Sum Of Weights Research Articles

The maximum spectral radius of the weighted bicyclic hypergraphs

Let B n , k , a be the set of weighted k-uniform connected bicyclic hypergraphs of order n with positive integer weights and fixed total weight sum a, where n, k and a are positive integers with k ≥ 4 and a ≥ n + 1 k − 1 ≥ 3 . An α-normal labelling method is proposed for comparing the spectral radii of the weighted hypergraphs under consideration. The weighted hypergraph having the maximum spectral radius among the hypergraps in B n , k , a is obtained.

Ant-Colony-Algorithm-Based Intelligent Transmission Network Planning

Background: The efficiency of wireless sensor networks is limited by limitations in energy supply. Efficient routing strategies should be designed to save and balance the energy consumption of each node in a wireless sensor network. Aim: In this study, a transmission network based on an ant colony algorithm was proposed to meet the power load demands of a city. Objective: Based on the chaos ant colony algorithm, using a combination of wireless sensor network and node residual energy factors, a neighbor selection strategy was proposed. Results: The optimal result was 1896, and additional lines were: N14-15= 2, N4-16= 1, N5-12= 2, N7-13= L, N6-14= 1, N7-8. The coding method of solving transmission network planning based on multi-stage and multi-dimensional control variables was employed to decompose each control variable into two variables. The sum of total weight and non-zero bits was transformed into high-dimensional variables in state transition probability. Conclusion: The key analysis showed that the ant colony algorithm, as a simulated evolutionary algorithm, is an efficient internal heuristic method.

Modelling chromosome-wide target search

The most common gene regulation mechanism is when a transcription factor (TF) protein binds to a regulatory sequence to increase or decrease RNA transcription. However, TFs face two main challenges when searching for these sequences. First, the sequences are vanishingly short relative to the genome length. Second, there are many nearly identical sequences scattered across the genome, causing proteins to suspend the search. But as pointed out in a computational study of LacI regulation in Escherichia coli, such almost-targets may lower search times if considering DNA looping. In this paper, we explore if this also occurs over chromosome-wide distances. To this end, we developed a cross-scale computational framework that combines established facilitated-diffusion models for basepair-level search and a network model capturing chromosome-wide leaps. To make our model realistic, we used Hi-C data sets as a proxy for 3D proximity between long-ranged DNA segments and binding profiles for more than 100 TFs. Using our cross-scale model, we found that median search times to individual targets critically depend on a network metric combining node strength (sum of link weights) and local dissociation rates. Also, by randomizing these rates, we found that some actual 3D target configurations stand out as considerably faster or slower than their random counterparts. This finding hints that chromosomes’ 3D structure funnels essential TFs to relevant DNA regions.

The impact of pandemic-related social distancing regulations on exercise performance-Objective data and training recommendations to mitigate losses in physical fitness.

In the context of the COVID-19 pandemic in Germany, governmental restrictions led to the closure of sports facilities for several months. To date, only subjective and fitness-tracking related data on physical activity during the pandemic are available. Using data of a chip-controlled fitness circuit, training data as a measure of physical performance before and after the lockdown during the first wave of the COVID-19 pandemic will show the impact of the training interruption on exercise performance in middle-aged and older adults. The re-training data are analyzed, to extract practical recommendations. Objective training data of 17,450 participants [11,097 middle-aged (45-64 yrs), 6,353 older (≥65 yrs)] were exported from chip-controlled milon® fitness circuit systems before and after the first COVID-19 related lockdown in Germany. The change in the product of training weight (sum of lifting and lowering the training weight) and repetitions on the leg extension resistance exercise device (leg score) between the last three training sessions before the lockdown and the first ten training sessions after individual training resumption as well as the last training session before the second lockdown in October 2020 was analyzed. Participants who trained with high intensity before the lockdown, experienced deleterious effects of the training interruption (middle-aged group: -218 kg, older group: ~-230.8 kg; p < 0.001 for change in leg score from to post-lockdown) with no age effect. Participants training with a leg score of more than 3,000 kg did not resume their leg score until the second lockdown. The interruption of training in a fitness circuit with combined resistance and endurance training due to the lockdown affected mainly those participants who trained at high intensity. Apparently, high-intensity training could not be compensated by home-based training or outdoor activities. Concepts for high-intensity resistance training during closure of sports facilities are needed to be prepared for future periods of high incidence rates of infectious diseases, while especially vulnerable people feel uncomfortable to visit sports facilities. Identifier, DRKS00022433.

