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The interplay between densification and positional ordering during the process of crystal nucleation is a greatly investigated topic. Even for the simplest colloidal model—hard spheres—there has been much debate regarding the potential foreshadowing of nucleation by significant fluctuations in either local density or local structure. Considering anisotropic particles instead of spheres adds a third degree of freedom to the self-organization process of crystal nucleation: orientational ordering. Here, we investigate the crystal nucleation of hard triangular prisms. Using Monte Carlo simulations, we first carefully determine the crystal–fluid coexistence values and calculate the nucleation barriers for two degrees of supersaturation. Next, we use brute force simulations to obtain a large set of spontaneous nucleation events. By studying the time evolution of the local density, positional ordering, and orientational ordering in the region in which the nucleus first arises, we demonstrate that all local order parameters increase simultaneously from the very start of the nucleation process. We thus conclude that we observe no precursor for the crystal nucleation of hard triangular prisms. [ABSTRACT FROM AUTHOR]

Colloidal and nanoparticle self-assembly enables the creation of ordered structures with a variety of electronic and photonic functionalities. The outcomes of the self-assembly processes used to synthesize such structures, however, strongly depend on the uniformity of the individual nanoparticles. Here, we explore the simplest form of particle size dispersity—bidispersity—and its impact on the self-assembly process. We investigate the robustness of self-assembling bcc-type crystals via isotropic interaction potentials in binary systems with increasingly disparate particle sizes by determining their terminal size ratio—the most extreme size ratio at which a mixed binary bcc crystal forms. Our findings show that two-well pair potentials produce bcc crystals that are more robust with respect to particle size ratio than one-well pair potentials. This suggests that an improved self-assembly process is accomplished with a second attractive length scale encoded in the particle–particle interaction, which stabilizes the second-nearest neighbor shell. In addition, we document qualitative differences in the process of ordering and disordering: in bidisperse systems of particles interacting via one-well potentials, we observe a breakdown of order prior to demixing, while in systems interacting via two-well potentials, demixing occurs first and bcc continues to form in parts of the droplet down to low size ratios. [ABSTRACT FROM AUTHOR]

Fe–x at% Ga (x = 17, 20, 23 and 25) were prepared by vacuum arc melting and subsequently exposed to different thermal treatments. The microstructure and magnetostrictive properties of the alloys exposed to various thermal histories have been investigated in detail. Detailed microstructural investigation indicates that at lower Ga concentration (17 and 20 at%), the ordering of A2 phase into DO3 occurs through diffusion assisted nucleation and growth transformation. On the contrary, the alloys richer in Ga exhibits ordering of A2 to DO3 through successive continuous ordering processes of A2→B2 and B2→DO3. The continuous ordering transformations being spontaneous process, the ordering could not be suppressed even by water quenching. The ordering is found to have profound influence on magnetostriction of the Fe-Ga alloy as higher magnetostriction was observed in either completely disordered A2 or completely ordered DO3. The magnetostriction is found to decrease in partially ordered material where DO3 phase co-exists with A2. [ABSTRACT FROM AUTHOR]

Many aspects of human performance require producing sequences of items in serial order. The current study takes a multiple-case approach to investigate whether the system responsible for serial order is shared across cognitive domains, focusing on working memory (WM) and word production. Serial order performance in three individuals with post-stroke language and verbal WM disorders (hereafter persons with aphasia, PWAs) were assessed using recognition and recall tasks for verbal and visuospatial WM, as well as error analyses in spoken and written production tasks to assess whether there was a tendency to produce the correct phonemes/letters in the wrong order. One PWA exhibited domain-specific serial order deficits in verbal and visuospatial WM. The PWA with verbal serial order WM deficit made more serial order errors than expected by chance in both repetition and writing-to-dictation tasks, whereas the other two PWAs showed no serial order deficits in verbal WM and production tasks. These findings suggest separable serial order systems for verbal and visuospatial WM and a shared system for serial order processing in verbal WM and word production. Implications for the domain-generality of WM, its connection to language production, and serial order processing across cognitive functionssc are discussed. [ABSTRACT FROM AUTHOR]

An accurate and efficient method for picking the first arrival of microseismic signals is crucial for processing microseismic monitoring data. However, the weak magnitude and low signal-to-noise ratio (SNR) of these signals make picking arrivals challenging. Recent advancements in deep learning-based methods for picking the first arrivals of microseismic signals have effectively addressed the inefficiencies and inaccuracies of traditional methods. Nevertheless, these methods often require many training samples, and the substantial size and labelling effort significantly hinder the development of deep learning-based first-arrival picking methods. This study introduces Semi-Picking: a semi-supervised method for picking the first arrival of microseismic signals, utilizing the TransUGA network and SimMatch. This approach automatically labels microseismic signals following sample augmentation by establishing a semi-supervised learning framework, significantly reducing the time required for sample labelling. Initially, the TransUNet model is enhanced by incorporating the Self-Supervised Predictive Convolutional Attention Block (SSPCAB) module to create a Deep-TransUNet architecture, which more effectively separates signal from noise in microseismic signals with low SNR and improves the accuracy of first-arrival picking. Subsequently, the data sets for this study are compiled from microseismic traces collected from field monitoring records. Finite-difference forward modelling is applied to the microseismic data to train the network, and hyperparameter tuning is performed to optimize the UGATIT and Deep-TransUNet architecture. The outcomes of the arrival-picking experiments, conducted under conditions of low SNR using both synthetic and real microseismic records, demonstrated that Semi-Picking offers robust resistance to incorrect labels. This resilience stems from the synergistic use of the semi-supervised learning framework and self-attention mechanisms. The proposed method demonstrates superiority over the TransUNet, the SSPCAB-TransUNet, the UNet++ and the traditional short-term average/long-term average method, respectively, with the picking error rate of the Semi-Picking Net being less than 0.1 s. The proposed method outperforms the commonly used deep learning-based approaches for picking the first arrivals of microseismic signals, exhibiting superior performance. [ABSTRACT FROM AUTHOR]

