Tunku Abdul Rahman University

In 2021, global sweet potato production hit 88.9 million metric tons, with China leading the pack, contributing 55% of the world’s total. Sweet potatoes are a highly adaptable crop, capable of thriving in marginal growing conditions with a wide production geography, short production cycles, and high yield potential. It is the most efficient staple food crop, with 14–26 metric tons per hectare yield and higher nutrient density than cereals. However, the cultivation and processing of sweet potatoes generate significant organic waste in the form of solid and liquid by-products, including peelings, trimmings, leaves, stems, and stalks. These by-products contain macronutrients such as carbohydrates, proteins, and bioactive compounds or phytochemicals such as phenolics, anthocyanins, and carotenoids that can be extracted or used in various downstream processes and products. This chapter reviews the valuable compounds found in sweet potato peels, leaves, stems, and stalks and methods for extracting bioactive compounds and other valuable ingredients. It also discusses the functional properties of the extract and bioactive compounds and their applications in food and non-food products and explores opportunities for their utilization for non-health-related purposes. Finally, the chapter provides research gaps for further investigation in the valorization of sweet potato by-products.

Youths are in the stage of developing their social identity and are susceptible to life challenges that influence their well-being level. Resilience and family resilience play a crucial role in maintaining well-being once youth emerge into young adulthood. This study investigated the contributors to well-being among Malaysian youth using family resilience, resilience, and gender. Utilising convenience sampling, 325 youths aged 15 to 24 years old ( M = 20.23, SD = 2.92) completed surveys on family resilience, resilience, and well-being. Data collected were analysed using hierarchical multiple regression in SPSS. Results showed that resilience and family resilience were significantly associated with well-being. Precisely, resilience was reported as the biggest contributor to well-being, followed by family resilience. This study supported the roles of resilience and family resilience in improving Malaysian youths’ well-being and advocated for resilience upskilling programmes that are customised and personalised to youths’ preferences to enhance their well-being.

This paper explores innovative approaches for reconstructing the wake flow field of yawed wind turbines from sparse data using data-driven and physics-informed machine learning techniques. The physics-informed machine learning wake flow estimation (WFE) integrates neural networks with fundamental fluid dynamics equations, providing robust and interpretable predictions. This method ensures adherence to essential fluid dynamics principles, making it suitable for reliable wake flow estimation in wind energy applications. In contrast, the data-driven machine learning wake flow estimation (DDML-WFE) leverages techniques such as proper orthogonal decomposition to extract significant flow features, offering computational efficiency and reduced reconstruction costs. Both methods demonstrate satisfactory performance in reconstructing the instantaneous wake flow field under yawed conditions. DDML-WFE maintains comparable performance even with reduced measurement resolution and increased noise, highlighting its potential for real-time wind turbine control. The study employs a limited number of measurement points to balance data collection challenges while capturing essential flow field characteristics. Future research will focus on optimizing turbine control strategies in wind farms by incorporating multi-scale modules and advanced data-driven techniques for temporal prediction of wake flow fields.

Neurodegenerative diseases are characterized by the progressive loss of neurons or their myelin sheaths, leading to dysfunction and worsening over time. In Alzheimer's disease (AD) and Huntington's disease (HD), certain specific types of neurons are symmetrically lost in the patient's brain, and these specific neuron losses cause motor, sensory, or conscious disorders of the patient. Induced pluripotent stem cells (iPSCs) are multipotent stem cells obtained through reprogramming of somatic cells. The iPSC of patient origin carries disease-related genetic and epigenetic information, and its differentiation process can reflect the development of the disease to a certain extent. This makes iPSCs an ideal tool for building a variety of disease models, including AD and HD, offering valuable insights into disease mechanisms and potential therapeutic strategies. Since most AD and HD still lack effective treatment methods, clarifying the possible pathogenesis of AD and HD will become a prerequisite and foundation for effective prevention and development of the disease and finding effective treatment methods, which is of great theoretical and practical significance for improving the quality of life and longevity of the elderly.