The system of self-consistent models based on quasi-SMILES as a tool to predict the potential of nano-inhibitors of human lung carcinoma cell line A549 for different experimental conditions

The different features of the impact of nanoparticles on cells, such as the structure of the core, presence/absence of doping, quality of surface, diameter, and dose, were used to define quasi-SMILES, a line of symbols encoded the above physicochemical features of the impact of nanoparticles. The correlation weight for each code in the quasi-SMILES has been calculated by the Monte Carlo method. The descriptor, which is the sum of the correlation weights, is the basis for a one-variable model of the biological activity of nano-inhibitors of human lung carcinoma cell line A549. The system of models obtained by the above scheme was checked on the self-consistence, i.e., reproducing the statistical quality of these models observed for different distributions of available nanomaterials into the training and validation sets. The computational experiments confirm the excellent potential of the approach as a tool to predict the impact of nanomaterials under different experimental conditions. In conclusion, our model is a self-consistent model system that provides a user to assess the reliability of the statistical quality of the used approach.

How to Statistically Disentangle the Effects of Environmental Factors and Human Disturbances: A Review

Contemporary biological assemblage composition and biodiversity are often shaped by a range of natural environmental factors, human disturbances, and their interactions. It is critical to disentangle the effects of individual natural variables and human stressors in data analysis to support management decision-making. Many statistical approaches have been proposed and used to estimate the biological effects of individual predictors, which often correlated and interacted with one another. In this article, we review nine of those approaches in terms of their strengths, limitations, and related r packages. Among those are hierarchical partitioning, propensity score, the sum of AIC weights, structural equation modeling, and tree-based machine learning algorithms. As no approach is perfect, we offer two suggestions: (1) reducing the number of predictors as low as possible by carefully screening all candidate predictors based on biological and statistical considerations; (2) selecting two or more approaches based on the characteristics of the given dataset and specific research goals of a study, and using them in parallel or sequence. Our review could help ecologists to navigate through this challenging process.

Adaptive normalization for IPW estimation

Abstract Inverse probability weighting (IPW) is a general tool in survey sampling and causal inference, used in both Horvitz–Thompson estimators, which normalize by the sample size, and Hájek/self-normalized estimators, which normalize by the sum of the inverse probability weights. In this work, we study a family of IPW estimators, first proposed by Trotter and Tukey in the context of Monte Carlo problems, that are normalized by an affine combination of the sample size and a sum of inverse weights. We show how selecting an estimator from this family in a data-dependent way to minimize asymptotic variance leads to an iterative procedure that converges to an estimator with connections to regression control methods. We refer to such estimators as adaptively normalized estimators. For mean estimation in survey sampling, the adaptively normalized estimator has asymptotic variance that is never worse than the Horvitz–Thompson and Hájek estimators. Going further, we show that adaptive normalization can be used to propose improvements of the augmented IPW (AIPW) estimator, average treatment effect (ATE) estimators, and policy learning objectives. Appealingly, these proposals preserve both the asymptotic efficiency of AIPW and the regret bounds for policy learning with IPW objectives, and deliver consistent finite sample improvements in simulations for all three of mean estimation, ATE estimation, and policy learning.

