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This study assesses the performance of kenaf, bamboo, and polyester nonwoven web in various mattress filling formulations. The influence of moisture and compression qualities on the web structure with a predefined thickness and the number of stacking layers is evaluated. Carding and thermal bonding techniques were employed to create the kenaf/bamboo/polyester web. Physical properties such as thickness (ASTM D177-96), areal weight (ASTM D6242), density (ASTM D3776), and moisture content (ASTM D2495-01) were determined, while the compressive performance was evaluated according to ASTM D471-00. Compressive strength decreased with higher ratios of untreated bamboo to kenaf, whereas moisture content increased with both higher kenaf and treated bamboo ratios. The compressive strength of kenaf/bamboo/polyester nonwoven web was minimally impacted by the treated bamboo. Consequently, the areal weight and density of the web were significantly influenced by a predetermined characteristic; the number of stacking layers and thickness of the web. Evidence suggests that a composition of 30% kenaf, 20% bamboo and 50% polyester is the optimal ratio to obtain the firmest mattress filler, as it exhibited a compressive percentage of 39% at a force of 2kN.

Nowadays, awareness towards environmental issues increases significantly where people have learned the important of protecting environment for a better future. Thus, this study investigated the embedded kenaf fiber as a natural material with different of fire-retardant loading content towards the fire resistance properties and acoustical performance for insulator application in future building component. Based on the study conducted toward the prepared size 200 mm x 2000 mm x 40 mm of fixed kenaf composition with various fire retardant by 5 wt. % and increasing gradually to 25 wt. %, this study found that the highest value of thermal conductivity which is 0.4472 W/mK and temperature different of 240 °C for S1. Also, this study found the higher percentage of non-burn fiber which is 98.103 % for S6 and the highest peak of 0.9104 coefficient at 1259 Hz and at 1600 Hz with coefficient of 0.9091 for S3. This study showed that kenaf fiber embedded with different of fire-retardant loading content have a potential to replace the current insulator used in industry.

The application of multiple linear regression analysis has significantly increased in popularity among researchers, becoming a predominant model for the analysis of data associated with complex phenomena. This study specifically focuses on the prediction of breast cancer symptoms using linear regression. Data was collected from 569 breast cancer patients who received treatment at general hospital in Malaysia with the secondary data being recorded by nurses and doctors. To ascertain the factors influencing breast cancer, a research was conducted at general hospital in Malaysia, which examined four independent variables, each with various combinations of variable types. The primary aim of this study was to identify the factors that significantly influence breast cancer factors at general hospital. All collected data will be analyzed employing the Statistical Package for Social Science (SPSS) software method. The analysis will include tests for data normality and the calculation of coefficients to meet the study's objectives. The findings indicate that breast cancer severity is significantly influenced by radius, as determined through multiple linear regression analysis. The conclusion of this chapter will present a comprehensive summary of the research findings, as well as acknowledge the limitations of the study. Furthermore, recommendations for enhancing another predicting modeling techniques in future breast cancer research are included.

This study investigates the implications of an aging population on government spending in Malaysia using the Fully Modified Ordinary Least Squares (FMOLS) method. Employing data spanning from 1992 to 2022, the study examines the relationship between the dependent variable, Government Expenditure, and the independent variable, Aging Population, while controlling for Gross Domestic Product and Unemployment as additional factors. The results reveal a positive connection between the aging population and government expenditure. As Malaysia experiences demographic shifts characterized by increased life expectancy and declining fertility rates, the findings suggest that addressing the needs of an aging population contributes to higher government spending. This study underscores the importance of recognizing and addressing the fiscal implications of demographic changes, providing valuable insights for policymakers in formulating strategies to navigate the challenges posed by an aging society in Malaysia.

Fiber break because of third-party intrusion has become one of the challenges in maintaining the fiber-based communication link, especially those buried underground. Hence, we investigate the feasibility of using Distributed Acoustic Sensing (DAS) system to sense possible surrounding activities that might cause fiber break. This paper reviews the current digital signal processing (DSP) algorithm used in the DAS system designed to detect ground disturbance, highlighting the specific design parameters for each technique. These parameters include identification rate, classification accuracy, detection accuracy, training time, and signal-to-noise ratio (SNR). The algorithms used are near-field beamforming, phased-array beamforming, image edge detection, gaussian mixture model (GMM), gaussian mixture model - hidden Markov model (GMM-HMM), faster region-based convolutional neural networks (R-CNN), transfer learning, dual-stage recognition network, group convolutional neural network (100G-CNN), and support vector machine (SVM). By reviewing the existing techniques used in the DAS system for ground disturbance detection, we can determine the best DSP algorithm that should be implemented for fiber break prevention, enabling us to design a DAS system specifically for it in the near future.

In a previous amplifier setup, a Gallium co-doped Erbium fiber (Ga-EDF) with a length of 2 m has been used as a gain medium. The amplifier which was designed as a single-pass configuration, achieving a highest gain of 22.45 dB. In this paper, the Ga-EDF amplifier is designed as a double-pass setup. The gain and noise figure at the input signal’s wavelength of 1520 nm - 1580 nm is investigated at various input powers, which are from -30 dBm to 0 dBm. This study compares the performance of the amplifiers as it is pumped by a laser signal at the wavelength of 980 nm and 1480 nm, with a power of 140 mW. The amplifier obtained the highest gain of 36.62 dB and 35.77 dB for the pump wavelength of 980 nm and 1480 nm, respectively. The corresponding noise figures are 3.48 dB and 5.01 dB, which occurs at the input signal’s wavelength of 1555 nm. The results indicate that the double-pass Ga-EDF amplifier pumped at 1480 nm outperforms the single pass Ga-EDF amplifier by 15.08 dB, with a comparable noise figure. The results also show that the double-pass Ga-EDF’s performance are comparable at both pump wavelengths.