Traditional communication methods rely on meticulously designed system modules to ensure accurate bit-level transmission. However, with the growing complexity and volume of data, these approaches are reaching the Shannon limit. Semantic communication (SC) emerges as a promising solution that emphasizes meaning rather than bit-level precision. Despite its potential, SC still faces challenges in efficiently extracting and preserving relevant features, especially in resource-constrained environments. This article proposes a SC method that utilizes bi-level routing attention (BRA), named BRASC. By capturing both region-to-region and token-to-token attention mechanisms, BRA captures broad meaning as well as specific details, retaining key semantic information while eliminating less relevant data, thereby enhancing feature representation and improving transmission accuracy. Experimental results demonstrate that BRASC consistently outperforms Original Images Direct Classification (OIDC), Deep Learning (ResNet18), and Baseline methods in image classification accuracy on the STL-10 dataset. BRASC shows superior performance across varying signal-to-noise ratios (SNR), maintaining high accuracy and stability, particularly excelling in low SNR conditions. This robustness across diverse channel conditions confirms BRASC’s effectiveness and adaptability for semantic communication in challenging communication scenarios.

Anode‐free lithium metal batteries are promising toward high‐energy‐density power sources with low‐cost, but their practical applications are challenged by poor cycling stability and low rate capability. Herein, a shape change‐free and lithium‐free anode that well controls the reversible Li plating‐stripping is reported, which is composed of a highly‐ordered hollow ZnO matrix with a surface‐coated lithium‐phosphorus‐oxynitride (LiPON) layer. The ZnO matrix supplies sufficient cavities and lithiophilic sites to facilitate uniform Li plating/stripping within the hollow cavity, while the LiPON layer maintains stable solid‐electrolyte interphase from mechanical and electrochemical damage. As a result, lithium is constrained within the cavity and the overall anode shape is effectively controlled during long‐term and high‐rate cycling. The assembled half‐cell stably works at 1.2 mA cm⁻² for 335 cycles with Coulombic efficiency of 98.8%. Without Li pre‐deposition, full‐cells using modified‐LiFePO4 and LiNi0.5Co0.2Mn0.3O2 cathodes demonstrate 150‐cycles lifespan and high energy density of 617 Wh kg⁻¹ at 2C rate.

The global pandemic has highlighted the necessity for organisations to develop ambidexterity and adaptability to build resilience in the face of unprecedented disruptions. Despite extensive research, the unique contributions of different organisational resources to organisational resilience amid macroeconomic challenges remain under research. This study aims to address this gap by examining the roles of economic, human, physical, and social capital in fostering organisational resilience. We hypothesise that these organisational resources are essential for achieving resilience and assess this through a combined approach of Partial Least Squares Structural Equation Modelling and Necessary Condition Analysis. Additionally, we employ Combined Importance-Performance Map Analysis to help practitioners prioritise resources effectively. Data was collected using purposive sampling from key organisational personnel via a self-reported questionnaire. The results confirm that all four types of organisational capital are necessary for resilience, with each exhibiting varying minimum levels and performance based on its relative importance. This study contributes original insights into how organisations can strategically leverage their resources to enhance resilience.

