up. Mean operative time was 308 ±95 minutes. There was no recurrence noted throughout the study period. Conclusion: Good operative results can also achieve at low volume centers. High level of surveillance and expertise help to achieve better outcomes in remote. Keywords: cystectomy, radical cystectomy, bladder tumor, ileal conduit

Connecting population functionality with distribution model predictions to support freshwater and marine management of diadromous fish species

Diadromous fish species have a complex life cycle during which they migrate between marine and freshwater habitats. They experience multiple human-induced pressures in both environments, likely exacerbated by climate change, leading to dramatic population declines across their distribution ranges. Currently Species Distribution Models (SDMs) have been applied separately in both their continental and marine habitats to improve our understanding of their lifecycles and help with species management. Integrating the freshwater-sea continuum into the decisions would now be a step further in improving their management. With this objective, we developed a decision tree that links marine and freshwater SDM outputs with current observations of population functionality and suggested management guidance options for the viability of these species. Potential effects of climate change were included through future SDM projections to guide integrative and long-term management. Several criteria were proposed to assess the SDM validity considering the main sources of SDM uncertainties and local expert knowledge on habitat and population status. The framework was applied to approximately one hundred catchments from southern Portugal to southern Scandinavia for four diadromous species. At the European level, management guidance options differed between the two anadromous and two catadromous species. Platichthys flesus and Chelon ramada European populations seemed in better state than those of Alosa alosa and A. fallax. Finally, with the help of national diadromous species experts, we focused on four catchments distributed along the European latitudinal gradient to test the proposed methodology and demonstrate local management challenges in terms of freshwater-sea continuity.

Breast Cancer Detection in Histopathology Images using ResNet101 Architecture

Cancer is a significant challenge in many fields, especially health and medicine. Breast cancer is among the most common and frequent cancers in women worldwide. Early detection of cancer is the main step for early treatment and increasing the chances of patient survival. As the convolutional neural network method has grown in popularity, breast cancer can be easily identified without the help of experts. Using BreaKHis histopathology data, this project will assess the efficacy of the CNN architecture ResNet101 for breast cancer image classification. The dataset is divided into two classes, namely 1146 malignant and 547 benign. The treatment of data preprocessing is considered. The implementation of data augmentation in the benign class to obtain data balance between the two classes and prevent overfitting. The BreaKHis dataset has noise and uneven color distribution. Approaches such as bilateral filtering, image enhancement, and color normalization were chosen to enhance image quality. Adding flatten, dense, and dropout layers to the ResNet101 architecture is applied to improve the model performance. Parameters were modified during the training stage to achieve optimal model performance. The Adam optimizer was used with a learning rate 0.0001 and a batch size of 32. Furthermore, the model was trained for 100 epochs. The accuracy, precision, recall, and f1-score results are 98.7%, 98.73%, 98.7%, and 98.7%, respectively. According to the results, the proposed ResNet101 model outperforms the standard technique as well as other architectures.

Analysis of the productivity of the construction sector in terrestrial communication routes, of the Central region of the state of Tabasco

The study of productivity in the different sectors of the industry is an advance for the development of the same, which allows being a notable factor in developed or developing countries in the current globalized world. For the above mentioned, the present research allows to know the effect of the construction sector and the subsector of terrestrial communication routes, as well as the importance in the accessibility to the different communities and how this helps to strengthen the different branches of the economy. The methodology applied for the research was structural analysis (MICMAC), which allowed a search and selection of factors that directly affect the subject of study. As a result, 15 determining factors for productivity in the sector of study were classified and the level of impact was determined with the help of experts from organizations related to the same sectors, thus creating a real and comprehensive scenario of the situation and giving way to the construction of a development model for the region.

