Sum Method Research Articles

The Causal Effects of Cholelithiasis on Acute Pancreatitis and Pancreatic Cancer: A Large Sample Size Mendelian Randomization Analysis.

The aim of two-sample Mendelian randomization (MR) with a large sample size was to explore the causal cholelithiasis impact on acute pancreatitis and pancreatic cancer. We performed the two-sample MR analysis with two models. Publicly available summary- level information for cholelithiasis was acquired from the Genome-Wide Summary Association Studies (GWAS) of FinnGen Biobank. The inverse variance weighted (IVW) method was the main method to obtain the MR estimates. Other methods were also used as supplementary methods, including MR-Egger, maximum likelihood, MR-Robust Adjusted Profile Score (MR-RAPS), weighted median, penalised weighted median method, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) method. After the selection of genetic instrumental variables (IVs), 11 single nucleotide polymorphisms (SNPs) (Model 1) and 22 SNPs (Model 2) were used to explore the effect of cholelithiasis on acute pancreatitis, and 10 SNPs (Model 1) and 24 SNPs (Model 2) on pancreatic cancer. The findings obtained by the fixed-effect IVW method with both Model 1 and Model 2 showed that genetically predicted cholelithiasis was significantly related to the elevated acute pancreatitis risk (Model 1: OR: 1.001, 95% CI: 1.000-1.002, p <0.001; Model 2: OR: 1.001, 95% CI: 1.000-1.002, p <0.001). Moreover, cholelithiasis would also raise the pancreatic cancer risk (Model 1: OR: 1.676, 95% CI: 1.228-2.288, p = 0.001; Model 2: OR: 1.432, 95% CI: 1.116-1.839, p = 0.005). Genetically predicted cholelithiasis was significantly related to the elevated risk of acute pancreatitis and pancreatic cancer. More attention should be paid to patients with cholelithiasis for the primary prevention of pancreatic-related diseases.

Sustainability in tourism demands a mode shift: Appraisal of heritage tourism; a safe bet for developing regions

AbstractThe study aims to determine heritage tourism potential in the Kashmir valley, a developing region, to lower the impact of mass tourism on the natural environment. The potential was assessed using criterion‐based indicators. After a Delphi survey, Content Validation Ratio determined indicator retention. Field trips and secondary sources identified the sites. The sites with cultural significance were prioritized with other supporting factors. The Weighted Sum Method assessed the heritage site potential. It was calculated for each criterion: Cultural, Physical, and Natural. Then, total potential was classified into three groups on the basis of equal intervals depicting high, medium, and low, where high ranges from 0.628 to 0.756, medium from 0.502 to 0.628, and low from 0.375 to 0.502. Being the capital city and hub of different activities, Srinagar district of the study area has maximum of the sites with high heritage potential. Owing to its long history, the study region has many heritage sites; however, its tourism potential has yet to be tapped. The study emphasizes the significance of shifting surges in tourism forms in managing sustainable tourism development.

Learning curve for fusion magnetic resonance imaging targeted prostate biopsy and three-dimensional transrectal ultrasonography segmentation.

To report the learning curve of multiple operators for fusion magnetic resonance imaging (MRI) targeted biopsy and to determine the number of cases needed to achieve proficiency. All adult males who underwent fusion MRI targeted biopsy between February 2012 and July 2021 for clinically suspected prostate cancer (PCa) in a single centre were included. Fusion transrectal MRI targeted biopsy was performed under local anaesthesia using the Koelis platform. Learning curves for segmentation of transrectal ultrasonography (TRUS) images and the overall MRI targeted biopsy procedure were estimated with locally weighted scatterplot smoothing by computing each operator's timestamps for consecutive procedures. Non-risk-adjusted cumulative sum (CUSUM) methods were used to create learning curves for clinically significant (i.e., International Society of Urological Pathology grade ≥ 2) PCa detection. Overall, 1721 patients underwent MRI targeted biopsy in our centre during the study period. The median (interquartile range) times for TRUS segmentation and for the MRI targeted biopsy procedure were 4.5 (3.5, 6.0) min and 13.2 (10.6, 16.9) min, respectively. Among the 14 operators with experience of more than 50 cases, a plateau was reached after 40 cases for TRUS segmentation time and 50 cases for overall MRI targeted biopsy procedure time. CUSUM analysis showed that the learning curve for clinically significant PCa detection required 25 to 45 procedures to achieve clinical proficiency. Pain scores ranged between 0 and 1 for 84% of patients, and a plateau phase was reached after 20 to 100 cases. A minimum of 50 cases of MRI targeted biopsy are necessary to achieve clinical and technical proficiency and to reach reproducibility in terms of timing, clinically significant PCa detection, and pain.