Traffic cameras remain the primary source data for surveillance activities such as congestion and incident monitoring. To date, State agencies continue to rely on manual effort to extract data from networked cameras due to limitations of the current automatic vision systems including requirements for complex camera calibration and inability to generate high resolution data. This study implements a three-stage video analytics framework for extracting high-resolution traffic data such vehicle counts, speed, and acceleration from infrastructure-mounted CCTV cameras. The key components of the framework include object recognition, perspective transformation, and vehicle trajectory reconstruction for traffic data collection. First, a state-of-the-art vehicle recognition model is implemented to detect and classify vehicles. Next, to correct for camera distortion and reduce partial occlusion, an algorithm inspired by two-point linear perspective is utilized to extracts the region of interest (ROI) automatically, while a 2D homography technique transforms the CCTV view to bird's-eye view (BEV). Cameras are calibrated with a two-layer matrix system to enable the extraction of speed and acceleration by converting image coordinates to real-world measurements. Individual vehicle trajectories are constructed and compared in BEV using two time-space-feature-based object trackers, namely Motpy and BYTETrack. The results of the current study showed about +/- 4.5% error rate for directional traffic counts, less than 10% MSE for speed bias between camera estimates in comparison to estimates from probe data sources. Extracting high-resolution data from traffic cameras has several implications, ranging from improvements in traffic management and identify dangerous driving behavior, high-risk areas for accidents, and other safety concerns, enabling proactive measures to reduce accidents and fatalities., Comment: 25 pages, 9 figures, this paper was submitted for consideration for presentation at the 102nd Annual Meeting of the Transportation Research Board, January 2023

Resources act as an arm which often facilitates firm’s sustainable performance in volatile business markets. Few studies have emphasized the agile operant resources that propel family-owned firm’s profitability. The aim of this article is to show the concealed role of agile operant resources of firm owners that expedite family-owned businesses in profitability to ensure a firm’s sustainability. This research uses relativistic perspective based on interpretive worldview. For data collection, purposive sampling is used. While directing interviews, open-ended questions (interview guide) along with observations are used. Abductive research accompanied by Gioia methodology has been utilized for broader themes of discussion. The findings indicated relationship proneness, reputational resources, religious resources, agile soft skills, performance efficiency and excellency as hidden agile intangible resources which facilitate family firms of catering profitability. The paper presents a conceptual framework that highlights how family-owned firms can ensure profitability. The proposed research framework contributes to the present literature of family-owned firms by inspecting the mystical role of agile resources. It opens new avenues for practitioners to work on these resources that support to enhance profitability., Los recursos funcionan como un arma que a menudo facilita el rendimiento sostenible de las empresas en un mercado empresarial volátil. Pocos estudios han enfocado los recursos operativos ágiles que impulsan la rentabilidad de las empresas familiares. El objetivo de este artículo es mostrar el papel oculto de los recursos operativos ágiles de los propietarios de empresas que aceleran la rentabilidad de las empresas familiares para garantizar la sostenibilidad de las empresas. Esta investigación se basa en una perspectiva relativista e interpretativa a nivel mundial. Para la recopilación de datos, se utiliza un muestreo intencional/judicial. Durante las entrevistas, se emplea un cuestionario abierto (guía de entrevistas) junto con observaciones. Se ha utilizado una investigación abductiva acompañada de la metodología de Gioia para ampliar los temas de discusión. Los resultados indicaron que la propensión a las relaciones, los recursos reputacionales, los recursos religiosos, las habilidades blandas ágiles, la eficiencia y excelencia en el rendimiento son recursos intangibles ágiles ocultos que facilitan la rentabilidad de las empresas familiares. Este artículo propuso un marco conceptual que guía a las empresas familiares para lograr rentabilidad. El marco propuesto contribuye a la literatura actual sobre empresas familiares al examinar el papel místico de los recursos ágiles y recomendar a los profesionales pulir estos recursos que ayudan a mejorar la rentabilidad, lo que lleva a la sostenibilidad de las empresas familiares.

In the past ten years, the increasing customer awareness of environmental sustainability has driven the development of green products. As the initiator of product development, this situation can challenge product designers. Since customers may have varied expectations and preferences for green products, it depends on the green attributes embedded in the product and cultural value influences. As the natural behavior setting, cultural value has been proven to influence customer preferences in the literature. However, it was identified that previous studies had not clearly defined the consideration of cultural values in green product design. Therefore, this study aimed to generate a conceptual framework for embedding cultural value consideration in green product design. A comprehensive review of green product design and cultural values has been performed to align the relevancies for constructing the conceptual framework. Bibliographic analysis using the PRISMA approach was also performed to identify the current trend of green product design. It was expected that the proposed conceptual framework could be used as supporting insight in determining the customers’ preferences as an essential process for green product development.

The difficulties in the communication between the deaf and normal people through sign language can be overcome by implementing deep learning in the gestures signal recognition. The use of the Convolution Neural Network (CNN) in distinguishing radar-based gesture signals of deaf sign language has not been investigated. This paper describes the recognition of gestures of deaf sign language using radar and CNN. Six gestures of deaf sign language were acquired from normal subjects using a radar system and processed. Short-time Fourier Transform was performed to extract the gestures features and the classification was performed using CNN. The performance of CNN was examined using two types of inputs; segmented and non-segmented spectrograms. The accuracy of recognising the gestures is higher (92.31%) using the non-segmented spectrograms compared to the segmented spectrogram. The radar-based deaf sign language could be recognised accurately using CNN without segmentation.