Enabled via recent technological advances coupled with the advent of new systems providers and decreased price points, automated and robotized order-picking solutions (e.g., pick-assisting autonomous mobile robots) have evolved as a surging market. Such innovative picking technologies aim to reduce labor costs, use available space more efficiently, and increase throughput rates. As implementation projects and the variety of solutions rise, managers decide which ones to select for their specific warehouse and products. However, comprehensive decision models for this strategic problem are lacking in the pertinent literature. We propose a mathematical optimization model for the novel problem that selects and sizes order-picking solutions and assigns them products and warehouse spaces. Expert interviews are used to identify the comprehensive decision-relevant costs and constraints. Specifically, we minimize setup, module, labor, and error costs while adhering to characteristics related to the area (e.g., available space), technology (e.g., throughput, handling capabilities of certain products), and product (e.g., physical dimensions). We conduct a case study and complement our findings with numerical experiments. We find significant cost reduction potential of up to 57% by selecting a mix of different order-picking solutions. Further analyses highlight the need to retain human workers and to account for maximum labor capacity. [ABSTRACT FROM AUTHOR]

Maturation of human mitochondrial tRNA is essential for cellular energy production, yet the underlying mechanisms remain only partially understood. Here, we present several cryo-EM structures of the mitochondrial RNase Z complex (ELAC2/SDR5C1/TRMT10C) bound to different maturation states of mitochondrial tRNAHis, showing the molecular basis for tRNA-substrate selection and catalysis. Our structural insights provide a molecular rationale for the 5′-to-3′ tRNA processing order in mitochondria, the 3′-CCA antideterminant effect, and the basis for sequence-independent recognition of mitochondrial tRNA substrates. Furthermore, our study links mutations in ELAC2 to clinically relevant mitochondrial diseases, offering a deeper understanding of the molecular defects contributing to these conditions. Synopsis: The human mitochondrial RNase Z complex is essential for the production of mitochondrial tRNAs. This study reveals its complete structural framework, detailing its role in tRNA maturation and substrate recognition, and provides insights into mitochondrial disease mechanisms linked to mutations in its catalytic subunit ELAC2. Cryo-EM shows the full-length human mitochondrial RNase Z complex in various maturation states of mitochondrial tRNA. The structure explains substrate recognition and catalysis, the 5′-to-3′ processing order, and the 3′-CCA antideterminant effect that prevents unnecessary RNA processing. The structural findings provide a foundation to interpret clinical mutations in the ELAC2 gene in the context of mitochondrial pathologies and reveal that substrate recognition, cleavage and 3'-CCA antidetermination depend on tightly interconnected mechanisms. Cryo-EM reveals the molecular basis for substrate recognition and the 5′-to-3′ processing order of mitochondrial tRNAs. [ABSTRACT FROM AUTHOR]

This article examines the relevance of Hegel's theory of recognition within educational theory and practice in relation to the development of a non-affirmative theory of education. The article argues that Hegel's theory of recognition can serve as a fruitful starting point for articulating an educational theory that can contribute to the subject's open-ended formation in modern society. To start with, the article surveys the connection between Hegel's educational thought and his concept of recognition. Against this backdrop, the article singles out how Hegel's theory of recognition provides a compelling theory of intersubjectivity that calls attention to the role of norms in personal development and the construction of the social world. In continuation of a non-affirmative principle, it is argued that Hegelian recognition underlines, first, that the subject's formation can fruitfully be an open-ended and dynamic process and, second, that in order to underpin this process it is necessary to critically assess norms and norm-generating practices within an educational context. [ABSTRACT FROM AUTHOR]

In order to solve the problem of narrow band coverage of traditional infrared gratings, a new type of diffraction grating is invented and named as angle-gradient echelle grating. The blaze angle of the grating gradually changes along the direction of the grating grooves, which can be regarded as etching countless sub-gratings with different blaze angles on a grating, breaking the limitation of the number of blaze angles of traditional gratings. In addition, in order to solve the processing problem of angle-gradient echelle grating, a new processing method, shaped vibration cutting (SVC) with a time-varying trajectory is developed. By exploring the influence of different processing parameters on the grating processing results, a suitable processing plan was proposed. Eventually, angle-gradient echelle grating with blaze angles varying from 30° to 55° and surface roughness of as low as 20 nm was fabricated on metallic glass, a material that is difficult to machine. • A blazed grating with a gradient blaze angle is proposed. • The proposed grating has high diffraction efficiency in the infrared band. • A variable vibration trajectory processing method is proposed. • The feasibility of the processing method is verified on an aluminum substrate. • This method can achieve high-quality structural processing on metallic glass. [ABSTRACT FROM AUTHOR]

Forecasting future observations is one of the main goals of time series modeling. Point forecasts are the most common type of prediction, but interval predictions are more informative, usually obtained as prediction intervals (PIs). The conventional Box-Jenkins PIs perform well when the underlying distributional assumptions hold. To circumvent such adherence, resampling methods such as residual based Bootstrap were one of the approaches for constructing PIs, but these are only suitable when the order of the process is known. Sieve Bootstrap method has the advantage of requiring no such prior knowledge. In this work, two new Sieve Bootstrap methods have been proposed. The performance of the proposed methods for constructing PIs have been compared with the existing Bootstrap methods. One of the proposed methods, namely, predictive residual based rescaled Sieve Bootstrap (PRSB) has been found to outperform the other proposed predictive residual based Sieve Bootstrap (PSB) and also the existing methods considered. PSB method has been found to be superior to Box-Jenkins and existing Sieve Bootstrap methods. The proposed methods are not only an improvement over the existing predictive residual based Bootstrap methods in AR(p) set up but also have been extended to be applicable in ARMA(p, q) situations as well. [ABSTRACT FROM AUTHOR]

