Search results for: optimize profit

Authors: Evgeny Pokushalov, Andrey Ponomarenko, John Smith, Michael Johnson, Claire Garcia, Inessa Pak, Evgenya Shrainer, Dmitry Kudlay, Sevda Bayramova, Richard Miller

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Background: Obesity is a complex, multifactorial chronic disease that poses significant health risks. Recent advancements in artificial intelligence (AI) offer the potential for more personalized and effective dietary supplement (DS) regimens to promote weight loss. This study aimed to evaluate the efficacy of AI-guided DS prescriptions compared to standard physician-guided DS prescriptions in obese patients. Methods: This randomized, parallel-group pilot study enrolled 60 individuals aged 40 to 60 years with a body mass index (BMI) of 25 or greater. Participants were randomized to receive either AI-guided DS prescriptions (n = 30) or physician-guided DS prescriptions (n = 30) for 180 days. The primary endpoints were the percentage change in body weight and the proportion of participants achieving a ≥5% weight reduction. Secondary endpoints included changes in BMI, fat mass, visceral fat rating, systolic and diastolic blood pressure, lipid profiles, fasting plasma glucose, hsCRP levels, and postprandial appetite ratings. Adverse events were monitored throughout the study. Results: Both groups were well balanced in terms of baseline characteristics. Significant weight loss was observed in the AI-guided group, with a mean reduction of -12.3% (95% CI: -13.1 to -11.5%) compared to -7.2% (95% CI: -8.1 to -6.3%) in the physician-guided group, resulting in a treatment difference of -5.1% (95% CI: -6.4 to -3.8%; p < 0.01). At day 180, 84.7% of the AI-guided group achieved a weight reduction of ≥5%, compared to 54.5% in the physician-guided group (Odds Ratio: 4.3; 95% CI: 3.1 to 5.9; p < 0.01). Significant improvements were also observed in BMI, fat mass, and visceral fat rating in the AI-guided group (p < 0.01 for all). Postprandial appetite suppression was greater in the AI-guided group, with significant reductions in hunger and prospective food consumption, and increases in fullness and satiety (p < 0.01 for all). Adverse events were generally mild-to-moderate, with higher incidences of gastrointestinal symptoms in the AI-guided group, but these were manageable and did not impact adherence. Conclusion: The AI-guided dietary supplement regimen was more effective in promoting weight loss, improving body composition, and suppressing appetite compared to the physician-guided regimen. These findings suggest that AI-guided, personalized supplement prescriptions could offer a more effective approach to managing obesity. Further research with larger sample sizes is warranted to confirm these results and optimize AI-based interventions for weight loss.

Keywords: obesity, AI-guided, dietary supplements, weight loss, personalized medicine, metabolic health, appetite suppression

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Authors: Valentina Tereshkova

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The paper shows how the relationship between international law and national sovereignty is viewed through the implementation of European Court of Human Right judgments. Methodology: Сonclusions are based on a survey of representatives of the legislative authorities and judges of the Krasnoyarsk region, the Rostov region, Sverdlovsk region and Tver region. The paper assesses the activities of the Russian Constitutional Court from 1998 to 2015 related to the establishment of the implementation mechanism and the Russian Constitutional Court judgments of 14.07.2015, № 21-P and of 19.04.2016, № 12-P where the Constitutional Court stated the impossibility of executing ECtHR judgments. I. Implementation of ECHR judgments by courts and other authorities. Despite the publication of the report of the RF Ministry of Justice on the implementation, we could not find any formal information on the Russian policy of the ECtHR judgment implementation. Using the results of the survey, the paper shows the effect of ECtHR judgments on law and legal practice in Russia. II. Implementation of ECHR judgments by Russian Constitutional Court. Russian Constitutional Court had implemented the ECtHR judgments. However, the Court determined on July, 14, 2015 its competence to consider the question of implementation of ECHR judgments. Then, it stated that the execution of the judgment [Anchugov and Gladkov case] was impossible because the Russian Constitution has the highest legal force on April, 19, 2016. Recently the CE Committee of Ministers asked Russia to provide ‘without further delay’ a compensation plan for the Yukos case. On November 11, 2016, Constitutional Court accepted a request from the Ministry of Justice to consider the possibility of execution of the ECtHR judgment in the Yukos case. Such a request has been made possible due to a lack of implementation mechanism. Conclusion: ECtHR judgments are as an effective tool to solve the structural problems of a legal system. However, Russian experts consider the ECHR as a tool of protection of individual rights. The paper shows link between the survey results and the absence of the implementation mechanism. New Article 104 par. 2 and Article 106 par. 2 of the Federal Law of the Constitutional Court are in conflict with international obligations of the Convention on the Law on Treaties 1969 and Article 46 ECHR. Nevertheless, a dialogue may be possible between Constitutional Court and the ECtHR. In its judgment [19.04.2016] the Constitutional Court determined that the general measures to ensure fairness, proportionality and differentiation of the restrictions of voting rights were possible in judicial practice. It also stated the federal legislator had the power ‘to optimize the system of Russian criminal penalties’. Despite the fact that the Constitutional Court presented the Görgülü case [Görgülü v Germany] as an example of non-execution of the ECtHR judgment, the paper proposes to draw on the experience of German Constitutional Court, which in the Görgülü case, on the one hand, stressed national sovereignty and, on the other hand, took advantage of this sovereignty, to resolve the issue in accordance with the ECHR.

Keywords: implementation of ECtHR judgments, sovereignty, supranational jurisdictions, principle of subsidiarity

Procedia PDF Downloads 194

Authors: Emanuela Zilli, Suana Tikvina, Davide Bonaldo, Monica Varotto, Scilla Rizzardi, Barbara Ruzzante, Raffaele Napolitano, Stefano Bevilacqua, Antonella Ruffatto

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A healthy workplace increases productivity, creativity and decreases absenteeism and turnover. It also contributes to creating a more secure work environment with fewer risks of violence. In the past 3 years, the healthcare system has suffered the psychological, economic and social consequences of the COVID-19 pandemic. On the other hand, the healthcare staff reductions determine high levels of work-related stress that are often unsustainable. The Hospital of Cittadella (in the province of Padua) has 400 beds and serves a territory of 300,000 inhabitants. The hospital itself counts 1.250 healthcare employees (healthcare professionals). This year, the Medical Board of Directors has requested additional staff; however, the economic situation of Italy can not sustain additional hires. At the same time, we have initiated projects that aim to increase well-being, decrease stress and encourage activities that promote self-care. One of the projects that the hospital has organized is the psychomotor practice. It is held by therapists and trainers who operate according to the traditional method. According to the literature, the psychomotor practice is specifically intended for the staff operating in the Intensive Care Unit, Emergency Department and Pneumology Ward. The project consisted of one session of 45 minutes a week for 3 months. This method brings focus to controlled breathing, posture, muscle work and movement that help manage stress and fatigue, creating a more mindful and sustainable lifestyle. In addition, a Qigong course was held every two weeks for 5 months. It is an ancient Chinese practice designed to optimize the energy within the body, reducing stress levels and increasing general well-being. Finally, Tibetan singing crystal bowls sessions, held by a music therapist, consisted of monthly guided meditation sessions using the sounds of the crystal bowls. Sound therapy uses the vibrations created from the crystal bowls to balance the vibrations within the body to promote relaxation. In conclusion, well-being and organizational performance are closely related to each other. It is crucial for any organization to encourage and maintain better physical and mental health of the healthcare staff as it directly affects productivity and, consequently, user satisfaction of the services provided.

