Search results for: hybrid teams

Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Uzaira Rafique, Kousar Parveen

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The discharge volume and composition of Textile effluents gains scientific concern due to its hazards and biotoxcity of azo dyes. Azo dyes are non-biodegradable due to its complex molecular structure and recalcitrant nature. Serious attempts have been made to synthesize and develop new materials to combat the environmental problems. The present study is designed for removal of a range of azo dyes (Methyl orange, Congo red and Basic fuchsine) from synthetic aqueous solutions and real textile effluents. For this purpose, Metal (cobalt) doped alumina hybrids are synthesized and applied as adsorbents in the batch experiment. Two different aluminium precursor (aluminium nitrate and spent aluminium foil) and glucose are mixed following sol gel method to get hybrids. The synthesized materials are characterized for surface and bulk properties using FTIR, SEM-EDX and XRD techniques. The characterization of materials under FTIR revealed that –OH (3487-3504 cm-1), C-H (2935-2985 cm-1), Al-O (~ 800 cm-1), Al-O-C (~1380 cm-1), Al-O-Al (659-669 cm-1) groups participates in the binding of dyes onto the surface of hybrids. Amorphous shaped particles and elemental composition of carbon (23%-44%), aluminium (29%-395%), and oxygen (11%-20%) is demonstrated in SEM-EDX micrograph. Time-dependent batch-experiments under identical experimental parameters showed 74% congo red, 68% methyl orange and 85% maximum removal of basic fuchsine onto the surface of cobalt doped alumina hybrids probably through the ion-exchange mechanism. The experimental data when treated with adsorption models is found to have good agreement with pseudo second order kinetic and freundlich isotherm for adsorption process. The present study concludes the successful synthesis of novel and efficient cobalt doped alumina hybrids providing environmental friendly and economical alternative to the commercial adsorbents for the treatment of industrial effluents.

Keywords: alumina hybrid, adsorption, dopant, isotherm, kinetic

Procedia PDF Downloads 174

Authors: Munir Kassa, Mengistu Hailemariam, Meghan Obermeyer, Kefelegn Baruda, Yonas Getachew, Asnakech Dessie

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Improving the quality of sexual and reproductive health services that women receive is expected to have an impact on women’s satisfaction with the services, on their continued use and, ultimately, on their ability to achieve their fertility goals or reproductive intentions. Surprisingly, however, there is little empirical evidence of either whether this expectation is correct, or how best to improve service quality within sexual and reproductive health programs so that these impacts can be achieved. The Recent focus on quality has prompted more physicians to do quality improvement work, but often without the needed skill sets, which results in poorly conceived and ultimately unsuccessful improvement initiatives. As this renders the work unpublishable, it further impedes progress in the field of health care improvement and widens the quality chasm. Moreover, since 2014, the Center for International Reproductive Health Training (CIRHT) has worked diligently with 11 teaching hospitals across Ethiopia to increase access to contraception and abortion care services. This work has included improving pre-service training through education and curriculum development, expanding hands-on training to better learn critical techniques and counseling skills, and fostering a “team science” approach to research by encouraging scientific exploration. This is the first time this systematic approach has been applied and documented to improve access to high-quality services in Ethiopia. The purpose of this article is to report initiatives undertaken, and findings concluded by the clinical service team at CIRHT in an effort to provide a pragmatic approach to quality improvement projects. An audit containing nearly 300 questions about several aspects of patient care, including structure, process, and outcome indicators was completed by each teaching hospital’s quality improvement team. This baseline audit assisted in identifying major gaps and barriers, and each team was responsible for determining specific quality improvement aims and tasks to support change interventions using Shewart’s Cycle for Learning and Improvement (the Plan-Do-Study-Act model). To measure progress over time, quality improvement teams met biweekly and compiled monthly data for review. Also, site visits to each hospital were completed by the clinical service team to ensure monitoring and support. The results indicate that applying an evidence-based, participatory approach to quality improvement has the potential to increase the accessibility and quality of services in a short amount of time. In addition, continued ownership and on-site support are vital in promoting sustainability. This approach could be adapted and applied in similar contexts, particularly in other African countries.

Keywords: abortion, contraception, quality improvement, service provision

Procedia PDF Downloads 192

Authors: Makhlouf Mourad, Messabih Sidi Mohamed, Bouchher Omar, Houali Farida, Benrachedi Khaled

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Mesoporous materials are very commonly used as adsorbent materials for removing phenolic compounds. However, the adsorption mechanism of these compounds is still poorly controlled. However, understanding the interactions mesoporous materials/adsorbed molecules is very important in order to optimize the processes of liquid phase adsorption. The difficulty of synthesis is to keep an orderly and cubic pore structure and achieve a homogeneous surface modification. The grafting of Si(CH₃)₃ was chosen, to transform hydrophilic surfaces hydrophobic surfaces. The aim of this work is to study the kinetics and thermodynamics of two volatile organic compounds VOC phenol (PhOH) and P hydroxy benzoic acid (4AHB) on a mesoporous material of type MCM-48 grafted with an organosilane of the Trimethylchlorosilane (TMCS) type, the material thus grafted or functionalized (hereinafter referred to as MCM-48-G). In a first step, the kinetic and thermodynamic study of the adsorption isotherms of each of the VOCs in mono-solution was carried out. In a second step, a similar study was carried out on a mixture of these two compounds. Kinetic models (pseudo-first order, pseudo-second order) were used to determine kinetic adsorption parameters. The thermodynamic parameters of the adsorption isotherms were determined by the adsorption models (Langmuir, Freundlich). The comparative study of adsorption of PhOH and 4AHB proved that MCM-48-G had a high adsorption capacity for PhOH and 4AHB; this may be related to the hydrophobicity created by the organic function of TMCS in MCM-48-G. The adsorption results for the two compounds using the Freundlich and Langmuir models show that the adsorption of 4AHB was higher than PhOH. The values ​​obtained by the adsorption thermodynamics show that the adsorption interactions for our sample with the phenol and 4AHB are of a physical nature. The adsorption of our VOCs on the MCM-48 (G) is a spontaneous and exothermic process.

