Search results for: sequential patterns

Authors: Seyed Mohammad Ali Zahedi

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This field experiment was conducted in Isfahan in 2011 in order to study the effect of plant density and planting pattern on growth, yield and quality of silage corn (SC 704) using a randomized complete block design with split plot layout and four replications. The main plot consisted of three planting patterns (60 and 75 cm single planting row and 75 cm double planting row referred to as 60S, 75S and 75T, respectively). The subplots consisted of four levels of plant densities (65000, 80000, 95000 and 110000 plants per hectare). Each subplot consisted of 7 rows, each with 10m length. Vegetative and reproductive characteristics of plants at silking and hard dough stages (when the plants were harvested for silage) were evaluated. Results of variance analysis showed that the effects of planting pattern and plant density were significant on leaf area per plant, leaf area index (at silking), plant height, stem diameter, dry weights of leaf, stem and ear in silking and harvest stages and on fresh and dry yield, dry matter percentage and crude protein percentage at harvest. There was no planting pattern × plant density interaction for these parameters. As row space increased from 60 cm with single planting to 75 cm with single planting, leaf area index and plant height increased, but leaf area per plant, stem diameter, dry weight of leaf, stem and ear, dry matter percentage, dry matter yield and crude protein percentage decreased. Dry matter yield reduced from 24.9 to 18.5 t/ha and crude protein percentage decreased from 6.11 to 5.60 percent. When the plant density increased from 65000 to 110000 plant per hectare, leaf area index, plant height, dry weight of leaf, stem and ear and dry matter yield increased from 19.2 to 23.3 t/ha, whereas leaf area per plant, stem diameter, dry matter percentage and crude protein percentage decreased from 6.30 to 5.25. The best results were obtained with 60 cm row distance with single planting and 110000 plants per hectare.

Keywords: silage corn, plant density, planting pattern, yield

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Authors: Jiajia Peng, Yijun Dong, Jianjun Ren, Yu Zhao

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Objectives: Understanding the association between sleep traits and tinnitus could help prevent and provide appropriate interventions against tinnitus. Therefore, this study aimed to assess the relationship between different sleep patterns and tinnitus. Design: A cross-sectional analysis using baseline data (2006–2010, n=168,064) by logistic regressions was conducted to evaluate the association between sleep traits (including the overall health sleep score and five sleep behaviors), and the occurrence (yes/no), frequency (constant/transient), and severity (upsetting/not upsetting) of tinnitus. Further, a prospective analysis of participants without tinnitus at baseline (n=9,581) was performed, who had been followed up for seven years (2012–2019) to assess the association between new-onset tinnitus and sleep characteristics. Moreover, a subgroup analysis was also carried out to estimate the differences in sex by dividing the participants into male and female groups. A sensitivity analysis was also conducted by excluding ear-related diseases to avoid their confounding effects on tinnitus (n=102,159). Results: In the cross-sectional analysis, participants with “current tinnitus” (OR: 1.13, 95% CI: 1.04–1.22, p=0.004) had a higher risk of having a poor overall healthy sleep score and unhealthy sleep behaviors such as short sleep durations (OR: 1.09, 95% CI: 1.04–1.14, p<0.001), late chronotypes (OR: 1.09, 95% CI: 1.05–1.13, p<0.001), and sleeplessness (OR: 1.16, 95% CI: 1.11–1.22, p<0.001) than those participants who “did not have current tinnitus.” However, this trend was not obvious between “constant tinnitus” and “transient tinnitus.” When considering the severity of tinnitus, the risk of “upsetting tinnitus” was obviously higher if participants had lower overall healthy sleep scores (OR: 1.31, 95% CI: 1.13–1.53, p<0.001). Additionally, short sleep duration (OR: 1.22, 95% CI: 1.12–1.33, p<0.001), late chronotypes (OR: 1.13, 95% CI: 1.04–1.22, p=0.003), and sleeplessness (OR: 1.43, 95% CI: 1.29–1.59, p<0.001) showed positive correlations with “upsetting tinnitus.” In the prospective analysis, sleeplessness presented a consistently significant association with “upsetting tinnitus” (RR: 2.28, P=0.001). Consistent results were observed in the sex subgroup analysis, where a much more pronounced trend was identified in females compared with males. The results of the sensitivity analysis were consistent with those of the cross-sectional and prospective analyses. Conclusions: Different types of sleep disturbance may be associated with the occurrence and severity of tinnitus; therefore, precise interventions for different types of sleep disturbance, particularly sleeplessness, may help in the prevention and treatment of tinnitus.

Keywords: tinnitus, sleep, sleep behaviors, sleep disturbance

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Iris Sauerbrei, Jörg Trojan, Erich Lehner

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Introduction and significance of the study: This study examines if three-dimensional shapes elicit distinct patterns of perceptions. If so, it is relevant for all fields of design, especially for the design of the built environment. Description of basic methodologies: The five platonic solids are the geometrical base for all other three-dimensional shapes, among which tetrahedron and icosahedron provide the clearest representation of the qualities sharp and round. The component pair of attributes ‘sharp versus round’ has already been examined in various surveys in a psychology of perception and in neuroscience by means of graphics, images of products of daily use, as well as by photographs and walk-through-videos of landscapes and architecture. To verify a transfer of outcomes of the existing surveys to the perception of three-dimensional shapes, walk-in models (total height 2.2m) of tetrahedron and icosahedron were set up in a public park in Frankfurt am Main, Germany. Preferences of park visitors were tested by questionnaire; also they were asked to write down associations in a free text. In summer 2015, the tetrahedron was assembled eight times, the icosahedron seven times. In total 288 participants took part in the study; 116 rated the tetrahedron, 172 rated the icosahedron. Findings: Preliminary analyses of the collected data using Wilcoxon Rank-Sum tests show that the perceptions of the two solids differ in respect to several attributes and that each of the tested model show significance for specific attributes. Conclusion: These findings confirm the assumptions and provide first evidence that the perception of three-dimensional shapes are associated to characteristic attributes and to which. In order to enable conscious choices for spatial arrangements in design processes for the built environment, future studies should examine attributes for the other three basic bodies - Octahedron, Cube, and Dodecahedron. Additionally, similarities and differences between the perceptions of two- and three-dimensional shapes as well as shapes that are more complex need further research.

