Search results for: potential cracking

Authors: Mitansha, Suzanne Wilkinson, Regan Potangaroa

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The built environment is designed, maintained, operated, and decommissioned by construction organisations, which play a significant role in providing physical resources and rebuilding infrastructures during major crises and disasters. It is evident that enhancing the resilience of construction organisations allows better responding ability and speedy recovery from disasters and acts as a boon for the nation in the face of significant disruptions. As individuals are the integral component of any organisation, hence, individual resilience is considered a critical aspect, which may boost organisational resilience of construction sector. It has been observed that individual resilience is indirectly supported by organisation’s citizenship behaviour, job performance, and career success. Not only this, it also tends to hold a directly proportional relation with job satisfaction, physical and emotional well-being affected by organisation’s work culture, whereas the resilience of organisation increases as a result of positive adaption, growth and collective learning of the employees as an entity. Moreover, indicators like Situation awareness in staff and crisis related issues, effective vulnerability management, organisational leadership and culture ensured by approachable, encouraging and people-oriented leaders, are prominent for achieving organisational resilience. It, thus, becomes perceptible that both, organisational and individual resiliencies have the potential to influence each other. Consequently, it arises a major question that how these characteristics are associated and tend to behave with respect to each other The study, thus, aims to explore the overlapping dimensions of organisational and individual resilience to determine the impact boundaries. The research methodology of the paper would be based on systematic literature review specifically focused on the resilience of construction industry. This would provide a direct comparison of characteristics influencing individual and organisational resilience and will present the most significant indicators of individual resilience, that can eventually help to enhance the resilience of construction organisations amidst any disaster or crisis.

Keywords: construction industry, individual resilience, organizational resilience, overlapping dimension

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Authors: Zahrul Faizi M. S., Ali A., Norhuda A. M.

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Emission of greenhouse gases (GHG) from solid waste treatment and dependency on fossil fuel to produce electricity are the major concern in Malaysia as well as global. Innovation in downdraft gasification with combined heat and power (CHP) systems has the potential to minimize solid waste and reduce the emission of anthropogenic GHG from conventional fossil fuel power plants. However, the efficiency and capability of downdraft gasification to generate electricity from various alternative fuels, for instance, agriculture residues (i.e., woodchip, coconut shell) and municipal solid waste (MSW), are still controversial, on top of the toxicity level from the produced bottom ash. Thus this study evaluates the adaptability and reliability of the 20 kW downdraft gasification system to generate electricity (while considering environmental sustainability from the bottom ash) using flexible local feedstock at 20, 40, and 60% mixed ratio of MSW: agriculture residues. Feedstock properties such as feed particle size, moisture, and ash contents are also analyzed to identify optimal characteristics for the combination of feedstock (feedstock flexibility) to obtain maximum energy generation. Results show that the gasification system is capable to flexibly accommodate different feedstock compositions subjected to specific particle size (less than 2 inches) at a moisture content between 15 to 20%. These values exhibit enhance gasifier performance and provide a significant effect to the syngas composition utilizes by the internal combustion engine, which reflects energy production. The result obtained in this study is able to provide a new perspective on the transition of the conventional gasification system to a future reliable carbon-negative energy technology. Subsequently, promoting commercial scale-up of the downdraft gasification system.

Keywords: carbon-negative energy, feedstock flexibility, gasification, renewable energy

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Authors: Naveen Kumar B. T., Anuj Tyagi, Niraj Kumar Singh, Visanu Boonyawiwat, Shanthanagouda A. H., Orawan Boodde, Shankar K. M., Prakash Patil, Shubhkaramjeet Kaur

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Since 2009, Acute Hepatopancreatic Necrosis Disease (AHPND) outbreaks have increased rapidly, and these have led to the major economic losses to the global shrimp industry. In comparison to other treatments, passive immunity and monoclonal antibody (MAb) based farmer level kit have proved their importance in controlling and treating the diseases in the shrimp industry. In the present study, MAbs were produced against the recombinant PirB protein Vibrio parahaemolyticus strain causing AHPND. Briefly, Balb/C mice were immunized with rPirB at 15 days interval, and antibody titer was determined by ELISA. Spleen cells from mice showing high antibody titer were fused with SP2O myeloma cells for hybridoma production. Among 130 hybridomas, four showed high antibody titer and positive reactivity in an immunoblot assay. In Western blot assay, three out of four MAbs (4C4, 2C2 and 4G3) showed reactivity to rPirB protein. However, in the natural host, only Mab clone 4G3 show strong reactivity (with a strain of V. parahemolyticus causing EMS/AHPND). These clones also showed reactivity with less than 20 kDa proteins in AHPND free V. parahaemolyticus (Thailand stain). Further, on from MAb 4G3 clone, four panels of single cell MAbs clones (G3F5, G3B8, G3H2, and G3D6) were produced of which three showed strong positive reactivity to rPirB protein in the Western blot. These MAbs have potential for controlling and prevention of the AHPND through passive immunity and development of filed level rapid diagnostic kits.