Keywords: adsorption, kinetics, isotherm, mesoporous materials, Phenol, P-hydroxy benzoique acid

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Authors: Rui Wu

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In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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Authors: Jihuai Wu, Zeyu Song, Zhang Lan, Liuxue Sun

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Solar energy is clean, open, and infinite, but solar radiation on the earth is fluctuating, intermittent, and unstable. So, the sustainable utilization of solar energy requires a combination of high-efficient energy conversion and low-loss energy storage technologies. Hence, a photo capacitor integrated with photo-electrical conversion and electric-chemical storage functions in single device is a cost-effective, volume-effective and functional-effective optimal choice. However, owing to the multiple components, multi-dimensional structure and multiple functions in one device, especially the mismatch of the functional modules, the overall conversion and storage efficiency of the photocapacitors is less than 13%, which seriously limits the development of the integrated system of solar conversion and energy storage. To this end, two typical photocapacitors were studied. A three-terminal photocapacitor was integrated by using perovskite solar cell as solar conversion module and symmetrical supercapacitor as energy storage module. A function portfolio management concept was proposed the relationship among various efficiencies during photovoltaic conversion and energy storage process were clarified. By harmonizing the energy matching between conversion and storage modules and seeking the maximum power points coincide and the maximum efficiency points synchronize, the overall efficiency of the photocapacitor surpassed 18 %, and Joule efficiency was closed to 90%. A voltage adjustable hybrid supercapacitor (VAHSC) was designed as energy storage module, and two Si wafers in series as solar conversion module, a three-terminal photocapacitor was fabricated. The VAHSC effectively harmonizes the energy harvest and storage modules, resulting in the current, voltage, power, and energy match between both modules. The optimal photocapacitor achieved an overall efficiency of 15.49% and Joule efficiency of 86.01%, along with excellent charge/discharge cycle stability. In addition, the Joule efficiency (ηJoule) was defined as the energy ratio of discharge/charge of the devices for the first time.

Keywords: joule efficiency, perovskite solar cell, photocapacitor, silicon solar cell, supercapacitor

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Authors: Ayman M. Mansour, Bilal Hawashin, Hesham Alsalem

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Faster delivery of laboratory test results is one of the most noticeable signs of good laboratory service and is often used as a key performance indicator of laboratory performance. Despite the availability of technology, the delivery time of clinical laboratory test results continues to be a cause of customer dissatisfaction which makes patients feel frustrated and they became careless to get their laboratory test results. The Medical Clinical Laboratory test results are highly sensitive and could harm patients especially with the severe case if they deliver in wrong time. Such results affect the treatment done by physicians if arrived at correct time efforts should, therefore, be made to ensure faster delivery of lab test results by utilizing new trusted, Robust and fast system. In this paper, we proposed a distributed Multi-Agent System to enhance and faster the process of laboratory test results delivery using SMS. The developed system relies on SMS messages because of the wide availability of GSM network comparing to the other network. The software provides the capability of knowledge sharing between different units and different laboratory medical centers. The system was built using java programming. To implement the proposed system we had many possible techniques. One of these is to use the peer-to-peer (P2P) model, where all the peers are treated equally and the service is distributed among all the peers of the network. However, for the pure P2P model, it is difficult to maintain the coherence of the network, discover new peers and ensure security. Also, security is a quite important issue since each node is allowed to join the network without any control mechanism. We thus take the hybrid P2P model, a model between the Client/Server model and the pure P2P model using GSM technology through SMS messages. This model satisfies our need. A GUI has been developed to provide the laboratory staff with the simple and easy way to interact with the system. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.

Keywords: multi-agent system, delivery process, GSM technology, clinical laboratory results

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: D. Berg, N. Hartley, L. Nasr

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This paper presents a conceptual model of human-robot interaction within service encounters and the effect on the well-being of both consumers and service providers. In this paper, service providers are those employees who work alongside frontline service robots. The significance of this paper lies in the knowledge created which outlines how frontline service robots can be effectively utilized in service encounters for the benefit of organizations and society as a whole. As this paper is conceptual in nature, the main methodologies employed are theoretical, namely problematization and theory building. The significance of this paper is underpinned by the shift of service robots from manufacturing plants and factory floors to consumer-facing service environments. This service environment places robots in direct contact with frontline employees and consumers creating a hybrid workplace where humans work alongside service robots. This change from back-end to front-end roles may have implications not only on the physical environment, servicescape, design, and strategy of service offerings and encounters but also on the human parties of the service encounter itself. Questions such as ‘how are frontline service robots impacting and changing the service encounter?’ and ‘what effect are such changes having on the well-being of the human actors in a service encounter?’ spring to mind. These questions form the research question of this paper. To truly understand social service robots, an interdisciplinary perspective is required. Besides understanding the function, system, design or mechanics of a service robot, it is also necessary to understand human-robot interaction. However not simply human-robot interaction, but particularly what happens when such robots are placed in commercial settings and when human-robot interaction becomes consumer-robot interaction and employee-robot interaction? A service robot in this paper is characterized by two main factors; its social characteristics and the consumer-facing environment within which it operates. The conceptual framework presented in this paper contributes to interdisciplinary discussions surrounding social robotics, service, and technology’s impact on consumer and service provider well-being, and hopes that such knowledge will help improve services, as well as the prosperity and well-being of society.

Keywords: frontline service robots, human-robot interaction, service encounters, well-being

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Authors: Heiko Weiß, Andreas Meister, Christoph Ament, Nils Dreifke

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Linear actuators are deployed in a wide range of applications. This paper presents the modeling and system identification of a variable excited linear direct drive (LDD). The LDD is designed based on linear hybrid stepper technology exhibiting the characteristic tooth structure of mover and stator. A three-phase topology provides the thrust force caused by alternating strengthening and weakening of the flux of the legs. To achieve best possible synchronous operation, the phases are commutated sinusoidal. Despite the fact that these LDDs provide high dynamics and drive forces, noise emission limits their operation in calm workspaces. To overcome this drawback an additional excitation of the magnetic circuit is introduced to LDD using additional enabling coils instead of permanent magnets. The new degree of freedom can be used to reduce force variations and related noise by varying the excitation flux that is usually generated by permanent magnets. Hence, an identified simulation model is necessary to analyze the effects of this modification. Especially the force variations must be modeled well in order to reduce them sufficiently. The model can be divided into three parts: the current dynamics, the mechanics and the force functions. These subsystems are described with differential equations or nonlinear analytic functions, respectively. Ordinary nonlinear differential equations are derived and transformed into state space representation. Experiments have been carried out on a test rig to identify the system parameters of the complete model. Static and dynamic simulation based optimizations are utilized for identification. The results are verified in time and frequency domain. Finally, the identified model provides a basis for later design of control strategies to reduce existing force variations.

