Relative Distance Research Articles

Coupling Molecular Systems with Plasmonic Nanocavities: A Quantum Dynamics Approach.

Plasmonic nanoparticles have the capacity to confine electromagnetic fields to the subwavelength regime and provide strong coupling with few or even a single emitter at room temperature. The photophysical properties of the emitters are highly dependent on the relative distance and orientation between them and the nanocavity. Therefore, there is a need for accurate and general light-matter interaction models capable of guiding their design in application-oriented devices. In this work, we present a Hermitian formalism within the framework of quantum dynamics and based on first-principles electronic structure calculations. Our vibronic approach considers the quantum nature of the plasmonic excitations and the dynamics of nonradiative channels to model plasmonic nanocavities and their dipolar coupling to molecular electronic states. Thus, the quantized and dissipative nature of the nanocavity is fully addressed.

A comparative study of interpolation algorithms on non-matching meshes for PFEM-FEM fluid-structure interactions

In simulations involving fluid-structure interactions, the partitioned coupling approach allows calculating the fluid flow and the structural displacement using different solvers, which are coupled by a structure-to-fluid algorithm. This partitioned scheme can result in non-conforming meshes at the solid-fluid interface, especially when the fluid and the structure meshes contain elements of different characteristic sizes. In this context, a mesh-interpolation technique is required to transmit the nodal information from one mesh to the other. This paper focuses on comparing radial basis functions and k-nearest neighbours interpolations on fluid-structure interaction test cases. Indeed, those are fast and flexible techniques requiring no topological information other than relative distances between nodes, allowing a straightforward transfer of nodal data between non-conforming meshes. This feature is particularly favourable in the Particle Finite Element Method (PFEM), where remeshing procedures result in significant changes of the finite element discretisation at the fluid-structure interface. Accordingly, our contribution compares the interpolations in a PFEM/FEM partitioned scheme, using 2D and 3D benchmark problems.

Two-particle quantum walk on graphene structure graph

Graphene, a new material with a hexagonal honeycomb sheet structure composed of a single layer of carbon atoms, is the world's thinnest and strongest substance known to human, it has low resistivity and strong light transmission characteristics, so it can be used as a candidate material for integrated circuit chips and new energy batteries. In this paper, we mainly discuss the quantum walk of two non-interacting particles on the graphene structure graph, in which we select coin operator G in coin space HC and construct shift operator S, the time evolution operator U is obtained from the tensor of G and S. Since two particles without interaction can occupy the same site, the initial state is a composite of two particles at the same site. On this foundation, the relation between the relative distance and evolution time of two non-interacting particles is studied by the distance evolution operator.

Intermastoid distance as a criterion for determining the sex of the human skull

Annotation. The mastoid processes of the temporal bones are of great interest from the point of view of determining the sex of whole skulls and their fragments. The researchers established sex differences in the linear dimensions of the mastoid processes, the shape and dimensions of the mastoid triangle, and the length of the intermastoidale distance. By discriminant function analysis, it was determined that the intermastoidale distance is one of the best indicators for determining the gender of the skull. At the same time, previous studies of the sex difference in the intermastoidale distance did not consider the relationship of this indicator with morphometric parameters characterizing the size of the skull. The purpose of this study is to establish the patterns of individual variability of the intermastoidale distance, namely, its relationship with the variability of the width of the skull base, the distance between asterions and the width of the cerebral cranium (transverse diameter of the skull). The study was conducted on 55 skulls (35 male and 20 female) from the craniological collection of the Department of Human Anatomy of KhNMU. Correspondence of the distribution of morphometric indicators to the normal distribution was determined using the Kolmogorov-Smirnov test with the Lilliefors correction. Statistical processing of measurement results was carried out using Excel 10 and Statistica 7 software packages. It was established that the intermastoidale distance in men is significantly greater than in women (M±s: 108,0±5,7 and 98±1,6, respectively; p<0.05). This is explained by the larger size of the male skull compared to the female one and the peculiarities of the constitution of male and female organisms. In men, there are statistical relationships between the intermastoidale distance and the width of the base of the skull (y = 0.5x + 41.0; r = 0.6; ); between the intermastoidale distance and the width of the cerebral part of the skull (y=0,4x+52,4; r=0,4); between the intermastoidale distance and the distance between asterions (y=0,6x+41,8; r=0,4) are noticeable and statistically significant (p<0.05). At the same time, in women they are small and statistically insignificant (respectively y=0,1x+87,4; r=0,3; y=0,1x+88,1; r=0,2; y=0,2x+74.8; r=0,3, p>0,05). The difference in the strength of the correlation between the studied parameters in male and female skulls may indicate the influence of various factors on the degree of the intermastoidale distance relationships with the studied skull dimensions depending on sex. We propose to consider the strong positive correlation between the intermastoidale distance and the width of the skull base established in this study as a factor that will allow for a qualitative (significant) increase in the accuracy of skull sex determination.

Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations

Physics-informed neural networks have emerged as an alternative method for solving partial differential equations. However, for complex problems, the training of such networks can still require high-fidelity data which can be expensive to generate. To reduce or even eliminate the dependency on high-fidelity data, we propose a novel multi-fidelity architecture which is based on a feature space shared by the low- and high-fidelity solutions. In the feature space, the representations of the low-fidelity and high-fidelity solutions are adjacent by constraining their relative distance. The feature space is represented with an encoder and its mapping to the original solution space is effected through a decoder. The proposed multi-fidelity approach is validated on forward and inverse problems for steady and unsteady problems described by partial differential equations.

What produces corporate social irresponsibility in offshore outsourcing? The effects of interorganizational relationship governance and institutional distance

We theorize on how institutional distance and interorganizational relationship (IOR) governance interact to produce corporate social irresponsibility (CSiR) in offshore outsourcing. Managers generally find it challenging to align practices with stakeholders’ responsibility expectations and more so when activities occur offshore and outside organizational boundaries. This is evident from Apple’s repeated problems in China but insufficiently understood in international business (IB) literature. Institutional distance increases the likelihood and severity of CSiR because it produces a gap in buyers’ and suppliers’ stakeholder expectations and leads to divergence between suppliers’ practices and buyers’ responsibility policies. Trust-based cooperative IORs reduce CSiR and lessen the effect of institutional distance on CSiR. Supplier dependence also reduces CSiR but increases the effect of institutional distance on CSiR and is therefore a double-edged sword. Our novel framework generates insights into CSiR, a dark side of IB, by uncovering the mechanisms that co-produce CSiR in the offshore outsourcing context. We enrich work on offshore outsourcing by suggesting that CSiR represents a hidden cost and advance multilevel theorizing in IB by showing how institutional distance interacts with IOR governance. Managers should consider the tradeoff between performance and CSiR in offshore outsourcing and the downside that comes from (over)exploiting supplier dependence.

A Security Scheme for Statistical Anomaly Detection and the Mitigation of Rank Attacks in RPL Networks (IoT Environment)

A Routing Protocol for Low-power-lossy (RPL) networks builds a Destination Oriented Directed Acyclic Graph (DODAG) to provide IPv6 connectivity for resource-constrained devices over a large variety of low-power-lossy link layer technologies. Each RPL node maintains a rank value, which quantizes its relative topological distance from the DODAG root and is calculated based on the rank of its preferred parents and the objective function being employed. The RPL routing process does not impose any check to monitor the action and conduct of the parent nodes. A malicious attacking node can exploit this weakness by faking its rank value to be much lower than the original to attract more traffic to traverse through it from its neighboring and underlying child nodes. An attacking node can choose to perform selective forwarding or a sinkhole attack (Rank Attack type 1 – RA1) or exacerbate network performance parameters by causing topological instability (Rank Attack type 2 - RA2). This paper presents the Statistically-based Anomaly Detection Scheme (SARPL) to detect RA1 and RA2 and attempts to mitigate their effects. The simulations and performance evaluations show that SARPL can successfully detect RA1 attacks in all scenarios whereas it has a positive detection rate of approximately 93% for RA2 type attacks. SARPL also significantly improves network performance parameters, such as packet delivery rate and end-to-end delay, while mitigating the effects of RA1 and RA2.

Evaluation of the Genetic Diversity and Population Structure of Four Native Pig Populations in Gansu Province.

