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This study aims to evaluate the effect of sucrose replacer mixtures (erythritol, mannitol, or tagatose in combination with inulin or polydextrose) on the crystal morphology, particle size distribution, rheology, melting properties, and fat polymorphism of dark compound chocolate. The result showed that the replacer mixture's hygroscopicity, particle size, and sugar crystal shape might significantly impact dark compound chocolate's rheological and textural properties but had no substantial impact on the melting properties and fat crystallization. Mannitol-containing samples exhibited the highest rheological value, likely related to their high moisture content, small particle size, and elongated crystal shape. Due to the similar specific surface area and comparable D90 value, the sample containing erythritol-polydextrose mixture resulted in a similar (P ≥ 0.05) Casson yield value (46.184 ± 2.45 Pa) compared to the sample containing sucrose (38.348 ± 1.68 Pa). It could be a potential sucrose replacer in the dark compound chocolate. © 2023 Monash University Malaysia

Background: Severe cutaneous adverse reactions (SCAR) are a group of delayed presumed T-cell mediated hypersensitivities associated with significant morbidity and mortality. Despite their shared global healthcare burden and impact, the clinical phenotypes, genomic predisposition, drug causality, and treatment outcomes may vary. We describe the establishment and results from the first Australasian registry for SCAR (AUS-SCAR), that via a collaborative network advances strategies for the prevention, diagnosis and treatment of SCAR. Methods: Prospective multi-center registry of SCAR in Australian adult and adolescents, with planned regional expansion. The registry collects externally verified phenotypic data drug causality, therapeutics and long-term patient outcomes. In addition, biorepository specimens and DNA are collected at participating sites. Results: we report on the first 100 patients enrolled in the AUS-SCAR database. DRESS (50%) is the most predominant phenotype followed by SJS/TEN (39%) and AGEP (10%), with median age of 52 years old (IQR 37.5, 66) with 1:1 male-to-female ratio. The median latency for all implicated drugs is highly variable but similar for DRESS (median 15 days IQR 5,25) and SJS/TEN (median 21 days, IQR 7,27), while lowest for AGEP (median 2.5 days, IQR 1,8). Antibiotics (54.5%) are more commonly listed as primary implicated drug compare with non-antibiotics agent (45.5%). Mortality rate at 90 days was highest in SJS/TEN at 23.1%, followed by DRESS (4%) and AGEP (0%). Conclusion: In the first prospective national phenotypic and biorepository of SCAR in the southern hemisphere we demonstrate notable differences to other reported registries; including DRESS-predominant phenotype, varied antibiotic causality and low overall mortality rate. This study also highlights the lack of standardised preventative pharmacogenomic measures and in vitro/in vivo diagnostic strategies to ascertain drug causality. Trial registration: ANZCTR ACTRN1261900024113

Reliable estimates of vocabulary knowledge offer useful information for planning and improving language learning. However, problems arise when existing vocabulary measures signal a lack of validation evidence, and they are predominantly used for instructional purposes. Therefore, this study addresses the gap by providing a description of the development of a valid and reliable instrument for research and evaluation. Adhering to Read and Chapelle’s (2001) framework for vocabulary assessment, the instrument was created using resources which were closely related to the research subject and context to enhance the validity and reliability. Results indicated that the instrument was valid, reliable and sensitive to different vocabulary instructions. This study not only presents validation evidence which is consistent with current educational measurement theory, but also encourages language teachers and researchers to become vocabulary assessment literate to assure the psychometric qualities of the instrument they develop., Unas estimaciones fiables del conocimiento del vocabulario ofrecen información útil para planificar y mejorar el aprendizaje de idiomas. No obstante, los problemas surgen cuando las medidas del vocabulario actuales señalan una falta de evidencia de validación y se utilizan predominantemente con fines educativos. Por tanto, este trabajo aborda la cuestión facilitando una descripción del desarrollo de un instrumento válido y fiable para la investigación y la evaluación. Siguiendo el marco para la evaluación del vocabulario de Read y Chapelle (2001), el instrumento se creó utilizando recursos relacionados estrechamente con el sujeto y el contexto de investigación para mejorar la validez y fiabilidad. Los resultados indicaron que el instrumento era válido, y sensible a diferentes instrucciones de vocabulario. Este trabajo no solo presenta una evidencia de validación que es consistente con la teoría de la medición educativa actual, sino también anima a los profesores e investigadores de idiomas a que se familiaricen con la evaluación del vocabulario para asegurar las cualidades psicométricas del instrumento que desarrollan.

Afforestation is of international interest for its positive benefits on carbon storage, ecology, and society, but its impacts on terrestrial and atmospheric processes are still poorly understood. This study presents the first use of a coupled land surface and convection permitting atmospheric model (CPM) to quantify hydrometeorological effects of afforestation across the United Kingdom, focusing on atmospheric processes often missing in hydrological models. Generating a scenario of 93 000 km2 (40%) additional woodland across the UK, the periods of 2042-2052 and 2062-2072 are analyzed. Simulated afforestation alters seasonal and regional UK hydrometeorology. Countrywide runoff increases in all seasons (between 5.4-11 mm and 4.3-8.6% per season) due to elevated subsurface flows from greater soil moisture. Evaporation decreases in summer (-20.6 mm, -10%) but increases in winter (8.1 mm, 15%) whereas rainfall increases throughout all seasons (between 2.2-6.86 mm and 0.9-2.2% per season). Greater winter rainfall is detected along Great Britain's west coastline as increased surface roughness produces prolonged and heavier rainfall. In the summer, higher albedo increases potential evapotranspiration and reduces near surface specific humidity: water is locked in deeper soil layers as transpiration diminishes and the topsoil dries out. However, the magnitude of hydrometeorological change due to altered land cover is smaller than the uncertainty in local climate change projections. This work sets a precedent in illustrating the impacts of afforestation on hydrology using a high-resolution CPM and highlights the importance of coupled hydrometeorological processes when investigating land cover impacts on hydrological processes.