Keywords: force variations, linear direct drive, modeling and system identification, variable excitation flux

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Authors: David Amoah Oduro

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In the ever-evolving terrain of international business, a profound revolution is underway, guided by the swift integration and advancement of disruptive technologies like digital analytics. In today's international business landscape, where competition is fierce, and decisions are data-driven, the essence of this paper lies in offering a tangible roadmap for practitioners. It is a guide that bridges the chasm between theory and actionable insights, helping businesses, investors, and entrepreneurs navigate the complexities of international expansion into sub-Saharan Africa. This practitioner paper distils essential insights, methodologies, and actionable recommendations for businesses seeking to leverage digital analytics in their pursuit of market entry and expansion across the African continent. What sets this paper apart is its unwavering focus on a region ripe with potential: sub-Saharan Africa. The adoption and adaptation of digital analytics are not mere luxuries but essential strategic tools for evaluating countries and entering markets within this dynamic region. With the spotlight firmly fixed on sub-Saharan Africa, the aim is to provide a compelling resource to guide practitioners in their quest to unearth the vast opportunities hidden within sub-Saharan Africa's digital desert. The paper illuminates the pivotal role of digital analytics in providing a data-driven foundation for market entry decisions. It highlights the ability to uncover market trends, consumer behavior, and competitive landscapes. By understanding Africa's incredible diversity, the paper underscores the importance of tailoring market entry strategies to account for unique cultural, economic, and regulatory factors. For practitioners, this paper offers a set of actionable recommendations, including the creation of cross-functional teams, the integration of local expertise, and the cultivation of long-term partnerships to ensure sustainable market entry success. It advocates for a commitment to continuous learning and flexibility in adapting strategies as the African market evolves. This paper represents an invaluable resource for businesses, investors, and entrepreneurs who are keen on unlocking the potential of digital analytics for informed market entry in Africa. It serves as a guiding light, equipping practitioners with the essential tools and insights needed to thrive in this dynamic and diverse continent. With these key insights, methodologies, and recommendations, this paper is a roadmap to prosperous and sustainable market entry in Africa. It is vital for anyone looking to harness the transformational potential of digital analytics to create prosperous and sustainable ventures in a region brimming with promise. In the ever-advancing digital age, this practitioner paper becomes a lodestar, guiding businesses and visionaries toward success amidst the unique challenges and rewards of sub-Saharan Africa's international business landscape.

Keywords: global analytics, digital analytics, sub-Saharan Africa, data analytics

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Authors: Robert Prohaska, Arnaud Konan, Kenneth Kelly, Adam Ragatz, Adam Duran

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In an effort to evaluate the in-use performance of electrified Power Take-off (PTO) usage on bucket utility trucks operating under real-world conditions, data from 20 medium- and heavy-duty vehicles operating in California, USA were collected, compiled, and analyzed by the National Renewable Energy Laboratory's (NREL) Fleet Test and Evaluation team. In this paper, duty-cycle statistical analyses of class 5, medium-duty quick response trucks and class 8, heavy-duty material handler trucks are performed to examine and characterize vehicle dynamics trends and relationships based on collected in-use field data. With more than 100,000 kilometers of driving data collected over 880+ operating days, researchers have developed a robust methodology for identifying PTO operation from in-field vehicle data. Researchers apply this unique methodology to evaluate the performance and utilization of the conventional and electric PTO systems. Researchers also created custom representative drive-cycles for each vehicle configuration and performed modeling and simulation activities to evaluate the potential fuel and emissions savings for hybridization of the tractive driveline on these vehicles. The results of these analyses statistically and objectively define the vehicle dynamic and kinematic requirements for each vehicle configuration as well as show the potential for further system optimization through driveline hybridization. Results are presented in both graphical and tabular formats illustrating a number of key relationships between parameters observed within the data set that relates specifically to medium- and heavy-duty utility vehicles operating under real-world conditions.

Keywords: drive cycle, heavy-duty (HD), hybrid, medium-duty (MD), PTO, utility

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Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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Authors: Sandra Arango-Caro, Kristine Callis-Duehl

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The Education Research and Outreach Lab at the Donald Danforth Plant Science Center established the Plant and Agriculture Augmented and Virtual Reality Learning Laboratory (PAVRLL) to promote science education through professional development, school programs, internships, and outreach events. Professional development is offered to high school and college science and agriculture educators on the use and applications of zSpace and Oculus platforms. Educators learn to use, edit, or create lesson plans in the zSpace platform that are aligned with the Next Generation Science Standards. They also learn to use virtual reality experiences created by the PAVRLL available in Oculus (e.g. The Soybean Saga). Using a cost-free loan rotation system, educators can bring the AVR units to the classroom and offer AVR activities to their students. Each activity has user guides and activity protocols for both teachers and students. The PAVRLL also offers activities for 3D plant modeling. High school students work in teams of art-, science-, and technology-oriented students to design and create 3D models of plant species that are under research at the Danforth Center and present their projects at scientific events. Those 3D models are open access through the zSpace platform and are used by PAVRLL for professional development and the creation of VR activities. Both teachers and students acquire knowledge of plant and agriculture content and real-world problems, gain skills in AVR technology, 3D modeling, and science communication, and become more aware and interested in plant science. Students that participate in the PAVRLL activities complete pre- and post-surveys and reflection questions that evaluate interests in STEM and STEM careers, students’ perceptions of three design features of biology lab courses (collaboration, discovery/relevance, and iteration/productive failure), plant awareness, and engagement and learning in AVR environments. The PAVRLL was established in the fall of 2019, and since then, it has trained 15 educators, three of which will implement the AVR programs in the fall of 2021. Seven students have worked in the 3D plant modeling activity through a virtual internship. Due to the COVID-19 pandemic, the number of teachers trained, and classroom implementations have been very limited. It is expected that in the fall of 2021, students will come back to the schools in person, and by the spring of 2022, the PAVRLL activities will be fully implemented. This will allow the collection of enough data on student assessments that will provide insights on benefits and best practices for the use of AVR technologies in the classrooms. The PAVRLL uses cutting-edge educational technologies to promote science education and assess their benefits and will continue its expansion. Currently, the PAVRLL is applying for grants to create its own virtual labs where students can experience authentic research experiences using real Danforth research data based on programs the Education Lab already used in classrooms.

