Does the Addition of Piracetam Safely and Effectively Improve Behavioral and or Cognitive Functions in Schizophrenia?

OBJECTIVE: The objective of this selective evidence based medicine (EBM) review is to determine whether or not the addition of piracetam safely and effectively improve behavioral and or cognitive functions in schizophrenia. STUDY DESIGN: The selected review from all English language, primary literature sources that were published between 1979 and 1999. DATA SOURCES: Three double blind randomized controlled trials (RCT) and one case controlled clinical study that compared piracetam to a visually matched placebo was selected and found using Medline, PubMed, Ebscohost, and Cochrane databases. OUTCOMES MEASURED: Each of the trials assessed the effect of Piracetam on behavioral and or clinical functions of Schizophrenia patients by utilizing the following assessment tools: Brief Psychiatric Rating Scale (BPRS), The Behavior Rating Scale, The Wing Symptom Rating, and Positive and Negative Syndrome Scale (PANSS). RESULTS: The trials demonstrated that the mean change before treatment with the use of piracetam as opposed to the visually matched placebo, as compared to after the treatment was large, with all statistically significant P values ≤ 0.05. This demonstrated that there was improvement in behavioral and cognitive functions achieved with the treatment of piracetam versus placebo. CONCLUSION: Based on the studies, all reported that with the use of piracetam in schizophrenia, there showed improvement of some type of behavioral and or cognitive functions above baseline. Although the pattern of outcome was similar in all the studies, there requires a continued and more updated investigation to be aimed at determining a specific dose of piracetam therapy, a specific patient population for which piracetam is most effective and to further elaborate its safety profile outside a controlled research setting

APPLYING ANALYTIC HIERARCHY PROCESS (AHP) TO SELECT CLIMATE CHANGE ADAPTATION METHODS IN AGRICULTURAL SECTOR: A LITERATURE REVIEW

Abstract: According to Conference of the Parties 22 (COP22) statement, climate change adaptation is the concern of not only an individual but also the whole society. Since the climate change issue is a multidimensional problem, decision-making in climate change adaptation is a complex process. In this paper, we analyze the advantages and disadvantages of three main group of decision-support tools, namely Expert preference, Monetary valuation, and Multi-criteria analysis (MCA). The paper recommends MCA in general and AHP in particular as effective tools to compensate for the disadvantages of other techniques as well as to overcome the challenges and requirements from the climate change adaptation decision-making process.Keywords: climate change, AHP, MCA, monetary valuation, expert preferenc

La maison tube des nouveaux quartiers d'Hanoï : effets de paramètres architecturaux sur l'ambiance thermique

Dans les pays tropicaux, comme le Vietnam, les gens vivent en permanence avec la chaleur et l'humidité, deux causes principales de conditions inconfortables. L'architecture traditionnelle vietnamienne a réduit les impacts négatifs du climat sur l'ambiance thermique à l'aide d'espaces ouverts tels des jardins, des cours intérieures et des puits de lumière. Toutefois, dans les maisons en milieu urbain, l'adaptation au climat a été minimisée à cause de leurs traits typologiques. Ces maisons, qui sont des habitations typiques de Hanoi depuis plusieurs décennies, sont étroites et profondes. De ces faits, pour les maisons de ville, en arriver à un design permettant d'obtenir à la fois le confort thermique et l'économie énergétique est toujours un défi pour l'architecte. Une bonne stratégie architecturale est donc particulièrement importante. Cette stratégie doit à la fois procurer une ambiance thermique intérieure confortable et minimiser l'utilisation d'appareils de climatisation, considérée comme une perte du point de vue énergétique. L'objectif principal de cette recherche est d'étudier l'influence de différentes stratégies architecturales sur la qualité de l'ambiance thermique dans la maison tube des nouveaux quartiers d'Hanoi. Cette étude a été réalisée à l'aide de simulations thermiques dynamiques avec le logiciel Derob-LTH. L'ensemble des résultats obtenus a permis de confirmer la plupart des hypothèses de recherche. Selon ces résultats, on peut conclure que les stratégies architecturales ont influencé l'ambiance thermique intérieure des maisons urbaines. De plus, on peut voir que certaines stratégies à faible coût et très simples à appliquer peuvent améliorer significativement l'ambiance thermique intérieure. Finalement, ce mémoire suggère une combinaison de stratégies architecturales pouvant augmenter significativement l'ambiance thermique intérieure des maisons urbaines