Sleep is often viewed by the general public as a “perceptual hole in time” where it is the period in which nothing productive occurs. However, sleep is an important part of health which affects mental and physical health. Sleep-disordered breathing (SDB) encompasses a range of respiratory disorders that are distinguished by intermittent pauses in breathing during the sleep cycle. This includes obstructive sleep apnoea (OSA), a global disease with a rising incidence along with its comorbidity. OSA creates an impact on the quality of life as it is associated with multiple negative implications which include neurocognitive problems and increases the risk of cardiometabolic diseases. This article illustrates the importance to determine the proportion of patients in the district of Sepang who are at high risk of obstructive sleep apnoea (OSA) and its determinants. Method: A cross-sectional study was carried out among individuals aged 18 years and above in Sepang district Malaysia. Using systematic random sampling, 521 participants were recruited. The questionnaire given gathered respondents information regarding their socio-demography, clinical profiles, and the STOP-BANG questionnaire was used to screen for OSA. Result: Almost a third of the participants (30.3%) were at risk of having OSA. It is found that the predictors for having OSA are menopausal women (AOR: 2.46; 95% CI: 1.22, 4.93; p = 0.011) and having large waist circumference measurement (AOR: 1.07; 95% CI: 1.04,1.10; p <0.001). Conclusion: The findings in this study will help healthcare workers to detect early patients at risk of OSA with the aid of STOP-BANG questionnaire.

Introduction: The number of patients diagnosed with hypertension among the population is rising rapidly. Its inherent risk of mortality is a grave cause of concern. Therefore, this study aims to determine the level of knowledge, attitude, practices and awareness on hypertension and associated factors among students and staff in the FMHS, Universiti Putra Malaysia. Methods: A cross sectional study was done at the FMHS, Universiti Putra Malaysia for 17 weeks duration in 2020. Through stratified random sampling, students and staff selected from the faculty answered a questionnaire distributed in Google Documents form via Whatsapp. The data was analyzed using the SPSS v25. Results: 340 students and 87 staff participated in our study. Overall, majority of the students and staffs demonstrated a good level of knowledge, attitude, practice and awareness of hypertension. In multivariate analysis, ethnicity shows a significant association with awareness among students. There was significant association between age with the level of practice of hypertension among staff, and between the field of staff with the level of practice and awareness of hypertension among the staff in multivariate analysis. Conclusion: Majority of the students and staffs demonstrated a good level of knowledge, attitude, practices and awareness among both staffs and students. This augurs well for this current and future health professionals in their battle in reducing the prevalence of hypertension.

Introduction: This study aimed to determine the prevalence of suspected depression and its associated factors among patients with hypertension in a Malaysian primary care clinic. Methods: This cross-sectional study was conducted in a primary care clinic from 1 June to 31 August 2019 using the Patient Health Questionnaire-9. Results: The prevalence of suspected depression was 9.0%. The significant predictors of depression were Indian ethnicity (adjusted odd ratio [AOR]: 2.373; confidence interval [CI]: 1.147–4.907), divorce (AOR: 3.5; CI: 1.243–9.860), singleness (AOR: 2.241; CI: 1.182–4.251), heavy episodic drinking (AOR: 7.343; CI: 2.494–21.624), low physical activity level (AOR: 1.921; CI: 1.093– 2.274), low fibre intake (AOR: 1.836; CI: 1.061–3.178), uncontrolled blood pressure (AOR: 1.800; CI: 1.134–2.858) and presence of hypertension complications (AOR: 3.263; CI: 2.053–5.185). Conclusion: Primary health care providers must screen for depression among patients with hypertension, particularly those within high-risk groups, and implement interventions that address modifiable risk factors.

This study investigates the dosimetric characteristics of a real-time radioluminescence (RL) Ge-doped optical fiber sensor, model LS-1000, providing measurement of absorbed dose in terms of counts in use of a computed tomography (CT) system. A CT dose index head phantom has been used as the reference tool. The response of the LS-1000 sensor has been compared against that of two other forms of dosimeter - a RaySafe X2 CT sensor (an ionization chamber system) and a Black Piranha CT dose profiler (a point dose solid-state detector). The three dosimeters have been irradiated in each of five available holes within the CT dose index head phantom. The results show RL response at the position of the peripheral holes of around 250 counts/gate for a gate time of 10 ms, while at the position of the central hole the response was 80 counts/gate. The maximum dose rate for the RaySafe X2 CT sensor has been found to be 5 mGy/s while that observed for the CT dose profiler was 6 mGy/s. In respect of CT applications, this trial of the luminescence device demonstrates that the germanium-doped optical fiber device may offer a promising alternative to conventional dosimeters, also allowing measurements at high accuracy and precision.

Since the start of the pandemic, there have been extensive studies from all over the world reporting on coronavirus disease 2019 (COVID-19)-associated neurological syndromes. Although initially thought of as primarily a respiratory pathogen, it became increasingly clear that the virus does have other systemic manifestations, including on the neurological system. Since then, the discovery of the many neuroimaging features of COVID-19-associated neurological syndromes have puzzled researchers and physicians in terms of interpretation, and how best to manage these findings to benefit patients. We sought to review the neuroimaging findings of COVID-19-associated neurological syndromes, particularly the vessel wall imaging (VWI) features, in the hope of finding a common feature that would better guide physicians in terms of further management of this group of patients. We will also look into the potential pitfalls of interpreting the VWI findings in these patients.

