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This paper studies a novel robotic warehousing system called the overhead robotic compact storage and retrieval system, which can free up the floor space occupation at a low cost. Bins, as basic storage containers, are stacked on top of each other to form a bin stack. Along overhead tracks, bin-picking robots transport bins between storage/retrieval positions and workstations with the aid of track-changing robots. Little research has been done to study operational policies and performance analysis for this new robotic compact warehousing system. We propose a nested queuing network model that considers two transportation resources and performs reinforcement learning using real data to improve the reshuffling efficiency. We find that reinforcement learning based reshuffling policy greatly reduces the reshuffling distance and saves computation time compared to existing policies. We find that the storage policy of stacks affects the optimal width/length ratio regardless of the system height. Interestingly, we obtain the number of robots that can stabilise the system to avoid an explosion of the order queue; two more robots than that number will produce relatively low throughput times. Compared to an AutoStore system, using our system reduces cost by 30% with a slight increase in throughput time. [ABSTRACT FROM AUTHOR]

Motivated by a transit line planning problem in transportation systems, we investigate the following capacitated assignment problem under a budget constraint. Our model involves L bins and P items. Each bin l has a utilization cost c l and an n l -dimensional capacity vector. Each item p has an n l -dimensional binary weight vector r l p , where the 1s in r l p (if any) appear in consecutive positions, and its assignment to bin l yields a reward v l p. The objective is to maximize total rewards through an assignment that satisfies three constraints: (i) the total weights of assigned items do not violate any bin's capacity; (ii) each item is assigned to at most one open bin; and (iii) the overall utilization costs remain within a total budget B. We propose the first randomized rounding algorithm with a constant approximation ratio for this problem. We then apply our framework to the motivating transit line planning problem, presenting corresponding models and conducting numerical experiments using real-world data. Our results demonstrate significant improvements over previous approaches in addressing this critical transportation challenge. [ABSTRACT FROM AUTHOR]

The "Author Index to Volume 42, 2024" from the Chinese Journal of Chemistry provides a comprehensive list of authors and their corresponding page numbers in the journal. This index showcases a diverse range of authors with different backgrounds and research interests, highlighting the journal's commitment to inclusivity and varied perspectives. Researchers seeking specific authors or topics covered in Volume 42 can utilize this index as a valuable reference tool, featuring names like Qian Xue‐Wei, Zhang Bo‐Chao, and Zhou Yang, among others, each making distinct contributions to the field. [Extracted from the article]

This study focuses on the opening width of parallel grippers in bin picking and proposes a method to optimize this width based on the evaluation of graspability in distance images. The method relies on fast graspability evaluation (FGE), which reduces the robot's grasp position calculation to a convolution problem between binary images representing the object and hand. This approach determines the hand parameters that yield the highest graspability score for the entire bin-picking scene. When introduced in multi-bin-picking tasks involving eight types of industrial parts, this optimization method demonstrated improvements in grasp success rates of up to 35% and an average improvement of approximately 14.4%. The proposed method confirms the importance of optimizing hand parameters in challenging industrial bin-picking scenarios. [ABSTRACT FROM AUTHOR]

The identification of key nodes in complex networks is an important topic in many network science areas. It is vital to a variety of real-world applications, including viral marketing, epidemic spreading and influence maximization. In recent years, machine learning algorithms have proven to outperform the conventional, centrality-based methods in accuracy and consistency, but this approach still requires further refinement. What information about the influencers can be extracted from the network? How can we precisely obtain the labels required for training? Can these models generalize well? In this paper, we answer these questions by presenting an enhanced machine learning-based framework for the influence spread problem. We focus on identifying key nodes for the Independent Cascade model, which is a popular reference method. Our main contribution is an improved process of obtaining the labels required for training by introducing "Smart Bins" and proving their advantage over known methods. Next, we show that our methodology allows ML models to not only predict the influence of a given node, but to also determine other characteristics of the spreading process—which is another novelty to the relevant literature. Finally, we extensively test our framework and its ability to generalize beyond complex networks of different types and sizes, gaining important insight into the properties of these methods. [ABSTRACT FROM AUTHOR]

