Search results for: Ornstein-Uhlenbeck type models

Authors: Benjamin Thomas Greer, Grace Cotulla, Mandy Johnson

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Human trafficking is one of the fastest growing international crimes and human rights violations in the world. The United States Department of State (State Department) approximates some 800,000 to 900,000 people are annually trafficked across sovereign borders, with approximately 14,000 to 17,500 of these people coming into the United States. Today’s slavery is conducted by unscrupulous individuals who are often connected to organized criminal enterprises and transnational gangs, extracting huge monetary sums. According to the International Labour Organization (ILO), human traffickers collect approximately $32 billion worldwide annually. Surpassed only by narcotics dealing, trafficking of humans is tied with illegal arms sales as the second largest criminal industry in the world and is the fastest growing field in the 21st century. Perpetrators of this heinous crime abound. They are not limited to single or “sole practitioners” of human trafficking, but rather, often include Transnational Criminal Organizations (TCO), domestic street gangs, labor contractors, and otherwise seemingly ordinary citizens. Monetary gain is being elevated over territorial disputes and street gangs are increasingly operating in a collaborative effort with TCOs to further disguise their criminal activity; to utilizing their vast networks, in an attempt to avoid detection. Traffickers rely on a network of clandestine routes to sell their commodities with impunity. As law enforcement agencies seek to retard the expansion of transnational criminal organization’s entry into human trafficking, it is imperative that they develop reliable trafficking mapping of known exploitative routes. In a recent report given to the Mexican Congress, The Procuraduría General de la República (PGR) disclosed, from 2008 to 2010 they had identified at least 47 unique criminal networking routes used to traffic victims and that Mexico’s estimated domestic victims number between 800,000 adults and 20,000 children annually. Designing a reliable mapping system is a crucial step to effective law enforcement response and deploying a successful victim support system. Creating this mapping analytic is exceedingly difficult. Traffickers are constantly changing the way they traffic and exploit their victims. They swiftly adapt to local environmental factors and react remarkably well to market demands, exploiting limitations in the prevailing laws. This article will highlight how human trafficking has become one of the fastest growing and most high profile human rights violations in the world today; compile current efforts to map and illustrate trafficking routes; and will demonstrate how the proprietary analytical mapping analysis of point-source and destination-source mapping can help local law enforcement, governmental agencies and victim services providers effectively respond to the type and nature of trafficking to their specific geographical locale. Trafficking transcends state and international borders. It demands an effective and consistent cooperation between local, state, and federal authorities. Each region of the world has different impact factors which create distinct challenges for law enforcement and victim services. Our mapping system lays the groundwork for a targeted anti-trafficking response.

Keywords: human trafficking, mapping, routes, law enforcement intelligence

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Authors: Catherine Bradshaw

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Educators often report difficulty managing behavior problems and other mental health concerns that students display at school. These concerns also interfere with the learning process and can create distraction for teachers and other students. As such, schools play an important role in both preventing and intervening with students who experience these types of challenges. A number of models have been proposed to serve as a framework for delivering prevention and early intervention services in schools. One such model is called Positive Behavioral Interventions and Supports (PBIS), which has been scaled-up to over 26,000 schools in the U.S. and many other countries worldwide. PBIS aims to improve a range of student outcomes through early detection of and intervention related to behavioral and mental health symptoms. PBIS blends and applies social learning, behavioral, and organizational theories to prevent disruptive behavior and enhance the school’s organizational health. PBIS focuses on creating and sustaining tier 1 (universal), tier 2 (selective), and tier 3 (individual) systems of support. Most schools using PBIS have focused on the core elements of the tier 1 supports, which includes the following critical features. The formation of a PBIS team within the school to lead implementation. Identification and training of a behavioral support ‘coach’, who serves as a on-site technical assistance provider. Many of the individuals identified to serve as a PBIS coach are also trained as a school psychologist or guidance counselor; coaches typically have prior PBIS experience and are trained to conduct functional behavioral assessments. The PBIS team also identifies a set of three to five positive behavioral expectations that are implemented for all students and by all staff school-wide (e.g., ‘be respectful, responsible, and ready to learn’); these expectations are posted in all settings across the school, including in the classroom, cafeteria, playground etc. All school staff define and teach the school-wide behavioral expectations to all students and review them regularly. Finally, PBIS schools develop or adopt a school-wide system to reward or reinforce students who demonstrate those 3-5 positive behavioral expectations. Staff and administrators create an agreed upon system for responding to behavioral violations that include definitions about what constitutes a classroom-managed vs. an office-managed discipline problem. Finally, a formal system is developed to collect, analyze, and use disciplinary data (e.g., office discipline referrals) to inform decision-making. This presentation provides a brief overview of PBIS and reports findings from a series of four U.S. based longitudinal randomized controlled trials (RCTs) documenting the impacts of PBIS on school climate, discipline problems, bullying, and academic achievement. The four RCTs include 80 elementary, 40 middle, and 58 high schools and results indicate a broad range of impacts on multiple student and school-wide outcomes. The session will highlight lessons learned regarding PBIS implementation and scale-up. We also review the ways in which PBIS can help educators and school leaders engage in data-based decision-making and share data with other decision-makers and stakeholders (e.g., students, parents, community members), with the overarching goal of increasing use of evidence-based programs in schools.

Keywords: positive behavioral interventions and supports, mental health, randomized trials, school-based prevention

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Authors: Danielle Slomberg, Jerome Labille, Riccardo Catalano, Jean-Claude Hubaud, Alexandra Lopes, Alice Tagliati, Teresa Fernandes

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In the assessment and management of cosmetics and personal care products, sunscreens are of emerging concern regarding both human and environmental health. Organic UV blockers in many sunscreens have been evidenced to undergo rapid photodegradation, induce dermal allergic reactions due to skin penetration, and to cause adverse effects on marine systems. While mineral UV-blockers may offer a safer alternative, their fate and impact and resulting regulation are still under consideration, largely related to the potential influence of nanotechnology-based products on both consumers and the environment. Nanometric titanium dioxide (TiO₂) UV-blockers have many advantages in terms of sun protection and asthetics (i.e., transparency). These UV-blockers typically consist of rutile nanoparticles coated with a primary mineral layer (silica or alumina) aimed at blocking the nanomaterial photoactivity and can include a secondary organic coating (e.g., stearic acid, methicone) aimed at favouring dispersion of the nanomaterial in the sunscreen formulation. The nanomaterials contained in the sunscreen can leave the skin either through a bathing of everyday usage, with subsequent release into rivers, lakes, seashores, and/or sewage treatment plants. The nanomaterial behaviour, fate and impact in these different systems is largely determined by its surface properties, (e.g. the nanomaterial coating type) and lifetime. The present work aims to develop the eco-design of sunscreens through the minimisation of risks associated with nanomaterials incorporated into the formulation. All stages of the sunscreen’s life cycle must be considered in this aspect, from its manufacture to its end-of-life, through its use by the consumer to its impact on the exposed environment. Reducing the potential release and/or toxicity of the nanomaterial from the sunscreen is a decisive criterion for its eco-design. TiO₂ UV-blockers of varied size and surface coating (e.g., stearic acid and silica) have been selected for this study. Hydrophobic TiO₂ UV-blockers (i.e., stearic acid-coated) were incorporated into a typical water-in-oil (w/o) formulation while hydrophilic, silica-coated TiO₂ UV-blockers were dispersed into an oil-in-water (o/w) formulation. The resulting sunscreens were characterised in terms of nanomaterial localisation, sun protection factor, and photo-passivation. The risk to the direct aquatic environment was assessed by evaluating the release of nanomaterials from the sunscreen through a simulated laboratory aging procedure. The size distribution, surface charge, and degradation state of the nano-composite by-products, as well as their nanomaterial concentration and colloidal behaviour were determined in a variety of aqueous environments (e.g., seawater and freshwater). Release of the hydrophobic nanocomposites into the aqueous environment was driven by oil droplet formation while hydrophilic nano-composites were readily dispersed. Ecotoxicity of the sunscreen by-products (from both w/o and o/w formulations) and their risk to marine organisms were assessed using coral symbiotes and tropical corals, evaluating both lethal and sublethal toxicities. The data dissemination and provided risk knowledge from the present work will help guide regulation related to nanomaterials in sunscreen, provide better information for consumers, and allow for easier decision-making for manufacturers.

Keywords: alteration, environmental fate, sunscreens, titanium dioxide nanoparticles

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Authors: Teodora Vukovic, Christoph Hottiger, Noah Bubenhofer

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The development of VIAN-DH aims at bridging two linguistic approaches: conversation analysis/interactional linguistics (IL), so far a dominantly qualitative field, and computational/corpus linguistics and its quantitative and automated methods. Contemporary IL investigates the systematic organization of conversations and interactions composed of speech, gaze, gestures, and body positioning, among others. These highly integrated multimodal behaviour is analysed based on video data aimed at uncovering so called “multimodal gestalts”, patterns of linguistic and embodied conduct that reoccur in specific sequential positions employed for specific purposes. Multimodal analyses (and other disciplines using videos) are so far dependent on time and resource intensive processes of manual transcription of each component from video materials. Automating these tasks requires advanced programming skills, which is often not in the scope of IL. Moreover, the use of different tools makes the integration and analysis of different formats challenging. Consequently, IL research often deals with relatively small samples of annotated data which are suitable for qualitative analysis but not enough for making generalized empirical claims derived quantitatively. VIAN-DH aims to create a workspace where many annotation layers required for the multimodal analysis of videos can be created, processed, and correlated in one platform. VIAN-DH will provide a graphical interface that operates state-of-the-art tools for automating parts of the data processing. The integration of tools that already exist in computational linguistics and computer vision, facilitates data processing for researchers lacking programming skills, speeds up the overall research process, and enables the processing of large amounts of data. The main features to be introduced are automatic speech recognition for the transcription of language, automatic image recognition for extraction of gestures and other visual cues, as well as grammatical annotation for adding morphological and syntactic information to the verbal content. In the ongoing instance of VIAN-DH, we focus on gesture extraction (pointing gestures, in particular), making use of existing models created for sign language and adapting them for this specific purpose. In order to view and search the data, VIAN-DH will provide a unified format and enable the import of the main existing formats of annotated video data and the export to other formats used in the field, while integrating different data source formats in a way that they can be combined in research. VIAN-DH will adapt querying methods from corpus linguistics to enable parallel search of many annotation levels, combining token-level and chronological search for various types of data. VIAN-DH strives to bring crucial and potentially revolutionary innovation to the field of IL, (that can also extend to other fields using video materials). It will allow the processing of large amounts of data automatically and, the implementation of quantitative analyses, combining it with the qualitative approach. It will facilitate the investigation of correlations between linguistic patterns (lexical or grammatical) with conversational aspects (turn-taking or gestures). Users will be able to automatically transcribe and annotate visual, spoken and grammatical information from videos, and to correlate those different levels and perform queries and analyses.