Following the significant achievements of large language models (LLMs), researchers have employed in-context learning for text classification tasks. However, these studies focused on monolingual, single-turn classification tasks. In this paper, we introduce LARA (Linguistic-Adaptive Retrieval-Augmented Language Models), designed to enhance accuracy in multi-turn classification tasks across six languages, accommodating numerous intents in chatbot interactions. Multi-turn intent classification is notably challenging due to the complexity and evolving nature of conversational contexts. LARA tackles these issues by combining a fine-tuned smaller model with a retrieval-augmented mechanism, integrated within the architecture of LLMs. This integration allows LARA to dynamically utilize past dialogues and relevant intents, thereby improving the understanding of the context. Furthermore, our adaptive retrieval techniques bolster the cross-lingual capabilities of LLMs without extensive retraining and fine-tune. Comprehensive experiments demonstrate that LARA achieves state-of-the-art performance on multi-turn intent classification tasks, enhancing the average accuracy by 3.67% compared to existing methods.

Zero-shot open-ended inference on untrimmed videos poses a significant challenge, especially when no annotated data is utilized to navigate the inference direction. In this work, we aim to address this underexplored domain by introducing an adaptable framework that efficiently combines both the frozen vision-language (VL) model and off-the-shelf large language model (LLM) for conducting zero-shot open-ended inference tasks without requiring any additional training or fine-tuning. Our comprehensive experiments span various video action datasets for goal inference and action recognition tasks. The results demonstrate the framework's superior performance in goal inference compared to conventional vision-language models in open-ended and close-ended scenarios. Notably, the proposed framework exhibits the capability to generalize effectively to action recognition tasks, underscoring its versatility and potential contributions to advancing the video-based zero-shot understanding.

Introduction: One of the key staple foods in many different countries, including Malaysia, is rice (Oryzae sativa L.). Pesticides are used to reduce weed growth and safeguard crops from insect attacks in order to boost paddy output. Objective: This research quantifies the concentration of pymetrozine, chlorantraniliprole, and difenoconazole, along with any potential health risks to consumers. Methods: Samples of polished rice from three rice milling factories in Tanjung Karang and Sekinchan were extracted using the QuEChERS (Quick Easy Cheap Effective Rugged Safe) technique. The amount of pesticide residue in polished rice was then measured using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). A health risk assessment was conducted utilizing the Hazard Quotient (HQ) and Lifetime Cancer Risk (LCR) to estimate the non-carcinogenic and carcinogenic health risks. Results: The mean concentration of pesticides in polished rice ranged from less than the detection limit (difenoconazole) to 1.122 µg/kg (pymetrozine). No rice samples above the Maximum Residue Limit (MRL) specified in the Food Act 1983 as implemented by Malaysia’s Food Regulations 1985. Pymetrozine, chlorantraniliprole, and difenoconazole in rice had respective MRLs of 50 µg/kg, 2000 µg/kg, and 100 µg/kg. For all age groups, no significant non-carcinogenic health risk was associated with consuming polished rice from the study area, where the HQ and Hazard Index (HI) were less than one. When LCR values were less than 10-6, carcinogenic health risks of consuming polished rice from the study area were at a clearly acceptable risk level. Conclusion: As no sample exceeded the MRL, the findings indicated that all rice samples collected from Tanjung Karang and Sekinchan were safe for consumption.

Introduction: One of the key staple foods in many different countries, including Malaysia, is rice (Oryzae sativa L.). Pesticides are used to reduce weed growth and safeguard crops from insect attacks in order to boost paddy output. Objective: This research quantifies the concentration of pymetrozine, chlorantraniliprole, and difenoconazole, along with any potential health risks to consumers. Methods: Samples of polished rice from three rice milling factories in Tanjung Karang and Sekinchan were extracted using the QuEChERS (Quick Easy Cheap Effective Rugged Safe) technique. The amount of pesticide residue in polished rice was then measured using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). A health risk assessment was conducted utilizing the Hazard Quotient (HQ) and Lifetime Cancer Risk (LCR) to estimate the non-carcinogenic and carcinogenic health risks. Results: The mean concentration of pesticides in polished rice ranged from less than the detection limit (difenoconazole) to 1.122 µg/kg (pymetrozine). No rice samples above the Maximum Residue Limit (MRL) specified in the Food Act 1983 as implemented by Malaysia’s Food Regulations 1985. Pymetrozine, chlorantraniliprole, and difenoconazole in rice had respective MRLs of 50 µg/kg, 2000 µg/kg, and 100 µg/kg. For all age groups, no significant non-carcinogenic health risk was associated with consuming polished rice from the study area, where the HQ and Hazard Index (HI) were less than one. When LCR values were less than 10-6, carcinogenic health risks of consuming polished rice from the study area were at a clearly acceptable risk level. Conclusion: As no sample exceeded the MRL, the findings indicated that all rice samples collected from Tanjung Karang and Sekinchan were safe for consumption.

Distraction disrupts Working Memory (WM) performance, but how the brain filters distraction is not known. One possibility is that neural activity associated with distractions is suppressed relative to a baseline/passive task (biased competition). Alternatively, distraction may be denied access to WM, with no suppression. Furthermore, behavioural work indicates separate mechanisms for ignoring distractions which occur (1) while we put information into WM (Encoding Distraction, ED) and (2) while we maintain already encoded information during the WM delay period (Delay Distraction, DD). Here we used fMRI in humans to measure category-sensitive cortical activity and probe the extent to which ED/DD mechanisms involve enhancement/suppression during a WM task. We observed significant enhancement of task-relevant activity, relative to a passive view task, which did not differ according to whether or when distractors appeared. For both ED and DD we found no evidence of suppression, but instead a robust increase in stimulus specific activity in response to additional stimuli presented during the passive view task, which was not seen for the WM task, when those additional stimuli were to be ignored. The results indicate that ED/DD resistance does not necessarily involve suppression of distractor-related activity. Rather, a rise in distractor-associated activity is prevented when distractors are presented, supporting models of input gating, and providing a potential mechanism by which input-gating might be achieved.

