Search results for: language learning strategies

Authors: Jian Li

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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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Authors: Kambiz Rasoulkhani, Jeanne Cole, Sybil Sharvelle, Ali Mostafavi

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Dual water distribution systems have been proposed as solutions to enhance the sustainability and resilience of urban water systems by improving performance and decreasing energy consumption. The objective of this study was to evaluate the long-term resilience and robustness of dual water distribution systems versus singular water distribution systems under various stressors such as demand fluctuation, aging infrastructure, and funding constraints. To this end, the long-term dynamics of these infrastructure systems was captured using a simulation model that integrates institutional agency decision-making processes with physical infrastructure degradation to evaluate the long-term transformation of water infrastructure. A set of model parameters that varies for dual and singular distribution infrastructure based on the system attributes, such as pipes length and material, energy intensity, water demand, water price, average pressure and flow rate, as well as operational expenditures, were considered and input in the simulation model. Accordingly, the model was used to simulate various scenarios of demand changes, funding levels, water price growth, and renewal strategies. The long-term resilience and robustness of each distribution infrastructure were evaluated based on various performance measures including network average condition, break frequency, network leakage, and energy use. An ecologically-based resilience approach was used to examine regime shifts and tipping points in the long-term performance of the systems under different stressors. Also, Classification and Regression Tree analysis was adopted to assess the robustness of each system under various scenarios. Using data from the City of Fort Collins, the long-term resilience and robustness of the dual and singular water distribution systems were evaluated over a 100-year analysis horizon for various scenarios. The results of the analysis enabled: (i) comparison between dual and singular water distribution systems in terms of long-term performance, resilience, and robustness; (ii) identification of renewal strategies and decision factors that enhance the long-term resiliency and robustness of dual and singular water distribution systems under different stressors.

Keywords: complex systems, dual water distribution systems, long-term resilience performance, multi-agent modeling, sustainable and resilient water systems

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Authors: Stephen Wagman

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This paper identifies three common structures in English sentences that are important for understanding academic texts, regardless of the characteristics or background of the readers or whether they are reading English as a second or a foreign language. Adapting a model from the Humanities, the explication of texts used in literary studies, the paper analyses sample sentences to reveal structures that enable the reader not only to decide which words are necessary for understanding the main ideas but to make the decision without knowing the meaning of the words. By their very syntax noun structures point to the key word for understanding them. As a rule, the key noun is followed by easily identifiable prepositions, relative pronouns, or verbs and preceded by single adjectives. With few exceptions, the modifiers are unnecessary for understanding the idea of the sentence. In addition, sentences are often structured by lists in which the items frequently consist of parallel groups of words. The principle of a list is that all the items are similar in meaning and it is not necessary to understand all of the items to understand the point of the list. This principle is especially important when the items are long or there is more than one list in the same sentence. The similarity in meaning of these items enables readers to reduce sentences that are hard to grasp to an understandable core without excessive use of a dictionary. Finally, the idea of subordination and the identification of the subordinate parts of sentences through connecting words makes it possible for readers to focus on main ideas without having to sift through the less important and more numerous secondary structures. Sometimes a main idea requires a subordinate one to complete its meaning, but usually, subordinate ideas are unnecessary for understanding the main point of the sentence and its part in the development of the argument from sentence to sentence. Moreover, the connecting words themselves indicate the functions of the subordinate structures. These most frequently show similarity and difference or reasons and results. Recognition of all of these structures can not only enable students to read more efficiently but to focus their attention on the development of the argument and this rather than a multitude of unknown vocabulary items, the repetition in lists, or the subordination in sentences are the one necessary element for comprehension of academic articles.

Keywords: development of the argument, lists, noun structures, subordination

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Authors: Patsawut Sukserm

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Oracy proficiency, encompassing both speaking and listening skills, is vital for EFL learners, yet Thai university students often face significant challenges in developing these abilities. This study aims to identify and analyze the barriers that hinder oracy proficiency in EFL learners. To achieve this, a questionnaire was developed based on a comprehensive review of the literature and administered to a large cohort of Thai EFL students. The data were subjected to exploratory factor analysis (EFA) to validate the questionnaire and uncover the underlying factors influencing learners’ performance. The results revealed that the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was 0.912, and Bartlett’s test of sphericity was significant at 2345.423 (p < 0.05), confirming the suitability for factor analysis. There are five main barriers in oracy proficiency, namely Listening and Comprehension Obstacles (LCO), Accent and Speech Understanding (ASU), Speaking Anxiety and Confidence Issues (SACI), Fluency and Expression Issues (FEI), and Grammar and Conversational Understanding (GCU), with eigenvalues ranging from 1.066 to 12.990, explaining 60.305 % of the variance of the 32 variables. These findings highlight the complexity of the challenges faced by Thai EFL learners and emphasize the need for diverse and authentic listening experiences, a supportive classroom environment, or balanced grammar instruction. The findings of the study suggest that educators, curriculum developers, and policy makers should implement evidence-based strategies to address these barriers in order to improve Thai EFL learners’ oral proficiency and enhance their overall academic and professional success. Also, this study will discuss these findings in depth, offering evidence-based strategies for addressing these barriers. Recommendations include integrating diverse and authentic listening experiences, fostering a supportive classroom environment, and providing targeted instruction in both speaking fluency and grammar. The study’s implications extend to educators, curriculum developers, and policymakers, offering practical solutions to enhance learners’ oracy proficiency and support their academic and professional development.

