Miracle-dz/UniFAR-FTUs huggingface dataset:
An Urban Bus Network Generation Algorithm Based on Particle Swarm Optimization and Force Field Properties

Due to continuous urban sprawl, large-scale bus network design has become a major challenge in urban transport planning. The continuous increase in urban population and scale makes the factors considered in the urban route network design increasingly complex. Contemporary public transportation network design problems are based more on efficiency goals such as the accessibility and comfort of the transportation network, which increases the difficulty of analyzing the problem. Bus network design is not only an NP-hard (nondeterministic polynomial) problem but also a multivariable and multiobjective problem. This paper focuses on the bivariate and multiobjective bus network design problem of route generation and station selection. This paper proposes an algorithm called the Pseudo Force Field. By combining the idea of Particle Swarm Optimization (PSO) and the properties of the force field, a feasible route generation scheme is provided for the design of the bus network. The algorithm does not need to determine the end station and has a high degree of completion of the demand. This solves the problem of the selection of terminal stations in large-scale road network design. On this basis, the article combines Genetic Algorithm (GA) and Pareto frontier to provide a new route optimization algorithm and proves the effectiveness of the algorithm. The model has achieved theoretical results in the design of the bus route network in the megacity of Shenzhen, China.
A weak lensing detection of a deviation from General Relativity on cosmic scales

We consider evidence for deviations from General Relativity (GR) in the growth of large scale structure, using two parameters, $\gamma$ and $\eta$, to quantify the modification. We consider the Integrated Sachs-Wolfe effect (ISW) in the WMAP Cosmic Microwave Background data, the cross-correlation between the ISW and galaxy distributions from 2MASS and SDSS surveys, and the weak lensing shear field from the Hubble Space Telescope's COSMOS survey along with measurements of the cosmic expansion history. We find current data, driven by the COSMOS weak lensing measurements, disfavors GR on cosmic scales, preferring $\eta<1$ at $1
Simulation study of DDoS attacks and remediation based on OPNET

DDoS (Distributed Denial of Service) attacks are easy to implement, difficult to prevent and difficult to track, resulting in widespread DDoS attacks, making them one of the most difficult network security problems to solve and bringing great harm to the network society. However, traditional defence methods suffer from low detection rate of attack detection and link congestion after the attack cannot handle legitimate user requests properly. Therefore, this paper proposes a remediation scheme based on a hybrid mechanism of detection and congestion avoidance defence by simulating a DDoS (Distributed Denial of Service) attack example in a local area network, which is experimentally verified to be effective.
Automatic extractive summarization for Japanese documents by LDA

The demand for automatic summarization of newspaper headlines and article sum- maries has increasing with various studies on automatic summarization being currently conducted. However, there are only a few studies on Japanese documents as compared English documents.In this paper, wheter existing summarization methods can be effective for academic pa- pers written in Japanese is verified. First, we demonstrate the effectiveness of topic-based extractive summarization methods Latent Semantic Analysis (LSA). Then, a more effec- tive topic-based extractive summarization is possible by using Latent Dirichlet Allocation (LDA) is demonstrated.
The Genetic Architecture of Non-Syndromic Rhegmatogenous Retinal Detachment

Rhegmatogenous retinal detachment (RRD) is the most common form of retinal detachment (RD), affecting 1 in 10,000 patients per year. The condition has significant ocular morbidity, with a sizeable proportion of patients obtaining poor visual outcomes. Despite this, the genetics underpinning Idiopathic Retinal Detachment (IRD) remain poorly understood; this is likely due to small sample sizes in relevant studies. The majority of research pertains to the well-characterised Mende lian syndromes, such as Sticklers and Wagners, associated with RRD. Nevertheless, in recent years, there has been an increasing body of literature identifying the common genetic mutations and mechanisms associated with IRD. Several recent Genomic Wide Association Studies (GWAS) studies have identified a number of genetic loci related to the development of IRD. Our review aims to provide an up-to-date summary of the significant genetic mechanisms and associations of Idiopathic RRD.
Trust in COVID‐19 public health information