Keywords: multimodal analysis, corpus linguistics, computational linguistics, image recognition, speech recognition

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Authors: Annika J. Meyer, Tom Piechotta

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Unmanned Aerial Vehicles (UAVs) have increasingly become vital tools in various applications, including surveillance, search and rescue, and environmental monitoring. One common approach to ensure redundant communication systems when flying beyond visual line of sight is for UAVs to employ multiple mobile data modems by different providers. Although widely adopted, this approach suffers from several drawbacks, such as high costs, added weight and potential increases in signal interference. In light of these challenges, this paper proposes a communication framework intermeshing mobile networks and LoRa (Long Range) technology—a low-power, long-range communication protocol. LoRaWAN (Long Range Wide Area Network) is commonly used in Internet of Things applications, relying on stationary gateways and Internet connectivity. This paper, however, utilizes the underlying LoRa protocol, taking advantage of the protocol’s low power and long-range capabilities while ensuring efficiency and reliability. Conducted in collaboration with the Potsdam Fire Department, the implementation of mobile network technology in combination with the LoRa protocol in small UAVs (take-off weight < 0.4 kg), specifically designed for search and rescue and area monitoring missions, is explored. This research aims to test the viability of LoRa as an additional redundant communication system during UAV flights as well as its intermeshing with the primary, mobile network-based controller. The methodology focuses on direct UAV-to-UAV and UAV-to-ground communications, employing different spreading factors optimized for specific operational scenarios—short-range for UAV-to-UAV interactions and long-range for UAV-to-ground commands. This explored use case also dramatically reduces one of the major drawbacks of LoRa communication systems, as a line of sight between the modules is necessary for reliable data transfer. Something that UAVs are uniquely suited to provide, especially when deployed as a swarm. Additionally, swarm deployment may enable UAVs that have lost contact with their primary network to reestablish their connection through another, better-situated UAV. The experimental setup involves multiple phases of testing, starting with controlled environments to assess basic communication capabilities and gradually advancing to complex scenarios involving multiple UAVs. Such a staged approach allows for meticulous adjustment of parameters and optimization of the communication protocols to ensure reliability and effectiveness. Furthermore, due to the close partnership with the Fire Department, the real-world applicability of the communication system is assured. The expected outcomes of this paper include a detailed analysis of LoRa's performance as a communication tool for UAVs, focusing on aspects such as signal integrity, range, and reliability under different environmental conditions. Additionally, the paper seeks to demonstrate the cost-effectiveness and operational efficiency of using a single type of communication technology that reduces UAV payload and power consumption. By shifting from traditional cellular network communications to a more robust and versatile cellular and LoRa-based system, this research has the potential to significantly enhance UAV capabilities, especially in critical applications where reliability is paramount. The success of this paper could pave the way for broader adoption of LoRa in UAV communications, setting a new standard for UAV operational communication frameworks.

Keywords: LoRa communication protocol, mobile network communication, UAV communication systems, search and rescue operations

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Authors: Dhekra Khazri, Hakim Gabtni

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Because of Sidi Bouzid water table overexploitation, this study aims at integrating geophysical methods to determinate aquifers geometry assessing their geological situation and geophysical characteristics. However in highly tectonic zones controlled by Atlassic structural features with NE-SW major directions (central Tunisia), Bouguer gravimetric responses of some areas can be as much dominated by the regional structural tendency, as being non-identified or either defectively interpreted such as the case of Sidi Bouzid basin. This issue required a residual gravity anomaly elaboration isolating the Sidi Bouzid basin gravity response ranging between -8 and -14 mGal and crucial for its aquifers geometry characterization. Several gravity techniques helped constructing the Sidi Bouzid basin's residual gravity anomaly, such as Upwards continuation compared to polynomial regression trends and power spectrum analysis detecting deep basement sources at (3km), intermediate (2km) and shallow sources (1km). A 3D Euler Deconvolution was also performed detecting deepest accidents trending NE-SW, N-S and E-W with depth values reaching 5500 m and delineating the main outcropping structures of the study area. Further gravity treatments highlighted the subsurface geometry and structural features of Sidi Bouzid basin over Horizontal and vertical gradient, and also filters based on them such as Tilt angle and Source Edge detector locating rooted edges or peaks from potential field data detecting a new E-W lineament compartmentalizing the Sidi Bouzid gutter into two unequally residual anomaly and subsiding domains. This subsurface morphology is also detected by the used 2D seismic reflection sections defining the Sidi Bouzid basin as a deep gutter within a tectonic set of negative flower structures, and collapsed and tilted blocks. Furthermore, these structural features were confirmed by forward gravity modeling process over several modeled residual gravity profiles crossing the main area. Sidi Bouzid basin (central Tunisia) is also of a big interest cause of the unknown total thickness and the undefined substratum of its siliciclastic Tertiary package, and its aquifers unbounded structural subsurface features and deep accidents. The Combination of geological, hydrogeological and geophysical methods is then of an ultimate need. Therefore, a geophysical methods integration based on gravity survey supporting available seismic data through forward gravity modeling, enhanced lateral and vertical extent definition of the basin's complex sedimentary fill via 3D gravity models, improved depth estimation by a depth to basement modeling approach, and provided 3D isochronous seismic mapping visualization of the basin's Tertiary complex refining its geostructural schema. A subsurface basin geomorphology mapping, over an ultimate matching between the basin's residual gravity map and the calculated theoretical signature map, was also displayed over the modeled residual gravity profiles. An ultimate multidisciplinary geophysical study of the Sidi Bouzid basin aquifers can be accomplished via an aeromagnetic survey and a 4D Microgravity reservoir monitoring offering temporal tracking of the target aquifer's subsurface fluid dynamics enhancing and rationalizing future groundwater exploitation in this arid area of central Tunisia.

Keywords: aquifer geometry, geophysics, 3D gravity modeling, improved depths, source edge detector

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Authors: Juan Pablo Botero Torres, Alba Avila, Luis Felipe Giraldo

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Independent navigation and mobility through unknown spaces pose a challenge for the autonomy of visually impaired people (VIP), who have relied on the use of traditional assistive tools like the white cane and trained dogs. However, emerging visually assistive technologies (VAT) have proposed several human-machine interfaces (HMIs) that could improve VIP’s ability for self-guidance. Hereby, we introduce the design and implementation of a visually assistive device, Anajaa – Visual Substitution System (AVSS). This system integrates ultrasonic sensors with custom electronics, and computer vision models (convolutional neural networks), in order to achieve a robust system that acquires information of the surrounding space and transmits it to the user in an intuitive and efficient manner. AVSS consists of two modules: the sensing and the actuation module, which are fitted to a chest mount and belt that communicate via Bluetooth. The sensing module was designed for the acquisition and processing of proximity signals provided by an array of ultrasonic sensors. The distribution of these within the chest mount allows an accurate representation of the surrounding space, discretized in three different levels of proximity, ranging from 0 to 6 meters. Additionally, this module is fitted with an RGB-D camera used to detect potentially threatening obstacles, like staircases, using a convolutional neural network specifically trained for this purpose. Posteriorly, the depth data is used to estimate the distance between the stairs and the user. The information gathered from this module is then sent to the actuation module that creates an HMI, by the means of a 3x2 array of vibration motors that make up the tactile display and allow the system to deliver haptic feedback. The actuation module uses vibrational messages (tactones); changing both in amplitude and frequency to deliver different awareness levels according to the proximity of the obstacle. This enables the system to deliver an intuitive interface. Both modules were tested under lab conditions, and the HMI was additionally tested with a focal group of VIP. The lab testing was conducted in order to establish the processing speed of the computer vision algorithms. This experimentation determined that the model can process 0.59 frames per second (FPS); this is considered as an adequate processing speed taking into account that the walking speed of VIP is 1.439 m/s. In order to test the HMI, we conducted a focal group composed of two females and two males between the ages of 35-65 years. The subject selection was aided by the Colombian Cooperative of Work and Services for the Sightless (COOTRASIN). We analyzed the learning process of the haptic messages throughout five experimentation sessions using two metrics: message discrimination and localization success. These correspond to the ability of the subjects to recognize different tactones and locate them within the tactile display. Both were calculated as the mean across all subjects. Results show that the focal group achieved message discrimination of 70% and a localization success of 80%, demonstrating how the proposed HMI leads to the appropriation and understanding of the feedback messages, enabling the user’s awareness of its surrounding space.