Bagworms, particularly Metisa plana Walker (Lepidoptera: Psychidae), are one of the most destructive leaf-eating pests, especially in oil palm plantations, causing severe defoliation which reduces yield. Due to the delayed control of the bagworm population, it was discovered to be the most widespread oil palm pest in Peninsular Malaysia. Identification and classification of bagworm instar stages are critical for determining the current outbreak and taking appropriate control measures in the infested area. Therefore, this work proposes an automatic classification of bagworm larval instar stage starting from the second (S2) to the fifth (S5) instar stage using a transfer learning-based framework. Five different deep CNN architectures were used i.e., VGG16, ResNet50, ResNet152, DenseNet121 and DenseNet201 to categorize the larval instar stages. All the models were fine-tuned using two different optimizers, i.e., stochastic gradient descent (SGD) with momentum and adaptive moment estimation (Adam). Among the five models used, the DenseNet121 model, which used SGD with momentum (0.9) had the best classification accuracy of 96.18 with a testing time of 0.048 s per sample. Besides, all the instar stages from S2 to S5 can be identified with high value accuracy (94.52“97.57), precision (89.71“95.87), sensitivity (87.67“96.65), specificity (96.51“98.61) and the F1-score (88.89“96.18). The presented transfer learning approach yields promising results, demonstrating its ability to classify bagworm instar stages.

Polyaniline (PANI) is one of the most promising conducting polymers to be used in several applications, owing to its easily synthesized, high surface area, cost-effectiveness, and tremendous electrical conductivity. In this research, 1 toluene-4-sulfonic acid monohydrate (PTSA) doped PANI film was fabricated using twelve different concentrations from 0.5 to 6 wt contents of N-methyl-2-pyrrolidone (NMP) as a solvent since the amount of NMP is still a vital aspect to recognize optimum combination. The chemical, optical, thermal, morphological, and electrical conductivity properties are investigated through Fourier transform infrared (FT-IR) spectroscopy, photoluminescence (PL) spectroscopy, ultraviolet-visible (UV“vis) spectroscopy, thermal gravity analysis (TGA), field emission scanning electron microscopy (FE-SEM) and Breuneur“Emmet“Teller (BET), then the four-point probe method. The existence of a hydrogen (H) bonding association between the C=O functional group within NMP and the N“H functional group throughout the PANI films will be shown using FT-IR analysis. Bandgap and PL intensity decreased with increasing NMP concentrations. FE-SEM displays the high-quality morphology of PANI can be achieved by increasing NMP concentrations. The specific electrical conductivity of prepared samples did not significantly change. The 1 PTSA and 3 NMP doped PANI is introduced as optimized PANI film with a low bandgap value of 2.54 (eV), high PL intensity, high specific surface area value of 121.457 (m2/g), and stable conductivity value of 2.45 ( cm)ˆ’1 owing to the arranged design of benzenoid and quinoid parts in its structure which seems a proper candidate to improve PANI film properties for use in sensing and supercapacitor applications.

In recent years, limited research has been conducted on enhancing DNA hybridization-based biosensor approaches using statistical models. This study explores the application of response surface methodology (RSM) to improve the performance of a DNA hybridization biosensor for dengue virus (DENV) detection. The biosensor is based on silicon nanowires decorated with gold nanoparticles (SiNWs/AuNPs) and utilizes methylene blue as a redox indicator. The DNA hybridization process between the immobilized DNA probe and the target DENV gene was monitored using differential pulse voltammetry (DPV) based on the reduction of methylene blue. Fourier-transform infrared spectroscopy (FTIR) and electrochemical impedance spectroscopy (EIS) were employed to confirm successful DNA hybridization events on the modified screen-printed gold electrode (SPGE) surface. Several parameters, including pH buffer, NaCl concentration, temperature, and hybridization time, were simultaneously optimized, with NaCl concentration having the most significant impact on DNA hybridization events. This study enhances the understanding of the role of each parameter in influencing DNA hybridization detection in electrochemical biosensors. The optimized biosensor demonstrated the ability to detect complementary oligonucleotide and amplified DENV gene concentrations as low as 0.0891 ng mL−1 (10 pM) and 2.8 ng mL−1 , respectively. The developed biosensor shows promise for rapid clinical diagnosis of dengue virus infection.

Background: Hepcidin is considered to play a central role in the pathophysiology of renal anemia. Recent studies in healthy individuals have demonstrated a suppressive effect of vitamin D (VD) on the expression of hepcidin. In this post-hoc analysis based on a randomized controlled study, we evaluated the effect of supplementing chronic kidney disease (CKD) patients (stage G3-G4) with a high daily dose of native VD on serum levels of hepcidin-25, the hepcidin/ferritin ratio, as well as on markers of erythropoiesis. Methods: Patients with CKD stage G3-G4 included in a double blind, randomized, placebo (PBO) controlled study with available hepcidin measurements were analyzed. Study subjects received either 8000 international units (IU) of cholecalciferol daily or PBO for 12 weeks. We evaluated the change in markers of hepcidin expression, erythropoiesis, and iron status from baseline to week 12 and compared the change between the groups. Results: Eighty five patients completed the study. Calcitriol, but not 25-hydroxyvitamin D (25(OH) D), was inversely correlated with serum levels of hepcidin-25 (rho = -0,38; p = < 0, 01 and rho = -0,02; p = 0, 89, respectively) at baseline. Supplementation with VD significantly raised the serum concentration of serum 25(OH)D in the treatment group (from 54 (39-71) to 156 (120-190) nmol/L; p = < 0, 01)) but had no effect on any of the markers of hepcidin, erythropoiesis, or iron status in the entire cohort. However, we did observe an increase in hemoglobin (HB) levels and transferrin saturation (TSAT) as compared to the PBO group in a subgroup of patients with low baseline 25(OH)D levels (< 56 nmol/L). In contrast, in patients with high baseline 25(OH)D values (>= 56 nmol/L), VD supplementation associated with a decrease in HB levels and TSAT (p = 0,056) within the VD group in addition to a decrease in hepcidin levels as compared to the PBO group. Conclusion: High-dose VD supplementation had no discernible effect on marker