Análisis comparativo de K-NN, Naïve-Bayes y regresión logística para la detección de fraude con tarjetas de crédito

Introduction: This paper highlights the outcome of the comparative study of “Various Machine learning algorithms namely K-NN, Naive Bayes, and Logistic Regression for Credit Card Fraud Detection” carried out based on a dataset taken from UCI.com in 2022-23 at Manav Rachna International Institute of Research and Studies. Problem: Credit card fraud is still rife today and the modes are increasingly varied. Quite often we hear of fraud cases that cause irreplaceable injury to banks and financial institutions which cannot be compensated in terms of costs. To avoid scams with various modes of credit cards, we must be able to identify and find out the modes often used by fraudsters. This scheme liberates such financial institutions and banks with complete and appropriate information using Machine Learning Techniques, not only about the modes that scammers or fraudsters often use but also ways to protect against such frauds. Objective: The present paper discusses the various machine learning models based on classification and regression, namely K-Nearest Neighbors, Naïve Bayes, and Logistic Regression, which are successfully able to achieve the classification accuracy of 80% using Logistic Regression with a Precision of 78%, Recall of 100%, and F1-Score of 88% for fraudulent credit card transactions. Methodology: The comparative analysis demonstrates that for Precision, Recall, and Accuracy parameters, the K-Nearest Neighbor is a better approach for detecting fraudulent transactions than the Logistic Regression and Naïve Bayes. Results: The accuracy is marginal high in Logistic Regression but the False Positive parameters are not able to identify the imbalanced data; therefore, they disguise the results and accuracy of Logistic Regression and K-Nearest Neighbor deems fit for such cases. Conclusion: This scheme depicts the automated fraud classification systems using machine learning techniques, namely K-Nearest Neighbor, Logistic Regression, and Naive Bayes, to produce a model that can distinguish valid and invalid credit card transactions. Originality: Through this research, the most relevant features are used to go through the visualization of accuracy with the confusion matrix, and accuracy calculations are obtained from the dataset used.Limitations: Deep learning techniques could have been used to fetch even better results.Introducción: este artículo muestra el resultado de un estudio comparativo de “varios algoritmos de machine learning, a saber, K-NN, Naïve-Bayes y regresión logística para la detección de fraudes con tarjetas de crédito”, realizado con base en un conjunto de datos tomado de UCI.com en 2022-23 en el Instituto Internacional de Investigaciones y Estudios Manav Rachna. Problema: el fraude con tarjetas de crédito está muy extendido hoy en día y las modalidades son cada vez más variadas. A menudo, se oye hablar de casos de fraude que causan daños irreparables a bancos e instituciones financieras, que no pueden ser compensados en términos de costos. Para evitar estafas con diversos modos de tarjetas de crédito, se debe poder identificar y descubrir los modos que suelen utilizar los estafadores. Este esquema proporciona a dichas instituciones financieras y bancos información completa y adecuada utilizando técnicas de machine learning, no solo sobre los modos que suelen utilizar los estafadores o defraudadores, sino también sobre las formas de protegerse contra dichos fraudes. Objetivo: el presente artículo analiza los diversos modelos de machine learning basados en clasificación y regresión, a saber, K-Nearest Neighbors (K-NN), Naïve Bayes y regresión logística, que pueden lograr con éxito una precisión de clasificación del 80% utilizando regresión logística con una precisión de 78%, Retiro del 100% y F1 Score del 88% para transacciones fraudulentas con tarjeta de crédito. Método: el análisis comparativo muestra que, para los parámetros de precisión, recuperación y exactitud, el K-NN es un mejor enfoque para detectar transacciones fraudulentas que la regresión logística y el Naïve Bayes.Resultados: la precisión es marginalmente alta en la regresión logística, pero los parámetros de falso positivo no pueden identificar los datos desequilibrados; por lo tanto, disfrazan los resultados y la precisión de la regresión logística y el K-NN se considera adecuado para tales casos. Conclusión: este esquema describe los sistemas automatizados de clasificación de fraude que utilizan técnicas de machine learning, a saber, K-NN, Regresión logística y Naïve Bayes, para producir un modelo que pueda distinguir transacciones con tarjetas de crédito válidas e inválidas. Originalidad: a través de esta investigación, se utilizan las características más relevantes para visualizar la precisión con la matriz de confusión y se obtienen cálculos de precisión a partir del conjunto de datos utilizado.Limitaciones: se podrían haber utilizado técnicas de Deep learning para obtener mejores resultados