Keywords: computer vision on embedded systems, electronic trave aids, human-machine interface, haptic feedback, visual assistive technologies, vision substitution systems

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Authors: D. Malouch, M. Berchel, C. Dreanno, S. Stachowski-Haberkorn, P-A. Jaffres

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Biofilm is a predominant lifestyle chosen by bacteria. Whether it is developed on an immerged surface or a mobile biofilm known as flocs, the bacteria within this form of life show properties different from its planktonic ones. Within the biofilm, the self-formed matrix of Extracellular Polymeric Substances (EPS) offers hydration, resources capture, enhanced resistance to antimicrobial agents, and allows cell-communication. Biofouling is a complex natural phenomenon that involves biological, physical and chemical properties related to the environment, the submerged surface and the living organisms involved. Bio-colonization of artificial structures can cause various economic and environmental impacts. The increase in costs associated with the over-consumption of fuel from biocolonized vessels has been widely studied. Measurement drifts from submerged sensors, as well as obstructions in heat exchangers, and deterioration of offshore structures are major difficulties that industries are dealing with. Therefore, surfaces that inhibit biocolonization are required in different areas (water treatment, marine paints, etc.) and many efforts have been devoted to produce efficient and eco-compatible antifouling agents. The different steps of surface fouling are widely described in literature. Studying the biofilm and its stages provides a better understanding of how to elaborate more efficient antifouling strategies. Several approaches are currently applied, such as the use of biocide anti-fouling paint6 (mainly with copper derivatives) and super-hydrophobic coatings. While these two processes are proving to be the most effective, they are not entirely satisfactory, especially in a context of a changing legislation. Nowadays, the challenge is to prevent biofouling with non-biocide compounds, offering a cost effective solution, but with no toxic effects on marine organisms. Since the micro-fouling phase plays an important role in the regulation of the following steps of biofilm formation7, it is desired to reduce or delate biofouling of a given surface by inhibiting the micro fouling at its early stages. In our recent works, we reported that some amphiphilic compounds exhibited bacteriostatic or bactericidal properties at a concentration that did not affect eukaryotic cells. These remarkable properties invited us to assess this type of bio-inspired phospholipids9 to prevent the colonization of surfaces by marine bacteria. Of note, other studies reported that amphiphilic compounds interacted with bacteria leading to a reduction of their development. An amphiphilic compound is a molecule consisting of a hydrophobic domain and a polar head (ionic or non-ionic). These compounds appear to have interesting antifouling properties: some ionic compounds have shown antimicrobial activity, and zwitterions can reduce nonspecific adsorption of proteins. Herein, we investigate the potential of amphiphilic compounds as inhibitors of bacterial growth and marine biofilm formation. The aim of this study is to compare the efficacy of four synthetic phospholipids that features a cationic charge (BSV36, KLN47) or a zwitterionic polar-head group (SL386, MB2871) to prevent microfouling with marine bacteria. We also study the toxicity of these compounds in order to identify the most promising compound that must feature high anti-adhesive properties and a low cytotoxicity on two links representative of coastal marine food webs: phytoplankton and oyster larvae.

Keywords: amphiphilic phospholipids, bacterial biofilm, marine microfouling, non-toxic antifouling

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Authors: Andreas Rudisch, Ralf Lampert, Andreas Kolbitsch

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It is a well-known fact among the engineering community that earthquakes with comparatively low magnitudes can cause serious damage to nonstructural components (NSCs) of buildings, even when the supporting structure performs relatively well. Past research works focused mainly on NSCs of nuclear power plants and industrial plants. Particular attention should also be given to architectural façade elements of old masonry buildings (e.g. ornamental figures, balustrades, vases), which are very vulnerable under seismic excitation. Large numbers of these historical nonstructural components (HiNSCs) can be found in highly frequented historical city centers and in the event of failure, they pose a significant danger to persons. In order to estimate the vulnerability of acceleration sensitive HiNSCs, the peak horizontal floor acceleration (PHFA) is used. The PHFA depends on the dynamic characteristics of the building, the ground excitation, and induced nonlinearities. Consequently, the PHFA can not be generalized as a simple function of height. In the present research work, an extensive case study was conducted to investigate the influence of induced nonlinearity on the PHFA for old masonry buildings. Probabilistic nonlinear FE time-history analyses considering three different hazard levels were performed. A set of eighteen synthetically generated ground motions was used as input to the structure models. An elastoplastic macro-model (multiPlas) for nonlinear homogenized continuum FE-calculation was calibrated to multiple scales and applied, taking specific failure mechanisms of masonry into account. The macro-model was calibrated according to the results of specific laboratory and cyclic in situ shear tests. The nonlinear macro-model is based on the concept of multi-surface rate-independent plasticity. Material damage or crack formation are detected by reducing the initial strength after failure due to shear or tensile stress. As a result, shear forces can only be transmitted to a limited extent by friction when the cracking begins. The tensile strength is reduced to zero. The first goal of the calibration was the consistency of the load-displacement curves between experiment and simulation. The calibrated macro-model matches well with regard to the initial stiffness and the maximum horizontal load. Another goal was the correct reproduction of the observed crack image and the plastic strain activities. Again the macro-model proved to work well in this case and shows very good correlation. The results of the case study show that there is significant scatter in the absolute distribution of the PHFA between the applied ground excitations. An absolute distribution along the normalized building height was determined in the framework of probability theory. It can be observed that the extent of nonlinear behavior varies for the three hazard levels. Due to the detailed scope of the present research work, a robust comparison with code-recommendations and simplified PHFA distributions are possible. The chosen methodology offers a chance to determine the distribution of PHFA along the building height of old masonry structures. This permits a proper hazard assessment of HiNSCs under seismic loads.

Keywords: nonlinear macro-model, nonstructural components, time-history analysis, unreinforced masonry

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Authors: Majdah Alnefaie

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The ‘netnographic study’ and data mining have been used to monitor the public interaction on Social Media Sites (SMSs) to understand what the motivational factors influence the Saudi intentions regarding allowing women driving in Saudi Arabia in 2018. The netnographic study monitored the publics’ textual and visual communications in Twitter, Snapchat, and YouTube. SMSs users’ communications method is also known as electronic word of mouth (eWOM). Netnography methodology is still in its initial stages as it depends on manual extraction, reading and classification of SMSs users text. On the other hand, data mining is come from the computer and physical sciences background, therefore it is much harder to extract meaning from unstructured qualitative data. In addition, the new development in data mining software does not support the Arabic text, especially local slang in Saudi Arabia. Therefore, collaborations between social and computer scientists such as ‘netnographic study’ and data mining will enhance the efficiency of this study methodology leading to comprehensive research outcome. The eWOM communications between individuals on SMSs can promote a sense that sharing their preferences and experiences regarding politics and social government regulations is a part of their daily life, highlighting the importance of using SMSs as assistance in promoting participation in political and social. Therefore, public interactions on SMSs are important tools to comprehend people’s intentions regarding the new government regulations in the country. This study aims to answer this question, "What factors influence the Saudi Arabians' intentions of Saudi female's car-driving in 2018". The study utilized qualitative method known as netnographic study. The study used R studio to collect and analyses 27000 Saudi users’ comments from 25th May until 25th June 2018. The study has developed data collection model that support importing and analysing the Arabic text in the local slang. The data collection model in this study has been clustered based on different type of social networks, gender and the study main factors. The social network analysis was employed to collect comments from SMSs owned by governments’ originations, celebrities, vloggers, social activist and news SMSs accounts. The comments were collected from both males and females SMSs users. The sentiment analysis shows that the total number of positive comments Saudi females car driving was higher than negative comments. The data have provided the most important factors influenced the Saudi Arabians’ intention of Saudi females car driving including, culture and environment, freedom of choice, equal opportunities, security and safety. The most interesting finding indicted that women driving would play a role in increasing the individual freedom of choice. Saudi female will be able to drive cars to fulfill her daily life and family needs without being stressed due to the lack of transportation. The study outcome will help Saudi government to improve woman quality of life by increasing the ability to find more jobs and studies, increasing income through decreasing the spending on transport means such as taxi and having more freedom of choice in woman daily life needs. The study enhances the importance of using use marketing research to measure the public opinions on the new government regulations in the country. The study has explained the limitations and suggestions for future research.

Keywords: netnographic study, data mining, social media, Saudi Arabia, female driving

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Authors: Stefano Scippo, Damiana Luzzi, Stefano Cuomo, Maria Ranieri

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Background: In response to the rise in natural disasters linked to climate change, numerous studies on Disaster Risk Reduction Education (DRRE) have emerged since the '90s, mainly using a didactic transmission-based approach. Effective DRRE should align with an interactive, experiential, and participatory educational model, which can be costly and risky. A potential solution is using simulations facilitated by eXtended Reality (XR). Research Question: This study aims to conduct a scoping review to explore educational methodologies that use XR to enhance knowledge among teachers, students, and citizens about environmental risks, natural disasters (including climate-related ones), and their management. Method: A search string of 66 keywords was formulated, spanning three domains: 1) education and target audience, 2) environment and natural hazards, and 3) technologies. On June 21st, 2023, the search string was used across five databases: EBSCOhost, IEEE Xplore, PubMed, Scopus, and Web of Science. After deduplication and removing papers without abstracts, 2,152 abstracts (published between 2013 and 2023) were analyzed and 2,062 papers were excluded, followed by the exclusion of 56 papers after full-text scrutiny. Excluded studies focused on unrelated technologies, non-environmental risks, and lacked educational outcomes or accessible texts. Main Results: The 34 reviewed papers were analyzed for context, risk type, research methodology, learning objectives, XR technology use, outcomes, and educational affordances of XR. Notably, since 2016, there has been a rise in scientific publications, focusing mainly on seismic events (12 studies) and floods (9), with a significant contribution from Asia (18 publications), particularly Japan (7 studies). Methodologically, the studies were categorized into empirical (26) and non-empirical (8). Empirical studies involved user or expert validation of XR tools, while non-empirical studies included systematic reviews and theoretical proposals without experimental validation. Empirical studies were further classified into quantitative, qualitative, or mixed-method approaches. Six qualitative studies involved small groups of users or experts, while 20 quantitative or mixed-method studies used seven different research designs, with most (17) employing a quasi-experimental, one-group post-test design, focusing on XR technology usability over educational effectiveness. Non-experimental studies had methodological limitations, making their results hypothetical and in need of further empirical validation. Educationally, the learning objectives centered on knowledge and skills for surviving natural disaster emergencies. All studies recommended XR technologies for simulations or serious games but did not develop comprehensive educational frameworks around these tools. XR-based tools showed potential superiority over traditional methods in teaching risk and emergency management skills. However, conclusions were more valid in studies with experimental designs; otherwise, they remained hypothetical without empirical evidence. The educational affordances of XR, mainly user engagement, were confirmed by the studies. Authors’ Conclusions: The analyzed literature lacks specific educational frameworks for XR in DRRE, focusing mainly on survival knowledge and skills. There is a need to expand educational approaches to include uncertainty education, developing competencies that encompass knowledge, skills, and attitudes like risk perception.