Background and purpose: Several randomized trials have demonstrated the lack of effect of arthroscopic lavage as treatment for knee osteoarthritis (OA). These results have in turn resulted in a change in Swedish guidelines and reimbursement. We aimed to investigate the use of knee arthroscopies in Sweden between 2002 and 2016. Patient demographics, regional differences, and the magnitude of patients with knee OA undergoing knee arthroscopy were also analyzed. Patients and methods: Trends in knee arthroscopy were investigated using the Swedish Hospital Discharge Register (SHDR) to conduct a nationwide register-based study including all adults (>18 years of age) undergoing any knee arthroscopy between 2002 and 2016. Results: The total number of knee arthroscopies performed during the studied period was 241,055. The annual surgery rate declined in all age groups, for males and females as well as patients with knee OA. The incidence dropped from 247 to 155 per 105 inhabitants. Over 50% of arthroscopies were performed in metropolitan regions. Conclusion: We showed a dramatic decline in knee arthroscopy. There is variability in the surgery rate between males and females and among the regions of Sweden.

The main issue encountered in the food industry is the contamination and spoilage of food caused by microbes that result in food wastage and foodborne illness. Active food packaging is a new and innovative type of packaging that can help to solve this issue. Due to the consumer demands for environmentally friendly and sustainable packaging materials, the development of active food packaging material is now directed towards utilizing biopolymers and natural antimicrobial agents. Biopolymers such as starch are promising to be developed into food packaging material owing to their film-forming ability, biodegradability, and low cost. Hence, this work was directed towards exploiting starch for the production of active food packaging material that is environmentally friendly and sustainable. Cellulose nanofiber (CNF) which acts as a reinforcing compound was incorporated into the starch films, thus producing starch/CNF bionanocomposite films. Moreover, thymol, an antimicrobial agent was also added producing starch/CNF/thymol films. The films were produced using a solvent casting method and characterized in terms of mechanical, thermal, barrier, and antibacterial properties. The addition of CNF to the starch films was found to improve the mechanical, thermal, and barrier properties of the films. Meanwhile, the addition of thymol reduced the mechanical and barrier properties but increased the thermal stability of the films. The disc diffusion assay revealed clear inhibition zones of starch/CNF/thymol films against bacteria. A liquid culture analysis also confirmed the inhibitory effect of the films whereby there was a reduction in the number of bacteria in log CFU/mL. To demonstrate the application of the films, the films were applied in contact with meat slices and stored for 7 days. The meat samples in contact with the films containing thymol were less impacted by microbes than the films without thymol. In conclusion, this study will be advantageous to the agri-food and pa

The prediction of cryptocurrency prices is a hot topic among academics. Nevertheless, predicting the cryptocurrency price accurately can be challenging in the real world. Numerous studies have been undertaken to determine the best model for successful prediction. However, they lacked correct results because they avoided identifying the critical features. It is important to remember that trends are critical features in time series to obtain data information. A dearth of research demonstrates that the cryptocurrency trend comprises linear and nonlinear patterns. Therefore, this study attempted to fill this gap and focused on modelling and forecasting trends in cryptocurrency. This study examined the linear and nonlinear dependency trend patterns of the top five cryptocurrency closing prices. The weekly historical data of each cryptocurrency were taken at different periods due to the availability of data on the system. In achieving its goal, this study examined the results by plotting based on residual trend and diagnostic statistic checking using three deterministic methods: linear trend regression, quadratic trend, and exponential trend. Based on the minimum Akaike Information Criterion (AIC), the result showed that the top five cryptocurrency closing price data series contained nonlinear and linear trend patterns. The information of this study will assist traders and investors in comprehending the trend of the top five cryptocurrencies and choosing the suitable model to predict cryptocurrency prices. Additionally, accurately measuring the forecast will protect investors from losing their investment.

This work aims to evaluate the potential of bamboo/polyester blended needle-punched nonwoven batts as thermal insulators. This research investigated the effects of physical properties on the thermal resistance and the bursting strength subjected to the different number of layers of the batt structure. Bamboo/polyester nonwoven batt was prepared by using a needle-punching technique. The nonwoven batt was made into single, two and three-layers structures termed as 1BP, 2BP and 3BP. Physical properties such as thickness, areal weight, density and porosity were determined to evaluate their relationship with thermal resistance and bursting strength. The properties of bamboo/polyester nonwoven batt were compared with that of polyester nonwoven batt commercially used as insulation layers in comforters. The thermal resistance and bursting strength were found to increase with the increased number of layers and were better than the commercial sample. The ranking shows that density and porosity have the most effect on thermal resistance and bursting strength, followed by areal weight and thickness. High and significant Pearson’s correlation coefficient and P-value indicated that density and porosity are the parameters that mainly influence the thermal resistance of the nonwoven batt. On the other hand, the number of layers was the most influential parameter for bursting strength. Based on the findings, 3BP nonwoven batts exhibited better thermal insulation performance and better strength with the value of 0.2932 m2 K/W and 3.78 kgf, respectively. In comparison, the commercial polyester nonwoven batt recorded a thermal resistance value of 0.2390 m2 K/W and bursting strength of 2.92 kgf.