Due to population mixing and genetic recombination, each chromosome in the genome can be regarded as a chimera of ancestral chromosomes from different genetic backgrounds. Local Ancestry Inference (LAI) is an important part of genetic analysis, which infers the ancestral origin of each chromosome segment in the genome by using genetic marker information. In order to simplify the process of LAI design, most of the existing methods use fixed-size windows and ignore the real recombination breakpoints in the individual genome to be tested. In this study, we design a strategy based on k-mers to find recombination breakpoints, and combine Hidden Markov models (HMMs) to infer local ancestry based on splitting of variable-length recombination windows in each haploid. Simulation results show that the accuracy of Wadmix is similar to that of other mainstream tools including RFMix. [ABSTRACT FROM AUTHOR]

Cryo‐electron tomography (cryo‐ET) and subtomogram averaging (STA) are becoming the preferred methodologies for investigating subcellular and macromolecular structures in native or near‐native environments. Although cryo‐ET is amenable to a wide range of biological problems, these problems often have data‐processing requirements that need to be individually optimized, precluding the notion of a one‐size‐fits‐all processing pipeline. Cryo‐ET data processing is also becoming progressively more complex due to the increasing number of packages for each processing step. Though each package has its strengths and weaknesses, independent development and different data formats make them difficult to interface with one another. TOMOMAN (TOMOgram MANager) is an extensible package for streamlining the interoperability of packages, enabling users to develop project‐specific processing workflows. TOMOMAN does this by maintaining an internal metadata format and wrapping external packages to manage and perform preprocessing, from raw tilt‐series data to reconstructed tomograms. TOMOMAN can also export these metadata between various STA packages. TOMOMAN includes tools for archiving projects to data repositories, allowing subsequent users to download TOMOMAN projects and directly resume processing. By tracking essential metadata, TOMOMAN streamlines data sharing, which improves the reproducibility of published results, reduces computational costs by minimizing reprocessing, and enables the distribution of cryo‐ET projects between multiple groups and institutions. TOMOMAN provides a way for users to test different software packages in order to develop processing workflows that meet the specific needs of their biological questions and to distribute their results to the broader scientific community. [ABSTRACT FROM AUTHOR]

The removal of inclusion particles is an important function of tundish metallurgy. During ladle change, the liquid level fluctuation around the ladle shroud is severe, which may affect the effectiveness of inclusion removal. In the present study, the fluid flow characteristics and inclusion‐removal behavior in the tundish during ladle change are investigated by numerical simulation method. And the effectiveness of flow control devices on the flow characteristics of molten steel is evaluated. It is found that the escape rate of inclusion particles during ladle change is ordered as emptying process < steady process < filling process. The proper combination of weir, dam, and turbulence inhibitor can optimize the conditions for the floating and removal of inclusion particles to the greatest extent. In the tundish with weir and dam, the escape rates of inclusion particles with sizes of 10, 50, and 100 μm throughout the entire ladle change period are respectively reduced by 9.8%, 1.6%, and 1.4%, compared to not using flow control devices. With a combination of weir, dam, and turbulence inhibitor, the escape rates of the three types of inclusion particles are reduced by 24.7%, 9.9%, and 1.2%, respectively. [ABSTRACT FROM AUTHOR]

This article studies a scheduling problem of a two-machine flowshop , considering outsourcing lead-time, where outsourcing a job incurs outsourcing cost as well as outsourcing lead-time. Each job has an option of being outsourced, i.e. the first operation of the outsourced job is handled by an external subcontractor while the second operation must be processed in-house after its delivery. The objective is to find a schedule for minimizing the weighted sum of the outsourcing costs and the total completion time. For the problem, the subset of jobs to be outsourced and the processing order of jobs are interwoven, implying that decisions have to be made simultaneously. This study examines the properties of the optimal solution and proposes various heuristics based on iterative local search and the biased random-key genetic algorithm. Extensive computational experiments are carried out in various settings. [ABSTRACT FROM AUTHOR]

The concluding chapter of Karl Marx's Capital (volume 1) has received remarkably little scholarly commentary. This is especially surprising as Marx addresses there "the modern theory of colonization" developed by Edward Gibbon Wakefield. But rather than systematically pursue the issue of colonialism, Marx investigates Wakefield's theory in order to illuminate the processes of primitive accumulation (or "originary dispossession") that gave birth to capitalism in Europe. This article suggests directions in which Marx ought to have gone in order to analyze the globalization of capitalism outside of Europe by means of colonialism. In so doing, it proposes the need to recenter bondage, slavery, colonialism, and racism as constitutive elements of capitalism as a global system. JEL Classification: B51, N3, P1 [ABSTRACT FROM AUTHOR]

Local asymptotic normality (LAN) and uniform local asymptotic normality (ULAN) conditions are obtained for a linear functional autoregressive process of order p, p≥1, using a martingale central limit theorem. As a consequence of the LAN property, asymptotically efficient tests for determining the order are constructed. An example is discussed as a special cases. [ABSTRACT FROM AUTHOR]

