Search results for: radiation patterns

Authors: Raudone Lina, Raudonis Raimondas, Gaivelyte Kristina, Pukalskas Audrius, Janulis Valdimaras, Viskelis Pranas

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Sorbus L. species are widely distributed in the Northern hemisphere and have been used for medicinal purposes in various traditional medicine systems and as food ingredients. Various Sorbus L. raw materials, fruits, leaves, inflorescences, barks, possess diuretic, anti-inflammatory, hypoglycemic, anti-diarrheal and vasoprotective activities. Phenolics, to whom main pharmacological activities are attributed, are compounds of interest due to their notable antioxidant activity. The aim of this study was to determine the antioxidant profiles of fruits and leaves of selected Sorbus L. species (S. anglica, S. aria f. latifolia, S. arranensis, S. aucuparia, S. austriaca, S. caucasica, S. commixta, S. discolor, S. gracilis, S. hostii, S. semi-incisa, S. tianschanica) and to identify the phenolic compounds with potent contribution to antioxidant activity. Twenty two constituents were identified in Sorbus L. species using ultra high performance liquid chromatography coupled to quadruple and time-of-flight mass spectrometers (UPLC–QTOF–MS). Reducing activity of individual constituents was determined using high performance liquid chromatography (HPLC) coupled to post-column FRAP assay. Signicantly greatest trolox equivalent values corresponding up to 45% of contribution to antioxidant activity were assessed for neochlorogenic and chlorogenic acids, which were determined as markers of antioxidant activity in samples of leaves and fruits. Characteristic patterns of antioxidant profiles obtained using HPLC post-column FRAP assay significantly depend on specific Sorbus L. species and raw materials and are suitable for equivalency research of Sorbus L. fruits and leaves. Selecting species and target plant organs with richest phenolic composition and strongly expressed antioxidant power is the first step in further research of standardized extracts.

Keywords: FRAP, antioxidant, phenolic, Sorbus L., chlorogenic acid, neochlorogenic acid

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Authors: Sahar Heidary

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Radiography and radiotherapy have emerged as crucial pillars of modern medical practice, revolutionizing diagnostics and treatment for a myriad of health conditions. This abstract highlights the pivotal role of radiography and radiotherapy in favor of healthcare and society. Radiography, a non-invasive imaging technique, has significantly advanced medical diagnostics by enabling the visualization of internal structures and abnormalities within the human body. With the advent of digital radiography, clinicians can obtain high-resolution images promptly, leading to faster diagnoses and informed treatment decisions. Radiography plays a pivotal role in detecting fractures, tumors, infections, and various other conditions, allowing for timely interventions and improved patient outcomes. Moreover, its widespread accessibility and cost-effectiveness make it an indispensable tool in healthcare settings worldwide. On the other hand, radiotherapy, a branch of medical science that utilizes high-energy radiation, has become an integral component of cancer treatment and management. By precisely targeting and damaging cancerous cells, radiotherapy offers a potent strategy to control tumor growth and, in many cases, leads to cancer eradication. Additionally, radiotherapy is often used in combination with surgery and chemotherapy, providing a multifaceted approach to combat cancer comprehensively. The continuous advancements in radiotherapy techniques, such as intensity-modulated radiotherapy and stereotactic radiosurgery, have further improved treatment precision while minimizing damage to surrounding healthy tissues. Furthermore, radiography and radiotherapy have demonstrated their worth beyond oncology. Radiography is instrumental in guiding various medical procedures, including catheter placement, joint injections, and dental evaluations, reducing complications and enhancing procedural accuracy. On the other hand, radiotherapy finds applications in non-cancerous conditions like benign tumors, vascular malformations, and certain neurological disorders, offering therapeutic options for patients who may not benefit from traditional surgical interventions. In conclusion, radiography and radiotherapy stand as indispensable tools in modern medicine, driving transformative improvements in patient care and treatment outcomes. Their ability to diagnose, treat, and manage a wide array of medical conditions underscores their favor in medical practice. As technology continues to advance, radiography and radiotherapy will undoubtedly play an ever more significant role in shaping the future of healthcare, ultimately saving lives and enhancing the quality of life for countless individuals worldwide.

Keywords: radiology, radiotherapy, medical imaging, cancer treatment

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Authors: P. Y. Chiang, Y. H. Chen, Y. J. Lin, C. C. Chang, W. C. Hsu

