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This paper develops an innovative Objective-based Survival Individual Enhancement approach for the Chimp Optimization Algorithm (OSIE-CHOA) designed to enhance financial accounting profit prediction using information systems. The OSIE-CHOA focuses on improving the search process by simultaneously elevating the fitness of under-performing individuals within a population and strengthening the diversity among the top-performing ones. Within the OSIE-CHOA, we identify the four most promising chimps during each iteration. Subsequently, half of the highest-performing chimps are selected for elimination and repositioning around these fortunate individuals, with an equal probability assigned to each chimp. According to the experimental findings, it is clearly seen that OSIE-CHOA considerably enhances prediction accuracy, allowing a decrease in the root mean square error (RMSE) by 15% and the mean absolute error (MAE) by 18% compared to the traditional CHOA. Moreover, OSIE-CHOA shows a convergence rate that is 20% higher, which makes it a good and efficient tool for financial analysts who require accurate and reliable profit forecasting. By facilitating the optimization of profit prediction models, OSIE-CHOA leads to the improvement of decision-making within the context of financial accounting information systems.

Flavonoids, polyphenolic compounds found in plant-based diets, are associated with reduced risk of cardiovascular disease and longevity. These components are reported to reduce plasma levels of low-density lipoprotein (LDL) through an upregulation of the LDL receptor (LDLR), but the mechanism is still largely unknown. In this study, we have systematically screened the effect of 12 flavonoids from six different flavonoid subclasses on the effect on LDLR. This paper provides an in-depth analysis on how these flavonoids affect LDLR regulation and functionality. We found that most but not all of the tested flavonoids increased LDLR mRNA levels. Surprisingly, this increase was attributed to different regulatory mechanisms, such as enhanced LDLR promoter activity, LDLR mRNA stabilization, or LDLR protein stabilization, of which specific effectual parts of the flavonoid molecular structure could be assigned. These types of comparative analysis of various flavonoids enhance clarity and deepen the understanding of how the different structures of flavonoids affect LDLR regulation. Our data offer useful insights that may guide future research in developing therapeutic approaches for cardiovascular health.

Purpose: To investigate self-reported work ability in patients with musculoskeletal disorders in physiotherapy treatment. What characterizes patients with reduced work ability, whether work ability changes during treatment and characteristics of patients reporting no improvement. Design: Cohort study Material: 1498 patients with musculoskeletal disorders of working age who attend physiotherapy in primary healthcare. Method: Questionnaires at baseline and after three months. Results: 63% reported reduced work ability at baseline. Factors associated with reduced work ability were reduced daily activity level, physical work, psychological complaints, widespread pain, and high pain intensity. Participants with reduced work ability improved their average work ability by 1.7 on the WAS (work ability scale 0-10), however 53% did not achieve improvement. Characteristics of patients without improvement in work ability were long-term complaints, widespread pain, and psychological complaints. Conclusion: It seems difficult to improve work ability for patients with long-term and complex disorders in physiotherapy treatment. Physiotherapists should pay particular attention to psychological factors that inhibit improvement in work ability.

Abstract This research proposes a hybrid improved marine predator algorithm (IMPA) and deep gated recurrent unit (DGRU) model for profit prediction in financial accounting information systems (FAIS). The study addresses the challenge of real-time processing performance caused by the increasing complexity of hybrid networks due to the growing size of datasets. To enable effective comparison, a new dataset is created using 15 input parameters from the original Chinese stock market Kaggle dataset. Additionally, five DGRU-based models are developed, including chaotic MPA (CMPA) and the nonlinear MPA (NMPA), as well as the best Levy-based variants, such as the dynamic Levy flight chimp optimization algorithm (DLFCHOA) and the Levy-base gray wolf optimization algorithm (LGWO). The results indicate that the most accurate model for profit forecasting among the tested algorithms is DGRU-IMPA, followed by DGRU-NMPA, DGRU-LGWO, DGRU-DLFCHOA, DGRU-CMPA, and traditional DGRU. The findings highlight the potential of the proposed hybrid model to improve profit prediction accuracy in FAIS, leading to enhanced decision-making and financial management.

Excess cholesterol originating from nonhepatic tissues is transported within HDL particles to the liver for metabolism and excretion. Cholesterol efflux is initiated by lipid-free or lipid-poor apolipoprotein A1 interacting with the transmembrane protein ABCA1, a key player in cholesterol homeostasis. Defective ABCA1 results in reduced serum levels of HDL cholesterol, deposition of cholesterol in arteries, and an increased risk of early onset CVD. Over 300 genetic variants in ABCA1 have been reported, many of which are associated with reduced HDL cholesterol levels. Only a few of these have been functionally characterized. In this study, we have analyzed 51 previously unclassified missense variants affecting the extracellular domains of ABCA1 using a sensitive, easy, and low-cost fluorescence-based assay. Among these, only 12 variants showed a distinct loss-of-function phenotype, asserting their direct association with severe HDL disorders. These findings emphasize the crucial role of functional characterization of genetic variants in pathogenicity assessment and precision medicine. The functional rescue of ABCA1 loss-of-function variants through proteasomal inhibition or by the use of the chemical chaperone 4-phenylbutyric acid was genotype specific. Genotype-specific responses were also observed for the ability of apolipoprotein A1 to stabilize the different ABCA1 variants. In view of personalized medicine, this could potentially form the basis for novel therapeutic strategies.