Pairing New Approach of Tree Soft with MCDM Techniques: Toward Advisory an Outstanding Web Service Provider Based on QoS Levels

&#x0D; Web services (WSs) have become dynamic because of technological advancements and internet usage. Hence, selecting a WS provider among a variety of WS providers that perform the same function is a critical process. However, the crucial point is that various consumers may have varied needs when it comes to the quality attributes of services, such as cost, response time, throughput, security, availability, etc. These aspects of Web services are known as quality of service (QoS), or non-functional characteristics. Hence, this issue is the robust motivator for conducting this study. The objective of this study is to evaluate a set of WSs that provide various services for various consumers and organizations. This evaluation is conducted based on a set of QoS attributes. Hence, we are applying a new approach to describe this problem in the form of leaves or branches of a tree or hierarchy. This approach is represented in a soft tree set. Also, we leveraged Multi-Criteria Decision Making (MCDM) techniques such as entropy and weighted sum methods under the authority of the Single Value Neutrosophic (SVN) Scale. The entropy technique analyzes attributes or leaves in each level contained in the tree's soft approach, obtaining attributes’ weights. These weights are used to rank and recommend optimal WS providers through the application of these weights in WSM. The results of implementing entropy-WSM in a tree-soft approach indicated that WS2 is the optimal provider. In contrast, WS3 is the worst provider.&#x0D;

Economic and environmental factors based multi-objective approach for optimizing energy management in a microgrid

This article proposes an approach to optimize energy management (EM) in a microgrid (MG) with a battery storage system (BSS) and distributed generation. The primary objective is to address the challenge of cost-effective and environmental-friendly operation of the microgrid, with a specific focus on minimizing operational cost and emission through optimal BSS utilization in the daily schedule. Balancing economic and environmental factors through optimization poses a complex problem, which is addressed here by applying the slime mould algorithm (SMA) along with the weighted sum and fuzzy decision-making method. Three scenarios are considered to demonstrate the MG's EM. In Scenario A, SMA outperforms differential evolution (DE), sine cosine algorithm (SCA), and grasshopper optimization algorithm (GOA) by reducing operational cost by 17.59 %, 8.19 %, and 9.84 %, respectively, and achieves better emission reduction with reductions of 4.93 %, 15.74 %, and 9.91 % compared to DE, SCA, and GOA, respectively. SMA also dominates DE, SCA, and GOA in other scenarios, producing superior Pareto-optimal solutions. Additionally, comparing the Pareto-optimal results achieved with SMA, Scenario C outperforms Scenarios A and B by achieving reductions of 25.47 % and 35.20 % in operational cost, respectively, along with a corresponding 6.4 % and 36.26 % decrease in emission, highlighting the superior performance of Scenario C.

The learning curve for laparoscopic pancreaticoduodenectomy by a proficient laparoscopic surgeon: a retrospective study at a single center