Indigenous pig populations, including Bamei pigs (BM), Hezuo pigs (HZ), Huixian Qingni Black pigs (HX), and Minxian Black pigs (MX) in Gansu Province, live in a particular climate and a relatively closed geographical environment. These local pig breeds are characterized by excellent characteristics (e.g., cold tolerance, robust disease resistance, and superior meat quality). In the past few years, pig populations in Gansu Province have decreased significantly because of their poor lean meat percentage, high fat content, and slow growth rate. Maintaining the diversity of these four breeds can act as a source of new alleles to be incorporated into commercial breeds which are more susceptible to disease and less adaptable to changing conditions because of inbreeding. Genomic data analysis is adequate for determining the genetic diversity and livestock breeding population structure, even in local pig populations. However, the genetic diversity and population structure of the four native pig populations in Gansu Province are still unknown. Thus, we used "Zhongxin-I" porcine chip for the SNP detection of 102 individuals living on four pig conservation farms. A total of 57,466 SNPs were identified among the four pig breeds. The linkage disequilibrium (LD) plot showed that MX had the highest level of LD, followed by BM, HZ, and HX. The observed heterozygosity (Ho) in all four populations was higher than the expected heterozygosity (He). A principal component analysis (PCA) demonstrated that the four local pig populations were isolated. The identity displayed by the state matrix and G matrix heat map results indicated that small numbers of individuals among the four pig breeds had a high genetic distance and weak genetic relationships. The results of the population genetic structure of BM, HZ, HX, and MX pigs showed a slight genetic diversity loss. Our findings enabled us to better understand the genome characteristics of these four indigenous pig populations, which will provide novel insights for the future germplasm conservation and utilization of these indigenous pig populations.

Risk analysis of autonomous vehicle test scenarios using a novel analytic hierarchy process method

AbstractScenario‐based test methods are employed to assess the safety and performance of autonomous vehicles. The analytic hierarchy process (AHP) method is a common assessment method for determining the criticality of test scenarios. However, the AHP method is subjective and less reproducible when performed by different persons, as the elements of pairwise comparison values that are directly linked to the outcome must be assigned by the person involved. This paper proposes a novel AHP method that automatically generates pairwise comparison values by optimizing the correlation between performance metrics and risk of test scenarios by simulation. Performance metrics are defined as the minimum relative distances and corresponding relative velocities between vehicles, and the risk of the test scenario is determined by the pairwise comparison values of AHP. The novel AHP method was evaluated using a cut‐in scenario. The results showed that the minimum relative distance and the risk determined by the novel AHP method achieved a better correlation coefficient of −0.96, which is better than the conventional AHP of −0.828 and Fuzzy AHP of −0.824. These results suggest that the criticality of the test scenarios determined by the novel AHP method can more accurately reflect real‐world driving environments.

Relative Distance Control of Uncooperative Tethered Debris

Relative Distance Control of Uncooperative Tethered Debris

Group efficiency and individual fairness tradeoff in making wise decisions

In group decision making, the consensus model with minimum cost has been researched with the aim of improving group efficiency and saving resources. However, one limitation of the minimum cost consensus model is that the reach of consensus is usually at the expense of some group members. We consider two issues that we see as keys in group consensus: efficiency and fairness. We propose the price of fairness in the opinion revision process and give two kinds of fairness schemes. According to the individual's perception of inequity, we introduce inequity aversion parameters and classify experts into two types: experts with non-cooperative behaviors and with altruistic behaviors. Experts with altruistic behaviors will be allowed to contribute more than the recommended number of modifications. Then, we discuss how to achieve the tradeoff between efficiency and fairness. Furthermore, with the rapid development of social media, cloud, and e-government platforms, collective intelligence (CI), i.e., groups of individuals doing things collectively that seem intelligent, has been a hot topic. We expand our work to a crowd context with many individuals. We investigate how the opinion revision process and fairness schemes can influence the emergence of CI. Results suggest that the proportional fairness and max-min fairness have similar performance in stimulating CI. Moreover, the improvement of group accuracy is mainly related to two factors: the group consensus level of initial opinions and the relative distance between group aggregated opinion and the ground truth.