Keywords: health promotion, healthcare workers management, Weel being and organizational performance, Psychomotor practice

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Authors: Farhad Ahmadi, Hammed Kimiaee

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Context: This research study focuses on the effect of different levels and sources of calcium on egg production, egg traits, and calcium retention in laying Japanese quail. The study aims to determine the impact of nano calcium carbonate (NCC) and calcium carbonate (CC) on these factors. Research Aim: The main objective of this research is to investigate the effect of different levels and sources of calcium on egg production, egg traits, and calcium retention in laying Japanese quail. Specifically, the study aims to compare the effects of NCC and CC on these parameters. Methodology: The research was conducted using a total of 280 laying quail with an average age of 8 weeks. The quails were randomly distributed in a completely randomized design (CRD) with 7 treatments, 4 replications, and 10 quails in each pen. The study lasted for 90 days. The experimental diets included a control group (T1) with a basal diet consisting of 3.17% CaCO₃, and other groups supplemented with different levels (0.5%, 0.1%, and 0.15%) of either calcium carbonate (CC) or nano calcium carbonate (NCC). The quails had free access to water and feed throughout the study period. Findings: The results of the study showed that NCC at the levels of 0.1% and 0.15% (T6 and T7) improved eggshell thickness, shell thickness, and shell breaking strength compared to the control group. Although not statistically significant, there was an increasing trend in quail egg production and calcium retention in the calcareous shell of the egg in birds that consumed the experimental diets containing different levels of NCC compared to the control and other treatment groups. Theoretical Importance: This research contributes to our understanding of the effect of NCC and CC on egg production, egg traits, and calcium retention in laying Japanese quail. It highlights the potential benefits of using NCC as a calcium source in quail diets, specifically in improving the quantity and quality of eggs and calcium retention. Data Collection and Analysis Procedures: Quail egg production was recorded monthly for each treatment group. At the end of the study, a total of 40 eggs (10 eggs/replicate) from each treatment group were randomly selected for analysis. Parameters such as eggshell thickness, shell thickness, shell breaking strength, and calcium retention were measured. Statistical analysis was performed to compare the results between the different treatment groups. Questions Addressed: This research aimed to answer the following questions: What is the effect of different levels and sources of calcium on egg production, egg traits, and calcium retention in laying Japanese quail? How does nano calcium carbonate compare to calcium carbonate in terms of these parameters? Conclusion: In conclusion, this study suggests that NCC at the levels of 0.1% and 0.15% can improve the quantity and quality of eggs and calcium retention in laying Japanese quail. These findings highlight the potential benefits of using NCC as a calcium source in quail diets. Further research could be conducted to explore the mechanisms behind these improvements and optimize the dosage of NCC for maximum effect.

Keywords: egg, calcium, nanoparticles, retention

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Authors: Vlad Andrei Raducanu, Mariana Lucia Angelescu, Ion Cinca, Vasile Danut Cojocaru, Doina Raducanu

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By using smart digital tools, such as generative design (GD) and digital fabrication (DF), problems of high actuality concerning resources optimization (materials, energy, time) can be solved and applications or products of free-form type can be created. In the new digital technology materials are active, designed in response to a set of performance requirements, which impose a total rethinking of old material practices. The article presents the design procedure key steps of a free-form architectural object - a column type one with connections to get an adaptive 3D surface, by using the parametric design methodology and by exploiting the properties of conventional metallic materials. In parametric design the form of the created object or space is shaped by varying the parameters values and relationships between the forms are described by mathematical equations. Digital parametric design is based on specific procedures, as shape grammars, Lindenmayer - systems, cellular automata, genetic algorithms or swarm intelligence, each of these procedures having limitations which make them applicable only in certain cases. In the paper the design process stages and the shape grammar type algorithm are presented. The generative design process relies on two basic principles: the modeling principle and the generative principle. The generative method is based on a form finding process, by creating many 3D spatial forms, using an algorithm conceived in order to apply its generating logic onto different input geometry. Once the algorithm is realized, it can be applied repeatedly to generate the geometry for a number of different input surfaces. The generated configurations are then analyzed through a technical or aesthetic selection criterion and finally the optimal solution is selected. Endless range of generative capacity of codes and algorithms used in digital design offers various conceptual possibilities and optimal solutions for both technical and environmental increasing demands of building industry and architecture. Constructions or spaces generated by parametric design can be specifically tuned, in order to meet certain technical or aesthetical requirements. The proposed approach has direct applicability in sustainable architecture, offering important potential economic advantages, a flexible design (which can be changed until the end of the design process) and unique geometric models of high performance.

Keywords: parametric design, algorithmic procedures, free-form architectural object, sustainable architecture

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Authors: Su Yin Chiam, Zhipeng Ding, Guang Yang, Danny Jian Hang Tng, Peiyi Song, Geok Ing Ng, Ken-Tye Yong, Qing Xin Zhang

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Brain-machine interfaces (BMI) is a ground rich of exploration opportunities where manipulation of neural activity are used for interconnect with myriad form of external devices. These research and intensive development were evolved into various areas from medical field, gaming and entertainment industry till safety and security field. The technology were extended for neurological disorders therapy such as obsessive compulsive disorder and Parkinson’s disease by introducing current pulses to specific region of the brain. Nonetheless, the work to develop a real-time observing, recording and altering of neural signal brain-machine interfaces system will require a significant amount of effort to overcome the obstacles in improving this system without delay in response. To date, feature size of interface devices and the density of the electrode population remain as a limitation in achieving seamless performance on BMI. Currently, the size of the BMI devices is ranging from 10 to 100 microns in terms of electrodes’ diameters. Henceforth, to accommodate the single cell level precise monitoring, smaller and denser Nano-scaled nanowire electrode arrays are vital in fabrication. In this paper, we would like to showcase the fabrication of high aspect ratio of vertical silicon nanowire electrodes arrays using microelectromechanical system (MEMS) method. Nanofabrication of the nanowire electrodes involves in deep reactive ion etching, thermal oxide thinning, electron-beam lithography patterning, sputtering of metal targets and bottom anti-reflection coating (BARC) etch. Metallization on the nanowire electrode tip is a prominent process to optimize the nanowire electrical conductivity and this step remains a challenge during fabrication. Metal electrodes were lithographically defined and yet these metal contacts outline a size scale that is larger than nanometer-scale building blocks hence further limiting potential advantages. Therefore, we present an integrated contact solution that overcomes this size constraint through self-aligned Nickel silicidation process on the tip of vertical silicon nanowire electrodes. A 4 x 4 array of vertical silicon nanowires electrodes with the diameter of 290nm and height of 3µm has been successfully fabricated.

Keywords: brain-machine interfaces, microelectromechanical systems (MEMS), nanowire, nickel silicide

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Authors: Dinesh Munjurulimana, Anil Tiwari, Tingwen Li, Carlos Pereira, Sreekanth Pannala, John Waters

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With the rapid transition to electric vehicles (EVs) across the globe, car manufacturers are in need of integrated and lightweight solutions for the battery packs of these vehicles. An integral part of a battery pack is the battery tray, which constitutes a significant portion of the pack’s overall weight. Based on the functional requirements, cost targets, and packaging space available, a range of materials –from metals, composites, and plastics– are often used to develop these battery trays. This paper considers the design and development of integrated thermoplastic-intensive battery trays, using the available packaging space from a representative EV battery pack. Presented as a proposed alternative are multiple concepts to integrate several connected systems such as cooling plates and underbody impact protection parts of a multi-piece incumbent battery pack. The resulting digital prototype was evaluated for several mechanical performance measures such as mechanical shock, drop, crush resistance, modal analysis, and torsional stiffness. The performance of this alternative design is then compared with the incumbent solution. In addition, insights are gleaned into how these novel approaches can be optimized to meet or exceed the performance of incumbent designs. Preliminary manufacturing feasibility of the optimal solution using injection molding and other commonly used manufacturing methods for thermoplastics is briefly explained. Then numerical and analytical evaluations are performed to show a representative Pareto front of cost vs. volume of the production parts. The proposed solution is observed to offer weight savings of up to 40% on a component level and part elimination of up to two systems in the battery pack of a typical battery EV while offering the potential to meet the required performance measures highlighted above. These conceptual solutions are also observed to potentially offer secondary benefits such as improved thermal and electrical isolations and be able to achieve complex geometrical features, thus demonstrating the ability to use the complete packaging space available in the vehicle platform considered. The detailed study presented in this paper serves as a valuable reference for researches across the globe working on the development of EV battery packs – especially those with an interest in the potential of employing alternate solutions as part of a mixed-material system to help capture untapped opportunities to optimize performance and meet critical application requirements.

