Many Researchers In Different Fields Research Articles

A novel approach to optimize an integrated network design and pricing of a healthcare supply chain

Adopting various pricing policies has been highly regarded in recent years for setting prices and increasing firms' profits. One of the most common steps in pricing is to identify costs. Since a significant part of costs is related to the corresponding supply chain, many researchers in different fields have used decision-making for simultaneous pricing and network design. However, there is no such approach in the field of healthcare. This paper tries to fill this gap by formulating a mixed-integer nonlinear bi-level programming model examining the interaction of hospitals and their medicines suppliers. At the upper level, there is a competitive market where a new firm (entrant) intends to enter the market and faces the challenge of pricing medicines and making network design decisions. At the lower level, there is a private hospital competing with a public hospital, and it also struggles with healthcare services pricing and supplier selection. A comprehensive utility function that considers healthcare services prices, quality, waiting time, health insurance, readmission rate, and referral rate is extended at this level. Three novel meta-heuristic algorithms are recommended, including bi-level, improved fruit fly, jellyfish optimization, and forensic-based investigation optimization algorithms to solve the presented complex mathematical problem.

Implicit Surface Tension for SPH Fluid Simulation

The numerical simulation of surface tension is an active area of research in many different fields of application and has been attempted using a wide range of methods. Our contribution is the derivation and implementation of an implicit cohesion force based approach for the simulation of surface tension effects using the Smoothed Particle Hydrodynamics (SPH) method. We define a continuous formulation inspired by the properties of surface tension at the molecular scale which is spatially discretized using SPH. An adapted variant of the linearized backward Euler method is used for time discretization, which we also strongly couple with an implicit viscosity model. Finally, we extend our formulation with adhesion forces for interfaces with rigid objects. Existing SPH approaches for surface tension in computer graphics are mostly based on explicit time integration, thereby lacking in stability for challenging settings. We compare our implicit surface tension method to these approaches and further evaluate our model on a wider variety of complex scenarios, showcasing its efficacy and versatility. Among others, these include but are not limited to simulations of a water crown, a dripping faucet, and a droplet toy.

IndiSPENsable for X Chromosome Inactivation and Gene Silencing.

For about 30 years, SPEN has been the subject of research in many different fields due to its variety of functions and its conservation throughout a wide spectrum of species, like worms, arthropods, and vertebrates. To date, 216 orthologues have been documented. SPEN had been studied for its role in gene regulation in the context of cell signaling, including the NOTCH or nuclear hormone receptor signaling pathways. More recently, SPEN has been identified as a major regulator of initiation of chromosome-wide gene silencing during X chromosome inactivation (XCI) in mammals, where its function remains to be fully understood. Dependent on the biological context, SPEN functions via mechanisms which include different domains. While some domains of SPEN are highly conserved in sequence and secondary structure, species-to-species differences exist that might lead to mechanistic differences. Initiation of XCI appears to be different between humans and mice, which raises additional questions about the extent of generalization of SPEN's function in XCI. In this review, we dissect the mechanism of SPEN in XCI. We discuss its subregions and domains, focusing on its role as a major regulator. We further highlight species-related research, specifically of mouse and human SPEN, with the aim to reveal and clarify potential species-to-species differences in SPEN's function.

CoDiS: Community Detection via Distributed Seed Set Expansion on Graph Streams

Community detection has been (and remains) a very important topic in several fields. From marketing and social networking to biological studies, community detection plays a key role in advancing research in many different fields. Research on this topic originally looked at classifying nodes into discrete communities (non-overlapping communities) but eventually moved forward to placing nodes in multiple communities (overlapping communities). Unfortunately, community detection has always been a time-inefficient process, and datasets are too large to realistically process them using traditional methods. Because of this, recent methods have turned to parallelism and graph stream models, where the edge list is accessed one edge at a time. However, all these methods, while offering a significant decrease in processing time, still have several shortcomings. We propose a new parallel algorithm called community detection with seed sets (CoDiS), which solves the overlapping community detection problem in graph streams. Initially, some nodes (seed sets) have known community structures, and the aim is to expand these communities by processing one edge at a time. The innovation of our approach is that it splits communities among the parallel computation workers so that each worker is only updating a subset of all the communities. By doing so, we decrease the edge processing throughput and decrease the amount of time each worker spends on each edge. Crucially, we remove the need for every worker to have access to every community. Experimental results show that we are able to gain a significant improvement in running time with no loss of accuracy.