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The number of the elderly in the world population and the rate of falls in this increasing numbers of older people are increasing. Decreasing muscle strength and an increasing risk of falling are associated with the ageing process. Because the effects of seated stepping training on the walking performance in the elderly remain unclear, the main purpose of the proposed study is to perform electromyography analysis during walking and seated stepping in the elderly. Four surface EMG electrodes were sticked on the surface of lower limbs muscles, including vastus lateralis (VL), and gastrocnemius (GT) of both sides. Before test, maximal voluntary contraction (MVC) of the respective muscle was obtained using manual muscle testing. The analog raw data of EMG signals were digitized with a sampling frequency of 2000 Hz. The signals were fully rectified and the linear envelope were calculated. Stepping motion cycle was separated into two phases by stepping timing (ST) and pedal return timing (PRT). ST refer to the time when the pedal marker reached the highest height, representing the contra-lateral leg was going to release the pedal. PRT refer to the time when the pedal marker reached the lowest height, representing the contra-lateral leg was going to step the pedal. We assumed that ST acted the same role in initial contact during walking, and PRT for toe-off. The period from ST to next PRT was called pushing phase (PP), during which the leg would start to step with resistance, and we compare this phase with the stance phase in level walking. The period from PRT to next ST was called returning phase (RP), during which leg would not have any resistance in this phase, and we compare this phase with the swing phase in level walking. VL and Gastro muscular activation had similar patterns in both side. The ability may transfer to those needed during loading response, mid-stance and terminal swing phase. User needed to make more effort in stepping compared with walking with similar timing; thus the strengthening of the VL and Gastro may be helpful to improve the walking endurance and efficiency for the elderly.

Keywords: elderly, electromyography, seated stepping, walking

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Authors: Velimir Monty Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

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Authors: Gabriella Notarianni Burk

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The present study investigates the Aspect Hypothesis (AH) in Italian child language in the production of frog story narratives from the CHILDES database. The AH is based on the assumption that children initially encode aspectual and lexical distinctions rather than temporal relations. Children from a variety of first languages have been shown to mark past initially with achievements and accomplishments (telic predicates) and in later stages with states and activities (atelic predicates). Aspectual distinctions in Romance languages are obligatorily and overtly encoded in the inflectional morphology. In Italian the perfective viewpoint is realized by the passato prossimo, which expresses a temporal and aspectual meaning of pastness and perfectivity, whereas the imperfective viewpoint in the past tense is realized by the imperfetto. The aim of this study is to assess the role of lexical aspect in the acquisition of tense and aspect morphology and to understand if Italian children’s mapping of aspectual and temporal distinctions follows consistent developmental patterns across languages. The research methodology aligns with the cross-linguistic designs, tasks and coding procedures previously developed in the frog story literature. Results from two-factor ANOVA show that Italian children (age range: 4-6) exhibited a statistically significant distinction between foregrounded perfective and backgrounded imperfective marking. However, a closer examination of the sixty narratives reveals an idiosyncratic production pattern for Italian children, whereby the marking of imperfetto deviates from the tenets of AH and emerges as deictic tense to entail completed and bounded events in foreground clauses. Instances of ‘perfective’ uses of imperfetto were predominantly found in the four-year old narratives (25%). Furthermore, the analysis of the perfective marking suggests that morphological articulation and diatopic variation may influence the child production of formal linguistic devices in discourse.

Keywords: actionality, aspect, grounding, temporal reference

Procedia PDF Downloads 241

Authors: M. Schapira, S. Françoise, F. Maheux, O. Pierre-Duplessix, E. Rabiller, B. Simon, R. Le Gendre

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Pico- and nano-phytoplankton are abundant and ecologically critical components of the autotrophic communities in the pelagic realm. While the role of physical forcing related to tidal cycle, water mass intrusion, nutrient availability, mixing and stratification on microphytoplankton blooms have been widely investigated, these are often overlooked for pico- and nano-phytoplankton especially in estuarine waters. This study investigates changes in abundances and community composition of pico- and nano-phytoplankton under different estuarine tidal conditions in the mouth of the Seine River in relation to nutrient availability, water column stratification and spatially localized currents. Samples were collected each day at high tide, over spring tide to neap tide cycle, from 21 stations homogeneously distributed in the Seine river month in May 2011. Vertical profiles of temperature, salinity and fluorescence were realized at each sampling station. Sub-surface water samples (i.e. 1 m depth) were collected for nutrients (i.e. N, P and Si), phytoplankton biomass (i.e. Chl a) and pico- and nano-phytoplankton enumeration and identification. Pico- and nano-phytoplankton populations were identified and quantified using flow cytometry. Total abundances tend to decrease from spring tide to neap tide. Samples were characterized by high abundances of Synechococcus and Cryptophyceae. The composition of the pico- and nano-phytoplankton varied greatly under the different estuarine tidal conditions. Moreover, at the scale of the river mouth, the pico- and nano-phytoplankton population exhibited patchy distribution patterns that were closely controlled by water mass intrusion from the Sea, freshwater inputs from the Seine River and the geomorphology of the river mouth. This study highlights the importance of physical forcing to the community composition of pico- and nano-phytoplankton that may be critical for the structure of the pelagic food webs in estuarine and adjacent coastal seas.