Keywords: thermoplastics, lightweighting, part integration, electric vehicle battery packs

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Authors: Anwesha Pathak

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With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

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Authors: Andrey A. Lipovskii, Alexey V. Redkov, Vyacheslav V. Rusan, Dmitry K. Tagantsev, Valentina V. Zhurikhina

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The presented research is related to the development of recently proposed technique of the formation of composite materials, like optical glass-ceramics, with predetermined structure and properties of the crystalline component. The technique is based on the control of the size and concentration of the crystalline grains using the phenomenon of glass-ceramics decrystallization (vitrification) induced by ion-exchange. This phenomenon was discovered and explained in the beginning of the 2000s, while related theoretical description was given in 2016 only. In general, the developed theory enables one to model the process and optimize the conditions of ion-exchange processing of glass-ceramics, which provide given properties of crystalline component, in particular, profile of the average size of the crystalline grains. The optimization is possible if one knows two dimensionless parameters of the theoretical model. One of them (β) is the value which is directly related to the solubility of crystalline component of the glass-ceramics in the glass matrix, and another (γ) is equal to the ratio of characteristic times of ion-exchange diffusion and crystalline grain dissolution. The presented study is dedicated to the development of experimental technique and simulation which allow determining these parameters. It is shown that these parameters can be deduced from the data on the space distributions of diffusant concentrations and average size of crystalline grains in the glass-ceramics samples subjected to ion-exchange treatment. Measurements at least at two temperatures and two processing times at each temperature are necessary. The composite material used was a silica-based glass-ceramics with crystalline grains of Li2OSiO2. Cubical samples of the glass-ceramics (6x6x6 mm3) underwent the ion exchange process in NaNO3 salt melt at 520 oC (for 16 and 48 h), 540 oC (for 8 and 24 h), 560 oC (for 4 and 12 h), and 580 oC (for 2 and 8 h). The ion exchange processing resulted in the glass-ceramics vitrification in the subsurface layers where ion-exchange diffusion took place. Slabs about 1 mm thick were cut from the central part of the samples and their big facets were polished. These slabs were used to find profiles of diffusant concentrations and average size of the crystalline grains. The concentration profiles were determined from refractive index profiles measured with Max-Zender interferometer, and profiles of the average size of the crystalline grains were determined with micro-Raman spectroscopy. Numerical simulation were based on the developed theoretical model of the glass-ceramics decrystallization induced by ion exchange. The simulation of the processes was carried out for different values of β and γ parameters under all above-mentioned ion exchange conditions. As a result, the temperature dependences of the parameters, which provided a reliable coincidence of the simulation and experimental data, were found. This ensured the adequate modeling of the process of the glass-ceramics decrystallization in 520-580 oC temperature interval. Developed approach provides a powerful tool for fine tuning of the glass-ceramics structure, namely, concentration and average size of crystalline grains.

Keywords: diffusion, glass-ceramics, ion exchange, vitrification

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Authors: Jayanta Basak, Somprakash Bandyopadhyay, Parama Bhaumik, Siuli Roy

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To solve the life and livelihood related problems of socially and economically backward rural women in India, several Women Self-Help Groups (WSHG) are formed in Indian villages. WSHGs are micro-communities (with 10-to 15 members) within a village community. WSHGs have been conceived not just to promote savings and provide credit, but also to act as a vehicle of change through the creation of women micro-entrepreneurs at the village level. However, in spite of huge investment and volume of people involved in the whole process, the success is still limited. Most of these entrepreneurial activities happen in small household workspaces where sales are limited to the inconsistent and unpredictable local markets. As a result, these entrepreneurs are perennially trapped in the vicious cycle of low risk taking ability, low investment capacity, low productivity, weak market linkages and low revenue. Market separation including customer-producer separation is one of the key problems in this domain. Researchers suggest that there are four types of market separation: (i) spatial, (ii) financial, (iii) temporal, and (iv) informational, which in turn impacts the nature of markets and marketing. In this context, a large group of intermediaries (the 'middleman') plays important role in effectively reducing the factors that separate markets by utilizing the resource of rural entrepreneurs, their products and thus, accelerate market development. The rural entrepreneurs are heavily dependent on these middlemen for marketing of their products and these middlemen exploit rural entrepreneurs by creating a huge informational separation between the rural producers and end-consumers in the market and thus hiding the profit margins. The objective of this study is to develop a transparent, online communities of purpose among rural and urban entrepreneurs using internet and web 2.0 technologies in order to decrease market separation and improve mutual awareness of available and potential products and market demands. Communities of purpose are groups of people who have an ability to influence, can share knowledge and learn from others, and be committed to achieving a common purpose. In this study, a cluster of SHG women located in a village 'Kandi' of West Bengal, India has been studied closely for six months. These women are primarily engaged in producing garments, soft toys, fabric painting on clothes, etc. These women were equipped with internet-enabled smart-phones where they can use chat applications in local language and common social networking websites like Facebook, Instagram, etc. A few handicraft experts and micro-entrepreneurs from the city (the 'seed') were included in their mobile messaging app group that enables the creation of a 'community of purpose' in order to share thoughts and ideas on product designs, market trends, and practices, and thus decrease the rural-urban market separation. After six months of regular group interaction in mobile messaging app among these rural-urban community members, it is observed that SHG women are empowered now to share their product images, design ideas, showcase, and promote their products in global marketplace using some common social networking websites through which they can also enhance and augment their community of purpose.

Keywords: communities of purpose, market separation, self-help group, social technologies

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Authors: Kim Katherine Castillo, Nelson John Datubatang, Terrence Phillip Dy, Norelie Hampac, Reichen Crismark Martinez, Nina Faith Pantinople, Jose Dante Santos II, Marchel Ann Santos, Sophia Abigail Santiago, Zyrill Xsar San Juan, Aira Mae Tagao, Crystal Kylla Viagedor

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The Work Immersion Program was implemented to help students gain abundant work-related experiences while on-site; additionally, the program aims to help students improve their competencies and interpersonal skills as they are given the option to join the workforce if they ever choose to do so after senior high school. The work immersion experience posed diverse challenges for students, spanning personal, financial, engagement, environmental, and equipment-related domains. These included the need for assistance in time management, transportation expenses, and procurement of materials. Furthermore, students faced difficulties in independent task completion and encountered suboptimal work environments. Addressing these multifaceted obstacles is crucial to optimize the educational outcomes of work immersion programs. In addition to the challenges, several other issues have been identified, including the absence of standardized work immersion programs across schools and industries, the challenges in securing appropriate work immersion placements, the necessity for enhanced monitoring and evaluation of program effectiveness, and the limited availability of field programs aligned with students' chosen courses. Furthermore, there is a lack of comprehensive information regarding the attitudes of Senior High School students toward work immersion programs within their respective schools. This study aims to investigate the attitudes of senior high school students at Nazareth School of National University towards work immersion programs, with a focus on identifying factors that influence their perception and participation, including collegiality and expectations. By exploring the students' attitudes, the research endeavors to enhance the school's work immersion programs and contribute to the overall educational experience of the students. This study addresses challenges related to work immersion programs, focusing on six subtopics: Work Immersion, Work Immersion in the Philippines, Students' Attitudes, Factors Affecting Students' Attitudes, Effectiveness of Work Immersion for Senior High School Students, and Students' Perception and Willingness to Participate. Using a descriptive research design, the study examines the attitudes of senior high school students at Nazareth School of National University in Manila. Data was collected from 100 students, representing different academic strands, through a 35-item researcher-made survey. Descriptive statistics, including measures of central tendency and variability, will be used to analyze the data using JASP, providing valuable insights into the students' attitudes toward work immersion.