In this paper, we consider a class of k-order (3 ≤ k ≤ 5) backward differentiation formulas (BDF-k) for the molecular beam epitaxial (MBE) model without slope selection. Convex splitting technique along with k-th order Douglas-Dupont regularization term τ n k (− Δ) k D _ k ϕ n ( D _ k represents a truncated BDF-k formula) is added to the numerical schemes to ensure unconditional energy stability. The stabilized convex splitting BDF-k (3 ≤ k ≤ 5) methods are unique solvable unconditionally. Then the modified discrete energy dissipation laws are established by using the discrete gradient structures of BDF-k (3 ≤ k ≤ 5) formulas and processing k-th order explicit extrapolations of the concave term. In addition, based on the discrete energy technique, the L 2 norm stability and convergence of the stabilized BDF-k (3 ≤ k ≤ 5) schemes are obtained by means of the discrete orthogonal convolution kernels and the convolution type Young inequalities. Numerical results are carried out to verify our theory and illustrate the validity of the proposed schemes. [ABSTRACT FROM AUTHOR]

In this paper, tartaric acid (C4H6O6) was used as a reductant to treat chromium (VI)-containing solution. Several independent experimental parameters, including reaction temperature, concentration of H2SO4, concentration of C4H6O6 and reaction time, on the reduction process were studied. The results showed that 100% of the Cr (VI) could be reduced by C4H6O6 in a strong acidic environment under a high reaction temperature. All of the experimental parameters showed positive effects on the reduction process and followed the order [H2SO4] > [C4H6O6] > reaction temperature > reaction time. A higher concentration of tartaric acid and higher reaction temperature could facilitate the reduction process and reduce reaction time. [ABSTRACT FROM AUTHOR]

As a rapidly growing interdisciplinary literature has argued, rankings have become a key means of valuation in contemporary society. However, the majority of the work focuses on rankings in only a few areas, and even if spatial aspects play a role in the interdisciplinary literature, the number of explicitly geographical works on rankings is surprisingly low. Against this backdrop, in this paper I aim firstly to flesh out a pragmatism‐inspired geographical perspective on rankings. Secondly, using the example of wine rankings, I will ask the question as to how the growing importance of rankings has changed valuation schemes. The wine industry is particularly well suited to this, as nominal classifications in the form of designations of origin have historically played a central role here. A pragmatist, geographical perspective on ordinal ordering processes illustrates that rankings evoke both economic and geographical realities; they do this not only through the ranking processes as such, but also through observation of and engagement with rankings by different actors. In the case of wine, local/regional specificity is an inherent part of the world of rankings—be it through the fact that ranking processes build on (embodied) geographically contextualised knowledge of wine judges, through the possibilities of using (or not using) (different) rankings for different markets by wine producers, or through the balance between the marketing of wine through rankings and the suitability of those very wines for the specific markets in which they are to be sold. This is perhaps the biggest difference compared with other fields in which the importance of rankings has increased considerably—in particular, higher education. It helps to explain why the historically significant valuation scheme of geographical origin has not lost any of its significance, despite the increase in the importance of rankings in the world of wine. [ABSTRACT FROM AUTHOR]

The concept of sovereignty, like the concept of power, has been one of the key concepts that politicians, statesmen and thinkers have thought about, tried to define, conceptualize and draw the general framework since the emergence of the state. The concept of sovereignty, which has developed in connection with the change and development process of the state over time, has become a more prominent and considered concept, especially after the new nation-state-centered system that emerged after the Westphalia international system. This concept, which preoccupies thinkers, politicians and statesmen, has become questionable and debatable in the modern age, especially as world politics has changed following developments in the field of communication and processes such as Globalization. In order to overcome this process, the concept of Sovereignty has also changed, and in order to meet the conditions of the new era, a new concept emerged, called Cyber Sovereignty. [ABSTRACT FROM AUTHOR]

An unsupervised computational protocol is proposed with the aim of obtaining accurate structures of large molecules in the gas phase at the cost of standard density functional theory (DFT) computations. The whole workflow is fully automated and provides optimized equilibrium geometries and ground state rotational constants to be directly compared with experiments. The results for a panel of molecules of biological or medicinal interest show that the accuracy of the results delivered by the new tool at the cost of a single DFT geometry optimization is close to that delivered by state-of-the-art composite wavefunction methods for small semi-rigid molecules. [ABSTRACT FROM AUTHOR]

Third-party logistics (3PL) services are essential in many supply chains and aim at providing flexible and cost-effective transport and warehouse solutions. This study focuses on Warehouse Service Providers (WSPs) with shared, multi-client warehouses. We investigate how the main internal resources should be shared among clients. We focus on labor (order pickers and sorters) and pick storage space (zones) as the main internal resources in the order picking process in such a warehouse. We evaluate different possible resource-sharing configurations and develop a model to find the configuration that can satisfy set service-level agreements at minimum cost. The cost consists of labor and space cost, whereas the service-level requirements are based on the mean and tail of the order-throughput-time distribution. The results show that whether to share the resources or not highly depends on the clients' characteristics, such as the order demand rate. Generally, for low-demand clients, sharing all the resources is optimal, whereas for high-demand clients, dedicating all resources is preferred. In addition, the decision to share resources depends on the warehouse's characteristics, similarities between clients' product and order picking characteristics. The findings of this article provide valuable insights for WSPs to minimize cost, while meeting the service-level requirements of clients by optimally selecting the warehouse configuration. This may, in turn, benefit their clients by offering better pricing policies to them, which can also be a compelling selling point, ultimately contributing to business growth and attracting more clients. [ABSTRACT FROM AUTHOR]