Keywords: nanophytoplancton, picophytoplankton, physical forcing, river mouth, tidal cycle

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Authors: Shiv Mohan Singh, Gwyneth Matcher

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To understand the culturable microbial composition and diversity patterns, soil samples were collected from inland nunataks of Jutulsessen and Ahlmannryggen ranges in Dronning Maud Land, Antarctica. 16S rRNA, ITS and the D1/D2 domain sequencing techniques were used for characterization of microbial communities of these geographical areas. The total 37 species of bacteria such as Arthrobacter agilis, Acinetobacter baumannii, Arthrobacter flavus, Arthrobacter ginsengisoli, Arthrobacter oxydans, Arthrobacter oryzae, Arthrobacter polychromogenes, Arthrobacter sulfonivorans, Bacillus altitudinis, Bacillus cereus, Bacillus paramycoides, Brevundimonas vesicularis, Brachybacterium rhamnosum, Curtobacterium luteum, Dermacoccus nishinomiyaensis, Dietzia aerolata, Janibacter indicus, Knoellia subterranean, Kocuria palustris, Kytococcus aerolatus, Lysinibacillus sphaericus, Microbacterium phyllosphaerae, Micrococcus yunnanensis, Methylobacterium rhodesianum, Moraxella osloensis, Paracoccus acridae, Pontibacter amylolyticus, Pseudomonas hunanensis, Pseudarthrobacter siccitolerans, Pseudarthrobacter phenanthrenivorans, Rhodococcus aerolatus, Rhodococcus sovatensis, Sphingomonas daechungensis, Sphingomonas sanguinis, Stenotrophomonas pavanii, Staphylococcus gallinarum, Staphylococcus arlettae and 9 species of fungi such as Candida davisiana, Cosmospora arxii, Geomyces destructans, Lecanicillium muscarium, Memnoniella humicola, Paecilomyces lilacinus, Pseudogymnoascus verrucosus, Phaeophlebiopsis ignerii and Thyronectria caraganae were recorded. Fatty acid methyl esters (FAME) analyses of representative species of each genus have shown predominance branched and unsaturated fatty acids indicate its adaptation strategy in Antarctic cold environment. To the best of our knowledge, this is the first record of culturable bacterial communities from Jutulsessen and Ahlmannryggen ranges in Western Dronning Maud Land, Antarctica.

Keywords: antarctica, microbe, adaptation, polar

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Authors: Dongxue Li, Zhonghua Ning, Yi’na Li, Baoshan Cui, Wasner Daniel, Sebastian Dötterl

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Most of the world's coastal alluvial plains can be significant carbon (C) eservoirs in which upland sediments are deposited and bury former topsoil, thereby contributing to soil C preservation, especially in river-controlled deltas like the Yellow River Delta, China. These deltas are affected by the continuous large amount of sediment transport and strong river dynamics from the upper reaches, which makes the river course in the deltas change frequently. However, the impact of varying river course changes on C stocks in these estuary wetlands is unclear. To investigate this, we drilled five 2 m cores along a sediment deposition sequence of the Yellow River Delta, which shifted its main course flow in the delta several times throughout the 20th century. Covering 80 years of sediment deposition, we explored both soil C stocks and their potential sources, and identified key soil physicochemical and hydrometeorological variables that correlate to C density and deposition rate. Further, the spatiotemporal C distribution and its relationship with these variables was examined. Our results showed that sediments at a soil depth of 200 cm in the main courses of the Yellow River corresponded to deposition ages ranging from 1942 to 1989. The oldest course has the lowest C stocks and showed C-enriched compared with younger courses. Contributions of soil C stemming from fresh particulate organic carbon from deposited upstream sources were significantly higher than local, in-situ vegetation. In addition, the carbon of the oldest and relatively young courses tends to be affected by interaction effects of hydrometeorological and physiochemical varibales, and that of the middle courses tends to be affected by independent variables. Our findings can help prioritize conservation efforts across different river courses and provide quantitative support for global carbon emission reduction by assessing sediment carbon reservoirs.

Keywords: alluvial plains, coastal wetland, core drilling, course diversion, organic carbon, sediment deposition rate, soil deposition

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Authors: Daniel Schwarz, Jan Fivaz, Alessia Neuroni

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Although digitization is a buzzword in almost every election campaign, the political parties leave voters largely in the dark about their specific positions on digital issues. In the run-up to the 2019 elections in Switzerland, the ‘Digitization Monitor’ project (DMP) was launched in order to change this situation. Within the framework of the DMP, all 4,736 candidates were surveyed about their digital policy positions and values. The DMP is designed as a digital policy supplement to the existing ‘smartvote’ voting advice application. This enabled a direct comparison of the digital policy attitudes according to the DMP with the topics of the ‘smartvote’ questionnaire which are comprehensive in content but mainly related to conventional policy areas. This paper’s main research goal is to analyze and visualize possible differences between conventional and digital policy areas in terms of response patterns between and within political parties. The analysis is based on dimensionality reduction methods (multidimensional scaling and principal component analysis) for the visualization of inter-party differences, and on standard deviation as a measure of variation for the evaluation of intra-party unity. The results reveal that digital issues show a lower degree of inter-party polarization compared to conventional policy areas. Thus, the parties have more common ground in issues on digitization than in conventional policy areas. In contrast, the study reveals a mixed picture regarding intra-party unity. Homogeneous parties show a lower degree of unity in digitization issues whereas parties with heterogeneous positions in conventional areas have more united positions in digital areas. All things considered, the findings are encouraging as less polarized conditions apply to the debate on digital development compared to conventional politics. For the future, it would be desirable if in further countries similar projects to the DMP could emerge to broaden the basis for conclusions.