Underwater vision is essential in numerous applications, such as marine resource surveying, autonomous navigation, objective detection, and target monitoring. However, raw underwater images often suffer from significant color deviations due to light attenuation, presenting challenges for practical use. This systematic literature review examines the latest advancements in color correction methods for underwater image enhancement. The core objectives of the review are to identify and critically analyze existing approaches, highlighting their strengths, limitations, and areas for future research. A comprehensive search across eight scholarly databases resulted in the identification of 67 relevant studies published between 2010 and 2024. These studies introduce 13 distinct methods for enhancing underwater images, which can be categorized into three groups: physical models, non-physical models, and deep learning-based methods. Physical model-based methods aim to reverse the effects of underwater image degradation by simulating the physical processes of light attenuation and scattering. In contrast, non-physical model-based methods focus on manipulating pixel values without modeling these underlying degradation processes. Deep learning-based methods, by leveraging data-driven approaches, aim to learn mappings between degraded and enhanced images through large datasets. However, challenges persist across all categories, including algorithmic limitations, data dependency, computational complexity, and performance variability across diverse underwater environments. This review consolidates the current knowledge, providing a taxonomy of methods while identifying critical research gaps. It emphasizes the need to improve adaptability across diverse underwater conditions and reduce computational complexity for real-time applications. The review findings serve as a guide for future research to overcome these challenges and advance the field of underwater image enhancement.

Geothermal energy, a form of renewable energy, has been extensively utilized for building heating. However, there is a lack of detailed comparative studies on the use of shallow and medium-deep geothermal energy in building energy systems, which are essential for decision-making. Therefore, this paper presents a comparative study of the performance and economic analysis of shallow and medium-deep borehole heat exchanger heating systems. Based on the geological parameters of Xi’an, China and commonly used borehole heat exchanger structures, numerical simulation methods are employed to analyze performance and economic efficiency. The results indicate that increasing the spacing between shallow borehole heat exchangers can effectively reduce thermal interference between the pipes and improve heat extraction performance. As the flow rate increases, the outlet water temperature ranges from 279.3 to 279.7 K, with heat extraction power varying between 595 and 609 W. For medium-deep borehole heat exchangers, performance predictions show that a higher flow rate results in greater heat extraction power. However, when the flow rate exceeds 30 m³/h, further increases in flow rate have only a minor effect on enhancing heat extraction power. Additionally, the economic analysis reveals that the payback period for shallow geothermal heating systems ranges from 10 to 11 years, while for medium-deep geothermal heating systems, it varies more widely from 3 to 25 years. Therefore, the payback period for medium-deep geothermal heating systems is more significantly influenced by operational and installation parameters, and optimizing these parameters can considerably shorten the payback period. The results of this study are expected to provide valuable insights into the efficient and cost-effective utilization of geothermal energy for building heating.

The thermal instability of the perovskite layer hinders the commercialization of perovskite solar cells (PSCs). In this work, the effect of cold isostatic pressing (CIP) on the thermal stability of poly (methyl methacrylate) (PMMA) interlayer-encapsulated methylammonium lead iodide (MAPbI 3 ) perovskite (PMMA-MAPbI 3 ) film was investigated. The MAPbI 3 perovskite film was prepared via a vacuum-assisted solution process (VASP) on the SnO 2 -coated FTO glass substrate. Following this, a PMMA interlayer was spin-coated on the MAPbI 3 film. The PMMA-MAPbI 3 film was then vacuum-sealed in a thermoplastic bag and pressed in a CIP chamber filled with silicone oil at a pressure of 5 MPa for 10 min. The CIP-treated film was then subjected to thermal stressing at 150 °C for 1–5 h to compare its thermal stability against a pristine film untreated with CIP. The CIP treatment densified the MAPbI 3 perovskite grains and enhanced the interfacial bonding between the PMMA interlayer and the perovskite film. These enhancements contributed to the superior thermal stability of the CIP-treated film, as its morphology retained most of the MAPbI 3 perovskite grains with minimal conversion to PbI 2 nanorods, evidenced by the minimal evolution of the PbI 2 XRD peak. The photoluminescence (PL) spectra of the CIP-treated film showed higher retention of the emission peak at 770 nm after 5 h of thermal stressing, signifying less thermal degradation than the untreated pristine film. Thus, CIP is demonstrated as a simple method that can enhance the thermal stability of the PMMA-MAPbI 3 film.

