Search results for: Public space

Authors: Julius Steinkopf, Eric Rost, Aike Hessel, Sonia Lippke

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Objective: This study examined possible determinants of return to work (RTW) in individuals who participated in a medical rehabilitation program longitudinally over a time period of six months. Design/methodology/approach: N=1,044 rehabilitants were included in the baseline measurement in terms of completing a questionnaire during their medical rehabilitation. About 30% (n=350) have remained in the study in terms of participating in computer-assisted telephone interviewing (CATI) six months later. Frequency analyses and Regression analyses were run. Findings: About 70% of the rehabilitants returned to work six months after rehabilitation. Regression analyses revealed that the RTW rates were significantly predicted by gender (OR=0.12, men were more likely to return), perceived social support (OR=3.01) and current physical functioning (OR=1.25). Furthermore RTW motives, like expected monetary rewards (OR=25.2) and feelings of being needed (OR=0.18) same as motives for not returning to work (nRTW), like the wish to stop working in order to spend time with the spouse (OR=0.13) or a lack of enjoyment of work (OR=3.81), significantly predicted return to work rates. Life satisfaction, self-efficacy beliefs, mental health, current income, educational background or age did not significantly increase explained variance (all ps > .05). Practical implications: Taking theses predictors into account provides options to increase the effectiveness of interventions aiming at increasing RTW: Medical rehabilitations should not only aim at improving the physical functioning but also to enhance beneficial motives and social support as well as support women specifically in order to improve the effectiveness of medical rehabilitation and public health interventions. Originality/value: Illness-caused work absences are related to high financial costs and individual burden. Despite of the public health and societal implications, this is one of the very few studies investigating systematically fitness and health for the return to work.

Keywords: gender, fitness, health, physical functioning

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Authors: Hamed D. Alsharari

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This paper first analyses the current status regarding electrical engineering higher education in Saudi Arabian public universities. The paper focuses on the two EE sub-specialties most commonly present in Saudi Arabia, power and communications and discusses recruitment in this field, showing various market and employment demand for EE.

Keywords: communications, electrical engineering, higher education, Saudi Arabia, power

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Authors: Khodr Fakih

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The Ombudsman is a procedural mechanism that provides a different approach of dispute resolution. The ombudsman primarily deals with specific grievances from the public against governmental injustice and misconduct. The ombudsman theory is considered an important instrument to any democratic government. This is true since it improves the transparency of the governmental activities in a world in which executive power are rising. Many countries have adopted the concept of Ombudsman but under different terminologies. This paper will provide the different types of Ombudsman and the common activities/processes of fulfilling their mandates.

Keywords: administration, citizens, government, mediator, ombudsman, presidential mediator

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Authors: Seung-Jun Yu, Hwan-Jun Choi, Hyoung-Kyu Song

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Among spatial diversity scheme, orthogonal space-time block code (OSTBC) and cyclic delay diversity (CDD) have been widely studied for the cooperative wireless relaying system. However, conventional OSTBC and CDD cannot cope with change in the number of relays owing to low throughput or error performance. In this paper, we propose a cooperative cyclic delay diversity (CDD) scheme that use hierarchical modulation at the source and adaptive modulation based on cyclic redundancy check (CRC) code at the relays.

Keywords: adaptive modulation, cooperative communication, CDD, OSTBC

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Authors: Michael Sonne Kristensen, Frank Loesche, James Foster, Elif Ozcan, Judy Edworthy

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Auditory alarms play an integral role in intensive care nurses’ daily work. Most medical devices in the intensive care unit (ICU) are designed to produce alarm sounds in order to make nurses aware of immediate or prospective safety risks. The utilisation of sound as a carrier of crucial patient information is highly dependent on nurses’ presence - both physically and mentally. For ICU nurses, especially the ones who work with stationary alarm devices at the patient bed space, it is a challenge to display ‘appropriate’ alarm responses at all times as they have to navigate with great flexibility in a complex work environment. While being primarily responsible for a small number of allocated patients they are often required to engage with other nurses’ patients, relatives, and colleagues at different locations inside and outside the unit. This work explores the social strategies used by a team of nurses to comprehend and react to the information conveyed by the alarms in the ICU. Two main research questions guide the study: To what extent do alarms from a patient bed space reach the relevant responsible nurse by direct auditory exposure? By which means do responsible nurses get informed about their patients’ alarms when not directly exposed to the alarms? A comprehensive video-ethnographic field study was carried out to capture and evaluate alarm-related events in an ICU. The study involved close collaboration with four nurses who wore eye-level cameras and ear-level binaural audio recorders during several work shifts. At all time the entire unit was monitored by multiple video and audio recorders. From a data set of hundreds of hours of recorded material information about the nurses’ location, social interaction, and alarm exposure at any point in time was coded in a multi-channel replay-interface. The data shows that responsible nurses’ direct exposure and awareness of the alarms of their allocated patients vary significantly depending on work load, social relationships, and the location of the patient’s bed space. Distributed listening is deliberately employed by the nursing team as a social strategy to respond adequately to alarms, but the patterns of information flow prompted by alarm-related events are not uniform. Auditory Spatiotemporal Trajectory (AST) is proposed as a methodological label to designate the integration of temporal, spatial and auditory load information. As a mixed-method metrics it provides tangible evidence of how nurses’ individual alarm-related experiences differ from one another and from stationary points in the ICU. Furthermore, it is used to demonstrate how alarm-related information reaches the individual nurse through principles of social and distributed cognition, and how that information relates to the actual alarm event. Thereby it bridges a long-standing gap in the literature on medical alarm utilisation between, on the one hand, initiatives to measure objective data of the medical sound environment without consideration for any human experience, and, on the other hand, initiatives to study subjective experiences of the medical sound environment without detailed evidence of the objective characteristics of the environment.