Keywords: comparison of political issue dimensions, digital awareness of candidates, digital policy space, party positions on digital issues

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Authors: Saima Murtaza

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Ethics and aesthetics have invariably remained the two closely integrated artistic appurtenances for the production of any work of art. These artistic devices configure themselves into a complex synthesis in our contemporary literature. The labyrinthine integration of ethics and aesthetics, operating in the lives of human characters, to the extent of transcending all limits has resulted in an artistic puzzle for the readers. Art, no doubt, is an extrinsic expression of the intrinsic life of man. The use of aesthetics in literature pertaining to human existence; aesthetic solipsism, has resulted in the artistic objectification of these characters. The practice of the like aestheticism deprives the characters of their souls, rendering them as mere objects of aesthetic gaze at the hands of their artists-creators. Artists orchestrate their lives founding it on a plot which deviates from normal social and ethical standards. Their perverse attitude can be seen in dealing with characters, their feelings and the incidents of their lives. Morality is made to appear not as a religious construct but as an individual’s private affair. Furthermore, the idea of beauty incarnated, in other words hedonistic aesthetic does not placate a true aesthete. Ethics and aesthetics are the two most recurring motifs of our contemporary literature, especially of Nabokov’s world. The purpose of this study is to peruse these aforementioned motifs in Nabokov’s most enigmatic novel Lolita, a story of pedophilia, which is in fact reflective of our complex individual psychic and societal patterns. The narrative subverts all the traditional and hitherto known notions of aesthetics and ethics. When applied to literature, aesthetic does not simply mean ‘beautiful’ in the text. It refers to an intricate relationship between feelings and perception and also incorporates within its range wide-ranging emotional reactions to text. The term aesthetics in literature is connected with the readers whose critical responses to the text determine the merit of any work to be really a piece of art. Aestheticism is the child of ethics. Morality sets the grounds for the production of any work and the idea of aesthetics gives it transcendence.

Keywords: ethics, aesthetics and hedonistic aesthetic, nymphet syndrome, pedophilia

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Authors: Dong Tang, Yongli Zhao

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The study of the microstructure of asphalt is of great importance for the analysis of its macroscopic properties. However, the peculiarities of the chemical composition of the asphalt itself and the limitations of existing direct imaging techniques have caused researchers to face many obstacles in studying the microstructure of asphalt. The advantage of small-angle X-ray scattering (SAXS) is that it allows quantitative determination of the internal structure of opaque materials and is suitable for analyzing the microstructure of materials. Therefore, the SAXS technique was used to study the evolution of microstructures on the nanoscale during asphalt aging. And the reasons for the change in scattering contrast during asphalt aging were also explained with the help of Fourier transform infrared spectroscopy (FTIR). SAXS experimental results show that the SAXS curves of asphalt are similar to the scattering curves of scattering objects with two-level structures. The Porod curve for asphalt shows that there is no obvious interface between the micelles and the surrounding mediums, and there is only a fluctuation of the hot electron density between the two. The Beaucage model fit SAXS patterns shows that the scattering coefficient P of the asphaltene clusters as well as the size of the micelles, gradually increase with the aging of the asphalt. Furthermore, aggregation exists between the micelles of asphalt and becomes more pronounced with increasing aging. During asphalt aging, the electron density difference between the micelles and the surrounding mediums gradually increases, leading to an increase in the scattering contrast of the asphalt. Under long-term aging conditions due to the gradual transition from maltenes to asphaltenes, the electron density difference between the micelles and the surrounding mediums decreases, resulting in a decrease in the scattering contrast of asphalt SAXS. Finally, this paper correlates the macroscopic properties of asphalt with microstructural parameters, and the results show that the high-temperature rutting resistance of asphalt is enhanced and the low-temperature cracking resistance decreases due to the aggregation of micelles and the generation of new micelles. These results are useful for understanding the relationship between changes in microstructure and changes in properties during asphalt aging and provide theoretical guidance for the regeneration of aged asphalt.