Accuracy of impression scan bodies for complete arch fixed implant-supported restorations

Statement of problemDespite the extensive studies on and comparisons of different implant impression techniques for completely edentulous patients, studies on novel techniques that combine conventional impression making with digital scanning are lacking. PurposeThe primary aim of this study was to compare the accuracy of the impression scan body technique with conventional impression making and digital scanning for a completely edentulous mandibular arch. The secondary aim was to assess the relationship between different implant angulations and interimplant distances in relation to the recording accuracy. Material and methodsAn edentulous mandibular definitive cast (control) was designed with 5 implants placed at different angles and interimplant distances. Three recording techniques were tested: a conventional impression with splinted copings (conventional) (n=15), an impression scan body technique where impression scan bodies were attached to the splinted impression copings in a conventional elastomeric impression and then digitally scanned with an extraoral scanner (n=15), and an intraoral digital scanning technique (digital) (n=15). For comparison, the definitive cast and the conventional impression stone casts were digitized into standard tessellation language (STL) datasets using the extraoral scanner. The 3-dimensional (3D) deviations between the 3 test groups and the control were calculated by superimposing the STL datasets. The 3D deviations from the control were compared by using the Kruskal-Wallis test followed by the Dunn post hoc test (α=.05). The Mann-Whitney test was used to investigate the effect of implant angulation and interimplant distance on impression accuracy (α=.05). ResultsThe conventional splinted-coping impression technique showed a mean 3D deviation of 0.408 mm. The impression scan body and intraoral digital scan showed similar mean 3D deviations, 0.219 mm and 0.257 mm, respectively (P=.334). Both techniques showed significantly lower 3D deviations than the conventional technique (P<.001). Implants at an angle of 5 degrees and 10 degrees showed a statistically significant difference (P=.010) with mean 3D deviations of 0.340 mm and 0.396 mm, respectively. Implants with 5-mm and 10-mm interimplant distance showed a significant difference (P<.001) with mean 3D deviations of 0.301 mm and 0.423 mm, respectively. ConclusionsThe impression scan body technique is comparable with intraoral digital scanning for a completely edentulous arch. Increased implant angulation and increased interimplant distance significantly reduced the accuracy of implant impression making or scanning.

Self-Supervised Triplet Contrastive Learning for Classifying Endometrial Histopathological Images.

Early identification of endometrial cancer or precancerous lesions from histopathological images is crucial for precise endometrial medical care, which however is increasing hampered by the relative scarcity of pathologists. Computer-aided diagnosis (CAD) provides an automated alternative for confirming endometrial diseases with either feature-engineered machine learning or end-to-end deep learning (DL). In particular, advanced self-supervised learning alleviates the dependence of supervised learning on large-scale human-annotated data and can be used to pre-train DL models for specific classification tasks. Thereby, we develop a novel self-supervised triplet contrastive learning (SSTCL) model for classifying endometrial histopathological images. Specifically, this model consists of one online branch and two target branches. The second target branch includes a simple yet powerful augmentation module named random mosaic masking (RMM), which functions as an effective regularization by mapping the features of masked images close to those of intact ones. Moreover, we add a bottleneck Transformer (BoT) model into each branch as a self-attention module to learn the global information by considering both content information and relative distances between features at different locations. On public endometrial dataset, our model achieved four-class classification accuracies of 77.31 ± 0.84, 80.87 ± 0.48 and 83.22 ± 0.87% using 20, 50 and 100% labeled images, respectively. When transferred to the in-house dataset, our model obtained a three-class diagnostic accuracy of 96.81% with 95% confidence interval of 95.61-98.02%. On both datasets, our model outperformed state-of-the-art supervised and self-supervised methods. Our model may help pathologists to automatically diagnose endometrial diseases with high accuracy and efficiency using limited human-annotated histopathological images.