Keywords: assessment, augmented reality, education, plant science, virtual reality

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Authors: Chia-Yi Wu, Jung-Chen Chang, Wen-Yu Hu, Ming-Been Lee

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In nearly all physical health conditions, suicide risk is increased compared to healthy people even after adjustment for age, gender, mental health, and substance use diagnoses. In order to highlight the importance of suicide risk assessment for the inpatients and early identification and engagement for inpatients’ mental health problems, a study was designed aiming at developing a comprehensive psychosomatic nursing engagement (PSNE) model with standardized operation procedures informing how nurses communicate, assess, and engage with the inpatients with emotional distress. The purpose of the study was to promote the gatekeeping role of clinical nurses in performing brief assessment and interventions to detect depression and anxiety symptoms among the inpatients, particularly in non-psychiatric wards. The study will be carried out in a 2000-bed university hospital in Northern Taiwan in 2019. We will select a ward for trial and develop feasible procedures and in-job training course for the nurses to offer mental health care, which will also be validated through professional consensus meeting. The significance of the study includes the following three points: (1) The study targets at an important but less-researched area of PSNE model in the cultural background of Taiwan, where hospital service is highly accessible, but mental health and suicide risk assessment are hardly provided by non-psychiatric healthcare personnel. (2) The issue of PSNE could be efficient and cost-effective in the identification of suicide risks at an early stage to prevent inpatient suicide or to reduce future suicide risk by early treatment of mental illnesses among the high-risk group of hospitalized patients who are more than three-times lethal to suicide. (3) Utilizing a brief tool with its established APP ('The Five-item Brief Symptom Rating Scale, BSRS-5'), we will invent the standardized procedure of PSNE and referral steps in collaboration with the medical teams across the study hospital. New technological tools nested within nursing assessment/intervention will concurrently be invented to facilitate better care quality. The major outcome measurements will include tools for early identification of common mental distress and suicide risks, i.e., the BSRS-5, revised BSRS-5, and the 9-item Concise Mental Health Checklist (CMHC-9). The main purpose of using the CMHC-9 in clinical suicide risk assessment is mainly to provide care and build-up therapeutic relationship with the client, so it will also be used to nursing training highlighting the skills of supportive care. Through early identification of the inpatients’ depressive symptoms or other mental health care needs such as insomnia, anxiety, or suicide risk, the majority of the nursing clinicians would be able to engage in critical interventions that alleviate the inpatients’ suffering from mental health problems, given a feasible nursing input.

Keywords: mental health care, clinical outcome improvement, clinical nurses, suicide prevention, psychosomatic nursing

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Authors: Hossam E. Emam

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Metal–organic frameworks (MOFs) are new hybrid materials investigated from 15 years ago; they synthesized from metals as inorganic center joined with multidentate organic linkers to form a 1D, 2D or 3D network structure. MOFs have unique properties such as pore crystalline structure, large surface area, chemical tenability and luminescent characters. These significant properties enable MOFs to be applied in many fields such like gas storage, adsorption/separation, drug delivery/biomedicine, catalysis, polymerization, magnetism and luminescence applications. Recently, many of published reports interested in superiority of MOFs for functionalization of textiles to exploit the unique properties of MOFs. Incorporation of MOFs is found to acquire the textiles some additional formidable functions to be used in considerable fields such like water treatment and fuel purification. Modification of textiles with MOFs could be easily performed by two main techniques; Ex-situ (preparation of MOFs then applied onto textiles) and in-situ (ingrowth of MOFs within textiles networks). Uniqueness of MOFs could be assimilated in acquirement of decorative color, antimicrobial character, anti-mosquitos character, ultraviolet radiation protective, self-clean, photo-luminescent and sensor character. Additionally, textiles treatment with MOFs make it applicable as filter in the adsorption of toxic gases, hazardous materials (such as pesticides, dyes and aromatics molecules) and fuel purification (such as removal of oxygenated, nitrogenated and sulfur compounds). Also, the porous structure of MOFs make it mostly utilized in control release of insecticides from the surface of the textile. Moreover, MOF@textiles as recyclable materials lead it applicable as photo-catalyst composites for photo-degradation of different dyes in the day light. Therefore, MOFs is extensively considered for imparting textiles with formidable properties as ingeniousness way for textile functionalization.

Keywords: MOF, functional textiles, water treatment, fuel purification, environmental applications

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Authors: Nuno Biga

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Artificial Intelligence (AI) allows machines to interpret information and learn from context analysis, giving them the ability to make predictions adjusted to each specific situation. In addition to learning by performing deterministic and probabilistic calculations, the 'artificial brain' also learns through information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) that provides users with useful suggestions, namely to pursue the following operations: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time the bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed in a pilot project. Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of this information is materialised in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" that players can use during the Game. Each participant in the Virtual Assisted-BIGAMES permanently asks himself about the decisions he should make during the game in order to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, and as the participants gain a better understanding of the game, they will more easily dispense with the VA's recommendations and rely more on their own experience, capability, and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator (Serious Game Controller) is responsible for supporting the players with further analysis and the recommended action may be (or not) aligned with the previous recommendations of the VA. All the information should be jointly analysed and assessed by each player, who are expected to add “Emotional Intelligence”, a component absent from the machine learning process.

Keywords: artificial intelligence (AI), gamification, key performance indicators (KPI), machine learning, management simulators, serious games, virtual assistant

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Authors: Rumbidzai Sipiwe Zimvumi

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The study aimed to identify the top management team attributes for ambidexterity in small and medium-sized enterprises by utilizing the upper echelons theory. The conventional opinion holds that an organization's ability to pursue both exploitative and explorative innovation methods at the same time is reflected in its ambidexterity. Top-level managers are critical to this matrix because they forecast and explain strategic choices that guarantee success by improving organizational performance. Since the focus of the study was on the unique characteristics of TMTs that can facilitate ambidexterity, the primary goal was to comprehend how TMTs in SMEs can better manage ambidexterity. The study used document analysis to collect information on ambidexterity and TMT traits. Finding, choosing, assessing, and synthesizing data from peer-reviewed publications allowed for the review and evaluation of papers. The fact that SMEs will perform better if they can achieve a balance between exploration and exploitation cannot be overstated. Unfortunately, exploitation is the main priority for most SMEs. The results showed that some of the noteworthy TMT traits that support ambidexterity in SMEs are age diversity, shared responsibility, leadership impact, psychological safety, and self-confidence. It has been shown that most SMEs confront significant obstacles in recruiting people, including formalizing their management and assembling executive teams with seniority. Small and medium-sized enterprises (SMEs) are often held by families or people who neglect to keep their personal lives apart from the firm, which eliminates the opportunity for management and staff to take the initiative. This helps to explain why exploitative strategies, which preserve present success, are used rather than explorative strategies, which open new economic opportunities and dimensions. It is evident that psychological safety deteriorates, and creativity is hindered in the process. The study makes the case that TMTs who are motivated to become ambidextrous can exist. According to the report, small- and medium-sized business owners should value the opinions of all parties involved and provide their managers and regular staff the freedom to think creatively and in a safe environment. TMTs who experience psychological safety are more likely to be inventive, creative, and productive. A team's collective perception that it is acceptable to take chances, voice opinions and concerns, ask questions, and own up to mistakes without fear of unfavorable outcomes is known as team psychological safety. Thus, traits like age diversity, leadership influence, learning agility, psychological safety, and self-assurance are critical to the success of SMEs. As a solution to ensuring ambidexterity is attained, the study suggests a clear separation of ownership and control, the adoption of technology to stimulate creativity, team spirit and excitement, shared accountability, and good management of diversity. Among the suggestions for the SME's success are resource allocation and important collaborations.

