Tendons transmit forces from muscles to bones through joints. Typically, tendons and muscles work together to innovate a motion. In addition, tendons are often subjected to much higher stresses than the muscles that they serve in any given action. As a result, tendons are susceptible to injuries that may lead to a permanent dysfunction in joint mobility due to the fact that the scar tissue that forms after healing often does not have the same mechanical properties of the original tissue. It is therefore very important to understand the mechanical response of tendons. In this paper the performances are examined of two viscoelastic standard nonlinear models in modelling the elastic and plastic behaviour of the tendon in the light of a well-known hyperelastic Yeoh model. The use of the Yeoh model is more for validating the performances of the viscoelastic models within the elastic region than for comparison purposes. The Yeoh model was selected based on its superior performance in modelling the elastic phase of soft tissue, as reported in previous studies, combined with its simplicity. The results show that the two standard nonlinear solid models perform extremely well both in fitting accuracies and in correlating stress results. The most promising result is the fact that the two standard nonlinear models can model tendon behaviour in the nonlinear plastic region. It is also noted that the two standard nonlinear models are physically insightful since their optimisation parameters can easily be interpreted in terms of tendon elasticity and viscoelastic parameters.

Many of mimic analogues synthesized before depending on the change in the structure of aromatic rings. In this work, the carbonyl group in the structure of compounds 1-4 converted to thiocarbonyl group, and then studying the toxicological activity due to chemical change in the active center of mimic analogues was performed for compounds N-tert-butyl-2,4-dichloro-N'-(2,4-dichlorobenzoyl)benzohydrazide (2) and N-tert-butyl-2,4-dichloro-N'-[(2,4-dichlorophenyl)carbonothioyl]benzenecarbothiohydrazide (6). The toxicological study was done by using 2nd and 4th instar larvae of the cotton leaf worm, Spodoptera littoralis (Boisd.). Five concentration levels (600, 300, 150, 75 and 37.5 ppm) of compounds (2) and (6) were applied on the fresh plant food to the newly grown (2^nd and 4^th) instar larvae.

This research determines to evaluate the level of implementing Total Quality Management (TQM) and examine the relationship between dimensions of TQM and Quality performance in the accredited Jordanian Private Hospitals. The study used a survey questionnaire as the main data collection. The total respondents used were 330, where 140 respondents were from five Private Jordanian Hospitals, resulting in a 42.4% response rate. The confirmatory factor analyses (CFA) and multiple linear regression were used to study data analyses. The results revealed that the level of TQM implementation in Private Jordanian Hospitals was high. Besides, a significant was found between TQM dimensions with quality performance. The study found that leadership commitment and Support to Quality, strategic quality planning, information and data, training and participation, customer focus, and continuous improvement have been found to have significant impacts on quality performance. This study can raise the attentiveness of the important strategy of TQM, which could help Hospitals managers have an enhanced understanding of the benefits of practicing TQM and therefore enable Quality Performance within their Hospitals.

Red jasmine rice is recognized as a healthy food with high phenolic compounds. These compounds present antibacterial and anti-free radical properties. Moreover, colored rice exhibits a biological activity against anticancer. Objectives of this study are 1) exploring a biological screening and cell viability of 70% ethanol and aqueous extracts of red jasmine rice, 2) investigating cytotoxicity to fibroblast NIH3T3 (IC80) that is one hundred cells were found cell viability 80 cells. Red jasmine rice extracts were dried and transformed into a powder using the freeze-drying method. The extracts were treated with fibroblast NIH3T3 for MTT. The highest of IC50 of red jasmine rice extract to scavenge the DPPH and ABTS radicals was found in ethanol extract (53.20±7.37 and 64.17±5.76, respectively). The experiment showed that the ethanol and aqueous extract of red rice did not show cytotoxicity to fibroblast NIH3T3 (IC80). The extracts of red rice show the biological screening of anti-oxidation with total phenolic compounds and flavonoid contents. Moreover, it does not modify the physical properties of the cream formula. It can be concluded that the red rice extract is highly promising for the value addition.

The rapid evolution of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) has profoundly influenced various domains, including portfolio optimization. In today’s dynamic and interconnected global economy, understanding the development of scientific publications in this field is crucial for both academics and practitioners. This paper aims to conduct a comprehensive bibliometric study of the scientific literature on portfolio optimization, focusing on the impact of AI, ML, and DL advancements. By analyzing key trends, influential publications, and emerging research areas, this study provides valuable insights into the progression of portfolio optimization research in the context of these transformative technologies, helping to map future directions and identify knowledge gaps in the field. This paper endeavors to present an exhaustive synthesis of the most recent advancements and innovations within the domain of portfolio optimization, particularly as influenced by progressive developments in AI, ML and DL from 1996 to 2024. Employing a rigorous bibliometric analysis, this study scrutinizes the structural and global paradigms governing this field. The analytical framework integrates several dimensions, including: (1) comprehensive dataset interrogation, (2) critical evaluation of source repositories, (3) contributions of seminal authors, (4) geographical and institutional affiliations, (5) document-centric analysis, and (6) exploration of keyword dynamics. A corpus of 745 bibliographic entries, meticulously curated from the Web of Science database, forms the basis of this inquiry, which utilizes advanced Scientometric network methodologies to extrapolate substantive research insights. The discourse culminates in a robust critique of the inherent strengths and methodological limitations, while delineating strategic avenues for future research, with the objective of steering ongoing scholarly discourse in the realm of portfolio optimization. The empirical outcomes of this study enhance the understanding of prevailing intellectual trajectories, thus laying a fortified foundation for future investigative pursuits in this critically evolving discipline.