Keywords: 3D shapes, architecture, geometrical features, space perception, walk-in models

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Authors: Kayvan Khoramipour, Abbas Ali Gaeini, Elham Shirzad, Øyvind Sandbakk

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Basketball has different positions with individual movement profiles, which may influence metabolic demands. Accordingly, the present study aimed to compare the movement and metabolic load between different positions during elite male basketball games. Five main players of 14 teams (n = 70), who participated in the 2017-18 Iranian national basketball leagues, were selected as participants. The players were defined as backcourt (Posts 1-3) and frontcourt (Posts 4-5). Video based time motion analysis (VBTMA) was performed based on players’ individual running and shuffling speed using Dartfish software. Movements were classified into high and low intensity running with and without having the ball, as well as high and low-intensity shuffling and static movements. Mean frequency, duration, and distance were calculated for each class, except for static movements where only frequency was calculated. Saliva samples were collected from each player before and after 40-minute basketball games and analyzed using metabolomics. Principal component analysis (PCA) and Partial least square discriminant analysis (PLSDA) (for metabolomics data) and independent T-tests (for VBTMA) were used as statistical tests. Movement frequency, duration, and distance were higher in backcourt players (all p ≤ 0.05), while static movement frequency did not differ. Saliva samples showed that the levels of Taurine, Succinic acid, Citric acid, Pyruvate, Glycerol, Acetoacetic acid, Acetone, and Hypoxanthine were all higher in backcourt players, whereas Lactate, Alanine, 3-Metyl Histidine, and Methionine were higher in frontcourt players Based on metabolomics, we demonstrate that backcourt and frontcourt players have different metabolic profiles during games, where backcourt players move clearly more during games and therefore rely more on aerobic energy, whereas frontcourt players rely more on anaerobic energy systems in line with less dynamic but more static movement patterns.

Keywords: basketball, metabolomics, saliva, sport loadomics

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Authors: Syed Muhammad Wajih ul Hassan

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This research looks at the perception of first-time voters in Pakistan on the political dynamics of the country. This paper shall review the researches that were conducted by Gallup Pakistan and compare it with our findings regarding the voter behavior and factors that affect the priorities of the voters. A country where democracy has just completed its 2 consecutive tenures for the first time, one would always want to know about the voting trends among youth where young population makes 60% of the population in the country. In that case, it is not only a big task to find out voter patterns and trends voters might adhere to while a general election is approaching. Also, the paper discovers the psychology of young Pakistani voters on the upcoming election of 2018 but also the factors that influence the voting decisions of a voter. This research tries to study the relations among voters and how they view each other in general. The paper also explores the views of voters on the factors that impact decision making of a voter while casting his/her vote in Pakistan. The paper thoroughly studies the expectations of the voters from the current system that prevails in the country. The reason this research was conducted is that this kind of positive approach towards finding out the voter perception is heavily untouched in Pakistani academia. This study can benefit a lot of institutions and professions in the future too. The constraints and obstacles that came while this research was being conducted are also identified in the paper. The mode of research is primary research as it was impossible to find out the perceptions of first-time voters without going on the field and carrying out the research. The research was conducted in one of the most reputable and liberal educational institutions of Pakistan. This research is based on a survey that was conducted through questionnaires where responses were collected through a mix process of random and convenient sampling. The major findings of the study show that young voters have a realistic perspective about the electoral process in the country. The research also articulates the factors that affect the priorities of young voters, and also how young voters view other voters that belong from other sections of the society. To conclude, we can say that this research will give us a perspective that can define and identify the voter priorities of the future in Pakistan.

Keywords: first time voters, general election 2018, Pakistan, young

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Authors: Daniel Gidey, Kunwar Siddarth Dadhwal

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By evaluating India's aid systems and ongoing development initiatives, this conference paper offers light on India's role as a source of developmental assistance in Africa. This research attempts to provide insights into the developing landscape of foreign aid and development cooperation by focusing on understanding India's motivations and strategy. In recent years, India's connection with Africa has grown significantly, driven by economic, political, and strategic reasons. This conference paper covers India's many forms of aid, including financial, capacity building efforts, technical assistance, and infrastructure development projects, via a thorough investigation. The article seeks to establish India's priorities and highlight the possible impacts of its development assistance in Africa by examining the industries and locations of concentration. Using secondary data sources, the investigation delves into the underlying goals of India's aid policy in Africa. It investigates whether India's development assistance is consistent with its broader geopolitical aims, such as access to resources, competing with regional rivals, or strengthening diplomatic ties. Furthermore, the article investigates how India's aid policy combines the ideals of South-South cooperation and mutual development, as well as the ramifications for recipient countries. Furthermore, the paper assesses the efficacy and sustainability of India's aid operations in Africa. It takes into account the elements that influence their success, the problems they face, and the amount to which they contribute to local development goals, community empowerment, and poverty alleviation. The study also focuses on the accountability systems, transparency, and knowledge transfer aspects of India's development assistance. By providing a detailed examination of India's aid endeavors in Africa, the paper adds to the current literature on international development cooperation. By offering fresh insights into the motives, strategies, and impacts of India's assistance programs, it seeks to enhance understanding of the emerging patterns in South-South cooperation and the complex dynamics of contemporary international aid architecture.