Background The benefits of strength training on shooting accuracy in football players and other athletes are well known, but its effectiveness in improving shooting accuracy among basketball players remains unclear. Therefore, this study aimed to determine the effect of partial range of motion (PROM) and full range of motion (FROM) triceps strength training on stationary three-point shooting test (S3P) among recreational basketball players. Methods This was a single-blinded randomized controlled trial. 30 participants were randomly assigned into 3 equal groups; FROM, PROM, and control (CON). Triceps strength training was carried out using an adjustable overhead cable crossover machine. With shoulders over-head flexed to 160–180° for both experimental groups, the FROM group performed strength training from full elbow flexion to full extension. In contrast, the PROM group worked at a restricted range, between 60°-110° elbow flexion/extension. Both groups engaged in 4 sets of 10 repetitions, 2 sessions/week for 4-weeks at 67% of 1 repetition maximum, while the CON group did not participate in any exercise program. S3P was assessed at baseline and at the end of 4-weeks intervention. Results Participants mean age (20.20 ± 1.54 years), height (1.74 ± 0.61 m), and body mass index (22.55 ± 3.31) were descriptively analysed. Within group analysis showed a significant improvement of S3P in both FROM (p = 0.0345, 95% CI = -1.50 to -0.07, ES = 0.81) and PROM (p = 0.005, 95% CI = -2.44 to -0.97, ES = 2.40) compared to CON group (p = 0.8995, 95% CI = -0.61 to 0.68, ES = 0.05). Group-by-time interaction demonstrated PROM to be more promising (p = 0.0102, 95% CI = -1.70 to 0.21) than the FROM and CON groups. Conclusions PROM triceps strength training improves shooting accuracy and is a time-efficient technique highly recommended for basketball players. Trial registration clinicaltrials.gov, NCT04128826, registered on 14/10/2019 - retrospectively, https://clinicaltrials.gov/study/NCT04128826.

Glycyrrhiza uralensis Fisch ( G. uralensis ) is a key species for windbreak and sand fixation, possessing notable pharmacological and economic value. However, the yield of G. uralensis is considerably impacted due to its cultivation in arid, semi‐arid, and salt‐affected regions. Silicon (Si) has been reported to improve plant tolerance to drought and salt stress by regulating nitrogen and secondary metabolism. Herein, the effects of Si treatment on nitrogen and secondary metabolism of G. uralensis seedlings under drought (D), salt (S), and drought‐salt (SD) stresses were investigated in combination with physiological and transcriptomic analyses. The results indicated that stress conditions significantly inhibited the growth of G. uralensis seedlings by suppressing nitrogen and secondary metabolism. Si treatment counteracted these inhibitions to some extent. Specifically, Si treatment increased soluble protein content by approximately 15% by regulating the nitrogen metabolism of G. uralensis under D stress. Furthermore, Si treatment elevated the content of glycyrrhetinic acid by about 89% under SD stress by increasing the content of primary metabolites and regulating the expression of enzymes involved in the biosynthesis of glycyrrhizic acid and liquiritin, including 3‐hydroxy‐3‐methylglutaryl CoA reductase (HMGR), squalene synthase (SQS), and β ‐amyrin synthase ( β ‐AS). In summary, our findings suggest that Si could alleviate the adverse effects induced by drought and/or salt stresses on the growth of G. uralensis seedlings by regulating nitrogen metabolisms, which further triggered the accumulation of secondary metabolites, ultimately improving the stress resistance of cultivated G. uralensis seedlings. This work provides direction for Si to improve stress resistance.