Keywords: auditory spatiotemporal trajectory, medical alarms, social cognition, video-ethography

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Authors: K. A. Ghazaryan, H. S. Movsesyan, N. P. Ghazaryan

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The present study was aimed in assessing the heavy metal pollution of the soils around Agarak copper-molybdenum mine complex and related environmental risks. This mine complex is located in the south-east part of Armenia, and the present study was conducted in 2013. The soils of the five riskiest sites of this region were studied: surroundings of the open mine, the sites adjacent to processing plant of Agarak copper-molybdenum mine complex, surroundings of Darazam active tailing dump, the recultivated tailing dump of “ravine - 2”, and the recultivated tailing dump of “ravine - 3”. The mountain cambisol was the main soil type in the study sites. The level of soil contamination by heavy metals was assessed by Contamination factors (Cf), Degree of contamination (Cd), Geoaccumulation index (I-geo) and Enrichment factor (EF). The distribution pattern of trace metals in the soil profile according to Cf, Cd, I-geo and EF values shows that the soil is much polluted. Almost in all studied sites, Cu, Mo, Pb, and Cd were the main polluting heavy metals, and this was conditioned by Agarak copper-molybdenum mine complex activity. It is necessary to state that the pollution problem becomes pressing as some parts of these highly polluted region are inhabited by population, and agriculture is highly developed there; therefore, heavy metals can be transferred into human bodies through food chains and have direct influence on public health. Since the induced pollution can pose serious threats to public health, further investigations on soil and vegetation pollution are recommended. Finally, Cf calculating based on distance from the pollution source and the wind direction can provide more reasonable results.

Keywords: Agarak copper-molybdenum mine complex, heavy metals, soil contamination, enrichment factor (EF), Armenia

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Authors: D. I. Akintayo, C. O. Aje

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This study investigated the moderating influence of gender difference and conflict resolution strategy preference on managers` efficiency in managing industrial conflict in work organizations in South-Western Nigeria. This was for the purpose of ascertaining the relevance of gender difference and conflict resolution strategy preference to managerial efficiency towards ensuring sustainable industrial peace and harmonious labour-management relations at workplaces in Nigeria. Descriptive ex-post-facto research design was adopted for the study. A total of 185 respondents were selected for the study using purposive stratified sampling technique. A set of questionnaire titled ‘Rahim Organizational Conflict Inventory’ (ROCI) and Managerial Conflict Efficiency Scale (MCES) were adopted for the study. The three generated hypotheses were tested using Pearson Product Moment Correlation and t-test statistical methods. The findings of the study revealed that: A significant relationship exists between gender difference and conflict management preference of the managers(r = 0.644; P < 0.05). I t was also found that there was no significant difference between male and female managers’ conflict management strategy preference (t (181) = 11.08; P > 0.05).The finding reveals that there is no significant difference between female and male managers’ conflict management efficiency on the basis of conflict management preference of the managers (t (181) = 10.23; P > 0.05). Based on the findings of the study, it is recommended that collective bargaining strategy should be encouraged as conflict resolution strategy in order to guarantee effective management of industrial conflict and harmonious labour-management relations. Also, both male and female managers should be empowered to be appointed to managerial positions and should avoid the use of coercion, competition, aggressiveness and pro-task in the course of managing industrial conflict. Rather, persuasion, compromising, relational, lobbying and participatory approaches should be employed during collective bargaining process in order to foster effective management of conflict at workplaces.