New bag of features using reinforcement Aquila optimization and weighted Bayesian Gaussian mixture modelling for dental images

AbstractDentistry diseases are worldwide concern with the fact that 5% of medical budget is spent on it. Dental diagnosis requires frequent visits to clinic and multiple personal check‐ups by an expert. This delays the process of diagnosis as well as introduces the danger of oral infection spread. Automation is boon to speed up the process of diagnosis, reduce expert's involvement and help in handling volume of patients. In situations like pandemic as seen in this decade, computer based automatic systems in health have proven their importance and necessity. For dental diagnosis, images are useful tool for better anatomical views and accurate decision of treatment. However, manual dental analysis increases load on dentists for initial check‐up that can be easily performed with automated systems or self‐kits. Oral cavity is a dental illness, if not identified and treated on time may lead to other serious ailments. This work presents a framework that performs tooth image classification for cavity and non‐cavity with new bag of features (NBoF) method. NBoF method is an attempt to improve the performance of bag of features (BoF) using the proposed reinforcement Aquila optimization (RAO) and weighted Bayesian Gaussian mixture modelling (WBGMM). An analysis of the performance of the NBoF using the proposed RAO and WBGMM is conducted using standard metrics. The comparative study of results proves that the proposed NBoF method outperforms the existing state‐of‐the‐art algorithms.

The German Revised version of the Niigata PPPD Questionnaire (NPQ-R): Development with patient interviews and an expert Delphi consensus.

Persistent postural-perceptual dizziness (PPPD) is a functional disorder of the nervous system and currently one of the most common types of chronic dizziness. Currently existing questionnaires do not fully assess patients' specific symptoms of PPPD. The Japanese Niigata PPPD Questionnaire (NPQ) was recently developed following consensus-based diagnosis criteria. The aim of this study was to translate it into German, evaluate its content with the help of experts and patients and, if necessary, revise the original version to allow for a comprehensive assessment of patients' PPPD-related symptoms. A 3-round expert Delphi survey and semi-structured patient interviews were conducted. 28 experts from Switzerland, Germany and Austria working in hospitals or outpatient centres were asked to complete a first questionnaire on various aspects of PPPD, on the translated, original NPQ and their own related experiences (Round one), a second questionnaire with statements regarding PPPD they could agree or disagree with using a 6-point Likert-scale (Round two), and a third survey to finally reach a consensus on statements to be integrated into the NPQ. In addition, eleven patients (mean age of 64.6±12.6 years; 6 females) were selected according to the criteria for the diagnosis of PPPD proposed by the Bárány Society and participated in a semi-structured interview asking for their opinion on the content of the original NPQ. All collected data were analysed using a descriptive evaluation and a qualitative content analysis based on verbatim transcripts. Seven new items were added to the NPQ based on expert and patient comments and ratings. Its revised version (NPQ-R) comprises 19 items divided into five subscales using a 7-point Likert-scale with two additional subscales relating to associated symptoms and symptom behaviour in PPPD. The new maximal score is 114 points compared to 72 for the NPQ. The NPQ-R is the first patient-reported outcome measurement for patients with PPPD in German. It should help to provide a comprehensive assessment of the intensity of PPPD in affected patients.

Sequential Modeling and Knowledge Source Integration for Identifying the Structure of a Bayesian Network for Multistage Process Monitoring and Diagnosis

Abstract As a popular applied artificial intelligence tool, Bayesian networks are increasingly being used to model multistage manufacturing processes for fault diagnosis purposes. However, the major issue limiting the practical adoption of Bayesian networks is the difficulty of learning the network structure for large multistage processes. Traditionally, Bayesian network structures are learned either with the help of domain experts or by utilizing data-driven structure learning algorithms through trial and error. Both approaches have their limitations. On the one hand, the expert-driven approach is costly, time-consuming, cumbersome for large networks, and susceptible to errors in assessing probabilities; on the other hand, data-driven approaches suffer from noise, biases, and inadequacy of training data and often fail to capture the physical causal structure of the data. Therefore, in this article, we propose a Bayesian network structure learning approach where popular manufacturing knowledge sources like the failure mode and effect analysis (FMEA) and hierarchical variable ordering are used as structural priors to guide the data-driven structure learning process. In addition, to introduce modularity and flexibility into the learning process, we present a sequential modeling approach for structure learning so that large multistage networks can be learned stage by stage progressively. Furthermore, through simulation studies, we compare and analyze the performance of the knowledge source–based structurally biased networks in the context of multistage process fault diagnosis.