Tumor-inducing (Ti) plasmid is the requisite for Agrobacterium-mediated plant transformation. Over decades, continuous efforts have been made to improve the efficiency of Agrobacterium-mediated plant transformation and most of them focused on the binary vector system. A binary vector system comprises of a binary vector of which transferred DNA (T-DNA) resided on and a Ti plasmid to carry those essential virulence genes. In this study, we constructed a miniaturized helper Ti plasmid, designated as pYL102, with the aim to enhance the overall Agrobacterium-mediated transformation rate. The size of pYL102 was reduced to ~60% of the original plasmid pCAMBIA5105. Subsequently, pYL102 was coupled with the broad host range (BHR) bacterial expression vector, pYL101C, of which the key regulatory virulence gene, virG-N54D, was cloned in and expressed under the control of a strong constitutive PINTc promoter. To test the functionality of the constructed vector system, A. tumefaciens C58C1 carrying pYL102, pYL101C::virG-N54D and the transformation vector pGWB2::e35S-sfGFP was used to transform Nicotiana benthamiana leaves by agroinfiltration. Green fluorescence was observed in spots infiltrated with Agrobacterium carrying the test plasmids. The fluorescence intensity from the test agroinfiltrated leaves was significantly higher than those of the mock-infiltrated leaves (p<0.01), indicating the vector system can be used for plant transformation.

Tumor-inducing (Ti) plasmid is the requisite for Agrobacterium-mediated plant transformation. Over decades, continuous efforts have been made to improve the efficiency of Agrobacterium-mediated plant transformation and most of them focused on the binary vector system. A binary vector system comprises of a binary vector of which transferred DNA (T-DNA) resided on and a Ti plasmid to carry those essential virulence genes. In this study, we constructed a miniaturized helper Ti plasmid, designated as pYL102, with the aim to enhance the overall Agrobacterium-mediated transformation rate. The size of pYL102 was reduced to ~60% of the original plasmid pCAMBIA5105. Subsequently, pYL102 was coupled with the broad host range (BHR) bacterial expression vector, pYL101C, of which the key regulatory virulence gene, virG-N54D, was cloned in and expressed under the control of a strong constitutive PINTc promoter. To test the functionality of the constructed vector system, A. tumefaciens C58C1 carrying pYL102, pYL101C::virG-N54D and the transformation vector pGWB2::e35S-sfGFP was used to transform Nicotiana benthamiana leaves by agroinfiltration. Green fluorescence was observed in spots infiltrated with Agrobacterium carrying the test plasmids. The fluorescence intensity from the test agroinfiltrated leaves was significantly higher than those of the mock-infiltrated leaves (p<0.01), indicating the vector system can be used for plant transformation.

Purpose: Corporate innovation might be slowed by team creativity and other factors. When a company's team creativity is low, innovation suffers, impacting its market competitiveness and technological advancement. Low-creativity teams make more mistakes, slowing down the project and making it more difficult to achieve its goals. Teams who do not innovate will not be able to expand or compete. The impact of female entrepreneurs' leadership styles on team innovation has not been researched in China's education administration. This study will look at how the leadership styles of successful female business owners promote innovative teamwork. Theoretical framework: This study developed a theoretical model based on the constitutive theory of creativity, with transformational leadership, empowering leadership, authoritative leadership, and participative leadership as independent variables, entrepreneurial team creativity as the dependent variable, team psychological empowerment as the mediating variable, and the nature of the company's business as the moderating variable. Methodology: This research looks at how strong female leaders help Rise English Educational Organization. This study looks at how different female leadership styles affect group morale, effectiveness, and innovation. Research, Practical & Social implications: Through a review of existing literature and similar studies, this chapter outlines the theoretical model and related hypotheses of this study and provides a more specific direction for the accompanying empirical investigation. Female team leaders frequently place a high importance on effective communication and collaboration. They promote open dialogue, paying attention, and making valuable comments. These modes of communication make it easier for people to share ideas and collaborate, which is beneficial to team innovation. When their manager is a woman, team members who feel mentally encouraged are more inclined to think imaginatively, take th

Purpose: Chinese language learning motivation and the Chinese cultural identity of international students in China, as important influencing factors of second language learning, is a research topic of great practical value and actual significance. International students' Chinese language learning motivation affects intercultural identity to some extent. This study aims to explore the impact of Chinese language learning motivation on intercultural identity among international students and to provide experiences and reflections for the teaching and daily management of international students in the later stage. Research Methodology: Based on a questionnaire survey of 85 international students from an independent university in Henan Province, this paper uses SPSS26. software to analyze the overall degree of international students' Chinese language learning motivation and intercultural identity, the influence of different factors on motivation to learn Chinese and intercultural identity, and the impact of different Chinese language learning motivations on intercultural identity. Findings: There were significant differences in intrinsic motivation, extrinsic motivation, and intercultural identity by nationality, length of Chinese language study, and length of time in China for international students, and no significant differences by gender. International students' intrinsic and extrinsic motivations substantially positively affect intercultural identity. Students' overall Chinese language learning motivation and intercultural identity were high.

This study investigated the effects of work from home (WFH) on language educators in Malaysian universities gauging specifically their perceptions on its advantages and disadvantages during the COVID-19 pandemic. A mixed-methods research design was employed involving 152 language educators. The results revealed that although the overall mean scores were rather neutral, language educators were more inclined toward positive effects of WFH, most notably in terms of saving communing time and being closer to family. However, the negative effects were missing colleagues and feeling glued to the computer. The results also shed interesting insights into Malaysian language educators’ high confidence in focusing on their tasks and using tools to fulfill their teaching and work-related responsibilities. The outcome from this study is a guiding model that not only informs the literature on the feasibility of WFH in the higher education context but also highlights pertinent areas of concern for its future planning and implementation.