Keywords: exploratory factor analysis, barriers, oracy proficiency, EFL learners

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Authors: Shakila N. Senarath, Dinesh Asanka, Janaka Wijayanayake

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The necessity of cosmetic products is arising to fulfill consumer needs of personality appearance and hygiene. A cosmetic product consists of various chemical ingredients which may help to keep the skin healthy or may lead to damages. Every chemical ingredient in a cosmetic product does not perform on every human. The most appropriate way to select a healthy cosmetic product is to identify the texture of the body first and select the most suitable product with safe ingredients. Therefore, the selection process of cosmetic products is complicated. Consumer surveys have shown most of the time, the selection process of cosmetic products is done in an improper way by consumers. From this study, a content-based system is suggested that recommends cosmetic products for the human factors. To such an extent, the skin type, gender and price range will be considered as human factors. The proposed system will be implemented by using Machine Learning. Consumer skin type, gender and price range will be taken as inputs to the system. The skin type of consumer will be derived by using the Baumann Skin Type Questionnaire, which is a value-based approach that includes several numbers of questions to derive the user’s skin type to one of the 16 skin types according to the Bauman Skin Type indicator (BSTI). Two datasets are collected for further research proceedings. The user data set was collected using a questionnaire given to the public. Those are the user dataset and the cosmetic dataset. Product details are included in the cosmetic dataset, which belongs to 5 different kinds of product categories (Moisturizer, Cleanser, Sun protector, Face Mask, Eye Cream). An alternate approach of TF-IDF (Term Frequency – Inverse Document Frequency) is applied to vectorize cosmetic ingredients in the generic cosmetic products dataset and user-preferred dataset. Using the IF-IPF vectors, each user-preferred products dataset and generic cosmetic products dataset can be represented as sparse vectors. The similarity between each user-preferred product and generic cosmetic product will be calculated using the cosine similarity method. For the recommendation process, a similarity matrix can be used. Higher the similarity, higher the match for consumer. Sorting a user column from similarity matrix in a descending order, the recommended products can be retrieved in ascending order. Even though results return a list of similar products, and since the user information has been gathered, such as gender and the price ranges for product purchasing, further optimization can be done by considering and giving weights for those parameters once after a set of recommended products for a user has been retrieved.

Keywords: content-based filtering, cosmetics, machine learning, recommendation system

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Authors: Maryam Ramezankhani

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The present research tries to study the possibility of formalizing the sense relation of hyponymy. It applied mathematical tools and also uses mathematical logic concepts especially those from propositional logic. In order to do so, firstly, it goes over the definitions of hyponymy presented in linguistic dictionaries and semantic textbooks. Then, it introduces a formal translation of the sense relation of hyponymy. Lastly, it examines the efficiency of the suggested formula by some examples of natural language.

Keywords: sense relations, hyponymy, formalizing, words’ sense relation, formalizing sense relations

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Authors: Surichai Butcha, Dararat Khampusaen

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As the Internet is recognized as a high potential and powerful educational tool to access sources of knowledge, plagiarism is an increasing unethical issue found in students’ writing. This paper is deriving from the 1st phase of an on-going study investigating the effects of the supplementary on citing sources on undergraduate students’ writing. The 40 participants were divided into 1 experimental group and 1 control group. Both groups were administered with a questionnaire on knowledge and an interview on attitude related to using sources in writing. Only the experimental group undertook the 4 lessons focusing on using outside sources and citing the original work (quoting, synthesizing, summarizing and paraphrasing) were delivered to them via e-learning tools throughout a semester. Participants were required to produce 4 writing tasks after each lesson. The results were concerned with types and factors on using outside sources in writing of Thai undergraduate EFL students from the survey. The interview results supported and clarified the survey result. In addition, the writing rubrics confirmed the types of plagiarism frequently occurred in students’ writing. The results revealed the types and factors on plagiarism including their perceptions on using the outside sources in their writing from the interview. The discussion shed the lights on cultural dimensions of plagiarism in student writing, roles of teachers, library, and university policy on the rate of plagiarism. Also, the findings promoted the awareness on ethics in writing and prevented the rate of potential unintentional plagiarism. Additionally, the results of this phase of study could lead to the appropriate contents to be considered for inclusion in the supplementary on using sources for writing for future research.

Keywords: citing source, EFL writing, e-learning, Internet, plagiarism

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Authors: Nathaniel Carpenter

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Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

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Authors: Molly Gerrish

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This work explores the physical, emotional, social, and cognitive risks and benefits related to nature-based teaching and highlights the importance of promoting a sustainable workforce within early childhood programs. Assessing and managing risks can help programs reimagine their approach to teaching, learning, recruitment, family connectivity, and staff motivation. The importance of staff sustainability and motivation/engagement related to social justice and the environment will be discussed. We will explore ways to manage fears and limitations faced by early childhood programs regarding nature experiences and risky play in a variety of locations using a lens of place-based learning. We will also examine the alignment of sustainability and social-emotional development, mental health supports, social awareness, and risk assessment. The work will discuss the varied perceptions of risk in diverse areas and the impact on the early childhood workforce. Motivational theory and compassion resiliency are hallmarks of both recruiting and retaining high-quality early childhood educators; the work will discuss how to balance programmatic constraints and healthy motivation for students and teachers while empowering individuals to advocate for their mental health and well-being. Finally, the work will highlight the positive impact of nature-based teaching practices and the overall benefit to young children and their educators.