Understanding the factors that influence trust in public health information is critical for designing successful public health campaigns during pandemics such as COVID‐19. We present findings from a cross‐sectional survey of 454 US adults—243 older (65+) and 211 younger (18–64) adults—who responded to questionnaires on human values, trust in COVID‐19 information sources, attention to information quality, self‐efficacy, and factual knowledge about COVID‐19. Path analysis showed that trust in direct personal contacts (B = 0.071, p = .04) and attention to information quality (B = 0.251, p < .001) were positively related to self‐efficacy for coping with COVID‐19. The human value of self‐transcendence, which emphasizes valuing others as equals and being concerned with their welfare, had significant positive indirect effects on self‐efficacy in coping with COVID‐19 (mediated by attention to information quality; effect = 0.049, 95% CI 0.001–0.104) and factual knowledge about COVID‐19 (also mediated by attention to information quality; effect = 0.037, 95% CI 0.003–0.089). Our path model offers guidance for fine‐tuning strategies for effective public health messaging and serves as a basis for further research to better understand the societal impact of COVID‐19 and other public health crises.
A fuzzy classifier system that generates fuzzy if-then rules for pattern classification problems

We propose a fuzzy classifier system that can automatically generate fuzzy if-then rules from numerical data (i.e., from training patterns) for multi-dimensional pattern classification problems. Classifiers in our approach are fuzzy if-then rules such as "If x/sub p1/ is small and x/sub p2/ is large then classify x/sub p/ as Class 2". The proposed classifier system can find a compact rule set by attaching large fitness values to such fuzzy if-then rules that can correctly classify many training patterns. That is, only fuzzy if-then rules with large fitness values are selected to construct a compact fuzzy system with high classification performance.
Game theory approach to H∞-optimal discrete-time fixed-point and fixed-lag smoothing

Optimal H/sub /spl infin//-fixed-point and fixed-lag discrete-time smoothing estimators are developed by applying a game theory approach. A deterministic discrete-time game is defined where the estimator plays against nature. Nature determines the system initial condition, the driving input, and the measurement noise, whereas the estimator tries to find an estimate that brings a prescribed cost function that is based on the error of the estimation at a fixed time instant, to a saddle-point equilibrium. The latter estimate yields the H/sub /spl infin//-optimal fixed-point smoothing. Differently from the usual case in H/sub /spl infin//-optimal estimation and control, the critical value of the scalar design parameter of the smoothing game is obtained in closed form, explicitly in the terms of the corresponding H/sub 2/ solution. Unlike the H/sub 2/ case, the recursive application of the H/sub /spl infin// fixed-point smoothing algorithm does not lead to fixed-lag smoothing in the H/sub /spl infin//-norm sense. The H/sub /spl infin// fixed-lag smoothing filter is derived by augmenting the state vector of the system with additional delayed states. >
Global Vibration Comfort Evaluation of Footbridges Based on Computer Vision

The vibration comfort evaluation is a control standard other than strength and deflection, but the general comfort evaluation method only considers the response of the mid-span position and does not consider the difference in the vibration response of different positions at the same time. It is crucial to study how pedestrians actually feel when they walk on footbridges. The computer vision-based vibration comfort evaluation method is a novel method with advantages, such as noncontact and long-distance. In this study, a computer vision-based method was used to evaluate the global vibration comfort of footbridges under human-induced excitation. The improved Lucas–Kanade optical flow method is used for multitarget displacement identification of footbridges. Additionally, the YOLOv5 algorithm for pedestrian detection is used to obtain the position information of pedestrians on the footbridges. Then, according to the pedestrian position information, the structural responses of different pedestrian positions corresponding to time periods are extracted from the displacement responses of each point, and they are combined to obtain the structural global displacement. The global acceleration can be obtained by calculating the global displacement. The rms value can be calculated based on the global acceleration and compared with the standard for comfort evaluation. The global comfort evaluation method is validated by pedestrian walking experiments with different frequencies on a laboratory footbridge. The experimental results show that the computer vision-based global comfort evaluation method for footbridges is feasible and is a more specific and real-time comfort evaluation method.
Deep Label Feature Fusion Hashing for Cross-Modal Retrieval