Hong Kong has a well-established piped town gas network, with 27.7 billion MJ of gas sales in 2021. The feedstock for town gas production was converted from naphtha to a mixed feedstock of 40% naphtha and 60% natural gas (NG) in 2006, resulting in a 21% decrease in greenhouse gas (GHG) emissions and 1.58 billion HKD/year of cost savings. Increasing the proportion of the NG feedstock would potentially lead to more benefits. However, there may be difficulties in meeting the stringent combustion characteristics of town gas and the existing plant capacity may be reduced. Four processes for the production of town gas from NG are proposed in this work. The feasibility of each process was verified via simulation with Aspen Plus V14. A techno-economic evaluation showed that 296 million HKD/year of cost savings and 172224 t CO2-eq/year of GHG emission reduction could be achieved by using the proposed processes to produce town gas from NG. The reformer duties in the new processes were up to 16.6% lower compared to the existing process. There would not be any reduction in plant capacity associated with a limitation in heat transfer area, which is a common bottleneck. © 2023 Elsevier Ltd

This study investigated the effects of work from home (WFH) on language educators in Malaysian universities gauging specifically their perceptions on its advantages and disadvantages during the COVID-19 pandemic. A mixed-methods research design was employed involving 152 language educators. The results revealed that although the overall mean scores were rather neutral, language educators were more inclined toward positive effects of WFH, most notably in terms of saving communing time and being closer to family. However, the negative effects were missing colleagues and feeling glued to the computer. The results also shed interesting insights into Malaysian language educators’ high confidence in focusing on their tasks and using tools to fulfill their teaching and work-related responsibilities. The outcome from this study is a guiding model that not only informs the literature on the feasibility of WFH in the higher education context but also highlights pertinent areas of concern for its future planning and implementation.

Long-term planning of urban drainage systems aimed at maintaining the sustainability of urban hydrology remains challenging. In this study, an innovative multi-stage planning framework involving two adaptation pathways for opti-mizing hybrid low impact development and grey infrastructure (LID-GREI) layouts in opposing chronological orders was explored. The Forward Planning and Backward Planning are adaptation pathways to increase LID in chronological order based on the initial development stage of an urban built-up area and reduce LID in reverse chronological order based on the fnal development stage, respectively. Two resilience indicators, which considered potential risk scenar-ios of extreme storms and pipeline failures, were used to evaluate the performance of optimized layouts when land-use changed and evolved over time. Compared these two pathways, Forward Planning made the optimized layouts more economical and resilient in most risk scenarios when land-use changed, while the layouts optimized by Backward Plan-ning showed higher resilience only in the initial stage. Furthermore, a decentralized scheme in Forward Planning was chosen as the optimal solution when taking costs, reliability, resilience, and land-use changes into an overall consider-ation. Nevertheless, this kind of reverse optimization order offers a novel exploration in planning pathways for discov-ering the alternative optimization schemes. More comprehensive solutions can be provided to decision-makers. The findings will shed a light on the exploration of optimized layouts in terms of spatial configuration and resilience per-formance in response to land-use changes. This framework can be used to support long-term investment and planning in urban drainage systems for sustainable stormwater management.

Visual Abductive Reasoning is an emerging vision-language (VL) topic where the model needs to retrieve/generate a likely textual hypothesis from a visual input (image or its part) using backward reasoning based on commonsense. Unlike in conventional VL retrieval or captioning tasks, where entities of texts appear in the image, in abductive inferences, the relevant facts about inferences are not readily apparent in the input images. Besides, these inferences are causally linked to specific regional visual cues and would change as cues change. Existing works highlight cues utilizing a specific prompt (e.g., colorful prompt). Then, a full fine-tuning of a VL foundation model is launched to tweak its function from perception to deduction. However, the colorful prompt uniformly patchify ``regional hints'' and ``global context'' at the same granularity level and may lose fine-grained visual details crucial for VAR. Meanwhile, full fine-tuning of VLF on limited data would easily be overfitted. To tackle this, we propose a simple yet effective Region-Prompted Adapter (RPA), a hybrid parameter-efficient fine-tuning method that leverages the strengths of detailed cues and efficient training for the VAR task. RPA~consists of two novel modules: Regional Prompt Generator (RPG) and Adapter$^\textbf{+}$. The prior encodes ``regional visual hints'' and ``global contexts'' into visual prompts separately at fine and coarse-grained levels. The latter extends the vanilla adapters with a new Map Adapter, which modifies the attention map using a trainable low-dim query/key projection. Additionally, we propose a new Dual-Contrastive Loss to regress the visual feature toward features of factual description and plausible hypothesis. Experiments on the Sherlock demonstrate that RPA outperforms previous SOTAs, achieving the 1st rank on leaderboards (Comparison to Human Accuracy: RPA~31.74 vs CPT-CLIP 29.58)., Comment: 13 pages, 11 figures, Under Review of IEEE Transaction

Anthropogenic lead (Pb) has been the overwhelming Pb source to the global ocean, primarily contributed from Pb gasoline and industrial emissions. However, since Pb gasoline has been phased out globally, questions about whether there was a decrease in seawater Pb concentration, or if there are other sources taking over remains unclear in Southeast Asia. Here, combining Pb concentrations in seawater from Singapore Strait in 2010-2017; trap sediment in 2018-2019; and the previously published coral reconstruction covering 1975-2010; we found that the seawater Pb concentration in Singapore Strait over past decades followed the regional gasoline emissions, and no additional major source had contributed the Pb in the seawater since ~2010. The present-day Pb in Singapore Straits' water mainly follows the monsoonal current reversals, with variable degrees of scavenging that peak in inter-monsoon season. Minor Pb sources still contribute to some local-scale variabilities, despite a decadal-scale decreasing trend of Pb in seawater.