Keywords: disaster risk reduction education, educational technologies, scoping review, XR technologies

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Authors: Dmitriy Berillo, Areej K. A. Al-Jwaid, Jonathan L. Caplin, Andrew Cundy, Irina Savina

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Chlorophenols (CPs) are used as a precursor in the production of higher CPs and dyestuffs, and as a preservative. Contamination by CPs of the ground water is located in the range from 0.15-100mg/L. The EU has set maximum concentration limits for pesticides and their degradation products of 0.1μg/L and 0.5μg/L, respectively. People working in industries which produce textiles, leather products, domestic preservatives, and petrochemicals are most heavily exposed to CPs. The International Agency for Research on Cancers categorized CPs as potential human carcinogens. Existing multistep water purification processes for CPs such as hydrogenation, ion exchange, liquid-liquid extraction, adsorption by activated carbon, forward and inverse osmosis, electrolysis, sonochemistry, UV irradiation, and chemical oxidation are not always cost effective and can cause the formation of even more toxic or mutagenic derivatives. Bioremediation of CPs derivatives utilizing microorganisms results in 60 to 100% decontamination efficiency and the process is more environmentally-friendly compared with existing physico-chemical methods. Microorganisms immobilized onto a substrate show many advantages over free bacteria systems, such as higher biomass density, higher metabolic activity, and resistance to toxic chemicals. They also enable continuous operation, avoiding the requirement for biomass-liquid separation. The immobilized bacteria can be reused several times, which opens the opportunity for developing cost-effective processes for wastewater treatment. In this study, we develop a bioremediation system for CPs based on macroporous materials, which can be efficiently used for wastewater treatment. Conditions for the preparation of the macroporous material from specific bacterial strains (Pseudomonas mendocina and Rhodococus koreensis) were optimized. The concentration of bacterial cells was kept constant; the difference was only the type of cross-linking agents used e.g. glutaraldehyde, novel polymers, which were utilized at concentrations of 0.5 to 1.5%. SEM images and rheology analysis of the material indicated a monolithic macroporous structure. Phenol was chosen as a model system to optimize the function of the cryogel material and to estimate its enzymatic activity, since it is relatively less toxic and harmful compared to CPs. Several types of macroporous systems comprising live bacteria were prepared. The viability of the cross-linked bacteria was checked using Live/Dead BacLight kit and Laser Scanning Confocal Microscopy, which revealed the presence of viable bacteria with the novel cross-linkers, whereas the control material cross-linked with glutaraldehyde(GA), contained mostly dead cells. The bioreactors based on bacteria were used for phenol degradation in batch mode at an initial concentration of 50mg/L, pH 7.5 and a temperature of 30°C. Bacterial strains cross-linked with GA showed insignificant ability to degrade phenol and for one week only, but a combination of cross-linking agents illustrated higher stability, viability and the possibility to be reused for at least five weeks. Furthermore, conditions for CPs degradation will be optimized, and the chlorophenol degradation rates will be compared to those for phenol. This is a cutting-edge bioremediation approach, which allows the purification of waste water from sustainable compounds without a separation step to remove free planktonic bacteria. Acknowledgments: Dr. Berillo D. A. is very grateful to Individual Fellowship Marie Curie Program for funding of the research.

Keywords: bioremediation, cross-linking agents, cross-linked microbial cell, chlorophenol degradation

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Authors: Katarzyna Lubecka, Kirsty Flower, Megan Beetch, Lucinda Kurzava, Hannah Buvala, Samer Gawrieh, Suthat Liangpunsakul, Tracy Gonzalez, George McCabe, Naga Chalasani, James M. Flanagan, Barbara Stefanska

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Hepatocellular carcinoma (HCC), the most prevalent type of primary liver cancer, is the second leading cause of cancer death worldwide. Late onset of clinical symptoms in HCC results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable early detection biomarkers that can distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed and could increase the cure rate from 5% to 80%. We used Illumina-450K microarray to test whether blood DNA, an easily accessible source of DNA, bear site-specific changes in DNA methylation in response to HCC before diagnosis with conventional tools (pre-diagnostic). Top 11 differentially methylated sites were selected for validation by pyrosequencing. The diagnostic potential of the 11 pyrosequenced probes was tested in blood samples from a prospective cohort of cirrhotic patients. We identified 971 differentially methylated CpG sites in pre-diagnostic HCC cases as compared with healthy controls (P < 0.05, paired Wilcoxon test, ICC ≥ 0.5). Nearly 76% of differentially methylated CpG sites showed lower levels of methylation in cases vs. controls (P = 2.973E-11, Wilcoxon test). Classification of the CpG sites according to their location relative to CpG islands and transcription start site revealed that those hypomethylated loci are located in regulatory regions important for gene transcription such as CpG island shores, promoters, and 5’UTR at higher frequency than hypermethylated sites. Among 735 CpG sites hypomethylated in cases vs. controls, 482 sites were assigned to gene coding regions whereas 236 hypermethylated sites corresponded to 160 genes. Bioinformatics analysis using GO, KEGG and DAVID knowledgebase indicate that differentially methylated CpG sites are located in genes associated with functions that are essential for gene transcription, cell adhesion, cell migration, and regulation of signal transduction pathways. Taking into account the magnitude of the difference, statistical significance, location, and consistency across the majority of matched pairs case-control, we selected 11 CpG loci corresponding to 10 genes for further validation by pyrosequencing. We established that methylation of CpG sites within 5 out of those 10 genes distinguish cirrhotic patients who subsequently developed HCC from those who stayed cancer free (cirrhotic controls), demonstrating potential as biomarkers of early detection in populations at risk. The best predictive value was detected for CpGs located within BARD1 (AUC=0.70, asymptotic significance ˂0.01). Using an additive logistic regression model, we further showed that 9 CpG loci within those 5 genes, that were covered in pyrosequenced probes, constitute a panel with high diagnostic accuracy (AUC=0.887; 95% CI:0.80-0.98). The panel was able to distinguish pre-diagnostic cases from cirrhotic controls free of cancer with 88% sensitivity at 70% specificity. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established biomarker panel has high potential to be developed into a routine clinical test after validation in larger cohorts. This study was supported by Showalter Trust, American Cancer Society (IRG#14-190-56), and Purdue Center for Cancer Research (P30 CA023168) granted to BS.

Keywords: biomarker, DNA methylation, early detection, hepatocellular carcinoma

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Authors: C. Bel, J. Nevado, F. Ciceri, M. Ropacki, T. Hoffmann, P. Lapunzina, C. Buesa

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Background: The Phelan-McDermid syndrome (PMS) is a genetic disorder caused by the deletion of the terminal region of chromosome 22 or mutation of the SHANK3 gene. Shank3 disruption in mice leads to dysfunction of synaptic transmission, which can be restored by epigenetic regulation with both Lysine Specific Demethylase 1 (LSD1) inhibitors. PMS subjects result in a variable degree of intellectual disability, delay or absence of speech, autistic spectrum disorders symptoms, low muscle tone, motor delays and epilepsy. Vafidemstat is an LSD1 inhibitor in Phase II clinical development with a well-established and favorable safety profile, and data supporting the restoration of memory and cognition defects as well as reduction of agitation and aggression in several animal models and clinical studies. Therefore, vafidemstat has the potential to become a first-in-class precision medicine approach to treat PMS patients. Aims: The goal of this research is to perform an observational trial to psychometrically characterize individuals carrying deletions in SHANK3 and build a foundation for subsequent precision psychiatry clinical trials with vafidemstat. Methodology: This study is characterizing the clinical profile of 20 to 40 subjects, > 16-year-old, with genotypically confirmed PMS diagnosis. Subjects will complete a battery of neuropsychological scales, including the Repetitive Behavior Questionnaire (RBQ), Vineland Adaptive Behavior Scales, Escala de Observación para el Diagnostico del Autismo (Autism Diagnostic Observational Scale) (ADOS)-2, the Battelle Developmental Inventory and the Behavior Problems Inventory (BPI). Results: By March 2021, 19 patients have been enrolled. Unsupervised hierarchical clustering of the results obtained so far identifies 3 groups of patients, characterized by different profiles of cognitive and behavioral scores. The first cluster is characterized by low Battelle age, high ADOS and low Vineland, RBQ and BPI scores. Low Vineland, RBQ and BPI scores are also detected in the second cluster, which in contrast has high Battelle age and low ADOS scores. The third cluster is somewhat in the middle for the Battelle, Vineland and ADOS scores while displaying the highest levels of aggression (high BPI) and repeated behaviors (high RBQ). In line with the observation that female patients are generally affected by milder forms of autistic symptoms, no male patients are present in the second cluster. Dividing the results by gender highlights that male patients in the third cluster are characterized by a higher frequency of aggression, whereas female patients from the same cluster display a tendency toward higher repetitive behavior. Finally, statistically significant differences in deletion sizes are detected comparing the three clusters (also after correcting for gender), and deletion size appears to be positively correlated with ADOS and negatively correlated with Vineland A and C scores. No correlation is detected between deletion size and the BPI and RBQ scores. Conclusions: Precision medicine may open a new way to understand and treat Central Nervous System disorders. Epigenetic dysregulation has been proposed to be an important mechanism in the pathogenesis of schizophrenia and autism. Vafidemstat holds exciting therapeutic potential in PMS, and this study will provide data regarding the optimal endpoints for a future clinical study to explore vafidemstat ability to treat shank3-associated psychiatric disorders.