The rapid growth of multi-modal data in recent years has driven the strong demand for retrieving semantic-related data within different modalities. Therefore, cross-modal hashing has attracted extensive interest and studies due to its fast retrieval speed and good accuracy. Most of the existing cross-modal hashing models simply apply neural networks to extract the features of the original data, ignoring the unique semantic information attached to each data by the labels. In order to better capture the semantic correlation between different modal data, a novel cross-modal hashing model called deep label feature fusion hashing (DLFFH) is proposed in this article. We can effectively embed semantic label information into data features by building label networks in different modal networks for feature fusion. The fused features can more accurately capture the semantic correlation between data and bridge the semantic gap, thus improving the performance of cross-modal retrieval. In addition, we construct feature label branches and the corresponding feature label loss to ensure that the generated hash codes are discriminative. Extensive experiments have been conducted on three general datasets and the results demonstrate the superiority of the proposed DLFFH which performs better than most cross-modal hashing models.
Shifting the Focus: A Pilot Study on the Effects of Positive Body Exposure on Body Satisfaction, Body Attitude, Eating Pathology and Depressive Symptoms in Female Patients with Eating Disorders

One of the most commonly used techniques for the treatment of body image problems in eating disorders (ED) is body exposure (BE). However, evidence of its effectiveness in clinical populations is scarce. In the Positive Body Experience (PBE) protocol, the focus of positive BE is on aesthetic, functional and tactile aspects of the body. The current study evaluates the outcomes of positive BE with regard to changes in attitudinal body image and eating pathology, as well as the factors that influence these changes, in a sample of 84 adult female patients with different EDs who did not receive any other treatment for their EDs during the period in which BE treatment occurred. The results show significant positive changes in attitudinal body image, ED behaviors and depressive symptoms, with depressive symptoms at baseline mediating the changes in attitudinal body image. This study indicates that the PBE protocol is a suitable intervention for reducing negative attitudinal body image in anorexia and bulimia nervosa patients, as well as those with binge eating disorder. Furthermore, the results suggest that positive non-weight-related and functional body satisfaction are strong catalysts for change and that depressive symptoms play an important role in the ability to change. Additional RCTs are needed to gain more insight into the effects of PBE.
PENINGKATAN PANGAN FUNGSIONAL CHICKEN NUGGET DENGAN SUBSTITUSI TEPUNG BEKATUL BERDASARKAN KANDUNGAN ASAM LEMAK DAN VITAMINNYA

Penelitian ini bertujuan untuk mengetahui pengaruh substitusi tepung bekatul terhadap tepung terigu terhadap sifat fungsionalitas chicken nugget. Parameter pengujian sifat fungsionalitas chicken nugget meliputi kadar vitamin B, vitamin E, kadar kolesterol, serta kadar asam lemak. Penelitian ini menggunakan 5 perlakuan dengan 3 kali ulangan dengan variasi perbandingan tepung terigu:tepung bekatul, yaitu 100:0 untuk T0; 75:25 untuk T1; 50:50 untuk T2; serta 25:75 untuk T3. Pengujian vitamin B dan vitamin E dilakukan dengan menggunakan instrument High Performance Liquid Chromatography (HPLC), pengujian kadar kolesterol dilakukan menggunakan spektrofotometer, sedangkan untuk pengujian kadar asam lemak menggunakan Gas Chromatography (GC). Semakin tinggi substitusi tepung bekatul terhadap tepung terigu, maka semakin baik pula sifat fungsionalitas chicken nugget. Peningkatan sifat fungsionalitas tersebut ditandai dengan meningkatnya kadar vitamin B, vitamin E, kadar kolesterol (HDL), dan asam lemak tak jenuh. Perlakuan chicken nugget dengan substitusi tepung bekatul terbaik adalah perlakuan T3 (75% tepung bekatul) karena perlakuan tersebut memiliki kadar vitamin B sebesar 0,915 mg/1000g, vitamin E sebesar 43,35 µg/1000g, kadar kolesterol (HDL) sebesar 43,35%, serta memiliki kandungan asam lemak tak jenuh tertinggi.
A vanishing theorem for the p‐local homology of Coxeter groups