A 24-month updated analysis of the comparative effectiveness of ZUMA-5 (axi-cel) vs. SCHOLAR-5 external control in relapsed/refractory follicular lymphoma

ABSTRACT Background In the ZUMA-5 trial (Clinical trials identification: NCT03105336), axicabtagene ciloleucel (axi-cel; a chimeric antigen receptor T-cell therapy) demonstrated high rates of durable response in relapsed/refractory (r/r) follicular lymphoma (FL) patients and clear superiority relative to the SCHOLAR-5 external control cohort. We update this comparison using the ZUMA-5 24-month data. Research design and methods The SCHOLAR-5 cohort is comprised of r/r FL patients who initiated ≥3rd line of therapy after July 2014 and meeting ZUMA-5 eligibility criteria. Groups were balanced for patient characteristics through propensity scoring on prespecified prognostic factors using standardized mortality ratio (SMR) weighting. The overall response rate was compared using a weighted logistic regression. Time-to-event outcomes were evaluated using a Cox regression. Results For SCHOLAR-5, the sum of weights for the 143 patients was 85 after SMR weighting, versus 86 patients in ZUMA-5. The median follow-up was 29.4 months and 25.4 months for ZUMA-5 and SCHOLAR-5, respectively. The hazard ratios for overall survival and progression-free survival were 0.52 (95% confidence interval (CI): 0.28–0.95) and 0.28 (95% CI: 0.17–0.45), favoring axi-cel. Conclusion This updated analysis, using a longer minimum follow-up than a previously published analysis, shows that the improved efficacy of axi-cel, relative to available therapies, in r/r FL is durable. .

Fixed set search applied to the clique partitioning problem

The Clique Partitioning Problem (CPP) seeks to decompose a set of vertices into disjoint subsets (cliques) maximizing the sum of edge weights over all the cliques. The interest for the CPP comes from the fact that it represents well many practical problems from areas like data mining, engineering, bio-informatics, etc. To address this NP-hard combinatorial optimization problem, the novel fixed set search (FSS) metaheuristic is applied. This is performed, firstly, by developing a greedy randomized adaptive search procedure (GRASP) using a new type of neighborhood in the local search. The GRASP is further extended to the FSS by adding a learning mechanism. The FSS application to the CPP provides a new approach for generating fixed sets for problems with solution symmetries. This approach opens the application of the FSS to new families of combinatorial optimization problems. The conducted computational experiments show that the FSS significantly outperforms state-of-the-art metaheuristics for the CPP. The proposed approach obtains a large number of new best solutions for commonly used CPP test instances.

ПРОСТРАНСТВЕННАЯ ДЕЗИНТЕГРАЦИЯ ГОСУДАРСТВА И ОЦЕНКА ЕЕ РИСКОВ (НА ПРИМЕРЕ ЭКВАДОРА)

The article studies the processes of spatial disintegration, understood as the weakening, disruption and destruction of system-forming ties between the regions of the state, and determines the possibility of adverse consequences (risks) due to the impact of these processes. The authors’ methodology for assessing the risks of spatial disintegration involves seven factors: historical, socio-economic, domestic-political, ethno-cultural, transport, military-strategic, and foreign policy. The methodology uses parameters that make it possible to establish the effect of each of the factors. The risks of spatial disintegration are measured at two levels. The risk of disintegration for the whole state is calculated as the sum of the risk weights for individual factors. The weight of the risk factor is determined by the proportion of the country's population living in administrative-territorial units experiencing disintegration under this factor. The risk of spatial disintegration of a part of a country (a unit of administrative-territorial division) is determined by the number of factors under which this region has high risks of spatial disintegration. The object of the study is Ecuador. The structure and socio-political situation in this country demonstrate a combination of features characteristic of a Latin American state (sharp territorial contrasts in living standards, internal political turbulence, complex relationships with Indian ethnic groups, an extractivist model of development, technological dependence on developed countries, a high level of social stratification, significant crime rates, etc.). At the same time, Ecuador has a number of unique features compared with neighboring countries. These include the presence of a spatially remote region (Galapagos Islands), the compactness of the continental territory, a variety of landscapes, a bicentric model of regional development with the largest nodes in the capital city of Quito and the city of Guayaquil, an alternative capital and the largest seaport. The calculations showed that Ecuador has lower risks of spatial disintegration compared to other Latin American countries previously considered in other publications (Chile, Bolivia, Venezuela, Mexico). Among the territorial units of the country, the greatest risks of spatial disintegration are demonstrated by the provinces of Morona-Santiago and Pastasa, located in the east of Ecuador.