Background As climate change raises global temperatures, there remains a notable gap in understanding the body’s mechanisms of heat stress defense exhibited by Heat Shock Protein (HSP) within the populations. Objective This study aims to investigate the expression level of HSP70 in response to indoor heat exposure among vulnerable populations in both urban and rural settings. Methods A comparative cross-sectional was conducted among 108 participants from urban and rural areas in Klang Valley, Malaysia. The study included face-to-face interviews, indoor heat exposure monitoring, and thermal stress classification using the Universal Thermal Climate Index (UTCI). HSP70 gene and protein expressions were analyzed using reverse-transcription quantitative polymerase chain reaction (RT-qPCR) and HSP70 High Sensitivity Enzyme-linked Immunosorbent Assay (ELISA), respectively. Results Urban areas experienced signficantly higher UTCI heat exposure levels than rural areas (p < 0.001). In response to heat stress, vulnerable populations in urban areas exhibited higher HSP70 gene relative expression and HSP70 protein expression. A significant mean difference in the plasma HSP70 protein expression was observed between the two groups (p < 0.001). The linear mixed model (LMM) revealed a significant association between UTCI heat exposure levels and HSP70 gene and protein expression in both groups (p < 0.001). Impact While previous studies have examined cellular responses to heat stress in healthy individuals within controlled experimental settings, our study uniquely focuses on vulnerable individuals in actual environmental conditions. This is crucial for establishing baseline information on the ability of these populations to adapt to climate change and surrounding temperatures. Such information is essential for building resilient communities and preventing fatal incidents such as heat stroke during extreme heat events. By highlighting the differences between urban and rural populations, this study provides critical information for policymakers and health practitioners to design location-specific and population-specific heat stress mitigation strategies.

The aim of this study is twofold. First, we investigate the mediating role of trust in principals in the relationship between organizational justice and organizational citizenship behavior (OCB). Second, we examine the moderating effect of self-efficacy between organizational justice and OCB as well as between trust in principals and OCB. A total of 467 teachers participated voluntarily in this survey. Partial least square structural equation modeling was employed to analyze the proposed research model and hypotheses. Based on the results, we discovered that trust in principals significantly mediates the relationship between organizational justice and OCB. Besides, the relationship between trust in principals and OCB is more pronounced among teachers with higher self-efficacy. Conversely, the impact of organizational justice on OCB is more significant among teachers with lower self-efficacy. These key findings have several implications for both practical applications and theoretical considerations, providing valuable insights for stakeholders.

E-commerce platforms face heightened challenges in post-pandemic, necessitating intensified customer retention efforts. Retaining existing customers is more cost-effective than acquiring new customers. Central to this endeavor is the quality of e-services, which profoundly influences customers’ likelihood of making repeat purchases. By exploring how different e-service dimensions—customer service, fulfilment, platform design, security/privacy, and trust—impact repurchase intentions, this study brings a new lens to understanding consumer behavior, particularly how gender shapes these relationships. Through purposive and convenience sampling, 200 responses were collected from online Malaysian shoppers. Data analysis conducted via PLS-SEM unveils the significant influences of customer service, fulfilment, and security/privacy on repurchase intentions. Notably, platform design and trust exert negligible influence, whereas security/privacy emerges as the primary driver of repurchase intention. Gender plays a pivotal role in moderating the effects of platform design and trust differently for male and female consumers. From a managerial perspective, e-commerce platforms must tailor their strategies to account for gender differences in customer preferences. For instance, investing in security/privacy measures is critical for both genders, while enhancing platform design and fulfilment processes may better attract female customers. On the other hand, focusing on customer service quality will improve retention among male shoppers.

Damping material performance influences the efficacy of vibration and noise reduction. However, traditional damping materials often have low damping peaks or narrow damping temperature ranges. In this study, a series of polyurethane (PU)/poly(ethylene methacrylate) (PEMA) composites were synthesised, in which the PU hard segments were varied using toluene diisocyanate (TDI), diphenylmethane diisocyanate (MDI), isophorone diisocyanate (IPDI), and hexamethylene diisocyanate. The soft segments comprised tetrahydrofuran homopolymer glycol. The influence of the hard-segment structure on the properties of the PU/PEMA composites was investigated by infrared spectroscopy, thermogravimetric analysis, dynamic mechanical thermal analysis, and other experimental methods. The performance mechanism was explored from a molecular perspective via integration with molecular dynamics simulations. The PU/PEMA material with IPDI hard segments comprised numerous microphase-separated structures and exhibited greater free volume, fuller molecular-chain movement, and the highest damping performance, with a loss factor of 0.56. The PU/PEMA composites synthesised with TDI and MDI hard segments exhibited better compatibility, with the MDI-PU/PEMA system exhibiting a higher hydrogen-bonding force. This material also exhibited a higher thermal stability, with an initial breakdown temperature of 287.87 °C. This study provides a basis for regulating and optimising the performance of PU-based damping materials.