BackgroundTo explore the learning curve of single center laparoscopic pancreaticoduodenectomy (LPD) and evaluate the safety and efficacy of the operation at different stages.MethodsA detailed review was conducted on the clinical data of 120 cases of laparoscopic pancreatoduodenectomy performed by the same surgeon between June 2018 and June 2022. Cases that did not provide insights into the learning curve of the procedure were excluded. The cumulative sum (CUSUM) analysis and the best fitting curve methods were employed to delineate the learning curve based on operation time and intraoperative blood loss. The study further evaluated the number of surgeries required to traverse the learning curve. Outcome measures, including operation time, intraoperative blood loss, length of stay, complications, and other relevant indicators, were extracted and compared across different phases of the learning curve.ResultThe maximum turning point of the fitting curve was found in 35 cases by the cumulative sum method of operation time, after which the learning curve could be considered to have passed. The fitting curve obtained by the cumulative sum method of intraoperative blood loss was stable in 30 cases and proficient in 60 cases, which was basically consistent with the fitting curve of operation time. Taking 35 cases as the boundary, the learning curve is divided into learning improvement stage and mastering stage. There was no statistical significance in the general data of the two stage patients (P > 0.05). Hospitalization days decreased from 19 to 15 days (P < 0.05);Pancreatic fistula decreased from 20.0% of grade B and 8.6% of grade C to 7.1% of grade B and 3.5% of grade C (P < 0.05), and the operative time decreased from (376.9 ± 48.2) minutes to (294.4 ± 18.7) minutes (P < 0.05). Intraoperative blood loss decreased from 375 to 241 ml (P < 0.05).ConclusionThirty-five patients with LPD can reach the proficiency stage and the perioperative indexes can be improved.

Checklist das categorias da CIF relevantes para o desenvolvimento de fala e linguagem

ABSTRACT Purpose Create a checklist of the International Classification of Functioning, Disability and Health (ICF) based on relevant categories for the development of speech and language, according to the perception of parents and speech therapists. Methods Pilot application and research were carried out. 100 parents of preschool children with typical language/cognition development and 57 language specialist speech therapists participated in the survey. A questionnaire was created with 199 ICF categories of body function components, activities and participation, and environmental factors. Each category was scored as: indispensable (2); important (1) or unimportant (0). Statistical analysis was performed (descriptive, sum, cluster/K-means and Mann-Whitney method). Results With the sum of the points (essential, important and unimportant) and the number of responses essential, the most relevant categories were identified for each group of respondents, as well as the set of categories in common (72 considered to have the greatest influence). The common list to the groups included the three components: body functions (30 categories/40% of the total), activities and participation (35/49.29%) and environmental factors (seven/13.20%). From the selected categories, 58.33% presented statistically significant results between the groups, regarding the relevance given. Conclusions The categories were considered with different scores between the groups: those of body functions were more scored by speech therapists, while those of environmental factors by parents. Thus, it was possible to create a checklist from the identification of the most relevant categories for the development of speech and language, in preschool age, contemplating the components of body functions, activities and participation and environmental factors.

Causal associations of BAFF-R on IgD+ CD24- B cell immune cell trait with hepatocellular carcinoma and the mediating role of phenylacetylglutamate levels: a Mendelian randomization study.

We conducted a bi-directional two-sample Mendelian randomization (MR) analysis to investigate the causal associations between immune cell traits and hepatocellular carcinoma (HCC) and identified the mediating factor of metabolites. The exposure factors were immune cell traits, the mediators were metabolites, and the outcome variable was HCC. Inverse-variance weighted method (IVW) was the main method. Weighted median, MR-Egger regression, weighted mode, simple mode, and MR pleiotropy residual sum and outlier (MRPRESSO) methods were used as complementary methods. The results were tested by using the Bayesian weighted Mendelian randomization (BWMR) approach in our MR study. Subsequently, the potential mediating effect was investigated by conducting a two-step mediation analysis. We identified 26 traits with suggestive correlations between immune cell traits and HCC, with 4 immune cell traits among them having causal correlations with HCC. There were no causal correlations between HCC and immune cell traits in the reverse MR analysis. In the mediation analysis, we found a positive causal association between B cell-activating factor receptors (BAFF-R) on IgD+ CD24- B cell and HCC [IVW: odd ratio (OR), 0.845; 95% CI, 0.759-0.942; p = 0.002]. Phenylacetylglutamate (PAG) levels mediated 7.353% of the causal pathway from BAFF-R on IgD+ CD24- B cell and HCC. In conclusion, BAFF-R on IgD+ CD24- B cell lowers risk of HCC, with PAG levels playing a mediating role.