Keywords: shrimp, economic loss, AHPND, MAb

Procedia PDF Downloads 253

Authors: Hasan Muslemani, Jeffrey Wilson, Xi Liang, Francisco Ascui, Katharina Kaesehage

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This paper aims to examine consumer behaviour towards, and the willingness to adopt, green steel use in the automotive sector, in order to identify potential barriers and opportunities for its widespread adoption. Semi-structured interviews were held with experts from global, regional and country-specific industry associations and automakers. The analysis shows there is a new shift towards lifecycle thinking in the sector, although these efforts have been voluntary and driven by customer and employee pressures rather than regulation. The paper further appraises possible demand for green steel within different vehicle types (based on size and powertrain), and shows that manufacturers of electric heavy-duty vehicles are most likely to adopt green steel in the first instance, given the amount of incorporated steel in the vehicles and the fact that lifecycle emissions lie predominantly in their manufacturing phase. A case for green advanced higher-strength steels (AHSS) can also be made in light-duty passenger vehicles, which may mitigate competition from light-weight alternative materials in terms of cost and greenness (depending on source and utilisation zones). This work builds on a wide sustainability-related literature in the automotive sector and highlights areas in need of urgent action if the sector as a whole were to meet its Paris Agreement climate targets, in particular a need to revisit current CO2 performance regulations to include Scope 1 and Scope 2 emissions, engage in educational green marketing campaigns, and explore innovative market-based mechanisms to bridge the gap between relatively-low carbon abatement costs of steelmaking and high abatement costs of vehicle manufacturing.

Keywords: Green steel, Consumer behaviour, Automotive industry, Environmental sustainability

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Authors: Linghui Meng, James Atlas, Deborah Munro

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There is an increasing demand for prosthetics capable of mimicking natural limb movements and hand gestures, but precise movement control of prosthetics using only electrode signals continues to be challenging. This study considers the implementation of machine learning as a means of improving accuracy and presents an initial investigation into hand gesture recognition using models based on electromyographic (EMG) signals. EMG signals, which capture muscle activity, are used as inputs to machine learning algorithms to improve prosthetic control accuracy, functionality and adaptivity. Using logistic regression, a machine learning classifier, this study evaluates the accuracy of classifying two hand gestures from the publicly available Ninapro dataset using two-time series feature extraction algorithms: Time Series Feature Extraction (TSFE) and Convolutional Neural Networks (CNNs). Trials were conducted using varying numbers of EMG channels from one to eight to determine the impact of channel quantity on classification accuracy. The results suggest that although both algorithms can successfully distinguish between hand gesture EMG signals, CNNs outperform TSFE in extracting useful information for both accuracy and computational efficiency. In addition, although more channels of EMG signals provide more useful information, they also require more complex and computationally intensive feature extractors and consequently do not perform as well as lower numbers of channels. The findings also underscore the potential of machine learning techniques in developing more effective and adaptive prosthetic control systems.

Keywords: EMG, machine learning, prosthetic control, electromyographic prosthetics, hand gesture classification, CNN, computational neural networks, TSFE, time series feature extraction, channel count, logistic regression, ninapro, classifiers

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Authors: Conor Blunt, Mariluz del Pino-de Elias, Grace Cott, Saoirse Tracy, Rainer Melzer

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The European Green Deal announced in 2021 details agricultural chemical pesticide use and synthetic fertilizer application to be reduced by 50% and 20% by 2030. Increasing and maintaining expected yields under these ambitious goals has strained the agricultural sector. This intergovernmental plan has identified plant biostimulants as one potential input to facilitate this new phase of sustainable agriculture; these products are defined as microorganisms or substances that can stimulate soil and plant functioning to enhance crop nutrient use efficiency, quality and tolerance to abiotic stresses. Spring barley is Ireland’s most widely sown tillage crop, and grain destined for malting commands the most significant market price. Heavy erratic rainfall is forecasted in Ireland’s climate future, and barley is particularly susceptible to waterlogging. Recent findings suggest that plant receptivity to biostimulants may depend on the level of stress inflicted on crops to elicit an assisted plant response. In this study, three biostimulants of different genesis (seaweed, protein hydrolysate and bacteria) are applied to ‘RGT Planet’ malting barley fertilized at three different rates (0 kg/ha, 40 kg/ha, 75 kg/ha) of calcium ammonium nitrogen (27% N) under non-stressed and waterlogged conditions. This 4x3x2 factorial trial design was planted in a completed randomized block with one plant per experimental unit. Leaf gas exchange data and key agronomic and grain quality parameters were analyzed via ANOVA. No penalty on productivity was evident on plants receiving 40 kg/ha of N and bio stimulant compared to 75 kg/ha of N treatments. The main effects of nitrogen application and waterlogging provided the most significant variation in the dataset.

Keywords: biostimulant, Barley, malting, NUE, waterlogging

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Authors: Lakshmikanth Reddy, Bhavin Desai, Chandrakala Kari, Sanjay Sarkar, Pradeep Binu

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The sulphur dioxide gases generated as a by-product of smelting and converting operations of copper concentrate contain selenium apart from zinc, lead, copper, cadmium, bismuth, antimony, and arsenic. The gaseous stream is treated in waste heat boiler, electrostatic precipitator and scrubbers to remove coarse particulate matter in order to produce commercial grade sulfuric acid. The gas cleaning section of the acid plant uses water to scrub the smelting gases. After scrubbing, the sludge settled at the bottom of the scrubber, was analyzed in present investigation. It was found to contain 30 to 40 wt% copper and selenium up to 40 wt% selenium. The sludge collected during blow-down is directly recycled to the smelter for copper recovery. However, the selenium is expected to again vaporize due to high oxidation potential during smelting and converting, causing accumulation of selenium in sludge. In present investigation, a roasting process has been developed to recover the selenium before the copper recovery from the sludge at smelter. Selenium is associated with copper in sludge as copper selenide, as determined by X-ray diffraction and electron microscopy. The thermodynamic and thermos-gravimetry study revealed that the copper selenide phase present in the sludge was amenable to oxidation at 600°C forming oxides of copper and selenium (Cu-Se-O). However, the dissociation of selenium from the copper oxide was made possible by sulfatation using sulfur dioxide between 450 to 600°C, resulting into the formation of CuSO₄ (s) and SeO₂ (g). Lab scale trials were carried out in vertical tubular furnace to determine the optimum roasting conditions with respect to roasting time, temperature and molar ratio of O₂:SO₂. Using these optimum conditions, selenium up to 90 wt% in the form of SeO₂ vapors could be recovered from the sludge in a large-scale commercial roaster. Roasted sludge free from the selenium and containing oxides and sulfates of copper could now be recycled in the smelter for copper recovery.