Ostwald Rule of Stages─Myth or Reality?

In 1897, following a number of crystallization studies, Ostwald suggested that if a system has a number of metastable states open to it then it proceeds sequentially by means of the nearest thermodynamic state and so on. This conjecture, which is known as Ostwald’s Rule of Stages (ORS), has gained traction with many researchers in many different fields. However, there has been no general proof of its validity. In this paper the specific case of batch solution crystallization of a polymorphic compound using classical nucleation and growth theory is examined in some detail and the ORS conjecture is found wanting. Classical nucleation theory presents not a sequential process, as in ORS, but a parallel process of multiphase nucleation and growth development of all metastable phases. What is observed is not the appearance of metastable phases sequentially but the disappearance of phases sequentially in the order of their metastability. If the crystallization kinetics of the metastable phases are suitably differentiated and advantageous the system might appear to be sequential under suitable conditions. This analysis does not exclude ORS from being applicable in other transformation cases. For instance, it is possible that systems where the subsequent phase changes are governed by solid-state transformations then the sequential model proposed by Ostwald might be appropriate but whether this covers all available metastable states is an open question.

Biotopic Features Change the Size of Carabus Odoratus Shil

Body size variation attracts attention of many researchers in different fields because of its importance in organisms functioning. We sampled ground beetles of mountain species Carabus odoratus in different biotopes of Barguzinskiy Ridge (northeast part of Baikal Lake; N 54° 20’; E 109° 30’; Russia). Nine biotopes at different elevation were under the study. We measured sampled beetles for six morphometric traits (elytra, pronotum, head lengths and width). In total 984 specimens were measured individually. Length parameters varied to greater extent in C. odoratus. Elytra length and pronotum and head length as well were significantly shorter in beetles dwelling in aspen, fir, tundra, health and park birch if compared with ones in forestry habitats. Wherein width parameters were, roughly speaking, similar in beetles of all studied biotopes. Undoubtedly observed effect of biotope impact on beetles’ size variation was connected with differing environmental factors at the certain elevations.

A Pairing-Free Heterogeneous Signcryption Scheme for Unmanned Aerial Vehicles

During the past few years, as Internet of Things develops rapidly, the applications of unmanned aerial vehicle (UAV) technology have been increasingly widely used. Meanwhile, the efficiency and security issues of UAV communication have brought about widespread attention of many researchers in different fields. In an open wireless network, the attacks on UAV communication mainly include eavesdropping, tampering, interrupting, forgery, etc. Signcryption is an appropriate method to address these security problems. However, the existing signcryption schemes are not suitable for UAVs with limited resources and ground station (GS) that needs to process a large number of messages from UAVs. Moreover, in a certain area, UAVs and a GS may belong to different cryptosystems. Therefore, in this article, we came up with a heterogeneous signcryption scheme for UAVs to communicate to a GS (HSC-U2G) without bilinear pairing operation, where UAVs belong to identity-based cryptography (IBC) while the GS belongs to public-key infrastructure (PKI). Moreover, our scheme provides identity privacy for UAVs and supports batch verification for the GS. Using the random oracle model, we demonstrate HSC-U2G can achieve insider security for confidentiality as well as unforgeability. After that, HSC-U2G is compared with several important related works and we provide all experimental results to show the efficiency.