This research aims to collect some of the narrations of Mujahid bin Jabr Al-Makki from Aisha, may God be pleased with her, and consider them in terms of connection and interruption, using the inductive and analytical approach by collecting some of his narrations about her, which I refer to the explanation of the transmission, and then I analyze them in terms of explain and study of the chains of evidence, with a focus on the statement of their condition in terms of connection and interruption, by mentioning the statements of the critical Imams and then concluding the final results reached by the researcher . [ABSTRACT FROM AUTHOR]

This study examines the role of Sheikh Abd al-Latif bin Abd al-Rahman Al al-Sheikh in the political life during the second Saudi state, and tries to investigate his various positions towards the values of the events that this state went through, especially during the era of Imam Faisal bin Turki in his second period, and then a period of time. His sons, Imams Abdullah and Saud. Faisal, or even the authority of his sons after him. [ABSTRACT FROM AUTHOR]

The signal of dipole anisotropy in quasar number counts is studied using the CatWISE2020 catalogue in various colour bins. It is found that the dipole signal differs significantly in two colour bins, namely |$W1-W2\lt 1.1$| and |$W1-W2\gt 1.1$|⁠. While the dipole in the bin |$W1-W2\lt 1.1$| points close to the direction of the cosmic microwave background dipole, the dipole in the bin |$W1-W2\gt 1.1$| points in the direction |$(l,b) = (194^\circ \pm 7^\circ ,19^\circ \pm 4^\circ)$|⁠ , quite close to the Galactic plane. Despite the proximity to the Galactic plane, we are unable to attribute this signal to a Galactic bias. If we interpret the dipole in the bin |$W1-W2\lt 1.1$| as due to our local motion, the extracted velocity turns out to be |$900\pm 113$| km s |$^{-1}$|⁠ , which deviates from the cosmic microwave background dipole velocity with approximately 4.7σ significance. We speculate that the dipole signal in both bins is of cosmological origin and that the difference may be attributed to a redshift dependence of the dipole, representing a departure from the standard |$\Lambda$| CDM model. [ABSTRACT FROM AUTHOR]

An outlier probability is the probability that an observation is an outlier. Typically, outlier detection algorithms calculate real-valued outlier scores to identify outliers. Converting outlier scores into outlier probabilities increases the interpretability of outlier scores for domain experts and makes outlier scores from different outlier detection algorithms comparable. Although several transformations to convert outlier scores to outlier probabilities have been proposed in the literature, there is no common understanding of good outlier probabilities and no standard approach to evaluate outlier probabilities. We require that good outlier probabilities be sharp, refined, and calibrated. To evaluate these properties, we adapt and propose novel measures that use ground-truth labels indicating which observation is an outlier or an inlier. The refinement and calibration measures partition the outlier probabilities into bins or use kernel smoothing. Compared to the evaluation of probability in supervised learning, several aspects are relevant when evaluating outlier probabilities, mainly due to the imbalanced and often unsupervised nature of outlier detection. First, stratified and weighted measures are necessary to evaluate the probabilities of outliers well. Second, the joint use of the sharpness, refinement, and calibration errors makes it possible to independently measure the corresponding characteristics of outlier probabilities. Third, equiareal bins, where the product of observations per bin times bin length is constant, balance the number of observations per bin and bin length, allowing accurate evaluation of different outlier probability ranges. Finally, we show that good outlier probabilities, according to the proposed measures, improve the performance of the follow-up task of converting outlier probabilities into labels for outliers and inliers. [ABSTRACT FROM AUTHOR]

Understanding the expansion rate history is a primary goal in cosmology. There are various ways to measure the expansion rate at different redshifts and measuring it through the luminosity distance of SNIa is widely used in cosmology. In this work, we split the latest dataset of SNIa (the Pantheon+ sample) into several redshift bins and compute the expansion rate through a non-parametric technique. To do this, we use the Gaussian process to obtain the expansion rate considering data in different redshift bins. For the sake of comparison, we also consider the Λ CDM model and find the expansion history through an MCMC analysis. Our results indicate that the degeneracy between free parameters prevents a good constraint using the low redshifts data but this is not the case in the GP scenario. Moreover, we study how high redshift SNIa can affect the current expansion rate and observe that data at z > 0. 5 has almost no impact on the current expansion rate in both approaches. [ABSTRACT FROM AUTHOR]