Applying analytic hierarchy process to adaptation to saltwater intrusion in Vietnam

Given the multidimensional nature of climate change issues, decision-making in climate change adaptation is a complex process, and suitable decision support methods are needed. The aim of this paper was to rank saltwater intrusion adaptation options for farmers in two provinces in the central coastal region of Vietnam using the analytical hierarchy process method. Data for the analysis were obtained through a literature review, field observations, and face-to-face interviews and focus group discussions with key informants. We combined two ways of weighting to arrive at final scores for each of the identified adaptation options: prioritizing criteria and subcriteria by pairwise comparison and rating the different alternatives with respect to the lowest level subcriteria. In doing so, we also investigated differences in the priority sets and final rankings of the analytical hierarchy process applications in both provinces. In our study, we worked with group consensus scores on both the criteria weights and the ratings for the different adaptation options for each of the criteria. Our results revealed that “sustainability and equity” was the most important criteria, while coherence ranked lowest. The final ranking of adaptation options differed between both provinces due to differences in the geographical and socioeconomic characteristics of the study areas. The consistency ratios for all pairwise matrices were less than 0.1, indicating that judgments from the focus group discussions with respect to the different criteria were highly consistent. A sensitivity analysis of our results confirmed the robustness of the rankings in our research

Desarrollo de la presión del sujetador: Sistema de medición con aire y sensor de presión

Introduction: This paper is the result of the research “Development of bra pressure measuring system using air pressure sensor” developed in the Ha Noi University of Science and Technology in 2019.  Proplem: The pressure of the bra on the human body affects the comfort of the wearer and the wearer's health. Therefore, bra pressure is one of the most important parameters taken into account when designing and manufacturing bras. Objective: To determine the pressure value of a bra, it is necessary to use a suitable pressure measuring device. Methodology: The device operates on the principle of resitive gas pressure sensor, with 8 measuring channels. The system is controlled by the computer via programming software in the Visual C language, measuring the pressure of the shirt on the position on the curved surface of the human body. Pressure values ​​and timed charts are displayed on the computer. The measuring device was tested with GE Druck DPI 610 pressure generator.  Results: Test results showed that the device has a sensitivity of 0.01 kPa, measuring range from 0.1to 10 kPa and an accuracy of 0.01 kPa. Conclusion: This measurement system is important for objectively assessing the pressure of the bra on the wearer.  Originality: This paper presents the results of research and design of the PB228 system when measuring the pressure of the bra on the wearer's body in static, dynamic and static-dynamic combined states.  Limitations: The accuracy of the device only applies in standard condition

Effects of Corporate Social Responsibility on Online Recruitment Processes in the Vietnamese Food and Beverage Industry