Keywords: autism, epigenetics, LSD1, personalized medicine

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Authors: Ching-Sung Lee, Wei-Chou Hsu, Han-Yin Liu, Hung-Hsi Huang, Si-Fu Chen, Yun-Jung Yang, Bo-Chun Chiang, Yu-Chuang Chen, Shen-Tin Yang

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AlGaN/GaN high electron mobility transistors (HEMTs) have been intensively studied due to their intrinsic advantages of high breakdown electric field, high electron saturation velocity, and excellent chemical stability. They are also suitable for ultra-violet (UV) photodetection due to the corresponding wavelengths of GaN bandgap. To improve the optical responsivity by decreasing the dark current due to gate leakage problems and limited Schottky barrier heights in GaN-based HEMT devices, various metal-oxide-semiconductor HEMTs (MOS-HEMTs) have been devised by using atomic layer deposition (ALD), molecular beam epitaxy (MBE), metal-organic chemical vapor deposition (MOCVD), liquid phase deposition (LPD), and RF sputtering. The gate dielectrics include MgO, HfO2, Al2O3, La2O3, and TiO2. In order to provide complementary circuit operation, enhancement-mode (E-mode) devices have been lately studied using techniques of fluorine treatment, p-type capper, piezoneutralization layer, and MOS-gate structure. This work reports an Al2O3-dielectric Al0.25Ga0.75N/GaN E-mode MOS-HEMT design by using a cost-effective ozone water oxidization technique. The present ozone oxidization method advantages of low cost processing facility, processing simplicity, compatibility to device fabrication, and room-temperature operation under atmospheric pressure. It can further reduce the gate-to-channel distance and improve the transocnductance (gm) gain for a specific oxide thickness, since the formation of the Al2O3 will consume part of the AlGaN barrier at the same time. The epitaxial structure of the studied devices was grown by using the MOCVD technique. On a Si substrate, the layer structures include a 3.9 m C-doped GaN buffer, a 300 nm GaN channel layer, and a 5 nm Al0.25Ga0.75N barrier layer. Mesa etching was performed to provide electrical isolation by using an inductively coupled-plasma reactive ion etcher (ICP-RIE). Ti/Al/Au were thermally evaporated and annealed to form the source and drain ohmic contacts. The device was immersed into the H2O2 solution pumped with ozone gas generated by using an OW-K2 ozone generator. Ni/Au were deposited as the gate electrode to complete device fabrication of MOS-HEMT. The formed Al2O3 oxide thickness 7 nm and the remained AlGaN barrier thickness is 2 nm. A reference HEMT device has also been fabricated in comparison on the same epitaxial structure. The gate dimensions are 1.2 × 100 µm 2 with a source-to-drain spacing of 5 μm for both devices. The dielectric constant (k) of Al2O3 was characterized to be 9.2 by using C-V measurement. Reduced interface state density after oxidization has been verified by the low-frequency noise spectra, Hooge coefficients, and pulse I-V measurement. Improved device characteristics at temperatures of 300 K-450 K have been achieved for the present MOS-HEMT design. Consequently, Al2O3-dielectric Al0.25Ga0.75N/GaN E-mode MOS-HEMTs by using the ozone water oxidization method are reported. In comparison with a conventional Schottky-gate HEMT, the MOS-HEMT design has demonstrated excellent enhancements of 138% (176%) in gm, max, 118% (139%) in IDS, max, 53% (62%) in BVGD, 3 (2)-order reduction in IG leakage at VGD = -60 V at 300 (450) K. This work is promising for millimeter-wave integrated circuit (MMIC) and three-terminal active UV photodetector applications.

Keywords: MOS-HEMT, enhancement mode, AlGaN/GaN, passivation, ozone water oxidation, gate leakage

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Authors: Sebastião Milton Pinheiro da Silva, Michele Barbosa da Rocha, Ana Lúcia Fernandes Campos, Miquéias Rildo de Souza Silva

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Water is an essential natural resource for life on Earth. Rivers, lakes, lagoons and dams are the main sources of water storage for human consumption. The costs of extracting and using these water sources are lower than those of exploiting groundwater on transition zones to semi-arid terrains. However, the volume of surface water has decreased over time, with the depletion of first-order drainage and the disappearance of springs, phenomena which are easily observed in the field. Climate change worsens water scarcity, compromising supply and hydric security for rural populations. To minimize the expected impacts, producing and storing water through watershed management planning requires detailed cartographic information on the relief and topography, and updated data on the stage and intensity of catchment basin environmental degradation problems. The cartography available of the Brazilian northeastern territory dates to the 70s, with topographic maps, printed, at a scale of 1:100,000 which does not meet the requirements to execute this project. Exceptionally, there are topographic maps at scales of 1:50,000 and 1:25,000 of some coastal regions in northeastern Brazil. Still, due to scale limitations and outdatedness, they are products of little utility for mapping low-order watersheds drainage and springs. Remote sensing data and geographic information systems can contribute to guiding the process of mapping and environmental recovery by integrating detailed relief and topographic data besides social and other environmental information in the Guajiru River Basin, located on the east coast of Rio Grande do Norte, on the Northeast region of Brazil. This study aimed to recognize and map catchment basin, springs and low-order drainage features along estimating morphometric parameters. Alos PALSAR and Copernicus DEM digital elevation models were evaluated and provided regional drainage features and the watersheds limits extracted with Terraview/Terrahidro 5.0 software. CBERS 4A satellite images with 2 m spatial resolution, processed with ESA SNAP Toolbox, allowed generating land use land cover map of Guajiru River. A Mappir Survey 3 multiespectral camera onboard of a DJI Phantom 4, a Mavic 2 Pro PPK Drone and an X91 GNSS receiver to collect the precised position of selected points were employed to detail mapping. Satellite images enabled a first knowledge approach of watershed areas on a more regional scale, yet very current, and drone images were essential in mapping details of catchment basins. The drone multispectral image mosaics, the digital elevation model, the contour lines and geomorphometric parameters were generated using OpenDroneMap/ODM and QGis softwares. The drone images generated facilitated the location, understanding and mapping of watersheds, recharge areas and first-order ephemeral watercourses on an adequate scale and will be used in the following project’s phases: watershed management planning, recovery and environmental protection of Rio's springs Guajiru. Environmental degradation is being analyzed from the perspective of the availability and quality of surface water supply.

Keywords: imaging, relief, UAV, water

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Authors: Marija Mihajlovic Pereira

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Teaching and learning a musical instrument is challenging for both teachers and students. Teachers generally use diverse strategies to resolve students' particular issues in a one-to-one context. Considering individual sessions as a supportive educational context, the teacher can play a decisive role in stimulating and promoting self-regulated learning strategies, especially with beginning learners. The teachers who promote self-controlling behaviors, strategic monitoring, and regulation of actions toward goals could expect their students to practice more qualitatively and consciously. When encouraged to adopt self-regulation habits, students' could benefit from greater productivity on a longer path. Founded on Bary Zimmerman's cyclical model that comprehends three phases - forethought, performance, and self-reflection, this work aims to articulate self-regulated and music learning. Self-regulated learning appeals to the individual's attitude in planning, controlling, and reflecting on their performance. Furthermore, this study aimed to present an observation grid for perceiving teaching instructions that encourage students' controlling cognitive behaviors in light of the belief that conscious promotion of self-regulation may motivate strategic actions toward goals in musical performance. The participants, two teachers, and two students have been involved in the social inclusion project in Lisbon (Portugal). The author and one independent inter-observer analyzed six video-recorded string instrument lessons. The data correspond to three sessions per teacher lectured to one (different) student. Violin (f) and violoncello (m) teachers hold a Master's degree in music education and approximately five years of experience. In their second year of learning an instrument, students have acquired reasonable skills in musical reading, posture, and sound quality until then. The students also manifest positive learning behaviors, interest in learning a musical instrument, although their study habits are still inconsistent. According to the grid's four categories (parent codes), in-class rehearsal frames were coded using MaxQda software, version 20, according to the grid's four categories (parent codes): self-regulated learning, teaching verbalizations, teaching strategies, and students' in-class performance. As a result, selected rehearsal frames qualitatively describe teaching instructions that might promote students' body and hearing awareness, such as "close the eyes while playing" or "sing to internalize the pitch." Another analysis type, coding the short video events according to the observation grid's subcategories (child codes), made it possible to perceive the time teachers dedicate to specific verbal or non-verbal strategies. Furthermore, a coding overlay analysis indicated that teachers tend to stimulate. (i) Forethought – explain tasks, offer feedback and ensure that students identify a goal, (ii) Performance – teach study strategies and encourage students to sing and use vocal abilities to ensure inner audition, (iii) Self-reflection – frequent inquiring and encouraging the student to verbalize their perception of performance. Although developed in the context of individual string instrument lessons, this classroom observation grid brings together essential variables in a one-to-one lesson. It may find utility in a broader context of music education due to the possibility to organize, observe and evaluate teaching practices. Besides that, this study contributes to cognitive development by suggesting a practical approach to fostering self-regulated learning.