Genetic Insights into Glycine's Protective Role Against CAD - European and East Asia, 2015 and 2020.

The purpose of this study is to examine the potential causal relationship between levels of circulating glycine and coronary artery disease (CAD) using a two-step Mendelian randomization (MR) analysis. We analyzed data from genome-wide association studies (GWAS) conducted on European and East Asian populations. To assess the causal effects of circulating glycine levels on the risk of CAD. We used the inverse-variance weighting (IVW), weighted median (WM), MR-Egger, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) methods. Furthermore, we conducted mediation analysis to investigate the contribution of blood pressure and other cardiovascular disease-related traits. The two-step Mendelian randomization analysis revealed that higher levels of glycine in the blood were associated with a reduced risk of CAD in Europeans [odds ratio ( OR)=0.84, 95% confidence interval ( CI): 0.72, -0.98; P=0.029] and East Asians: ( OR=0.76, 95% CI: 0.66, -0.89; P=3.57×10 -4). Sensitivity analysis confirmed the robustness of these findings. Additionally, our results suggest that about 6.06% of the observed causal effect is mediated through genetically predicted systolic blood pressure (SBP) in the European population. Our results contribute to the current knowledge regarding the involvement of glycine in the progression of CAD, and provide valuable methodological insights for the prevention and treatment of this condition.

A Sample Based Algorithm for Constructing Guaranteed Confidence Ellipsoids for Linear Regression Models with Deterministic Regressor

This paper presents a novel algorithm for constructing non-asymptotic confidence ellipsoids for linear regression models with deterministic regressors. The confidence ellipsoids are centered at the least-squares estimate, and the true parameter lies within the ellipsoid with a probability specified by the user. The confidence ellipsoid is constructed by drawing independent samples of the noise sequence and exploiting an ordering property for independent and identically distributed random variables. The main assumption on the noise is that it has a known joint density so that samples can be drawn. The efficacy of the approach is demonstrated through a simulation example of an FIR system. The constructed confidence ellipsoid is compared with the confidence regions obtained using the Sign-Perturbed Sum method and asymptotic system identification theory.

Value retention using remanufacturing: A case study on part and process down selection for wind turbine applications

As a key component of a circular economy, remanufacturing is gaining popularity across various sectors. This paper focuses on the wind energy sector, a major player in renewable technologies, which is gradually recognizing its increasing resource-intensive material usage. We present a case study outlining a method for selecting parts from an industrial supply chain partner’s inventory. This strategy is further employed to streamline the manufacturing processes for the chosen part. We utilized the Weighted Sum method, a multi-criteria decision-making strategy, in both instances. We discuss how expertise of process specialists and multi-criteria decision-making techniques could be synthesised for adopting a remanufacturing approach. Data from the commercial partners was collected and any identifying information was stripped. From this, we discovered that the Yaw gear pinion shaft is the top candidate for remanufacturing due to its high commercial value. After comparing various additive manufacturing technologies, Arc Directed Energy Deposition stands out as the best fit for remanufacturing this particular pinion shaft. Although our initial aim was to consider additive manufacturing technologies as solutions for remanufacturing, we show how even conventional manufacturing processes, such as friction welding, could emerge as strong contenders.

Análise comparativa dos métodos de monitorização do estado dos bovinos de pequeno porte utilizando tecnologias modernas

Abstract For successful animal husbandry, farmers need to monitor the health status of animals on a daily basis, as well as ensure the safety and protection of animals. In this regard, the problem of choosing the optimal system for monitoring the condition of farm animals in the modern market is urgent. The practical value of the scientific article is to analyze the problems of stakeholders and, based on the needs, conduct a comparative analysis of various modern systems for monitoring the condition of small cattle using the weighted sum method. The object of the study was the process of monitoring the condition of small cattle using RFID tags, as well as the ability to monitor their health depending on the chosen approach. The subject of the study was a livestock enterprise that raises small cattle. It was found that the health of small cattle directly affects the financial stability of the farm. In the presented study, the authors analyze the problems of stakeholders and, based on the needs of stakeholders, conduct a comparative analysis of various modern systems for monitoring the condition of small cattle using the weighted sum method. The results obtained will help farmers make informed decisions in the future when choosing the most appropriate monitoring option for more effective and high-quality monitoring of the condition of small cattle, thereby reducing the risk of diseases and increasing profits for companies.

