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Authors: Hatem Abou-Senna

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Interstate 4 (I-4) is a primary east-west transportation corridor between Tampa and Daytona cities, serving commuters, commercial and recreational traffic. I-4 is known to have severe recurring congestion during peak hours. The congestion spans about 11 miles in the evening peak period in the central corridor area as it is considered the only non-tolled limited access facility connecting the Orlando Central Business District (CBD) and the tourist attractions area (Walt Disney World). Florida officials had been skeptical of tolling I-4 prior to the recent legislation, and the public through the media had been complaining about the excessive toll facilities in Central Florida. So, in search for plausible mitigation to the congestion on the I-4 corridor, this research is implemented to evaluate the effectiveness of different toll pricing alternatives that might divert traffic from I-4 to the toll facilities during the peak period. The network is composed of two main diverging limited access highways, freeway (I-4) and toll road (SR 417) in addition to two east-west parallel toll roads SR 408 and SR 528, intersecting the above-mentioned highways from both ends. I-4 and toll road SR 408 are the most frequently used route by commuters. SR-417 is a relatively uncongested toll road with 15 miles longer than I-4 and $5 tolls compared to no monetary cost on 1-4 for the same trip. The results of the calibrated Orlando PARAMICS network showed that percentages of route diversion vary from one route to another and depends primarily on the travel cost between specific origin-destination (O-D) pairs. Most drivers going from Disney (O1) or Lake Buena Vista (O2) to Lake Mary (D1) were found to have a high propensity towards using I-4, even when eliminating tolls and/or providing real-time information. However, a diversion from I-4 to SR 417 for these OD pairs occurred only in the cases of the incident and lane closure on I-4, due to the increase in delay and travel costs, and when information is provided to travelers. Furthermore, drivers that diverted from I-4 to SR 417 and SR 528 did not gain significant travel-time savings. This was attributed to the limited extra capacity of the alternative routes in the peak period and the longer traveling distance. When the remaining origin-destination pairs were analyzed, average travel time savings on I-4 ranged between 10 and 16% amounting to 10 minutes at the most with a 10% increase in the network average speed. High propensity of diversion on the network increased significantly when eliminating tolls on SR 417 and SR 528 while doubling the tolls on SR 408 along with the incident and lane closure scenarios on I-4 and with real-time information provided. The toll roads were found to be a viable alternative to I-4 for these specific OD pairs depending on the user perception of the toll cost which was reflected in their specific travel times. However, on the macroscopic level, it was concluded that route diversion through toll reduction or elimination on surrounding toll roads would only have a minimum impact on reducing I-4 congestion during the peak period.

Keywords: congestion pricing, dynamic feedback assignment, microsimulation, paramics, route diversion

Procedia PDF Downloads 144

Authors: Rodrigo Arnaldo Scarpel

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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

Procedia PDF Downloads 51

Authors: Sheikh Mohammed Rafiul Huque

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Bangladesh since its inception has been an economy that is fuelled by agriculture and agriculture has significant contribution to the GDP of Bangladesh. The agriculture of Bangladesh predominantly and historically dependent on organic sources of raw material though the place has taken in decades by inorganic sources of raw materials due to the high demand of food for rapidly growing of population. Meanwhile, a new market segment, which is niche market, has been evolving in the urban area in favor of organic products, though 71.1% population living in rural areas is dependent mainly on conventional products. The new market segment is search of healthy and safer source of food and they could believe that organic products are the solution of that. In Bangladesh, food adulteration is very common practices among the shop-keepers to extend the shelf life of raw vegetables and fruits. The niche group of city dwellers is aware about the fact and gradually shifting their buying behavior to organic products. A recent survey on organic farming revealed that 16,200 hectares under organic farming in recent time, which was only 2,500 hectares in 2008. This study is focused on consumer awareness of organic products and tried to explore the factors affecting organic food consumption among high income group of people. The hypothesis is developed to explore the effect of gender (GENDER), ability to purchase (ABILITY) and health awareness (HEALTH) on purchase intention (INTENTION). A snowball sampling was administered among the high income group of people in Dhaka city among 150 respondents. In this sampling process the study could identify only those samples who has consume organic products. A Partial Least Square (PLS) method was used to analyze data using path analysis. It was revealed from the analysis that coefficient determination R2 is 0.829 for INTENTION endogenous latent variable. This means that three latent variables (GENDER, ABILITY, and HEALTH) significantly explain 82.9% of the variance in INTENTION of purchasing organic products. Moreover, GENDER solely explains 6.3% and 8.6% variability of ABILITY and HEALTH respectively. The inner model suggests that HEALTH has strongest negative effect on INTENTION (-0.647) followed by ABILITY (0.344) and GENDER (0.246). The hypothesized path relationship between ABILITY->INTENTION, HEALTH->INTENTION and GENDER->INTENTION are statistically significant. Furthermore, the hypothesized path relationship between GENDER->ABILITY (0.262) and GENDER->HEALTH (-0.292) also statistically significant. The purpose of the study is to demonstrate how an organic product producer can improve his participatory guarantee system (PGS) while marketing the products. The study focuses on understanding gender (GENDER), ability (ABILITY) and health (HEALTH) factors while positioning the products (INTENTION) in the mind of the consumer. In this study, the respondents are found to care about high price and ability to purchase variables with loading -0.920 and 0.898. They are good indicators of ability to purchase (ABILITY). The marketers should consider about price of organic comparing to conventional products while marketing, otherwise, that will create negative intention to buy with a loading of -0.939. Meanwhile, it is also revealed that believability of chemical free component in organic products and health awareness affects health (HEALTH) components with high loading -0.941 and 0.682. The study analyzes that low believability of chemical free component and high price of organic products affects intension to buy. The marketers should not overlook this point while targeting the consumers in Bangladesh.

Keywords: health awareness, organic products, purchase ability, purchase intention

Procedia PDF Downloads 350

Authors: Allison Herlene Du Plessis, Dalena (R.M.) Van Rooyen, Wilma Ten Ham-Baloyi, Sihaam Jardien-Baboo

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Introduction: Women die in pregnancy and childbirth for five main reasons—severe bleeding, infections, unsafe abortions, hypertensive disorders (pre-eclampsia and eclampsia), and medical complications including cardiac disease, diabetes, or HIV/AIDS complicated by pregnancy. In 2015, WHO classified sepsis as the third highest cause for maternal mortalities in the world. Chorioamnionitis is a clinical syndrome of intrauterine infection during any stage of the pregnancy and it refers to ascending bacteria from the vaginal canal up into the uterus, causing infection. While the incidence rates for chorioamnionitis are not well documented, complications related to chorioamnionitis are well documented and midwives still struggle to identify this condition in time due to its complex nature. Few diagnostic methods are available in public health services, due to escalated laboratory costs. Often the affordable biomarkers, such as C-reactive protein CRP, full blood count (FBC) and WBC, have low significance in diagnosing chorioamnionitis. A lack of screening impacts on effective and timeous management of chorioamnionitis, and early identification and management of risks could help to prevent neonatal complications and reduce the subsequent series of morbidities and healthcare costs of infants who are health foci of perinatal infections. Objective: This integrative literature review provides an overview of current best research evidence on the screening of women at risk for chorioamnionitis. Design: An integrative literature review was conducted using a systematic electronic literature search through EBSCOhost, Cochrane Online, Wiley Online, PubMed, Scopus and Google. Guidelines, research studies, and reports in English related to chorioamnionitis from 2008 up until 2020 were included in the study. Findings: After critical appraisal, 31 articles were included. More than one third (67%) of the literature included ranked on the three highest levels of evidence (Level I, II and III). Data extracted regarding screening for chorioamnionitis was synthesized into four themes, namely: screening by clinical signs and symptoms, screening by causative factors of chorioamnionitis, screening of obstetric history, and essential biomarkers to diagnose chorioamnionitis. Key conclusions: There are factors that can be used by midwives to identify women at risk for chorioamnionitis. However, there are a paucity of established sociological, epidemiological and behavioral factors to screen this population. Several biomarkers are available to diagnose chorioamnionitis. Increased Interleukin-6 in amniotic fluid is the better indicator and strongest predictor of histological chorioamnionitis, whereas the available rapid matrix-metalloproteinase-8 test requires further testing. Maternal white blood cells count (WBC) has shown poor selectivity and sensitivity, and C-reactive protein (CRP) thresholds varied among studies and are not ideal for conclusive diagnosis of subclinical chorioamnionitis. Implications for practice: Screening of women at risk for chorioamnionitis by health care providers providing care for pregnant women, including midwives, is important for diagnosis and management before complications arise, particularly in resource-constraint settings.