Keywords: navigating, ambidexterity, top management team, small and medium enterprises

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Ji-Won Park, Jong-Wha Kim

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Triploid L. lancifolium have a wide geographic distribution. By contrast, diploid L. lancifolium have limited distributions in the islands and coastal regions of the South and West Korean Peninsula and northern Tsushima Island, Japan. L. lancifolium diploids and triploids are not sympatrically distributed with other lily species or ploidy lines in West Sea and South Sea Islands of the Korean Peninsula. This observation raises the following questions: 'Why have autotriploid L. lancifolium never been observed in those isolated islands?', 'What mechanism excludes the occurrence of autotriploids, if they arise?'. To determine the occurrence and survival of triploid plants in natural diploid populations of tiger lily (Lilium lancifolium), ploidy analysis was conducted on natural open-pollinated seeds produced from plants grown on isolated islands, and on hybrid seeds produced by artificial crossing between plant populations originating on different Korean islands. Normal seeds were classified into five grades depending on the ratio of embryo/endosperm lengths, including 5/5, 4/5, 3/5, 2/5, and 1/5. Triploids were not observed among seedlings produced from natural open pollinations on isolated islands. Triploids were detected only in seedlings of underdeveloped seed grades(3/5 and 2/5) from artificial crosses between populations from different isolated islands. The triploid occurrence frequency was calculated as 0.0 for natural open-pollinated seedlings and 0.000582 for artificial crosses(6 triploids from 10,303 seedlings). Triploids were produced from crosses between isolated populations located at least 70 km apart; no triploids were detected in inter-population crosses of plants originating on the same islands. Triploid seedlings have very low viability in soil. We analyzed factors affecting triploid occurrence and survival in natural diploid populations of L. lancifolium. The results suggest that triploids originate from fertilization between plants that are genetically isolated due to geographical isolation and/or genotypic differences.

Keywords: Lilium lancifolium, autotriploid, natural population, genetic distance, 2n female gamete

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Authors: Kaori Narita, Juan de Dios Tena Horrillo, Claudio Detotto

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Decisions on replacement of leaders are of significance and high prevalence in any organization, and concerns many of its stakeholders, whether it is a leader in a political party or a CEO of a firm, as indicated by high media coverage of such events. This merits an investigation into the consequences and implications of a leadership change on the performances and behavior of organizations and their workers. Sport economics provides a fruitful field to explore these issues due to the high frequencies of managerial changes in professional sports clubs and the transparency and regularity of observations of team performance and players’ abilities. Much of the existing research on managerial change focuses on how this affects the performance of an organization. However, there is scarcely attention paid to the consequences of such events on the behavior of individuals within the organization. Changes in behavior and attitudes of a group of workers due to a managerial change could be of great interest in management science, psychology, and operational research. On the other hand, these changes cannot be observed in the final outcome of the organization, as this is affected by many other unobserved shocks, for example, the stress level of workers with the need to deal with a difficult situation. To fill this gap, this study shows the first attempt to evaluate the impact of managerial change on players’ behaviors such as attack intensity, aggressiveness, and efforts. The data used in this study is from the top tier Italian football league (“Serie A”), where an average of 13 within season replacements of head coaches were observed over the period of seasons from 2000/2001 to 2017/18. The preliminary estimation employs Pooled Ordinary Least Square (POLS) and club-season Fixed Effect (FE) in order to assess the marginal effect of having a new manager on the number of shots, corners and red/yellow cards after controlling for a home-field advantage, ex ante abilities and current positions in the league of a team and their opponent. The results from this preliminary estimation suggest that the teams do not show a significant difference in their behaviors before and after the managerial change. To build on these preliminary results, other methods, including propensity score matching and non-linear model estimates, will be used. Moreover, the study will further investigate these issues by considering other measurements of attack intensity, aggressiveness, and efforts, such as possessions, a number of fouls and the athletic performance of players, respectively. Finally, the study is going to investigate whether these results vary over the characteristics of a new head coach, for example, their age and experience as a manager and a player. Thus far, this study suggests that certain behaviours of individuals in an organisation are not immediately affected by a change in leadership. To confirm this preliminary finding and lead to a more solid conclusion, further investigation will be conducted in the aforementioned manner, and the results will be elaborated in the conference.

Keywords: behaviour, effort, manager characteristics, managerial change, sport economics

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Authors: Young Ik Suh, Tywan G. Martin