Keywords: music education, observation grid, self-regulated learning, string instruments, teaching practices

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Authors: Ashley L. Freeman, Jessica D. Watkins

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TeleEmergency Medicine (TeleEM) is an innovative approach leveraging virtual technology to deliver specialized emergency medical care across diverse healthcare settings, including internal acute care and critical access hospitals, remote patient monitoring, and nurse triage escalation, in addition to external emergency departments, skilled nursing facilities, and community health centers. TeleEM represents a significant advancement in the delivery of emergency medical care, providing healthcare professionals the capability to deliver expertise that closely mirrors in-person emergency medicine, exceeding geographical boundaries. Through qualitative research, the extension of timely, high-quality care has proven to address the critical needs of patients in remote and underserved areas. TeleEM’s service design allows for the expansion of existing services and the establishment of new ones in diverse geographic locations. This ensures that healthcare institutions can readily scale and adapt services to evolving community requirements by leveraging on-demand (non-scheduled) telemedicine visits through the deployment of multiple video solutions. In terms of financial management, TeleEM currently employs billing suppression and subscription models to enhance accessibility for a wide range of healthcare facilities. Plans are in motion to transition to a billing system routing charges through a third-party vendor, further enhancing financial management flexibility. To address state licensure concerns, a patient location verification process has been integrated through legal counsel and compliance authorities' guidance. The TeleEM workflow is designed to terminate if the patient is not physically located within licensed regions at the time of the virtual connection, alleviating legal uncertainties. A distinctive and pivotal feature of TeleEM is the introduction of the TeleEmergency Medicine Care Team Assistant (TeleCTA) role. TeleCTAs collaborate closely with TeleEM Physicians, leading to enhanced service activation, streamlined coordination, and workflow and data efficiencies. In the last year, more than 800 TeleEM sessions have been conducted, of which 680 were initiated by internal acute care and critical access hospitals, as evidenced by quantitative research. Without this service, many of these cases would have necessitated patient transfers. Barriers to success were examined through thorough medical record review and data analysis, which identified inaccuracies in documentation leading to activation delays, limitations in billing capabilities, and data distortion, as well as the intricacies of managing varying workflows and device setups. TeleEM represents a transformative advancement in emergency medical care that nurtures collaboration and innovation. Not only has advanced the delivery of emergency medicine care virtual technology through focus group participation with key stakeholders, rigorous attention to legal and financial considerations, and the implementation of robust documentation tools and the TeleCTA role, but it’s also set the stage for overcoming geographic limitations. TeleEM assumes a notable position in the field of telemedicine by enhancing patient outcomes and expanding access to emergency medical care while mitigating licensure risks and ensuring compliant billing.

Keywords: emergency medicine, TeleEM, rural healthcare, telemedicine

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Authors: Catherine P. Bradshaw, Elise T. Pas, Katrina J. Debnam, Jessika H. Bottiani, Michael Rosenberg

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Worldwide, ethnically and culturally diverse students are at increased risk for school failure, discipline problems, and dropout. Despite decades of concern about this issue of disparities in education and other fields (e.g., 'school to prison pipeline'), there has been limited empirical examination of models that can actually reduce these gaps in schools. Moreover, few studies have examined the effectiveness of in-service teacher interventions and supports specifically designed to reduce discipline disparities and improve student engagement. This session provides an overview of the evidence-based Double Check model which serves as a framework for teachers to use culturally-responsive strategies to engage ethnically and culturally diverse students in the classroom and reduce discipline problems. Specifically, Double Check is a school-based prevention program which includes three core components: (a) enhancements to the school-wide Positive Behavioral Interventions and Supports (PBIS) tier-1 level of support; (b) five one-hour professional development training sessions, each of which addresses five domains of cultural competence (i.e., connection to the curriculum, authentic relationships, reflective thinking, effective communication, and sensitivity to students’ culture); and (c) coaching of classroom teachers using an adapted version of the Classroom Check-Up, which intends to increase teachers’ use of effective classroom management and culturally-responsive strategies using research-based motivational interviewing and data-informed problem-solving approaches. This paper presents findings from a randomized controlled trial (RCT) testing the impact of Double Check, on office discipline referrals (disaggregated by race) and independently observed and self-reported culturally-responsive practices and classroom behavior management. The RCT included 12 elementary and middle schools; 159 classroom teachers were randomized either to receive coaching or serve as comparisons. Specifically, multilevel analyses indicated that teacher self-reported culturally responsive behavior management improved over the course of the school year for teachers who received the coaching and professional development. However, the average annual office discipline referrals issued to black students were reduced among teachers who were randomly assigned to receive coaching relative to comparison teachers. Similarly, observations conducted by trained external raters indicated significantly more teacher proactive behavior management and anticipation of student problems, higher student compliance, less student non-compliance, and less socially disruptive behaviors in classrooms led by coached teachers than classrooms led teachers randomly assigned to the non-coached condition. These findings indicated promising effects of the Double Check model on a range of teacher and student outcomes, including disproportionality in office discipline referrals among Black students. These results also suggest that the Double Check model is one of only a few systematic approaches to promoting culturally-responsive behavior management which has been rigorously tested and shown to be associated with improvements in either student or staff outcomes indicated significant reductions in discipline problems and improvements in behavior management. Implications of these findings are considered within the broader context of globalization and demographic shifts, and their impacts on schools. These issues are particularly timely, given growing concerns about immigration policies in the U.S. and abroad.

Keywords: ethnically and culturally diverse students, student engagement, school-based prevention, academic achievement

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Authors: Sithandazile Masuku

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Introduction: Public health approaches to offender mental health are driven by international policies and frameworks in response to the disproportionately large representation of people with mental health problems within the offender pathway compared to the general population. Public health service innovations include mental health courts in the US, restorative models in Singapore and, liaison and diversion services in Australia, the UK, and some other European countries. Mental health nurses are at the forefront of offender health service innovations. In the U.K. context, police custody has been identified as an early point within the offender pathway where nurses can improve outcomes by offering assessments and share information with criminal justice partners. This scope of nursing practice has introduced challenges related to skills and support required for nurses working at the interface of health and the criminal justice system. Parallel literature exploring experiences of nurses working in forensic settings suggests the presence of compassion fatigue, burnout and vicarious trauma that may impede risk harm to the nurses in these settings. Published research explores mainly service-level outcomes including monitoring of figures indicative of a reduction in offending behavior. There is minimal research exploring the experiences of liaison and diversion nurses who are situated away from a supportive clinical environment and engaged in complex autonomous decision-making. Aim: This paper will share qualitative findings (in progress) from a PhD study that aims to explore the experiences of liaison and diversion nurses in one service in the U.K. Methodology: This is a qualitative interview study conducted using an Interpretative Phenomenological Analysis to gain an in-depth analysis of lived experiences. Methods: A purposive sampling technique was used to recruit n=8 mental health nurses registered with the UK professional body, Nursing and Midwifery Council, from one UK Liaison and Diversion service. All participants were interviewed online via video call using semi-structured interview topic guide. Data were recorded and transcribed verbatim. Data were analysed using the seven steps of the Interpretative Phenomenological Analysis data analysis method. Emerging Findings Analysis to date has identified pertinent themes: • Difficulties of meaning-making for nurses because of the complexity of their boundary spanning role. • Emotional burden experienced in a highly emotive and fast-changing environment. • Stress and difficulties with role identity impacting on individual nurses’ ability to be resilient. • Challenges to wellbeing related to a sense of isolation when making complex decisions. Conclusion Emerging findings have highlighted the lived experiences of nurses working in liaison and diversion as challenging. The nature of the custody environment has an impact on role identity and decision making. Nurses left feeling isolated and unsupported are less resilient and may go on to experience compassion fatigue. The findings from this study thus far point to a need to connect nurses working in these boundary spanning roles with a supportive infrastructure where the complexity of their role is acknowledged, and they can be connected with a health agenda. In doing this, the nurses would be protected from harm and the likelihood of sustained positive outcomes for service users is optimised.

Keywords: liaison and diversion, nurse experiences, offender health, staff wellbeing

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Authors: Wiam El Kheir, Anais Dumais, Maude Beaudoin, Bernard Marcos, Nick Virgilio, Benoit Paquette, Nathalie Faucheux, Marc-Antoine Lauzon