The association between the sum of fetal weights in twin pregnancies and perinatal complications

The association between the sum of fetal weights in twin pregnancies and perinatal complications

Cooperative Deployment Multi-Objective Optimization Approach for High-Resolution Multi-Airship Earth-Observation Coverage Network

As a platform for Near space-based Earth-observation network, stratospheric airship has attracted a lot of attention in recent years, because of its advantages in endurance, coverage, cost, and durability. However, the airship has low conversion speed and large vehicle inertia, so it is significant to deploy Multi-airship Earth-observation Coverage Network (MAEON) collaboratively. To this end, this paper proposes an Earth-observation model with considerations of loading devices side-swing characteristics and field of view (FOV), and establishes a collaborative deployment model of MAEON to realize objectives of observation coverage, target point statistics, observation resolution, multi-airship community profit. To obtain the solution set of cooperative deployment problem efficiently and widely, a multi-objective evolutionary optimization algorithm (MOEA) with associated bi-criterion is proposed. Then, weight vector distribution control with dynamic adjustment is introduced to ensure that the solution set spreads more uniform and extensive. By embedding improved evolution factors, Non-Pareto criterion (NPC) and Pareto criterion (PC) based parts co-evolve and exchange information, which is effective in diversity and convergence. The normalized weight sum method is modified by adding the moderators, which are controlled by the population outcome in the iterative process. The experiment is repeated in 8 groups of data, and compared with 4 popular MOEAs. Through simulation experiments, it can be seen that the proposed algorithm has advantages in performance, universality, and stability.

RESULTS OF THE RESEARCH ON THE ALLOCATION OF TASKS IN A COLLABORATIVE ROBOTIC SYSTEM WITH MINIMIZATION OF THEIR EXECUTION TIME

The article presents a generalized algorithm for allocation of tasks in a collaborative robotic system with minimizing the time of their execution (an algorithm of assigning the performers to work within the technological process), as well as the results of modeling the developed algorithm. The maximum value among the sums of the edge weights for the longest path from the source of the graph to its drain is used as the execution time of the technological process that needs to be minimized.

Modified Sombor index of unicyclic graphs with a given diameter

The modified Sombor index of a graph [Formula: see text] is defined as the sum of weights [Formula: see text] over all edges [Formula: see text] of [Formula: see text], where [Formula: see text] and [Formula: see text] are the degrees of the vertices [Formula: see text] and [Formula: see text] in [Formula: see text], respectively. In this paper, we give a sharp lower bound on the modified Sombor index of unicyclic graphs with given diameter in terms the number of vertices.

A Genome‐Wide Search for Pleiotropy in Cognitive Domain Scores

AbstractBackgroundGenome‐wide association studies (GWASs) have identified loci for Alzheimer’s disease (AD)‐related cognitive traits, and genetic correlations among these traits suggest that a single gene may affect them jointly, i.e., pleiotropy.MethodWe conducted GWASs for scores previously generated by factor analyses for cognitive domains—executive function, language, and memory—using longitudinal data from 7,503 Framingham Heart Study (FHS) and 6,758 National Alzheimer’s Coordinating Center (NACC) subjects who had an average of five and three exams, respectively. We averaged domain scores for each participant by weighting down scores at the visit without normal cognition and used the sum of weights to account for heterogeneous residual variances. The association of each domain score with 8.9 million genetic variants (MAF&gt;0.01), imputed using the TOPMed reference panel (GRCh38), was tested separately in each dataset using linear models including age, sex, education level, and five principal components of ancestry as covariates. Results from FHS and NACC datasets were combined by meta‐analyses using the inverse‐variance method. Pleiotropy for each pair of cognitive domains was evaluated using PLACO (pleiotropic analysis under the composite null hypothesis).ResultScores for paired cognitive domains were moderately genetically correlated—executive function and language (ρP =0.46, ρG =0.69), executive function and memory (ρP =0.39, ρG =0.43), language and memory (ρP =0.44, ρG =0.46). Pleiotropy analyses revealed genome‐wide significant associations for all paired domain scores with many variants in the APOE region (p&lt;3.91×10‐9 for each). For pleiotropy of executive function and language, we identified genome‐wide significant associations with DOK5 (rs28663252, p=4.51×10‐8) and suggestive associations with SOX14 (rs55829884, p=8.03×10‐8), IL20RB (rs11925531, p=9.26×10‐8), and RIMS2 (rs140291972, p=8.76×10‐7). We also found suggestive associations for pleiotropy of language and memory with LHFPL4 (rs2936482, p=5.08×10‐8) and for pleiotropy of executive function and memory with MC4R (rs1943220, p=7.54×10‐8) and CDH20 (rs78756286, p=1.50×10‐7).ConclusionWe identified significant evidence of pleiotropy for multiple cognitive domains, and these findings may improve the interpretation of the genetic basis of cognition and AD‐related traits. These results highlight the benefits of factor scores derived from groups of subjects assessed with various cognitive tests and pleiotropy analysis as a tool for identifying genes that contribute to performance in multiple cognitive domains.