Keywords: chorioamnionitis, guidelines, best evidence, screening, diagnosis, pregnant women

Procedia PDF Downloads 96

Authors: Saule Mussabekova

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A number of chemical elements widely presented in the nature is seldom met in people and vice versa. This is a peculiarity of accumulation of elements in the body, and their selective use regardless of widely changed parameters of external environment. Microelemental identification of human hair and particularly dead body is a new step in the development of modern forensic medicine which needs reliable criteria while identifying the person. In the condition of technology-related pressing of large industrial cities for many years and specific for each region multiple-factor toxic effect from many industrial enterprises it’s important to assess actuality and the role of researches of human hair while assessing degree of deposition with specific pollution. Hair is highly sensitive biological indicator and allows to assess ecological situation, to perform regionalism of large territories of geological and chemical methods. Besides, monitoring of concentrations of chemical elements in the regions of Kazakhstan gives opportunity to use these data while performing forensic medical identification of dead bodies of unknown persons. Methods based on identification of chemical composition of hair with further computer processing allowed to compare received data with average values for the sex, age, and to reveal causally significant deviations. It gives an opportunity preliminary to suppose the region of residence of the person, having concentrated actions of policy for search of people who are unaccounted for. It also allows to perform purposeful legal actions for its further identification having created more optimal and strictly individual scheme of personal identity. Hair is the most suitable material for forensic researches as it has such advances as long term storage properties with no time limitations and specific equipment. Besides, quantitative analysis of micro elements is well correlated with level of pollution of the environment, reflects professional diseases and with pinpoint accuracy helps not only to diagnose region of temporary residence of the person but to establish regions of his migration as well. Peculiarities of elemental composition of human hair have been established regardless of age and sex of persons residing on definite territories of Kazakhstan. Data regarding average content of 29 chemical elements in hair of population in different regions of Kazakhstan have been systemized. Coefficients of concentration of studies elements in hair relative to average values around the region have been calculated for each region. Groups of regions with specific spectrum of elements have been emphasized; these elements are accumulated in hair in quantities exceeding average indexes. Our results have showed significant differences in concentrations of chemical elements for studies groups and showed that population of Kazakhstan is exposed to different toxic substances. It depends on emissions to atmosphere from industrial enterprises dominating in each separate region. Performed researches have showed that obtained elemental composition of human hair residing in different regions of Kazakhstan reflects technogenic spectrum of elements.

Keywords: analysis of elemental composition of hair, forensic medical research of hair, identification of unknown dead bodies, microelements

Procedia PDF Downloads 122

Authors: Hasneet K. Kalsi, Julie K. Kilgariff

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Introduction: Within dentistry, the process for gaining informed consent has become more complex. To consent for treatment, patients must understand all reasonable treatment options and associated risks and benefits. Consenting is therefore deeply embedded in health literacy. Patients attending for dental consultation are often presented with an array of information and choices, yet studies show patients recall less than half of the information provided immediately after. Appropriate and comprehensible patient information leaflets (PILs) may be useful aid memories. In 2016 the World Health Organisation set improving health literacy as a global priority. Soon after, Scotland’s 2017-2025 Making it Easier: A Health Literacy Action Plan followed. This project involved the review of Restorative PILs used within Dundee Dental Hospital to assess the Content and Readability. Method: The current PIL on Root Canal Treatment (RCT) was created in 2011. This predates the Montgomery vs. NHS Lanarkshire case, a ruling which significantly impacted dental consenting processes, as well as General Dental Council’s (GDC’s) Standards for the Dental Team and Faculty of General Dental Practice’s Good Practice Guidance on Clinical Examination and Record-Keeping. Current evidence-based guidance, including that stipulated by the GDC, was reviewed. A 20-point Essential Content Checklist was designed to conform to best practice guidance for valid consenting processes. The RCT leaflet was scored against this to ascertain if the content was satisfactory. Having ensured the content satisfied medicolegal requirements, health literacy considerations were reviewed regarding readability. This was assessed using McLaughlin’s Simple Measure of Gobbledygook (SMOG) formula, which identifies school stages that would have to be achieved to comprehend the PIL. The sensitivity of the results to alternative readability methods were assessed. Results: The PIL was not sufficient for modern consenting processes and reflected a suboptimal level of health literacy. Evaluation of the leaflet revealed key content was missing, including information pertaining to risks and benefits. Only five points out of the 20-point checklist were present. The readability score was 16, equivalent to a level 2 in National Adult Literacy Standards/Scottish Credit and Qualification Framework Level 5; 62% of Scottish adults are able to read to this standard. Discussion: Assessment of the leaflet showed it was no longer fit for purpose. Reasons include a lack of pertinent information, a text-heavy leaflet lacking flow, and content errors. The SMOG score indicates a high level of comprehension is required to understand this PIL, which many patients may not possess. A new PIL, compliant with medicolegal and health literacy guidance, was designed with patient-driven checklists, notes spaces for annotations/ questions and areas for clinicians to highlight important case-specific information. It has been tested using the SMOG formula. Conclusion: PILs can be extremely useful. Studies show that interactive use can enhance their effectiveness. PILs should reflect best practice guidance and be understood by patients. The 2020 leaflet designed and implemented aims to fulfill the needs of a modern healthcare system and its service users. It embraces and embeds Scotland’s Health Literacy Action Plan within the consenting process. A review of further leaflets using this model is ongoing.

Keywords: consent, health literacy, patient information leaflet, restorative dentistry

Procedia PDF Downloads 121

Authors: Nishimwe Clemence, Mchunu Gugu, Mukamusoni Dariya

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Background: Community health workers and extension workers can play an important role in supporting families to adopt health practices, encourage delivery in a health care facility, and ensure time referral of mothers and newborns if needed. Saving the lives of neonates should, therefore, be a significant health outcome in any maternal and newborn health program that is being implemented. Furthermore, about half of a million mothers die from pregnancy-related causes. Maternal and newborn deaths related to the period of postnatal care are neglected. Some authors emphasized that in developing countries, newborn mortality rates have been reduced much more slowly because of the lack of many necessary facility-based and outreach service. The aim of this review was to critically analyze the implementation and integration process of the maternal and newborn health care program by maternal community health workers, into the health care system, in Africa. Furthermore, it aims to reduce maternal and newborn mortality. We addressed the following review question: (1) what process is involved in the implementation and integration of the maternal and newborn health care program by maternal community health workers during antenatal, delivery and postnatal care into health system care in Africa? Methods: The database searched was from Health Source: Nursing/Academic Edition through academic search complete via EBSCO Host. An iterative approach was used to go through Google scholarly papers. The reviewers considered adapted Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidance, and the Mixed Methods Appraisal Tool (MMAT) was used. Synthesis method in integrative review following elements of noting patterns and themes, seeing plausibility, clustering, counting, making contrasts and comparisons, discerning commons and unusual patterns, subsuming particulars into general, noting relations between variability, finding intervening factors and building a logical chain of evidence, using data–based convergent synthesis design. Results: From the seventeen of studies included, results focused on three dimensions inspired by the literature on antenatal, delivery, and postnatal interventions. From this, further conceptual framework was elaborated. The conceptual framework process of implementation and integration of maternal and newborn health care program by maternal community health workers was elaborated in order to ensure the sustainability of community based intervention. Conclusions: the review revealed that the implementation and integration of maternal and newborn health care program require planning. We call upon governments, non-government organizations, the global health community, all stakeholders including policy makers, program managers, evaluators, educators, and providers to be involved in implementation and integration of maternal and newborn health program in updated policy and community-based intervention. Furthermore, emphasis should be placed on competence, responsibility, and accountability of maternal community health workers, their training and payment, collaboration with health professionals in health facilities, and reinforcement of outreach service. However, the review was limited in focus to the African context, where the process of maternal and newborn health care program has been poorly implemented.