Given an odd prime number p and a Coxeter group W such that the order of the product st is prime to p for all Coxeter generators s,t of W , we prove that the p ‐local homology groups Hk(W,Z(p)) vanish for 1⩽k⩽2(p−2) . This generalizes a known vanishing result for symmetric groups due to Minoru Nakaoka.
Evaluation of the Antihyperglycemic and Antihyperlipidemic Activity of Saussurea hypoleuca Root in Alloxan-Induced Diabetes in Rat Model and Correlation to Its Major Secondary Metabolites

Saussurea hypoleuca belongs to the family Asteraceae, which has previously shown hepatoprotective, anticancer, and antioxidant activity. This study aimed to evaluate the antihyperglycemic and antihyperlipidemic activity of its root methanol extract and various fractions for the first time. This was performed using alloxan-induced diabetes in the rat model for both short, and long-term periods using different administration doses. Different biochemical parameters were studied and further consolidated by histopathological examination and in silico molecular modeling. The results showed that in the long-term study, at a dose of 400 mg/kg b.wt, the ethyl acetate fraction caused a pronounced reduction in fasting blood glucose level (FBG) and glycated hemoglobin (HbA1c) by 77.2% and 36.8%, respectively, compared to the diabetic group. This was confirmed by the histopathological examination of the animals’ pancreatic sections. The ethyl acetate fraction also showed a reduction in total cholesterol (TC), total glycerides (TG), and low-density lipoprotein cholesterol (LDL-C) levels. It improved kidney and liver functions, causing a reduction in aspartate aminotransferase (AST), alkaline phosphatase (ALP), alanine transaminase (ALT), urea, and creatinine levels. This is mainly attributed to its richness in secondary metabolites. Molecular docking showed that all the tested compounds showed certain inhibitory potential towards human α-glucosidase (HAG) and ATP citrate lyase (ACL). Thus, Saussurea hypoleuca roots can help in the management of hyperglycemia, hyperlipidemia, and hepatic and kidney dysfunction.
The method of weighted residuals and variational principles : with application in fluid mechanics, heat and mass transfer

Preface to the classics edition Preface Acknowledgments Part I. The Method of Weighted Residuals: 1. Introduction 2. Boundary-value problems in heat and mass transfer 3. Eigenvalue and initial-value problems in heat and mass transfer 4. Applications to fluid mechanics 5. Chemical reaction systems 6. Convective instability problems Part II. Variational Principles: 7. Introduction to variational principles 8. Variational principles in fluid mechanics 9. Variational principles for heat and mass transfer problems 10. On the search for variational principles 11. Convergence and error bounds Author index Subject index.
Impact of a Multistep Bundles Intervention in the Management and Outcome of Gram-Negative Bloodstream Infections: A Single-Center “Proof-of-Concept” Study

Abstract Background This is a “proof-of-concept” study aiming to evaluate the impact of a multistep bundles intervention in the management and outcomes of patients with gram-negative bloodstream infections (GN-BSIs). Methods This was a single-center, quasi-experimental design study. In the pre-phase (January 2019 to May 2020), patients were retrospectively enrolled. During the post-phase (June 2020 to September 2021), all patients were prospectively enrolled in a nonmandatory 3-step bundles intervention arm including (i) step 1: imaging to detect deep foci of infection, follow-up blood cultures and procalcitonin monitoring; (ii) step 2: early targeted antibiotic treatment and surgical source control; (iii) step 3: discontinuation of antibiotics within 7–10 days in case of uncomplicated BSI. Patients were followed up to 28 days from BSI onset. The primary outcome was 28-day mortality. Results A total of 271 patients were enrolled: 127 and 144 in the pre- vs post-phase, respectively. Full application of step 1 (67% vs 42%; P < .001), step 2 (83% vs 72%; P = .031), and step 3 (54% vs 2%; P < .001) increased in the post-phase. Overall, the intervention reduced 28-day mortality (22% vs 35%, respectively; P = .016) and the median duration of total (11 vs 15 days; P < .001) and targeted (8 vs 12 days; P = .001) antibiotic therapy. Finally, the multivariate Cox regression confirmed the independent protective effect of adherence to step 1 (adjusted hazard ratio [aHR], 0.36; 95% CI, 0.20–0.63) and step 2 (aHR, 0.48; 95% CI, 0.29–0.81) on risk of 28-day mortality. Conclusions Clinical management and outcomes of patients with GN-BSIs may be improved by providing a pre-established multistep bundles intervention.
On the Sum and Spread of Reciprocal Distance Laplacian Eigenvalues of Graphs in Terms of Harary Index