Application of the Grey TOPSIS Method to Assess and Select a Contractor in Terms of Occupational Safety Management

Abstract The objective of the article is to analyze the possibility of using the gray TOPSIS method to evaluate and select a contractor due to specific criteria regarding occupational health and safety management (OHSM). The choice of contractor is a problem for the decision-maker to make decisions based on many criteria, and most often, these criteria are very diverse, both quantitative and qualitative. The gray TOPSIS method is based on the use of a measure of the relative distance from the best solution, constituting the pattern, and from the worst solution, constituting the anti-pattern, to sort the solutions, using the Grey System Theory. To evaluate and select the contractor, 12 different criteria were used, describing the key areas of OHSM for the decision-maker. The criteria and their weights were selected taking into account the nature of the work planned to be carried out by the company ordering the work. Z-10 annual reports on working conditions in a given year submitted by enterprises to the Central Statistical Office, expert assessments and occupational health and safety procedures provided by five potential contractors were used as sources of information. The research confirmed that the use of gray numbers as part of the TOPSIS method allows the ranking of potential contractors from the point of view of selected criteria and the selection of the company that best meets the assumed occupational health and safety management criteria.

Hubungan Antara Self Disclosure dengan Interpersonal Trust pada Pasangan Dewasa Awal yang Menjalani Long Distance Relationship (LDR)

Long distance relationship (LDR) is a form of romantic relationship where two people are separated by physical distance which makes it difficult for both to establish closeness within a certain period. Of course, living in a long-distance relationship is not an easy thing if there is no self-disclosure and interpersonal trust in the relationship. Openness is one of the factors that play an important role in forming interpersonal trust. Openness arises because of the trust between partners and this encourages them to feel comfortable in sharing all kinds of information about themselves to their partners. The purpose of this study is to determine the relationship between self-disclosure and interpersonal trust in early adult couples who undergo long-distance relationships. This study uses a correlational quantitative approach with 120 respondents. The sampling technique in this study used accidental sampling. The results of the correlation coefficient analysis obtained are 0.837 and the significance value of the correlation r is 0.000 (p &lt;0.05). The effective contribution between self-disclosure and interpersonal trust is 70%. So it can be concluded that there is a positive relationship between self-disclosure and interpersonal trust, meaning that the higher the self-disclosure, the higher the level of interpersonal trust in early adult couples who undergo long-distance relationships, and vice versa

Identification of Approaching Vehicle using Arduino

Many safety-critical Advanced Driver Assistance Systems (ADAS) applications, including automatic emergency braking, pedestrian detection, surround view parking assistance, driver drowsiness detection, and gaze detection, are dedicated to helping drivers prevent car accidents and safeguard lives. In situations where numerous vehicles share the road simultaneously, having precise data onthe relative speed and distance between these vehicles is of paramount importance. To calculate both long-range and short-range information, specialized sensors are utilized to estimate vehicle speed and range.The central objective of this project is to effectively detect approaching vehicles. This goal is achieved by using a Doppler radar module to sense vehicle movements, and an Arduino board is employed to process the radar signals, providing the necessary data.

Robust spacecraft relative pose estimation via CNN-aided line segments detection in monocular images

Autonomous spacecraft relative navigation via monocular images became a hot topic in the past few years and, recently, received a further push thanks to the constantly growing field of artificial neural networks and the publication of several spaceborne image datasets. Despite the proliferation of spacecraft relative-state initialization algorithms developed, most architectures adopt computationally expensive solutions relying on convolutional neural networks (CNNs) that provide accurate output at the cost of a high computational burden that seems unfeasible for current spaceborne hardware. The paper addresses this issue by proposing a novel pose initialization algorithm based on lightweight CNNs. Inspired by previous state-of-the-art algorithms, the developed architecture leverages a fast and accurate target detection CNN followed by a line segment detection CNN capable of running with low inference time on mobile devices. The line segments and their junctions are grouped into complex geometrical groups, reducing the solution search space, and subsequently, they are adopted to extract the final pose estimate. As a main outcome, the analyses demonstrate that the lightweight architecture developed scores high accuracy in the pose estimation task, with a mean estimation error of less than 10 cm in translation and 2.5°in rotation. The baseline algorithm scores a mean SLAB error of 0.04552 with a standard deviation of 0.22972 in the test dataset. Detailed analyses demonstrate that the uncertainties on the overall pose score are driven mainly by errors in the relative attitude, which gives the highest contribution to the pose error metric adopted. The analyses on the error distributions point out that the uncertainties on the estimated relative position are higher in the camera boresight axis direction. Concerning the relative attitude, the algorithm proposed has higher uncertainties in estimating directions of the target x and y axes due to ambiguities related to the target geometry. Notably, the target detection CNN trained in this work outperforms the previous top scores in the benchmark dataset. The performances of the proposed algorithm have been investigated further by analyzing the effects on the accuracy due to the relative distance and the presence of background in the images. Lastly, the paper delves into the possibility of adopting a sub-portion of the 2D-to-3D match matrix made by the most complex perceptual groups identified that positively affects the overall run-time, pointing out the performances in terms of accuracy of the estimates and providing a comparison of both the baseline and the reduced match matrix versions against state-of-the-art algorithms concerning relative position and attitude errors and solution availability, highlighting the high accuracy and solution availability of the proposed architectures.