Keywords: child’s rights, inclusion, nature-based education, risk assessment

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Authors: Gözde Arzu Sarıcan

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Contemporary urbanization processes and spatial transformations are intensely debated across various fields of social sciences. One prominent concept in these discussions is "common spaces." Common spaces offer a critical theoretical framework, particularly for addressing the social and economic inequalities brought about by urbanization. This study examines the processes of commoning and their impacts through the lens of squatter neighborhoods in Turkey, emphasizing the importance of affordable housing. It focuses on the role and significance of these neighborhoods in the formation of common spaces, analyzing the collective actions and resistance strategies of residents. This process, which began with the construction of shelters to meet the shelter needs of low-income households migrating from rural to urban areas, has turned into low-quality squatter settlements over time. For low-income households lacking the economic power to rent or buy homes in the city, these areas provided an affordable housing solution. Squatter neighborhoods reflect the efforts of local communities to protect and develop their communal living spaces through collective actions and resistance strategies. This collective creation process involves the appropriation of occupied land as a common resource through the rules established by the commons. Organized occupations subdivide these lands, shaped through collective creation processes. For the squatter communities striving for economic and social adaptation, these areas serve as buffer zones for urban integration. In squatter neighborhoods, bonds of friendship, kinship, and compatriotism are strong, playing a significant role in the creation and dissemination of collective knowledge. Squatter areas can be described as common spaces that emerge out of necessity for low-income and marginalized groups. The design and construction of housing in squatter neighborhoods are shaped by the collective participation and skills of the residents. Streets are formed through collective decision-making and labor. Over time, the demands for housing are communicated to local authorities, enhancing the potential for commoning. Common spaces are shaped by collective needs and demands, appropriated, and transformed into potential new spaces. Common spaces are continually redefined and recreated. In this context, affordable housing becomes an essential aspect of these common spaces, providing a foundation for social and economic stability. This study evaluates the processes of commoning and their effects through the lens of squatter neighborhoods in Turkey. Communities living in squatter neighborhoods have managed to create and protect communal living spaces, especially in situations where official authorities have been inadequate. Common spaces are built on values such as solidarity, cooperation, and collective resistance. In urban planning and policy development processes, it is crucial to consider the concept of common spaces. Policies that support the collective efforts and resistance strategies of communities can contribute to more just and sustainable living conditions in urban areas. In this context, the concept of common spaces is considered an important tool in the fight against urban inequalities and in the expression and defense mechanisms of communities. By emphasizing the importance of affordable housing within these spaces, this study highlights the critical role of common spaces in addressing urban social and economic challenges.

Keywords: affordable housing, common space, squating process, turkey

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Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

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5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

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Authors: Robert Jedrys, Zdzislaw Kobos, Justyna Skrzynska, Zbigniew Wochynski

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Professions connected to aviation require an assessment of the suitability of health, psychological and psychomotor skills and overall physical fitness of the organism, who applies. Assessment of the physical condition is conducted by the committees consisting of aero-medical specialists in clinical medicine and aviation. In addition, psychological predispositions should be evaluated by specialized psychologists familiar with the specifics of the tasks and requirements for the various positions in aviation. Both, physical abilities and general physical fitness of candidates for aviation shall be assessed during the selection exams, which also test the ability to deal with stress what is very important in aviation. Hence, the mentioned exams in physical education not only help to judge on the ranking in candidates in terms of their efficiency and performance, but also allows to evaluate the functioning under stress measured using psychological tests. Moreover, before-test stress is a predictors of successfulness in the next stages of education and practical training in the aviation. The aim of the study was to evaluate the influence of temperamental traits on strategies used for coping with stress during selection exams in physical education, deciding on admission to aviation school. The study involved 30 candidates for fighter pilot training in aviation school . To evaluate the temperament 'The Formal Characteristics of Behavior-Temperament Inventory' (FCB-TI) by B. Zawadzki and J.Strelau was used. To determine the pattern of coping with stress 'The Coping Inventory for Stressful Situations' (CISS) to N. S. Endler and J. D. A. Parker were engaged. Study of temperament and styles of coping with stress was conducted directly before the exam selection of physical education. The results were analyzed with 'Statistica 9' program. The studies showed that:-There is a negative correlation between such a temperament feature as 'perseverance' and preferred style of coping with stress concentrated on the task (r = -0.590; p < 0.004); -There is a positive correlation between such a feature of temperament as 'emotional reactivity,' and preference to deal with a stressful situation with ‘style centered on emotions’ (r = 0.520; p <0.011); -There is a negative correlation between such a feature of temperament as ‘strength’ and ‘style of coping with stress concentrated on emotions’ (r = -0.580; p < 0.004). Studies indicate that temperament traits determine the perception of stress and preferred coping styles used during the selection, as during the exams in physical education.