A Semidefinite Programming Method Weighted Sum Based for Solving a Multi-area Emission (Environmental) Economic Dispatch Problem

This paper presents a semi-definite programming (SDP) optimisation approach for solving multi area, emission/economic dispatch (MAEED) problems in thermal power systems. The multi-objective problem was transformed into matrix form as an SDP relaxation problem and subsequently solved with a MATLAB programming suite. The system inequality and equality constraints were entered into a Self-Dual Minimisation (SeDuMi) parser. Simulations were tested on four (4) IEEE benchmark models to validate the efficiency of the proposed SDP method. However, in the generation of the Pareto-fr ont solutions, ideal minimum points were used in the determination of the maximum spread out of the Pareto solutions by the algorithm. This involves the use of a standard weighted sum method in generating the Pareto-optimal solution between two objective functions. Twenty-one (21) runs were carried out for the parameter value to explore the effect of control weight selection k1. A comparative study demonstrated the effectiveness of tie-line constraint and without tie-line constraint, respectively on the optimi sation model for the power dispatch problems solved by using the proposed SDP approach. The optimisation results for the minimum fuel cost using the SDP approach for the case when a tie-line constraint is included was US$ 2,151.7 /hr with minimum emission of 3.4687 Ton/hr. This is lower than US$ 2,162.2 /hr with minimum emission of 3.6662 Ton/hr obtained when the tie-line constraint is not included in the optimisation model on IEEE four-area, sixteen network. Additionally, the comparative results with all other methods reported in the literature for different test cases were also presented in this paper. Lower operational costs were obtained for both tie-lines and no tie-lines power transfer cases, showing that the SDP method performed well in accuracy compared to other methods. The SDP method was employed in this research to deal with the multi-area emission economic power dispatch problem due to its inherent advantages in achieving a global optimal solution and, this approach would also assist the power administrator to come up with an improved decision making in attaining an optimum power dispatch of power generation.

A Comparative Study of ε-constraint, LP-metric, and Weighted Sum Multi-objective Optimization Methods in a Circular Economy

Approximately 74.7 Mt (Million Metric Tonnes) of e-waste is expected to be produced in 2030, and laptop e-waste is one of the major constituents of this. The goal of this paper is to develop and optimize a mixed-integer linear programming (MILP) mathematical model for a laptop manufacturer in India, based on a framework that integrates secondary reuse concept associated with traditional circular economy waste avoidance strategies. The multi-objective solution techniques of ε-constraint, LP-metric, and weighted sum methods are used to optimize the circular economy model. The proposed model aids as a policy tool to decide the optimum number of inspection/collection centers, sales/distribution centers, disassembly centers, refurbishing centers, recycling centers, and their optimum locations and allocations. This study results suggest that reuse, secondary customer centers, refurbishing, and recycling of the laptops is not only economically beneficial to the organization but also environment friendly and helps to create more jobs in the rural economy.

Identifying the most critical behavioral lifestyles associated with MAFLD: evidence from the NHANES 2017-2020.