The increasing variety of types of food circulating in Bekasi, has both positive and negative impacts at the same time. The positive impact is the increasing variety of food choices owned by Bekasi residents. In addition, the negative impact is that there is often no guarantee of halalness for the foods offered, both in terms of raw materials, processes and presentations. This study aims to determine the effect of internal control of raw materials and production planning on the smooth process of SMEs, especially based on halal food in Bekasi. The study involved 49 SME entrepreneurs in Bekasi and processed data using the multivariate statistical method and path analysis. The results show that in very specific cases, namely halal food products, internal control and production process planning had a positive influence on the smoothness of the production process and business competitiveness.

The power-law memory effect is taken into consideration in a generalisation of the economic model of natural growth. The memory effect refers to a process's reliance on its current state and its history of previous changes. However, the study that focuses on natural growth in economics considering the memory effect with fractional order-linear differential equation model is still limited. The current investigation seeks to solve the natural growth with memory effect in the economics model and decide the best model using fractional differential equation (FDE), namely Adomian Decomposition and Variational Iteration Methods. Also, this study assumes the level of consumer loss memory during a certain time interval denoted by a parameter (α). This study showed the model of loss memory effect with 0 < α ≤ 1 given a slowdown in output growth compared to a model without memory effect. Besides that, this study also found that output Y(t) is growing faster with the Variational Iteration method compared to the Adomian decomposition method. Also, using graphical simulation, this study found the output Y(t) is closer to the exact solution with α=0.4 and α=0.9. In conclusion, this study successfully solved natural growth with memory effect in economics and decided the best model between FDE, namely Adomian decomposition and Variational iterative methods using numerical analysis.

The 0-1 Multidimensional Knapsack Problem (MKP) is an NP-Hard problem that has many important applications in business and industry. However, business and industrial applications typically involve large problem instances that can be time consuming to solve for a guaranteed optimal solution. There are many approximate solution approaches, heuristics and metaheuristics, for the MKP published in the literature, but these typically require the fine-tuning of several parameters. Fine-tuning parameters is not only time-consuming (especially for operations research (OR) practitioners), but also implies that solution quality can be compromised if the problem instances being solved change in nature. In this paper, we demonstrate an efficient and effective implementation of a robust population-based metaheuristic that does not require parameter fine-tuning and can easily be used by OR practitioners to solve industrial size problems. Specifically, to solve the MKP, we provide an efficient adaptation of the two-phase Teaching-Learning Based Optimization (TLBO) approach that was originally designed to solve continuous nonlinear engineering design optimization problems. Empirical results using the 270 MKP test problems available in Beasley’s OR-Library demonstrate that our implementation of TLBO for the MKP is competitive with published solution approaches without the need for time-consuming parameter fine-tuning.

The production of ceramic creates scrap material that is often wasted. The aims of this study are to know the influence of size and material on scrap material and the role of accounting in managing the environment. The results show that product size and material used together have an effect on scrap material. Partial testing shows that only materials used have a positive and significant effect on the emergence of scrap materials. The accounting treatment is done by debiting Cash IDR 5,258,753.99 and crediting Work in Process-Raw Material Cost IDR 5,258,753.99. The cost of goods manufactured of ceramic products after accounting treatment for scrap material is lower than before. The selling price also decreased for the same product. The operating profit will increase IDR 5,013,038.64 (use original selling price) and decrease IDR 1,272,112.67 (use selling price after treatment for scrap material). The emergence of scrap material causes environmental problems. Environmental accounting overcomes this by removing scrap material from its place. The transfer is done by selling at a price of half the standard price. The proceeds from the sale are treated as a deduction from the cost of raw materials in an account in the Work in Process-Raw Materials Cost credit.

A series of some new pyrazole-substituted 7H-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazines was synthesized in this study. The structures of target substances were confirmed by using 1H and 13С NMR spectroscopy, mass spectrometry and elemental analysis. The synthesized compounds have been evaluated for antimicrobial activity against five bacterial strains (Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Staphylococcus aureus) and two fungal strains (Candida albicans and Cryptococcus neoformans). The antimicrobial screening studies of synthesized substances established that 2 of 12 compounds show pronounced antibacterial activity against the strain Staphylococcus aureus.