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The high infiltrative pattern of glioblastoma multiforme cells (GBM) is the main cause responsible for the actual standard treatments failure. The tumor high heterogeneity, the interstitial fluid flow (IFF) and chemokines guides GBM cells migration in the brain parenchyma resulting in tumor recurrence. Drug delivery systems emerged as an alternative approach to develop effective treatments for the disease. Some recent studies have proposed to harness the effect CXC-lchemokine-ligand-12 to direct and control the cancer cell migration through delivery system. However, the dynamics of the brain environment on the delivery system remains poorly understood. Nanoparticles (NPs) and hydrogels are known as good carriers for the encapsulation of different agents and control their release. We studied the release of CXCL12 (free or loaded into NPs) from an alginate-based hydrogel under static and indirect perfusion (IP) conditions. Under static conditions, the main phenomena driving CXCL12 release from the hydrogel was diffusion with the presence of strong interactions between the positively charged CXCL12 and the negatively charge alginate. CXCL12 release profiles were independent from the initial mass loadings. Afterwards, we demonstrated that the release could tuned by loading CXCL12 into Alginate/Chitosan-Nanoparticles (Alg/Chit-NPs) and embedded them into alginate-hydrogel. The initial burst release was substantially attenuated and the overall cumulative release percentages of 21%, 16% and 7% were observed for initial mass loadings of 0.07, 0.13 and 0.26 µg, respectively, suggesting stronger electrostatic interactions. Results were mathematically modeled based on Fick’s second law of diffusion framework developed previously to estimate the effective diffusion coefficient (Deff) and the mass transfer coefficient. Embedding the CXCL12 into NPs decreased the Deff an order of magnitude, which was coherent with experimental data. Thereafter, we developed an in-vitro 3D model that takes into consideration the convective contribution of the brain IFF to study CXCL12 release in an in-vitro microenvironment that mimics as faithfully as possible the human brain. From is unique design, the model also allowed us to understand the effect of IP on CXCL12 release in respect to time and space. Four flow rates (0.5, 3, 6.5 and 10 µL/min) which may increase CXCL12 release in-vivo depending on the tumor location were assessed. Under IP, cumulative percentages varying between 4.5-7.3%, 23-58.5%, 77.8-92.5% and 89.2-95.9% were released for the three initial mass loadings of 0.08, 0.16 and 0.33 µg, respectively. As the flow rate increase, IP culture conditions resulted in a higher release of CXCL12 compared to static conditions as the convection contribution became the main driving mass transport phenomena. Further, depending on the flow rate, IP had a direct impact on CXCL12 distribution within the simulated brain tissue, which illustrates the importance of developing such 3D in-vitro models to assess the efficiency of a delivery system targeting the brain. In future work, using this very model, we aim to understand the impact of the different phenomenon occurring on GBM cell behaviors in response to the resulting chemokine gradient subjected to various flow while allowing them to express their invasive characteristics in an in-vitro microenvironment that mimics the in-vivo brain parenchyma.

Keywords: 3D culture system, chemokines gradient, glioblastoma multiforme, kinetic release, mathematical modeling

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Authors: Vipin Bhandari, Anupama Singh, Kopal Gupta

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Solid state fermentation, an eminent bioconversion technique for converting many biological substrates into a value-added product, has proven its role in the biotransformation of crops by nutritionally enriching them. Hence, an effort was made for nutritional enhancement of underutilized crops viz. barnyard millet, amaranthus and horse gram based composite flour using SSF. The grains were given pre-treatments before fermentation and these pre-treatments proved quite effective in diminishing the level of antinutrients in grains and in improving their nutritional characteristics. The present study deals with the enhancement of nutritional characteristics of underutilized crops viz. barnyard millet, amaranthus and horsegram based composite flour using solid state fermentation (SSF) as the principle bioconversion technique to convert the composite flour substrate into a nutritionally enriched value added product. Response surface methodology was used to design the experiments. The variables selected for the fermentation experiments were substrate particle size, substrate blend ratio, fermentation time, fermentation temperature and moisture content having three levels of each. Seventeen designed experiments were conducted randomly to find the effect of these variables on microbial count, reducing sugar, pH, total sugar, phytic acid and water absorption index. The data from all experiments were analyzed using Design Expert 8.0.6 and the response functions were developed using multiple regression analysis and second order models were fitted for each response. Results revealed that pretreatments proved quite handful in diminishing the level of antinutrients and thus enhancing the nutritional value of the grains appreciably, for instance, there was about 23% reduction in phytic acid levels after decortication of barnyard millet. The carbohydrate content of the decorticated barnyard millet increased to 81.5% from initial value of 65.2%. Similarly popping and puffing of horsegram and amaranthus respectively greatly reduced the trypsin inhibitor activity. Puffing of amaranthus also reduced the tannin content appreciably. Bacillus subtilis was used as the inoculating specie since it is known to produce phytases in solid state fermentation systems. These phytases remarkably reduce the phytic acid content which acts as a major antinutritional factor in food grains. Results of solid state fermentation experiments revealed that phytic acid levels reduced appreciably when fermentation was allowed to continue for 72 hours at a temperature of 35°C. Particle size and substrate blend ratio also affected the responses positively. All the parameters viz. substrate particle size, substrate blend ratio, fermentation time, fermentation temperature and moisture content affected the responses namely microbial count, reducing sugar, pH, total sugar, phytic acid and water absorption index but the effect of fermentation time was found to be most significant on all the responses. Statistical analysis resulted in the optimum conditions (particle size 355µ, substrate blend ratio 50:20:30 of barnyard millet, amaranthus and horsegram respectively, fermentation time 68 hrs, fermentation temperature 35°C and moisture content 47%) for maximum reduction in phytic acid. The model F- value was found to be highly significant at 1% level of significance in case of all the responses. Hence, second order model could be fitted to predict all the dependent parameters. The effect of fermentation time was found to be most significant as compared to other variables.

Keywords: composite flour, solid state fermentation, underutilized crops, cereals, fermentation technology, food processing

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Authors: Adriana De Serio, Adrian Korek

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Aims: This experiential research work presents a Group-MusicTherapy-Theatre-Plan (MusThePlan) the authors have carried out to support the actors. The MusicTherapy gives rise to individual psychophysical feedback and influences the emotional centres of the brain and the subconsciousness. Therefore, the authors underline the effectiveness of the preventive, educational, and training goals of the MusThePlan to lead theatre students and actors to deal with anxiety and to overcome psychophysical weaknesses, shyness, emotional stress in stage performances, to increase flexibility, awareness of one's identity and resources for a positive self-development and psychophysical health, to develop and strengthen social bonds, increasing a network of subjects working for social inclusion and reduction of stigma. Materials-Methods: Thirty students from the University Theatre Faculty participated in weekly music therapy sessions for two months; each session lasted 120 minutes. MusThePlan: Each session began with a free group rhythmic-sonorous-musical-production by body-percussion, voice-canto, instruments, to stimulate communication. Then, a synchronized-structured bodily-rhythmic-sonorous-musical production also involved acting, dances, movements of hands and arms, hearing, and more sensorial perceptions and speech to balance motor skills and the muscular tone. Each student could be the director-leader of the group indicating a story to inspire the group's musical production. The third step involved the students in rhythmic speech and singing drills and in vocal exercises focusing on the musical pitch to improve the intonation and on the diction to improve the articulation and lead up it to an increased intelligibility. At the end of each musictherapy session and of the two months, the Musictherapy Assessment Document was drawn up by analysis of observation protocols and two Indices by the authors: Patient-Environment-Music-Index (time to - tn) to estimate the behavior evolution, Somatic Pattern Index to monitor subject’s eye and mouth and limb motility, perspiration, before, during and after musictherapy sessions. Results: After the first month, the students (non musicians) learned to play percussion instruments and formed a musical band that played classical/modern music on the percussion instruments with the musictherapist/pianist/conductor in a public concert. At the end of the second month, the students performed a public musical theatre show, acting, dancing, singing, and playing percussion instruments. The students highlighted the importance of the playful aspects of the group musical production in order to achieve emotional contact and harmony within the group. The students said they had improved kinetic and vocal and all the skills useful for acting activity and the nourishment of the bodily and emotional balance. Conclusions: The MusThePlan makes use of some specific MusicTherapy methodological models, techniques, and strategies useful for the actors. The MusThePlan can destroy the individual "mask" and can be useful when the verbal language is unable to undermine the defense mechanisms of the subject. The MusThePlan improves actor’s psychophysical activation, motivation, gratification, knowledge of one's own possibilities, and the quality of life. Therefore, the MusThePlan could be useful to carry out targeted interventions for the actors with characteristics of repeatability, objectivity, and predictability of results. Furthermore, it would be useful to plan a University course/master in “MusicTherapy for the Theatre”.

Keywords: musictherapy, sonorous-musical energy, quality of life, theatre

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Anjalika Fernando, Banuka Athuraliya

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This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

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Authors: David A. Olasehinde, Peter I. Olasehinde, Segun M. A. Adelana, Dapo O. Olasehinde

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An investigation was carried out on underground water system dynamics within Ilorin metropolis to monitor the subsurface flow and its corresponding pollution. Africa population growth rate is the highest among the regions of the world, especially in urban areas. A corresponding increase in waste generation and a change in waste composition from predominantly organic to non-organic waste has also been observed. Percolation of leachate from non-engineered landfills, the chief means of waste disposal in many of its cities, constitutes a threat to the underground water bodies. Ilorin city, a transboundary town in southwestern Nigeria, is a ready microcosm of Africa’s unique challenge. In spite of the fact that groundwater is naturally protected from common contaminants such as bacteria as the subsurface provides natural attenuation process, groundwater samples have been noted to however possesses relatively higher dissolved chemical contaminants such as bicarbonate, sodium, and chloride which poses a great threat to environmental receptors and human consumption. The Geographic Information System (GIS) was used as a tool to illustrate, subsurface dynamics and the corresponding pollutant indicators. Forty-four sampling points were selected around known groundwater pollutant, major old dumpsites without landfill liners. The results of the groundwater flow directions and the corresponding contaminant transport were presented using expert geospatial software. The experimental results were subjected to four descriptive statistical analyses, namely: principal component analysis, Pearson correlation analysis, scree plot analysis, and Ward cluster analysis. Regression model was also developed aimed at finding functional relationships that can adequately relate or describe the behaviour of water qualities and the hypothetical factors landfill characteristics that may influence them namely; distance of source of water body from dumpsites, static water level of groundwater, subsurface permeability (inferred from hydraulic gradient), and soil infiltration. The regression equations developed were validated using the graphical approach. Underground water seems to flow from the northern portion of Ilorin metropolis down southwards transporting contaminants. Pollution pattern in the study area generally assumed a bimodal pattern with the major concentration of the chemical pollutants in the underground watershed and the recharge. The correlation between contaminant concentrations and the spread of pollution indicates that areas of lower subsurface permeability display a higher concentration of dissolved chemical content. The principal component analysis showed that conductivity, suspended solids, calcium hardness, total dissolved solids, total coliforms, and coliforms were the chief contaminant indicators in the underground water system in the study area. Pearson correlation revealed a high correlation of electrical conductivity for many parameters analyzed. In the same vein, the regression models suggest that the heavier the molecular weight of a chemical contaminant of a pollutant from a point source, the greater the pollution of the underground water system at a short distance. The study concludes that the associative properties of landfill have a significant effect on groundwater quality in the study area.