Keywords: Africa, implementation of integration, maternal, newborn

Procedia PDF Downloads 123

Authors: E. Mosiniewicz-Szablewska, P. Suchocki, P. C. Morais

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Despite the significant progress in cancer treatment, there is a need to search for new therapeutic methods in order to minimize side effects. Chemotherapy, the main current method of treating cancer, is non-selective and has a number of limitations. Toxicity to healthy cells is undoubtedly the biggest problem limiting the use of many anticancer drugs. The problem of how to kill cancer without harming a patient can be solved by using organic selenium (IV) compounds. Organic selenium (IV) compounds are a new class of materials showing a strong anticancer activity. They are first organic compounds containing selenium at the +4 oxidation level and therefore they eliminate the multidrug-resistance for all tumor cell lines tested so far. These materials are capable of selectively killing cancer cells without damaging the healthy ones. They are obtained by the incorporation of selenous acid (H2SeO3) into molecules of fatty acids of sunflower oil and therefore, they are inexpensive to manufacture. Attaching these compounds to magnetic carriers enables their precise delivery directly to the tumor area and the simultaneous application of the magnetic hyperthermia, thus creating a huge opportunity to effectively get rid of the tumor without any side effects. Polylactic-co-glicolic acid (PLGA) nanocapsules loaded with maghemite (-Fe2O3) nanoparticles and organic selenium (IV) compounds are successfully prepared by nanoprecipitation method. In vitro antitumor activity of the nanocapsules were evidenced using murine melanoma (B16-F10), oral squamos carcinoma (OSCC) and murine (4T1) and human (MCF-7) breast lines. Further exposure of these cells to an alternating magnetic field increased the antitumor effect of nanocapsules. Moreover, the nanocapsules presented antitumor effect while not affecting normal cells. Magnetic properties of the nanocapsules were investigated by means of dc magnetization, ac susceptibility and electron spin resonance (ESR) measurements. The nanocapsules presented a typical superparamagnetic behavior around room temperature manifested itself by the split between zero field-cooled/field-cooled (ZFC/FC) magnetization curves and the absence of hysteresis on the field-dependent magnetization curve above the blocking temperature. Moreover, the blocking temperature decreased with increasing applied magnetic field. The superparamagnetic character of the nanocapsules was also confirmed by the occurrence of a maximum in temperature dependences of both real ′(T) and imaginary ′′ (T) components of the ac magnetic susceptibility, which shifted towards higher temperatures with increasing frequency. Additionally, upon decreasing the temperature the ESR signal shifted to lower fields and gradually broadened following closely the predictions for the ESR of superparamagnetoc nanoparticles. The observed superparamagnetic properties of nanocapsules enable their simple manipulation by means of magnetic field gradient, after introduction into the blood stream, which is a necessary condition for their use as magnetic drug carriers. The observed anticancer and superparamgnetic properties show that the magnetic nanocapsules loaded with organic selenium (IV) compounds should be considered as an effective material system for magnetic drug delivery and magnetohyperthermia inductor in antitumor therapy.

Keywords: cancer treatment, magnetic drug delivery system, nanomaterials, nanotechnology

Procedia PDF Downloads 175

Authors: Serhat Tüzün, Tufan Demirel

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Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

Procedia PDF Downloads 245

Authors: Hassan Younis

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Purpose: The objective of this study is to review influential papers in the sustainability and supply chain studies domain, leveraging insights from this review to develop a structured framework for academics and researchers. This framework aims to assist scholars in identifying the most impactful publications for their scholarly pursuits. Subsequently, the study will apply and trial the developed framework on selected scholarly articles within the sustainability and supply chain studies domain to evaluate its efficacy, practicality, and reliability. Design/Methodology/Approach: Utilizing the "Publish or Perish" tool, a search was conducted to locate papers incorporating "sustainability" and "supply chain" in their titles. After rigorous filtering steps, a panel of university professors identified five crucial criteria for evaluating research robustness: average yearly citation counts (25%), scholarly contribution (25%), alignment of findings with objectives (15%), methodological rigor (20%), and journal impact factor (15%). These five evaluation criteria are abbreviated as “ACMAJ" framework. Each paper then received a tiered score (1-3) for each criterion, normalized within its category, and summed using weighted averages to calculate a Final Normalized Score (FNS). This systematic approach allows for objective comparison and ranking of the research based on its impact, novelty, rigor, and publication venue. Findings: The study's findings highlight the lack of structured frameworks for assessing influential sustainability research in supply chain management, which often results in a dependence on citation counts. A complete model that incorporates five essential criteria has been suggested as a response. By conducting a methodical trial on specific academic articles in the field of sustainability and supply chain studies, the model demonstrated its effectiveness as a tool for identifying and selecting influential research papers that warrant additional attention. This work aims to fill a significant deficiency in existing techniques by providing a more comprehensive approach to identifying and ranking influential papers in the field. Practical Implications: The developed framework helps scholars identify the most influential sustainability and supply chain publications. Its validation serves the academic community by offering a credible tool and helping researchers, students, and practitioners find and choose influential papers. This approach aids field literature reviews and study suggestions. Analysis of major trends and topics deepens our grasp of this critical study area's changing terrain. Originality/Value: The framework stands as a unique contribution to academia, offering scholars an important and new tool to identify and validate influential publications. Its distinctive capacity to efficiently guide scholars, learners, and professionals in selecting noteworthy publications, coupled with the examination of key patterns and themes, adds depth to our understanding of the evolving landscape in this critical field of study.

Keywords: supply chain management, sustainability, framework, model

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Authors: Xu Qian

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This abstract examines the concept of resilience in adolescents from both adolescent medicine and child psychology perspectives. It discusses the role of healthcare providers in fostering resilience among adolescents, encompassing physical, psychological, and social aspects. The paper highlights evidence-based interventions and practical strategies for promoting resilience in this population. Introduction: Resilience plays a crucial role in the healthy development of adolescents, enabling them to navigate through the challenges of this transitional period. This abstract explores the concept of resilience from the perspectives of adolescent medicine and child psychology, shedding light on the collective efforts of healthcare providers in fostering resilience. By integrating the principles and practices of these two disciplines, this abstract emphasizes the multidimensional nature of resilience and its significance in the overall well-being of adolescents. Methods: A comprehensive literature review was conducted, encompassing research articles, empirical studies, and expert opinions from both adolescent medicine and child psychology fields. The search included databases such as PubMed, PsycINFO, and Google Scholar, focusing on publications from the past decade. The review aimed to identify evidence-based interventions and practical strategies employed by healthcare providers to promote resilience among adolescents. Results: The review revealed several key findings regarding the promotion of resilience in adolescents. Firstly, resilience is a dynamic process influenced by individual characteristics, environmental factors, and the interaction between the two. Secondly, healthcare providers play a critical role in fostering resilience by addressing the physical, psychological, and social needs of adolescents. This entails comprehensive healthcare services that integrate medical care, mental health support, and social interventions. Thirdly, evidence-based interventions such as cognitive-behavioral therapy, social skills training, and positive youth development programs have shown promising outcomes in enhancing resilience. Discussion: The integration of adolescent medicine and child psychology perspectives provides a comprehensive framework for promoting resilience in adolescents. By acknowledging the interplay between physical health, psychological well-being, and social functioning, healthcare providers can tailor interventions to address the specific needs and challenges faced by adolescents. Collaborative efforts between medical professionals, psychologists, educators, and families are vital in creating a supportive environment that fosters resilience. Additionally, the findings highlight the importance of early identification and intervention, emphasizing the need for routine screening and assessment to identify adolescents at risk and provide timely support. Conclusion: Promoting resilience in adolescents requires a holistic approach that integrates adolescent medicine and child psychology perspectives. By recognizing the multifaceted nature of resilience, healthcare providers can implement evidence-based interventions and practical strategies to enhance the well-being of adolescents. The collaboration between healthcare professionals from different disciplines, alongside the involvement of families and communities, is crucial for creating a resilient support system. By investing in the promotion of resilience during adolescence, we can empower young individuals to overcome adversity and thrive in their journey toward adulthood.