Keywords: asphalt, Beaucage model, microstructure, SAXS

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Authors: María García-García, Esther Simancas-González, Said Balhadj, Carmen Silva-Robles, Driss Ferhane

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Cooperation between the territories on both sides of the Strait of Gibraltar is an urgent reality. the south of Spain and northern Morocco share a common historical past and belong to a very similar geographical and ecological area. Economic, social and cultural relations make cooperation between the two countries’ (Spain and Morocco) a priority for the EU and both countries governments. Likewise, deepened changes happened in production systems and consumption patterns had seriously damaged and weakened the craftwork sector. The promotion of local crafts, and its economic value, and the cooperation with the north of Morocco has been an important issue for the Andalusian government in recent years. The main aim of this work is to understand the strengths and weaknesses of the Tangier - Tetuan region craftworks sector in order to develop accurate communication and promotion plans. From the knowledge of the real identity, the sector could be repositioned. Promotion and communication could be a spur to traditional sectors, such as crafts. Competitiveness requires "the culture of communication, the cooperation between different companies to build powerful territory brands and maintain the establishment confidence and effectiveness relationships among agencies and organizations". The lack of previous literature addressing how Tangier craftwork promote and communicate its value to their stakeholders, has conducted the study to an exploratory approach with a double dimension: internal, Tangier craftwork sector image, and external, Andalusia image of the sector in Tangier. Different interviews were conducted with Andalusian partners involved in the artisanal sector (9 master craftsmen and 3 institutions) and focus groups with 9 Tangiers craftsmen were developed. The result of these interviews and expert groups are reflected in a SWOT analysis which reveals a handcraft industry with a worrying wide-spread and undifferentiated identity and reluctance to innovation and new technologies.

Keywords: communication management, image, Moroccan crafts, Spain-Morocco cooperation

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Authors: Maha Ben Salem

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The transformative aspect of emerging adulthood brings about a development of self-processes, including changes in self-esteem and personal goals. Success in this life stage entails the emotional growth necessary to navigate the demands and challenges of college life. Understanding the concept of self-awareness within this particular age group sheds light on emerging adults’ internal world and the transformative aspect of their emotional growth. Uncovering the thoughts' processes that foster or hinder self-awareness is important to the understanding of how emerging adults learn to make themselves positive or negative. However, existing research in self-awareness has explored this phenomenon mostly using quantitative research methodology or through tying an individual’s level of self-awareness to specific actions or outcomes. Little is known about the process of how college students emerging adults notice and monitor their inner thoughts and emotions. Methodology and theoretical orientation: A grounded theory study using in-depth semi-structured interview was utilized. Nine interviews have been conducted. A constructionist framework was employed to generate a theory as for how self-awareness facilitates specific patterns of thinking in emerging adults. The choice of grounded theory emanates from a lack of knowledge regarding underlying thinking procedures and internal states that emerging adult college students navigate in an attempt to make meaning out of the new academic experience and life stage. Findings: Initial data analysis generated the following categories of the theory: (a) a non-judgmental perception of negative thinking and negative emotions that allow for a better understanding of the self; (b) negative state of mind is easy to overcome when it is accepted and acknowledged; (c) knowledge of the actual and desired self-generates an intentional decision to shift to a positive mindset. Preliminary findings indicate that college academic and social environment foster a new understanding of the self that yield a change in mindset and in self-knowledge.

Keywords: college environment, emergent adults, grounded theory, positive mindset, self-awareness

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Authors: Akhil Teja Kambhampati, Mark A. Hoffman

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In the realm of infectious disease research, airborne viral transmission stands as a paramount concern due to its pivotal role in propagating pathogens within densely populated regions. However, amidst this landscape, the phenomenon of hygroscopic growth within respiratory bioaerosols remains relatively underexplored. Unlike pure water aerosols, the unique composition of respiratory bioaerosols leads to varied evaporation rates and hygroscopic growth patterns, influenced by factors such as ambient humidity, temperature, and airflow. This study addresses this gap by focusing on the behaviors of single respiratory bioaerosol utilizing salinity to induce saliva-like hygroscopic behavior. By employing mass, momentum, and energy equations, the study unveils the intricate interplay between evaporation and hygroscopic growth over time. The numerical model enables temporal analysis of bioaerosol characteristics, including size, temperature, and trajectory. The analysis reveals that due to evaporation, there is a reduction in initial size, which shortens the lifetime and distance traveled. However, when hygroscopic growth begins to influence the bioaerosol size, the rate of size reduction slows significantly. The interplay between evaporation and hygroscopic growth results in bioaerosol size within the inhalation range of humans and prolongs the traveling distance. Findings procured from the analysis are crucial for understanding the spread of infectious diseases, especially in high-risk environments such as healthcare facilities and public transportation systems. By elucidating the nuanced behaviors of respiratory bioaerosols, this study seeks to inform the development of more effective preventative strategies against pathogens propagation in the air, thereby contributing to public health efforts on a global scale.

