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Cost comparison for non-seismic and seismic design of a rectangular building structure located on different soil types based on Malaysian annex
(2021-07-27)
Toh, Wei Jian
Malaysia is situated in an earthquake-free zone. However, due to incidents that questioned the integrity of the existing buildings that were designed without considering seismic load, the construction industry in Malaysia will be adopting Malaysian National Annex (NA) to Eurocode 8 (EC 8). However, there is limited information on the material cost change if earthquake resistant design implemented in Malaysia. Objective of this study are to determine the cost difference between building structure with seismic and non- seismic design and to evaluate the effect of different soil type to the overall material cost of the main building structural frame. Five types of RC building frame categorised as 10 storeys, 15 storeys, 20 storeys, 25 storeys and 30 storeys were analysed and designed using ETABS software. The reinforced concrete building designed based on EC 2 and redesigned according to EC 8 with peak ground acceleration, αgR 0.06g reflecting the low seismic zone in Malaysia for ductility class low (DCL) and also with soil type A, D and E which reflecting the common soil type in Malaysia. The results showed that overall cost for building models situated on soil type A and subjected to seismic load decreased in the range of 3% - 13% compared to the non-seismic design. Soil type D showed an increase in the percentage difference from 10 storeys until 25 storeys, which is in the range of 2% - 15%. After 25 storeys, the percentage difference of cost of material was found to reduce by 2% for 30 storeys. Other than that, soil type E showed an increase in the percentage difference from 10 storeys until 20 storeys, which is in the range of 0% - 8%. The percentage difference of cost of material tends to reduce by 3% -7 % on 25 storeys onward. This is due to the significant wind load effect on high-rise building. It can be concluded that building models situated soil type D showed the highest increase in the cost among the soil types compared to non-seismic design due to the high value of base shear force, Fb and spectral acceleration at the fundamental period T1.
Evaluation of sputtering process parameters on microstructural properties and silicon precipitate of aluminium-silicon-copper films
(2025-09-01)
Devah S/O Kalai Selvam
Silicon (Si) precipitates in Aluminium-Silicon-Copper (AlSiCu) bond pad metallization can cause interlayer dielectric (ILD) cracking during Copper (Cu) wire bonding, reducing device reliability. This study investigated the influence of sputtering process parameters such as deposition temperature, degas cooling, and post-deposition cooling rate on Si precipitate behaviour and film integrity. The Design of Experiments was performed using three factors: Deposition Temperature (60 °C, 120 °C, 180 °C, and 240 °C), Degas Cooling (with and without), and Cooling Rate (rapid and slow). Eight experimental conditions (Samples A–H) were evaluated for surface defect inspection, wafer stress, surface roughness, grain size, Si precipitate size and count, and electrical yield. Statistical analysis confirmed that deposition temperature is the dominant factor, significantly affecting Si precipitate size and count, grain growth, surface roughness, and wafer stress. Elevated deposition temperatures (240 °C) enhanced atomic mobility, resulting in larger grains and partial stress relaxation but also rougher surfaces and pronounced Si segregation. Cooling rate was identified as a secondary parameter, with slow cooling reducing wafer stress and producing smoother surfaces, while degas cooling showed only minor contributions, limited to surface roughness. Among the tested conditions, low deposition temperature (60 °C) combined with degas cooling and rapid post-deposition cooling produced the most favourable outcome, yielding fine grains (~6 μm), smooth morphology (~25–28 nm RMS), minimal Si precipitate (~950 nm average size, ~8 counts/region), and low wafer stress (~120 MPa). Despite microstructural variations, electrical yield remained consistently high (>98%), indicating that Si precipitate primarily impacts mechanical reliability rather than electrical performance. Overall, this study demonstrates a clear correlation between sputtering parameters and AlSiCu film properties, showing that precise control of deposition temperature combined with optimized cooling strategies is essential to suppress Si precipitate and improve bond pad stability. These findings provide a practical basis for tailoring sputtering conditions to achieve reliable metallization with reduced bonding failures.
The effects of combined omega-3 and vitamin d supplementation on nutritional status, quality of life and inflammatory biomarkers among the breast cancer women in gaza strip, Palestine: a randomised controlled trial
(2025-01)
Almassri, Heba F. H.