Keywords: attitudes, challenges, educational outcomes, work immersion programs

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Authors: Nitika Sharma, Yogesh Jain

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Introduction: An efficient Information System helps in improving the service delivery as well provides the foundation for policy and regulation of other building blocks of Health System. Health care organizations require an integrated working of its various sub-systems. An efficient EMR software boosts the teamwork amongst the various sub-systems thereby resulting in improved service delivery. Although there has been a huge impetus to EMR under the Digital India initiative, it has still not been mandated in India. It is generally implemented in huge funded public or private healthcare organizations only. Objective: The study was conducted to understand the factors that lead to the successful adoption of an affordable EMR in the low level healthcare organization. It intended to understand the design of the EMR and address the solutions to the challenges faced in adoption of the EMR. Methodology: The study was conducted in a non-profit registered Healthcare organization that has been providing healthcare facilities to more than 2500 villages including certain areas that are difficult to access. The data was collected with help of field notes, in-depth interviews and participant observation. A total of 16 participants using the EMR from different departments were enrolled via purposive sampling technique. The participants included in the study were working in the organization before the implementation of the EMR system. The study was conducted in one month period from 25 June-20 July 2018. The Ethical approval was taken from the institute along with prior approval of the participants. Data analysis: A word document of more than 4000 words was obtained after transcribing and translating the answers of respondents. It was further analyzed by focused coding, a line by line review of the transcripts, underlining words, phrases or sentences that might suggest themes to do thematic narrative analysis. Results: Based on the answers the results were thematically grouped under four headings: 1. governance of organization, 2. architecture and design of the software, 3. features of the software, 4. challenges faced in adoption and the solutions to address them. It was inferred that the successful implementation was attributed to the easy and comprehensive design of the system which has facilitated not only easy data storage and retrieval but contributes in constructing a decision support system for the staff. Portability has lead to increased acceptance by physicians. The proper division of labor, increased efficiency of staff, incorporation of auto-correction features and facilitation of task shifting has lead to increased acceptance amongst the users of various departments. Geographical inhibitions, low computer literacy and high patient load were the major challenges faced during its implementation. Despite of dual efforts made both by the architects and administrators to combat these challenges, there are still certain ongoing challenges faced by organization. Conclusion: Whenever any new technology is adopted there are certain innovators, early adopters, late adopters and laggards. The same pattern was followed in adoption of this software. He challenges were overcome with joint efforts of organization administrators and users as well. Thereby this case study provides a framework of implementing similar systems in public sector of countries that are struggling for digitizing the healthcare in presence of crunch of human and financial resources.

Keywords: EMR, healthcare technology, e-health, EHR

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Authors: Shiau-Fang Chao, Yu-Chih Chen

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Owing to physical limitations and restrained lifestyle, older long-term care (LTC) residents are more likely to be affected by their environment than their community-dwelling counterparts. They also participate fewer activities and experience worse mental health than healthy older adults. This study adopts the ICF model to determine the extent to which the clustered patterns of LTC environment and activity participation are associated with older residents’ mental health. Method: Data were collected from a stratified equal probability sample of 634 older residents in 155 LTC institutions in Taiwan. Latent profile analysis (LPA) and latent class analysis (LCA) were conducted to explore the profiles for environment and activity participation. Multilevel modeling was performed to elucidate the relationships among environment profiles, activity profiles, and mental health. Results: LPA identified three mutually exclusive environment profiles (Low-, Moderate-, and High-Support Environment) based on the physical, social, and attitudinal environmental domains, consolidated from 12 environmental measures. LCA constructed two distinct activity profiles (Low- and High-Activity Participation) across seven activity domains (outdoor, volunteer-led leisure, spiritual, household chores, interpersonal exchange, social, and sedentary activity) that were factored from 20 activities. Compared to the Low-Support Environment class, older adults in the Moderate- and High-Support Environment classes had better mental health. Older residents in the Moderate- and High-Support Environment classes were more likely to be in the “High Activity” class, which in turn, exhibited better mental health. Conclusion: This study advances the current knowledge through rigorous methods and study design. The study findings lead to several conclusions. First, this study supports the use of ICF framework to institutionalized older individuals with functional limitations and demonstrates that both measures of environment and activity participation can be refined from multiple indicators. Second, environmental measures that encompass the physical, social, and attitudinal domains would provide a more comprehensive assessment on the place where an older individual embeds. Third, simply counting activities in which an older individual participates or considering a certain type of activity may not capture his or her way of life. Practitioners should not only focus on group or leisure activities within the institutions; rather, more efforts should be made to consider residents’ preferences for everyday life and support their remaining ability by encouraging continuous participation in activities they still willing and capable to perform. Fourth, environment and activity participation are modifiable factors which have greater potential to strengthen older LTC residents’ mental health, and activity participation should be considered in the link between environment and mental health. A combination of enhanced physical, social, and attitudinal environments, and continual engagement in various activities may optimize older LTC residents’ mental health.

Keywords: activity, environment, mental health, older LTC residents

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

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In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: availability, design for maintenance (DFM), dynamic maintenance, life cycle cost (LCC), maintenance free operating period (MFOP), simultaneous optimization

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Authors: C. S. Chen, F. Y. Hui, B. S. Farhana, J. De Leon

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Introduction: Stroke can lead to long-term disability, affecting one’s quality of life. Providing stroke education to patient and family members is essential to optimize stroke recovery and prevent recurrent stroke. Currently, nurses conduct stroke education by handing out pamphlets and explaining their contents to patients. However, this is not always effective as nurses have varying levels of knowledge and depth of content discussed with the patient may not be consistent. With the advancement of information technology, health education is increasingly being disseminated via electronic software and studies have shown this to have benefitted patients. Hence, a multi-disciplinary team consisting of doctors, nurses and allied health professionals was formed to create the stroke journey map software to deliver consistent and concise stroke education. Research Objectives: To evaluate the effectiveness of using a stroke journey map software in improving patients’ perceived knowledge in the acute stroke unit during hospitalization. Methods: Patients admitted to the acute stroke unit were given stroke journey map software during patient education. The software consists of 31 interactive slides that are brightly coloured and 4 videos, based on input provided by the multi-disciplinary team. Participants were then assessed with pre-and-post survey questionnaires before and after viewing the software. The questionnaire consists of 10 questions with a 5-point Likert scale which sums up to a total score of 50. The inclusion criteria are patients diagnosed with ischemic stroke and are cognitively alert and oriented. This study was conducted between May 2017 to October 2017. Participation was voluntary. Results: A total of 33 participants participated in the study. The results demonstrated that the use of a stroke journey map as a stroke education medium was effective in improving patients’ perceived knowledge. A comparison of pre- and post-implementation data of stroke journey map revealed an overall mean increase in patients’ perceived knowledge from 24.06 to 40.06. The data is further broken down to evaluate patients’ perceived knowledge in 3 domains: (1) Understanding of disease process; (2) Management and treatment plans; (3) Post-discharge care. Each domain saw an increase in mean score from 10.7 to 16.2, 6.9 to 11.9 and 6.6 to 11.7 respectively. Project Impact: The implementation of stroke journey map has a positive impact in terms of (1) Increasing patient’s perceived knowledge which could contribute to greater empowerment of health; (2) Reducing need for stroke education material printouts making it environmentally friendly; (3) Decreasing time nurses spent on giving education resulting in more time to attend to patients’ needs. Conclusion: This study has demonstrated the benefit of using stroke journey map as a platform for stroke education. Overall, it has increased patients’ perceived knowledge in understanding their disease process, the management and treatment plans as well as the discharge process.