Keywords: airborne viral transmission, high-risk environments, hygroscopic growth, evaporation, numerical modeling, pathogen propagation, preventative strategies, public health, respiratory bioaerosols

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Patrizia Bonaventura, Magda Di Renzo

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This project aims to measure and assess the voice quality in children with autism. Few previous studies exist which have analyzed the voice quality of individuals with autism: abnormal voice characteristics have been found, like a high pitch, great pitch range, and sing-song quality. Existing studies did not focus specifically on Italian-speaking children’s voices and provided analysis of a few acoustic parameters. The present study aimed to gather more data and to perform acoustic analysis of the voice of children with autism in order to identify patterns of abnormal voice features that might shed some light on the causes of the dysphonia and possibly be used to create a pediatric assessment tool for early identification of autism. The participants were five native Italian-speaking boys with autism between the age of 4 years and 10 years (mean 6.8 ± SD 1.4). The children had a diagnosis of autism, were verbal, and had no other comorbid conditions (like Down syndrome or ADHD). The voices of the autistic children were recorded in the production of sustained vowels [ah] and [ih] and of sentences from the Italian version of the CAPE-V voice assessment test. The following voice parameters, representative of normal quality, were analyzed by acoustic spectrography through Praat: Speaking Fundamental Frequency, F0 range, average intensity, and dynamic range. The results showed that the pitch parameters (Speaking Fundamental Frequency and F0 range), as well as the intensity parameters (average intensity and dynamic range), were significantly different from the relative normal reference thresholds. Also, variability among children was found, so confirming a tendency revealed in previous studies of individual variation in these aspects of voice quality. The results indicate a general pattern of abnormal voice quality characterized by a high pitch and large variations in pitch and intensity. These acoustic voice characteristics found in Italian-speaking autistic children match those found in children speaking other languages, indicating that autism symptoms affecting voice quality might be independent of the native language of the children.

Keywords: autism, voice disorders, speech science, acoustic analysis of voice

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Authors: Saad M. Algharib

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The major concern of planners when placing fire stations is finding their optimal locations such that the fire companies can reach fire locations within reasonable response time or distance. Planners are also concerned with the numbers of fire stations that are needed to cover all service areas and the fires, as demands, with standard response time or distance. One of the tools for such analysis is location-allocation models. Location-allocation models enable planners to determine the optimal locations of facilities in an area in order to serve regional demands in the most efficient way. The purpose of this study is to examine the geographic distribution of the existing fire stations in Kuwait City. This study utilized location-allocation models within the Geographic Information System (GIS) environment and a number of statistical functions to assess the current locations of fire stations in Kuwait City. Further, this study investigated how well all service areas are covered and how many and where additional fire stations are needed. Four different location-allocation models were compared to find which models cover more demands than the others, given the same number of fire stations. This study tests many ways to combine variables instead of using one variable at a time when applying these models in order to create a new measurement that influences the optimal locations for locating fire stations. This study also tests how location-allocation models are sensitive to different levels of spatial dependency. The results indicate that there are some districts in Kuwait City that are not covered by the existing fire stations. These uncovered districts are clustered together. This study also identifies where to locate the new fire stations. This study provides users of these models a new variable that can assist them to select the best locations for fire stations. The results include information about how the location-allocation models behave in response to different levels of spatial dependency of demands. The results show that these models perform better with clustered demands. From the additional analysis carried out in this study, it can be concluded that these models applied differently at different spatial patterns.

Keywords: geographic information science, GIS, location-allocation models, geography

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Authors: Noor Abdelhamid, Donovan Nelson, Cara Prosser

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The architectural design process could be mapped out as a dialogue between designer and user that is constructed across multiple phases with the overarching goal of aligning design outcomes with user needs. Traditionally, this dialogue is bounded within a preliminary phase of determining factors that will direct the design intent, and a completion phase, of handing off the project to the client. Pre- and post-occupancy evaluations (P/POE’s) could provide an alternative process by extending this dialogue on both ends of the design process. The purpose of this research is to study the influence of systematic pre-occupancy data collection in achieving design goals by conducting post-occupancy evaluations of two case studies. In the context of this study, systematic pre-occupancy data collection is defined as the preliminary documentation of the existing conditions that helps portray stakeholders’ needs. When implemented, pre-occupancy occurs during the early phases of the architectural design process, utilizing the information to shape the design intent. Investigative POE’s are performed on two case studies with distinct early design approaches to understand how the current space is impacting user needs, establish design outcomes, and inform future strategies. The first case study underwent systematic pre-occupancy data collection and synthesis, while the other represents the traditional, uncoordinated practice of informally collecting data during an early design phase. POE’s target the dynamics between the building and its occupants by studying how spaces are serving the needs of the users. Data collection for this study consists of user surveys, audiovisual materials, and observations during regular site visits. Mixed methods of qualitative and quantitative analyses are synthesized to identify patterns in the data. The paper concludes by positioning value on both sides of the architectural design process: the integration of systematic pre-occupancy methods in the early phases and the reinforcement of a continued dialogue between building and design team after building completion.