Keywords: conflict management, gender difference, managerial studies, public organization and managers, strategy preference

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Authors: Christian Rathgeber, Franz Winkler, Dirk Odenthal, Steffen Müller

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In this contribution a structure for high level lateral vehicle tracking control based on the disturbance observer is presented. The structure is characterized by stationary compensating side forces disturbances and guaranteeing a cooperative behavior at the same time. Driver inputs are not compensated by the disturbance observer. Moreover the structure is especially useful as it robustly stabilizes the vehicle. Therefore the parameters are selected using the Parameter Space Approach. The implemented algorithms are tested in real world scenarios.

Keywords: disturbance observer, trajectory tracking, robust control, autonomous driving, cooperative driving

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Authors: Mladen Djuric, Ivan Janicijevic, Sasa Lazarevic

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One of the organizational issues is how to develop and shape decision making and knowledge management systems which will continually avoid traps of both paralyses by analyses“ and extinction by instinct“, the concepts that are a kind of tolerant limits anti-patterns which define what we can call decision making and knowledge management patterns control zone. This paper discusses potentials for development of a core base for recognizing, capturing, and analyzing anti-patterns in the educational organization, thus creating a space for improving decision making and knowledge management processes in education.

Keywords: anti-patterns, decision making, education, knowledge management

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Authors: Pankaj Dhiman, Simranjeet Kaur

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This research paper presents a comprehensive sentiment analysis of social media responses to videos on Facebook, YouTube, Twitter, and Instagram during the 2024 Indian general elections. The study focuses on the sentiment patterns of voters towards the National Democratic Alliance (NDA) and The Indian National Developmental Inclusive Alliance (INDIA) on these platforms. The analysis aims to understand the impact of social media on voter sentiment and its correlation with the election outcome. The study employed a mixed-methods approach, combining both quantitative and qualitative methods. With a total of 200 posts analysed during general election-2024 final phase, the sentiment analysis was conducted using natural language processing (NLP) techniques, including sentiment dictionaries and machine learning algorithms. The results show that NDA received significantly more positive sentiment responses across all platforms, with a positive sentiment score of 47% compared to INDIA's score of 38.98 %. The analysis also revealed that Twitter and YouTube were the most influential platforms in shaping voter sentiment, with 60% of the total sentiment score coming from these two platforms. The study's findings suggest that social media sentiment analysis can be a valuable tool for understanding voter sentiment and predicting election outcomes. The results also highlight the importance of social media in shaping public opinion and the need for political parties to engage effectively with voters on these platforms. The study's implications are significant, as they indicate that social media can be a key factor in determining the outcome of elections. The findings also underscore the need for political parties to develop effective social media strategies to engage with voters and shape public opinion.

Keywords: Indian Elections-2024, NDA, INDIA, sentiment analysis, social media, democracy

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Authors: Murat Sözen

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It is not at all difficult to estimate which level today’s technology reaches considering that humankinds space-faring in early 1950s. Technology is a means to help achieve goals and people can produce systems on their physical and mental abilities. Needed and used as tools in all areas of life and became a necessity and dependency, technology, widely used in the military field. To be a revolutionary change in the military matters, opportunities offered by technology should be put into practice. Tech makes weapons, sensors, platforms and soldiers carrying them more effective. To increase this efficiency in the battlefield defense industry is seeking every advantage of technology. In this study, the applicability of existing and on-going augmented reality applications for Armed Forces will be evaluated.

Keywords: augmented reality, battlefield, military, virtual reality

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Authors: Salimah Hasnah, Namratha Radhakrishnan

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Communities play a vital role in mobilizing people and resources for the benefit of all. Since time immemorial, communities have been spear heading different activities ranging from disaster management, palliative care, local economic development and many more with laudable success. Urban agriculture is one such activity where communities can prove to make a real difference. Farming activities in cities across different developed countries have proved to have favorable outcomes in the form of increased food security, neighborhood revitalization, health benefits and local economic growth. However, urban agriculture in the developing nations have never been prioritized as an important planning tool to cater to the basic needs of the public. Urban agricultural practices are being carried out in a fragmented fashion without a formal backing. The urban dwellers rely heavily on their far-off rural counterparts for daily food requirements. With the onset of the pandemic and the recurring lockdowns, the significance of geographic proximity and its impact on the availability of food to the public are gradually being realized around the globe. This warrants a need for localized food systems by shortening the distance between production and consumption of food. The significance of communities in realizing these urban farming benefits is explored in this paper. A case-study approach is adopted to understand how different communities have overcome barriers to urban farming in cities. The applicability of these practices is validated against the state of Kerala in India wherein different community centered approaches have been successful in the past. The existing barriers are assessed and way forward to achieve a self-sufficient localized food systems is formulated with the key lessons from the case studies. These recommendations will be helpful to successfully establish and sustain farming activities in urban areas by leveraging the power of communities.