Analysis of Manufacturing Companies by Weight Sum Method

In this from analysis EDAS method is the most ideal solution Short-distance and negative-best The solution with the longest distance from the solution Determines, but the comparison of these distances Does not consider importance. From the result it is seen that Market turmoil ranks first, with management support having the lowest ranking. This article addresses the issue of customer complexity, Customer center, innovation, service diversity and Explores the relationship between business performance and. The study of 332 manufacturing companies provides the basis for empirical inquiry. There are two broad types of financing research dealing with the use of rates Read Corporate Structure. Increased market complexity and impending Competitiveness is their position in the freight-service continuum by expanding the business power to expand Is a traditional service to manufacturing-manufacturing companies. World-class quality of life, production plays a key role in improving companies. However, linearity in the system they are combined with standard Production and consumption patterns. This is a measure of performance and Store site status report is not financial. This research science includes macroeconomics; Financial risk management, audit scenarios, equity returns, investment decisions, financial results and Good Corporate Management There are 147 models of manufacturing companies listed on the Indonesian Stock Exchange. Sustained performance in organizational research is one of the primary ideas. Its importance and effectiveness of the many advances that have appeared over the years are, despite criticisms, a difficult concept to apply in a scientifically rigorous manner. Multi-Objective Optimization Issues Mostly big dominance Lead to unpaid packages, Because of the size of the problem or the number of goals to create a complete non-dominant set Requires significant calculation time Related at the same time Most of the solutions are unsuitable for the decision maker (DM) Shows that Manufacturing Companies Alternative: Perceived benefits, technical resources, management support, computer perspective, market turmoil, peer pressure. Evaluation Preference: Technology, Organization, Environment. From the result it is seen that Market turbulence and is got the first rank whereas is the Management support got is having the lowest rank

Comparative Analysis of Multi-Criteria Decision-Making Techniques for Outdoor Heat Stress Mitigation

Decision making is the process of making choices by organizing relevant information and evaluating alternatives. MCDMs (Multi-Criteria Decision Methods) help to select and prioritize alternatives step by step. These tools can help in many engineering fields where the problem is complex and advanced. However, there are some limitations of the different MCDMs that reduce the reliability of the decision that needs to be improved and highlighted. In this study, Elimination and Choice Expressing Reality (ELECTRE) NI (Net Inferior), NS (Net Superior), Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS), Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), VIekriterijumsko KOmpromisno Rangiranje (VIKOR), Multi-Objective Optimization Ratio Analysis (MOORA), Weight Sum Method (WSM) and Weighted Product Method (WPM) are applied for the selection of urban heat mitigation measurements under certain criteria. The models were applied using weighting criteria determined by two ways, (i) the direct weighting method and (ii) the Analytic Hierarchy Process (AHP), for precise weighting factoring through pairwise comparison. This numerical research evaluated the reliability of MCDMs using the same decision matrix under different normalization techniques and shows the impact of AHP on the decision. The results show that WSM and PROMETHEE provided reliable and consistent results for all normalization techniques. The combination of AHP with applied MCDMs improved the frequency of consistent ranking, except with ELECTRE-NS.