Keywords: psychology, clinical psychology, child psychology, adolescent psychology, adolescent

Procedia PDF Downloads 44

Authors: Asma Ben Hmidene, Mizuho Hanaki, Kazuma Murakami, Kazuhiro Irie, Hiroko Isoda, Hideyuki Shigemori

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Type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD) are characterized as a peripheral metabolic disorder and a degenerative disease of the central nervous system, respectively. It is now widely recognized that T2DM and AD share many pathophysiological features including glucose metabolism, increased oxidative stress and amyloid aggregation. Amyloid beta (Aβ) is the components of the amyloid deposits in the AD brain and while the component of the amyloidogenic peptide deposit in the pancreatic islets of Langerhans is identified as human islet amyloid polypeptide (hIAPP). These two proteins are originated from the amyloid precursor protein and have a high sequence similarity. Although the amino acid sequences of amyloidogenic proteins are diverse, they all adopt a similar structure in aggregates called cross-beta-spine. Add at that, extensive studies in the past years have found that like Aβ1-42, IAPP forms early intermediate assemblies as spherical oligomers, implicating that these oligomers possess a common folding pattern or conformation. These similarities can be used in the search for effective pharmacotherapy for DM, since potent therapeutic agents such as antioxidants with a catechol moiety, proved to inhibit Aβ aggregation, may play a key role in the inhibit the aggregation of hIAPP treatment of patients with DM. Tamarix gallica is one of the halophyte species having a powerful antioxidant system. Although it was traditionally used for the treatment of various liver metabolic disorders, there is no report about the use of this plant for the treatment or prevention of T2DM and AD. Therefore, the aim of this work is to investigate their protective effect towards T2DM and AD by isolation and identification of α-glucosidase inhibitors, with antioxidant potential, that play an important role in the glucose metabolism in diabetic patient, as well as, the polymerization of hIAPP and Aβ aggregation inhibitors. Structure-activity relationship study was conducted for both assays. And as for α-glucosidase inhibitors, their mechanism of action and their synergistic potential when applied with a very low concentration of acarbose were also suggesting that they can be used not only as α-glucosidase inhibitors but also be combined with established α-glucosidase inhibitors to reduce their adverse effect. The antioxidant potential of the purified substances was evaluated by DPPH and SOD assays. Th-T assay using 42-mer amyloid β-protein (Aβ42) for AD and hIAPP which is a 37-residue peptide secreted by the pancreatic β –cells for T2DM and Transmission electronic microscopy (TEM) were conducted to evaluate the amyloid aggragation of the actives substances. For α-glucosidase, p-NPG and glucose oxidase assays were performed for determining the inhibition potential and structure-activity relationship study. The Enzyme kinetic protocol was used to study the mechanism of action. From this research, it was concluded that polyphenols playing a role in the glucose metabolism and oxidative stress can also inhibit the amyloid aggregation, and that substances with a catechol and glucuronide moieties inhibiting amyloid-β aggregation, might be used to inhibit the aggregation of hIAPP.

Keywords: α-glucosidase inhibitors, amyloid aggregation inhibition, mechanism of action, polyphenols, structure activity relationship, synergistic potential, tamarix gallica

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Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Pedro A. V. Ramos, Duarte M. S. Albuquerque, José C. F. Pereira

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Global warming mitigation is one of the main challenges of this century, having the net balance of greenhouse gas (GHG) emissions to be null or negative in 2050. Industry electrification is one of the main paths to achieving carbon neutrality within the goals of the Paris Agreement. Microwave heating is becoming a popular industrial heating mechanism due to the absence of direct GHG emissions, but also the rapid, volumetric, and efficient heating. In the present study, a mathematical model is used to simulate the production using microwave heating of two ceramic pigments, at high temperatures (above 1200 Celsius degrees). The two pigments studied were the yellow (Pr, Zr)SiO₂ and the brown (Ti, Sb, Cr)O₂. The chemical conversion of reactants into products was included in the model by using the kinetic triplet obtained with the model-fitting method and experimental data present in the Literature. The coupling between the electromagnetic, thermal, and chemical interfaces was also included. The simulations were computed in COMSOL Multiphysics. The geometry includes a moving plunger to allow for the cavity impedance matching and thus maximize the electromagnetic efficiency. To accomplish this goal, a MATLAB controller was developed to automatically search the position of the moving plunger that guarantees the maximum efficiency. The power is automatically and permanently adjusted during the transient simulation to impose stationary regime and total conversion, the two requisites of every converged solution. Both 2D and 3D geometries were used and a parametric study regarding the axial bed velocity and the heat transfer coefficient at the boundaries was performed. Moreover, a Verification and Validation study was carried out by comparing the conversion profiles obtained numerically with the experimental data available in the Literature; the numerical uncertainty was also estimated to attest to the result's reliability. The results show that the model-fitting method employed in this work is a suitable tool to predict the chemical conversion of reactants into the pigment, showing excellent agreement between the numerical results and the experimental data. Moreover, it was demonstrated that higher velocities lead to higher thermal efficiencies and thus lower energy consumption during the process. This work concludes that the electromagnetic heating of materials having high loss tangent and low thermal conductivity, like ceramic materials, maybe a challenge due to the presence of hot spots, which may jeopardize the product quality or even the experimental apparatus. The MATLAB controller increased the electromagnetic efficiency by 25% and global efficiency of 54% was obtained for the titanate brown pigment. This work shows that electromagnetic heating will be a key technology in the decarbonization of the ceramic sector as reductions up to 98% in the specific GHG emissions were obtained when compared to the conventional process. Furthermore, numerical simulations appear as a suitable technique to be used in the design and optimization of microwave applicators, showing high agreement with experimental data.

Keywords: automatic impedance matching, ceramic pigments, efficiency maximization, high-temperature microwave heating, input power control, numerical simulation

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Authors: Sun-Hee Lee, Amanda Kraley

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The “MeToo” movement is a social movement against sexual abuse and harassment. Though the hashtag went viral in 2017 following different cultural flashpoints in different countries, the initial response was quiet in South Korea. This radically changed in January 2018, when a high-ranking senior prosecutor, Seo Ji-hyun, gave a televised interview discussing being sexually assaulted by a colleague. Acknowledging public anger, particularly among women, on the long-existing problems of sexual harassment and abuse, the South Korean media have focused on several high-profile cases. Analyzing the media representation of these cases is a window into the evolving South Korean discourse around “MeToo.” This study presents a linguistic analysis of “MeToo” discourse in South Korea by utilizing a corpus-based approach. The term corpus (pl. corpora) is used to refer to electronic language data, that is, any collection of recorded instances of spoken or written language. A “MeToo” corpus has been collected by extracting newspaper articles containing the keyword “MeToo” from BIGKinds, big data analysis, and service and Nexis Uni, an online academic database search engine, to conduct this language analysis. The corpus analysis explores how Korean media represent accusers and the accused, victims and perpetrators. The extracted data includes 5,885 articles from four broadsheet newspapers (Chosun, JoongAng, Hangyore, and Kyunghyang) and 88 articles from two Korea-based English newspapers (Korea Times and Korea Herald) between January 2017 and November 2020. The information includes basic data analysis with respect to keyword frequency and network analysis and adds refined examinations of select corpus samples through naming strategies, semantic relations, and pragmatic properties. Along with the exponential increase of the number of articles containing the keyword “MeToo” from 104 articles in 2017 to 3,546 articles in 2018, the network and keyword analysis highlights ‘US,’ ‘Harvey Weinstein’, and ‘Hollywood,’ as keywords for 2017, with articles in 2018 highlighting ‘Seo Ji-Hyun, ‘politics,’ ‘President Moon,’ ‘An Ui-Jeong, ‘Lee Yoon-taek’ (the names of perpetrators), and ‘(Korean) society.’ This outcome demonstrates the shift of media focus from international affairs to domestic cases. Another crucial finding is that word ‘defamation’ is widely distributed in the “MeToo” corpus. This relates to the South Korean legal system, in which a person who defames another by publicly alleging information detrimental to their reputation—factual or fabricated—is punishable by law (Article 307 of the Criminal Act of Korea). If the defamation occurs on the internet, it is subject to aggravated punishment under the Act on Promotion of Information and Communications Network Utilization and Information Protection. These laws, in particular, have been used against accusers who have publicly come forward in the wake of “MeToo” in South Korea, adding an extra dimension of risk. This corpus analysis of “MeToo” newspaper articles contributes to the analysis of the media representation of the “MeToo” movement and sheds light on the shifting landscape of gender relations in the public sphere in South Korea.