Keywords: community-centric, COVID-19, drivers and barriers, local food system, urban agriculture

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Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, G. A. P. Thé

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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

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Authors: Urooj Saeed, Sajid Rashid Ahmad, Iqra Khalid, Sahar Mirza, Imtiaz Younas

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Pakistan, a flood-prone country, has experienced worst floods in the recent past which have caused extensive damage to the urban and rural areas by loss of lives, damage to infrastructure and agricultural fields. Poor flood management system in the country has projected the risks of damages as the increasing frequency and magnitude of floods are felt as a consequence of climate change; affecting national economy directly or indirectly. To combat the needs of flood emergency, this paper focuses on remotely sensed data based approach for rapid mapping and monitoring of flood extent and its damages so that fast dissemination of information can be done, from local to national level. In this research study, spatial extent of the flooding caused by heavy rains of 2014 has been mapped by using space borne data to assess the crop damages and affected population in sixteen districts of Punjab. For this purpose, moderate resolution imaging spectroradiometer (MODIS) was used to daily mark the flood extent by using Normalised Difference Water Index (NDWI). The highest flood value data was integrated with the LandScan 2014, 1km x 1km grid based population, to calculate the affected population in flood hazard zone. It was estimated that the floods covered an area of 16,870 square kilometers, with 3.0 million population affected. Moreover, to assess the flood damages, Object Based Image Analysis (OBIA) aided with spectral signatures was applied on Landsat image to attain the thematic layers of healthy (0.54 million acre) and damaged crops (0.43 million acre). The study yields that the population of Jhang district (28% of 2.5 million population) was affected the most. Whereas, in terms of crops, Jhang and Muzzafargarh are the ‘highest damaged’ ranked district of floods 2014 in Punjab. This study was completed within 24 hours of the peak flood time, and proves to be an effective methodology for rapid assessment of damages due to flood hazard

Keywords: flood hazard, space borne data, object based image analysis, rapid damage assessment

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Authors: Omotoyosi Bilikies Ilori, Adekunle Saheed Ajisebiyawo

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After the Second World War, there was an emergence of a new stage of capitalist globalization with its Neo-liberal ideology. There were global economic and political restructurings that affected third-world countries like Nigeria. Neo-liberalism is the driving force of globalization, which is the latest manifestation of imperialism that engenders endemic poverty in Nigeria. Poverty is severe and widespread in Nigeria. Poverty entails a situation where a person lives on less than one dollar per day and has no access to basic necessities of life. Poverty is inhuman and a breach of human rights. The Nigerian government initiated some strategies in the past to help in poverty reduction. Neo-liberalism manifested in the Third World, such as Nigeria, through the privatization of public enterprises, trade liberalization, and the rollback of the state investments in providing important social services. These main ideas of Neo-liberalism produced poverty in Nigeria and also encouraged the abandonment of the social contract between the government and the people. There is thus a gap in the provision of social services and subsidies for the masses, all of which Neo-liberal ideological positions contradict. This paper is a qualitative study which draws data from secondary sources. The theoretical framework is anchored on the market theory of capitalist globalization and public choice theory. The objectives of this study are to (i) examine the impacts of Neo-liberalism on poverty in Nigeria as a typical example of a Third World country and (ii) find out the effects of Neo-liberalism on the provision of social services and subsidies and employment. The findings from this study revealed that (i) the adoption of the Neo-liberal ideology by the Nigerian government has led to increased poverty and poor provision of social services and employment in Nigeria; and (ii) there is an increase in foreign debts which compounds poverty situation in Nigeria. This study makes the following recommendations: (i) Government should adopt strategies that are pro-poor to eradicate poverty; (ii) The Trade Unions and the masses should develop strategies to challenge Neo-liberalism and reject Neo-liberal ideology.

Keywords: neo-liberalism, poverty, employment, poverty reduction, structural adjustment programme

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Authors: Matthew Venunye Fianu, Jerry Fiave, Ebenezer Kye-Mensah, Dacosta Aboagye, Felix Osei-Sarpong