Analysis of Manufacturing Companies by Weight Sum Method

In this from analysis EDAS method is the most ideal solution Short-distance and negative-best The solution with the longest distance from the solution Determines, but the comparison of these distances Does not consider importance. From the result it is seen that Market turmoil ranks first, with management support having the lowest ranking. This article addresses the issue of customer complexity, Customer center, innovation, service diversity and Explores the relationship between business performance and. The study of 332 manufacturing companies provides the basis for empirical inquiry. There are two broad types of financing research dealing with the use of rates Read Corporate Structure. Increased market complexity and impending Competitiveness is their position in the freight-service continuum by expanding the business power to expand Is a traditional service to manufacturing-manufacturing companies. World-class quality of life, production plays a key role in improving companies. However, linearity in the system they are combined with standard Production and consumption patterns. This is a measure of performance and Store site status report is not financial. This research science includes macroeconomics; Financial risk management, audit scenarios, equity returns, investment decisions, financial results and Good Corporate Management There are 147 models of manufacturing companies listed on the Indonesian Stock Exchange. Sustained performance in organizational research is one of the primary ideas. Its importance and effectiveness of the many advances that have appeared over the years are, despite criticisms, a difficult concept to apply in a scientifically rigorous manner. Multi-Objective Optimization Issues Mostly big dominance Lead to unpaid packages, Because of the size of the problem or the number of goals to create a complete non-dominant set Requires significant calculation time Related at the same time Most of the solutions are unsuitable for the decision maker (DM) Shows that Manufacturing Companies Alternative: Perceived benefits, technical resources, management support, computer perspective, market turmoil, peer pressure. Evaluation Preference: Technology, Organization, Environment. From the result it is seen that Market turbulence and is got the first rank whereas is the Management support got is having the lowest rank.

Partitioning through projections: Strong SDP bounds for large graph partition problems

The graph partition problem (GPP) aims at clustering the vertex set of a graph into a fixed number of disjoint subsets of given sizes such that the sum of weights of edges joining different sets is minimized. This paper investigates the quality of doubly nonnegative (DNN) relaxations, i.e., relaxations having matrix variables that are both positive semidefinite and nonnegative, strengthened by additional polyhedral cuts for two variations of the GPP: the k-equipartition and the graph bisection problem. After reducing the size of the relaxations by facial reduction, we solve them by a cutting-plane algorithm that combines an augmented Lagrangian method with Dykstra’s projection algorithm. Since many components of our algorithm are general, the algorithm is suitable for solving various DNN relaxations with a large number of cutting planes.We are the first to show the power of DNN relaxations with additional cutting planes for the GPP on large benchmark instances up to 1,024 vertices. Computational results show impressive improvements in strengthened DNN bounds.

Optimization of the Reduction of Shrinkage and Warpage for Plastic Parts in the Injection Molding Process by Extended Adaptive Weighted Summation Method.

The consumer market has changed drastically in recent times. Consumers are becoming more demanding, and many companies are competing to be market leaders. Therefore, companies must reduce rejects and minimize their operating costs. One problem that arises in producing plastic parts is controlling deformation, mainly in the form of shrinkage due to the material and warpage associated with the geometry of the parts. This work presents a novel extended adaptive weighted sum method (EAAWSM: Extended Adaptive Weighted Summation Method) integrated into a Pareto front model. The performance of this model is evaluated against three other conventional optimization methods-Taguchi-Gray (TG), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Model Optimization by Genetic Algorithm (MOGA)-and compared with EAAWSM. Two response variables and three input factors are considered to be analyzed: material melting temperature, mold temperature, and filling time. Subsequently, the performance is compared and its behavior observed using Moldflow® simulation. The results show that with the EAAWSM method, the shrinkage is 15.75% and the warpage is 3.847 mm, regarding the manufacturing process parameters of a plastic part. This proposed deterministic model is easy to use to optimize two or more output variables, and its results are straightforward and reliable.