Keywords: acute stroke, education, ischemic stroke, knowledge, stroke

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Authors: Kavita Khoiwal, Vatsla Dadhwal, K. Aparna Sharma, Dipika Deka, Plabani Sarkar

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Introduction: About 2.4 million (1.93 - 3.04 million) people are living with HIV/AIDS in India. Of all HIV infections, 39% (9,30,000) are among women. 5.4% of infections are from mother to child transmission (MTCT), 25,000 infected children are born every year. Besides the risk of mother to child transmission of HIV, these women are at risk of the higher adverse pregnancy outcome. The objectives of the study were to compare the obstetric and neonatal outcome in women who are HIV positive with low-risk HIV negative women and effect of antiretroviral drugs on preterm birth and IUGR. Materials and Methods: This is a retrospective case record analysis of 212 HIV-positive women delivering between 2002 to 2015, in a tertiary health care centre which was compared with 238 HIV-negative controls. Women who underwent medical termination of pregnancy and abortion were excluded from the study. Obstetric outcome analyzed were pregnancy induced hypertension, HIV positive intrauterine growth restriction, preterm birth, anemia, gestational diabetes and intrahepatic cholestasis of pregnancy. Neonatal outcome analysed were birth weight, apgar score, NICU admission and perinatal transmission.HIV-positiveOut of 212 women, 204 received antiretroviral therapy (ART) to prevent MTCT, 27 women received single dose nevirapine (sdNVP) or sdNVP tailed with 7 days of zidovudine and lamivudine (ZDV + 3TC), 15 received ZDV, 82 women received duovir and 80 women received triple drug therapy depending upon the time period of presentation. Results: Mean age of 212 HIV positive women was 25.72+3.6 years, 101 women (47.6 %) were primigravida. HIV positive status was diagnosed during pregnancy in 200 women while 12 women were diagnosed prior to conception. Among 212 HIV positive women, 20 (9.4 %) women had preterm delivery (< 37 weeks), 194 women (91.5 %) delivered by cesarean section and 18 women (8.5 %) delivered vaginally. 178 neonates (83.9 %) received exclusive top feeding and 34 neonates (16.03 %) received exclusive breast feeding. When compared to low risk HIV negative women (n=238), HIV positive women were more likely to deliver preterm (OR 1.27), have anemia (OR 1.39) and intrauterine growth restriction (OR 2.07). Incidence of pregnancy induced hypertension, diabetes mellitus and ICP was not increased. Mean birth weight was significantly lower in HIV positive women (2593.60+499 gm) when compared to HIV negative women (2919+459 gm). Complete follow up is available for 148 neonates till date, rest are under evaluation. Out of these 7 neonates found to have HIV positive status. Risk of preterm birth (P value = 0.039) and IUGR (P value = 0.739) was higher in HIV positive women who did not receive any ART during pregnancy than women who received ART. Conclusion: HIV positive pregnant women are at increased risk of adverse pregnancy outcome. Multidisciplinary team approach and use of highly active antiretroviral therapy can optimize the maternal and perinatal outcome.

Keywords: antiretroviral therapy, HIV infection, IUGR, preterm birth

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Authors: Bander Alzahrani, Mohammed Alreshoodi

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Information-centric networking (ICN) using architectures such as the Publish-Subscribe Internet Technology (PURSUIT) has been proposed as a new networking model that aims at replacing the current used end-centric networking model of the Internet. This emerged model focuses on what is being exchanged rather than which network entities are exchanging information, which gives the control plane functions such as routing and host location the ability to be specified according to the content items. The forwarding plane of the PURSUIT ICN architecture uses a simple and light mechanism based on Bloom filter technologies to forward the packets. Although this forwarding scheme solve many problems of the today’s Internet such as the growth of the routing table and the scalability issues, it is vulnerable to brute force attacks which are starting point to distributed- denial-of-service (DDoS) attacks. In this work, we design and analyze a novel source-routing and information delivery technique that keeps the simplicity of using Bloom filter-based forwarding while being able to deter different attacks such as denial of service attacks at the ingress of the network. To achieve this, special forwarding nodes called Edge-FW are directly attached to end user nodes and used to perform a security test for malicious injected random packets at the ingress of the path to prevent any possible attack brute force attacks at early stage. In this technique, a core entity of the PURSUIT ICN architecture called topology manager, that is responsible for finding shortest path and creating a forwarding identifiers (FId), uses a cryptographically secure hash function to create a 64-bit hash, h, over the formed FId for authentication purpose to be included in the packet. Our proposal restricts the attacker from injecting packets carrying random FIds with a high amount of filling factor ρ, by optimizing and reducing the maximum allowed filling factor ρm in the network. We optimize the FId to the minimum possible filling factor where ρ ≤ ρm, while it supports longer delivery trees, so the network scalability is not affected by the chosen ρm. With this scheme, the filling factor of any legitimate FId never exceeds the ρm while the filling factor of illegitimate FIds cannot exceed the chosen small value of ρm. Therefore, injecting a packet containing an FId with a large value of filling factor, to achieve higher attack probability, is not possible anymore. The preliminary analysis of this proposal indicates that with the designed scheme, the forwarding function can detect and prevent malicious activities such DDoS attacks at early stage and with very high probability.

Keywords: forwarding identifier, filling factor, information centric network, topology manager

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Authors: Maria Fontenele, Claude-Gilles Dussap, Vincent Dumouilla, Baptiste Boit

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Roquette Frères is a producer of plant-based ingredients that employs many processes to extract relevant molecules and often transforms them through chemical and physical processes to create desired ingredients with specific functionalities. In this context, Roquette encounters numerous multi-component complex systems in their processes, including fibers, proteins, and carbohydrates, in an aqueous environment. To develop, control, and optimize both new and old processes, Roquette aims to develop new in silico tools. Currently, Roquette uses process modelling tools which include specific thermodynamic models and is willing to develop computational methodologies such as molecular dynamics simulations to gain insights into the complex interactions in such complex media, and especially hydrogen bonding interactions. The issue at hand concerns aqueous mixtures of polyols with high dry matter content. The polyols mannitol and sorbitol molecules are diastereoisomers that have nearly identical chemical structures but very different physicochemical properties: for example, the solubility of sorbitol in water is 2.5 kg/kg of water, while mannitol has a solubility of 0.25 kg/kg of water at 25°C. Therefore, predicting liquid-solid equilibrium properties in this case requires sophisticated solution models that cannot be based solely on chemical group contributions, knowing that for mannitol and sorbitol, the chemical constitutive groups are the same. Recognizing the significance of solvation phenomena in polyols, the GePEB (Chemical Engineering, Applied Thermodynamics, and Biosystems) team at Institut Pascal has developed the COSMO-UCA model, which has the structural advantage of using quantum mechanics tools to predict formation and phase equilibrium properties. In this work, we use molecular dynamics simulations to elucidate the behavior of polyols in aqueous solution. Specifically, we employ simulations to compute essential metrics such as radial distribution functions and hydrogen bond autocorrelation functions. Our findings illuminate a fundamental contrast: sorbitol and mannitol exhibit disparate hydrogen bond lifetimes within aqueous environments. This observation serves as a cornerstone in elucidating the divergent physicochemical properties inherent to each compound, shedding light on the nuanced interplay between their molecular structures and water interactions. We also present a methodology to predict the physicochemical properties of complex solutions, taking as sole input the three-dimensional structure of the molecules in the medium. Finally, by developing knowledge models, we represent some physicochemical properties of aqueous solutions of sorbitol and mannitol.

Keywords: COSMO models, hydrogen bond, molecular dynamics, thermodynamics

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Authors: Zhuoran Li, Guan Qin

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A robust and efficient compositional equilibrium characterization model for hydrate-containing systems is required, especially for time-critical simulations such as subsea pipeline flow assurance analysis, compositional simulation in hydrate reservoirs etc. A multiphase flash calculation framework, which combines Gibbs energy minimization function and cubic plus association (CPA) EoS, is developed to describe the highly non-ideal phase behavior of hydrate-containing systems. A non-iterative eigenvalue problem-solving approach for the trust-region sub-problem is selected to guarantee efficiency. The developed flash model is based on the state-of-the-art objective function proposed by Michelsen to minimize the Gibbs energy of the multiphase system. It is conceivable that a hydrate-containing system always contains polar components (such as water and hydrate inhibitors), introducing hydrogen bonds to influence phase behavior. Thus, the cubic plus associating (CPA) EoS is utilized to compute the thermodynamic parameters. The solid solution theory proposed by van der Waals and Platteeuw is applied to represent hydrate phase parameters. The trust-region method combined with the trust-region sub-problem non-iterative eigenvalue problem-solving approach is utilized to ensure fast convergence. The developed multiphase flash model's accuracy performance is validated by three available models (one published and two commercial models). Hundreds of published hydrate-containing system equilibrium experimental data are collected to act as the standard group for the accuracy test. The accuracy comparing results show that our model has superior performances over two models and comparable calculation accuracy to CSMGem. Efficiency performance test also has been carried out. Because the trust-region method can determine the optimization step's direction and size simultaneously, fast solution progress can be obtained. The comparison results show that less iteration number is needed to optimize the objective function by utilizing trust-region methods than applying line search methods. The non-iterative eigenvalue problem approach also performs faster computation speed than the conventional iterative solving algorithm for the trust-region sub-problem, further improving the calculation efficiency. A new thermodynamic framework of the multiphase flash model for the hydrate-containing system has been constructed in this work. Sensitive analysis and numerical experiments have been carried out to prove the accuracy and efficiency of this model. Furthermore, based on the current thermodynamic model in the oil and gas industry, implementing this model is simple.