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Introduction: Road traffic accidents involving motorbikes are a priority public health concern in Ghana. While there are local initiatives to address this public health challenge, little is known about motor riders’ knowledge and compliance with road safety regulations (RSR) and their association with RTAs. The aim of this study was, therefore, to assess motorbike riders’ knowledge and compliance with RSRs. Methodology: Motorbike riders in Hohoe Municipality were randomly sampled in a cross-sectional study in June 2022. Data were collected from 237 riders using a questionnaire designed in Kobocollect and administered by ten research assistants. A score of 70% or less is considered low for knowledge and compliance. The data were exported into Excel and imported into STATA 17 for analysis. A chi-square test was performed to generate descriptive and inferential statistics to establish the association between independent and dependent variables. Results: All 237 respondents were male, and each of them completed the questionnaire representing a 100% response rate. Participants who had knowledge about speed limit at different segments of the road were 59(24.9%), the use of helmet were 124 (52.3%), and alcohol use were 152 (64.1%). Participants who complied with regulations on speed limits, helmet use, and alcohol use were 108 (45.6%), 179(75.5%), and 168(70.8%), respectively. Riders who had at least junior high school education were 2.43 times more likely to adhere to RSR [cOR =2.43(95%CI= 1.15-6.33) p= 0.023] than those who had less education. Similarly, riders who had high knowledge about RSR were 2.07 times more likely to comply with RSR than those who had less knowledge [AOR= -2.07 (95% CI= 0.34-0.97), p=0.038]. Conclusion: Motor riders in the Hohoe Municipality had low knowledge as well as low compliance with road safety regulations. This could be a contributor to road traffic accidents. It is therefore recommended that road safety regulatory authorities and relevant stakeholders enhance the enforcement of RSR. There should also be country-specific efforts to increase awareness among all motor riders, especially those with less than junior high school education.

Keywords: compliance, motor riders, road safety regulations, road traffic accident

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Authors: Kalimah Ibrahiim, Israa Elmousa

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This study employed the world café method alongside semi-structured interviews within a 'conversation café' setting to engage stakeholders from the public health and primary care sectors. The objective was to collaboratively explore strategies to improve outcomes for young people not in education, employment, or training (NEET). The discussions were aimed at identifying the underlying causes of disparities faced by NEET individuals, exchanging experiences, and formulating community-driven solutions to bolster preventive efforts and shape policy initiatives. A thematic analysis of the qualitative data gathered emphasized the importance of community problem-solving through the exchange of ideas and reflective discussions. Healthcare professionals reflected on their potential roles, pinpointing a significant gap in understanding the specific needs of the NEET population and the unclear distribution of responsibilities among stakeholders. The results underscore the necessity for a unified approach in primary care and the fostering of multi-agency collaborations that focus on addressing social determinants of health. Such strategies are critical not only for the immediate improvement of health outcomes for NEET individuals but also for informing broader policy decisions that can have long-term benefits. Further research is ongoing, delving deeper into the unique challenges faced by this demographic and striving to develop more effective interventions. The study advocates for continued efforts to integrate insights from various sectors to create a more holistic and effective response to the needs of the NEET population, ensuring that future strategies are informed by a comprehensive understanding of their circumstances and challenges.

Keywords: multi-agency working, primary care, public health, social inequalities

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Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

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Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: Ashwini Mohan, Haris Batley

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An orthodontic index is used to rate or categorise an individual’s occlusion using a numeric or alphanumeric score. Indexing of malocclusions and their correction is important in epidemiology, diagnosis, communication between clinicians as well as their patients and assessing treatment outcomes. Many useful indices have been put forward, but to the author’s best knowledge, no one method to this day appears to be equally suitable for the use of epidemiologists, public health program planners and clinicians. This article describes the common clinical orthodontic indices and classifications used in United Kingdom.

Keywords: classification, indices, orthodontics, validity

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Authors: Amritee Bora, B. S. Mipun

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Land degradation is often used to describe the land environmental phenomena that reduce land’s original productivity both qualitatively and quantitatively. The study of land degradation vulnerability primarily deals with “Environmentally Sensitive Areas” (ESA) and the amount of topsoil loss due to erosion. In many studies, it is observed that the assessment of the existing status of land degradation is used to represent the vulnerability. Moreover, it is also noticed that in most studies, the primary emphasis of land degradation vulnerability is to assess its sensitivity to soil erosion only. However, the concept of land degradation vulnerability can have different objectives depending upon the perspective of the study. It shows the extent to which changes in land use land cover can imprint their effect on the land. In other words, it represents the susceptibility of a piece of land to degrade its productive quality permanently or in the long run. It is also important to mention that the vulnerability of land degradation is not a single factor outcome. It is a probability assessment to evaluate the status of land degradation and needs to consider both biophysical and human induce parameters. To avoid the complexity of the previous models in this regard, the present study has emphasized on to generate a simplified model to assess the land degradation vulnerability in terms of its current human population pressure, land use practices, and existing biophysical conditions. It is a “Mixed-Method” termed as the land degradation vulnerability index (LDVi). It was originally inspired by the MEDALUS model (Mediterranean Desertification and Land Use), 1999, and Farazadeh’s 2007 revised version of it. It has followed the guidelines of Space Application Center, Ahmedabad / Indian Space Research Organization for land degradation vulnerability. The model integrates the climatic index (Ci), vegetation index (Vi), erosion index (Ei), land utilization index (Li), population pressure index (Pi), and cover management index (CMi) by giving equal weightage to each parameter. The final result shows that the very high vulnerable zone primarily indicates three (3) prominent circumstances; land under continuous population pressure, high concentration of human settlement, and high amount of topsoil loss due to surface runoff within the study sites. As all the parameters of the model are amalgamated with equal weightage further with the help of regression analysis, the LDVi model also provides a strong grasp of each parameter and how far they are competent to trigger the land degradation process.