Under which conditions do manufacturing companies choose FDI for service provision in foreign markets? An investigation using fsQCA

Studying the provision of services from the point of view of manufacturing firms has been highlighted by many researchers in different fields. Besides, research on international business on the internationalization of either goods or services is vast, but rare on the combination thereof. While some studies have shown that firm-, country- and offering-specific factors can influence the foreign operation mode (FOM) of goods-related services, only a few have examined how these factors interrelate. The purpose of this study is to detect different configurations of conditions leading to a same decision. To answer this, the present study draws on the configurational approach and examines how combinations of different conditions lead to the choice of foreign direct investment (FDI) for service provision.A state-of-the-art fuzzy set qualitative comparative analysis (fsQCA) is applied to a sample of 111 Swiss and German industrial goods manufacturers. Choosing FDI for the provision of goods in foreign markets constitutes a necessary condition for service FDI. From the sufficiency analysis, several causal paths are detected. Companies with a servitization strategy choose FDI for their service resources only in digitally ready countries. The results furthermore show that differences between base, intermediate and advanced services exist. Also, the digital readiness of the country is found to be an important influence factor on the FDI decision.

Quantitative ABCD Analysis of Online Food Delivery Services

Purpose: The core idea of the study is to understand the development of ABCD framework for analysing Online Food Delivery Services and to identify and evaluate the determinant issues and key attributes affecting the factors such as Advantages, Benefits, Constraints, and Disadvantages from stakeholders’ point of view and to find the major affecting factor in respect to Online Food Delivery Services. Design: The study has systematically reviewed the published paper related to the ABCD analysis framework from 2016 to 2021. The study employed quantitative analysis through focus group interaction by allotting appropriate weightage to key attributes to find the major affecting factors and critical constituent elements for Online Food Delivery Services. Findings: ABCD analysis framework is the technique used to analyse and evaluate a business model, concept, product, strategy or system. This technique is used by many researchers in different fields for the analysis of their research studies. Quantitative ABCD analysis of Online Food Delivery Services found that Advantages factors affect majorly for the success of the business. The result of ABCD analysis supports the concept/ ideas effectiveness of Online Food Delivery Services. Originality: The paper gives insights on the determinant issues, key attributes, major affecting factors and critical constituent component elements as per the ABCD analysis framework for Online Food Delivery Services. Type of Paper: Empirical Analysis

The soundscape of quarantine

Given the drastic effect of ongoing lockdowns during the COVID-19 pandemic of 2020–2021, many researchers in different fields found themselves learning the basics of epidemiology and public health. However, in the midst of such a crisis, it is incumbent for content experts to apply their own expertise to the problem at hand, no matter how marginal their contribution may be. It is argued that at the broadest level, acousticians may contribute to the mental and physical health of those undergoing pandemic lockdowns via soundscape analysis. Given the widespread lockdown fatigue of staying largely indoors for nearly a year, even small improvements in quality of life under lockdown may be help the wider crisis by helping people follow public health recommendations longer than they otherwise would. The first part of this analysis focuses on noise prevention, especially in multi-unit housing where sound transmission between units can exacerbate social ties. Second, this talk examines the role of acoustic simulation, spatial audio, and VR to open up larger worlds to those under prolonged confinment.

Predictors of family violence through the COVID-19 pandemic: Structural equation modeling.

There has been much talk, globally and locally, about family violence during the COVID‐19 pandemic. Family violence has received increasing interest from the researchers in many different fields, while family violence during the COVID‐19 pandemic outbreak still needs researchers' attention to investigate its predictors and detect the prevalence among family members through this health crisis. This study aimed to investigate the spread of family violence and detect the predictors of it with the applied advanced statistical procedure, structural equation modeling (SEM). The researchers prepared the family violence scale that consisted of 21 items, and applied it in a random sample that consisted of (312) individual. The finding indicated that there are high levels of family violence, violence between spouses, violence from parents to children, and sibling violence. As well as, the findings found that the years of marriage are statistically significant of violence between spouses, violence from parents to children, and sibling violence, and the total score of the family violence. As well as, sex is a statistically significant predictor of violence between spouses. While the educational level, age, and income level did not predict violence (total score or dimensions). Based on the results of the current study, counseling programs to reduce family violence and psychotherapy programs to reduce the negative effects of family violence on parents and children must be planned. Therefore, the role of traditional and online family counseling and psychotherapy must be activated in light of the outbreak of the COVID‐19 pandemic.