Keywords: architecture, design process, pre-occupancy data, post-occupancy evaluation

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Authors: Yananda Siraphatthada

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The objectives of this research were to study the level of influencing factors, leadership, supply chain management, innovation, competitive advantages, business success, and affecting factors to the business success of the mobile phone system service providers in Bangkok Metropolitan. This research was done by the quantitative approach and the qualitative approach. The quantitative approach was used for questionnaires to collect data from the 331 mobile service shop managers franchised by AIS, Dtac and TrueMove. The mobile phone system service providers/shop managers were randomly stratified and proportionally allocated into subgroups exclusive to the number of the providers in each network. In terms of qualitative method, there were in-depth interviews of 6 mobile service providers/managers of Telewiz and Dtac and TrueMove shop to find the agreement or disagreement with the content analysis method. Descriptive Statistics, including Frequency, Percentage, Means and Standard Deviation were employed; also, the Structural Equation Model (SEM) was used as a tool for data analysis. The content analysis method was applied to identify key patterns emerging from the interview responses. The two data sets were brought together for comparing and contrasting to make the findings, providing triangulation to enrich result interpretation. It revealed that the level of the influencing factors – leadership, innovation management, supply chain management, and business competitiveness had an impact at a great level, but that the level of factors, innovation and the business, financial success and nonbusiness financial success of the mobile phone system service providers in Bangkok Metropolitan, is at the highest level. Moreover, the business influencing factors, competitive advantages in the business of mobile system service providers which were leadership, supply chain management, innovation management, business advantages, and business success, had statistical significance at .01 which corresponded to the data from the interviews.

Keywords: mobile service providers, facilitating factors, Bangkok Metropolitan, business success

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Authors: Qianhui Li, Christoph H. Bruecker

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Atherosclerotic plaques are typically found where flow separation and variations of shear stress occur. Although helical flow patterns and flow separations have been recorded in the aorta, their relation has not been clearly clarified and especially in the condition of artificial heart valve prostheses. Therefore, an experimental study is performed to investigate the hemodynamic performance of different mechanical heart valves (MHVs), i.e. the SJM Regent bileaflet mechanical heart valve (BMHV) and the Lapeyre-Triflo FURTIVA trileaflet mechanical heart valve (TMHV), in a transparent model of the human aorta under a physiological pulsatile right-hand helical flow condition. A typical systolic flow profile is applied in the pulse-duplicator to generate a physiological pulsatile flow which thereafter flows past an axial turbine blade structure to imitate the right-hand helical flow induced in the left ventricle. High-speed particle image velocimetry (PIV) measurements are used to map the flow evolution. A circular open orifice nozzle inserted in the valve plane as the reference configuration initially replaces the valve under investigation to understand the hemodynamic effects of the entered helical flow structure on the flow evolution in the aortic arch. Flow field analysis of the open orifice nozzle configuration illuminates the helical flow effectively delays the flow separation at the inner radius wall of the aortic arch. The comparison of the flow evolution for different MHVs shows that the BMHV works like a flow straightener which re-configures the helical flow pattern into three parallel jets (two side-orifice jets and the central orifice jet) while the TMHV preserves the helical flow structure and therefore prevent the flow separation at the inner radius wall of the aortic arch. Therefore the TMHV is of better hemodynamic performance and reduces the pressure loss.

Keywords: flow separation, helical aortic flow, mechanical heart valve, particle image velocimetry

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

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Authors: C. A. Bradley, D. Patsios, D. Berridge

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This paper presents evidence to better understand the risk and protective factors related to sibling conflict and the patterns of association between sibling conflict and negative adjustment outcomes by incorporating additional familial and societal factors within statistical models of risk and adjustment. It was conducted through the secondary analysis of a large representative cross-sectional dataset of children in the UK. The original study includes proxy interviews for young children and self-report interviews for adolescents. The study applies an ecological systems framework for the analyses. Hierarchical regression models assess risk and protective factors and adjustment outcomes associated with sibling conflict. Interactions reveal differential effect between contextual risk factors and the social context of influence. The general pattern of findings suggested that, although factors affecting likelihood of experiencing sibling conflict were often determined by child age, some remained consistent across childhood. These factors were often conditional on each other, reinforcing the importance of an ecological framework. Across both age-groups, sibling conflict was associated with siblings closer in age; male sibling groups; most advantaged socio-economic group; and exposure to community violence, such as witnessing violent assault or robbery. The study develops the evidence base on the influence of ethnicity and socio-economic group on sibling conflict by exploring interactions between social context. It also identifies key new areas of influence – such as family structure, disability, and community violence in exacerbating or reducing risk of conflict. The study found negative associations between sibling conflict and young children’s mental well-being and adolescents' mental well-being and anti-social behaviour, but also more context specific associations – such as sibling conflict moderating the negative impact of adversity and high risk experiences for young children such as parental violence toward the child.