Keywords: aviation, physical education, stress, temperamental traits

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Authors: Jarrod Sio Jyh Lih

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This paper discusses the factors contributing to student achievement in literacy and numeracy in primary schools within Sibu division. The study involved 694 level 1 primary schoolteachers. Using descriptive statistics, the study observed high levels of practice for teacher efficacy, instructional leadership and professional learning communities (PLCs). The differences between gender, teaching experience and academic qualification were analyzed using the t-test and one-way analysis of variance (ANOVA). The study reported significant differences in respondent perceptions based on teaching experience vis-à-vis teacher efficacy. Here, the post hoc Tukey test revealed that efficaciousness grows with experience. A correlation test observed positive and significant correlations between all independent variables. Binary logistic regression was applied to predict the independent variables’ influence on student achievement. The findings revealed that a dimension of instructional leadership – ‘monitoring student progress’ - emerged as the best predictor of student achievement for literacy and numeracy. The result indicated the students were more than 4 times more likely to achieve the national key performance index for both literacy and numeracy when student progress was monitored. In conclusion, ‘monitoring student progress’ had a positive influence on students’ achievement for literacy and numeracy, hence making it a possible course of action for school heads. However, more comprehensive studies are needed to ascertain its consistency within the context of Malaysia.

Keywords: efficacy, instructional, literacy, numeracy

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Authors: Vandana Mishra, Niladri Sekhar Dash, Jayshree Charkraborty

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This present paper focuses on the application of corpus linguistics techniques for critical discourse analysis (CDA) of Hindi newspapers. While Corpus linguistics is the study of language as expressed in corpora (samples) of 'real world' text, CDA is an interdisciplinary approach to the study of discourse that views language as a form of social practice. CDA has mainly been studied from a qualitative perspective. However, we can say that recent studies have begun combining corpus linguistics with CDA in analyzing large volumes of text for the study of existing power relations in society. The corpus under our study is also of a sizable amount (1 million words of Hindi newspaper texts) and its analysis requires an alternative analytical procedure. So, we have combined both the quantitative approach i.e. the use of corpus techniques with CDA’s traditional qualitative analysis. In this context, we have focused on the Keyword Analysis Sorting Concordance Lines of the selected Keywords and calculating collocates of the keywords. We have made use of the Wordsmith Tool for all these analysis. The analysis starts with identifying the keywords in the political news corpus when compared with the main news corpus. The keywords are extracted from the corpus based on their keyness calculated through statistical tests like chi-squared test and log-likelihood test on the frequent words of the corpus. Some of the top occurring keywords are मोदी (Modi), भाजपा (BJP), कांग्रेस (Congress), सरकार (Government) and पार्टी (Political party). This is followed by the concordance analysis of these keywords which generates thousands of lines but we have to select few lines and examine them based on our objective. We have also calculated the collocates of the keywords based on their Mutual Information (MI) score. Both concordance and collocation help to identify lexical patterns in the political texts. Finally, all these quantitative results derived from the corpus techniques will be subjectively interpreted in accordance to the CDA’s theory to examine the ways in which political news discourse produces social and political inequality, power abuse or domination.

Keywords: critical discourse analysis, corpus linguistics, Hindi newspapers, power relations

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Authors: Shanshan Zhu, Mohammad Nasim

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Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

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Authors: Zehra Gencel Efe, Fatma Susam Ozsayın, Satı Tas

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Background and Aim: It is not possible to teach all the knowledge related to operating room nursing in the nursing education process. Certified courses are organized by the Ministry of Health to compensate the lack of postgraduate training and the theoretical and practical training needs of working nurses. In this study; It is aimed to investigate the participants’ opinions and recommendations attending the certified course of operating room nursing that organized in İKCU AtaturkTraining and Research Hospital. Method: Two operating room nursing courses were organized in 2016. The 1st Operating Room Nursing Certified Course Program was organized between March 07, 2016 and April 6, 2016and the 2nd Operating Room Nursing Certified Course Program was organized between 07 November 2016 - 06 December 2016 at the İKCU Ataturk Training and Research Hospital. The first program was accepted for 29 participants, the second program was accepted for 30 participants. In the collection of the data, the 'Operating Room Nursing Certified Training Program Evaluation Form', 'Operating Room Nursing Certified Training Program Theoretical Training Evaluation Form' were used. Three point Likert-type scale is used for responses in the 'Operating Room Nursing Certified Training Program Evaluation Form’ (1=verygood, 2=good, 3=poor). Data is collected in five areas related to training program, operation room practice, communication, responsibility, experiences of learning. Four point Likert-type scale is used for responses in the 'Operating Room Nursing Certified Training Program Theoretical Training Evaluation Form' (1=verysatisfied, 2=quitesatisfied, 3=satisfied, 4=dissatisfied). Data is collected in two areas include presentation and content. Data were analyzed with SPSS 16 program. Findings and Conclusion: It was found that 93,22% of participants were female in addition, 62,7% had bachelor degree. It was seen that 33,87% of the work group had 1-5 years of experience in their field. It was found that; 88% of trainees participating in the first group to the operating room nursing-certified course program stated the training program was very good, 12% of them stated the training program was good. Nobody was signed the ‘poor’ choice. 81% of the trainees who participated in the 2nd group to the operating room nursing-certified course program stated the training program was very good, 19% of them stated the training program was good. Nobody was signed the ‘poor’ choice. It was found that there was no meaningful difference between the achievement ratios of the trainees and the learning status of the trainees when compared with the t test in the groups with success level of the operating room nursing certified course program according to the learning status of the participants (p ˃ 0,05). The trainees noted that the course was satisfied with theoretical and practical steps but the support services (lunch, coffee breaks etc.) were in adequate.