Missing observations and unevenly spaced data are problems common to different disciplines in the context of time series analysis. This paper introduces a new approach to deal with both issues, by considering an irregularly spaced autoregressive moving average process of order (1,1) that is stationary (and therefore homoscedastic) and invertible allowing temporal variations in its coefficients. We test our model in the analysis of greenhouse time series by comparing it with a standard benchmark in the literature. As a result, our methodology leads to a huge advantage in the computational time with respect to the competitor. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) materials and their heterostructures have been widely explored for high-performance energy conversion applications. The Thomson effect—a higher order transport process—plays an important role in thermoelectric devices, yet its effect on the performance of thermionic devices remains unknown thus far. Here, we investigate the performance of thermionic refrigeration in vertically stacked heterostructure (VHS) and laterally stitched heterointerface (LHS) composed of a graphene and a 2D semiconductor (i.e., MoS 2 and WSe 2) in the presence of the Thomson effect. Using a temperature-dependent Seebeck coefficient, we derived the analytical expressions of the cooling efficiency and the effective Z T. We shall show that the Thomson effect improves the coefficient of performance (COP) by up to 20%, particularly, in the case where the temperature difference between the cold and the hot electrodes is large. However, the Carnot efficiency decreases with the temperature difference. The overall COP is reduced by the Thomson effect. We calculate the COP in graphene/MoS 2 /graphene and graphene/WSe 2 /graphene VHS and LHS devices. We show that the LHS composed of WSe 2 significantly outperforms the VHS and MoS 2 counterpart. These findings provide an understanding of thermionic processes in the higher-order transport regime and shall offer insights into the design of novel 2D material heterostructure thermionic energy converters. [ABSTRACT FROM AUTHOR]

This note presents insights on the Jordan structure of a matrix which are derived from an extension of the I(1) and I(2) conditions in Johansen (1996). It is first observed that these conditions not only characterize, as it is well known, the size (1 or 2) of the largest Jordan block in the Jordan form of the companion matrix but more generally the geometric multiplicities, the algebraic multiplicities and the whole Jordan structure for eigenvalues of index 1 or 2. In the context of the Granger representation theorem, this means that the Johansen rank conditions do more than determine the order of integration of the process. It is then shown that an extension of these conditions leads to the characterization of the Jordan structure of any matrix. [ABSTRACT FROM AUTHOR]

Positional reasoning is the process of ordering an unsorted set of parts into a consistent structure. To address this problem, we present Positional Diffusion , a plug-and-play graph formulation with Diffusion Probabilistic Models. Using a diffusion process, we add Gaussian noise to the set elements' position and map them to a random position in a continuous space. Positional Diffusion learns to reverse the noising process and recover the original positions through an Attention-based Graph Neural Network. To evaluate our method, we conduct extensive experiments on three different tasks and seven datasets, comparing our approach against the state-of-the-art methods for visual puzzle-solving, sentence ordering, and room arrangement, demonstrating that our method outperforms long-lasting research on puzzle solving with up to + 17 % compared to the second-best deep learning method, and performs on par against the state-of-the-art methods on sentence ordering and room rearrangement. Our work highlights the suitability of diffusion models for ordering problems and proposes a novel formulation and method for solving various ordering tasks. We release our code at https://github.com/IIT-PAVIS/Positional_Diffusion. • The article presents a novel method for Ordering Elements of a Set in 1D and 2D space. • We propose a task-agnostic method, Positional Diffusion for different ordering tasks • Our approach combines Graph Neural Networks with Diffusion Probabilistic Models. • Without any task-specific modes, our method can outperform task-specific approaches. • We test our approach on Sentence ordering, Visual Puzzles, and Furniture Arrangement. [ABSTRACT FROM AUTHOR]

The smart mobile Internet of Things (IoT) is a novel paradigm that is rapidly gaining ground in the field of modern wireless telecommunications. Picking operations are the key link in an entire warehousing operation, and congestion problems significantly contribute to managers' decisions regarding the warehousing layout, the storage strategy, and the number of pickers. In this paper, the discrete Markov method is used to study the problem of picking congestion in a narrow-aisle double picking system with a traditional layout, an S-type picking path and a classified storage strategy. First, congestion models are constructed when the picker picks one item with a picking speed that is equal to the walking speed and when the picker picks multiple items on one picking surface under a picking speed that is very different from the walking speed. A sensitivity analysis involving parameter changes was carried out. Second, the paper compares and analyzes situations in which the picking speed is equal to the walking speed and in which there is a large difference between the picking speed and the walking speed and determines the impact of the picking speed, the number of goods picked on a picking surface, the differentiated classified storage strategy, and the number of picking surfaces on the picking congestion rate. The effectiveness of the mathematical model was verified by a MATLAB simulation, and the exploration and discovery for subsequent research were performed. [ABSTRACT FROM AUTHOR]

This paper deals with some probabilistic and statistical properties of periodic generalized Poisson integer-valued autoregressive processes of order p, PG P INAR (p). Necessary and sufficient conditions for the periodic stationarity, both in mean and second order, are established. The closed-forms of the mean and the second moment are, under these conditions, obtained. Moreover, the Wold–Cramér expression of the underlying second-order periodically stationary process is then established. The autocovariance structure is studied, while providing the closed-form of the periodic autocorrelation function. The Yule–Walker (YW), the two-stage conditional least squares (CLS) and the conditional maximum likelihood (CML) estimation methods of the underlying parameters are obtained. An intensive simulation study and an application on a real count data consisting of the daily number of daytime road accidents in Schiphol area, in Netherlands are provided. [ABSTRACT FROM AUTHOR]

New families of composition methods with processing of order 4 and 6 are presented and analyzed. They are specifically designed to be used for the numerical integration of differential equations whose vector field is separated into three or more parts which are explicitly solvable. The new schemes are shown to be more efficient than previous state-of-the-art splitting methods. [ABSTRACT FROM AUTHOR]