Keywords: India, Africa, developmental assistance, aid projects and South-South cooperation

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Authors: Elif D. Oguz Erkal, David Krackhardt, Erica Cochran-Hameen

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Even though social network analysis (SNA) is an abundantly studied concept for many organizations and industries, a clear SNA approach to the project teams has not yet been adopted by the construction industry. The main challenges for performing SNA in construction and the apparent reason for this gap is the unique and complex structure of each construction project, the comparatively high circulation of project team members/contributing parties and the variety of authentic problems for each project. Additionally, there are stakeholders from a variety of professional backgrounds collaborating in a high-stress environment fueled by time and cost constraints. Within this case study on Project RE, a design & build project performed at the Urban Design Build Studio of Carnegie Mellon University, social network analysis of the project design team will be performed with the main goal of applying social network theory to construction project environments. The research objective is to determine a correlation between the network of how individuals relate to each other on one’s perception of their own professional strengths and weaknesses and the communication patterns within the team and the group dynamics. Data is collected through a survey performed over four rounds conducted monthly, detailed follow-up interviews and constant observations to assess the natural alteration in the network with the effect of time. The data collected is processed by the means of network analytics and in the light of the qualitative data collected with observations and individual interviews. This paper presents the full ethnography of this construction design team of fourteen architecture students based on an elaborate social network data analysis over time. This study is expected to be used as an initial step to perform a refined, targeted and large-scale social network data collection in construction projects in order to deduce the impacts of social networks on project performance and suggest better collaboration structures for construction project teams henceforth.

Keywords: construction design teams, construction project management, social network analysis, team collaboration, network analytics

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Authors: Ramona Georgeta Biholar

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Gender-based violence against women plagues societies around the world. The work to eliminate it is an ongoing battle. At the international level, Article 5 (a) CEDAW establishes an agenda for social and cultural transformation: it imposes on States parties to CEDAW an obligation to modify sex roles and stereotypical social and cultural patterns of conduct. Also, it provides for the protection of women from violence stemming from such gender norms. Yet, the lived realities of women are frequently disconnected from this agenda. Nonetheless, it is the reality of the local that is crucial for the articulation, implementation and realization of women’s rights in general, and for the elimination of gender-based violence against women in particular. In this paper we discuss the transformation of sex roles and gender stereotyping with a view to realize women’s right to be free from gender-based violence. This paper is anchored in qualitative data collection undertaken in Jamaica and socio-legal research. Based on this research, 1) We explain the process of vernacularisation as a strategy that enables women’s human rights to hit the ground and benefit rights holders, and 2) We present a synergistic model for the implementation of Article 5 (a) CEDAW so that women’s right to be free from gender-based violence can be realized in a concrete national jurisdiction. This model is grounded in context-based demands and recommendations for social and cultural transformation as a remedy for the incidence of gender-based violence against women. Moreover, the synergistic model offers directions that have a general application for the implementation of CEDAW and Article 5 (a) CEDAW in particular, with a view to realize women’s right to be free from gender-based violence. The model is thus not only a conceptual tool of analysis, but also a prescriptive tool for action. It contributes to the work of both academics and practitioners, such as Governmental officials, and national and local civil society representatives. Overall, this paper contributes to understanding the process necessary to bridge that gap between women’s human rights norms and women’s life realities of discrimination and violence.

Keywords: CEDAW, gender-based violence against women, international human rights law, women’s rights implementation, the Caribbean

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Authors: Jennifer Hunter, Francisco Ramirez, Neil A. Nedley, Thania Solorio, Christian Freed, Erica Kinjo

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People who have autoimmune disease are often at an increased risk for psychological disorders such as anxiety. Untreated psychological conditions can affect the development of disease and can affect one’s general quality of life. In this study, it was hypothesized that an educational community-based intervention would be useful in decreasing the anxiety levels of participants with autoimmune disease. Programs, 2-hours long each, were held weekly over a period of eight weeks. During every meeting, a 45-minute DVD presentation by a skilled physician was shown, a small group discussion was guided by trained facilitators, and weekly practical assignments were given to each participant. The focus of the program was to educate participants about healthy lifestyle behaviors such as exercise, nutrition, sleep hygiene, helpful thought patterns etc., and to provide a group environment in which each participant was supported. Participants were assessed pre-post program for anxiety using the Depression and Anxiety Assessment Test (registration TX 7-398-022), a validated mental health test based on DSM-5 criteria and demographics. Anxiety scores were classified according to the DSM-5 criteria into 4 categories: none (0-6), mild (7-10), moderate (11-19) or severe (20 or more). Out of the participants who participated in programs conducted in the manner explained above (n=431), the average age was 54.9 (SD 16.6) and 81.9% were female. At baseline, the mean group anxiety level was 9.4 (SD 5.4). Within the baseline group, anxiety levels were as follows: none (21.1%), mild (22.0%), moderate (27.1%) and severe (29.7%). After the program, mean group anxiety decreased to 4.7 (SD 4.0). Post-program anxiety levels were as follows: none (54.8%), mild (27.1%), moderate (12.5%), severe (5.6%). The decrease in overall anxiety levels was significant t(431)=19.3 p<.001, 95% CI [0.815, 1.041]. It was concluded that the eight-week intensive was beneficial in decreasing the anxiety levels of participants. A long-term follow-up study would be beneficial in determining how lasting such improvements are especially since autoimmune diseases are often chronic. Additionally, future studies that utilize a control group would aid in establishing whether the improvements seen are due to the use of this specific lifestyle-educational program.