This paper estimates the marginal accident externality of driving in Central London by exploiting variation in traffic flow induced by the London Congestion Charge Zone using an instrumental variable approach. The charge attributed to a 9.4% reduction in traffic flow, which resulted in a less than proportional 6.0% and 7.6% decrease in accidents and slight injuries, and a 6.5% increase in serious injuries/fatalities. Our preferred estimates indicate that the accident, slight injuries and serious injuries/fatalities rate elasticities with respect to traffic flow are -0.36, -0.19 and -1.65, respectively. These estimates imply that the marginal external benefit of road safety from an additional kilometer driven is approximately £0.16. The marginal accident externality is positive, as the marginal driver along congested roads decreases the risk and severity of traffic collisions for other road users by slowing others down and increasing awareness.

Technology development is increasingly important for creating efficient and sustainable economies. Policy-makers have encouraged the co-location of technology-based firms that could lead to innovation benefits. One of the innovation policies are science parks, area developments where technology-based firms, universities and research institutes co-locate. Science parks enable firms to focus on their core activities. However, the trade-off that technology-based firms make regarding the science park location choice and the impact of organisational characteristics on these trade-offs is unknown. To collect tenant preference data, an exploratory survey with a stated choice experiment is distributed among technology-based firms both on and off science parks in the Netherlands. This approach allows for the estimation of the utilities that firms assign to design-related attributes and their willingness to pay for these attributes. Results show that science park tenants prefer locations with universities within the same area, shared business support and leisure facilities and near station locations relatively more than off-park counterparts do. Tenant firms are most eager to pay for the proximity of the university followed by provided R&D facilities, accessibility of the location, provided shared facilities, technological focus of the area and lastly events held in the area.

A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook. Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.

Numerous biological mechanisms contribute to outcome after stroke, including brain injury, inflammation, and repair mechanisms. Clinical genetic studies have the potential to discover biological mechanisms affecting stroke recovery in humans and identify intervention targets. Large sample sizes are needed to detect commonly occurring genetic variations related to stroke brain injury and recovery. However, this usually requires combining data from multiple studies where consistent terminology, methodology, and data collection timelines are essential. Our group of expert stroke and rehabilitation clinicians and researchers with knowledge in genetics of stroke recovery here present recommendations for harmonizing phenotype data with focus on measures suitable for multicenter genetic studies of ischemic stroke brain injury and recovery. Our recommendations have been endorsed by the International Stroke Genetics Consortium.

Most existing recommendation systems (RSs) are primarily concerned about the accuracy of rating prediction and only recommending popular items. However, other non-accuracy metrics such as novelty and diversity should not be overlooked. Existing multi-objective (MO) RSs employed collaborative filtering and combined with evolutionary algorithms to handle bi-objective optimization. Besides cold-start problem from collaborative filtering, it also vulnerable to highly sparse environment, while the evolutionary algorithm suffers from premature convergence and curse of dimensionality. These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. Several works in DRL are available but none has addressed MO RS problems. In this study, the performances of proposed DRL approaches that based on Deep Q-Network in MO recommendation problem were investigated. The approaches were evaluated with movie recommendation dataset by using three conflicting metrics, namely precision, novelty, and diversity. The results demonstrated that deep reinforcement learning approaches has superiority performance in MO optimization, and its capability of recommending precise item along with achieving high novelty and diversity against the benchmark that using probabilistic based multi-objective approach based on evolutionary algorithm (PMOEA). Although PMOEA algorithm secured higher average value in precision, it has lower values of novelty and diversity than the proposed DRL approaches. The DRL approaches surpassed the benchmark results in average of maximum novelty and the average of mean diversity metrics, the optimization between accuracy and non-accuracy metrics is inevitable. In addition, the experiments revealed that incorporation of user latent features enhanced the recommendation quality.

The increasing consumer awareness of healthier food choices with low calories and high fiber content has driven the development of sucrose-free dark compound chocolate enriched with dietary fiber. Therefore, this study aimed to determine the effect of adding dietary fiber-low digestible carbohydrate (LDC) polymer on the moisture sorption behavior and thermal properties of a sucrose replacer mixture. Duo-trio and acceptance tests were also conducted to identify the relative sweetness of sucrose replacer compared to that of sucrose. Among these samples, erythritol-polydextrose mixture and tagatose-inulin mixture have similar sweetness levels as sucrose at P ≥ 0.05. Most sucrose replacer mixtures were well-accepted by panelists, except the trehalose-polydextrose mixture. Moisture content, hygroscopicity, and thermal properties of the sucrose replacer mixture were also studied. The result showed that all sucrose replacer mixtures had significantly (P<0.05) higher moisture content than sucrose. The addition of LDC polymer altered the moisture content, hygroscopicity, and melting temperature of the samples due to its amorphous nature and large molecular structure. Considering the average relative humidity in tropical countries was reported at 65% RH, the sucrose replacer mixtures containing erythritol, mannitol, or tagatose could replace sucrose in dark compound chocolate of their low moisture content and hygroscopicity at aw of 0.65.

Most existing recommendation systems (RSs) are primarily concerned about the accuracy of rating prediction and only recommending popular items. However, other non-accuracy metrics such as novelty and diversity should not be overlooked. Existing multi-objective (MO) RSs employed collaborative filtering and combined with evolutionary algorithms to handle bi-objective optimization. Besides cold-start problem from collaborative filtering, it also vulnerable to highly sparse environment, while the evolutionary algorithm suffers from premature convergence and curse of dimensionality. These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. Several works in DRL are available but none has addressed MO RS problems. In this study, the performances of proposed DRL approaches that based on Deep Q-Network in MO recommendation problem were investigated. The approaches were evaluated with movie recommendation dataset by using three conflicting metrics, namely precision, novelty, and diversity. The results demonstrated that deep reinforcement learning approaches has superiority performance in MO optimization, and its capability of recommending precise item along with achieving high novelty and diversity against the benchmark that using probabilistic based multi-objective approach based on evolutionary algorithm (PMOEA). Although PMOEA algorithm secured higher average value in precision, it has lower values of novelty and diversity than the proposed DRL approaches. The DRL approaches surpassed the benchmark results in average of maximum novelty and the average of mean diversity metrics, the optimization between accuracy and non-accuracy metrics is inevitable. In addition, the experiments revealed that incorporation of user latent features enhanced the recommendation quality.