Keywords: population pressure, land utilization, soil erosion, land degradation vulnerability

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Authors: Ladda Thiamwong, Renata Komalasari

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Falls are the leading cause of disability and hospitalization in low-income older adults. Fear of falling is present in 20% to 85 % of older adults and has been identified as an independent risk factor of fall risk, activity restriction, and loss of independence. About 12% of American older adults have subjective cognitive decline. Cognitive impairment is also an established factor of fall risk. However, it is unclear whether measures of fear of falling and subjective cognitive decline have the greatest association with fall risk in low-income older adults. The aim of this study was to evaluate the association between fear of falling, subjective cognitive decline-functional performance (SCD-FP), and fall risk using simple screening tools. In this cross-section study, we collected data from community-dwelling older adults 60 years or older in low-income settings in Central Florida, and 86 participants were included in the data analysis. Fear of falling was assessed by the Short Fall Efficacy Scale- International (Short FES-I) with seven items. Subjective cognitive decline-functional performance (SCD-FP) was assessed by a self-reported experience of worsening or more frequent confusion or memory loss in the past 12 months and its functional implications. Fall risk was evaluated by the Centers for Disease Control and Prevention (CDC)'s Stay Independent checklist with 12 items. The majority of participants were female, and more than half of the participants were African American. More than half of the participants had a higher school degree or higher, and less than 20% had no financial problems. Less than 30% of the participants perceived their general health as very good- excellent. More than half of the participants lived alone, and less than 15% lived with a partner or spouse. About 60% of the participants had hypertension, 40% had diabetes, 16% had cancer, and 50% had arthritis. About 30% of the participants had difficulty walking up ten steps without resting, more than 40% felt unsteady when walking, and 30% had been advised to use a cane or walker to get around safely. Regression analysis showed that fall risk was associated with fear of falling ( = .524, p <.001) and subjective cognitive decline-functional performance ( = .465, p =.027). The structure coefficient showed that fear of falling (rs2 = .922) was a stronger predictor of fall risk than subjective cognitive decline-functional performance (rs2= .200). Fear of falling and subjective cognitive decline-functional performance are growing public health issues, and addressing those issues is a public priority. Proactive screening for fear of falling and subjective cognitive decline-functional performance is critical in fall prevention. A combination of all three self-reported tools (Short FES-I, SCD-FP, and CDC's Stay Independent checklist) takes less than 5 minutes to complete. Primary care providers or public health professionals should consider including these tools to screen fear of falling and subjective cognitive decline-functional performance as part of fall risk assessment, especially in low-income settings. Thus, encouraging older adults and healthcare professionals to discuss fear of falling, subjective cognitive decline, and fall risk during routine medical office visits.

Keywords: falls, fall risk, fear of falling, cognition, subjective cognitive decline, low-income, older adults, community, screening, nursing, primary care

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Authors: T. Hansen

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Many consumers are uncertain of what financial borrowing behavior may serve their interests in the best way. This is important since consumers’ risky financial decisions may not only negatively affect their short-term liquidity but may haunt them for years after they are made. Obviously, this is especially critical for young adults who often carry large amounts of student loans or credit card debt, which in turn may hinder their future ability to obtain financial healthiness. Even though factors such as financial knowledge, attitudes towards risk, gender, and motivations of borrowing, among others, are known to influence consumer borrowing behavior, no existing model comprehensibly describes the mechanisms behind young adults’ risky borrowing behavior. This is unfortunate since a better understanding of the relationships between such factors and young adults’ risky borrowing behavior may be of value to financial service providers and financial authorities aiming to improve young adults’ borrowing behavior. This research extends prior research by developing a conceptual framework for the purpose of understanding young adults’ risky borrowing behavior. The study is based on two survey samples comprising 488 young adults aged 18-25 who have not obtained a risky loan (sample 1) and 214 young adults aged 18-25 who already have obtained a risky loan (sample 2), respectively. The results suggest several psychological, sociological, and behavioral factors that may influence young adults’ intentional risky borrowing behavior, which in turn is shown to affect actualized risky borrowing behavior. We also found that the relationship between intentional risky borrowing behavior and actualized risky borrowing behavior is negatively moderated by perceived risk – but not by perceived complexity. In particular, the results of this study indicate that public policy makers, banks and financial educators should seek to eliminate less desirable social norms on how to behave financially. In addition, they should seek to enhance young adults’ risky borrowing perceived risk, thereby preventing that intentional risky borrowing behavior translates into actualized risky behavior.