Keywords: dumpsite, leachate, groundwater pollution, linear regression, principal component

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: Papakonstantinou Apostolos, Argyrios Moustakas, Panagiotis Zervos, Dimitrios Stefanakis, Manolis Tsapakis, Nektarios Spyridakis, Mary Paspaliari, Christos Kontos, Antonis Legakis, Sarantis Houzouris, Konstantinos Topouzelis

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For years unmanned and remotely operated robots have been used as tools in industry research and education. The rapid development and miniaturization of sensors that can be attached to remotely operated vehicles in recent years allowed industry leaders and researchers to utilize them as an affordable means for data acquisition in air, land, and sea. Despite the recent developments in the ground and unmanned airborne vehicles, a small number of Unmanned Surface Vehicle (USV) platforms are targeted for mapping and monitoring environmental parameters for research and industry purposes. The ARGO project is developed an open-design USV equipped with multi-level control hardware architecture and state-of-the-art sensors and payloads for the autonomous monitoring of environmental parameters in large sea areas. The proposed USV is a catamaran-type USV controlled over a wireless radio link (5G) for long-range mapping capabilities and control for a ground-based control station. The ARGO USV has a propulsion control using 2x fully redundant electric trolling motors with active vector thrust for omnidirectional movement, navigation with opensource autopilot system with high accuracy GNSS device, and communication with the 2.4Ghz digital link able to provide 20km of Line of Sight (Los) range distance. The 3-meter dual hull design and composite structure offer well above 80kg of usable payload capacity. Furthermore, sun and friction energy harvesting methods provide clean energy to the propulsion system. The design is highly modular, where each component or payload can be replaced or modified according to the desired task (industrial or research). The system can be equipped with Multiparameter Sonde, measuring up to 20 water parameters simultaneously, such as conductivity, salinity, turbidity, dissolved oxygen, etc. Furthermore, a high-end multibeam echo sounder can be installed in a specific boat datum for shallow water high-resolution seabed mapping. The system is designed to operate in the Aegean Sea. The developed USV is planned to be utilized as a system for autonomous data acquisition, mapping, and monitoring bathymetry and various environmental parameters. ARGO USV can operate in small or large ports with high maneuverability and endurance to map large geographical extends at sea. The system presents state of the art solutions in the following areas i) the on-board/real-time data processing/analysis capabilities, ii) the energy-independent and environmentally friendly platform entirely made using the latest aeronautical and marine materials, iii) the integration of advanced technology sensors, all in one system (photogrammetric and radiometric footprint, as well as its connection with various environmental and inertial sensors) and iv) the information management application. The ARGO web-based application enables the system to depict the results of the data acquisition process in near real-time. All the recorded environmental variables and indices are presented, allowing users to remotely access all the raw and processed information using the implemented web-based GIS application.

Keywords: monitor marine environment, unmanned surface vehicle, mapping bythometry, sea environmental monitoring

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Authors: Demetrio L. Valle Jr., Juliana Janet M. Puzon, Windell L. Rivera

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From the various medicinal plants available in the Philippines, crude ethanol extracts of twelve (12) Philippine medicinal plants, namely: Senna alata L. Roxb. (akapulko), Psidium guajava L. (bayabas), Piper betle L. (ikmo), Vitex negundo L. (lagundi), Mitrephora lanotan (Blanco) Merr. (Lanotan), Zingiber officinale Roscoe (luya), Curcuma longa L. (Luyang dilaw), Tinospora rumphii Boerl (Makabuhay), Moringga oleifera Lam. (malunggay), Phyllanthus niruri L. (sampa-sampalukan), Centella asiatica (L.) Urban (takip kuhol), and Carmona retusa (Vahl) Masam (tsaang gubat) were studied. In vitro methods of evaluation against selected Gram-positive and Gram-negative multidrug-resistant (MDR), bacteria were performed on the plant extracts. Although five of the plants showed varying antagonistic activities against the test organisms, only Piper betle L. exhibited significant activities against both Gram-negative and Gram-positive multidrug-resistant bacteria, exhibiting wide zones of growth inhibition in the disk diffusion assay, and with the lowest concentrations of the extract required to inhibit the growth of the bacteria, as supported by the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assays. Further antibacterial studies of the Piper betle L. leaf, obtained by three extraction methods (ethanol, methanol, supercritical CO2), revealed similar inhibitory activities against a multitude of Gram-positive and Gram-negative MDR bacteria. Thin layer chromatography (TLC) assay of the leaf extract revealed a maximum of eight compounds with Rf values of 0.92, 0.86, 0.76, 0.53, 0.40, 0.25, 0.13, and 0.013, best visualized when inspected under UV-366 nm. TLC- agar overlay bioautography of the isolated compounds showed the compounds with Rf values of 0.86 and 0.13 having inhibitory activities against Gram-positive MDR bacteria (MRSA and VRE). The compound with an Rf value of 0.86 also possesses inhibitory activity against Gram-negative MDR bacteria (CRE Klebsiella pneumoniae and MBL Acinetobacter baumannii). Gas Chromatography-Mass Spectrometry (GC-MS) was able to identify six volatile compounds, four of which are new compounds that have not been mentioned in the medical literature. The chemical compounds isolated include 4-(2-propenyl)phenol and eugenol; and the new four compounds were ethyl diazoacetate, tris(trifluoromethyl)phosphine, heptafluorobutyrate, and 3-fluoro-2-propynenitrite. Phytochemical screening and investigation of its antioxidant, cytotoxic, possible hemolytic activities, and mechanisms of antibacterial activity were also done. The results showed that the local variant of Piper betle leaf extract possesses significant antioxidant, anti-cancer and antimicrobial properties, attributed to the presence of bioactive compounds, particularly of flavonoids (condensed tannin, leucoanthocyanin, gamma benzopyrone), anthraquinones, steroids/triterpenes and 2-deoxysugars. Piper betle L. is also traditionally known to enhance wound healing, which could be primarily due to its antioxidant, anti-inflammatory and antimicrobial activities. In vivo studies on mice using 2.5% and 5% of the ethanol leaf extract cream formulations in the excised wound models significantly increased the process of wound healing in the mice subjects, the results and values of which are at par with the current antibacterial cream (Mupirocin). From the results of the series of studies, we have definitely proven the value of Piper betle L. as a source of bioactive compounds that could be developed into therapeutic agents against MDR bacteria.

Keywords: Philippine herbal medicine, multidrug-resistant bacteria, Piper betle, TLC-bioautography

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Authors: Joel A. Gordon, Nazmiye Balta-Ozkan, Seyed Ali Nabavi

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Hydrogen-fueled technologies are rapidly advancing as a critical component of the low-carbon energy transition. In countries historically reliant on natural gas for home heating, such as the UK, hydrogen may prove fundamental for decarbonizing the residential sector, alongside other technologies such as heat pumps and district heat networks. While the UK government is set to take a long-term policy decision on the role of domestic hydrogen by 2026, there are considerable uncertainties regarding consumer preferences for ‘hydrogen homes’ (i.e., hydrogen-fueled appliances for space heating, hot water, and cooking. In comparison to other hydrogen energy technologies, such as road transport applications, to date, few studies have engaged with the social acceptance aspects of the domestic hydrogen transition, resulting in a stark knowledge deficit and pronounced risk to policymaking efforts. In response, this study aims to safeguard against undesirable policy measures by revealing the underlying relationships between the factors of domestic hydrogen acceptance and their respective dimensions: attitudinal, socio-political, community, market, and behavioral acceptance. The study employs an online survey (n=~2100) to gauge how different UK householders perceive the proposition of switching from natural gas to hydrogen-fueled appliances. In addition to accounting for housing characteristics (i.e., housing tenure, property type and number of occupants per dwelling) and several other socio-structural variables (e.g. age, gender, and location), the study explores the impacts of consumer heterogeneity on hydrogen acceptance by recruiting respondents from across five distinct groups: (1) fuel poor householders, (2) technology engaged householders, (3) environmentally engaged householders, (4) technology and environmentally engaged householders, and (5) a baseline group (n=~700) which filters out each of the smaller targeted groups (n=~350). This research design reflects the notion that supporting a socially fair and efficient transition to hydrogen will require parallel engagement with potential early adopters and demographic groups impacted by fuel poverty while also accounting strongly for public attitudes towards net zero. Employing a second-order multigroup confirmatory factor analysis (CFA) in Mplus, the proposed hydrogen acceptance model is tested to fit the data through a partial least squares (PLS) approach. In addition to testing differences between and within groups, the findings provide policymakers with critical insights regarding the significance of knowledge and awareness, safety perceptions, perceived community impacts, cost factors, and trust in key actors and stakeholders as potential explanatory factors of hydrogen acceptance. Preliminary results suggest that knowledge and awareness of hydrogen are positively associated with support for domestic hydrogen at the household, community, and national levels. However, with the exception of technology and/or environmentally engaged citizens, much of the population remains unfamiliar with hydrogen and somewhat skeptical of its application in homes. Knowledge and awareness present as critical to facilitating positive safety perceptions, alongside higher levels of trust and more favorable expectations for community benefits, appliance performance, and potential cost savings. Based on these preliminary findings, policymakers should be put on red alert about diffusing hydrogen into the public consciousness in alignment with energy security, fuel poverty, and net-zero agendas.

Keywords: hydrogen homes, social acceptance, consumer heterogeneity, heat decarbonization

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