Keywords: certified courses, nursing certified courses, operating room nursing, training program

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Authors: Poonam Goswami

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Background: The diagnosis of a serious illness like cancer can have an impact on a patient’s emotional well-being and may result in psychological symptoms, anxiety, depression, and loss of control. Advance care planning discussions ensure patients’ values and goals of care, including patients’ freedom to choose their place of death, are respected. Unfortunately, these discussions are often delayed and are not initiated early in patients’ cancer trajectory. As a result, patients’ wishes often remains unknown until the last phase of their life. Evidence suggests that many patients inappropriately receive aggressive treatment near the end of life, which does lead to higher resource utilization, decreased quality of life, and increased cost. Additionally, the novel coronavirus disease 2019 (COVID-19) pandemic challenged the health care systems worldwide and raised important ethical issues, especially regarding the potential need for rationing health care in the context of scarce resources and crisis capacity. The importance of goal concordant care is now even substantially important and is heightened in the context of this pandemic. Problem: Although there is growing evidence on the effects of the ACP on the completion of advanced directives, improved patient and family concordance for preferences for medical care, and receipt of care, there is still a lack of standardized ACP conversation strategies for patients with cancer. Methods: The Key concepts of ACP include (1) assessing patient and family readiness, (2) identifying a surrogate decision maker ( medical power of attorney), (3) exploring patient and family understanding of the disease and treatment options,(4) discussing the values and goals of care, and options for end-of-life care, (5) documenting patient preferences in the medical record, and (6) revisiting the discussions at every change in the treatment plan and /or change in clinical status, including at every hospitalization. Conclusion/Implication for practice: Advance Care Planning (ACP) and end-of-life (EOL) discussions are important for patients, families, and health care providers. Adopting the verbal and nonverbal communication strategies can help overcome the barriers to effective communication on these difficult discussions. ACP with goals of care discussions should not be delayed until the patient is hospitalized.

Keywords: advance care planning, end of life, cancer, global, pandemic

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Authors: Camille Deprez

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This paper proposes to present research findings of an ongoing Hong Kong government-funded project on ‘The Documentary Film in India (1948-1975)’ (GRF 1240314), for which an extensive research fieldwork has been carried out in various archives in India. This project investigates the role and significance of the Indian documentary film sector from the inauguration of the state-sponsored Films Division one year after independence in 1948 until the declaration of a ‘State of Emergency’ in 1975. The documentary film production of this first period of national independence was characterised by increasing formal experimentation and analytical social and political enquiry, and by a complex, mixed structure of state-sponsored monopoly and free-market operation. However, that production remains significantly under-researched. What were the main production, distribution and exhibition strategies over this period? What were the recurrent themes and stylistic features of the films produced? In the new context of national independence (in which the State considered film as means of mass persuasion), consolidation of the commercial film, and the emergence of television and art cinema, what role did official, professional and creative factors play in the development of the documentary film sector? What were the impact of such films and the challenges faced by the documentary film in India? Based upon the crossed-analysis of primary written research documents, interviews and relevant films, this study interweaves empirical study of the sector's financing, production, distribution and exhibition strategies, as well as the films' content and form, with the larger historical context of India over the period from 1948 to 1975. Whilst most of the films made within the sector explored social issues, they were rarely able to do so from an overtly critical perspective. However, this paper proposes to analyse the contribution of important filmmakers and producers, including Ezra Mir, Paul Zils, Jean Bhownagary, S. Sukhdev, S. N. S. Sastri, and P. Pati, to the development of the Indian documentary film sector and style within and outside the remits of Films Division. It will more specifically assess the extent to which they criticised the State, showed the inequalities in Indian society and explored film form.

Keywords: documentary film, film archives, film history, India

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

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Authors: Guillaume P. Fernandez