Breast cancer (BC) is a leading cause of cancer-related mortality worldwide, particularly among women. Early nutritional care is essential to prevent cancer cachexia, improve overall health, and enhance the quality of life (QoL) for BC patients. This study aimed to assess the impact of omega-3 fatty acids (ω3) and vitamin D3 (VitD) supplementation on nutritional status, QoL, blood biomarkers, and dietary intake in newly diagnosed BC women in Gaza, Palestine. In this 9-week randomized, controlled, open-labelled trial, 96 participants were recruited and randomly assigned to one of four groups: i) ω3 group, ii) VitD group, iii) ω3+VitD group, and iv) control group. The intervention groups received either two daily 300mg ω3 capsules and/or one weekly 50,000 IU VitD tablet. Outcome measures included patient-generated subjective global assessment (PG-SGA) scores, anthropometric measurements, dietary intake analysis via 24-hour recall, and QoL assessments using the EORTC QLQ-C30 and QLQ-BR23, serum albumin, serum tumour necrosis factor-alpha (TNF-α), serum high-sensitive C-reactive protein (hsCRP). Of the total 96 participants, 88 had completed at the end of study, achieving a 91.7% response rate. There was a significant increase in PG-SGA-derived nutritional risk scores (p<0.01), body weight, and body mass index (BMI) (both p<0.05) in the ω3+ VitD group compared to other groups. Furthermore, there was a significant rise in blood albumin levels (p< 0.05) compared to baseline in the ω3+ VitD group. Dietary nutrient intake analysis demonstrated substantial increases in daily energy and protein intake in both the ω3+VitD group and the ω3 group alone (both p<0.05) compared to the baseline. Significant differences in total global health status (p<0.01) among ω3+VitD group were observed compared to other groups, and women in the ω3+ VitD group reported significantly higher functional scores (all p<0.05), and lower scores for fatigue (p<0.01), nausea and vomiting, pain, and appetite loss (all p<0.05), compared to the baseline. Notably, the ω3+ VitD group showed a significant reduction in serum hsCRP and TNF-α (both p<0.05) from the baseline, and significant differences in TNF-α (p<0.05) and hsCRP (p< 0.001) were noted between groups at the trial's end. Overall, combined ω3 and VitD supplementation significantly improved nutritional status, QoL, and inflammatory markers among BC women who had undergoing an active treatment. These findings highlight the potential use of ω3 and VitD supplements as an effective adjuvant therapy in BC patient management, improving health outcomes and reducing inflammation, particularly in resource-limited settings. Hence, tailored nutritional guidelines and interventions are crucial for optimizing their nutritional care integration into the medical oncology care.
Machine learning application in predicting anterior cruciate ligament injury among basketball players
(2025-01)
Longfei, Guo
Anterior cruciate ligament (ACL) injury is among the most prevalent injuries in athletes, significantly impacting their competitive performance. Preventing ACL injury is challenging due to their multifactorial nature. Machine learning-based data mining techniques have shown significant potential in identifying risk factors associated with ACL injury. This study aimed to assess the predictive capability of these features using machine learning models. Data on athlete’s profile, physical function, specialized qualities, three-dimensional movement analysis, and simultaneous electromyography were prospectively collected from 104 male basketball players. A one-year follow-up was conducted to monitor ACL injury, identifying n=11 injured players. Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. The optimal model was selected based on the mean area under the receiver operating characteristic curve (AUC-ROC) across 10 cross-validation runs and was used with Shapley Additive exPlanations to analyze the risk factors. The results show that AUC-ROC values varied slightly across repetitions and methods (0.66-0.80), the best classifier was RF. SHAP analysis identified key feature with the highest predictive value for ACL injury during specific sports motions. Emergency Stop phase: Increased knee flexion moment, posterior ground reaction forces, knee flexion angle, and overactivation of the lateral quadriceps and rectus femoris. Initial Acceleration phase: Elevated knee internal rotation torque and lateral stress on the lower limbs. Side-Cutting phase: Reduced tibial inclination and hip flexion angles, increased ankle inversion angle, ankle eversion moment, and excessive lateral thigh muscle activation. Furthermore, poor stability in the non-dominant leg, weak Squat Jump performance, training loads exceeding 15 hours per week, and prior injury history were significant ACL injury predictors. This study emphasizes the Machine Learning model's effectiveness in predicting ACL injury, highlighting biomechanical metrics, functional attributes, and historical feature as critical predictors for targeted prevention strategies.
Characterisation and anti-asthmatic effects of polysaccharides from lignosus rhinocerotis in an acute airway inflammation model
(2024-09)
Rosdan, Bushra Solehah Mohd
murine model of asthma. Female BALB/c mice were sensitised with ovalbumin (OVA) and aluminium hydroxide at day 0 and day 14, followed by OVA challenges from day 21 to day 27. LRP (1, 10 and 100 mg/kg) and dexamethasone (DEX) (0.25 mg/kg) were administered intranasally following each challenge, with a normal group receiving only PBS treatment. Bronchoalveolar lavage fluid (BALF) was collected for cytokine analysis and differential blood count, serum for immunoglobulin E (IgE), lungs for histopathological, immunohistopathological and gene expression. The findings revealed that LRP exhibited a semi-crystalline structure primarily composed of glucose, with the predicted structural elements of →4)-α-D-Glcp-(1→ and →3)-β-D-Glcp-(1→. Cell viability studies demonstrated that LRP had no cytotoxic effects on Vero cell lines over 24-48 hours of treatment, with cell viability remaining above 80 %. LRP treatments significantly reduced Th2 cytokines production and IgE levels (p<0.05). Histological assessment revealed a decrease in inflammatory cell infiltration, mucus production, and TGF-β1 expression in the lungs of LRP treatment groups. Furthermore, gene expression analysis exhibited reduced COX-2, iNOS and Muc5ac expression in LRP treatment groups, with iNOS exhibiting a significant reduction. In conclusion, LRP has the potential to mitigate allergic inflammation in an OVA-challenged murine model, offering potential as an alternative approach for managing allergic asthma.