Keywords: copper, selenium, copper selenide, sludge, roasting, SeO₂

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Authors: Rajesh Agarwal

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Carrier mobility at the organic/insulator interface is essential to the performance of organic thin film transistors (OTFT). The present work describes estimation of field dependent mobility (FDM) parameters and the threshold voltage of an OTFT using a simple, easy to fabricate two terminal asymmetric capacitive test structure using admittance measurements. Conventionally, transfer characteristics are used to estimate the threshold voltage in an OTFT with field independent mobility (FIDM). Yet, this technique breaks down to give accurate results for devices with high contact resistance and having field dependent mobility. In this work, a new technique is presented for characterization of long channel organic capacitor (LCOC). The proposed technique helps in the accurate estimation of mobility enhancement factor (γ), the threshold voltage (V_th) and band mobility (µ₀) using capacitance-voltage (C-V) measurement in OTFT. This technique also helps to get rid of making short channel OTFT or metal-insulator-metal (MIM) structures for making C-V measurements. To understand the behavior of devices and ease of analysis, transmission line compact model is developed. The 2-D numerical simulation was carried out to illustrate the correctness of the model. Results show that proposed technique estimates device parameters accurately even in the presence of contact resistance and field dependent mobility. Pentacene/Poly (4-vinyl phenol) based top contact bottom-gate OTFT’s are fabricated to illustrate the operation and advantages of the proposed technique. Small signal of frequency varying from 1 kHz to 5 kHz and gate potential ranging from +40 V to -40 V have been applied to the devices for measurement.

Keywords: capacitance, mobility, organic, thin film transistor

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Authors: Setapo Moloi, Jun-Ichiro Giorgos Tsutsumi

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South Africa’s need for the provision of housing within its major city centres, specifically Gauteng Province (GP), is a major concern. Initiatives for converting misused/ unused buildings to suitable housing for residents who work in the city as well as prospective citizens are currently underway, one aspect that is needed currently, is the re-possession of these buildings repurposing, into housing communities for quality low cost mixed density housing and for this process to have minimal strain on existing infrastructure like energy, emission reduction etc. Unfortunately, there are instances in Johannesburg, the country’s economic capital, with 2017 estimates claiming that 700 buildings lay unused or misused due to issues that will be discussed in this paper, these then become hubs for illegal activity and are an unacceptable form of shelter. It can be argued that the provision of inner-city social housing is lacking, but not due to the unavailability of funding or usable land and buildings, but that these assets are not being used appropriately nor to their full potential. Currently the GP government has mandated the re-purposing of all buildings that meet their criteria (structural stability, feasibility, adaptability, etc.) with the intention of inviting interested parties to propose conversions of the buildings into densified social housing. Going forward, the proposed focus is creation of social housing communities within existing buildings which may be retrofitted with sustainable technologies, green design strategies and principles, aiming for the finished buildings to achieve ‘Net-Zero/Positive’ status. A Net-Zero building, according to The Green Building Council of South Africa (GBCSA) is a building which manages to produce resources it needs to function, and reduces wastage, emissions and demand of these resources during its lifespan. The categories which GBCSA includes are carbon, water, waste and ecology, this may include material selection, construction methods, etc.

Keywords: adaptive reuse, conversion, net-zero, social housing, sustainable communities

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Authors: Li-Ting Huang, Yu-Hsiang Shen, Cing-Ciao Ke, Sheng-Pin Tseng, Fan-Pin Tseng, Yu-Ching Ni, Chia-Yu Lin

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Chest radiography is the most common technique for the diagnosis and follow-up of pulmonary diseases. However, the lesions superimposed with normal structures are difficult to be detected in chest radiography. Chest tomosynthesis is a relatively new technique to obtain 3D section images from a set of low-dose projections acquired over a limited angular range. However, there are some limitations with chest tomosynthesis. Patients undergoing tomosynthesis have to be able to hold their breath firmly for 10 seconds. A digital tomosynthesis system with advanced reconstruction algorithm and high-stability motion mechanism was developed by our research group. The potential for the system to perform a bidirectional chest scan within 10 seconds is expected. The purpose of this study is to realize the influences of the scan speed on the image quality for our digital tomosynthesis system. The major factors that lead image blurring are the motion of the X-ray source and the patient. For the fore one, an experiment of imaging a chest phantom with three different scan speeds, which are 6 cm/s, 8 cm/s, and 15 cm/s, was proceeded to understand the scan speed influences on the image quality. For the rear factor, a normal SD (Sprague-Dawley) rat was imaged with it alive and sacrificed to assess the impact on the image quality due to breath motion. In both experiments, the profile of the ROIs (region of interest) and the CNRs (contrast-to-noise ratio) of the ROIs to the normal tissue of the reconstructed images was examined to realize the degradations of the qualities of the images. The preliminary results show that no obvious degradation of the image quality was observed with increasing scan speed, possibly due to the advanced designs for the hardware and software of the system. It implies that higher speed (15 cm/s) than that of the commercialized tomosynthesis system (12 cm/s) for the proposed system is achieved, and therefore a complete chest scan within 10 seconds is expected.