Higher-order relationships are a central concept in the science of complex systems. A popular method of attempting to estimate the higher-order relationships of synergy and redundancy from data is through the O-information. It is an information–theoretic measure composed of Shannon entropy terms that quantifies the balance between redundancy and synergy in a system. However, bias is not yet taken into account in the estimation of the O-information of discrete variables. In this paper, we explain where this bias comes from and explore it for fully synergistic, fully redundant, and fully independent simulated systems of n = 3 variables. Specifically, we explore how the sample size and number of bins affect the bias in the O-information estimation. The main finding is that the O-information of independent systems is severely biased towards synergy if the sample size is smaller than the number of jointly possible observations. This could mean that triplets identified as highly synergistic may in fact be close to independent. A bias approximation based on the Miller–Maddow method is derived for the O-information. We find that for systems of n = 3 variables the bias approximation can partially correct for the bias. However, simulations of fully independent systems are still required as null models to provide a benchmark of the bias of the O-information. [ABSTRACT FROM AUTHOR]

Gene-based burden tests are a popular and powerful approach for analysis of exome-wide association studies. These approaches combine sets of variants within a gene into a single burden score that is then tested for association. Typically, a range of burden scores are calculated and tested across a range of annotation classes and frequency bins. Correlation between these tests can complicate the multiple testing correction and hamper interpretation of the results. We introduce a method called the sparse burden association test (SBAT) that tests the joint set of burden scores under the assumption that causal burden scores act in the same effect direction. The method simultaneously assesses the significance of the model fit and selects the set of burden scores that best explain the association at the same time. Using simulated data, we show that the method is well calibrated and highlight scenarios where the test outperforms existing gene-based tests. We apply the method to 73 quantitative traits from the UK Biobank, showing that SBAT is a valuable additional gene-based test when combined with other existing approaches. This test is implemented in the REGENIE software. Gene-based burden tests are commonly used in exome-wide association studies. We introduce SBAT (sparse burden association test), which jointly models a set of burden scores under the assumption that the causal burden scores act in the same effect direction. We apply SBAT to 73 quantitative traits in the UK Biobank. [ABSTRACT FROM AUTHOR]

In the balanced allocations framework, there are \(m\) jobs (balls) to be allocated to \(n\) servers (bins). The goal is to minimize the gap, the difference between the maximum and the average load. In 2015, Peres, Talwar and Wieder used the hyperbolic cosine potential function to analyze the challenging case where \(m\gg n\) , for a large family of processes, including the \((1+\beta)\) -process and graphical balanced allocations. The key ingredient was to prove that the potential drops in every step, i.e., a drift inequality. In this work, we improve the drift inequality so that (i) it is asymptotically tight (leading to tighter gap bounds), (ii) it assumes weaker preconditions (thereby resolving an open problem regarding weighted graphical allocations), (iii) it applies not only to processes allocating to more than one bin in a single step but also (iv) to processes allocating a varying number of balls depending on the sampled bin. Our applications include the aforementioned large family of processes, and also several new processes and settings, including outdated information and memory. We hope that our techniques can be used to analyze further interesting settings and processes. [ABSTRACT FROM AUTHOR]

Order batching facilitates order picking by merging orders into single vehicle trips. Filling orders with a total volume larger than a vehicle's bin capacity, however, requires binning into multiple suborders, a procedure that influences batching performance by altering both the number of suborders and the routes for each suborder. This paper introduces the binning and batching problem (BBP) in an order picking system with pick support vehicles. To minimize the weighted sum of the number of bins and the total travel distance, we propose a binning and batching model (BBM) based on a mixed-integer programming (MIP) and an MIP-based heuristic for large-scale BBPs. Our heuristic obtains near-optimal solutions by the tight lower bound in the problems. A comparison of the heuristic and lower bound shows optimal gaps between 1.38 and 9.21% in a parallel-aisle system for 250–1000 orders. We demonstrate that the heuristic achieves the shortest travel distance for a large number of orders when the number of bins varies within a reasonable range. [ABSTRACT FROM AUTHOR]