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Bundling strategy is a common marketing practice today. In the past decades, both academicians and practitioners have increasingly emphasized the strategic importance of bundling in today’s markets. The reason for increased interest in bundling strategy is that they normally believe that it can significantly increase profits on organization’s sales over time and it is convenient for the customer. However, little efforts has been made on ticket bundling and purchase considerations in hedonic and utilitarian options in sport consumer behavior context. Consumers often face choices between utilitarian and hedonic alternatives in decision making. When consumers purchase certain products, they are only interested in the functional dimensions, which are called utilitarian dimensions. On the other hand, others focus more on hedonic features such as fun, excitement, and pleasure. Thus, the current research examines how utilitarian and hedonic consumption can vary in typical ticket purchasing process. The purpose of this research is to understand the following two research themes: (1) the differential effect of discount framing on ticket bundling: utilitarian and hedonic options and (2) moderating effect of team identification on ticket bundling. In order to test the research hypotheses, an experimental study using a two-way ANOVA, 3 (team identification: low, medium, and high) X 2 (discount frame: ticket bundle sales with utilitarian product, and hedonic product), with mixed factorial design will be conducted to determine whether there is a statistical significance between purchasing intentions of two discount frames of ticket bundle sales within different team identification levels. To compare mean differences among the two different settings, we will create two conditions of ticket bundles: (1) offering a discount on a ticket ($5 off) if they would purchase it along with utilitarian product (e.g., iPhone8 case, t-shirt, cap), and (2) offering a discount on a ticket ($5 off) if they would purchase it along with hedonic product (e.g., pizza, drink, fans featured on big screen). The findings of the current ticket bundling study are expected to have many theoretical and practical contributions and implications by extending the research and literature pertaining to the relationship between team identification and sport consumer behavior. Specifically, this study can provide a reliable and valid framework to understanding the role of team identification as a moderator on behavioral intentions such as purchase intentions. From an academic perspective, the study will be the first known attempt to understand consumer reactions toward different discount frames related to ticket bundling. Even though the game ticket itself is the major commodity of sport event attendance and significantly related to teams’ revenue streams, most recent ticket pricing research has been done in terms of economic or cost-oriented pricing and not from a consumer psychological perspective. For sport practitioners, this study will also provide significant implications. The result will imply that sport marketers may need to develop two different ticketing promotions for loyal fan and non-loyal fans. Since loyal fans concern ticket price than tie-in products when they see ticket bundle sales, advertising campaign should be more focused on discounting ticket price.

Keywords: ticket bundling, hedonic, utilitarian, team identification

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Authors: D. Mulligan, D. Casey

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Introductory Statement: Delegation is when a registered nurse (RN) transfers a task or activity that is normally within their scope of practice to another person (delegatee). RN delegation is common practice with unregistered staff, e.g., student nurses and health care assistants (HCAs). As the role of the HCA is increasingly embedded as a direct care and support role, especially in long-term residential care for older adults, there is RN uncertainty as to their role as a delegator. The assignment is when a task is transferred to a person that is within the role specification of the delegatee. RNs in long-term care (LTC) for older people are increasingly working in teams where there are less RNs and more HCAs providing direct care to the residents. The RN is responsible and accountable for their decision to delegate and assign tasks to HCAs. In an interpretive, multiple case studies to explore how delegation of tasks by RNs to HCAs occurred in long-term care settings in Ireland the importance of the RN understanding their scope of practice emerged. Methodology: Focus group interviews and individual interviews were undertaken as part of a multiple case study. Both cases, anonymized as Case A and Case B, were within the public health service in Ireland. The case study sites were long-term care settings for older adults located in different social care divisions, and in different geographical areas. Four focus group interviews with staff nurses and three individual interviews with CNMs were undertaken. The interactive data analysis approach was the analytical framework used, with within-case and cross-case analysis. The theoretical lens of organizational role theory, applying the role episode model (REM), was used to understand, interpret, and explain the findings. Study Findings: RNs and CNMs understood the role of the nurse regulator and the scope of practice. RNs understood that the RN was accountable for the care and support provided to residents. However, RNs and CNM2s could not describe delegation in the context of their scope of practice. In both cases, the RNs did not have a standardized process for assessing HCA competence to undertake nursing tasks or interventions. RNs did not routinely supervise HCAs. Tasks were assigned and not delegated. There were differences between the cases in relation to understanding which nursing tasks required delegation. HCAs in Case A undertook clinical vital sign assessments and documentation. HCAs in Case B did not routinely undertake these activities. Delegation and assignment were influenced by the organizational factors, e.g., model of care, absence of delegation policies, inadequate RN education on delegation, and a lack of RN and HCA role clarity. Concluding Statement: Nurse staffing levels and skill mix in long-term care settings continue to change with more HCAs providing more direct care and support. With decreasing RN staffing levels RNs will be required to delegate and assign more direct care to HCAs. There is a requirement to distinguish between RN assignment and delegation at policy, regulation, and organizational levels.

Keywords: assignment, delegation, registered nurse, scope of practice

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Authors: Ionelia Taranu, Gina Cecilia Pistol, Mihai Alexandru Gras, Mihai Laurentiu Palade, Mariana Stancu, Veronica Sanda Chedea

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In the last decade bioactive compounds from grape waste are investigated as new therapeutic agents for the inhibition of carcinogenesis and other diseases. The objective of this study was to characterize several bioactive compounds (polyphenols and polyunsaturated fatty acids) of a dried grape pomace (GP) derived from a Romanian winery and further to evaluate their effect on inflammation and oxidative markers in liver of pig used as animal model. The total polyphenol concentration of pomace was 36.2g gallic acid equiv /100g. The pomace was rich in polyphenols from the flavonoids group, the main class being flavanols (epicatechins, catechin, epigallocatechin, procyanidins) and antocyanins (Malvidin 3-O-glucoside). The highest concentration was recorded for epicatechin (51.96g/100g) and procyanidin dimer (22.79g/100g). A high concentration of total polyunsaturated fatty acids (PUFA) especially ω-6 fatty acids (59.82 g/100g fat) was found in grape pomace. 20 crossbred TOPIG hybrid fattening pigs were randomly assigned (n = 10) to two experimental treatments: a normal diet (control group) and a diet included 5% grape pomace (GP group) for 24 days. The GP diet lowered the gene expression and protein concentration of IL-1β, IL-8, TNF-α and IFN-γ cytokines in liver suggesting an anti-inflammatory effect of GP diet. Concentration of hepatic TBARS also decreased, but the total antioxidant capacity (liver TEAC) and activity and gene expression of antioxidant enzymes (superoxide dismutase, catalase and glutathione peroxidase) did not differ between the GP and control diet. The results showed that GP diet exerted an anti-inflammatory effect, but the 5% dietary inclusion modulated only partially the oxidative stress.