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Individual language use is a matter of choice in particular interactions. The paper proposes a conceptual and theoretical framework with methodological consideration to develop how language produced in dyadic relations is to be considered and situated in the larger social configuration the interaction is embedded within. An integrated and comprehensive view is taken: social interactions are expected to be ruled by a normative context, defined by the chain of interdependences that structures the personal network. In this approach, the determinants of discursive practices are not only constrained by the moment of production and isolated from broader influences. Instead, the position the individual and the dyad have in the personal network influences the discursive practices in a twofold manner: on the one hand, the network limits the access to linguistic resources available within it, and, on the other hand, the structure of the network influences the agency of the individual, by the social control inherent to particular network characteristics. Concretely, we investigate how and to what extent consistent ego is from one interaction to another in his or her use of adverbs. To do so, social network analysis (SNA) methods are mobilized. Participants (N=130) are college students recruited in the french speaking part of Switzerland. The personal network of significant ones of each individual is created using name generators and edge interpreters, with a focus on social support and conflict. For the linguistic parts, respondents were asked to record themselves with five of their close relations. From the recordings, we computed an average similarity score based on the adverb used across interactions. In terms of analyses, two are envisaged: First, OLS regressions including network-level measures, such as density and reciprocity, and individual-level measures, such as centralities, are performed to understand the tenets of linguistic similarity from one interaction to another. The second analysis considers each social tie as nested within ego networks. Multilevel models are performed to investigate how the different types of ties may influence the likelihood to use adverbs, by controlling structural properties of the personal network. Primary results suggest that the more cohesive the network, the less likely is the individual to change his or her manner of speaking, and social support increases the use of adverbs in interactions. While promising results emerge, further research should consider a longitudinal approach to able the claim of causality.

Keywords: personal network, adverbs, interactions, social influence

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Authors: Arvind Aggarwal

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We have developed a comprehensive global healthcare delivery System based on information technology. It has medical consultation system where a virtual consultant can give medical consultation to the patients and Doctors at the digital medical centre after reviewing the patient’s EMR file consisting of patient’s history, investigations in the voice, images and data format. The system has the surgical operation system too, where a remote robotic consultant can conduct surgery at the robotic surgical centre. The instant speech and text translation is incorporated in the software where the patient’s speech and text (language) can be translated into the consultant’s language and vice versa. A consultant of any specialty (surgeon or Physician) based in any country can provide instant health care consultation, to any patient in any country without loss of time. Robotic surgeons based in any country in a tertiary care hospital can perform remote robotic surgery, through patient friendly telemedicine and tele-surgical centres. The patient EMR, financial data and data of all the consultants and robotic surgeons shall be stored in cloud. It is a complete comprehensive business model with healthcare medical and surgical delivery system. The whole system is self-financing and can be implemented in any country. The entire system uses paperless, filmless techniques. This eliminates the use of all consumables thereby reduces substantial cost which is incurred by consumables. The consultants receive virtual patients, in the form of EMR, thus the consultant saves time and expense to travel to the hospital to see the patients. The consultant gets electronic file ready for reporting & diagnosis. Hence time spent on the physical examination of the patient is saved, the consultant can, therefore, spend quality time in studying the EMR/virtual patient and give his instant advice. The time consumed per patient is reduced and therefore can see more number of patients, the cost of the consultation per patients is therefore reduced. The additional productivity of the consultants can be channelized to serve rural patients devoid of doctors.

Keywords: e-health, telemedicine, telecare, IT-based healthcare

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Authors: Goudjil kamel, Boukhatem Ghania, Jlailia Djihene

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This paper delves into the development of a sophisticated desktop application designed to calculate soil bearing capacity and predict limit pressure. Drawing from an extensive review of existing methodologies, the study meticulously examines various approaches employed in soil bearing capacity calculations, elucidating their theoretical foundations and practical applications. Furthermore, the study explores the burgeoning intersection of artificial intelligence (AI) and geotechnical engineering, underscoring the transformative potential of AI- driven solutions in enhancing predictive accuracy and efficiency.Central to the research is the utilization of cutting-edge machine learning techniques, including Artificial Neural Networks (ANN), XGBoost, and Random Forest, for predictive modeling. Through comprehensive experimentation and rigorous analysis, the efficacy and performance of each method are rigorously evaluated, with XGBoost emerging as the preeminent algorithm, showcasing superior predictive capabilities compared to its counterparts. The study culminates in a nuanced understanding of the intricate dynamics at play in geotechnical analysis, offering valuable insights into optimizing soil bearing capacity calculations and limit pressure predictions. By harnessing the power of advanced computational techniques and AI-driven algorithms, the paper presents a paradigm shift in the realm of geotechnical engineering, promising enhanced precision and reliability in civil engineering projects.

Keywords: limit pressure of soil, xgboost, random forest, bearing capacity

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Authors: Zikra Faiz, Nisar Abid, Muhammad Waqas

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This study aim to examine the challenges faced by teachers during teaching to those students who are intellectually disable, suffering from autism spectrum disorder, learning disability, and ADHD at the primary level. The descriptive research design of quantitative approach was adopted to conduct this study; a cross-sectional survey method was used to collect data. The sample was comprised of 258 (43 male and 215 female) teachers who teach at special education institutes of Lahore district selected through proportionate stratified random sampling technique. Self-developed questionnaire was used which was comprised of 22 closed-ended items. Collected data were analyzed through descriptive and inferential statistical techniques by using Statistical Package for Social Sciences (SPSS) version 21. Results show that teachers faced problems during group activities, to handle bad behavior and different disabilities of students. It is concluded that there was a significant difference between male and female teachers perceptions about challenges faced during teaching with developmental disable students. Furthermore, there was a significant difference exist in the perceptions of teachers regarding challenges faced during teaching to students with developmental disabilities in term of teachers’ age and area of specialization. It is recommended that developmentally disable student require extra attention so that, teacher should trained through pre-service and in-service training to teach developmentally disabled students.