Most existing recommendation systems (RSs) are primarily concerned about the accuracy of rating prediction and only recommending popular items. However, other non-accuracy metrics such as novelty and diversity should not be overlooked. Existing multi-objective (MO) RSs employed collaborative filtering and combined with evolutionary algorithms to handle bi-objective optimization. Besides cold-start problem from collaborative filtering, it also vulnerable to highly sparse environment, while the evolutionary algorithm suffers from premature convergence and curse of dimensionality. These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. Several works in DRL are available but none has addressed MO RS problems. In this study, the performances of proposed DRL approaches that based on Deep Q-Network in MO recommendation problem were investigated. The approaches were evaluated with movie recommendation dataset by using three conflicting metrics, namely precision, novelty, and diversity. The results demonstrated that deep reinforcement learning approaches has superiority performance in MO optimization, and its capability of recommending precise item along with achieving high novelty and diversity against the benchmark that using probabilistic based multi-objective approach based on evolutionary algorithm (PMOEA). Although PMOEA algorithm secured higher average value in precision, it has lower values of novelty and diversity than the proposed DRL approaches. The DRL approaches surpassed the benchmark results in average of maximum novelty and the average of mean diversity metrics, the optimization between accuracy and non-accuracy metrics is inevitable. In addition, the experiments revealed that incorporation of user latent features enhanced the recommendation quality.

Most existing recommendation systems (RSs) are primarily concerned about the accuracy of rating prediction and only recommending popular items. However, other non-accuracy metrics such as novelty and diversity should not be overlooked. Existing multi-objective (MO) RSs employed collaborative filtering and combined with evolutionary algorithms to handle bi-objective optimization. Besides cold-start problem from collaborative filtering, it also vulnerable to highly sparse environment, while the evolutionary algorithm suffers from premature convergence and curse of dimensionality. These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. Several works in DRL are available but none has addressed MO RS problems. In this study, the performances of proposed DRL approaches that based on Deep Q-Network in MO recommendation problem were investigated. The approaches were evaluated with movie recommendation dataset by using three conflicting metrics, namely precision, novelty, and diversity. The results demonstrated that deep reinforcement learning approaches has superiority performance in MO optimization, and its capability of recommending precise item along with achieving high novelty and diversity against the benchmark that using probabilistic based multi-objective approach based on evolutionary algorithm (PMOEA). Although PMOEA algorithm secured higher average value in precision, it has lower values of novelty and diversity than the proposed DRL approaches. The DRL approaches surpassed the benchmark results in average of maximum novelty and the average of mean diversity metrics, the optimization between accuracy and non-accuracy metrics is inevitable. In addition, the experiments revealed that incorporation of user latent features enhanced the recommendation quality.

The increasing consumer awareness of healthier food choices with low calories and high fiber content has driven the development of sucrose-free dark compound chocolate enriched with dietary fiber. Therefore, this study aimed to determine the effect of adding dietary fiber-low digestible carbohydrate (LDC) polymer on the moisture sorption behavior and thermal properties of a sucrose replacer mixture. Duo-trio and acceptance tests were also conducted to identify the relative sweetness of sucrose replacer compared to that of sucrose. Among these samples, erythritol-polydextrose mixture and tagatose-inulin mixture have similar sweetness levels as sucrose at P ≥ 0.05. Most sucrose replacer mixtures were well-accepted by panelists, except the trehalose-polydextrose mixture. Moisture content, hygroscopicity, and thermal properties of the sucrose replacer mixture were also studied. The result showed that all sucrose replacer mixtures had significantly (P<0.05) higher moisture content than sucrose. The addition of LDC polymer altered the moisture content, hygroscopicity, and melting temperature of the samples due to its amorphous nature and large molecular structure. Considering the average relative humidity in tropical countries was reported at 65% RH, the sucrose replacer mixtures containing erythritol, mannitol, or tagatose could replace sucrose in dark compound chocolate of their low moisture content and hygroscopicity at aw of 0.65.

Numerous biological mechanisms contribute to outcome after stroke, including brain injury, inflammation, and repair mechanisms. Clinical genetic studies have the potential to discover biological mechanisms affecting stroke recovery in humans and identify intervention targets. Large sample sizes are needed to detect commonly occurring genetic variations related to stroke brain injury and recovery. However, this usually requires combining data from multiple studies where consistent terminology, methodology, and data collection timelines are essential. Our group of expert stroke and rehabilitation clinicians and researchers with knowledge in genetics of stroke recovery here present recommendations for harmonizing phenotype data with focus on measures suitable for multicenter genetic studies of ischemic stroke brain injury and recovery. Our recommendations have been endorsed by the International Stroke Genetics Consortium.

Malaysia has been experiencing smoke-haze episodes almost annually for the past few decades. PM2.5 is the main component in haze and causes harmful impacts on health due to its small aerodynamic size. This study aimed to explore the implications of PM2.5 exposure on the dietary intake of working individuals. Two phased 13-weeks follow-up study was conducted involving 440 participants, consisting of two cohorts of outdoor and indoor workers. Ambient PM2.5 concentrations were monitored using DustTrakTM DRX Aerosol Monitor. Data on Simplified Nutritional Appetite Questionnaire (SNAQ) and 24 h diet recall were collected weekly. The highest PM2.5 concentration of 122.90 ± 2.07 µg/m3 was recorded in August, and it vastly exceeded the standard value stipulated by US EPA and WHO. SNAQ scores and calorie intake were found to be significantly (p < 0.05) associated with changes in PM2.5 exposure of outdoor workers. Several moderate and positive correlations (R-value ranged from 0.4 to 0.6) were established between SNAQ scores, calorie intake and PM2.5 exposure. Overall findings suggested that long hours of PM2.5 exposure affect personal dietary intake, potentially increasing the risk of metabolic syndromes and other undesired health conditions. The current policy should be strengthened to safeguard the well-being of outdoor workers.