Accumulating studies have demonstrated associations between single lifestyle exposures and metabolic dysfunction-associated fatty liver disease (MAFLD). However, the joint effects of lifestyle exposures remain unclear, hindering the development of targeted prevention and control strategies. We aimed to investigate the joint associations between lifestyle exposomes and MAFLD. This study included 5,002 participants from NHANES 2017-2020. Lifestyle exposomes, including sleep duration, metabolic equivalent of task (MET), Healthy Eating Index (HEI)-2015 score, alcohol consumption, and smoke exposure, were identified from questionnaire data. MAFLD was diagnosed by vibration-controlled transient elastography measurements and laboratory data. A logistic regression model and the weighted quantile sum method were used to evaluate the associations of single and joint lifestyle exposomes, respectively, with MAFLD. The population attributable fractions (PAFs) were calculated to assess the population benefits of different intervention strategies. Per-quartile range increases in sleep duration (OR=0.883, 95% CI: 0.826-0.944), MET (0.916, 0.871-0.963), and HEI-2015 score (0.827, 0.756-0.904) were significantly associated with MAFLD. The joint exposure of sleep duration, MET, and HEI-2015 score was associated with MAFLD (0.772, 0.688-0.865), with the highest weight (importance) for MET (0.526). PAFs revealed greater intervention benefits for sleep and the HEI-2015 when the majority of the population (>5%) had a low MAFLD risk (weak intervention targets), whereas MET was the most efficient intervention strategy when minority populations (≤5%) had a low MAFLD risk (strong intervention targets). This study demonstrated significant associations between MAFLD and single and joint exposures to sleep duration, MET, and HEI-2015 and identified physical activity as the most important lifestyle factor. Further population benefit analyses may provide evidence and suggestions for population-level interventions.

An Efficient FPGA-Based Accelerator for Perceptual Weighting Filter in Speech Coding

In speech coding, denoising of the speech signal is essential as well as crucial. The filters for minimizing errors through denoising employ the autoregressive moving average (ARMA) approach, introducing higher computational complexity in speech coder design. This research work presents the design and implementation of an effective perceptual weighting filter (PWF) for speech coding. The high-level synthesis of the fixed-point PWF filter is optimized by multiple optimization techniques along with detailed design space exploration using the weighted sum (WS) method. To enhance the performance, an FPGA-based hardware accelerator is proposed using hardware/software (HW/SW) co-design in an embedded environment. Simulative analysis in Vivado HLS and final accelerator design in the Vitis IDE tool validate the proposed architecture by using real-time speech samples, demonstrating a 50% reduction in area and a 99% execution improvement. This makes it well-suited for use in modern speech codecs, enhancing the efficiency.

Coastal Vulnerability Assessment of Kanthi Coast, India by the Geospatial Technology

Since ancient times, most of the world’s civilization flourished along the banks of rivers and the coastal region. So the coastal region plays a vital role for human economic activities as well as their livelihood. The Kanthi coast, the northernmost part of the North Circus coast of India stretches in West Bengal and northern Odisha. The 45 km stretched coast land is associated with a dense population and faces the tropical cyclone emerging from the Bay of Bengal. The prime objective of the paper is to assess the coastal vulnerability of the study area. With the help of several indicators, viz. shoreline change rate, rate of sea level change, slope of the beach, wave height, tidal range, regional elevation, geomorphic features, sediment properties, coastal regulation zone (CRZ) violation ratio, the research work assess the Coastal Vulnerability Zone (CVZ) of the Kanthi Coastal region. The weightage sum method and Coastal Vulnerability Index (CVI) are being used. From this research work, it has been revealed that the western segment especially, Digha and Shankarpur are experiencing a high vulnerability situation.

Diagrammatic multiplet sum method (MSM) density functional theory (DFT): Investigation of the transferability of integrals in "simple" DFT-based approaches to multideterminantal problems.