Template matching is a common approach in bin-picking tasks. However, it often struggles in complex environments, such as those with different object poses, various background appearances, and varying lighting conditions, due to the limited feature representation of a single template. Additionally, during the bin-picking process, the template needs to be frequently updated to maintain detection performance, and finding an adaptive template from a vast dataset poses another challenge. To address these challenges, we propose a novel template searching method in a latent space trained by a Variational Auto-Encoder (VAE), which generates an adaptive template dynamically based on the current environment. The proposed method was evaluated experimentally under various conditions, and in all scenarios, it successfully completed the tasks, demonstrating its effectiveness and robustness for bin-picking applications. Furthermore, we integrated our proposed method with YOLO, and the experimental results indicate that our method effectively improves YOLO's detection performance. [ABSTRACT FROM AUTHOR]

Recent studies employing the spatial interference paradigm reveal qualitative differences in congruency effects between gaze and arrow targets. Typically, arrows produce a standard congruency effect (SCE), with faster responses when target direction aligns with its location. Conversely, gaze targets often lead to a reversed congruency effect (RCE), where responses are slower in similar conditions. We explored this dissociation using the Conditional Accuracy Function (CAF) to assess accuracy across reaction time bins. Using a hierarchical linear mixed modelling approach to compare cropped eyes, and full faces as social stimuli, and arrows as non‐social stimuli, we synthesized findings from 11 studies, which led to three distinct models. The results showed that with non‐social targets, incongruent trials exhibited lower accuracy rates in the first bin than in subsequent bins, while congruent trials maintained stable accuracy throughout the distribution. Conversely, social targets revealed a dissociation within the fastest responses; alongside a general reduction in accuracy for both congruency conditions, congruent trials resulted in even lower accuracy rates than incongruent ones. These results suggest with gaze targets that additional information, perhaps social, in addition to the automatic capture by the irrelevant target location, is being processed during the earlier stages of processing. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Al-Anbar University for Islamic Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper addresses the problem of full-model estimation for non-parametric finite mixture models. It presents an approach for selecting the number of components and the subset of discriminative variables (i.e. the subset of variables having different distributions among the mixture components) by considering an upper bound on the number of components (this number being allowed to increase with the sample size). The proposed approach considers a discretization of each variable into B bins and a penalization of the resulting log-likelihood. Considering that the number of bins tends to infinity as the sample size tends to infinity, we prove that our estimator of the model (number of components and subset of relevant variables for clustering) is consistent under a suitable choice of the penalty term. The relevance of our proposal is illustrated on simulated and benchmark data. [ABSTRACT FROM AUTHOR]

The strongest gamma-ray burst (GRB) of the century, GRB20221009A, has been detected by the Korean Pathfinder Lunar Orbiter Gamma-ray Spectrometer (KGRS) instrument onboard the Korean Pathfinder Lunar Orbiter (KPLO). KGRS uses a LaBr3 detector to measure GRB counts with five energy bins in the energy range from 30 keV to 12 MeV. KGRS detected GRB221009A at a distance of 1.508 million kilometers from the Earth. The full duration of the main burst was recorded between 13:20 and 13:26 on October 9, 2022 with peak counts of over 1000 times background. The dead time of KGRS reached as high as 50%, and the intrinsic gamma-ray spectrum of LaBr3 was significantly altered. [ABSTRACT FROM AUTHOR]

Background: Metagenomic binning, the clustering of assembled contigs that belong to the same genome, is a crucial step for recovering metagenome-assembled genomes (MAGs). Contigs are linked by exploiting consistent signatures along a genome, such as read coverage patterns. Using coverage from multiple samples leads to higher-quality MAGs; however, standard pipelines require all-to-all read alignments for multiple samples to compute coverage, becoming a key computational bottleneck. Results: We present fairy (https://github.com/bluenote-1577/fairy), an approximate coverage calculation method for metagenomic binning. Fairy is a fast k-mer-based alignment-free method. For multi-sample binning, fairy can be > 250 × faster than read alignment and accurate enough for binning. Fairy is compatible with several existing binners on host and non-host-associated datasets. Using MetaBAT2, fairy recovers 98.5 % of MAGs with > 50 % completeness and < 5 % contamination relative to alignment with BWA. Notably, multi-sample binning with fairy is always better than single-sample binning using BWA ( > 1.5 × more > 50 % complete MAGs on average) while still being faster. For a public sediment metagenome project, we demonstrate that multi-sample binning recovers higher quality Asgard archaea MAGs than single-sample binning and that fairy's results are indistinguishable from read alignment. Conclusions: Fairy is a new tool for approximately and quickly calculating multi-sample coverage for binning, resolving a computational bottleneck for metagenomics. FUg-6r-bD5B9L5eToLSA3E Video Abstract [ABSTRACT FROM AUTHOR]