Keywords: intellectual disability, autism spectrum disorder, ADHD, learning disability

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Authors: Hsiao Hsun Yuan

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Internal marketing was proposed in 1970s. The theory of the concept has continually changed over the past forty years. This study discussed the following themes: the definition and implication of internal marketing, the progress of its development, and the evolution of its theoretical model. Moreover, the study systematically organized the strategies of the internal marketing theory adopted on enterprise and how they were put into practice. It also compared the empirical studies focusing on how the existent theories influenced the important variables of internal marketing. The results of this study are expected to serve as references for future exploration of the boundary and studies aiming at how internal marketing is applied to different types of enterprises.

Keywords: corporate responsibility, employee organizational performance, internal marketing, internal customer

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Authors: A. F. G. Van Woezik, L. M. A. Braakman-Jansen, O. A. Kulyk, J. E. W. C. Van Gemert-Pijnen

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Background: Zoonoses pose a serious threat to public health and economies worldwide, especially as antimicrobial resistance grows and newly emerging zoonoses can cause unpredictable outbreaks. In order to prevent and control emerging and re-emerging zoonoses, collaboration between veterinary, human health and public health domains is essential. In reality however, there is a lack of cooperation between these three disciplines and uncertainties exist about their tasks and responsibilities. The objective of this ongoing research project (ZonMw funded, 2014-2018) is to develop an online education and communication One Health platform, “eZoon”, for the general public and professionals working in veterinary, human health and public health domains to support the risk communication of non-alimentary zoonoses in the Netherlands. The main focus is on education and communication in times of outbreak as well as in daily non-outbreak situations. Methods: A participatory development approach was used in which stakeholders from veterinary, human health and public health domains participated. Key stakeholders were identified using business modeling techniques previously used for the design and implementation of antibiotic stewardship interventions and consisted of a literature scan, expert recommendations, and snowball sampling. We used a stakeholder salience approach to rank stakeholders according to their power, legitimacy, and urgency. Semi-structured interviews were conducted with stakeholders (N=20) from all three disciplines to identify current problems in risk communication and stakeholder values for the One Health platform. Interviews were transcribed verbatim and coded inductively by two researchers. Results: The following key values were identified (but were not limited to): (a) need for improved awareness of veterinary and human health of each other’s fields, (b) information exchange between veterinary and human health, in particularly at a regional level; (c) legal regulations need to match with daily practice; (d) professionals and general public need to be addressed separately using tailored language and information; (e) information needs to be of value to professionals (relevant, important, accurate, and have financial or other important consequences if ignored) in order to be picked up; and (f) need for accurate information from trustworthy, centrally organised sources to inform the general public. Conclusion: By applying a participatory development approach, we gained insights from multiple perspectives into the main problems of current risk communication strategies in the Netherlands and stakeholder values. Next, we will continue the iterative development of the One Health platform by presenting key values to stakeholders for validation and ranking, which will guide further development. We will develop a communication platform with a serious game in which professionals at the regional level will be trained in shared decision making in time-critical outbreak situations, a smart Question & Answer (Q&A) system for the general public tailored towards different user profiles, and social media to inform the general public adequately during outbreaks.

Keywords: ehealth, one health, risk communication, stakeholder, zoonosis

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Authors: Felix Lankester, Alicia Davis, Safari Kinung'hi, Catherine Bunga, Shayo Alkara, Imam Mzimbiri, Jonathan Yoder, Sarah Cleaveland, Guy H. Palmer

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Achieving the London Declaration goal of a 90% reduction in neglected tropical diseases (NTDs) by 2030 requires cost-effective strategies that attain high and comprehensive coverage. The first objective of this trial was to assess the impact on cost and coverage of employing a novel integrative One Health approach linking two NTD control programs: mass drug administration (MDA) for soil-transmitted helminths in humans (STH) and mass dog rabies vaccination (MDRV). The second objective was to compare the coverage achieved by the MDA, a community-wide deworming intervention, with that of the existing national primary school-based deworming program (NSDP), with particular focus on the proportion of primary school-age children reached and their school enrolment status. Our approach was unconventional because, in line with the One Health approach to disease control, it coupled the responsibilities and resources of the Ministries responsible for human and animal health into one program with the shared aim of preventing multiple NTDs. The trial was carried out in hard-to-reach pastoral communities comprising 24 villages of the Ngorongoro District, Tanzania, randomly allocated to either Arm A (MDA and MDRV), Arm B (MDA only) or Arm C (MDRV only). Objective one: The percentage of people in each target village that received treatment through MDA in Arms A and B was 63% and 65%, respectively (χ2 = 1, p = 0.32). The percentage of dogs vaccinated in Arm A and C was 70% and 81%, respectively (χ2 =9, p = 0.003). It took 33% less time for a single person and a dog to attend the integrated delivery than two separate events. Cost per dose (including delivery) was lower under the integrated strategy, with delivery of deworming and rabies vaccination reduced by $0.13 (54%) and $0.85 (19%) per dose, respectively. Despite a slight reduction in the proportion of village dogs vaccinated in the integrated event, both the integrated and non-integrated strategies achieved the target threshold of 70% required to eliminate rabies. Objective two: The percentages of primary school age children enrolled in school that was reached by this trial (73%) and the existing NSDP (80%) were not significantly different (F = 0.9, p = 0.36). However, of the primary school age children treated in this trial, 46% were not enrolled in school. Furthermore, 86% of the people treated would have been outside the reach of the NSDP because they were not primary school age or were primary school age children not enrolled in school. The comparable reach, the substantial reductions in cost per dose delivered and the decrease in participants’ time support this integrated One Health approach to control multiple NTDs. Further, the recorded level of non-enrolment at primary school suggests that, in remote areas, school-based delivery strategies could miss a large fraction of school-age children and that programs that focus delivery solely at the level of the primary school will miss a substantial proportion of both primary school age children as well as other individuals from the community. We have shown that these populations can be effectively reached through extramural programs.