Keywords: adjustment, conflict, ecological systems, family systems, risk and protective factors, sibling

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Authors: Borislava Dimitrova, Didem Kepir Savoly

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The movie analysis offers a dynamic and multifaceted lens in order to explore and understand various aspects of human behavior and relationship, emotion, and cognition. Cinema therapy can be an important tool for counselor education and counselors in therapy. Therefore, this paper aims to delve deeper into human relationships and individual behavior patterns and analyze some of their most vivid aspects in light of the transactional analysis and its main components. While describing certain human behaviors and emotional states in real life, sometimes it can be difficult even for mental health practitioners to become aware of the subtle social cues and hints that are being transmitted, often in a rushed and swift manner. To address this challenge, the current paper focuses on the relationship dynamics as conveyed through the plot of the movie “Sunset Boulevard”, and examines slightly exaggerated yet true-to-life examples. The movie was directed by Billy Wilder and written by Charles Brackett, Billy Wilder, and D.M. Marshman Jr. The scenes of interest were examined through Transactional Analysis concepts: the different ego states, strokes, the various kinds of transactions, the paradigm of games in transactional analysis, and lastly, with the help of the drama triangle. The addressed themes comprised mainly the way the main characters engaged in game playing, which eventually had a negative outcome on the sequences of interactions between the individuals and the desired payoffs that they craved as a result. Furthermore, counselor educators can use the result of this paper for educational purposes, such as for teaching theoretical knowledge about Transactional Analysis, and for utilizing characters’ interactions and behaviors as real-life situations that can serve as case studies and role-playing activities. Finally, the paper aims to foster the use of movies as materials for psychological analysis which can assist the teaching of new mental health professionals in the field.

Keywords: transactional analysis, movie analysis, drama triangle, games, ego-state

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Authors: Marjeta Misigoj Durakovic, Maroje Soric, Lovro Stefan

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Background and aim: Physical inactivity has been linked with increased morbidity and premature mortality and adolescence has been recognised as the critical period for a decline in physical activity (PA) level. In order to properly direct interventions aimed at increasing PA, high-risk groups of individuals should be identified. Therefore, the aim of this study is to describe gender differences in: a) PA level; b) weekly PA patterns. Methods: This investigation is a part of the CRO-PALS study which is an on-going longitudinal study conducted in a representative sample of urban youth in Zagreb (Croatia). CRO-PALS involves 903 adolescents and for the purpose of this study data from a subgroup of 190 participants with information on objective PA level were analysed (116 girls; mean age [SD]=15.6[0.3] years). Duration of moderate and vigorous PA was measured during 5 consecutive by a multiple-sensor physical activity monitor (SenseWear Armband, BodyMedia inc., Pittsburgh, USA). Gender differences in PA level were evaluated using independent samples t-test. Differences in school week and weekend levels of activity were assessed using mixed ANOVA with gender as between-subjects factor. The amount of vigorous PA had to be log-transformed to achieve normality in the distribution. Results: Boys were more active than girls. Duration of moderate-to-vigorous PA averaged 111±44 min/day in boys and 80±38 min/day in girls (mean difference=31 min/day, 95%CI=20-43 min/day). Vigorous PA was 2.5 times higher in boys compared to girls (95%CI=1.9-3.5). Participants were more active during school days than on weekends. The magnitude of the difference in moderate-to-vigorous PA was similar in both gender (p value for time*gender interaction = 0.79) and averaged 19 min/day (95%CI=11-27 min/day). Similarly, vigorous PA was 36% lower on weekends compared with school days (95%CI=22-46%) with no gender difference (p value for time*gender interaction = 0.52). Conclusion: PA level was higher in boys than in girls throughout the week. Still, in both boys and girls, the amount of PA reduced markedly on weekends compared with school days.

Keywords: adolescence, multiple-sensor physical activity monitor, physical activity level, weekly physical activity pattern

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Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: Esther Mafunda, Simbarashe Muparangi

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The present paper tests the applicability of the Regression Hypothesis on the pathological language dissolution of a Shona male adult with Broca’s aphasia. It particularly assesses the prediction of the Regression Hypothesis, which states that the process according to which language is forgotten will be the reversal of the process according to which it will be acquired. The main aim of the paper is to find out whether mirror symmetries between L1 acquisition and L1 dissolution of tense in Shona and, if so, what might cause these regression patterns. The paper also sought to highlight the practical contributions that Linguistic theory can make to solving language-related problems. Data was collected from a 46-year-old male adult with Broca’s aphasia who was receiving speech therapy at St Giles Rehabilitation Centre in Harare, Zimbabwe. The primary data elicitation method was experimental, using the probe technique. The TART (Test for Assessing Reference Time) Shona version in the form of sequencing pictures was used to access tense by Broca’s aphasic and 3.5-year-old child. Using the SPSS (Statistical Package for Social Studies) and Excel analysis, it was established that the use of the future tense was impaired in Shona Broca’s aphasic whilst the present and past tense was intact. However, though the past tense was intact in the male adult with Broca’s aphasic, a reference to the remote past was made. The use of the future tense was also found to be difficult for the 3,5-year-old speaking child. No difficulties were encountered in using the present and past tenses. This means that mirror symmetries were found between L1 acquisition and L1 dissolution of tense in Shona. On the basis of the results of this research, it can be concluded that the use of tense in a Shona adult with Broca’s aphasia supports the Regression Hypothesis. The findings of this study are important in terms of speech therapy in the context of Zimbabwe. The study also contributes to Bantu linguistics in general and to Shona linguistics in particular. Further studies could also be done focusing on the rest of the Bantu language varieties in terms of aphasia.

Keywords: Broca’s Aphasia, regression hypothesis, Shona, language dissolution

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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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