INPUTING STUDENTS’ SCORE BASED ON GIST FEATURES, SUPPORT VECTOR MACHINES AND TESSERACT

Handwriting recogination plays an important role in data inputing and processing in the practice. This attracts much attention of many researchers in different fields. In this paper, a new algorithm is proposed by basing on GIST features, Support Vector Machines (SVM) and Tesseract for entering the score on students’ transcript form at Soc Trang Vocational College. The algorithm consists of two main works, i.e., recognizing students’code and recogziing handwritten digit. In the proposed algorithm, all regions of interest are determined and extract their dictint features with using tesseract and GIST. Then, these features are classified by SVM mechanism. Experimental results demonstrated that the proposed algorithm obtained high performance with accuracy up to 96,57% for students’ code and 93,55% for Handwritting scores. Average time was 7,9s per one transcript.

3D elastic plane-wave diffraction by a stress-free wedge for incident skew angles below the critical angle in diffraction

Elastic plane wave diffraction by a stress-free wedge is a canonical problem of interest to researchers in many different fields. To our knowledge, no fully analytical resolution has been found and semi-analytical evaluations of asymptotic approximations have therefore become a common approach. In this paper, a method called the spectral functions method is developed in a 3D configuration, meaning that the incident ray is not necessarily in the plane normal to the wedge edge. The diffracted displacement field is expressed as an integral in terms of two unknown functions called the spectral functions. These functions are decomposed into two parts: one which can be computed analytically and the other which is approached numerically using a collocation method. The details of the corresponding numerical scheme are given and first numerical validations are presented. The presented method is valid for incident skew angles which are below the critical angle in diffraction.

Legitimacy and Symbolic Capital in the Field of Kebaya: A Case Study on Anne Avantie’s Kebaya Show in Jakarta

Bourdieu’s concepts of legitimacy and symbolic capital have provided invaluable insights for the structures of social relations. These concepts have been used by many researchers in many different fields. However, there is a lack of academic discussion using these two concepts to study the connection between legitimacy and the practice of symbolic capital in the field of kebaya. Referring to this fact, this study aims to fill the gap. Therefore, this project is intended to examine how legitimacy is gained by an Indonesian female kebaya designer, Anne Avantie, and how the symbolic capital operates in the field of kebaya. In an attempt to collect the data, a close observation on a kebaya show held by Anne Avantie had been done and some articles about her had been read. Meanwhile, this project applies a qualitative method. The research finding shows that Avantie initially received legitimacy as a kebaya designer from consumers and then followed by many other important parties such as politicians, many organizations and institutions. This success generates the symbolic capital that puts her as a kebaya trandsetter and enables her to change the doxa of kebaya.
 Keywords: legitimacy, symbolic capital, doxa, field of kebaya

Detouring school to family: A reading of Antigone

Sophocles’ Antigone is a play that has been analyzed by many researchers in different fields, but the subject of Antigone’s parenting has been neglected in the field of education. Antigone’s parenting determines her action of burying her brother, for which she pays a high price because she has defied the polis rules. The will of the polis can be viewed as reflected in schools in modern society. Inspired by the thoughts of Hegel, Lacan, and Paul Ricœur, this study proposes that for children, the school is a detour to family that continually prompts them to rethink their family, thus helping them obtain self-comprehension.

Predicting Hospitals Hygiene Rate during COVID-19 Pandemic

COVID-19 pandemic has reached global attention with the increasing cases in the whole world. Increasing awareness for the hygiene procedures between the hospital’s staff, and the society became the main concern of the World Health Organization (WHO). However, the situation of COVID-19 Pan-demic has encouraged many researchers in different fields to investigate to support the efforts offered by the hospitals and their health practitioners. The main aim of this research is to predict the hospital’s hygiene rate during COVID-19 using COVID-19 Nursing Home Dataset. We have proposed a feature extraction, and comparing the results estimating from K-means clustering algorithm, and three classification algorithms: random forest, decision tree, and Naive Bayes, for predicting the hospital’s hygiene rate during COVID-19. However, the results show that classification algorithms have addressed better performance than K-means clustering, in which Naive Bayes considered the best algorithm for achieving the research goal with accuracy value equal to 98.1%. AS a result the research has discovered that the hospitals that offered weekly amounts of personal protective equipment (PPE) have passed the personal quality test, which lead to a decrease in the number of COVID-19 cases between the hospital’s staff.