The reciprocal distance Laplacian matrix of a connected graph G is defined as RDL(G)=RT(G)−RD(G), where RT(G) is the diagonal matrix of reciprocal distance degrees and RD(G) is the Harary matrix. Clearly, RDL(G) is a real symmetric matrix, and we denote its eigenvalues as λ1(RDL(G))≥λ2(RDL(G))≥…≥λn(RDL(G)). The largest eigenvalue λ1(RDL(G)) of RDL(G), denoted by λ(G), is called the reciprocal distance Laplacian spectral radius. In this paper, we obtain several upper bounds for the sum of k largest reciprocal distance Laplacian eigenvalues of G in terms of various graph parameters, such as order n, maximum reciprocal distance degree RTmax, minimum reciprocal distance degree RTmin, and Harary index H(G) of G. We determine the extremal cases corresponding to these bounds. As a consequence, we obtain the upper bounds for reciprocal distance Laplacian spectral radius λ(G) in terms of the parameters as mentioned above and characterize the extremal cases. Moreover, we attain several upper and lower bounds for reciprocal distance Laplacian spread RDLS(G)=λ1(RDL(G))−λn−1(RDL(G)) in terms of various graph parameters. We determine the extremal graphs in many cases.
BETWEEN FAIRNESS AND EFFICIENCY: TESTING WILSON’S THEORY OF PUBLIC ADMINISTRATION

During his first presidential term, faced with antitrust law reform, Woodrow Wilson had to deal with the reconstitution of conflicting values. These were, on the one hand, the importance of efficiency, guaranteed by the role of experts capable of effectively managing public administration; and, on the other hand, the importance of public and democratic participation, and therefore respect for traditional democratic values. Wilson faced a theoretical impasse in defining concepts such as competition and fairness when developing antitrust laws and had to put his theory of administration to the test. He opted for a pragmatic approach, based on managerial ideas and integrating the figure of the manager, expert in know-how.
Barreto-Naehrig Curve With Fixed Coefficient

This paper describes a method for constructing BarretoNaehrig curves that are pairing-friendly and have the embedding degree 12 having fixed coefficients, by using just primality tests without the complex multiplication method. Moreover, this paper discusses their twists. Specifically, this paper explains that the number of points on elliptic curves y = x± 16 and y = x± 2 over Fp(z) is given by one of 6 polynomials in z, n0(z), · · · , n5(z), classified by the value of z mod 12 for a prime p(z) = 36z +36z +24z +6z+1 with z an integer. The polynomial n5(z) represents the number of points on BN curves. For example, elliptic curve y = x + 2 over Fp(z) always becomes a BN curve for any integer z with z ≡ 2, 11 (mod 12). Then, to construct a pairing-friendly elliptic curve, it is enough to find an integer z of appropriate size such that p(z) and n5(z) are primes.
OSER—A Planning Tool for Power Systems Operation Simulation and for Impacts Evaluation of the Distributed Energy Resources on the Transmission System

The rapid expansion of distributed energy resources and variable renewable energy is occurring in most utilities around the world, pertaining to the clean energy transition. These technologies have brought new challenges and opportunities to transmission grid planners. In this context, the planning process cannot continue to focus solely on the instant of the peak demand to make decisions regarding the evolution of the grid. The OSER simulator (Outil de simulation de l’exploitation du réseau) presented in this paper allows the planning engineers to consider operational and transversal aspects (transmission and distribution view) of the system. OSER is composed of several modules, each of which is related to different parts of the utility. The load, interconnection, and production modules prepare profiles for each substation, interconnection, and generating unit, respectively. The virtual operator module models the actions and mitigation means of the grid operators. These include the generation load balance, voltage, reactive power control, and interconnection management. Thereby, OSER can simulate the reaction of the transmission system for all relevant scenarios by using the guidance of the transmission system operator. The results obtained by simulation validate the performance of the OSER simulator by comparing them with historical data. This tool enables transmission grid planners to include non-wire alternatives in their planning process. Further work will be conducted to extend the simulation modes towards year-long and stochastic simulations for better planning robustness.