Taxonomy underpins biological research because names are needed for comparative analysis, conservation status, and public communication. Despite this, many species remain undescribed and are therefore vulnerable and unprotected, particularly in the tropics. Neotropical Staphylinidae beetles (Coleoptera) are among the insect groups most likely to contain significant unknown and/or cryptic diversity. Here we used an integrative taxonomic framework to conduct a preliminary review of one particularly diverse genus of Staphylinidae (Anotylus) in Área de Conservaciόn Guanacaste, northwestern Costa Rica. We began by DNA barcoding novel collections and using Barcode Index Numbers (BINs) as an estimate of taxonomic diversity; we found 18 provisional new species. We augmented this genetic analysis with a morphometric analysis of adult morphological characters and found that we could differentiate most provisional species by external morphology as well as by elevation of collection. All the most abundant species could be differentiated from each other by differences in body size. One BIN included slight (~1%) genetic variation that corresponded with some morphological differentiation suggesting the existence of two species within a DNA BIN. Our results support the efficacy of DNA barcoding collections of tropical insects as an effective biodiversity estimator, one that can be used as a primer for integrative taxonomic studies using BINs as species hypotheses. [ABSTRACT FROM AUTHOR]

Traditional feature detection and description methods, such as scale-invariant feature transform, are susceptible to nonlinear radiation distortions (NRDs) and geometric distortions (GDs), which in turn generate a large number of outliers or incorrect correspondences. To address this issue, this paper proposes a simple yet effective heterogeneous model fitting (MIMF) for multi-source image correspondences. First, a multi-orientation phase consistency model is constructed, which fuses phase consistency, image amplitude and orientation to detect the correct correspondences of feature points. This model effectively reduces the influence of NRDs. Second, sub-region grids and orientation histograms are exploited to construct the log-polar descriptors with variable-size bins, which are robust to GDs. Finally, a heterogeneous model fitting method is proposed, which can effectively estimate the parameters of the transformation model for alleviating the influence of outliers. Experiments are performed on six public datasets and one constructed dataset containing ten types of multi-source images, and the experimental results show that the proposed MIMF method outperforms several state-of-the-art competing methods in terms of matching performance. [ABSTRACT FROM AUTHOR]

Copyright of Magazine General Union of Arab Archaeologists is the property of General Union of Arab Archaeologists and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Pragmatics, as a critical field, includes, in addition to the text, its creator and its recipients, as well as its environment and time. Thus, it serves as a comprehensive framework encompassing these elements. This research focuses on studying the famous vision of Umar ibn Abi Rabi'ah within the framework of pragmatics, in an attempt to uncover the text's indications and delve into its depths through analysis according to the descriptive-analytical method and within the contexts that the concept of contextual pragmatics. Objectives of the study: Analysis of Omar bin Abi Rabi’ah’s opinion based on a ruling on pragmatics, hukmiyyat al-hukm, and ruling Methodology: This research came in two sections: The first: The general foundational frameworks for pragmatics and speech acts. The user: The contextual membership in the vision of Omar bin Abi Rabia. The results of this research were as follows: Results: 1. Omar bin Abi Rabia’s narrator carries semantic dimensions that cannot be understood outside the pragmatic understanding that includes the elements of the discourse. 2. Through pragmatic analysis of texts, It is possible to reveal the text’s references, metaphors, and ambiguities. Conclusion: The research focused on understanding the opinion of Omar bin Abi Rabia in the context of pragmatics and the theory of speech acts, and concluded with a number of results and recommendations. [ABSTRACT FROM AUTHOR]