Numerical investigation of heat transfer enhancement in solar air heaters using polygonal-shaped ribs and grooves

Solar air heating thermal systems have found extensive utilization in a broad array of industrial and residential settings, playing a pivotal role in the conversion and reclamation of solar energy. Implementing repeated artificial roughness in the surfaces has the potential to augment thermal performance in solar air heaters (SAHs). This study presents a numerical investigation of SAHs with artificial rough surfaces, consisting of polygonal-shaped ribs and grooves located at different places inside the rectangular duct, that improve thermal efficiency. ANSYS Fluent software was employed to simulate the SAH with different relative pitch distances of p = 10 mm and 20 mm and relative rib heights e/d = 0.09–0.045. The working fluid air flows at different Reynolds numbers (Re), ranging from 3,800 to 18,000. Nusselt number (Nu), friction factor (f), and Thermal Hydraulic Performance (THP) are parameters to evaluate the performance of the SAH. The renormalized group (RNG) k-ϵ turbulent model was implemented in this simulation. The study outcomes indicate that increasing the rib height improves the heat transfer rate and nonetheless increases pressure drop while increasing the pitch distance. The higher Nusselt number (Nu) is 3.762 attained at p = 10 mm and 3.420 at p = 20 mm in the center-positioned rib at Re 3,800. The lower friction factor (ƒ) obtained in p = 20 mm is 1.681 and 0.785 in p = 10 mm in the staggered positioned rib at higher Re 15,000. The optimal THP was achieved at 2.813 at a staggered rib height at a pitch distance of p = 10 mm at Re 8,000. The study’s findings suggest that the incorporation of artificial rough surfaces has the potential to enhance the THP of an SAH.

Globalisation and agri-food trade

Abstract This study utilises structural gravity models to examine the impact of globalisation on distance in agricultural and processed food trade, the relative effects of international distance and home bias effects. The results show that larger internal distances lower domestic sales. The home bias effect is substantially larger in agricultural commodities compared to processed agricultural commodities. Omitted variable bias is observed in friction variables when the relative intra-national distance and home market bias are excluded. After controlling for relative intra-national trade costs and the home bias effect, globalisation does not lead to a smaller impact of distance on trade. Substantial heterogeneity exists when analysing individual commodities.

Bichronous pedagogy in ODFL

This developing case-study from the Initial Teacher Education suite of programmes at the Open Polytechnic | Te P?kenga, Aotearoa, New Zealand, describes how synchronous elements are added to an asynchronous delivery model to create bichronous delivery for Open, Distance and Flexible Learning (ODFL). From 2017 onwards, ODFL principles underpinned a wholly asynchronous delivery model at the Open Polytechnic that championed ?konga (learner) agency through anytime anyplace access to tertiary education. This delivery model, successful in removing the conditions of time and place, created a consequence of relational distance, with limited real-time academic presence and peer-peer interaction. The new ITE programmes, opening in 2023, provided an opportunity to introduce synchronous elements within the asynchronous model. These elements were predicated on the principles of ODFL aligned to the values of cultural responsiveness: whakawhanaungatanga (relational connections), manaakitanga (respect and care), rangatiratanga (self-determination), and akoranga (reciprocity of teaching and learning). Early experiences suggest that introducing synchronous elements to asynchronous ODFL provides opportunities for real-time communication, enhances relational connection, and reduces the negative consequence of relational distance and isolation sometimes experienced in asynchronous pedagogies.