Keywords: anxiety, auto-immune disease, community-based educational program, lifestyle

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Authors: Aishi Kundu, Elhan Raza

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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

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Authors: Rebecca S. Hock, Cyralene P. Bryce, Kevin Williams, Arielle G. Rabinowitz, Janina R. Galler

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Background: Findings have been mixed regarding whether offspring of parents who were abused or neglected as children have a greater risk of experiencing abuse or neglect themselves. In addition, many studies on this topic are restricted to physical abuse and take place in a limited number of countries, representing a small segment of the world's population. Methods: We examined relationships between childhood maltreatment history assessed in a subset (N=68) of the original longitudinal birth cohort (G1) of the Barbados Nutrition Study and their now-adult offspring (G2) (N=111) using the Childhood Trauma Questionnaire-Short Form (CTQ-SF). We used Pearson correlations to assess relationships between parent and offspring CTQ-SF total and subscale scores (physical, emotional, and sexual abuse; physical and emotional neglect). Next, we ran multiple regression analyses, using the parental CTQ-SF total score and the parental Sexual Abuse score as primary predictors separately in our models of G2 CTQ-SF (total and subscale scores). Results: G1 total CTQ-SF scores were correlated with G2 offspring Emotional Neglect and total scores. G1 Sexual Abuse history was significantly correlated with G2 Emotional Abuse, Sexual Abuse, Emotional Neglect, and Total Score. In fully-adjusted regression models, parental (G1) total CTQ-SF scores remained significantly associated with G2 offspring reports of Emotional Neglect, and parental (G1) Sexual Abuse was associated with offspring (G2) reports of Emotional Abuse, Physical Abuse, Emotional Neglect, and overall CTQ-SF scores. Conclusions: Our findings support a link between parental exposure to childhood maltreatment and their offspring's self-reported exposure to childhood maltreatment. Of note, there was not an exact correspondence between the subcategory of maltreatment experienced from one generation to the next. Compared with other subcategories, G1 Sexual Abuse history was the most likely to predict G2 offspring maltreatment. Further studies are needed to delineate underlying mechanisms and to develop intervention strategies aimed at preventing intergenerational transmission.

Keywords: trauma, family, adolescents, intergenerational trauma, child abuse, child neglect, global mental health, North America

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Authors: Cesar A. Nava-Gaxiola, C. Barrado

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Harmonized with SESAR (Single European Sky Research) initiatives, a new concept related with airspace structures have been introduced in Europe, the Free Route Airspace. The key of free route is based in an airspace where users may freely plan a route between a defined entry and exit waypoint, with the possibility of routing via intermediate points, the free route flights remain subject to air traffic control (ATC) for the established separations. Free route airspace does not present anymore fixed airways to airspace users, as a consequence it brings a new paradigm for managing safe separations of aircrafts inside these airspace blocks . Nowadays, several European nations have been introduced the concept, some of them in a complete or partial stage, but finally offering limited benefits to airspace users for this condition. This research evaluates the future scenario of free route implementation across Europe, considering a unique airspace block configuration with a complete upper airspace with free route. The paper is centered in investigating the benefits for airspace users, and the study of possible increments of Air Traffic Controllers task loads with a full application. In this research, fast time simulations are carrying out for discovering how much flight time and distance aircrafts can save with an overall free route establishment. In the other side, the paper explains the evolution of conflicts derivate from possible separation losses between aircrafts in this new environment. Free route conflicts can emerges in any points of the airspace, requiring a great effort for solving it, in comparison with fixed airways, where conflicts normally were found by controllers in known waypoints, and they solved using the fixed network as reference. The airspace configuration modelled in this study take into account the actual navigation waypoints structure, moving into a future scenario, where new ones waypoints are added and new traffic flow patterns appears. In this sense, this research explores the advantages and unknown difficulties that a large scale application of free route concept can carry out in the European airspace.

Keywords: ATC conflicts, efficiency, free route airspace, SESAR

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Authors: Sofya Komarova, Frashia Ndungu, Alessia Gavazzoli, Roberta Mineo

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Modern society requires people to be flexible and to develop innovative solutions to unexpected situations. Creativity refers to the “interaction among aptitude, process, and the environment by which an individual or group produces a perceptible product that is both novel and useful as defined within a social context”. It allows humans to produce novel ideas, generate new solutions, and express themselves uniquely. Only a few scientific studies have examined group dynamics' influence on individuals' creativity. There exist some gaps in the research on creative thinking, such as the fact that collaborative effort frequently results in the enhanced production of new information and knowledge. Therefore, it is critical to evaluate creativity via social settings. The study aimed at exploring the group dynamics of young adults in small group settings and the influence of these dynamics on their creativity. The study included 30 participants aged 20 to 25 who were attending university after completing a bachelor's degree. The participants were divided into groups of three, in gender homogenous and heterogeneous groups. The groups’ creative task was tied to the Lego mosaic created for the Scintillae laboratory at the Reggio Children Foundation. Group dynamics were operationalized into patterns of behaviors classified into three major categories: 1) Social Interactions, 2) Play, and 3) Distraction. Data were collected through audio and video recording and observation. The qualitative data were converted into quantitative data using the observational coding system; then, they were analyzed, revealing correlations between behaviors using median points and averages. For each participant and group, the percentages of represented behavior signals were computed. The findings revealed a link between social interaction, creative thinking, and creative activities. Other findings revealed that the more intense the social interaction, the lower the amount of creativity demonstrated. This study bridges the research gap between group dynamics and creativity. The approach calls for further research on the relationship between creativity and social interaction.