Keywords: financial services, risky borrowing behavior, young adults, financial knowledge, social norms, perceived risk, financial trust, public financial policy

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Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. The 2022 Annual Homeless Assessment Report (AHAR) to Congress highlighted alarming statistics, emphasizing the need for effective decision-making and budget allocation within local planning bodies known as Continuums of Care (CoC). This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical regression

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Authors: Elragig Aiman, Dreiwi Hanan, Townley Stuart, Elmabrook Idriss

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In this paper, we reconsider the analysis of the Oregonator model. We highlight an error in this analysis which leads to an incorrect depiction of the parameter region in which diffusion driven instability is possible. We believe that the cause of the oversight is the complexity of stability analyses based on eigenvalues and the dependence on parameters of matrix minors appearing in stability calculations. We regenerate the parameter space where Turing patterns can be seen, and we use the common Lyapunov function (CLF) approach, which is numerically reliable, to further confirm the dependence of the results on diffusion coefficients intensities.

Keywords: diffusion driven instability, common Lyapunov function (CLF), turing pattern, positive-definite matrix

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Authors: John Allard, Alex Rich, Iris Aguilar, Zachary Dodds

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With this paper we present several experiences deploying novel, low-cost resources for computing with 3D spatial models. Certainly, computing with 3D models undergirds some of our field’s most important contributions to the human experience. Most often, those are contrived artifacts. This work extends that tradition by focusing on novel resources that deliver uncontrived models of a system’s current surroundings. Atop this new capability, we present several projects investigating the student-accessibility of the computational tools for reasoning about the 3D space around us. We conclude that, with current scaffolding, real-world 3D models are now an accessible and viable foundation for creative computational work.

Keywords: 3D vision, matterport model, real-world 3D models, mathematical and computational methods

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Authors: Duckyong Kim, Jong Kang Park, Jong Tae Kim

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DOA (Direction of Arrival) estimation is an important method in array signal processing and has a wide range of applications such as direction finding, beam forming, and so on. In this paper, we briefly introduce the MUSIC (Multiple Signal Classification) Algorithm, one of DOA estimation methods for analyzing several targets. Then we apply the MUSIC algorithm to the two-dimensional antenna array to analyze DOA estimation in 3D space through MATLAB simulation. We also analyze the design factors that can affect the accuracy of DOA estimation through simulation, and proceed with further consideration on how to apply the system.

Keywords: DOA estimation, MUSIC algorithm, spatial spectrum, array signal processing

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Authors: Anetta Caplanova, Eva Sirakovova, Estera Szakadatova

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Non-payment of taxes and fees represents a problem, which occurs at national and local government levels in many countries. An effective tax collection is key for generating government and local government budget revenues to finance public services and infrastructure; thus, there is the need to address this problem. The standard approach considers as a solution raising taxes/fees to boost public revenues, which may be politically challenging and time-consuming to implement. An alternative approach is related to using behavioral interventions. These can be usually implemented relatively quickly, and in most cases, they are associated with low cost. In the paper, we present the results of the behavioral experiment focused on raising the level of compliance with the payment of garbage collection fees in a selected municipality in the Slovak Republic. The experiment was implemented using the leaflets sent to residential households together with the invoice for the garbage collection in the municipality Hlohovec, Western Slovakia, in Spring 2021. The sample of about 10000 households was divided into three random groups, a control group and two intervention groups. Households in intervention group 1 were sent a leaflet using the social norm nudge, while households in intervention group 2 were sent a leaflet using the deterrence nudge. The social norm framing leaflet pointed out that in the municipality, the prevailing majority of people paid the garbage collection fee and encouraged recipients to join this majority. The deterrent leaflet reminded the recipients that if they did not pay the fee on time, enforcement proceedings would follow. This was aimed to increase the subjective perception of citizens of the enforcement proceedings in case of noncompliance. In the paper, we present and discuss the results from the experiment and formulate relevant generalizations for other municipalities.

Keywords: municipal governments, garbage fee collection, behavioural intervention, social norm, deterrence nudge

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Authors: Ricardo A. Martins, Matheus S. da Silva, Gabriel H. F. Iarossi, Helen C. M. Senefonte, Cinthyan R. S. C. de Barbosa

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This paper is the development of a concept of the man/robot interaction. More accurately in developing of an autistic child that have more troubles with interaction, here offers an efficient solution, even though simple; however, less studied for this public. This concept is based on code applied thought out the Lego NXT kit, built for the interpretation of the robot, thereby can create this interaction in a constructive way for children suffering with Autism.