Haematopoietic stem cells (HSC) and macrophages hold promise for cell-based therapy. Induced pluripotent stem cells (iPSC) offer an alternative to human embryonic stem cells (hESC) for generating haematopoietic cells in vitro, sidestepping ethical concerns. However, precise comparisons of the developmental process and productivity between iPSC and hESC during haematopoietic differentiation are limited, and producing sufficient HSC for clinical use remains challenging. We introduce a refined, simplified protocol that is xeno-, serum-, and feeder-free for differentiating fibroblast-derived human iPSC (NHDF-iPSC) and the hESC-H9 clone (H9-ESC) using the STEMdiff™ Hematopoietic kit, with differentiation extended by in-house cytokine addition. We demonstrate that NHDF-iPSC recapitulate the haematopoietic differentiation of H9-ESC, forming CD31⁺CD144⁺CD34⁺ haemogenic endothelia (HE) as intermediates, and producing CD34⁺CD43⁺CD45+/− haematopoietic stem and progenitor cells (HSPC). This protocol facilitates the production of CD34⁺ HSPC over an extended period and enhances the yield of HSC from NHDF-iPSC-derived HE three-fold. Interestingly, our results demonstrated that NHDF-iPSC outperformed H9-ESC by exhibiting superior differentiation capabilities, resulting in a higher abundance of HE and greater haematopoietic cell output (e.g., HSPC and HSC) upon cytokine stimulation. This phenomenon is presumably due to the higher expression of RUNX1 in NHDF-iPSC-derived HE (three-fold) as observed in our study, which may lead to a more productive endothelial-to-haematopoietic transition process and potentially facilitate the efficient production of haematopoietic cells. These CD34⁺ haematopoietic cells mature into 25F9⁺CD45⁺ macrophages, which exhibit comparable functions to those derived from hESC. Together, our results underscore the potential of iPSCs as a sustainable source for deriving HSC and macrophages for cell-based therapies. Graphical Abstract

The direct CO2 emissions of the cement production industry have increased significantly, accounting for approximately 7% of the CO2 emissions. Rice husk ash (RHA), an agricultural byproduct, has gained substantial interest as a commonly used supplementary cementitious materials (SCMs) and shows potential application in concrete. This study comprehensively examines existing literature on ternary and quaternary cementitious composites mixed with RHA, providing a detailed overview of their mechanical properties, durability, and CO2 emissions. Analysis shows that the use of combinations of RHA and other materials as SCMs improves the mechanical and durability properties of cementitious composites and reduces CO2 emissions during concrete production when compared with that of replacing aggregates. Specifically, the synergistic use of RHA and olive waste ash increases compressive strength by 58.7%, and the synergistic use of RHA and steel fiber increases flexural strength by 78.4%. The combination of RHA, steel fiber, and waste marble powder increases splitting tensile strength by 96.5%, and the synergistic use of RHA and bacteria increases water absorption resistance by 69% and chloride resistance by 83%. The combination of RHA and bacteria increases permeability resistance by 83%. Furthermore, the synergistic use of RHA and nano-CuO also increases permeability resistance by 51.88%. Finally, the synergistic use of RHA and fly ash achieves the optimal reduction in CO2 emissions. Consequently, considering the challenges of global warming and climate change, this comprehensive review can be a reference for further exploring the utilization of RHA in building materials.