Kohn-Sham density functional theory (DFT) typically works well for describing dynamic correlation. Two other types of correlation, arising in the cases of degenerate (static) or quasidegenerate (nondynamic) zero-order states, represent a difficult problem for DFT. When symmetry is present, multiplet sum method (MSM) DFT [Ziegler et al., Theor. Chim. Acta 4, 877 (1977)] provides one of the earliest and simplest ways to include static correlation in DFT. MSM-DFT assumes that DFT provides a good description of single-determinant energies and uses symmetry and simple ansätze to include the effects of static correlation. This is equivalent to determining the off-diagonal matrix elements in a small configuration interaction (CI) eigenvalue problem. Our ultimate goal, however, is nondynamic correlation in cases where symmetry is inadequate for fixing the dynamic-correlation limitation of DFT. To this end, we have developed a diagrammatic approach to MSM-DFT, which does not, by itself, solve the nondynamic correlation problem in DFT but which facilitates comparison with wave function CI and so allows educated guesses of off-diagonal CI matrix elements even in the absence of symmetry. In every case, an additional exchange-only ansatz (EXAN) allows the MSM-DFT formulas to be transformed into wave function formulas. This EXAN also works for transforming time-dependent DFT into time-dependent Hartree-Fock. Although not enough to uniquely guess DFT formulas from wave function formulas, the diagrammatic approach and the EXAN provide important constraints on any guesses that might be used. We illustrate how diagrammatic MSM-DFT may be used to guess a nondynamic correlation correction for the dissociation of H2 and how diagrammatic MSM-DFT may be used to guess a nonsymmetry-based coupling element in the O2 multiplet problem, which is reasonably close to a previous symmetry-derived result.

Leveraging cost-effectiveness of photovoltaic-battery system in metro station under time-of-use pricing tariff

As the cornerstone of contemporary urban transit infrastructure, the metro rail transit system significantly contributes to both energy consumption and carbon emissions. Recognizing the potential of rooftop photovoltaic (PV) applications in elevated stations to mitigate the carbon footprint of the metro system, harnessing this potential becomes imperative for advancing toward a cleaner future in the metro transit sector. However, the techno-economic feasibility of the rooftop PV application in elevated metro stations has not been fully reported in existing literature. Addressing this research gap, our study delves into the impact of the photovoltaic-battery (PVB) system on energy conservation and economic benefits within the elevated stations of a metro line in Beijing, China, and a multi-objective nonlinear mixed-integer programming (MIP) is formulated under a 3-tier time-of-use tariff scheme for minimizing grid load and maximizing economic benefits. The results demonstrate that the incorporation of both the battery energy storage device and the PV subsystem leads to an 8.3% and 19.2% reduction in annualized costs, respectively. When applied across the entire metro line, the PVB system is anticipated to yield a substantial annualized cost reduction ranging from 26.1% to 47.8%. Moreover, outcomes from the multi-objective MIP optimization reveal that the simultaneous achievement of economic benefits maximization and grid load minimization is infeasible, and the weighted sum method offers a decision-making platform for investors to choose one option or another according to extra criteria.

Association between type 1 diabetes mellitus and ankylosing spondylitis: a two-sample Mendelian randomization study.

The development of ankylosing spondylitis (AS) is closely related to autoimmune system dysfunction. Type 1 diabetes mellitus (T1DM) is an autoimmune disease that is a risk factor for many diseases. This study aimed to investigate the causal relationship between T1DM mellitus and AS genetically. A genome-wide association study (GWAS) of causal relationships between exposure (T1DM) and outcome (AS) was performed using summary data from the GWAS database. We conducted a two-sample Mendelian randomization (MR) study of these two diseases. Inverse variance weighting (IVW) was used as the primary analysis method, with MR Egger, weighted median, and weighted mode used as supplementary methods. Sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept, MR-Pleiotropy RESidual Sum and outlier methods, leave-one-out analysis, and funnel plots. A total of 11 single nucleotide polymorphisms (SNPs)were identified for instrumental variables(IVs) for MR analysis.IVW found that T1DM was causally associated with AS ((IVW: OR = 1.0006 (95% CI 1.0001, 1.0011), p = 0.0057; MR-Egger: OR = 1.0003 (95% CI 0.9995, 1.0012), p = 0.4147; weighted median: OR = 1.0006 (95% CI 1.0003, 1.0008), p = 0.0001; weighted mode: OR = 1.0007 (95% CI 1.0005, 1.0009), p = 0.0001). No horizontal pleiotropy was found for the MR-Egger intercept, and leave -one-out analysis found that the results remained stable after the removal of individual SNPs. The results of the two-sample MR analysis supported a causal relationship between T1DM and AS risk.