Keywords: lego NXT, interaction, BricX, autismo, ANN (Artificial Neural Network), MLP back propagation, hidden layers

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Authors: Ekaterina Malova

Abstract:

Type 1 diabetes (T1D) is a chronic illness requiring immense lifestyle changes to reduce the chance of life-threatening complications. Moving to a college may be the first time for a young adult with T1D to take responsibility for all the aspects of their diabetes care. In addition, people with T1D constantly face stigmatization and discrimination as a result of their health condition, which puts additional pressure on young adults with T1D. Hence, omissions in diabetes self-care often occur during the time of transition to college when both the social and physical environment of young adults changes drastically and contribute to the fact that emerging young adults remain one of the age groups with the highest hemoglobin levels and poorest diabetes control. However, despite potential severe health risks caused by a lack of proper diabetes self-care, little is known about the experiences of emerging adults embarking on a higher education journey as this population. Thus, young adults with type 1 diabetes are a 'forgotten group,' meaning that their experiences are rarely addressed by researchers. Given that self-disclosure and information-seeking can be challenging for individuals with stigmatized illnesses, online platforms like YouTube have become a popular medium of self-disclosure and information-seeking for people living with T1D. Thus, this study aims to provide an analysis of experiences that college students with T1D choose to share with the general public online and explore the nature of information being communicated by college students with T1D to the online community in personal narratives posted on YouTube. A systematic approach was used to retrieve a video sample by searching YouTube with keywords 'type 1 diabetes' and 'college,' with results ordered by relevance. A total of 18 videos were saved. Video lengths ranged from 2 to 28 minutes. The data were coded using NVivo. Video transcripts were coded and analyzed utilizing the thematic analysis method. Three key themes emerged from thematic analysis: 1) Advice, 2) Personal experience, and 3) Things I wish everyone knew about T1D. In addition, Theme 1 was divided into subtopics to differentiate between the most common types of advice: 1) Overcoming stigma and b) Seeking social support. The identified themes indicate that two groups of the population can potentially benefit from watching students’ video testimonies: 1) lay public and 2) other students with T1D. Given that students in the videos reported a lack of T1D education in the lay public, such video narratives can serve important educational purposes and reduce health stigma, while perceived similarity and identification with students in the videos may facilitate the transition of health information to other individuals with T1D and positively affect their diabetes routine. Thus, online video narratives can potentially serve both educational and persuasive purposes, empowering students with T1D to stay in control of T1D while succeeding academically.

Keywords: type 1 diabetes, college students, health communication, transition period

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Authors: Elisabetta Ceretti, Silvia Bonizzoni, Alberto Bonetti, Milena Villarini, Marco Verani, Maria Antonella De Donno, Sara Bonetta, Umberto Gelatti

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Introduction: Air pollution is a global problem. In 2013, the International Agency for Research on Cancer (IARC) classified air pollution and particulate matter as carcinogenic to human. The study of the health effects of air pollution in children is very important because they are a high-risk group in terms of the health effects of air pollution and early exposure during childhood can increase the risk of developing chronic diseases in adulthood. The MAPEC_LIFE (Monitoring Air Pollution Effects on Children for supporting public health policy) is a project founded by EU Life+ Programme which intends to evaluate the associations between air pollution and early biological effects in children and to propose a model for estimating the global risk of early biological effects due to air pollutants and other factors in children. Methods: The study was carried out on 6-8-year-old children living in five Italian towns in two different seasons. Two biomarkers of early biological effects, primary DNA damage detected with the comet assay and frequency of micronuclei, were investigated in buccal cells of children. Details of children diseases, socio-economic status, exposures to other pollutants and life-style were collected using a questionnaire administered to children’s parents. Child exposure to urban air pollution was assessed by analysing PM0.5 samples collected in the school areas for PAHs and nitro-PAHs concentration, lung toxicity and in vitro genotoxicity on bacterial and human cells. Data on the chemical features of the urban air during the study period were obtained from the Regional Agency for Environmental Protection. The project created also the opportunity to approach the issue of air pollution with the children, trying to raise their awareness on air quality, its health effects and some healthy behaviors by means of an educational intervention in the schools. Results: 1315 children were recruited for the study and participate in the first sampling campaign in the five towns. The second campaign, on the same children, is still ongoing. The preliminary results of the tests on buccal mucosa cells of children will be presented during the conference as well as the preliminary data about the chemical composition and the toxicity and genotoxicity features of PM0.5 samples. The educational package was tested on 250 children of the primary school and showed to be very useful, improving children knowledge about air pollution and its effects and stimulating their interest. Conclusions: The associations between levels of air pollutants, air mutagenicity and biomarkers of early effects will be investigated. A tentative model to calculate the global absolute risk of having early biological effects for air pollution and other variables together will be proposed and may be useful to support policy-making and community interventions to protect children from possible health effects of air pollutants.

Keywords: air pollution exposure, biomarkers of early effects, children, public health policy

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