Keywords: chest radiography, digital tomosynthesis, image quality, scan speed

Procedia PDF Downloads 332

Authors: Stephanie Liu Lu

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With the proliferation of artificial intelligence tools in the field of education, it is crucial to explore their impact on language learning outcomes. This paper examines the use of AI tools, such as ChatGPT, in practical writing within business Chinese teaching to investigate how AI can enhance practical writing skills and teaching effectiveness. The study involved third and fourth-year university students majoring in accounting and finance from a university in Hong Kong within the context of a business correspondence writing class. Students were randomly assigned to a control group, who completed business letter writing independently, and an experimental group, who completed the writing with the assistance of AI. In the latter, the AI-assisted business letters were initially drafted by the students issuing commands and interacting with the AI tool, followed by the students' revisions of the draft. The paper assesses the performance of both groups in terms of grammatical expression, communicative effect, and situational awareness. Additionally, the study collected dialogue texts from interactions between students and the AI tool to explore factors that affect text generation and the potential impact of AI on enhancing students' communicative and identity awareness. By collecting and comparing textual performances, it was found that students assisted by AI showed better situational awareness, as well as more skilled organization and grammar. However, the research also revealed that AI-generated articles frequently lacked a proper balance of identity and writing purpose due to limitations in students' communicative awareness and expression during the instruction and interaction process. Furthermore, the revision of drafts also tested the students' linguistic foundation, logical thinking abilities, and practical workplace experience. Therefore, integrating AI tools and related teaching into the curriculum is key to the future of business Chinese teaching.

Keywords: AI-assistance, business Chinese, textual analysis, language education

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Authors: Milagros S. Salibad, Levita B. Grana

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The presence and role of Indigenous Peoples (IPs) residing in key biodiversity, protected, and watershed areas within the ancestral domain in the Caraga region, Mindanao, Philippines, hold immense significance. Recognizing their importance and rights, this study aimed to determine the level of biodiversity conservation practices and extent of environmental stewardship among the Mamanwas, Manobos, and Higaonons, assess potential differences in these practices, and identify factors that facilitate or hinder them. Employing an explanatory sequential mixed-method research design, 421 respondents participated through a researcher-made questionnaire. Additional data were collected through focus group discussions, key informant interviews, researcher field notes, community immersions, and secondary sources. The results revealed a high level of biodiversity conservation practices across the three IP groups, with variations influenced by their cultural and traditional practices, awareness, and access to resources and information. Each group exhibited unique environmental practices shaped by their distinct cultures, traditions, and customary knowledge. They have a strong sense of ownership and responsibility towards their ancestral lands and territories and adopt traditional knowledge and practices that promote sustainable resource management and biodiversity conservation. These practices align with the Indigenous Peoples Rights Act (IPRA), also known as Republic Act No. 8371. Various facilitating and hindering factors influenced their conservation efforts. To uphold the region's biodiversity resources, it is recommended that government agencies continue to evaluate and monitor the sustainability of IPs' local biodiversity conservation practices. Additionally, efforts should be made to involve IP communities as essential contributors and stakeholders in these conservation endeavors.

Keywords: biodiversity, conservation, indigenous peoples, traditional knowledge, environmental stewardship

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Authors: Pradakshina Sharma, Jagriti Narang

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Due to the critical significance in the early identification of infectious diseases, electrochemical sensors have garnered considerable interest. Here, we develop a detection platform for the chikungunya virus by rationally implementing the extremely high charge-transfer efficiency of a ternary nanocomposite of graphene oxide, silver, and gold (G/Ag/Au) (CHIKV). Because paper is an inexpensive substrate and can be produced in large quantities, the use of electrochemical paper analytical device (EPAD) origami further enhances the sensor's appealing qualities. A cost-effective platform for point-of-care diagnostics is provided by paper-based testing. These types of sensors are referred to as eco-designed analytical tools due to their efficient production, usage of the eco-friendly substrate, and potential to reduce waste management after measuring by incinerating the sensor. In this research, the paper's foldability property has been used to develop and create 3D multifaceted biosensors that can specifically detect the CHIKVX-ray diffraction, scanning electron microscopy, UV-vis spectroscopy, and transmission electron microscopy (TEM) were used to characterize the produced nanoparticles. In this work, aptamers are used since they are thought to be a unique and sensitive tool for use in rapid diagnostic methods. Cyclic voltammetry (CV) and linear sweep voltammetry (LSV), which were both validated with a potentiostat, were used to measure the analytical response of the biosensor. The target CHIKV antigen was hybridized with using the aptamer-modified electrode as a signal modulation platform, and its presence was determined by a decline in the current produced by its interaction with an anionic mediator, Methylene Blue (MB). Additionally, a detection limit of 1ng/ml and a broad linear range of 1ng/ml-10µg/ml for the CHIKV antigen were reported.