One of the most suggestive points of contact between the thought of the Japanese philosopher and psychiatrist Kimura Bin and the phenomenology of Renaud Barbaras is the parallel between the way the concepts of life as a movement (of becoming) and as an event (of individuation) function in Barbaras's work, and the way that Kimura employs the terms bios (the individuated life of the organism) and zoē (life as the shared power in all living things). This conceptual frame enables both thinkers to give an account of life as an event that itself is caught up in the ongoing activity of the world. The article shows that bringing Kimura's work together with Barbaras's allows us to apprehend something that neither alone could fully grasp: the character of human life as an unfolding event that, as continuous with the life of the world, can be more fully effectuated as a movement of self-realization. [ABSTRACT FROM AUTHOR]

Defective chips in wafer bin maps (WBMs) form different spatial patterns depending on the root causes of process failures. Therefore, the identification of defect patterns in WBMs can help practitioners identify the root causes. Previous studies have focused on wafer-level classification even though chip-level classification can provide additional information regarding defect locations and defect sizes. Chip-level classification is more challenging than wafer-level classification because existing chip-level classification methods require chip-level labels, which are laborious to collect. We propose a method for chip-level defect classification using only wafer-level labels based on weakly supervised semantic segmentation. We first train a classification network using wafer-level labels and extract class activation maps (CAMs), which are visualizations of the discriminative regions. We then generate chip-level pseudo-labels using the extracted CAMs and use these labels to train a segmentation network, which predicts chip-level defect types. Experimental results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Babylon Center for Humanities Studies is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of ABHATH is the property of ABHATH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This is a study and investigation into a modern manuscript entitled ‘Interpretation of the Hadith Saba’t Youzelluhum Allah fi Zelih’ authored by the Scholar Mohammed Bin Ali Bin Ahmed Bin Taoloun Al-Salehi AlDemashquei Al-Hanafei, who died in 953AH. Chapter I of the study demonstrated an autobiography of the author and further cited the literature review where scholars had authored several dependent publications to explain and interpret the subject Hadith and compiled a number of traits and characteristics that elicit such shades of ALLAH. Chapter II is mainly concerned with investigation of the manuscript, together with comments raised over issues indicated therein and a number of Hadith. The study concluded with findings and recommendations. [ABSTRACT FROM AUTHOR]

In this research, the researcher dealt with the investigation of a manuscript tagged with: (Mukhtasar Kitab al-Ruh by Ibn al-Qayyim), a summary of Imam al-Hafiz: Ismail bin Muhammad al-Baali (d. 786). The abbreviation includes a mention of the issue and the origin of the answer and sometimes mentions some of the statements on the issue. The abbreviation refrains from mentioning any evidence, discussion, or protest. The abbreviation included the same number of issues mentioned in the original: twenty-one issues, such as identifying the dead by visiting the living, the meeting of spirits, on whom death falls on the soul or body, and by what do souls distinguish from each other? And about the return of souls to bodies and the causes of their torment and salvation, as well as other issues of the soul and its relationship with the body and its base, which Ibn al-Qayyim mentioned in his book The Soul. [ABSTRACT FROM AUTHOR]