Keywords: group dynamics, creative thinking, creative action, social interactions, group play

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Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

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Authors: Thomas Louis, Irina Primac, Florent Morfoisse, Tania Durre, Silvia Blacher, Agnes Noel

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In vitro and in vivo lymphangiogenesis assays are essential for the identification of potential lymphangiogenic agents and the screening of pharmacological inhibitors. In the present study, we analyse three biological models: in vitro lymphatic endothelial cell spheroids, in vivo ear sponge assay, and in vivo lymph node colonisation by tumour cells. These assays provide suitable 3D models to test pro- and anti-lymphangiogenic factors or drugs. 3D images were acquired by confocal laser scanning and light sheet fluorescence microscopy. Virtual scan microscopy followed by 3D reconstruction by image aligning methods was also used to obtain 3D images of whole large sponge and ganglion samples. 3D reconstruction, image segmentation, skeletonisation, and other image processing algorithms are described. Fixed and time-lapse imaging techniques are used to analyse lymphatic endothelial cell spheroids behaviour. The study of cell spatial distribution in spheroid models enables to detect interactions between cells and to identify invasion hierarchy and guidance patterns. Global measurements such as volume, length, and density of lymphatic vessels are measured in both in vivo models. Branching density and tortuosity evaluation are also proposed to determine structure complexity. Those properties combined with vessel spatial distribution are evaluated in order to determine lymphangiogenesis extent. Lymphatic endothelial cell invasion and lymphangiogenesis were evaluated under various experimental conditions. The comparison of these conditions enables to identify lymphangiogenic agents and to better comprehend their roles in the lymphangiogenesis process. The proposed methodology is validated by its application on the three presented models.

Keywords: 3D image segmentation, 3D image skeletonisation, cell invasion, confocal microscopy, ear sponges, light sheet microscopy, lymph nodes, lymphangiogenesis, spheroids

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: Kwan Hee Han

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External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

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Authors: Frederic Heymes, Michael Albrecht Birk, Roland Eyssette

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Boiling Liquid Expanding Vapor Explosion (BLEVE) has been a well know industrial accident for over 6 decades now, and yet it is still poorly predicted and avoided. BLEVE is created when a vessel containing a pressure liquefied gas (PLG) is engulfed in a fire until the tank rupture. At this time, the pressure drops suddenly, leading the liquid to be in a superheated state. The vapor expansion and the violent boiling of the liquid produce several shock waves. This works aimed at understanding the contribution of vapor ad liquid phases in the overpressure generation in the near field. An experimental work was undertaken at a small scale to reproduce realistic BLEVE explosions. Key parameters were controlled through the experiments, such as failure pressure, fluid mass in the vessel, and weakened length of the vessel. Thirty-four propane BLEVEs were then performed to collect data on scenarios similar to common industrial cases. The aerial overpressure was recorded all around the vessel, and also the internal pressure changed during the explosion and ground loading under the vessel. Several high-speed cameras were used to see the vessel explosion and the blast creation by shadowgraph. Results highlight how the pressure field is anisotropic around the cylindrical vessel and highlights a strong dependency between vapor content and maximum overpressure from the lead shock. The time chronology of events reveals that the vapor phase is the main contributor to the aerial overpressure peak. A prediction model is built upon this assumption. Secondary flow patterns are observed after the lead. A theory on how the second shock observed in experiments forms is exposed thanks to an analogy with numerical simulation. The phase change dynamics are also discussed thanks to a window in the vessel. Ground loading measurements are finally presented and discussed to give insight into the order of magnitude of the force.

Keywords: phase change, superheated state, explosion, vapor expansion, blast, shock wave, pressure liquefied gas

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Authors: S. Malebary, W. Xu

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Antennas are important components that enable transmitting and receiving signals in mid-air (wireless). The radiation pattern of omni-directional (i.e., dipole) antennas, reflects the variation of power radiated by an antenna as a function of direction when transmitting. As the performance of the antenna is the same in transmitting and receiving, it also reflects the sensitivity of the antenna in different directions when receiving. The main observation when dealing with omni-directional antennas, regardless the application, is they equally radiate power in all directions in reference to Equivalent Isotropically Radiated Power (EIRP). Disseminating radio frequency signals in an omni-directional manner form a doughnut-shape-field with a cone in the middle of the elevation plane (when mounted vertically). In this paper, we investigate the existence of this physical phenomena namely silence cone zone (the zone where radiated power is nulled). First, we overview antenna types and properties that have the major impact on the shape of the electromagnetic field. Then we model various off the shelf dipoles in Matlab based on antennas’ features (dimensions, gain, operating frequency, … etc.) and compare the resulting radiation patterns. After that, we validate the existence of the null zone in Omni-directional antennas by conducting experiments and generating waveforms (using USRP1 and USRP2) at various frequencies using different types of antennas and gains in indoor/outdoor. We capture the generated waveforms around antennas' null zone in the reactive, near, and far field with a spectrum analyzer mounted on a drone, using various off the shelf antennas. We analyze the captured signals in RF-Explorer and plot the impact on received power and signal amplitude inside and around the null zone. Finally, it is concluded from evaluation and measurements the existence of null zones in Omni-directional antennas which we plan on extending this work in the near future to investigate the usability of the null zone for various applications such as localization and path finding.