Features in the beliefs in the mother goddesses in Lam Dong

For a long time, Beliefs in the Mother Goddesses has become a topic that attracts many researchers in different fields of science. Especially after the Practices Related to the Viet Beliefs in the Mother Goddesses in Three Realms recognized by the UNESCO as an Intangible Cultural Heritage of Humanity the number of monographs and articles that mention different aspects of this worship is more diverse. In the mid-20s of the twentieth century, Beliefs in the Mother Goddesses appeared on Lang Biang plateau along with the process of migration, settling and forming Vietnamese community in this land. After nearly a century of introduction, shaping and development in the new land of the South Central Highlands, besides keeping the cognitive values, human values and traditional art and culture of Beliefs in the Mother Goddesses. In addition to preserving the cognitive values, human values and traditional art and culture of Beliefs in the Mother Goddesses in the Northern Delta, this worship of ethnic Viet group in Lam Dong had a process of interference, shaping and development with many differences. These characteristics are reflected in the diversity in the form of worship and religious activities. Using some main methods such as synthesis methods, analytical methods, qualitative research methods with the approach of ethnic minority fieldwork through two forms of observation and participation as well as conducting in-depth interviews ... the research will cover access to features in the Mother worshiping tradition in Lam Dong on the basis of comparison with the worship of the same name throughout the country. Besides, the article also points out some of the main reasons leading to the formation of these characteristics.

2D elastic plane-wave diffraction by a stress-free wedge of arbitrary angle

2D elastic plane wave diffraction by a stress-free wedge is a canonical problem of interest to researchers in many different fields. To our knowledge, no fully analytical resolution has been found and semi-analytical evaluations of asymptotic approximations have therefore become a common approach. In this paper, a method called the spectral functions method is developed in the aforementioned 2D configuration. This method has the advantage of being valid for wedge angles lower and higher than π. The diffracted displacement field is expressed as an integral in terms of two unknown functions called the spectral functions. These functions are decomposed into two parts: one which can be computed analytically and the other which is approached numerically using a collocation method. The details of the corresponding numerical scheme are given and the method is validated numerically for all wedge angles.

Optimizing Software Effort Estimation Models Using Back-Propagation Versus Radial Base Function Networks

Software development effort estimation becomes a very important and vital tool for many researchers in different fields. Software estimation used in controlling, organizing and achieving projects in the required time and cost to avoid the financial punishments due to the time delay and other different circumstances that may happen. Good project cost estimation will lead to project success and reduce the risk of project failure. In this paper, two neural network models are used, the Back-propagation algorithm versus the redial base algorithm. A comparison is done between the suggested models to find the best model that can reduce the project risks related to time and increase the profit by achieving the demands of the required project in time. The two models are implemented on a 60 of NASA public dataset, divided into 45 data samples for training and 15 data samples for testing. From the result obtained we can clearly say that the performance of the back-propagation neural network in training and testing cases is actually better than the radial base function, so the back-propagation algorithm can be recommended as a useful tool in the software effort and cost estimation.

A belief-rule-based model for information fusion with insufficient multi-sensor data and domain knowledge using evolutionary algorithms with operator recommendations

Multi-sensor information fusion (IF) has attracted the attention of many researchers in different fields because it can improve modeling accuracy by integrating information gathered from multiple sensors. Traditionally, the inputs of the multi-sensor IF problem are mostly quantitative data. However, to provide a more comprehensive decision support, both quantitative data and experts’ domain knowledge should be synthesized in the IF process. Moreover, there may be insufficient data in many practical conditions, which would make many conventional approaches inapplicable. Because the belief rule base (BRB) has shown advantages in nonlinear modeling with insufficient data and experts’ domain knowledge, a BRB-IF model is proposed for the multi-sensor IF problem. To improve its efficiency, an optimization model and the corresponding optimization algorithm for BRB-IF are proposed. The particle swarm optimization algorithm and differential evolutionary algorithm are tested as the optimization engine to solve the optimization model with the operator recommendation strategy. The efficiency of the proposed BRB-IF is validated by a practical case study of threat level assessment, where a comparison between BRB-IF and the neural network is conducted.