Monomial ordering is the process of putting single polynomial terms, or monomials, in a certain order depending on predefined principles. It facilitates the systematic grouping and comparison of monomials, as well as the division and factorization of polynomials and other algebraic operations. Let R := 핂[xi,j|i ∈ [c],j ∈ ℕ], be a polynomial ring over arbitrary field 핂, where c is any fixed natural number. In this paper, we have defined different orderings like lexicographical, degree lexicographical and reverse degree lexicographical ordering on polynomial ring. We have discussed the infinitely many Inc-compatible term ordering on polynomial ring R with respect to two different weight vectors Wc and Wc,n′. [ABSTRACT FROM AUTHOR]

Compounds from the homologous series of (E)-4-[(4-heptyloxyphenyl)diazenyl]phenyl alkanoates (7OABOOCm) for m = 1–19, were synthesised. The phase behaviour was investigated by differential scanning calorimetry, polarised light (optical) microscopy, and thermo-optical analysis. The enantiotropic nematic, smectic C and crystal G phases were found for derivatives with m = 1–18, m = 7–17, and m = 4, respectively. In addition, during cooling, smectic F, crystal G, and unknown X phases were observed for derivatives with m = 7–9, m = 3,8,9, and m = 4, respectively. The X-ray diffraction results suggest that the X phase is presumably monotropic crystal H or a second crystal phase. The E–Z photoisomerisation process was observed during UV light irradiation. A photostationary state was reached after exposure time equal to approximately 80 s. The derived kinetic constant k of this process was of the order of 10−2 s−1. [ABSTRACT FROM AUTHOR]

Considering the increasing competition among manufacturers and the diversification of customer orders, it is important to use the optimal production system. Hybrid manufacturing systems have proven to be a viable solution to achieve a satisfactory level of customization while maintaining adequate production volumes. This article determines the optimal strategy for decision makers in order to choose the appropriate method of supplying customers’ orders. In this article, a hybrid MTS-MTO production system has been studied in two different scenarios. For this purpose, a mixed-integer linear bi-objective model with product substitution and replaceable materials has been developed and solved by a Lagrangian Relaxation algorithm. The findings of this study reveal that enabling product substitution by manufacturers leads to an increase in the number of accepted orders, along with resulting in a higher average level of customer dissatisfaction. The system prioritizes the fulfillment of orders from permissive customers. Also, with the increase of uncertainty in each of the supplying methods, manufacturers are using other sources to supply raw materials to satisfy the accepted orders. [ABSTRACT FROM AUTHOR]

This article reflects on the medicalization of psychic suffering in order to understand that process as part of a capitalist accumulation strategy. To do this, the first idea is that capitalism is in a phase of an initial residual accumulation terminal (Veraza, 2011) in which, psychic suffering is one of the aspects to expropriate and exploit. Second, the economic policies implemented in Argentina are described; in the following sections, it is particularized in the Alto Rio Negro valley and in the expropriation of livelihoods. In the last section, we present the inter-capitalist dispute within the health sector and medicalization as a means of repositioning the industrial fraction in that dispute from three dimensions, the abstract universalization of diagnostic categories in health Mental; The regulatory changes and the offensive against work. [ABSTRACT FROM AUTHOR]

To reduce the security authentication time cost, forwarding delay, and enhance message security of Beidou communication short messages, this paper proposes a Beidou communication short message encryption technology based on SM9 (Mobile Code Secure Communication). This technology uses split hierarchical clustering algorithm to cluster the short message data of Beidou Communication, in order to unify the processing of similar short message data and improve the encryption efficiency of subsequent short messages. Based on the data clustering results, this paper constructs a short message forwarding verification model using the SM9 identification password algorithm, and provides the message content of the communication application protocol and the communication receiving information protocol to achieve low‐cost and efficient forwarding verification. In addition, this article improves the initial value selection of Logistic chaotic mapping by coupling the tent map with coupled mapping lattice (CML) in the spatiotemporal chaos model to generate a chaotic initial value sequence, thereby expanding the key space, enhancing the ability to resist exhaustive attacks, enhancing the randomness of the generated key parameters, and optimizing the encryption effect of short messages. The experimental results show that the short message security authentication time of the technology proposed in this article is basically controlled within 25 ms, and the minimum forwarding delay is only 23.9 ms, which can effectively resist attacks and improve the security of Beidou communication. [ABSTRACT FROM AUTHOR]

Denial of Service (DoS) attacks remain a persistent threat to online systems, necessitating continual innovation in defense mechanisms. In this work, we present an improved algorithm for mitigating DoS attacks through the augmentation of client puzzle protocols. Building upon the foundation of hashcash trees, a recently proposed data structure combining hashcash and Merkle trees, we introduce a new version of the data structure that enhances resistance against parallel computation (a common tactic employed by attackers). By incorporating the labels of children and the next node in a breadth-first traversal into the hash function, we establish a sequential processing order that inhibits parallel node evaluation. The added dependency on the next node significantly elevates the complexity of constructing hashcash trees, introducing a linear number of synchronization points and fortifying resilience against potential attacks. Empirical evaluation demonstrates the efficacy of our approach, showcasing its ability to accurately control puzzle difficulty while bolstering system security against DoS threats. [ABSTRACT FROM AUTHOR]

Rapid changes in technological developments and their impact on daily life are changing the way of doing business, the communication process and the working order. This impact process creates innovations in parallel with technology in every sector. One of these innovations is undoubtedly blockchain technology. Emerging in 2008 with the introduction of Bitcoin, it is now an accepted fact that blockchain is a large-scale technology that has made a name for itself with its high returns in recent years and has become widespread with the effect of crypto assets. The innovation and transformation brought by blockchain technology affect audit and consultancy activities as it affects different professions. When the advantages brought by this technology are evaluated, it is expected that different opportunities will arise in the audit profession, providing transparency, efficiency and time savings in the audit process. In this study, the basic structure of blockchain technology is examined and the advantages and risks that may arise from the technology are evaluated. It is tried to explain how the audit process is affected by new developments and the possible change process of audit from a broader perspective. [ABSTRACT FROM AUTHOR]