Keywords: antennas, amplitude, field regions, frequency, FSPL, omni-directional, radiation pattern, RSSI, silence zone cone

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Authors: Bojana Horvat, Barbara Karleusa, Goran Volf, Nevenka Ozanic, Ivica Kisic

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Forest fire is a major threat in many regions in Croatia, especially in coastal areas. Although they are often caused by natural processes, the most common cause is the human factor, intentional or unintentional. Forest fires drastically transform landscapes and influence natural processes. The main goal of the presented research is to analyse and quantify the impact of the forest fire on hydrological processes and propose the model that best describes changes in hydrological patterns in the analysed catchments. Keeping in mind the spatial component of the processes, geospatial analysis is performed to gain better insight into the spatial variability of the hydrological response to disastrous events. In that respect, two catchments that experienced severe forest fire were delineated, and various hydrological and meteorological data were collected both attribute and spatial. The major drawback is certainly the lack of hydrological data, common in small torrential karstic streams; hence modelling results should be validated with the data collected in the catchment that has similar characteristics and established hydrological monitoring. The event chosen for the modelling is the forest fire that occurred in July 2019 and burned nearly 10% of the analysed area. Surface (land use/land cover) conditions before and after the event were derived from the two Sentinel-2 images. The mapping of the burnt area is based on a comparison of the Normalized Burn Index (NBR) computed from both images. To estimate and compare hydrological behaviour before and after the event, curve number (CN) values are assigned to the land use/land cover classes derived from the satellite images. Hydrological modelling resulted in surface runoff generation and hence prediction of hydrological responses in the catchments to a forest fire event. The research was supported by the Croatian Science Foundation through the project 'Influence of Open Fires on Water and Soil Quality' (IP-2018-01-1645).

Keywords: Croatia, forest fire, geospatial analysis, hydrological response

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Authors: Josef Novák, Alena Kohoutková, Vladimír Křístek, Jan Vodička

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Numerical analysis software belong to the main tools for simulating the real behavior of various concrete structures and elements. In comparison with experimental tests, they offer an affordable way to study the mechanical behavior of structures under various conditions. The contribution deals with a precast element of an innovative airfield pavement system which is being developed within an ongoing scientific project. The proposed system consists a two-layer surface course of precast concrete panels positioned on a two-layer base of fiber-reinforced concrete with recycled aggregate. As the panels are supposed to be installed directly on the hardened base course, imperfections at the interface between the base course and surface course are expected. Considering such circumstances, three various behavior patterns could be established and considered when designing the precast element. Enormous costs of full-scale experiments force to simulate the behavior of the element in a numerical analysis software using finite element method. The simulation was conducted on a nonlinear model in order to obtain such results which could fully compensate results from the experiments. First, several loading schemes were considered with the aim to observe the critical one which was used for the simulation later on. The main objective of the simulation was to optimize reinforcement of the element subject to quasi-static loading from airplanes. When running the simulation several parameters were considered. Namely, it concerns geometrical imperfections, manufacturing imperfections, stress state in reinforcement, stress state in concrete and crack width. The numerical simulation revealed that the precast element should be heavily reinforced to fulfill all the demands assumed. The main cause of using high amount of reinforcement is the size of the imperfections which could occur at real structure. Improving manufacturing quality, the installation of the precast panels on a fresh base course or using a bedding layer underneath the surface course belong to the main steps how to reduce the size of imperfections and consequently lower the consumption of reinforcement.

Keywords: nonlinear analysis, numerical simulation, precast concrete, pavement

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Authors: S. Jayalakshmi, Gayathri S., Subiksa V., Nithyasri P., Agasthiya

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Paleochannels are the buried part of an active river system which was separated from the active river channel by the process of cutoff or abandonment during the dynamic evolution of the active river. Over time, they are filled by young unconsolidated or semi-consolidated sediments. Additionally, it is impacted by geo morphological influences, lineament alterations, and other factors. The primary goal of this study is to identify the paleochannels in Periyar river basin for the year 2023. Those channels has a high probability in the presence of natural resources, including gold, platinum,tin,an duranium. Numerous techniques are used to map the paleochannel. Using the optical data, Satellite images were collected from various sources, which comprises multispectral satellite images from which indices such as Normalized Difference Vegetation Index (NDVI),Normalized Difference Water Index (NDWI), Soil Adjusted Vegetative Index (SAVI) and thematic layers such as Lithology, Stream Network, Lineament were prepared. Weights are assigned to each layer based on its importance, and overlay analysis has done, which concluded that the northwest region of the area has shown some paleochannel patterns. The results were cross-verified using the results obtained using microwave data. Using Sentinel data, Synthetic Aperture Radar (SAR) Image was extracted from European Space Agency (ESA) portal, pre-processed it using SNAP 6.0. In addition to that, Polarimetric decomposition technique has incorporated to detect the paleochannels based on its scattering property. Further, Principal component analysis has done for enhanced output imagery. Results obtained from optical and microwave radar data were compared and the location of paleochannels were detected. It resulted six paleochannels in the study area out of which three paleochannels were validated with the existing data published by Department of Geology and Environmental Science, Kerala. The other three paleochannels were newly detected with the help of SAR image.

Keywords: paleochannels, optical data, SAR image, SNAP

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Authors: Jakub Vávra, Milan Valenta, Petr Kosek