Keywords: canine mediated human rabies, integrated health interventions, mass drug administration, neglected tropical disease, One Health, soil-transmitted helminths

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

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Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

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Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

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Authors: Koryukaeva Ksenia, Jinfeng Sun

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Europe has been a traditional importer of Russian natural gas for more than 50 years. In 2021, Russian state-owned company Gazprom supplied about a third of all gas consumed in Europe. The Russia-Europe mutual dependence in terms of natural gas supplies has been causing many concerns about the energy security of the two sides for a long period of time. These days the issue has become more urgent than ever considering recent Russian invasion in Ukraine followed by increased large-scale geopolitical conflicts, making the future of Russian natural gas supplies and global gas markets as well highly uncertain. Hence, the main purpose of this study is to get insight into the possible futures of Russian pipeline natural gas exports by a scenario planning method based on Monte-Carlo simulation within LUSS model framework, and propose Russian pipeline natural gas export strategies based on the obtained scenario planning results. The scenario analysis revealed that recent geopolitical disputes disturbed the traditional, longstanding model of Russian pipeline gas exports, and, as a result, the prospects and the pathways for Russian pipeline gas on the world markets will differ significantly from those before 2022. Specifically, our main findings show, that (i) the events of 2022 generated many uncertainties for the long-term future of Russian pipeline gas export perspectives on both western and eastern supply directions, including geopolitical, regulatory, economic, infrastructure and other uncertainties; (ii) according to scenario modelling results, Russian pipeline exports will face many challenges in the future, both on western and eastern directions. A decrease in pipeline gas exports will inevitably affect country’s natural gas production and significantly reduce fossil fuel export revenues, jeopardizing the energy security of the country; (iii) according to proposed strategies, in order to ensure the long-term stable export supplies in the changing environment, Russia may need to adjust its traditional export strategy by performing export flows and product diversification, entering new markets, adapting its contracting mechanism, increasing competitiveness and gaining a reputation of a reliable gas supplier.

Keywords: Russian natural gas, Pipeline natural gas, Uncertainty, Scenario simulation, Export strategy

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Authors: Mazarine Roquet, Pierre Dewallef

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The building sector, both residential and tertiary, accounts for a significant share of greenhouse gas emissions. In Belgium, partly due to poor insulation of the building stock, but certainly because of the massive use of fossil fuels for heating buildings, this share reaches almost 30%. To reduce carbon emissions from urban building heating, district heating networks emerge as a promising solution as they offer various assets such as improving the load factor, integrating combined heat and power systems, and enabling energy source diversification, including renewable sources and waste heat recovery. However, mainly for sake of simple operation, most existing district heating networks still operate at high or medium temperatures ranging between 120°C and 60°C (the socalled second and third-generations district heating networks). Although these district heating networks offer energy savings in comparison with individual boilers, such temperature levels generally require the use of fossil fuels (mainly natural gas) with combined heat and power. The fourth-generation district heating networks improve the transport and energy conversion efficiency by decreasing the operating temperature between 50°C and 30°C. Yet, to decarbonise the building heating one must increase the waste heat recovery and use mainly wind, solar or geothermal sources for the remaining heat supply. Fifth-generation networks operating between 35°C and 15°C offer the possibility to decrease even more the transport losses, to increase the share of waste heat recovery and to use electricity from renewable resources through the use of heat pumps to generate low temperature heat. The main objective of this contribution is to exhibit on a real-life test case the benefits of replacing an existing third-generation network by a fifth-generation one and to decarbonise the heat supply of the building stock. The second objective of the study is to highlight the difficulties resulting from the use of a fifth-generation, low-temperature, district heating network. To do so, a simulation model of the district heating network including its regulation is implemented in the modelling language Modelica. This model is applied to the test case of the heating network on the University of Liège's Sart Tilman campus, consisting of around sixty buildings. This model is validated with monitoring data and then adapted for low-temperature networks. A comparison of primary energy consumptions as well as CO2 emissions is done between the two cases to underline the benefits in term of energy independency and GHG emissions. To highlight the complexity of operating a lowtemperature network, the difficulty of adapting the mass flow rate to the heat demand is considered. This shows the difficult balance between the thermal comfort and the electrical consumption of the circulation pumps. Several control strategies are considered and compared to the global energy savings. The developed model can be used to assess the potential for energy and CO2 emissions savings retrofitting an existing network or when designing a new one.

Keywords: building simulation, fifth-generation district heating network, low-temperature district heating network, urban building heating

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