Keywords: corpus linguistics, MeToo, newspapers, South Korea

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Authors: Alessandra Swiny, Yiorgos Hadjichristou

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There exists an on-going geographical scar creating a division through the Island of Cyprus and its capital, Nicosia. The currently amputated city center is accessed legally by the United Nations convoys, infiltrated only by Turkish and Greek Cypriot army scouts and illegal traders and scavengers. On Christmas day 1963 in Nicosia, Captain M. Hobden of the British Army took a green chinagraph pencil and on a large scale Joint Army-RAF map ‘marked’ the division. From then on this ‘buffer zone’ was called the ‘green line.' This once dividing form, separating the main communities of Greek and Turkish Cypriots from one another, has now been fully reclaimed by an autonomous intruder. It's currently most captivating inhabitant is nature. She keeps taking over, for the past fifty years indigenous and introduced fauna and flora thrive; trees emerge from rooftops and plants, bushes and flowers grow randomly through the once bustling market streets, allowing this ‘no man’s land’ to teem with wildlife. And where are its limits? The idea of fluidity is ever present; it encroaches into the urban and built environment that surrounds it, and notions of ownership and permanence are questioned. Its qualities have contributed significantly in the search for new ‘identities,' expressed in the emergence of new living conditions, be they real or surreal. Without being physically reachable, it can be glimpsed at through punctured peepholes, military bunker windows that act as enticing portals into an emotional and conceptual level of inhabitation. The zone is mystical and simultaneously suspended in time, it triggers people’s imagination, not just that of the two prevailing communities but also of immigrants, refugees, and visitors; it mesmerizes all who come within its proximity. The paper opens a discussion on the issues and the binary questions raised. What is natural and artificial; what is private and public; what is ephemeral and permanent? The ‘green line’ exists in a central fringe condition and can serve in mixing generations and groups of people; mingling functions of living with work and social interaction; merging nature and the human being in a new-found synergy of human hope and survival, allowing thus for new notions of place to be introduced. Questions seek to be answered, such as, “Is the impossibility of dwelling made possible, by interweaving these ‘in-between conditions’ into eloquently traced spaces?” The methodologies pursued are developed through academic research, professional practice projects, and students’ research/design work. Realized projects, case studies and other examples cited both nationally and internationally hold global and local applications. Both paths of the research deal with the explorative understanding of the impossibility of dwelling, testing the limits of its autonomy. The expected outcome of the experience evokes in the user a sense of a new urban landscape, created from human topographies that echo the voice of an emerging identity.

Keywords: urban wildlife, human topographies, buffer zone, no man’s land

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Authors: Ayla Hoeta

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The focus of this research is mahi Maramataka, ‘the practices of Maramataka’ as a traditional and evolving knowledge system and its connection to whaanau oranga (wellbeing) and healing. Centering kaupapa Maaori methods and knowledge this research will explore how Maramataka can be used as a tool for oranga and healing for whaanau to engage with different environments aligned with Maramataka flow and optimal time based on the environment. Maramataka is an ancestral lunar environmental knowledge system rooted within korero tuku iho, Maaori creation stories, dating back to the beginning of time. The significance of Maramataka is the ancient environmental knowledge and the connecting energy flow of mauri (life force) between whenua (land), moana (ocean) and rangi (sky). The lunar component of the Maramataka is widely understood and highlights the different phases of the moon. Each moon phase is named with references to puurakau stories and environmental and ecological information. Marama, meaning moon and taka, meaning cycle, is used as a lunar and environmental calendar. There are lunar phases that are optimal for specific activities, such as the Tangaroa phase, a time of abundance and productivity and ocean-based activities like fishing. Other periods in the Maramataka, such as Rakaunui (full moon), connect the highest tides and highest energy of the lunar cycle, ideal for social, physical activity and particularly planting. Other phases like Tamatea are unpredictable whereas Whiro (new moon/s) is reflective, deep and cautious during the darkest nights. Whaanau, particularly in urban settings have become increasingly disconnected from the natural environment, the Maramataka has become a tool that they can connect to which offers an alternative to dominant perspectives of health and is an approach that is uniquely Maaori. In doing so, this research will raise awareness of oranga or lack of oranga, and lived experience of whaanau in Tamaki Makaurau - Aotearoa, on a journey to revival of Maramataka and healing. The research engages Hautu Waka as a methodology using the methods of ancient kaupapa Māori practises based on wayfinding and attunement with the natural environment. Using ancient ways of being, knowing, seeing and doing the Hautu Waka will centre kaupapa Maaori perspectives to process design, reflection and evaluation. The methods of Hautu Waka consists of five interweaving phases, 1) Te Rapunga (the search) in infinite potential, 2) Te Kitenga (the seeing), observations of and attunement to tohu 3) te whainga (the pursuit) and deeply exploring key tohu 4) te whiwhinga (the acquiring), of knowledge and clearer ideas, 5) Te Rawenga (the celebration), reflection and acknowledgement of the journey and achievements. This research is an expansion from my creative practices across whaanau-centred inquiry, to understand the benefits of Maramataka and how it can be embodied and practised in a modern-day context to support oranga and healing. Thus, the goal is to work with kaupapa Maaori methodologies to authenticate as a Maaori practitioner and researcher and allow an authentic indigenous approach to the exploration of Maramataka and through a kaupapa Maaori lens.

Keywords: maramataka (Maaori calendar), tangata (people), taiao (environment), whenua (land), whaanau (family), hautu waka (navigation framework)

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Authors: Frederica Pettit

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Contribution: Stakeholder involvement in CSR is essential to ensuring pro-environmental attitudes and behaviours across multi-stakeholder groups. Despite increased awareness of the benefits surrounding a collaborative approach to sustainability communications, its success is limited by difficulties engaging with active online conversations with stakeholder groups. Whilst previous research defines the effectiveness of sustainability communications; this paper contributes to knowledge through the development of a theoretical framework that explores the processes to achieving pro-environmental attitudes and behaviours in stakeholder groups. The research will also consider social media as an opportunity to communicate CSR information to all stakeholder groups. Approach: A systematic review was chosen to investigate the effectiveness of the types of sustainability communications used in the hospitality and tourism industries. The systematic review was completed using Web of Science and Scopus using the search terms “sustainab* communicat*” “effective or effectiveness,” and “hospitality or tourism,” limiting the results to peer-reviewed research. 133 abstracts were initially read, with articles being excluded for irrelevance, duplicated articles, non-empirical studies, and language. A total of 45 papers were included as part of the systematic review. 5 propositions were created based on the results of the systematic review, helping to develop a theoretical framework of the processes needed for companies to encourage pro-environmental behaviours across multi-stakeholder groups. Results: The theoretical framework developed in the paper determined the processes necessary for companies to achieve pro-environmental behaviours in stakeholders. The processes to achieving pro-environmental attitudes and behaviours are stakeholder-focused, identifying the need for communications to be specific to their targeted audience. Collaborative communications that enable stakeholders to engage with CSR information and provide feedback lead to a higher awareness of CSR shared visions and pro-environmental attitudes and behaviours. These processes should also aim to improve their relationships with stakeholders through transparency of CSR, CSR strategies that match stakeholder values and ethics whilst prioritizing sustainability as part of their job role. Alternatively, companies can prioritize pro-environmental behaviours using choice editing by mainstreaming sustainability as the only option. In recent years, there has been extensive research on social media as a viable source of sustainability communications, with benefits including direct interactions with stakeholders, the ability to enforce the authenticity of CSR activities and encouragement of pro-environmental behaviours. Despite this, there are challenges to implementing CSR, including difficulties controlling stakeholder criticisms, negative stakeholder influences and comments left on social media platforms. Conclusion: A lack of engagement with CSR information is a reoccurring reason for preventing pro-environmental attitudes and behaviours across stakeholder groups. Traditional CSR strategies contribute to this due to their inability to engage with their intended audience. Hospitality and tourism companies are improving stakeholder relationships through collaborative processes which reduce single-use plastic consumption. A collaborative approach to communications can lead to stakeholder satisfaction, leading to changes in attitudes and behaviours. Different sources of communications are accessed by different stakeholder groups, identifying the need for targeted sustainability messaging, creating benefits such as direct interactions with stakeholders, the ability to enforce the authenticity of CSR activities, and encouraging engagement with sustainability information.