In the eighteenth century, the sciences and their applications adopted a new attitude based on quantification and, increasingly, on a notion of precision. Within this process, instruments played a significant role. However, while new devices such as the micrometer, telescope, and pendulum clock embodied a formerly unknown potential of precision, this could only be realized by defining a set of practices regulating their application and control. The paper picks up the case of pendulum clocks used in eighteenth-century observatories in order to show the process of learning in the course of which the pendulum clock first became a precision instrument. By examining the results of an especially developed statistical analysis, conducted to compare the performance of eighteenth-century clocks, it highlights the diversity of conditions, attitudes, and manners of handling that are characteristic for the epoch. In this way, it underlines the necessity of standardization of timekeeping practices rather than exclusively focusing on the technological development of clocks. Ultimately, the paper discusses the role of makers and users in order to show the evolution of a "precision instrument." [ABSTRACT FROM AUTHOR]

The just-in-time concept, mass customization, omnichannel distribution, and the rising global population have all fueled the logistics sector. Consequently, using automation inside the warehouses to make them more dynamic and sustainable for the future is one of the crucial components to adapt to this quick shift. Giants in the industry and technology are becoming more interested in the "smart warehouse" system, built with innovative warehousing technologies, as an achievable solution for the development of warehouses in the future. To contextualize the past and provide light on prospective future directions, a study of current articles in the literature is important. This study evaluates works published in the previous 32 years related to flexible automation in warehouses to create a framework that future academics might use to guide them in establishing an original conceptual model that might be implemented at warehouses. One hundred eleven selected, examined, and categorized publications were published between 1990 and 2022 to establish a significant foundation for earlier research. Results indicated that combining automated machinery, collecting data technologies, and management systems are essential to creating a flexible automated warehouse. Finally, based on the examined literature, a flexible automated warehouse framework is suggested to direct future research in this field. [ABSTRACT FROM AUTHOR]

It is known that artificial intelligence algorithms are based on calculations performed using various mathematical operations. In order for these calculation processes to be carried out correctly, some types of data cannot be fed directly into the algorithms. In other words, numerical data should be input to these algorithms, but not all data in datasets collected for artificial intelligence algorithms are always numerical. These data may not be quantitative but may be important for the study under consideration. That is, these data cannot be thrown away. In such a case, it is necessary to transfer categorical data to numeric type. In this research work, 14 encoding methods of transforming of categorical data were considered. At the same time, conclusions are given about the general conditions of using these methods. During the research, categorical data in the dataset that were collected in order to assess whether it is possible to give credit to customers will be transformed based on 14 methods. After applying each encoding method, experimental tests are conducted based on the classification algorithm, and they are evaluated. At the end of the study, the results of the experimental tests are discussed and research conclusions are presented. [ABSTRACT FROM AUTHOR]

This study describes our thorough experience of formal modeling and exhaustive verification of concurrent systems, particularly mutual exclusion algorithms. The experience focuses on Lycklama and Hadzilacos's (LH) mutual exclusion algorithm. LH rests on the reduced size of the shared state, contains a mechanism that tries to enforce an FCFS order to processes entering their critical section, and embodies Burns and Lamport's (BL) mutual exclusion algorithm. The modeling methodology is based on timed automata and the model checker of the popular Uppaal toolbox. The effectiveness of the modeling and analysis approach is first demonstrated by studying the BL's solution and retrieving all its properties, including, in general, its unbounded overtaking, which is the non-limited number of by-passes a process can suffer before accessing its critical section. Then, the LH algorithm is investigated in depth by showing it fulfills all the mutual exclusion properties when it operates with atomic memory. However, as this study demonstrates, LH is not free of deadlocks when used with non-atomic memory. Finally, a state-of-the-art mutual exclusion solution is proposed, which relies on a stripped-down LH version for processes, which is used as the arbitration unit in a tournament tree (TT) organization. This study documents that LH's TT-based algorithm satisfies all the mutual exclusion properties, with a linear overtaking, both using atomic and non-atomic memory. [ABSTRACT FROM AUTHOR]

Emerging research on the etiology of violent radical political behavior has begun to explore the role of empathy in shaping an individual's beliefs, attitudes, and intentions that culminate in radicalization. The existing studies focus on persuasive influence upon an individual, but they overlook the centrality of empathy and that in the absence of empathy, persuasion is not salient. If an individual empathizes with a message then when it is processed by the receiver, the message is more likely to be considered realistic, relatable, believable, and therefore, persuasive. However, very little is known as to how messages should be designed to stimulate empathy in order to optimize their persuasive impact, which is particularly relevant to terrorist and extremist messaging given the lethal outcome of successful persuasion. This study examines the neurocognitive process of radicalization, specifically as it occurs within virtual online space, and how message content and production features have the potential to arouse empathy and generate radical-persuasive outcomes among the target audience. The findings of this research demonstrate how emotions, specifically that of empathy, can be stimulated in order to facilitate the process of radicalization, thus increasing the potential for violent radical political behavior. [ABSTRACT FROM AUTHOR]