Keywords: biosensors, ePAD, arboviral infections, point of care

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Alison Brown

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Through stories, children make sense of their world, see themselves through the eyes of another, and process emotions and lived experiences in a non-threatening and indirect manner. Building on research around the use of narrative techniques with adults and families, this research looked directly at the use of narratives as a therapeutic technique with children in counseling. Based on individual therapy sessions with children over a six-year period, this work of collective case studies tells the story of a practice incorporating children’s narratives, of children’s experiences in writing and sharing their narratives, and of the clinical impact of the use of narratives with children. Not all stories were narratives of success or happiness. Children documented their fears and anger as well as their achievements and hope for the future. What emerged through this study was an awareness of recurring themes in the way children responded to the narrative process and in the benefits and limitations of story writing with children. Consistent with previous studies focusing on narrative work with adults and families, the use of narratives with children provided opportunities for healing, acceptance, developing greater understanding, externalizing, and re-authoring a preferred future. In terms of the children’s experiences in writing and sharing their narratives, consistent themes emerged again, with many children finding the experience cathartic and liberating, empowering and hopeful, but most importantly, an opportunity that allowed them to feel and understand that they were not alone. Whilst a small collection of case studies tells the stories of a limited number of children, it is hoped that this research provides both a model and inspiration for others to explore similar uses of narratives with children. As a greater number of children’s narratives are created, the potential to share and benefit from the many rich stories and experiences of other children becomes more of a reality. Across cultures, economic and social settings, rural and urban environments, and varying family structures, it is important that we hear the voices of our children – ‘In their own words’.

Keywords: narrative therapy children counselling, social, emotional, zone of proximal development, scaffolding

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Authors: Hien Thi Dieu Truong, Mahmoud Al-Sarayreh, Pullanagari Reddy, Marlon M. Reis, Richard Archer

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New Zealand mānuka honey is a honeybee product derived mainly from Leptospermum scoparium nectar. The potent antibacterial activity of mānuka honey derives principally from methylglyoxal (MGO), in addition to the hydrogen peroxide and other lesser activities present in all honey. MGO is formed from dihydroxyacetone (DHA) unique to L. scoparium nectar. Mānuka honey also has an idiosyncratic phenolic profile that is useful as a chemical maker. Authentic mānuka honey is highly valuable, but almost all honey is formed from natural mixtures of nectars harvested by a hive over a time period. Once diluted by other nectars, mānuka honey irrevocably loses value. We aimed to apply hyperspectral imaging to honey frames before bulk extraction to minimise the dilution of genuine mānuka by other honey and ensure authenticity at the source. This technology is non-destructive and suitable for an industrial setting. Chemometrics using linear Partial Least Squares (PLS) and Support Vector Machine (SVM) showed limited efficacy in interpreting chemical footprints due to large non-linear relationships between predictor and predictand in a large sample set, likely due to honey quality variability across geographic regions. Therefore, an advanced modelling approach, one-dimensional convolutional neural networks (1D-CNN), was investigated for analysing hyperspectral data for extraction of biochemical information from honey. The 1D-CNN model showed superior prediction of honey quality (R² = 0.73, RMSE = 2.346, RPD= 2.56) to PLS (R² = 0.66, RMSE = 2.607, RPD= 1.91) and SVM (R² = 0.67, RMSE = 2.559, RPD=1.98). Classification of mono-floral manuka honey from multi-floral and non-manuka honey exceeded 90% accuracy for all models tried. Overall, this study reveals the potential of HSI and deep learning modelling for automating the evaluation of honey quality in frames.

Keywords: mānuka honey, quality, purity, potency, deep learning, 1D-CNN, chemometrics

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Authors: Shu-Lien Chou, Chung-Feng Liu

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Self-health management of chronic illnesses plays an important part in chronic illness treatments. However, various kinds of health information (health education materials) which government or healthcare institutions provide for patients may not achieve the expected outcome. One of the critical reasons affecting patients’ use intention could be patients’ perceived Information overload regarding the health information. This study proposed an extended model of Theory of Planned Behavior, which integrating perceived information overload as another construct to explore patients’ use intention of the health information for self-health management. The independent variables are attitude, subject norm, perceived behavior control and perceived information overload while the dependent variable is behavior intention to use the health information. The cross-sectional study used a structured questionnaire for data collection, focusing on the chronic patients with coronary artery disease (CAD), who are the potential users of the health information, in a medical center in Taiwan. Data were analyzed using descriptive statistics of the basic information distribution of the questionnaire respondents, and the Partial Least Squares (PLS) structural equation model to study the reliability and construct validity for testing our hypotheses. A total of 110 patients were enrolled in this study and 106 valid questionnaires were collected. The PLS analysis result indicates that the patients’ perceived information overload of health information contributes the most critical factor influencing the behavioral intention. Subjective norm and perceived behavioral control of TPB constructs had significant effects on patients’ intentions to use health information also, whereas the attitude construct did not. This study demonstrated a comprehensive framework, which extending perceived information overload into TPB model to predict patients’ behavioral intention of using heath information. We expect that the results of this study will provide useful insights for studying health information from the perspectives of academia, governments, and healthcare providers.