Keywords: hospitality, pro-environmental attitudes and behaviours, sustainability communication, social media

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Authors: Yuliya Y. Gavrichenko

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Background and Aims: The increasing bacterial resistance to almost all the available antibiotics has encouraged scientists to search for alternative sources of antibacterial agents. Nowadays, it is known that many plant secondary metabolites have diverse biological activity. These compounds can be potentially active against human bacterial and viral infections. Extended research has been carried out to explore the use of the luminescent bacterial test as a rapid, accurate and inexpensive method to assess the antibacterial properties and to predict the biological activity spectra for plant origin substances. Method: Botanical material of fifteen species was collected from their natural and cultural habitats on the Crimean peninsula. The aqueous extracts of following plants were tested: Robinia pseudoacacia L., Sideritis comosa, Cotinus coggygria Scop., Thymus serpyllum L., Juglans regia L., Securigera varia L., Achillea millefolium L., Phlomis taurica, Corylus avellana L., Sambucus nigra L., Helichrysum arenarium L., Glycyrrhiza glabra L., Elytrigia repens L., Echium vulgare L., Conium maculatum L. The test was carried out using luminous strains of marine bacteria Photobacterium leiognathi, which was isolated from the Sea of Azov as well as four Escherichia coli MG1655 recombinant strains harbouring Vibrio fischeri luxCDABE genes. Results: The bactericidal capacity of plant extracts showed significant differences in the study. Cotinus coggygria, Phlomis taurica, Juglans regia L. proved to be the most toxic to P. leiognathi. (EC50 = 0.33 g dried plant/l). Glycyrrhiza glabra L., Robinia pseudoacacia L., Sideritis comosa and Helichrysum arenarium L. had moderate inhibitory effects (EC50 = 3.3 g dried plant/l). The rest of the aqueous extracts have decreased the luminescence of no more than 50% at the lowest concentration (16.5 g dried plant/l). Antibacterial activity of herbal extracts against constitutively luminescent E. coli MG1655 (pXen7-lux) strain was observed at approximately the same level as for P. leiognathi. Cotinus coggygria and Conium maculatum L. extracts have increased light emission in the mutant E. coli MG1655 (pFabA-lux) strain which is associated with cell membranes damage. Sideritis comosa, Phlomis taurica, Juglans regia induced SOS response in E. coli (pColD-lux) strain. Glycyrrhiza glabra L. induced protein damage response in E. coli MG1655 (pIbpA-lux) strain. Conclusion: The received results have shown that the plants’ extracts had nonspecific antimicrobial effects against both E. coli (pXen7-lux) and P. leiognathi biosensors. Mutagenic, cytotoxic and protein damage effects have been observed. In general, the bioluminescent inhibition test result correlated with the traditional use of screened plants. It leads to the following conclusion that whole-cell luminescent biosensors could be the indicator of overall plants antibacterial capacity. The results of the investigation have shown a possibility of bioluminescent method in medicine and pharmacy as an approach to research the antibacterial properties of medicinal plants.

Keywords: antibacterial property, bioluminescence, medicinal plants, whole-cell biosensors

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 47

Authors: V. Howard, R. Maguire, S. Corrigan

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Background: Type 1 Diabetes (T1D) is a chronic autoimmune disease, typically diagnosed in childhood. T1D puts an enormous strain on families; controlling blood-glucose in children is difficult and the consequences of poor control for patient health are significant. Successful illness management and better health outcomes can be dependent on quality of caregiving. On diagnosis, parent-caregivers face a steep learning curve as T1D care requires a significant level of knowledge to inform complex decision making throughout the day. The majority of illness management is carried out in the home setting, independent of clinical health providers. Parent-caregivers vary in their level of knowledge and their level of engagement in applying this knowledge in the practice of illness management. Enabling researchers to quantify these aspects of the caregiver experience is key to identifying targets for psychosocial support interventions, which are desirable for reducing stress and anxiety in this highly burdened cohort, and supporting better health outcomes in children. Currently, there are limited tools available that are designed to capture this information. Where tools do exist, they are not comprehensive and do not adequately capture the lived experience. Objectives: Development of quantitative tools, informed by lived experience, to enable researchers gather data on parent-caregiver knowledge and engagement, which accurately represents the experience/cohort and enables exploration of questions that are of real-world value to the cohort themselves. Methods: This research employed an engaged approach to address the problem of quantifying two key aspects of caregiver diabetes management: Knowledge and engagement. The research process was multi-staged and iterative. Stage 1: Working from a constructivist standpoint, literature was reviewed to identify relevant questionnaires, scales and single-item measures of T1D caregiver knowledge and engagement, and harvest candidate questionnaire items. Stage 2: Aggregated findings from the review were circulated among a PPI (patient and public involvement) expert panel of caregivers (n=6), for discussion and feedback. Stage 3: In collaboration with the expert panel, data were interpreted through the lens of lived experience to create a long-list of candidate items for novel questionnaires. Items were categorized as either ‘knowledge’ or ‘engagement’. Stage 4: A Delphi-method process (iterative surveys) was used to prioritize question items and generate novel questions that further captured the lived experience. Stage 5: Both questionnaires were piloted to refine wording of text to increase accessibility and limit socially desirable responding. Stage 6: Tools were piloted using an online survey that was deployed using an online peer-support group for caregivers for Juveniles with T1D. Ongoing Research: 123 parent-caregivers completed the survey. Data analysis is ongoing to establish face and content validity qualitatively and through exploratory factor analysis. Reliability will be established using an alternative-form method and Cronbach’s alpha will assess internal consistency. Work will be completed by early 2024. Conclusion: These tools will enable researchers to gain deeper insights into caregiving practices among parents of juveniles with T1D. Development was driven by lived experience, illustrating the value of engaged research at all levels of the research process.