Factors for initiating hibernation are unknown, but the condition shares some metabolic similarities with consciousness/sleep, which has been associated with n-3 fatty acids in humans. We investigated plasma phospholipid fatty acid profiles during hibernation and summer in free-ranging brown bears (Ursus arctos) and in captive garden dormice (Eliomys quercinus) contrasting in their hibernation patterns. The dormice received three different dietary fatty acid concentrations of linoleic acid (LA) (19%, 36% and 53%), with correspondingly decreased alpha-linolenic acid (ALA) (32%, 17% and 1.4%). Saturated and monounsaturated fatty acids showed small differences between summer and hibernation in both species. The dormice diet influenced n-6 fatty acids and eicosapentaenoic acid (EPA) concentrations in plasma phospholipids. Consistent differences between summer and hibernation in bears and dormice were decreased ALA and EPA and marked increase of n-3 docosapentaenoic acid and a minor increase of docosahexaenoic acid in parallel with several hundred percent increase of the activity index of elongase ELOVL2 transforming C20-22 fatty acids. The highest LA supply was unexpectantly associated with the highest transformation of the n-3 fatty acids. Similar fatty acid patterns in two contrasting hibernating species indicates a link to the hibernation phenotype and requires further studies in relation to consciousness and metabolism., Funding agencies:Westman FoundationCIMEDUniversity of Veterinary Medicine Vienna and the Austria Science Fund (FWF) P27267-B25 P31577-B25

The most common type of accident on the road is a rear-end crash. These crashes have a significant negative impact on traffic flow and are frequently fatal. To gain a more practical understanding of these scenarios, it is necessary to accurately model car following behaviors that result in rear-end crashes. Numerous studies have been carried out to model drivers' car-following behaviors; however, the majority of these studies have relied on simulated data, which may not accurately represent real-world incidents. Furthermore, most studies are restricted to modeling the ego vehicle's acceleration, which is insufficient to explain the behavior of the ego vehicle. As a result, the current study attempts to address these issues by developing an artificial intelligence framework for extracting features relevant to understanding driver behavior in a naturalistic environment. Furthermore, the study modeled the acceleration of both the ego vehicle and the leading vehicle using extracted information from NDS videos. According to the study's findings, young people are more likely to be aggressive drivers than elderly people. In addition, when modeling the ego vehicle's acceleration, it was discovered that the relative velocity between the ego vehicle and the leading vehicle was more important than the distance between the two vehicles.

Real-time traffic and sensor data from connected vehicles have the potential to provide insights that will lead to the immediate benefit of efficient management of the transportation infrastructure and related adjacent services. However, the growth of electric vehicles (EVs) and connected vehicles (CVs) has generated an abundance of CV data and sensor data that has put a strain on the processing capabilities of existing data center infrastructure. As a result, the benefits are either delayed or not fully realized. To address this issue, we propose a solution for processing state-wide CV traffic and sensor data on GPUs that provides real-time micro-scale insights in both temporal and spatial dimensions. This is achieved through the use of the Nvidia Rapids framework and the Dask parallel cluster in Python. Our findings demonstrate a 70x acceleration in the extraction, transformation, and loading (ETL) of CV data for the State of Missouri for a full day of all unique CV journeys, reducing the processing time from approximately 48 hours to just 25 minutes. Given that these results are for thousands of CVs and several thousands of individual journeys with sub-second sensor data, implies that we can model and obtain actionable insights for the management of the transportation infrastructure., Comment: Presented at the 102nd Transportation Research Board (TRB) Annual Meeting

Identifying unusual driving behaviors exhibited by drivers during driving is essential for understanding driver behavior and the underlying causes of crashes. Previous studies have primarily approached this problem as a classification task, assuming that naturalistic driving videos come discretized. However, both activity segmentation and classification are required for this task due to the continuous nature of naturalistic driving videos. The current study therefore departs from conventional approaches and introduces a novel methodological framework, DeepSegmenter, that simultaneously performs activity segmentation and classification in a single framework. The proposed framework consists of four major modules namely Data Module, Activity Segmentation Module, Classification Module and Postprocessing Module. Our proposed method won 8th place in the 2023 AI City Challenge, Track 3, with an activity overlap score of 0.5426 on experimental validation data. The experimental results demonstrate the effectiveness, efficiency, and robustness of the proposed system.

This work evaluates the impact of time step frequency and component scale on robotic manipulation simulation accuracy. Increasing the time step frequency for small-scale objects is shown to improve simulation accuracy. This simulation, demonstrating pre-assembly part picking for two object geometries, serves as a starting point for discussing how to improve Sim2Real transfer in robotic assembly processes., Comment: 3 pages, 3 figures, Best Poster Finalist at the 2023 Robotics and AI in Future Factory Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Video presentation [https://www.youtube.com/watch?v=JOXrBpMmI0A]. Robotics and AI in Future Factory workshop [https://sites.google.com/view/robot-ai-future-factory/]

Background : Malaria is still a major public health threat in some parts of the world. Many countries are targeting to achieve malaria free status country. This study aimed to determine the sero-prevalence of malaria and the knowledge, attitudes and practices relating to the prevention of malaria among the indigenous adults living in the central forest spine in Peninsular Malaysia. Methods: A mixed method study was conducted in indigenous settlements in 2020. Blood film for malaria parasite (BFMP) was used to diagnose malaria in this study. A structured questionnaire was used to collect data from the participants. For the qualitative data, in-depth interviews were conducted and data was collected until data saturation was reached. Multiple linear regression was used to determine the predictors after adjusting for confounders. A p-value of < 0.05 is considered as statistically significant. Meaningful statements from the in-depth interviews were assigned to the relevant codes using NVivo version 12 software. Results: A total of 284 indigenous people participated in the study. The prevalence of malaria in this study was 0%. Those in the middle age group between 25 and 41 years and tested positive for malaria previously were significantly more likely to have better knowledge and attitude scores. Significant correlations were also observed between knowledge-attitude and knowledge-practice. For the qualitative results, most of the respondents were unsure of monkey malaria, but all were aware of human malaria. Conclusion: The present study highlighted the absence of malaria in the study population and relatively good knowledge, attitudes and practices relating to the prevention of malaria.