Keywords: equation of state, hydrates, multiphase equilibrium, trust-region method

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Authors: Marcos Silva Tavares, Jamile Raquel Regazzo, Edson José de Souza Sardinha, Murilo Mesquita Baesso

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Common beans are a widely cultivated and consumed legume globally, serving as a staple food for humans, especially in developing countries, due to their nutritional characteristics. Nitrogen (N) is the most limiting nutrient for productivity, and foliar analysis is crucial to ensure balanced nitrogen fertilization. Excessive N applications can cause, either isolated or cumulatively, soil and water contamination, plant toxicity, and increase their susceptibility to diseases and pests. However, the quantification of N using conventional methods is time-consuming and costly, demanding new technologies to optimize the adequate supply of N to plants. Thus, it becomes necessary to establish constant monitoring of the foliar content of this macronutrient in plants, mainly at the V4 stage, aiming at precision management of nitrogen fertilization. In this work, the objective was to evaluate the performance of a deep learning model, Resnet-50, in the classification of foliar nitrogen in common beans using RGB images. The BRS Estilo cultivar was sown in a greenhouse in a completely randomized design with four nitrogen doses (T1 = 0 kg N ha-1, T2 = 25 kg N ha-1, T3 = 75 kg N ha-1, and T4 = 100 kg N ha-1) and 12 replications. Pots with 5L capacity were used with a substrate composed of 43% soil (Neossolo Quartzarênico), 28.5% crushed sugarcane bagasse, and 28.5% cured bovine manure. The water supply of the plants was done with 5mm of water per day. The application of urea (45% N) and the acquisition of images occurred 14 and 32 days after sowing, respectively. A code developed in Matlab© R2022b was used to cut the original images into smaller blocks, originating an image bank composed of 4 folders representing the four classes and labeled as T1, T2, T3, and T4, each containing 500 images of 224x224 pixels obtained from plants cultivated under different N doses. The Matlab© R2022b software was used for the implementation and performance analysis of the model. The evaluation of the efficiency was done by a set of metrics, including accuracy (AC), F1-score (F1), specificity (SP), area under the curve (AUC), and precision (P). The ResNet-50 showed high performance in the classification of foliar N levels in common beans, with AC values of 85.6%. The F1 for classes T1, T2, T3, and T4 was 76, 72, 74, and 77%, respectively. This study revealed that the use of RGB images combined with deep learning can be a promising alternative to slow laboratory analyses, capable of optimizing the estimation of foliar N. This can allow rapid intervention by the producer to achieve higher productivity and less fertilizer waste. Future approaches are encouraged to develop mobile devices capable of handling images using deep learning for the classification of the nutritional status of plants in situ.

Keywords: convolutional neural network, residual network 50, nutritional status, artificial intelligence

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Authors: Shamsa Al Sharji, Athar Al Jabri, Haitham Al Dughaishi, Mirfat Al Barwani, Raja Al Rawahi, Raiya Al Rajhi, Shurooq Al Ruqaishi, Thamreen Al Zadjali, Iman Al Humaidi

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Background: External Ventricular Drains (EVDs) are critical in managing traumatic brain injuries and hydrocephalus by controlling intracranial pressure, but they carry a high risk of infection. Infection rates vary globally, ranging from 5% to 45%, leading to increased morbidity, prolonged hospital stays, and higher healthcare costs. Nursing protocols play a pivotal role in reducing these infection rates. This study investigates the impact of a structured nursing protocol on EVD-associated infections in adult neurosurgery patients at the Directorate General of Khoula Hospital, Oman, from January to September 2024. Methods: A cluster-randomized trial was conducted across neurosurgery wards and the ICU. The intervention group followed a comprehensive nursing protocol, including strict sterile insertion, standardized dressing changes, infection control training, and regular clinical audits. The control group received standard care. The primary outcome was the incidence of EVD-associated infections, with secondary outcomes including protocol compliance, infection severity, recovery times, length of stay, and 30-day mortality. Statistical analysis was conducted using Chi-square tests, paired t-tests, and logistic regression to assess the differences between groups. Results: The study involved 75 patients, with an overall infection rate of 13.3%. The intervention group showed a reduced infection rate of 8.9% compared to 20% in the control group. Compliance rates for key nursing actions were high, with 89.7% for hand hygiene and 86.2% for wound dressing. The relative risk of infection was 0.44 in the intervention group, reflecting a 55.6% reduction. Logistic regression identified obesity as a significant predictor of EVD infections. Although mortality rates were slightly higher in the intervention group, the number needed to treat (NNT) of 9 suggests that the nursing protocol may improve survival outcomes. Conclusion: This study demonstrates that structured nursing protocols can reduce EVD-related infections and improve patient outcomes in neurosurgery. While the findings are promising, further research with larger sample sizes is needed to confirm these results and optimize infection control strategies in neurosurgical care.

Keywords: EVD, CSF, nursing protocol, EVD infection

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Authors: Elkington S. Mnguni

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Water and sanitation services in South Africa are characterized by both achievements and challenges. After the end of apartheid in 1994 the newly elected government faced the challenge of eradicating backlogs with respect to access to basic services, including water and sanitation. Capital investment made in the development of new water and sanitation infrastructure to provide basic services to previously disadvantaged communities has grown, to a certain extent, at the expense of investment in the operation and maintenance of new and existing infrastructure. Challenges resulting from aging infrastructure and poor plant performance highlight the need for investing in the maintenance, rehabilitation, and replacement of existing infrastructure to optimize the return on investment. Advanced water infrastructure asset management (IAM) is key to achieving adequate levels of service, particularly with regard to reliable and high quality drinking water supply, prevention of urban flooding, efficient use of natural resources and prevention of pollution and associated risks. Against this backdrop, this paper presents an appraisal of water and sanitation IAM systems in South Africa’s three utilities, being metropolitan cities in the Gauteng Province. About a quarter of the national population lives in the three rapidly urbanizing cities of Johannesburg, Ekurhuleni and Tshwane, located in a semi-arid region. A literature review has been done and field visits to some of the utility facilities are being conducted. Semi-structured interviews will be conducted with the three utilities. The following critical factors are being analysed in terms of compliance with the national Water Services IAM Strategy (2011) and other applicable legislation: asset registers; capacity of assets; current and predicted demand; funding availability / budget allocations; plans: operation & maintenance, renewal & replacement, and risk management; no-drop status (non-revenue water levels); blue drop status (water quality); green drop status (effluent quality); and skills availability. Some of the key challenges identified in the literature review include: funding constraints, Skills shortage, and wastewater treatment plants operating beyond their design capacities. These challenges will be verified during field visits and research interviews. Gaps between literature and practice will be identified and relevant recommendations made if necessary. The objective of this study is to contribute to the resolution of the challenges brought about by the backlogs in the operation and maintenance of water and sanitation assets in the country in general, and in the three cities in particular, thus improving the sustainability thereof.