Summary: Cognitive Radio Ad Hoc Networks (CRAHNs) are an essential method for resolving conflicts between extreme spectrum scarcity and rapid traffic increase while maintaining high‐quality service for consumers. However, the coexistence of primary and secondary users represents a critical challenge for reasonable resource allocation in order to provide a sustaining system performance. Many approaches have been developed to efficiently allocate resources; however, these methods are currently limited by things like user collision, strange traffic networks, and high data transmission error rates. To address these constraints, this paper proposes a policy‐configured reinforcement learning‐based ad hoc network (AHN) model. To obtain the ideal policy configuration for the network, the system first models the cognitive radio (CR) network, in which nodes are initialised and grouped employing the Link Reliability K‐Means clustering Algorithm (LR‐KMA). The available spectrum was then detected and separated into multiple bands utilizing coherent‐based detection (CBD) and signal source identification employing the Parzen–Rosenblatt Window‐based Restricted Boltzmann Machine (PRW‐RBM). Next, the learning model for the resource allocation process employs the Weibull Distribution‐based Blue Monkey Optimization (WD‐BMO) approach to pick the relevant bands. Finally, the experimental results were analyzed in order to evaluate the proposed resource allocation model's performance in CRAHNs. When compared with previous findings, the proposed method improves resource utilization by 5%, the proposed model achieves a 7% higher throughput, and the PRW‐RBM's accuracy improves classification accuracy by 1.07%. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the impact of music training on the processing of temporal order in Mandarin sentence reading using event-related potentials (ERPs). Two-clause sentences with temporal connectives ("before" or "after") were presented to both musicians and non-musicians. Additionally, a verbal N-back task was utilized to evaluate the participants' working memory capacities. The findings revealed that musicians, but not nonmusicians, demonstrated a more negative amplitude in the second clauses of "before" sentences compared with "after" sentences. In the N-back task, musicians exhibited faster reaction times than nonmusicians in the two-back condition. Furthermore, a correlation was observed between the ERP amplitude differences (before vs. after) and reaction time differences in the N-back task (0-back vs. 2-back) among musicians. These findings suggested that music training enhances the depth of temporal order processing, potentially mediated by improvements in working memory capacity. [ABSTRACT FROM AUTHOR]

The four-dimensional ellipsoid of an anisotropic hyper-structure corresponds to the four-dimensional sphere of an isotropic hyper-structure. In three dimensions, both theories for spherical and ellipsoidal harmonics have been developed by Laplace and Lamé, respectively. Nevertheless, in four dimensions, only the theory of hyper-spherical harmonics is hitherto known. This void in the literature is expected to be filled up by the present work. In fact, it is well known that the spectral decomposition of the Laplace equation in three-dimensional ellipsoidal geometry leads to the Lamé equation. This Lamé equation governs each one of the spectral functions corresponding to the three ellipsoidal coordinates, which, however, live in non-overlapping intervals. The analysis of the Lamé equation leads to four classes of Lamé functions, giving a total of 2n + 1 functions of degree n. In four dimensions, a much more elaborate procedure leads to similar results for the hyper-ellipsoidal structure. Actually, we demonstrate here that there are eight classes of the spectral hyper-Lamé equation and we provide a complete analysis for each one of them. The number of hyper-Lamé functions of degree n is (n + 1)2; that is, n2 more functions than the three-dimensional case. However, the main difficulty in the four-dimensional analysis concerns the evaluation of the three separation constants appearing during the separation process. One of them can be extracted from the corresponding theory of the hyper-sphero-conal system, but the other two constants are obtained via a much more complicated procedure than the three-dimensional case. In fact, the solution process exhibits specific nonlinearities of polynomial type, itemized for every class and every degree. An example of this procedure is demonstrated in detail in order to make the process clear. Finally, the hyper-ellipsoidal harmonics are given as the product of four identical hyper-Lamé functions, each one defined in its own domain, which are explicitly calculated and tabulated for every degree less than five. [ABSTRACT FROM AUTHOR]

Predictive coding accounts of perception state that the brain generates perceptual predictions in the service of processing incoming sensory data. These predictions are hypothesized to be afforded by the brain's ability to internalize useful patterns, that is, statistical regularities, from the environment. We have previously argued that the N300 ERP component serves as an index of the brain's use of representations of (real-world) statistical regularities. However, we do not yet know whether overt attention is necessary in order for this process to engage. We addressed this question by presenting stimuli of either high or low real-world statistical regularity in terms of their representativeness (good/bad exemplars of natural scene categories) to participants who either fully attended the stimuli or were distracted by another task (attended/distracted conditions). Replicating past work, N300 responses were larger to bad than to good scene exemplars, and furthermore, we demonstrate minimal impacts of distraction on N300 effects. Thus, it seems that overtly focused attention is not required to maintain the brain's sensitivity to real-world statistical regularity. Furthermore, in an exploratory analysis, we showed that providing additional, artificial regularities, formed by altering the proportions of good and bad exemplars within blocks, further enhanced the N300 effect in both attended and distracted conditions, shedding light on the relationship between statistical regularities learned in the real world and those learned within the context of an experiment. [ABSTRACT FROM AUTHOR]

Robotic Mobile Fulfillment Systems (RMFSs) face challenges in handling large-scale orders and navigating complex environments, frequently encountering a series of intricate decision-making problems, such as order allocation, shelf selection, and robot scheduling. To address these challenges, this paper integrates Deep Reinforcement Learning (DRL) technology into an RMFS, to meet the needs of efficient order processing and system stability. This study focuses on three key stages of RMFSs: order allocation and sorting, shelf selection, and coordinated robot scheduling. For each stage, mathematical models are established and the corresponding solutions are proposed. Unlike traditional methods, DRL technology is introduced to solve these problems, utilizing a Genetic Algorithm and Ant Colony Optimization to handle decision making related to large-scale orders. Through simulation experiments, performance indicators—such as shelf access frequency and the total processing time of the RMFS—are evaluated. The experimental results demonstrate that, compared to traditional methods, our algorithms excel in handling large-scale orders, showcasing exceptional superiority, capable of completing approximately 110 tasks within an hour. Future research should focus on integrated decision-making modeling for each stage of RMFSs and designing efficient heuristic algorithms for large-scale problems, to further enhance system performance and efficiency. [ABSTRACT FROM AUTHOR]