Gross domestic product (GDP) is an important indicator for determining a country’s or region’s economic status and development level, and it is closely linked to inflation, unemployment, and economic growth rates. These basic indicators can comprehensively and effectively reflect a country’s or region’s future economic development. The center of radial basis function neural network and smoothing factor to take a uniform distribution of the random radial basis function artificial neural network will be the focus of this study. This stochastic learning method is a useful addition to the existing methods for determining the center and smoothing factors of radial basis function neural networks, and it can also help the network more efficiently train. GDP forecasting is aided by the genetic algorithm radial basis neural network, which allows the government to make timely and effective macrocontrol plans based on the forecast trend of GDP in the region. This study uses the genetic algorithm radial basis, neural network model, to make judgments on the relationships contained in this sequence and compare and analyze the prediction effect and generalization ability of the model to verify the applicability of the genetic algorithm radial basis, neural network model, based on the modeling of historical data, which may contain linear and nonlinear relationships by itself, so this study uses the genetic algorithm radial basis, neural network model, to make, compare, and analyze judgments on the relationships contained in this sequence.

Introduction: Human immunodeficiency virus (HIV)-related stigmatisation and discrimination adversely affect health outcomes in terms of timely diagnosis, treatment and care. Despite global efforts, they remain common among healthcare workers worldwide. In Malaysia, family medicine specialists are entrusted with the care of HIV patients at the primary care level. This study aimed to assess HIV-related knowledge, acts of discrimination, stigmatising attitudes and their associated factors among family medicine trainees in Malaysia. Methodology: This cross-sectional study was conducted among 397 family medicine trainees in Malaysia using a validated, self-administered questionnaire that assessed the participants’ sociodemographic information, HIV/AIDS knowledge, stigmatising attitudes (attitudes of blame, attitudes towards imposed measures, comfort in dealing with HIV patients) and acts of discrimination. Results: The most common stigmatisation was “attitudes of blame” (mean [SD] score: 3.0 (0.74); range score:1–5), and the most frequent discriminatory act was breaching patient confidentiality (54.9%). Around 82.1% had good knowledge of HIV/AIDS. Married participants and participants who had 7 years or less in service were more stigmatising in “attitudes of imposed measures” towards people living with HIV (p=0.006). Conclusion: Family medicine trainees exhibited stigmatisation and discrimination towards HIV patients despite having good HIV knowledge. Hence, appropriate and concerted health education should be given to all family medicine trainees to eliminate stigmatisation and discrimination.

Background: Despite rapid advances in acute ischaemic stroke (AIS) management, many healthcare professionals (HCPs) might not be aware of the latest recommended management of AIS patients. Therefore, we aimed to determine the level and factors associated with AIS management knowledge among Malaysian HCPs. Methods: This cross-sectional online questionnaire study was conducted nationwide among 627 HCPs in Malaysia using the Acute Stroke Management Questionnaire (ASMaQ). Multiple logistic regression was used to predict the relationship between the independent variables (age, gender, years of service, profession, work setting, work sector, seeing stroke patients in daily practice, and working with specialists) and the outcome variable (good vs poor knowledge). Results: Approximately 76% (95% CI [73–79%]) of HCPs had good overall knowledge of stroke. The highest proportion of HCPs with good knowledge was noted for General Stroke Knowledge (GSK) [88.5% (95% CI [86–91%])], followed by Advanced Stroke Management (ASM) [61.2% (95% CI [57–65%])] and Hyperacute Stroke Management (HSM) [58.1% (95% CI [54–62%])]. The odds of having poor knowledge of stroke were significantly higher among non-doctor HCPs [adjusted OR = 3.46 (95% CI [1.49–8.03]), P = 0.004]; among those not seeing stroke patients in daily practice [adjusted OR = 2.67 (95% CI [1.73–4.10]), P < 0.001]; and among those working without specialists [adjusted OR = 2.41 (95% CI [1.38–4.18]), P = 0.002]. Conclusions: Stroke education should be prioritised for HCPs with limited experience and guidance. All HCPs need to be up-to-date on the latest AIS management and be able to make a prompt referral to an appropriate facility. Therefore, more stroke patients will benefit from advanced stroke care.

This study attempts to identify Malaysian youth's interest in anime culture and one of its subcultures, Virtual YouTubers (VTubers). Anime, manga and drama series count amongst the most popular and well-received types of Japanese popular culture since the 1990s, where their translation into various languages have rendered them globally renowned. A plethora of studies have been done on anime and manga globally. However, studies on its subculture, VTubers, an online platform that uses a digital avatar generated using computer graphics, are still scarce, particularly in the Malaysian context. A total of 104 respondents participated in an online survey conducted using Google Forms. The respondents comprised Japanese language students from two public universities in Malaysia. Some of the respondents are members of a Japanese Cultural Club from one of the universities. The survey was divided into three sections: respondents' background, respondents' interest in anime culture, and their interest in VTubers. The results showed that the most popular culture is anime, followed by manga, song and seiyuu (voice actor/actress). The most well-liked anime genre is fantasy, followed by humour, love stories (romance), and mystery. Most of the respondents knew the word "VTuber" from anime, friends, and internet platforms such as YouTube. The numbers proved that VTubers are a significant and famous product of Japanese culture among Japanese culture enthusiasts, and will likely gain extensive traction in the future.