Keywords: asset management, backlogs, levels of service, sustainability, water and sanitation infrastructure

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Authors: Sunidhi Sood, Drashti Narendrakumar Shah, Aakarsh Sharma, Nirali Harsh Panchal, Maria Karizhenskaia

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Cancer is a global health concern, causing a significant number of deaths, with chemotherapy being a standard treatment method. However, chemotherapy often induces side effects that profoundly impact the physical and emotional well-being of patients, lowering their overall quality of life (QoL). This research aims to investigate the potential of music and art therapy as holistic adjunctive therapy for cancer patients undergoing chemotherapy, offering non-pharmacological support. This is achieved through a comprehensive review of existing literature with a focus on the following themes, including stress and anxiety alleviation, emotional expression and coping skill development, transformative changes, and pain management with mood upliftment. A systematic search was conducted using Medline, Google Scholar, and St. Lawrence College Library, considering original, peer-reviewed research papers published from 2014 to 2023. The review solely incorporated studies focusing on the impact of music and art therapy on the health and overall well-being of cancer patients undergoing chemotherapy in North America. The findings from 16 studies involving pediatric oncology patients, females affected by breast cancer, and general oncology patients show that music and art therapies significantly reduce anxiety (standardized mean difference: -1.10) and improve perceived stress (median change: -4.0) and overall quality of life in cancer patients undergoing chemotherapy. Furthermore, music therapy has demonstrated the potential to decrease anxiety, depression, and pain during infusion treatments (average changes in resilience scale: 3.4 and 4.83 for instrumental and vocal music therapy, respectively). This data calls for consideration of the integration of music and art therapy into supportive care programs for cancer patients undergoing chemotherapy. Moreover, it provides guidance to healthcare professionals and policymakers, facilitating the development of patient-centered strategies for cancer care in Canada. Further research is needed in collaboration with qualified therapists to examine its applicability and explore and evaluate patients' perceptions and expectations in order to optimize the therapeutic benefits and overall patient experience. In conclusion, integrating music and art therapy in cancer care promises to substantially enhance the well-being and psychosocial state of patients undergoing chemotherapy. However, due to the small population size considered in existing studies, further research is needed to bridge the knowledge gap and ensure a comprehensive, patient-centered approach, ultimately enhancing the quality of life (QoL) for individuals facing the challenges of cancer treatment.

Keywords: anxiety, cancer, chemotherapy, depression, music and art therapy, pain management, quality of life

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Authors: Tam Viet Hoang

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With a plethora of new mobility services and payment systems found in our cities and across modern public transportation systems, several cities globally have turned to common ticketing systems to help navigate this complexity. Helping to create time and space-differentiated fare structures and tariff schemes, common ticketing systems can optimize transport utilization rates, achieve cost efficiencies, and provide key incentives to specific target groups. However, not all cities and transportation systems have enjoyed a smooth journey towards the adoption, roll-out, and servicing of common ticketing systems, with both the experiences of success and failure being attributed to a wide variety of critical factors. Using case study research as a methodology and cities as the main unit of analysis, this research will seek to address the fundamental question of “what are the critical factors for the success and failure of common ticketing systems?” Using rail/train systems as the entry point for this study will start by providing a background to the evolution of transport ticketing and justify the improvements in operational efficiency that can be achieved through common ticketing systems. Examining the socio-economic benefits of common ticketing, the research will also help to articulate the value derived for different key identified stakeholder groups. By reviewing case studies of the implementation of common ticketing systems in different cities, the research will explore lessons learned from cities with the aim to elicit factors to ensure seamless connectivity integrated e-ticketing platforms. In an increasingly digital age and where cities are now coming online, this paper seeks to unpack these critical factors, undertaking case study research drawing from literature and lived experiences. Offering us a better understanding of the enabling environment and ideal mixture of ingredients to facilitate the successful roll-out of a common ticketing system, interviews will be conducted with transport operators from several selected cities to better appreciate the challenges and strategies employed to overcome those challenges in relation to common ticketing systems. Meanwhile, as we begin to see the introduction of new mobile applications and user interfaces to facilitate ticketing and payment as part of the transport journey, we take stock of numerous policy challenges ahead and implications on city-wide and system-wide urban planning. It is hoped that this study will help to identify the critical factors for the success and failure of common ticketing systems for cities set to embark on their implementation while serving to fine-tune processes in those cities where common ticketing systems are already in place. Outcomes from the study will help to facilitate an improved understanding of common pitfalls and essential milestones towards the roll-out of a common ticketing system for railway systems, especially for emerging countries where mass rapid transit transport systems are being considered or in the process of construction.

Keywords: common ticketing, public transport, urban strategies, Bangkok, Fukuoka, Sydney

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Authors: Anirudh Lahiri

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Neuromorphic computing, inspired by the intricate operations of biological neural networks, offers a revolutionary approach to overcoming the limitations of traditional computing architectures. This research proposes the integration of spintronics with neuromorphic systems, aiming to enhance computational performance, scalability, and energy efficiency. Traditional computing systems, based on the Von Neumann architecture, struggle with scalability and efficiency due to the segregation of memory and processing functions. In contrast, the human brain exemplifies high efficiency and adaptability, processing vast amounts of information with minimal energy consumption. This project explores the use of spintronics, which utilizes the electron's spin rather than its charge, to create more energy-efficient computing systems. Spintronic devices, such as magnetic tunnel junctions (MTJs) manipulated through spin-transfer torque (STT) and spin-orbit torque (SOT), offer a promising pathway to reducing power consumption and enhancing the speed of data processing. The integration of these devices within a neuromorphic framework aims to replicate the efficiency and adaptability of biological systems. The research is structured into three phases: an exhaustive literature review to build a theoretical foundation, laboratory experiments to test and optimize the theoretical models, and iterative refinements based on experimental results to finalize the system. The initial phase focuses on understanding the current state of neuromorphic and spintronic technologies. The second phase involves practical experimentation with spintronic devices and the development of neuromorphic systems that mimic synaptic plasticity and other biological processes. The final phase focuses on refining the systems based on feedback from the testing phase and preparing the findings for publication. The expected contributions of this research are twofold. Firstly, it aims to significantly reduce the energy consumption of computational systems while maintaining or increasing processing speed, addressing a critical need in the field of computing. Secondly, it seeks to enhance the learning capabilities of neuromorphic systems, allowing them to adapt more dynamically to changing environmental inputs, thus better mimicking the human brain's functionality. The integration of spintronics with neuromorphic computing could revolutionize how computational systems are designed, making them more efficient, faster, and more adaptable. This research aligns with the ongoing pursuit of energy-efficient and scalable computing solutions, marking a significant step forward in the field of computational technology.

Keywords: material science, biological engineering, mechanical engineering, neuromorphic computing, spintronics, energy efficiency, computational scalability, synaptic plasticity.

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Authors: Vinu Viswanath, Lawrence Dsouza, Ugo Ravon

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Syngas typically and intermediary gas product has a wide range of application of producing various chemical products, such as mixed alcohols, hydrogen, ammonia, Fischer-Tropsch products methanol, ethanol, aldehydes, alcohols, etc. There are several technologies available for the syngas production. An alternative to the conventional processes an attractive route of utilizing carbon dioxide and methane in equimolar ratio to generate syngas of ratio close to one has been developed which is also termed as Dry Reforming of Methane technology. It also gives the privilege to utilize the greenhouse gases like CO2 and CH4. The dry reforming process is highly endothermic, and indeed, ΔG becomes negative if the temperature is higher than 900K and practically, the reaction occurs at 1000-1100K. At this temperature, the sintering of the metal particle is happening that deactivate the catalyst. However, by using this strategy, the methane is just partially oxidized, and some cokes deposition occurs that causing the catalyst deactivation. The current research work was focused to mitigate the main challenges of dry reforming process such coke deposition, and metal sintering at high temperature.To achieve these objectives, we employed three different strategies of catalyst development. 1) Use of bulk catalysts such as olivine and pyrochlore type materials. 2) Use of metal doped support materials, like spinel and clay type material. 3) Use of core-shell model catalyst. In this approach, a thin layer (shell) of redox metal oxide is deposited over the MgAl2O4 /Al2O3 based support material (core). For the core-shell approach, an active metal is been deposited on the surface of the shell. The shell structure formed is a doped metal oxide that can undergo reduction and oxidation reactions (redox), and the core is an alkaline earth aluminate having a high affinity towards carbon dioxide. In the case of metal-doped support catalyst, the enhanced redox properties of doped CeO2 oxide and CO2 affinity property of alkaline earth aluminates collectively helps to overcome coke formation. For all of the mentioned three strategies, a systematic screening of the metals is carried out to optimize the efficiency of the catalyst. To evaluate the performance of them, the activity and stability test were carried out under reaction conditions of temperature ranging from 650 to 850 ̊C and an operating pressure ranging from 1 to 20 bar. The result generated infers that the core-shell model catalyst showed high activity and better stable DR catalysts under atmospheric as well as high-pressure conditions. In this presentation, we will show the results related to the strategy.