Malaysia has been experiencing smoke-haze episodes almost annually for the past few decades. PM2.5 is the main component in haze and causes harmful impacts on health due to its small aerodynamic size. This study aimed to explore the implications of PM2.5 exposure on the dietary intake of working individuals. Two phased 13-weeks follow-up study was conducted involving 440 participants, consisting of two cohorts of outdoor and indoor workers. Ambient PM2.5 concentrations were monitored using DustTrakTM DRX Aerosol Monitor. Data on Simplified Nutritional Appetite Questionnaire (SNAQ) and 24 h diet recall were collected weekly. The highest PM2.5 concentration of 122.90 ± 2.07 µg/m3 was recorded in August, and it vastly exceeded the standard value stipulated by US EPA and WHO. SNAQ scores and calorie intake were found to be significantly (p < 0.05) associated with changes in PM2.5 exposure of outdoor workers. Several moderate and positive correlations (R-value ranged from 0.4 to 0.6) were established between SNAQ scores, calorie intake and PM2.5 exposure. Overall findings suggested that long hours of PM2.5 exposure affect personal dietary intake, potentially increasing the risk of metabolic syndromes and other undesired health conditions. The current policy should be strengthened to safeguard the well-being of outdoor workers.

Hydrothermal carbonization (HTC) provides a promising alternative to valorize food waste digestate (FWD) and avoid disposal issues. Although hydrochar derived from FWD alone had a low calorific content (HHV of 13.9 MJ kg−1), catalytic co-HTC of FWD with wet lignocellulosic biomass (e.g., wet yard waste; YW) and 0.5 M HCl exhibited overall superior attributes in terms of energy recovery (22.7 MJ kg−1), stable and comprehensive combustion behaviour, potential nutrient recovery from process water (2-fold higher N retention and 129-fold higher P extraction), and a high C utilization efficiency (only 2.4% C loss). In contrast, co-HTC with citric acid provided ∼3-fold higher autogenous pressure, resulting in a superior energy content of 25.0 MJ kg−1, but the high C loss (∼74%) compromised the overall environmental benefits. The results of this study established a foundation to fully utilize FWD and YW hydrochar for bioenergy application and resource recovery from the process water. © 2021 Elsevier Ltd

A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook. Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.

Associative memory (AM) is conceptualized as the ability to form links between two previously unrelated pieces of information so that the subsequent presentation of one activates the memory of the other. Unlike other types of memory for which standardized assessment tools exist, AM is assessed mostly by ad hoc tasks designed to tackle specific research questions that are not meant to capture AM as a universal cognitive ability. Typically, AM is assessed using paired-associate paradigms with unimodal (e.g., word pairs) or multimodal (e.g., face-word) stimuli sets. In culturally diverse and multilingual societies, the application of these paradigms can lead to an unreliable and biased assessment of memory abilities. To address this issue, we developed an AM paradigm that combines key aspects of AM assessment – associative encoding, associative recognition, and cued recall, as well as implicit AM effect. The stimuli for the task - pictures of common objects and natural scenes - have been selected to minimize language and culture effects. The task has been developed using free software (OpenSesame) and stimuli, in both online and offline mode of administration, thus enabling wide and free use for research purposes across different settings. The large-scale international collaboration is set to adapt the task into 25 languages so far, including Arabic, Bosnian, Czech, Catalan, Chinese, Croatian, Danish, Dutch, English, Estonian, French, German, Greek, Hebrew, Hungarian, Italian, Lithuanian, Malay, Polish, Portuguese, Romanian, Serbian, Slovak, Slovene, and Spanish. Data is collected across 26 countries with a total of 34 samples (150-300 participants each) to assess the psychometric properties of the task and crosslinguistic (in)variance of the memory performance. The collaboration is expected to result in a comprehensive multilingual AM assessment tool, that is freely available for research use.

The ferroelectricity of multivalent codoped Bismuth ferrite (BiFeO3; BFO) nanoparticles (NPs) is revealed and utilized for photocatalysis, exploiting their narrow electronic bandgap. The photocatalytic activity of ferroelectric photocatalysts BiFe0.95Mn0.05O3 (BFM) NPs and mono‐, di‐, or tri‐valent cations (Ag+, Ca2+, Dy3+; MDT) coincorporated BFM NPs are studied under ultrasonication and in acidic conditions. It is found that such doping enhances the photocatalytic activity of the ferroelectric NPs approximately three times. The correlation of the photocatalytic activity with structural, optical, and electrical properties of the doped NPs is established. The increase of spontaneous polarization by the mono‐ and tri‐valent doping is one of the major factors in enhancing the photocatalytic performance along with other factors such as stronger light absorption in the visible range, low recombination rate of charge carriers, and larger surface area of NPs. A‐site doping of BFO NPs by divalent elements suppresses the polarization, whereas trivalent (Dy3+) and monovalent (Ag+) cations provide an increase of polarization. The depolarization field in these single domain NPs acts as a driving force to mitigate recombination of the photoinduced charge carriers., The ferroelectricity of Ag/Ca/Dy‐doped BiFe0.95Mn0.05O3 nanoparticles are utilized for photocatalysis under ultrasonic conditions. The mitigated recombination of photoinduced charge‐carriers in the nanoparticles due to the depolarization field, is one of the important factors for the photocatalytic rate. The piezoresponse becomes a crucial parameter under ultrasonic conditions for ferroelectric photocatalysts. The pink dye (rhodamine B) is photodegraded using MDT doped nanoparticles. The ease of photoinduced charge carrier separation in single domain nanoparticles using the depolarization field as a driving force is shown. image, Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659, Peer Reviewed