Keywords: chronic patients, health information, information overload, theory of planned behavior

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Authors: A. Ghribi, M. Bagane

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The discharge of dye in industrial effluents is of great concern because their presence and accumulation have a toxic or carcinogenic effect on living species. The removal of such compounds at such low levels is a difficult problem. The adsorption process is an effective and attractive proposition for the treatment of dye contaminated wastewater. Activated carbon adsorption in fixed beds is a very common technology in the treatment of water and especially in processes of decolouration. However, it is expensive and the powdered one is difficult to be separated from aquatic system when it becomes exhausted or the effluent reaches the maximum allowable discharge level. The regeneration of exhausted activated carbon by chemical and thermal procedure is also expensive and results in loss of the sorbent. The focus of this research was to evaluate the adsorption potential of the raw clay in removing rhodamine B from aqueous solutions using a laboratory fixed-bed column. The continuous sorption process was conducted in this study in order to simulate industrial conditions. The effect of process parameters, such as inlet flow rate, adsorbent bed height, and initial adsorbate concentration on the shape of breakthrough curves was investigated. A glass column with an internal diameter of 1.5 cm and height of 30 cm was used as a fixed-bed column. The pH of feed solution was set at 8.5. Experiments were carried out at different bed heights (5 - 20 cm), influent flow rates (1.6- 8 mL/min) and influent rhodamine B concentrations (20 - 80 mg/L). The obtained results showed that the adsorption capacity increases with the bed depth and the initial concentration and it decreases at higher flow rate. The column regeneration was possible for four adsorption–desorption cycles. The clay column study states the value of the excellent adsorption capacity for the removal of rhodamine B from aqueous solution. Uptake of rhodamine B through a fixed-bed column was dependent on the bed depth, influent rhodamine B concentration, and flow rate.

Keywords: adsorption, breakthrough curve, clay, fixed bed column, rhodamine b, regeneration

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Authors: Catherine Mangan, Beth Anderson

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There has been a significant drive to use online or hybrid learning in Higher Education (HE) over recent years. HEs with a virtual presence offer their communities a range of benefits, including the potential for greater inclusivity, diversity, and collaboration; more flexible learning packages; and more engaging, dynamic content. Institutions can also experience significant challenges when seeking to extend learning spaces in this way, as can learners themselves. For example, staff members’ and learners’ digital literacy varies (as do their perceptions of technologies in use), and there can be confusion about optimal approaches to implementation. Furthermore, the speed with which HE institutions have needed to shift to fully online or hybrid models, owing to the COVID19 pandemic, has highlighted the significant barriers to successful implementation. HE environments have been shown to predict a range of organisational, academic, and experiential outcomes, both positive and negative. Much research has focused on the social aspect of virtual platforms, as well as the nature and effectiveness of the technologies themselves. There remains, however, a relative paucity of synthesised knowledge on the psychology of learners’ relationships with their institutions; specifically, how individual difference and interpersonal factors predict students’ ability and willingness to engage with novel virtual learning spaces. Accordingly, extending learning spaces remains challenging for institutions, and wholly remote courses, in particular, can experience high attrition rates. Focusing on the last five years, this pragmatic review summarises evidence from the psychological and pedagogical literature. In particular, the review highlights the importance of addressing the psychological and relational complexities of students’ shift from offline to online engagement. In doing so, it identifies considerations for HE institutions looking to deliver in this way.

Keywords: higher education, individual differences, interpersonal relationships, online learning, virtual environment

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Authors: Surajit Das Barman, Rakibuzzaman Shah, Apurv Kumar

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Bushfire is known as one of the ascendant factors to create pyrocumulus thundercloud that causes the ignition of new fires by pyrocumulonimbus (pyroCb) lightning strikes and creates major losses of lives and property worldwide. A conceptual model-based risk planning would be beneficial to predict the lightning striking zones on the surface of the earth underneath the pyroCb thundercloud. PyroCb thundercloud can generate both positive cloud-to-ground (+CG) and negative cloud-to-ground (-CG) lightning in which +CG tends to ignite more bushfires and cause massive damage to nature and infrastructure. In this paper, a simple line charge structured thundercloud model is constructed in 2-D coordinates using the method of image charge to predict the probable +CG lightning striking zones on the earth’s surface for two conceptual thundercloud charge configurations: titled dipole and conventional tripole structure with excessive lower positive charge regions that lead to producing +CG lightning. The electric potential and surface charge density along the earth’s surface for both structures via continuously adjusting the position and the charge density of their charge regions is investigated. Simulation results for tilted dipole structure confirm the down-shear extension of the upper positive charge region in the direction of the cloud’s forward flank by 4 to 8 km, resulting in negative surface density, and would expect +CG lightning to strike within 7.8 km to 20 km around the earth periphery in the direction of the cloud’s forward flank. On the other hand, the conceptual tripole charge structure with enhanced lower positive charge region develops negative surface charge density on the earth’s surface in the range |x| < 6.5 km beneath the thundercloud and highly favors producing +CG lightning strikes.

Keywords: pyrocumulonimbus, cloud-to-ground lightning, charge structure, surface charge density, forward flank

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Pradeep Raj Sharma, Bogeun Jang, Jongill Hong

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Spin-orbit torque (SOT) is an efficient approach for manipulating the magnetization of ferromagnetic materials (FMs), providing improved device performance, better compatibility, and ultra-fast switching with lower power consumption compared to spin-transfer torque (STT). Among the various materials and structural designs, two-dimensional (2D) van-der Waals (vdW) layered materials and their heterostructures have been demonstrated as highly scalable and promising device architecture for SOT. In particular, a bilayer heterostructure consisting of fully 2D-vdW-FM, non-magnetic material (NM) offers a potential platform for controlling the magnetization using SOT because of the advantages of being easy to scale and less energy to switch. Here, we report filed-free deterministic switching driven by SOT at room temperature, integrating perpendicularly magnetized 2D-vdW material Fe₃GaTe₂ (FGaT) and NM WTe₂. Pulse current-induced magnetization switching with an ultra-low current density of about 6.5×10⁵ A/cm², yielding a SOT efficiency close to double-digits at 300 K, is reported. These values are two orders of magnitude higher than those observed in conventional heavy metal (HM) based SOT and exceed those reported with 2D-vdW layered materials. WTe₂, a topological semimetal possessing strong SOC and high spin Hall angle, can induce significant spin accumulation with negligible spin loss across the transparent 2D bilayer heterointerface. This promising device architecture enables highly compatible, energy-efficient, non-volatile memory and lays the foundation for designing efficient, flexible, and miniaturized spintronic devices.