This work aims to evaluate the potential of bamboo/polyester blended needle-punched nonwoven batts as thermal insulators. This research investigated the effects of physical properties on the thermal resistance and the bursting strength subjected to the different number of layers of the batt structure. Bamboo/polyester nonwoven batt was prepared by using a needle-punching technique. The nonwoven batt was made into single, two and three-layers structures termed as 1BP, 2BP and 3BP. Physical properties such as thickness, areal weight, density and porosity were determined to evaluate their relationship with thermal resistance and bursting strength. The properties of bamboo/polyester nonwoven batt were compared with that of polyester nonwoven batt commercially used as insulation layers in comforters. The thermal resistance and bursting strength were found to increase with the increased number of layers and were better than the commercial sample. The ranking shows that density and porosity have the most effect on thermal resistance and bursting strength, followed by areal weight and thickness. High and significant Pearson’s correlation coefficient and P-value indicated that density and porosity are the parameters that mainly influence the thermal resistance of the nonwoven batt. On the other hand, the number of layers was the most influential parameter for bursting strength. Based on the findings, 3BP nonwoven batts exhibited better thermal insulation performance and better strength with the value of 0.2932 m2 K/W and 3.78 kgf, respectively. In comparison, the commercial polyester nonwoven batt recorded a thermal resistance value of 0.2390 m2 K/W and bursting strength of 2.92 kgf.

Wind energy is considered one of the fastest-growing and most used renewable energy sources which can produce electricity without any harm to the environment. However, the application of wind energy is not thoroughly undertaken all over the world. In this study, wind characteristics and wind energy potentials in three different wind stations in Peninsular Malaysia located in Chuping, Kuantan, and Melaka have been analysed at different altitudes starting from the standard 10 m height up to 150 m height above sea level. Wind speed seasonable variations and prevailing wind directions are also thoroughly studied. The analysis technique was based on two-parameter Weibull distribution function over three recent consecutive years starting from 2018 up to 2020 to identify the potentiality of the wind as a source of energy generation in these respective sites. The results show that the monthly highest mean wind speeds were 4.42 m/s, 2.96 m/s, and 2.17 m/s in Melaka, Kuantan, and Chuping, respectively. The highest most probable wind speed was 4.70 m/s and the wind speed carrying maximum energy was 1.74 m/s, both occurred in Melaka in 2019. The yearly highest Weibull shape parameter was 1.69 and the scale parameter was 2.96 m/s. Among the three stations studied, Melaka has shown the highest wind power potentials with an average value of 26.10 W/m2, followed by Kuantan with 12.71 W/m2 and Chuping with 6.80 W/m2 wind power densities. The corresponding wind energy densities were 595.58 kWh/m2/year, 111.37 kWh/m2/year, and 228.65 kWh/m2/year for Chuping, Kuantan, and Melaka stations respectively. The prevailing wind directions are northeast at both Kuantan and Melaka stations, and west and southwest direction at Chuping station. It is therefore concluded that although the potential of the wind power of the sites covered in the present study is considerable, they are suitable for small-scale power generation applications only

This study aims to treat kaolin synthetic wastewater by using sludge from water treatment plant as a coagulant via the coagulation process. Water treatment sludge (WTS) was characterized by using Fourier transform infrared (FTIR), Scanning electron microscope (SEM), and X-ray diffraction (XRD). WTS had an amorphous structure and contained high aluminium metal constituents at 25.3%, which can be recovered as a coagulant. Acidification was conducted to recover the aluminium in WTS using sulphuric acid and produced water treatment sludge coagulant (WTSC). The optimum condition of WTSC prepared from WTS was evaluated through sludge concentration and acid dosage parameters. It has been observed that 0.5% sludge concentration acidified with 0.08 ml/ml sulphuric acid and normality constant at 0.5N was the optimum condition as it can remove turbidity at 99.5%. The performance of WTSC in the coagulation process using a standard jar test was studied based on the effect of pH and dosage of coagulant. The highest percentage turbidity removal (98.66%) was obtained at pH 12, kaolin turbidity was 117NTU, and WTSC dosage at 40mg/L. The percentage turbidity removal for alum and WTSC was almost similar. Thus, WTSC can potentially replace alum as a coagulant in water treatment plant (WTP).

Work environment in highway construction are hazardous due to the particular dynamic and limited workspace availability. Within highway work zones, a variety of encounters involving employees, passing cars, and moving construction equipment exists, creating risky situations that may result in injury or death. Active approaches, such as the deployment of intrusion detection and alert devices in highway employees and the construction and maintenance of transportation infrastructure, can be effective in reducing these unforeseen situations. The study focus on development of the emergency signal system for the safety of highway workers was carried out to prevent accidents or danger from happening in the straight emergency line on the highway by developing a system of hazard detectors using a distance sensor. Therefore, the development of the Signal Warning Detector (SWAD) for the safety of highway workers was carried out to prevent accidents or danger from happening in the straight emergency line on the highway by developing a system of hazard detectors using a distance sensor. The distance sensor sensed the target at a certain distance and transmitted the signal emitted through the siren device and the emergency lamp mounted on the PLUS Malaysia Berhad (PLUS) car, while the signal was also transmitted to the receiver to create a danger signal to alert the worker by vibrating the vibrator motor located at the worker's hand. The study findings show that commercially accessible technologies have the ability to improve employee health in the work zone by providing early signal warning as vibration. This study adds to the knowledge base by offering methods for the collection and application of intruder sensing technologies for active protection in the work zone. The data produced in the result reveals that by performing the study, it was possible to find the best parameter setting for the Danger Signal Detector system. The farthest distance observed was at 14° of angle, 2.2