Keywords: animal model, inflammation, grape waste, immune organs

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Authors: Bekir Turedi

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Exploiting the potential of perovskite single-crystal solar cells in optoelectronic applications necessitates overcoming a significant challenge: the low charge collection efficiency at increased thickness, which has restricted their deployment in radiation detectors and nuclear batteries. Our research details a promising approach to this problem, wherein we have successfully fabricated single-crystal MAPbI3 solar cells employing a space-limited inverse temperature crystallization (ITC) methodology. Remarkably, these cells, up to 400-fold thicker than current-generation perovskite polycrystalline films, maintain a high charge collection efficiency even without external bias. The crux of this achievement lies in the long electron diffusion length within these cells, estimated to be around 0.45 mm. This extended diffusion length ensures the conservation of high charge collection and power conversion efficiencies, even as the thickness of the cells increases. Fabricated cells at 110, 214, and 290 µm thickness manifested power conversion efficiencies (PCEs) of 20.0, 18.4, and 14.7% respectively. The single crystals demonstrated nearly optimal charge collection, even when their thickness exceeded 200 µm. Devices of thickness 108, 214, and 290 µm maintained 98.6, 94.3, and 80.4% of charge collection efficiency relative to their maximum theoretical short-circuit current value, respectively. Additionally, we have proposed an innovative, self-consistent technique for ascertaining the electron-diffusion length in perovskite single crystals under operational conditions. The computed electron-diffusion length approximated 446 µm, significantly surpassing previously reported values for this material. In conclusion, our findings underscore the feasibility of fabricating halide perovskite single-crystal solar cells of hundreds of micrometers in thickness while preserving high charge extraction efficiency and PCE. This advancement paves the way for developing perovskite-based optoelectronics necessitating thicker active layers, such as X-ray detectors and nuclear batteries.

Keywords: perovskite, solar cell, single crystal, diffusion length

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Authors: Marwa A. A. Ragab, Hadir M. Maher, Eman I. El-Kimary

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Co-administration of methotrexate (MTX) and aspirin (ASP) can cause a pharmacokinetic interaction and a subsequent increase in blood MTX concentrations which may increase the risk of MTX toxicity. Therefore, it is important to develop a sensitive, selective, accurate and precise method for their simultaneous determination in urine. A new hybrid chemometric method has been applied to the emission response data of the two drugs. Spectrofluorimetric method for determination of MTX through measurement of its acid-degradation product, 4-amino-4-deoxy-10-methylpteroic acid (4-AMP), was developed. Moreover, the acid-catalyzed degradation reaction enables the spectrofluorimetric determination of ASP through the formation of its active metabolite salicylic acid (SA). The proposed chemometric method deals with convolution of emission data using 8-points sin xi polynomials (discrete Fourier functions) after the derivative treatment of these emission data. The first and second derivative curves (D1 & D2) were obtained first then convolution of these curves was done to obtain first and second derivative under Fourier functions curves (D1/FF) and (D2/FF). This new application was used for the resolution of the overlapped emission bands of the degradation products of both drugs to allow their simultaneous indirect determination in human urine. Not only this chemometric approach was applied to the emission data but also the obtained data were subjected to non-parametric linear regression analysis (Theil’s method). The proposed method was fully validated according to the ICH guidelines and it yielded linearity ranges as follows: 0.05-0.75 and 0.5-2.5 µg mL-1 for MTX and ASP respectively. It was found that the non-parametric method was superior over the parametric one in the simultaneous determination of MTX and ASP after the chemometric treatment of the emission spectra of their degradation products. The work combines the advantages of derivative and convolution using discrete Fourier function together with the reliability and efficacy of the non-parametric analysis of data. The achieved sensitivity along with the low values of LOD (0.01 and 0.06 µg mL-1) and LOQ (0.04 and 0.2 µg mL-1) for MTX and ASP respectively, by the second derivative under Fourier functions (D2/FF) were promising and guarantee its application for monitoring the two drugs in patients’ urine samples.

Keywords: chemometrics, emission curves, derivative, convolution, Fourier transform, human urine, non-parametric regression, Theil’s method

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Authors: Kirsi Korkealehto

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The purpose of this research was to investigate how the peer evaluation concept was perceived by language teachers developing online language courses. The online language courses in question were developed in language teacher teams within a nationwide KiVAKO-project funded by the Finnish Ministry of Education and Culture. The participants of the project were 86 language teachers of 26 higher education institutions in Finland. The KiVAKO-project aims to strengthen the language capital at higher education institutions by building a nationwide online language course offering on a shared platform. All higher education students can study the courses regardless of their home institutions. The project covers the following languages: Chinese, Estonian, Finnish Sign Language, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish on the levels CEFR A1-C1. The courses were piloted in the autumn term of 2019, and an online peer evaluation session was organised for all project participating teachers in spring 2020. The peer evaluation utilised the quality criteria for online implementation, which was developed earlier within the eAMK-project. The eAMK-project was also funded by the Finnish Ministry of Education and Culture with the aim to improve higher education institution teachers’ digital and pedagogical competences. In the online peer evaluation session, the teachers were divided into Zoom breakout rooms, in each of which two pilot courses were presented by their teachers dialogically. The other language teachers provided feedback on the course on the basis of the quality criteria. Thereafter good practices and ideas were gathered to an online document. The breakout rooms were facilitated by one teacher who was instructed and provided a slide-set prior to the online session. After the online peer evaluation sessions, the language teachers were asked to respond to an online questionnaire for feedback. The questionnaire included three multiple-choice questions using the Likert-scale rating and two open-ended questions. The online questionnaire was answered after the sessions immediately, the questionnaire link and the QR-code to it was on the last slide of the session, and it was responded at the site. The data comprise online questionnaire responses of the peer evaluation session and the researcher’s observations during the sessions. The data were analysed with a qualitative content analysis method with the help of Atlas.ti programme, and the Likert scale answers provided results per se. The observations were used as complementary data to support the primary data. The findings indicate that the working in the breakout rooms was successful, and the workshops proceeded smoothly. The workshops were perceived as beneficial in terms of improving the piloted courses and developing the participants’ own work as teachers. Further, the language teachers stated that the collegial discussions and sharing the ideas were fruitful. The aspects to improve the workshops were to give more time for free discussions and the opportunity to familiarize oneself with the quality criteria and the presented language courses beforehand. The quality criteria were considered to provide a suitable frame for self- and peer evaluations.