Poor overall survival of hematopoietic stem cell transplantation (HSCT) recipients who developed COVID-19 underlies the importance of SARS-CoV-2 vaccination. Previous studies of vaccine efficacy have reported weak humoral responses but conflicting results on T cell immunity. Here, we have examined the relationship between humoral and T cell response in 48 HSCT recipients who received two doses of Moderna’s mRNA-1273 or Pfizer/BioNTech’s BNT162b2 vaccines. Nearly all HSCT patients had robust T cell immunity regardless of protective humoral responses, with 18/48 (37%, IQR 8.679-5601 BAU/mL) displaying protective IgG anti-receptor binding domain (RBD) levels (>2000 BAU/mL). Flow cytometry analysis of activation induced markers (AIMs) revealed that 90% and 74% of HSCT patients showed reactivity towards immunodominant spike peptides in CD8+ and CD4+ T cells, respectively. The response rate increased to 90% for CD4+ T cells as well when we challenged the cells with a complete set of overlapping peptides spanning the entire spike protein. T cell response was detectable as early as 3 months after transplant, but only CD4+ T cell reactivity correlated with IgG anti-RBD level and time after transplantation. Boosting increased seroconversion rate, while only one patient developed COVID-19 requiring hospitalization. Our data suggest that HSCT recipients with poor serological responses were protected from severe COVID-19 by vaccine-induced T cell responses.

In recent years, new energy vehicles, as a high-tech industry, have developed rapidly. This paper uses “number of new energy project personnel” and “hours of R&D (research and development) personnel” as design indicators to evaluate the investment of innovative talents in enterprises. This paper first introduces the supporting factors of the innovation environment in the input of innovation resources, and conducts research from four perspectives: human resources, innovation R&D, technology acquisition, and environmental support. In the construction of the innovation output index system, this paper outlines that the technological innovation (TI) achievements of enterprises are related to factors such as technological capabilities, profits, and market competitiveness of enterprises. Finally, this paper evaluates it from three aspects: the research and development achievements, the economic benefits obtained and the competitive benefits of the enterprise. The results show that from 2018 to 2022, the average technological innovation efficiency of new energy enterprises is 1.06; TI’s efficiency indicators in the past five years are all above 1, and the overall improvement trend of TI is relatively stable. The new energy vehicle collaborative innovation system constructed in this paper will promote the overall development of the new energy vehicle industry.

Judgment about the outcome of plastic surgery, whether reconstruction or cosmetology, depends on the beautification of body image, which is difficult to be measured with physical parameters. How to exactly understand patients' perception and make correct medical decisions are everyday work of plastic surgeons. Hence patient reported outcome measures (PROMs) are particularly important. In this paper, the author briefly described the development of PROMs, and introduced their application in plastic surgery, so as to provide reference for clinical research.

Heat transfer experiment on water flow boiling was carried out in the upward direction under atmospheric pressure through a narrow rectangular channel heated on one-side by vapor having a gap of 2.75 mm, a width of 250 mm, and length of 1400 mm. The heat transfer coefficient and thermal hydraulic thresholds of the flow boiling in forced convective flow, such as the onset of nucleate boiling (ONB) and onset of fully developed nucleate boiling (OFDB) were investigated. The experiment was performed over a wide range of inlet temperature (75–95°C), mass flow rate (2–9 g/m), and heat fluxes (5–16 kW/m2). The effects of the parameters on the heat transfer coefficients have been discussed in detail. A series of ONB, FDB and heat transfer correlations were evaluated using the experimental data, and most of the correlations did not adequately fit the experimental results. A modified Hong et al. correlation and modified Zhu et al. correlation were used to predict the wall superheat at ONB and FDB respectively. The average errors (AEs) of the two correlations were 2.36% and −0.68%, and the root mean square errors (RMSEs) of them were both 14.00%. A modified Li and Wu correlation was used to predict heat transfer coefficients with the average error (AE) of 1.46% and the root mean square errors (RMSE) of 11.88%. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the prevalence of likely pathogenic or pathogenic variants and assess the diagnostic yield from genetic testing for cardiac arrhythmias in Norway since 2003. Data from 1991 probands and 2782 relatives were retrospectively collected from the laboratory information management system at Unit for Cardiac and Cardiovascular Genetics, Oslo University hospital. Of 1991 probands, 57.4% were females, age at genetic testing was 33.1 (±22.7) years, and 32.5% were under the age of 18. A likely pathogenic or pathogenic variant (including 14 novel) was detected in 15.4% in total. Of the 2782 relatives, 53.7% were females, age at genetic testing was 35.6 (±22.5) years, 27.3% were under the age of 18, and 45.3% carried the family variant. Probands and relatives combined, 1/3356 persons in the Norwegian population were heterozygous for an arrhythmia‐causing variant. The founder variant p.Q530X (NM_000218.2: c.1588C>T) in KCNQ1 accounted for 34% of all variants in Norway. In conclusion, genetic testing provided a genetic basis of the arrhythmia in 15.4% of the probands. Familial cascade screening identified four times as many variant‐positive relatives, allowing early detection and prompt stratification of arrhythmic risk of those variant carriers. [ABSTRACT FROM AUTHOR]