This paper examines the effect of CSR perceptions on online recruitment practices and outcomes in the Vietnamese food and beverage sector. Semi-structured interviews were conducted with seventeen participants, including CEOs, HR (human resource) staff and store managers. The results show that CSR perception varies and is exemplified through employee-related activities, ethical products, environment, philanthropy, and international standards. The study is novel in establishing that, despite high unemployment in developing economies, CSR communication in online recruitment sites impacts job applicants’ choice of company. While the strategic potency of CSR has been established, this study brings to light its critical significance for human resources processes, particularly online recruitment, in an emerging economy context. The study has considerable implications for practitioners and researchers, suggesting the necessity to strategically manage the interface between CSR and online recruitment

ASSESSING THE POTENTIAL OF COMMUNITY-BASED ECOTOURISM TOWARD SUSTAINABLE DEVELOPMENT: A CASE STUDY IN TUA CHUA KARST PLATEAU – DIEN BIEN – VIET NAM

Tua Chua Karst Plateau - a living area of the Mong ethnic group with spectacular natural landscapes, cool weather, and unique indigenous cultural values. They are all prerequisites for tourism development. This study aims to evaluate the potential of community-based ecotourism development in the Tua Chua Karst Plateau. This research uses the AHP method. Evaluation criteria include (i) uniqueness of natural landscape, (ii) indigenous cultural value, (iii) stakeholder engagement, (iv) local tourism development policy, (v) quality of infrastructure, (vi) quality of tourism facilities, (vii) accessibility, (viii) connectivity. The evaluation system includes eight criteria that have classified tourism resources according to each resource point and identified suitable internal and external potentials to exploit the geological value of the plateau and preserve indigenous culture. Results of this study reveal that the indigenous cultural values, the participation of local communities, and the uniqueness of the natural landscape have an important impact on the development of ecotourism. Tua Chua Karst Plateau has great potential for community-based ecotourism development with 14 tourist resource sites, of which 8 are highly appreciated

Geochemical characterization of groundwater and saltwater intrusion processes along the Luy River, Binh Thuan, Vietnam

With an average annual rainfall of 800-1150 mm/year, the Binh Thuan province is one of the driest places in Vietnam. The quantity and quality of groundwater play a significant role in the agriculture, aquaculture development and daily life of the local communities. In 2012, the national centre for water resources (Nawapi, 2012) delineated the seawater intrusion extent in Binh Thuan based on the total dissolved solids (TDS) content of water samples taken from shallow boreholes. The threshold of 3g/L and 1.5g/L were exceeded in the estuaries of the Luy, Long Song and Ca Ty rivers. In recent years, the prolonged droughts combined with the sea level rise and the over-extraction of groundwater during the dry season increased dramatically the seawater intrusion process especially in the estuaries of the province. The geochemistry of groundwater in the Luy River catchment was studied to investigate the contamination of the aquifers and identify the processes taking place. From 1991 to 2015, 98 water samples had been taken from the wells in the area in both dry and rainy seasons. 71% of the water samples were fresh while 21% and 5% were lightly saline and moderately saline respectively. In summer 2020, 110 new water samples from both shallow and deep wells were collected in the Luy river catchment in wells from 3m to 40m. The TDS values are ranging from 105 to 23080 mg/L and can be classified into 4 groups: freshwater (48%), slightly saline (40%), moderately saline (8%) and very saline (4%). The samples show that the seawater intrusion expands not only horizontally at shallow depth along the river but also deeper down the aquifer in most of the study area, what is also confirmed by geophysical data. Freshwater samples were mostly collected at a depth lower than 10m. The chemical composition of water samples was analyzed showing evidence of seawater intrusion, but also the occurrence of freshening processes within the study area. Together with the presence of saltwater at larger depths, this points towards a situation more complex than previously thought. Saltwater intrusions are likely not only related to interaction with the river estuary, but also to the presence of fossil saltwater in the aquifer, and to groundwater pumping and irrigation practices