Keywords: caregiving, engaged research, juvenile type 1 diabetes, quantified engagement and knowledge

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Authors: Awatef Ahmed Ben Ramadan, Aqsa Arshad

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Background: There is a huge Muslim migration movement to North America and Europe for several reasons, primarily refuge from war areas and partly to search for better work and educational chances. There are always concerns regarding first-Generation Immigrant women's health and computer literacy, an adequate understanding of the health systems, and the use of the existing healthcare technology and services effectively and efficiently. Language proficiency level, preference for cultural and traditional remedies, socioeconomic factors, fear of stereotyping, limited accessibility to health services, and general unfamiliarity with the existing health services and resources are familiar variables among these women. Aims: The current study aims to assess the health and digital literacy of first-generation Muslim women in Atlanta city. Also, the study aims to examine how the COVID-19 pandemic has encouraged the use of health information technology and increased technology awareness among the targeted women. Methods: The study design is cross-sectional correlational research. The study will be conducted to produce preliminary results that the investigators want to have to supplement an NIH grant application about leveraging information technology to reduce the health inequalities amongst the first-generation immigrant Muslim women in Atlanta City. The investigators will collect the study data in two phases using different tools. Phase one was conducted in June 2022; the investigators used tools to measure health and digital literacy amongst 42 first-generation immigrant Muslim women. Phase two was conducted in November 2022; the investigators measured the Knowledge, Attitude, and Practice (KAP) of using health information technology such as telehealth from a sample of 45 first-generation Muslim immigrant women in Atlanta; in addition, the investigators measured how the current pandemic has affected their KAP to use telemedicine and telehealth services. Both phases' study participants were recruited using convenience sampling methodology. The investigators collected around 40 of 18 years old or older first-generation Muslim immigrant women for both study phases. The study excluded Immigrants who hold work visas and second-generation immigrants. Results: At the point of submitting this abstract, the investigators are still analyzing the study data to produce preliminary results to apply for an NIH grant entitled "Leveraging Health Information Technology (Health IT) to Address and Reduce Health Care Disparities (R01 Clinical Trial Optional)". This research will be the first step of a comprehensive research project to assess and measure health and digital literacy amongst a vulnerable community group. The targeted group might have different points of view from the U.S.-born inhabitants on how to: promote their health, gain healthy lifestyles and habits, screen for diseases, adhere to health treatment and follow-up plans, perceive the importance of using available and affordable technology to communicate with their providers and improve their health, and help in making serious decisions for their health. The investigators aim to develop an educational and instructional health mobile application considering the language and cultural factors that affect immigrants' ability to access different health and social support sources, know their health rights and obligations in their communities, and improve their health behavior and behavior lifestyles.

Keywords: first-generation immigrant Muslim women, telehealth, COVID-19 pandemic, health information technology, health and digital literacy

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Authors: Tatiana Butkova, Nikolai Kibrik, Kristina Malsagova, Alexander Izotov, Alexander Stepanov, Anna Kaysheva

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Relevance. The genetic risk of developing schizophrenia is determined by two factors: single nucleotide polymorphisms and gene copy number variations. The search for serological markers for early diagnosis of schizophrenia is driven by the fact that the first five years of the disease are accompanied by significant biological, psychological, and social changes. It is during this period that pathological processes are most amenable to correction. The aim of this study was to analyze single nucleotide polymorphisms (SNPs) that are hypothesized to potentially influence the onset and development of the endogenous process. Materials and Methods It was analyzed 73 single nucleotide polymorphism variants. The study included 48 patients undergoing inpatient treatment at "Psychiatric Clinical Hospital No. 1" in Moscow, comprising 23 females and 25 males. Inclusion criteria: - Patients aged 18 and above. - Diagnosis according to ICD-10: F20.0, F20.2, F20.8, F21.8, F25.1, F25.2. - Voluntary informed consent from patients. Exclusion criteria included: - The presence of concurrent somatic or neurological pathology, neuroinfections, epilepsy, organic central nervous system damage of any etiology, and regular use of medication. - Substance abuse and alcohol dependence. - Women who were pregnant or breastfeeding. Clinical and psychopathological assessment was complemented by psychometric evaluation using the PANSS scale at the beginning and end of treatment. The duration of observation during therapy was 4-6 weeks. Total DNA extraction was performed using QIAamp DNA. Blood samples were processed on Illumina HiScan and genotyped for 652,297 markers on the Infinium Global Chips Screening Array-24v2.0 using the IMPUTE2 program with parameters Ne=20,000 and k=90. Additional filtration was performed based on INFO>0.5 and genotype probability>0.5. Quality control of the obtained DNA was conducted using agarose gel electrophoresis, with each tested sample having a volume of 100 µL. Results. It was observed that several SNPs exhibited gender dependence. We identified groups of single nucleotide polymorphisms with a membership of 80% or more in either the female or male gender. These SNPs included rs2661319, rs2842030, rs4606, rs11868035, rs518147, rs5993883, and rs6269.Another noteworthy finding was the limited combination of SNPs sufficient to manifest clinical symptoms leading to hospitalization. Among all 48 patients, each of whom was analyzed for deviations in 73 SNPs, it was discovered that the combination of involved SNPs in the manifestation of pronounced clinical symptoms of schizophrenia was 19±3 out of 73 possible. In study, the frequency of occurrence of single nucleotide polymorphisms also varied. The most frequently observed SNPs were rs4849127 (in 90% of cases), rs1150226 (86%), rs1414334 (75%), rs10170310 (73%), rs2857657, and rs4436578 (71%). Conclusion. Thus, the results of this study provide additional evidence that these genes may be associated with the development of schizophrenia spectrum disorders. However, it's impossible cannot rule out the hypothesis that these polymorphisms may be in linkage disequilibrium with other functionally significant polymorphisms that may actually be involved in schizophrenia spectrum disorders. It has been shown that missense SNPs by themselves are likely not causative of the disease but are in strong linkage disequilibrium with non-functional SNPs that may indeed contribute to disease predisposition.

Keywords: gene polymorphisms, genotyping, single nucleotide polymorphisms, schizophrenia.

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Authors: Melanie Grier, Adam Murry

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Objective: Worldwide, Indigenous Peoples experience underemployment and poverty at disproportionately higher rates than non-Indigenous people, despite similar rates of employment seeking. Euro-colonial conquest and genocidal assimilation policies are implicated as perpetuating poverty, which research consistently links to health and wellbeing disparities. Many of the contributors to poverty, such as inadequate income and lack of access to medical care, can be directly or indirectly linked to underemployment. Calls have been made to prioritize Indigenous perspectives in Industrial-Organizational (I/O) psychology research, yet the literature on Indigenous employment remains scarce. What does exist is disciplinarily diverse, topically scattered, and lacking evidence of community-based participatory research (CBPR) practices, a research project approach which prioritizes community leadership, partnership, and betterment and reduces the potential for harm. Due to the harmful colonial legacy of extractive scientific inquiry "on" rather than "with" Indigenous groups, Indigenous leaders and research funding agencies advocate for academic researchers to adopt reparative research methodologies such as CBPR to be used when studying issues pertaining to Indigenous Peoples or individuals. However, the frequency and consistency of CBPR implementation within scholarly discourse are unknown. Therefore, this project’s goal is two-fold: (1) to understand what comprises CBPR in Indigenous research and (2) to determine if CBPR has been historically used in Indigenous employment research. Method: Using a systematic literature review process, sixteen articles about CBPR use with Indigenous groups were selected, and content was analyzed to identify key components comprising CBPR usage. An Indigenous CBPR components framework was constructed and subsequently utilized to analyze the Indigenous employment empirical literature. A similar systematic literature review process was followed to search for relevant empirical articles on Indigenous employment. A total of 120 articles were identified in six global regions: Australia, New Zealand, Canada, America, the Pacific Islands, and Greenland/Norway. Each empirical study was procedurally examined and coded for criteria inclusion using content analysis directives. Results: Analysis revealed that, in total, CBPR elements were used 14% of the time in Indigenous employment research. Most studies (n=69; 58%) neglected to mention using any CBPR components, while just two studies discussed implementing all sixteen (2%). The most significant determinant of overall CBPR use was community member partnership (CP) in the research process. Studies from New Zealand were most likely to use CBPR components, followed by Canada, Australia, and America. While CBPR use did increase slowly over time, meaningful temporal trends were not found. Further, CBPR use did not directly correspond with the total number of topical articles published that year. Conclusions: Community-initiated and engaged research approaches must be better utilized in employment studies involving Indigenous Peoples. Future research efforts must be particularly attentive to community-driven objectives and research protocols, emphasizing specific areas of concern relevant to the field of I/O psychology, such as organizational support, recruitment, and selection.