This paper introduces the Quantum Chimp Optimization Algorithm (QU-ChOA), which integrates the Chimp Optimization Algorithm (ChOA) with quantum mechanics principles to enhance optimization capabilities. The study evaluates QU-ChOA across diverse domains, including benchmark tests, the IEEE CEC-06–2019 100-Digit Challenge, real-world optimization problems from IEEE-CEC-2020, and dynamic scenarios from IEEE-CEC-2022. Key findings highlight QU-ChOA's competitive performance in both unimodal and multimodal functions, achieving an average success rate (SR) of 88.98% across various benchmark functions. QU-ChOA demonstrates robust global search abilities, efficiently finding optimal solutions with an average fitness evaluations (AFEs) of 14 012 and an average calculation duration of 58.22 units in fire detection applications. In benchmark tests, QU-ChOA outperforms traditional algorithms, including achieving a perfect SR of 100% in the IEEE CEC-06–2019 100-Digit Challenge for several functions, underscoring its effectiveness in complex numerical optimization. Real-world applications highlight QU-ChOA's significant improvements in objective function values for industrial processes, showcasing its versatility and applicability in practical scenarios. The study identifies gaps in existing optimization strategies and positions QU-ChOA as a novel solution to these challenges. It demonstrates QU-ChOA's numerical advancements, such as a 20% reduction in AFEs compared to traditional methods, illustrating its efficiency and effectiveness across different optimization tasks. These results establish QU-ChOA as a promising tool for addressing intricate optimization problems in diverse fields. [ABSTRACT FROM AUTHOR]

This research introduces the Quantum Chimp Optimization Algorithm (QChOA), a pioneering methodology that integrates quantum mechanics principles into the Chimp Optimization Algorithm (ChOA). By incorporating non-linearity and uncertainty, the QChOA significantly improves the ChOA's exploration and exploitation capabilities. A distinctive feature of the QChOA is its ability to displace a 'chimp,' representing a potential solution, leading to heightened fitness levels compared to the current top search agent. Our comprehensive evaluation includes twenty- nine standard optimization test functions, thirty CEC-BC functions, the CEC06 test suite, ten real-world engineering challenges, and the IEEE CEC 2022 competition's dynamic optimization problems. Comparative analyses involve four ChOA variants, three leading quantum-behaved algorithms, three state-ofthe-art algorithms, and eighteen benchmarks. Employing three non-parametric statistical tests (Wilcoxon rank-sum, Holm-Bonferroni, and Friedman average rank tests), results show that the QChOA outperforms counterparts in 51 out of 70 scenarios, exhibiting performance on par with SHADE and CMA-ES, and statistical equivalence to jDE100 and DISHchain1e+12. The study underscores the QChOA's reliability and adaptability, positioning it as a valuable technique for diverse and intricate optimization challenges in the field. [ABSTRACT FROM AUTHOR]

The frequency and the suction refrigerant state are complex in the actual operation of variable compressors, which leads to the variability of compressor performance under different operating conditions. The characterization and the modeling of the compressor have become hot research topics. For modeling, the electrical efficiency model of the compressor, which could be applied to the suction refrigerant state at both the superheated and the two-phase stages, the compressor frequency, the pressure ratio, and the evaporation temperature, is analyzed through experiments in this paper. The results show that the linear electrical efficiency decreases with the declining superheated temperature and the increasing suction vapor quality when the system is at the fixed and evaporating temperature. Moreover, the slope of the two-phase suction is above that of the superheated suction. In addition, the system’s electrical efficiency at the fixed pressure ratio is inversely proportional to the evaporation temperature, and the electrical efficiency of the system at the fixed evaporating temperature is also inversely proportional to the pressure ratio. The higher the variation of the pressure ratio, the smaller the evaporation temperature influences. To demonstrate the precision of the model, the theoretical value is compared with a confirmatory experiment in this paper. The maximum relative error is 1.81%, and the minimum is 0.035%.