Keywords: spintronics, spin-orbit torque, spin Hall effect, spin Hall angle, topological semimetal, perpendicular magnetic anisotropy

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Authors: Hamida Memon, Muhammad Sanan

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A 34-year-old male with no prior health issues presented with a wound in his left leg exhibiting active pus discharge, intense inflammation, pain radiating from the buttocks to the knee, foot drop, and skin darkening. Four years prior, he sustained an untreated dislocation of the hip joint and acetabulum from a road traffic accident. Initial nerve conduction studies (NCS) and electromyography (EMG) revealed severe axonotomesis of the left sciatic nerve and reduced compound muscle action potential in the left common peroneal nerve. Despite normal venous flow, edema and cellulitis were noted. Follow-up NCS/EMG in 2022 showed improvement, but in 2023, the patient experienced recurrent infection and underwent surgical intervention with tissue culture. Postoperative care included antibiotics and pain management. NCS/EMG in 2024 indicated decreased nerve amplitudes and conduction velocities, consistent with moderate axonotmesis and ongoing recovery, alongside incidental right S1 radiculopathy. General lab tests and abdominal imaging were normal. The patient was treated with Pregabalin and Neurobion for neuropathic pain and nerve support and is currently under observation by a tertiary sector hospital for treatment. This case underscores the critical importance of prompt treatment for hip dislocations to prevent long-term complications such as neuropathy and avascular necrosis. Delays in treatment significantly increase the risk of severe outcomes, highlighting the need for timely intervention. Overall, the case illustrates the challenges of managing complex nerve injuries and the importance of comprehensive care for optimal recovery.

Keywords: sciatic nerve neuropathy, hip dislocation, acetabular fracture, radiculopathy

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Authors: Samuel Abraham Berhane, Lingbing Bu

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This paper presents the spatiotemporal variability of aerosols, clouds, and precipitation within the major cities in Eritrea and it investigates the relationship between aerosols, clouds, and precipitation concerning the presence of aerosols over the study region. In Eritrea, inadequate water supplies will have both direct and indirect adverse impacts on sustainable development in areas such as health, agriculture, energy, communication, and transport. Besides, there exists a gap in the knowledge on suitable and potential areas for cloud seeding. Further, the inadequate understanding of aerosol-cloud-precipitation (ACP) interactions limits the success of weather modification aimed at improving freshwater sources, storage, and recycling. Spatiotemporal variability of aerosols, clouds, and precipitation involve spatial and time series analysis based on trend and anomaly analysis. To find the relationship between aerosols and clouds, a correlation coefficient is used. The spatiotemporal analysis showed larger variations of aerosols within the last two decades, especially in Assab, indicating that aerosol optical depth (AOD) has increased over the surrounding Red Sea region. Rainfall was significantly low but AOD was significantly high during the 2011 monsoon season. Precipitation was high during 2007 over most parts of Eritrea. The correlation coefficient between AOD and rainfall was negative over Asmara and Nakfa. Cloud effective radius (CER) and cloud optical thickness (COT) exhibited a negative correlation with AOD over Nakfa within the June–July–August (JJA) season. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model that is used to find the path and origin of the air mass of the study region showed that the majority of aerosols made their way to the study region via the westerly and the southwesterly winds.

Keywords: aerosol-cloud-precipitation, aerosol optical depth, cloud effective radius, cloud optical thickness, HYSPLIT

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Authors: M. A. Wijewardane, S. A. N. C. Sudasinghe, H. K. G. Punchihewa, W. K. D. L. Wickramasinghe, S. A. Philip, M. R. S. U. Kumara

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Visual comfort is one of the major parameters that can be taken to measure the human comfort in any environment. If the provided illuminance level in a working environment does not meet the workers visual comfort, it will lead to eye-strain, fatigue, headache, stress, accidents and finally, poor productivity. However, improvements in lighting do not necessarily mean that the workplace requires more light. Unnecessarily higher illuminance levels will also cause poor visual comfort and health risks. In addition, more power consumption on lighting will also result in higher energy costs. So, during this study, visual comfort and the illuminance requirement for the workers in textile/apparel industry were studied to perform different tasks (i.e. cutting, sewing and knitting) at their workplace. Experimental studies were designed to identify the optimum illuminance requirement depending upon the varied fabric colour and type and finally, energy saving potentials due to controlled illuminance level depending on the workforce requirement were analysed. Visual performance of workers during the sewing operation was studied using the ‘landolt ring experiment’. It was revealed that around 36.3% of the workers would like to work if the illuminance level varies from 601 lux to 850 lux illuminance level and 45.9% of the workers are not happy to work if the illuminance level reduces less than 600 lux and greater than 850 lux. Moreover, more than 65% of the workers who do not satisfy with the existing illuminance levels of the production floors suggested that they have headache, eye diseases, or both diseases due to poor visual comfort. In addition, findings of the energy analysis revealed that the energy-saving potential of 5%, 10%, 24%, 8% and 16% can be anticipated for fabric colours, red, blue, yellow, black and white respectively, when the 800 lux is the prevailing illuminance level for sewing operation.