Keywords: carbon dioxide, dry reforming, supports, core shell catalyst

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Authors: C. Hall, J. Ramos, V. Ramasamy

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Hydrocarbon-based fuel vehicles are a major contributor to air pollution due to harmful emissions produced, leading to a demand for cleaner fuel types. A leader in this pursuit is hydrogen, with its application in vehicles producing zero harmful emissions and the only by-product being water. To compete with the performance of conventional vehicles, hydrogen gas must be stored on-board of vehicles in cylinders at high pressures (35–70 MPa) and have a short refueling duration (approximately 3 mins). However, the fast-filling of hydrogen cylinders causes a significant rise in temperature due to the combination of the negative Joule-Thompson effect and the compression of the gas. This can lead to structural failure and therefore, a maximum allowable internal temperature of 85°C has been imposed by the International Standards Organization. The technological solution to tackle the issue of rapid temperature rise during the refueling process is to decrease the temperature of the gas entering the cylinder. Pre-cooling of the gas uses a heat exchanger and requires energy for its operation. Thus, it is imperative to determine the least amount of energy input that is required to lower the gas temperature for cost savings. A validated universal thermodynamic model is used to identify an energy-efficient pre-cooling strategy. The model requires negligible computational time and is applied to previously validated experimental cases to optimize pre-cooling requirements. The pre-cooling characteristics include the location within the refueling timeline and its duration. A constant pressure-ramp rate is imposed to eliminate the effects of rapid changes in mass flow rate. A pre-cooled gas temperature of -40°C is applied, which is the lowest allowable temperature. The heat exchanger is assumed to be ideal with no energy losses. The refueling of the cylinders is modeled with the pre-cooling split in ten percent time intervals. Furthermore, varying burst durations are applied in both the early and late stages of the refueling procedure. The model shows that pre-cooling in the later stages of the refuelling process is more energy-efficient than early pre-cooling. In addition, the efficiency of pre-cooling towards the end of the refueling process is independent of the pressure profile at the inlet. This leads to the hypothesis that pre-cooled gas should be applied as late as possible in the refueling timeline and at very low temperatures. The model had shown a 31% reduction in energy demand whilst achieving the same final gas temperature for a refueling scenario when pre-cooling was applied towards the end of the process. The identification of the most energy-efficient refueling approaches whilst adhering to the safety guidelines is imperative to reducing the operating cost of hydrogen refueling stations. Heat exchangers are energy-intensive and thus, reducing the energy requirement would lead to cost reduction. This investigation shows that pre-cooling should be applied as late as possible and for short durations.

Keywords: cylinder, hydrogen, pre-cooling, refueling, thermodynamic model

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Authors: Ravi Raj, Louis Chiu, Deepak Marla, Aijun Huang

Abstract:

Hybridization of the directed laser deposition (DLD) process using an in-situ micro-roller to impart a vertical compressive load on the deposited bead at elevated temperatures can relieve tensile residual stresses incurred in the process. To investigate this stress relief mechanism and its relationship with the in-situ rolling parameters, a fully coupled dynamic thermo-mechanical model is presented in this study. A single bead deposition of Ti-6Al-4V alloy with an in-situ roller made of mild steel moving at a constant speed with a fixed nominal bead reduction is simulated using the explicit solver of the finite element software, Abaqus. The thermal model includes laser heating during the deposition process and the heat transfer between the roller and the deposited bead. The laser heating is modeled using a moving heat source with a Gaussian distribution, applied along the pre-formed bead’s surface using the VDFLUX Fortran subroutine. The bead’s cross-section is assumed to be semi-elliptical. The interfacial heat transfer between the roller and the bead is considered in the model. Besides, the roller is cooled internally using axial water flow, considered in the model using convective heat transfer. The mechanical model for the bead and substrate includes the effects of rolling along with the deposition process, and their elastoplastic material behavior is captured using the J2 plasticity theory. The model accounts for strain, strain rate, and temperature effects on the yield stress based on Johnson-Cook’s theory. Various aspects of this material behavior are captured in the FE software using the subroutines -VUMAT for elastoplastic behavior, VUHARD for yield stress, and VUEXPAN for thermal strain. The roller is assumed to be elastic and does not undergo any plastic deformation. Also, contact friction at the roller-bead interface is considered in the model. Based on the thermal results of the bead, the distance between the roller and the deposition nozzle (roller o set) can be determined to ensure rolling occurs around the beta-transus temperature for the Ti-6Al-4V alloy. It is identified that roller offset and the nominal bead height reduction are crucial parameters that influence the residual stresses in the hybrid process. The results obtained from a simulation at roller offset of 20 mm and nominal bead height reduction of 7% reveal that the tensile residual stresses decrease to about 52% due to in-situ rolling throughout the deposited bead. This model can be used to optimize the rolling parameters to minimize the residual stresses in the hybrid DLD process with in-situ micro-rolling.

Keywords: directed laser deposition, finite element analysis, hybrid in-situ rolling, thermo-mechanical model

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Authors: Danilo F. Rodrigues, Hérida Regina N. Salgado

Abstract:

Introduction: The emergence of resistant microorganisms to a large number of clinically approved antimicrobials has been increasing, which restrict the options for the treatment of bacterial infections. As a strategy, drugs with high antimicrobial activities are in evidence. Stands out a class of antimicrobial, the cephalosporins, having as fourth generation cefepime (CEF) a semi-synthetic product which has activity against various Gram-positive bacteria (e.g. oxacillin resistant Staphylococcus aureus) and Gram-negative (e.g. Pseudomonas aeruginosa) aerobic. There are few studies in the literature regarding the development of microbiological methodologies for the analysis of this antimicrobial, so researches in this area are highly relevant to optimize the analysis of this drug in the industry and ensure the quality of the marketed product. The development of microbiological methods for the analysis of antimicrobials has gained strength in recent years and has been highlighted in relation to physicochemical methods, especially because they make possible to determine the bioactivity of the drug against a microorganism. In this context, the aim of this work was the development and validation of a microbiological method for quantitative analysis of CEF in powder lyophilized for injectable solution by turbidimetric assay. Method: For performing the method, Staphylococcus aureus ATCC 6538 IAL 2082 was used as the test microorganism and the culture medium chosen was the Casoy broth. The test was performed using temperature control (35.0 °C ± 2.0 °C) and incubated for 4 hours in shaker. The readings of the results were made at a wavelength of 530 nm through a spectrophotometer. The turbidimetric microbiological method was validated by determining the following parameters: linearity, precision (repeatability and intermediate precision), accuracy and robustness, according to ICH guidelines. Results and discussion: Among the parameters evaluated for method validation, the linearity showed results suitable for both statistical analyses as the correlation coefficients (r) that went 0.9990 for CEF reference standard and 0.9997 for CEF sample. The precision presented the following values 1.86% (intraday), 0.84% (interday) and 0.71% (between analyst). The accuracy of the method has been proven through the recovery test where the mean value obtained was 99.92%. The robustness was verified by the parameters changing volume of culture medium, brand of culture medium, incubation time in shaker and wavelength. The potency of CEF present in the samples of lyophilized powder for injectable solution was 102.46%. Conclusion: The turbidimetric microbiological method proposed for quantification of CEF in lyophilized powder for solution for injectable showed being fast, linear, precise, accurate and robust, being in accordance with all the requirements, which can be used in routine analysis of quality control in the pharmaceutical industry as an option for microbiological analysis.

Keywords: cefepime hydrochloride, quality control, turbidimetric assay, validation

Procedia PDF Downloads 362