The effect of oxygen purity on the thermal efficiency of an enriched-oxygen-fed integrated gasification carbon cycle (IGCC) was studied. A simultaneous process optimization with heat integration framework is proposed and used for the study. Rigorous models were used to represent the cryogenic air separation unit (ASU), gasifier and combined cycle. It was found that the thermal efficiency was highest (41.3–42.3%) within a range of 35–85 mol% O2, with the optimum at 45.5 mol% O2. Furthermore, injection of the nitrogen-rich vapor distillate from the high-pressure column of the ASU to the gas turbine was found to be the optimal nitrogen integration scheme compared to no nitrogen integration or using vapor distillate from the low-pressure column. In the optimized solution, heat integration results showed that pre-heating of the gasifier's oxygen feed occurs at the pinch and steam turbine inlet pressure values were 165, 28.6 and 4.9 bar. © 2022 Elsevier Ltd

This paper estimates the marginal accident externality of driving in Central London by exploiting variation in traffic flow induced by the London Congestion Charge Zone using an instrumental variable approach. The charge attributed to a 9.4% reduction in traffic flow, which resulted in a less than proportional 6.0% and 7.6% decrease in accidents and slight injuries, and a 6.5% increase in serious injuries/fatalities. Our preferred estimates indicate that the accident, slight injuries and serious injuries/fatalities rate elasticities with respect to traffic flow are -0.36, -0.19 and -1.65, respectively. These estimates imply that the marginal external benefit of road safety from an additional kilometer driven is approximately £0.16. The marginal accident externality is positive, as the marginal driver along congested roads decreases the risk and severity of traffic collisions for other road users by slowing others down and increasing awareness.

Technology development is increasingly important for creating efficient and sustainable economies. Policy-makers have encouraged the co-location of technology-based firms that could lead to innovation benefits. One of the innovation policies are science parks, area developments where technology-based firms, universities and research institutes co-locate. Science parks enable firms to focus on their core activities. However, the trade-off that technology-based firms make regarding the science park location choice and the impact of organisational characteristics on these trade-offs is unknown. To collect tenant preference data, an exploratory survey with a stated choice experiment is distributed among technology-based firms both on and off science parks in the Netherlands. This approach allows for the estimation of the utilities that firms assign to design-related attributes and their willingness to pay for these attributes. Results show that science park tenants prefer locations with universities within the same area, shared business support and leisure facilities and near station locations relatively more than off-park counterparts do. Tenant firms are most eager to pay for the proximity of the university followed by provided R&D facilities, accessibility of the location, provided shared facilities, technological focus of the area and lastly events held in the area.

Chan Keat Kang, Paul N Brennan, John F Dillon Division of Molecular and Clinical Medicine, School of Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee, UKCorrespondence: John F Dillon, Email j.f.dillon@dundee.ac.ukAbstract: Hepatitis B virus (HBV) infection is a major global public health challenge associated with significant morbidity and mortality. Due to worldwide population aging, HBV infection in the elderly will become increasingly prevalent. Effective universal vaccination programs exist but these are largely targeted towards the younger population. Therefore, the elderly population remains at risk of higher disease burden. New diagnoses of HBV infection in the elderly are usually asymptomatic chronic infections which increases their risk of developing cirrhosis, hepatocellular carcinoma, and liver disease-related mortality, especially if left untreated. Physiological changes and the increasing prevalence of multimorbidity associated with aging also potentially worsen outcomes in elderly patients with chronic HBV infection. Therefore, this cohort of patients should be monitored closely and effectively. Current international clinical practice guidelines unfortunately do not provide hard treatment endpoints specific to elderly patients with chronic HBV infection. Management of these patients is complex and requires an individualized approach. Multiple factors such as physiological changes, comorbidities, compliance, treatment tolerability and efficacy, burden of treatment, and realistic treatment goals need to be considered. Shared decision-making between patient and clinician is essential to ensure that the final decision for or against treatment aligns with the patient’s values and preferences. This review article aims to summarize the monitoring and management of chronic HBV infection in the aging population.Keywords: chronic hepatitis B, aging, elderly, effective monitoring

Sharifah Saffinas Syed Soffian,1 Azmawati Mohammed Nawi,1 Rozita Hod,1 Mohd Rizal Abdul Manaf,1 Huan-Keat Chan,2 Muhammad Radzi Abu Hassan2 1Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, 56000, Malaysia; 2Clinical Research Center, Sultanah Bahiyah Hospital, Alor Setar, 05400, Kedah, MalaysiaCorrespondence: Azmawati Mohammed Nawi, Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, 56000, Malaysia, Tel +60 3 9145 8408, Email azmawati@ppukm.ukm.edu.myAbstract: Regardless of the high global burden of colorectal cancer (CRC), the uptake of CRC screening varies across countries. This systematic review aimed to provide a picture of the disparities in recommendations for CRC screening in average-risk individuals using an ecobiosocial approach. It was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search was conducted through Scopus, Web of Science, PubMed, and EBSCOHost. Full-text guidelines which were published between 2011 and 2021, along with guidelines which provided recommendations on CRC screening in average-risk individuals, were included in the review. However, guidelines focusing only on a single screening modality were excluded. Fourteen guidelines fulfilling the eligibility criteria were retained for the final review and analysis. Quality assessment of each guideline was performed using the AGREE II instrument. Disparities in guidelines identified in this review were classified into ecological (screening modalities and strategies), biological (recommended age, gender and ethnicities), and social (smoking history, socioeconomic status, and behavior) factors. In general, unstandardized practices in CRC screening for average-risk individuals are likely attributable to the inconsistent and non-specific recommendations in the literature. This review calls on stakeholders and policymakers