Keywords: Landolt Ring experiment, lighting energy consumption, illuminance, textile and apparel industry, visual comfort

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Authors: Cho Achidi

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Tomato is a crucial food crop significantly contributes to global food and nutrition security. However, postharvest losses severely limit its role. Therefore, it is necessary to develop sustainable strategies to minimize these losses and improve the shelf-life of tomato fruits. One of the major concerns is bacterial infections, particularly by faecal coliform bacteria, which can cause food poisoning and illnesses like diarrhoea and dysentery. This study seeks to identify the presence of coliform bacteria on tomato fruits in fields and markets in Muea, Buea Municipality. The study also evaluated different management strategies to reduce the bacterial incidence and load on tomato fruits. A total of 200 fruits were sampled for both the coliform survey and shelf-life analysis. Ten farmers and traders provided samples, including asymptomatic and symptomatic tomato fruits. The samples designated for shelf-life analysis were treated with Aquatab, warm water, lemon, and onion. The results indicated that out of the 80 symptomatic samples collected, 12.5% contained faecal and total coliform species. Among the ten farms sampled, 14% were infected with coliform bacteria, with the highest infestation rate of 60% recorded in field 4. Furthermore, 15% of the asymptomatic tomato fruits were found to be infected by coliform bacteria. Regarding the management strategies, Aquatabs exhibited the highest efficacy in reducing the incidence of coliform bacteria on tomato fruits, followed by onion and lemon extracts. Although hot water treatment effectively removed bacteria from the fruits, damaging the cell wall negatively affected their shelf-life. Overall, this study emphasizes the severity of coliform bacterial pathogens in the Muea area, particularly their occurrence on asymptomatic tomatoes, which poses a significant concern for plant quarantine services. It also demonstrates potential options for mitigating this bacterial challenge.

Keywords: tomato, shelf-life analysis, food and nutrition security, coliform bbacteria

Procedia PDF Downloads 67

Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

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Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The RMSE between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

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Authors: Nuhu Mohammed Gali, Kenichi Matsui

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Climate change poses a significant threat to agriculture and food security in Africa. The UNFCC recognized the need to address climate change adaptation in the broader context of sustainable development. African countries have initiated a governance system for adapting and responding to climate change in their Nationally Determined Contributions (NDCs). Despite the implementation limitations, Africa’s adaptation initiatives highlight the need to strengthen and expand adaptation responses. This paper looks at the extent to which South-South cooperation facilitates the implementation of adaptation actions between nations for agriculture and sustainable development. We conducted a literature review and content analysis of reports prepared by international organizations, reflecting the diversity of adaptation activities taking place in Sub-Saharan Africa. Our analysis of the connection between adaptation and nationally determined contributions (NDCs) showed that climate actions are mainstreamed into sustainable development. The NDCs in many countries on climate change adaptation action for agriculture aimed to strengthen the resilience of the poor. We found that climate-smart agriculture is the core of many countries target to end hunger. We revealed that South-South Cooperation, in terms of capacity, technology, and financial support, can help countries to achieve their climate action priorities and the Sustainable Development Goals (SDGs). We found that inadequate policy and regulatory frameworks between countries, differences in development priorities and strategies, poor communication, inadequate coordination, and the lack of local engagement and advocacy are some key barriers to South-South Cooperation in Africa. We recommend a multi-dimensional partnership, provisionoffinancialresources, systemic approach for coordination and engagement to promote and achieve the potential of SSC in Africa.

Keywords: climate change, adaptation, food security, sustainable development goals

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Authors: Yutong Xu, Wanting Zhang, Jia Wang, Zihan Guo, Weiguang Ma

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Background: The resilience education of intern nursing students has significant implications for the development and improvement of the nursing workforce. The clinical internship period is a critical time for enhancing resilience. Aims: To evaluate the resilience level of Chinese nursing interns and identify the factors affecting resilience early in their careers. Methods: The cross-sectional study design was adopted. From March 2022 to May 2023, 512 nursing interns in tertiary care hospitals were surveyed online with the Connor-Davidson Resilience Scale, the Clinical Learning Environment scale for Nurse, and the Career Adapt-Abilities Scale. Structural equation modeling was used to clarify the relationships among these factors. Indirect effects were tested using bootstrapped Confidence Intervals. Results: The nursing interns showed a moderately high level of resilience[M(SD)=70.15(19.90)]. Gender, scholastic attainment, had a scholarship, career adaptability and clinical learning environment were influencing factors of nursing interns’ resilience. Career adaptability and clinical learning environment positively and directly affected their resilience level (β = 0.58, 0.12, respectively, p＜0.01). career adaptability also positively affected career adaptability (β = 0.26, p < 0.01), and played a fully mediating role in the relationship between clinical learning environment and resilience. Conclusion: Career adaptability can enhance the influence of clinical learning environment on resilience. The promotion of career adaptability and the clinical teaching environment should be the potential strategies for nursing interns to improve their resilience, especially for those female nursing interns with low academic performance. Implications for Nursing Educators Nursing educators should pay attention to the cultivation of nursing students' resilience; for example, by helping them integrate to the clinical learning environment and improving their career adaptability. Reporting Method: The STROBE criteria were used to report the results of the observations critically. Patient or Public Contribution No patient or public contribution.

Keywords: resilience, clinical learning environment, career adaptability, nursing interns

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