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This article presents a perspective on the conduct of the dramatherapy process with persons with addictive behaviours with regard to the directiveness of the process. Although drama therapy as one of the creative arts approaches is rather non-directive in nature, depending on the clientele, there may be a need to structure the process more and, depending on the needs of the clients, to guide the process more directive. The specificity for people with addictive behaviours is discussed through the prism of the dramatherapeutic perspective, where we can find both a psychotherapeutic component as well as a component touching on expression and art, which is rather non-directive in nature. Within the context of practice with clients, this theme has repeatedly emerged and dramatherapists themselves have sought to find ways of coping with clients' demands and needs for structure and guidance within the dramatherapy process. Some of the outcomes from the supervision work also guided the research. Based on this insight, the research questions were approached. The first research question asks: in what ways is directive in dramatherapy manifested and manifested in the process? The second research question then complements the first and asks: to which phenomena are directivity in dramatherapy linked? In relation to the research questions, data were collected using focus groups and field notes. The qualitative approach of Content analysis and Relational analysis was chosen as the methodology. For analyzing qualitative research, we chose an Inductive coding scheme: Open coding, Axial coding, Pattern matching, Member checking, and Creating a coding scheme. In the presented partial research results, we find recurrent schemes related to directive coding in drama therapy. As an important element, directive leadership emerges in connection with safety for the client group, then in connection with the clients' order and also the department of the facility, and last but not least, to the personality of the drama therapist. By careful analysis and looking for patterns in the research results, we can see connections that are impossible to interpret at this stage but already provide clues to our understanding of the topic and open up further avenues for research in this area.

Keywords: dramatherapy, directivity, personal approach, aims of dramatherapy process, safetyness

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Authors: Md Y. Reja, Samuel D. Brody, Wesley E. Highfield, Galen D. Newman

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Historically, wetlands in the United States have been lost due to agriculture, anthropogenic activities, and rapid urbanization along the coast. Such losses of wetlands have resulted in high flooding risk for coastal communities over the period of time. In addition, alteration of wetlands via the Section 404 Clean Water Act permits can increase the flooding risk to future hurricane events, as the cumulative impact of this program is poorly understood and under-accounted. Further, recovery after hurricane events is acting as an encouragement for new development and reconstruction activities by converting wetlands under the wetland alteration permitting program. This study investigates the degree to which hurricane recovery activities in coastal communities are undermining the ability of these places to absorb the impacts of future storm events. Specifically, this work explores how and to what extent wetlands are being affected by the federal permitting program post-Hurricane Ike in 2008. Wetland alteration patterns are examined across three counties (Harris, Galveston, and Chambers County) along the Texas Gulf Coast over a 10-year time period, from 2004-2013 (five years before and after Hurricane Ike) by conducting descriptive spatial analyses. Results indicate that after Hurricane Ike, the number of permits substantially increased in Harris and Chambers County. The vast majority of individual and nationwide type permits were issued within the 100-year floodplain, storm surge zones, and areas damaged by Ike flooding, suggesting that recovery after the hurricane is compromising the ecological resiliency on which coastal communities depend. The authors expect that the findings of this study can increase awareness to policy makers and hazard mitigation planners regarding how to manage wetlands during a long-term recovery process to maintain their natural functions for future flood mitigation.

Keywords: ecological resiliency, Hurricane Ike, recovery, Section 404 Permitting, wetland alteration

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Authors: Komal Niazi, He Guoqiang

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This paper is focused on ‘CPEC (China Pakistan Economic Corridor) a changing mechanism in Pakistan’. China Pakistan Economic Corridor (CPEC) activity under OBOR (One Belt One Road (OBOR) CPEC is a piece of the bigger umbrella and goes for giving another hallway of exchange for China and Pakistan and is relied upon to profit the entire of South Asian area. But this study reveals that significance of acculturation can never be overemphasized in the investigation of diverse impacts and the routes people groups of various ethnic personalities figure out how to adjust and acknowledge the social attributes of a larger part group in a multiethnic culture. This study also deals with the effects of acculturation which can be seen at multiple levels through CPEC for both Pakistani and Chinese people, who were working on this project. China and Pakistan exchanged the cultural and social patterns with each other. Probably the most perceptible gathering level impacts of cultural assimilation regularly incorporate changes in sustenance (food), clothing, and language. At the individual level, the procedure of cultural assimilation alludes to the socialization procedure by which the Pakistani local people and Chinese who were working in Pakistan adopted values, traditions, attitudes, states of mind, and practices. But China has imposed discourse through economic power and language. CPEC dominates Pakistan’s poor area’s and changes their living, social and cultural values. People also claimed this acculturation was a great threat to their cultural values and religious beliefs. Main findings of the study clearly ascertained that research was to find out the conceptual understanding of people about the acculturation process through CPEC. At the cultural level, aggregate activities and social organizations end up plainly adjusted, and at the behavioral level, there are changes in a person's day by day behavioral collection and some of the time in experienced anxiety. Anthropological data methods were used to collect data, like snowball and judgmental sampling, case studied methods.

Keywords: CPEC, acculturation process, language discourse, social norms, cultural values, religious beliefs

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Authors: Semachew M. Kassa, Africa M Geremew, Tezera F. Azmatch, Nandyala Darga Kumar

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Frequency ratio (FR) and analytical hierarchy process (AHP) methods are developed based on past landslide failure points to identify the landslide susceptibility mapping because landslides can seriously harm both the environment and society. However, it is still difficult to select the most efficient method and correctly identify the main driving factors for particular regions. In this study, we used fourteen landslide conditioning factors (LCFs) and five soft computing algorithms, including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), Artificial Neural Network (ANN), and Naïve Bayes (NB), to predict the landslide susceptibility at 12.5 m spatial scale. The performance of the RF (F1-score: 0.88, AUC: 0.94), ANN (F1-score: 0.85, AUC: 0.92), and SVM (F1-score: 0.82, AUC: 0.86) methods was significantly better than the LR (F1-score: 0.75, AUC: 0.76) and NB (F1-score: 0.73, AUC: 0.75) method, according to the classification results based on inventory landslide points. The findings also showed that around 35% of the study region was made up of places with high and very high landslide risk (susceptibility greater than 0.5). The very high-risk locations were primarily found in the western and southeastern regions, and all five models showed good agreement and similar geographic distribution patterns in landslide susceptibility. The towns with the highest landslide risk include Amhara Saint Town's western part, the Northern part, and St. Gebreal Church villages, with mean susceptibility values greater than 0.5. However, rainfall, distance to road, and slope were typically among the top leading factors for most villages. The primary contributing factors to landslide vulnerability were slightly varied for the five models. Decision-makers and policy planners can use the information from our study to make informed decisions and establish policies. It also suggests that various places should take different safeguards to reduce or prevent serious damage from landslide events.