Keywords: community-based participatory research, content analysis, employment, indigenous research, international, reconciliation, recruitment, reparative research, selection, systematic literature review

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Authors: Palak V. Patel, Jessica Pixley, Steven R. Feldman

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Introduction: Basal cell carcinoma (BCC) is the most common skin cancer worldwide and requires substantial resources to treat. When choosing between indicated therapies, providers consider their associated adverse effects, efficacy, cosmesis, and function preservation. The patient’s tumor burden, infiltrative risk, and risk of tumor recurrence are also considered. Treatment cost is often left out of these discussions. This can lead to financial toxicity, which describes the harm and quality of life reductions inflicted by high care costs. Methods: We studied the guidelines set forth by the American Academy of Dermatology for the treatment of BCC. A PubMed literature search was conducted to identify the costs of each recommended therapy. We discuss costs alongside treatment efficacy and side-effect profile. Results: Surgical treatment for BCC can be cost-effective if the appropriate treatment is selected for the presenting tumor. Curettage and electrodesiccation can be used in low-grade, low-recurrence tumors in aesthetically unimportant areas. The benefits of cost-conscious care are not likely to be outweighed by the risks of poor cosmesis or tumor return ($471 BCC of the cheek). When tumor burden is limited, MMS offers better cure rates and lower recurrence rates than surgical excision, and with comparable costs (MMS $1263; SE $949). Surgical excision with permanent sections may be indicated when tumor burden is more extensive or if molecular testing is necessary. The utility of surgical excision with frozen sections, which costs substantially more than MMS without comparable outcomes, is less clear (SE with frozen sections $2334-$3085). Less data exists on non-surgical treatments for BCC. These techniques cost less, but recurrence-risk is high. Side-effects of nonsurgical treatment are limited to local skin reactions, and cosmesis is good. Cryotherapy, 5-FU, and MAL-PDT are all more affordable than surgery, but high recurrence rates increase risk of secondary financial and psychosocial burden (recurrence rates 21-39%; cost $100-270). Radiation therapy offers better clearance rates than other nonsurgical treatments but is associated with similar recurrence rates and a significantly larger financial burden ($2591-$3460 BCC of the cheek). Treatments for advanced or metastatic BCC are extremely costly, but few patients require their use, and the societal cost burden remains low. Vismodegib and sonidegib have good response rates but substantial side effects, and therapy should be combined with multidisciplinary care and palliative measures. Expert-review has found sonidegib to be the less expensive and more efficacious option (vismodegib $128,358; sonidegib $122,579). Platinum therapy, while not FDA-approved, is also effective but expensive (~91,435). Immunotherapy offers a new line of treatment in patients intolerant of hedgehog inhibitors ($683,061). Conclusion: Dermatologists working within resource-compressed practices and with resource-limited patients must prudently manage the healthcare dollar. Surgical therapies for BCC offer the lowest risk of recurrence at the most reasonable cost. Non-surgical therapies are more affordable, but high recurrence rates increase the risk of secondary financial and psychosocial burdens. Treatments for advanced BCC are incredibly costly, but the low incidence means the overall cost to the system is low.

Keywords: nonmelanoma skin cancer, basal cell skin cancer, squamous cell skin cancer, cost of care

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Authors: Nilki Upathissa, Torin Wirasinghe

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This solution addresses the challenges faced by traditional bookstores and the limitations of digital media, striking a balance between the tactile experience of printed books and the convenience of modern technology. The book exchange system offers a sustainable alternative, empowering users to access a diverse range of books while promoting community engagement. The user-friendly interfaces incorporated into the book exchange system ensure a seamless and enjoyable experience for users. Intuitive features for book management, search, and messaging facilitate effortless exchanges and interactions between users. By streamlining the process, the system encourages readers to explore new books aligned with their interests, enhancing the overall reading experience. Central to the system's success is the hybrid recommendation engine, which leverages advanced technologies such as Long Short-Term Memory (LSTM) models. By analyzing user input, the engine accurately predicts genre preferences, enabling personalized book recommendations. The hybrid approach integrates multiple technologies, including user interfaces, machine learning models, and recommendation algorithms, to ensure the accuracy and diversity of the recommendations. The evaluation of the book exchange system with the hybrid recommendation engine demonstrated exceptional performance across key metrics. The high accuracy score of 0.97 highlights the system's ability to provide relevant recommendations, enhancing users' chances of discovering books that resonate with their interests. The commendable precision, recall, and F1score scores further validate the system's efficacy in offering appropriate book suggestions. Additionally, the curve classifications substantiate the system's effectiveness in distinguishing positive and negative recommendations. This metric provides confidence in the system's ability to navigate the vast landscape of book choices and deliver recommendations that align with users' preferences. Furthermore, the implementation of this book exchange system with a hybrid recommendation engine has the potential to revolutionize the way readers interact with printed books. By facilitating book exchanges and providing personalized recommendations, the system encourages a sense of community and exploration within the reading community. Moreover, the emphasis on sustainability aligns with the growing global consciousness towards eco-friendly practices. With its robust technical approach and promising evaluation results, this solution paves the way for a more inclusive, accessible, and enjoyable reading experience for book lovers worldwide. In conclusion, the developed book exchange system with a hybrid recommendation engine represents a progressive solution to the challenges faced by traditional bookstores and the limitations of digital media. By promoting sustainability, widening access to printed books, and fostering engagement with reading, this system addresses the evolving needs of book enthusiasts. The integration of user-friendly interfaces, advanced machine learning models, and recommendation algorithms ensure accurate and diverse book recommendations, enriching the reading experience for users.

Keywords: recommendation systems, hybrid recommendation systems, machine learning, data science, long short-term memory, recurrent neural network

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Authors: Zuhal Kurt, Meral Kurt, Bilge T. Bal, Kemal Ozkan

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Shade matching and reproduction is the most important element of success in prosthetic dentistry. Until recently, shade matching procedure was implemented by dentists visual perception with the help of shade guides. Since many factors influence visual perception; tooth shade matching using visual devices (shade guides) is highly subjective and inconsistent. Subjective nature of this process has lead to the development of instrumental devices. Nowadays, colorimeters, spectrophotometers, spectroradiometers and digital image analysing systems are used for instrumental shade selection. Instrumental devices have advantages that readings are quantifiable, can obtain more rapidly and simply, objectively and precisely. However, these devices have noticeable drawbacks. For example, translucent structure and irregular surfaces of teeth lead to defects on measurement with these devices. Also between the results acquired by devices with different measurement principles may make inconsistencies. So, its obligatory to search for new methods for dental shade matching process. A computer-aided system device; digital camera has developed rapidly upon today. Currently, advances in image processing and computing have resulted in the extensive use of digital cameras for color imaging. This procedure has a much cheaper process than the use of traditional contact-type color measurement devices. Digital cameras can be taken by the place of contact-type instruments for shade selection and overcome their disadvantages. Images taken from teeth show morphology and color texture of teeth. In last decades, a new method was recommended to compare the color of shade tabs taken by a digital camera using color features. This method showed that visual and computer-aided shade matching systems should be used as concatenated. Recently using methods of feature extraction techniques are based on shape description and not used color information. However, color is mostly experienced as an essential property in depicting and extracting features from objects in the world around us. When local feature descriptors with color information are extended by concatenating color descriptor with the shape descriptor, that descriptor will be effective on visual object recognition and classification task. Therefore, the color descriptor is to be used in combination with a shape descriptor it does not need to contain any spatial information, which leads us to use local histograms. This local color histogram method is remain reliable under variation of photometric changes, geometrical changes and variation of image quality. So, coloring local feature extraction methods are used to extract features, and also the Scale Invariant Feature Transform (SIFT) descriptor used to for shape description in the proposed method. After the combination of these descriptors, the state-of-art descriptor named by Color-SIFT will be used in this study. Finally, the image feature vectors obtained from quantization algorithm are fed to classifiers such as Nearest Neighbor (KNN), Naive Bayes or Support Vector Machines (SVM) to determine label(s) of the visual object category or matching. In this study, SVM are used as classifiers for color determination and shade matching. Finally, experimental results of this method will be compared with other recent studies. It is concluded from the study that the proposed method is remarkable development on computer aided tooth shade determination system.

Keywords: classifiers, color determination, computer-aided system, tooth shade matching, feature extraction

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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