Keywords: higher education, language learning, online learning, peer-evaluation

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Authors: J. Lino Alves, L. Lopes

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It is not new that industrial design projects are a result of cooperative work from different areas of knowledge. However, in the academic teaching of Industrial Design and Mechanical Engineering courses, it is not recurrent that those competences are mixed before the professional life arrives. This abstract intends to describe two semester experiences carried out by two professors - a mechanical engineer and an industrial designer - in the last two academic years, for which they created mixed teams of Industrial Design and Mechanical Engineering (UPorto University). The two experiences differ in several factors; the main one is related to the challenges of online education, a constraint that affected the second experience. In the first year, even before foreseeing the effects that the pandemic would reconfigure the education system, a partnership with the Education Service of Águas do Porto was established. The purpose of the exercise was the project development of a game that could be an interaction element oriented to potentiate a positive experience and as an educational contribution to the children. In the second year, already foreseeing that the teaching experience would be carried out online, it was decided to design an open briefing, which allowed the groups to choose among three themes: a hand scale game using additive manufacturing; a modular system for ventilated facade using a parametric design basis; or, a modular system for vertical gardens. In methodological terms, besides the weekly follow-up, with the simultaneous support of the two professors, a group self-evaluation was requested; and a form to be filled individually to evaluate other groups. One of the first conclusions is related to the briefing format. Industrial Design students seem comfortable working on an open briefing that allows them to draw the project on a conceptual basis created for that purpose; on the other hand, Mechanical Engineering students were uncomfortable and insecure in the initial phase due to the absence of concrete, closed "order." In other words, it is not recurrent for Mechanical Engineering students that the creative component is stimulated, seemingly leaving them reserved to the technical solution and execution, depriving them of the co-creation phase during the conceptual construction of the project's own brief. Another fact that was registered is related to the leadership positions in the groups, which alternated according to the state of development of the project: design students took the lead during the ideation/concept phase, while mechanical engineering ones took a greater lead during the intermediate development process, namely in the definition of constructive solutions, mass/volume calculations, manufacturing, and material resistance. Designers' competences were again more evident and assumed in the final phase, especially in communication skills, as well as in simulations in the context of use. However, at some moments, it was visible the capacity for quite balanced leadership between engineering and design, in a constant debate centered on the human factor of the project - evidenced in the final solution, in the compromise and balance between technical constraints, functionality, usability, and aesthetics.

Keywords: education, industrial design, mechanical engineering, teaching ethodologies

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Authors: Lilian Nantume Wampande

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Group-based strategies in the delivery of HIV care have opened up new avenues not only for meaningful participation for HIV positive people but also platforms for deconstruction and reconstruction of knowledge about living with the virus. Yet the contributions of such strategies among patients who live in high risk areas are still not explored. This case study research assessed the impact of HIV support networks on sexual health outcomes of HIV positive out-of-school adolescents residing in fishing islands of Kalangala in Uganda. The study population was out-of-school adolescents living with HIV and their sexual partners (n=269), members of their households (n=80) and their health service providers (n=15). Data were collected via structured interviews, observations and focus group discussions between August 2016 and March 2017. Data was then analyzed inductively to extract key themes related to the approaches and outcomes of the groups’ activities. The study findings indicate that support groups unite HIV positive adolescents in a bid for social renegotiation to achieve change but individual constraints surpass the groups’ intentions. Some adolescents for example reported increased fear which led to failure to cope, sexual violence, self-harm and denial of status as a result of the high expectations placed on them as members of the support groups. Further investigations around this phenomenon show that HIV networks play a monotonous role as information sources for HIV positive out-of-school adolescents which limit their creativity to seek information elsewhere. Results still indicate that HIV adolescent groups recognize the complexity of long-term treatment and stay in care leading to improved immunity for the majority yet; there is still scattered evidence about how effective they are among adolescents at different phases in the disease trajectory. Nevertheless, the primary focus of developing adolescent self-efficacy and coping skills significantly address a range of disclosure difficulties and supports autonomy. Moreover, the peer techniques utilized in addition to the almost homogeneous group characteristics accelerates positive confidence, hope and belongingness. Adolescent HIV-support groups therefore have the capacity to both improve and/or worsen sexual health outcomes for a young adolescent who is out-of-school. Communication interventions that seek to increase awareness about ‘self’ should therefore be emphasized more than just fostering collective action. Such interventions should be sensitive to context and gender. In addition, facilitative support supervision done by close and trusted health care providers, most preferably Village Health Teams (who are often community elected volunteers) would help to follow-up, mentor, encourage and advise this young adolescent in matters involving sexuality and health outcomes. HIV/AIDS prevention programs have extended their efforts beyond individual focus to those that foster collective action, but programs should rekindle interpersonal level strategies to address the complexity of individual behavior.

Keywords: adolescent, HIV, support groups, Uganda

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Authors: Jovina Concepcion Bachynski, Lenora Duhn, Idevania G. Costa, Pilar Camargo-Plazas

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Kidney failure is a life-limiting condition for which treatment, such as dialysis (hemodialysis and peritoneal dialysis), can exact a tremendously high physical and psychosocial symptom burden. Kidney failure can be severe enough to require a palliative approach to care. The term supportive care can be used in lieu of palliative care to avoid the misunderstanding that palliative care is synonymous with end-of-life or hospice care. Kidney supportive care, encompassing advance care planning, is an approach to care that improves the quality of life for people receiving dialysis through early identification and treatment of symptoms throughout the disease trajectory. Advanced care planning involves ongoing conversations about the values, goals, and preferences for future care between individuals and their healthcare teams. Kidney supportive care is underutilized and often initiated late in this population. There is evidence to indicate nurses are not providing the necessary elements of supportive kidney care. Dialysis nurses’ delay or lack of engagement in supportive care until close to the end of life may result in people dying without receiving optimal palliative care services. Using Charmaz’s constructivist grounded theory, the purpose of this doctoral study is to develop a substantive theory that explains the process of engagement in supportive care by nurses working in dialysis settings in Canada. Through initial purposeful and subsequent theoretical sampling, 23 nurses with current or recent work experience in outpatient hemodialysis, home hemodialysis, and peritoneal dialysis settings drawn from across Canada were recruited to participate in two intensive interviews using the Zoom© teleconferencing platform. Concurrent data collection and data analysis, constant comparative analysis of initial and focused codes until the attainment of theoretical saturation, and memo-writing, as well as researcher reflexivity, have been undertaken to aid the emergence of concepts, categories, and, ultimately, the constructed theory. At the time of abstract submission, data analysis is currently at the second level of coding (i.e., focused coding stage) of the research study. Preliminary categories include: (a) focusing on biomedical care; (b) multi-dimensional challenges to having the conversation; (c) connecting and setting boundaries with patients; (d) difficulty articulating kidney-supportive care; and (e) unwittingly practising kidney-supportive care. For the conference, the resulting theory will be presented. Nurses working in dialysis are well-positioned to ensure the delivery of quality kidney-supportive care. This study will help to determine the process and the factors enabling and impeding nurse engagement in supportive care in dialysis to effect change for normalizing advance care planning conversations in the clinical setting. This improved practice will have substantive beneficial implications for the many individuals living with kidney failure and their supporting loved ones.

Keywords: dialysis, kidney failure, nursing, supportive care

Procedia PDF Downloads 90