Keywords: artificial neural network, logistic regression, landslide susceptibility, naïve Bayes, random forest, support vector machine

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Authors: Viktor Müller, Ulman Lindenberger

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Neurophysiological evidence suggests that the physiological states of the system are characterized by specific network structures and network topology dynamics, demonstrating a robust interplay between network topology and function. It is also evident that interpersonal action coordination or social interaction (e.g., playing music in duets or groups) requires strong intra- and interbrain synchronization resulting in a specific hyper brain network activity across two or more brains to support such coordination or interaction. Such complex hyper brain networks can be described as multiplex or multilayer networks that have a specific multidimensional or multilayer network organization characteristic for superordinate systems and their constituents. The aim of the study was to describe multilayer hyper brain networks and synchronization patterns of guitarists playing guitar in a quartet by using electroencephalography (EEG) hyper scanning (simultaneous EEG recording from multiple brains) and following time-frequency decomposition and multilayer network construction, where within-frequency coupling (WFC) represents communication within different layers, and cross-frequency coupling (CFC) depicts communication between these layers. Results indicate that communication or coupling dynamics, both within and between the layers across the brains of the guitarists, play an essential role in action coordination and are particularly enhanced during periods of high demands on musical coordination. Moreover, multilayer hyper brain network topology and dynamical structure of guitar sounds showed specific guitar-guitar, brain-brain, and guitar-brain causal associations, indicating multilevel dynamics with upward and downward causation, contributing to the superordinate system dynamics and hyper brain functioning. It is concluded that the neuronal dynamics during interpersonal interaction are brain-wide and frequency-specific with the fine-tuned balance between WFC and CFC and can best be described in terms of multilayer multi-brain networks with specific network topology and connectivity strengths. Further sophisticated research is needed to deepen our understanding of these highly interesting and complex phenomena.

Keywords: EEG hyper scanning, intra- and interbrain coupling, multilayer hyper brain networks, social interaction, within- and cross-frequency coupling

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Authors: Tanvi P. Medshinge, Prasad Vaidya, Monisha E. Royan

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In India, cooling loads in residential sector is a major contributor to its total energy consumption. Due to the increasing cooling need, the market penetration of air-conditioners is further expected to rise. Natural Ventilation (NV), however, possesses great potential to save significant energy consumption especially for residential buildings in moderate climates. As multifamily residential apartment buildings are designed by repetitive use of prototype designs, deriving individual NV based design prototype solutions for a combination of different wind incidence angles and orientations would provide significant opportunity to address the rise in cooling loads by residential sector. This paper presents the results of NV performance of a selected prototype apartment design with a cluster of four units in Pune, India, and an attempt to improve the NV performance through design modifications. The water table apparatus, a physical modelling tool, is used to study the flow patterns and simulate wind-induced NV performance. Quantification of NV performance is done by post processing images captured from video recordings in terms of percentage of area with good and poor access to ventilation. NV performance of the existing design for eight wind incidence angles showed that of the cluster of four units, the windward units showed good access to ventilation for all rooms, and the leeward units had lower access to ventilation with the bedrooms in the leeward units having the least access. The results showed improved performance in all the units for all wind incidence angles to more than 80% good access to ventilation. Some units showed an additional improvement to more than 90% good access to ventilation. This process of design and performance evaluation improved some individual units from 0% to 100% for good access to ventilation. The results demonstrate the ease of use and the power of the water table apparatus for performance-based design to simulate wind induced NV.  

Keywords: fluid dynamics, prototype design, natural ventilation, simulations, water table apparatus, wind incidence angles

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Authors: Rasha Ali Dheyab

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In today's increasingly interconnected and technologically-driven world, communication has evolved beyond traditional verbal exchanges. This paper delves into the fascinating realm of multimodal communication, a dynamic field at the intersection of linguistics, gesture studies, and technology. The study of how humans convey meaning through a combination of spoken language, gestures, facial expressions, and digital platforms has gained prominence as our modes of interaction continue to diversify. This exploration begins by examining the foundational theories in linguistics and gesture studies, tracing their historical development and mutual influences. It further investigates the role of nonverbal cues, such as gestures and facial expressions, in augmenting and sometimes even altering the meanings conveyed by spoken language. Additionally, the paper delves into the modern technological landscape, where emojis, GIFs, and other digital symbols have emerged as new linguistic tools, reshaping the ways in which we communicate and express emotions. The interaction between traditional and digital modes of communication is a central focus of this study. The paper investigates how technology has not only introduced new modes of expression but has also influenced the adaptation of existing linguistic and gestural patterns in online discourse. The emergence of virtual reality and augmented reality environments introduces yet another layer of complexity to multimodal communication, offering new avenues for studying how humans navigate and negotiate meaning in immersive digital spaces. Through a combination of literature review, case studies, and theoretical analysis, this paper seeks to shed light on the intricate interplay between language, gesture, and technology in the realm of multimodal communication. By understanding how these diverse modes of expression intersect and interact, we gain valuable insights into the ever-evolving nature of human communication and its implications for fields ranging from linguistics and psychology to human-computer interaction and digital anthropology.

Keywords: multimodal communication, linguistics ., gesture studies., emojis., verbal communication., digital

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