Our objectives were to (1) evaluate cows' preferences for visiting feed bins limited to either same- versus mixed-parity social interactions, depending on their parity; (2) examine the effect of parity and bin social dynamic type on competition behavior and feeding patterns, and (3) investigate cow-level relationships between feed bunk competition behavior, feeding patterns, and feed efficiency. Twenty-eight primiparous and 28 multiparous (2.4 ± 0.6 lactations) lactating Holstein cows (127.8 ± 30.1 and 145.3. ± 10.4 DIM, respectively) were housed in a freestall pen with 28 roughage intake control bins (2:1 stocking density). Each cow was assigned to 2 bins, including 1 shared with 3 other cows of the same parity (SM) and 1 with 3 cows of mixed parities (MX, 50% primiparous and 50% multiparous). Feed bunk competition was recorded via video in the first hour after morning feed delivery for 2 d, and feeding patterns were recorded from 24-h roughage intake control data. Residual feed intake was calculated as the difference between predicted and observed dry matter intake after accounting for known energy sinks. Based on the first visit to the feed bunk after fresh feed delivery, multiparous cows tended to prefer the MX bin compared with the SM one; cows showed no other overall preference for bin type based on number of visits. Over time, multiparous cows remained consistent in their magnitude of preference for visiting each bin type, but involvement in competition was not consistent over time. Primiparous cows tended to be involved in more total competitive contacts and ate faster at the SM bin compared with the MX one. Those primiparous cows who visited the SM bin more often within the first hour after morning feed delivery tended to be less feed efficient. Multiparous cows initiated more successful replacements after a displacement at the MX versus SM bin, with no difference in feeding patterns between bin types. Regardless of parity or bin type, visiting the bunk sooner after feed delivery was correlated with involvement in more competitive interactions and more time eating within the first 30 min. Consuming more feed during a longer first visit to the bunk after fresh feed delivery was correlated with being less feed efficient. Overall, when given the choice of feeding from bins shared with cows of the same or mixed parities at a 2:1 stocking density, primiparous cows showed differences in behavior between those bin types, with implications for feed efficiency; these effects are perhaps an unintended consequence of compensatory strategies to avoid direct competition with multiparous cows. [ABSTRACT FROM AUTHOR]

Sugarcane is one of the most important crops in India, which meets the sweeteners requirement of people. India is one of the largest sugarcane producers in the world. Jaggery is a conventional sugar that is unrefined and often eaten all over the world. It is regarded as the healthiest sugar in the world because of its mineral and vitamin content as present in sugar cane juice. It is produced in India by the concentration of sugar cane juice, without separating molasses. The Jaggery making plants are placed in decentralized sectors in India. The efficiency of traditional plants producing jaggery is very poor because they are manufactured by local artisans. The use of multi-pan plants with a heat pump based freeze concentration system is found to be a successful approach for efficient jaggery production from the available literature in the manufacture of jaggery manufacturing plants. Due to the presence of inverted sugars and mineral salts that are hygroscopic in nature, the storage of Jaggery is difficult. The storage of jaggery in a whey coated drying cum storage bin is found to be most efficient in preserving the consistency of jaggery. The greenhouse drying of jaggery is an effective way to extract and preserve the moisture content of jaggery for a longer period of time. [ABSTRACT FROM AUTHOR]

We present a new generalization of the bin covering problem that is known to be a strongly NP-hard problem. In our generalization there is a positive constant Δ , and we are given a set of items each of which has a positive size. We would like to find a partition of the items into bins. We say that a bin is near exact covered if the total size of items packed into the bin is between 1 and 1 + Δ . Our goal is to maximize the number of near exact covered bins. If Δ = 0 or Δ > 0 is given as part of the input, our problem is shown here to have no approximation algorithm with a bounded asymptotic approximation ratio (assuming that P ≠ N P ). However, for the case where Δ > 0 is seen as a constant, we present an asymptotic fully polynomial time approximation scheme (AFPTAS) that is our main contribution. [ABSTRACT FROM AUTHOR]

Nu`aym bin Ḥammād is one of the famous scholars who made important contributions in hadith and Islamic belief. His book al-Fitan wa al-Malāḥim is considered the earliest work on great calamities before the end times. However, Nu`aym and his book have been criticized by previous and current hadith scholars. This study was conducted with the aim of studying Nu`aym's character and the position of his book al-Fitan. In order to achieve this goal, a qualitative method is used by analyzing the content that were found in scholarly writings about Nu`aym and the position of his book al-Fitan. This study shows that Nu`aym is a ṣadūq hadith narrator but makes many mistakes. His firmness in opposing the Jahmiyyah group caused him to die in government custody. As for his book, there are several political slanders and natural phenomena that prompted him to write this book alFitan. However, hadith scholars stated that this book contains many hadiths that are not reliable, and people must be careful when referring to them. [ABSTRACT FROM AUTHOR]

This paper aims to discuss the model for the creation of wayang figures depicting Kekayon Khalifah, specifically focusing on Khalid bin Walid, a renowned figure in leading battles. The method employed involves Artistic Research and Practice Based Research in contemporary art. The focus of this discussion lies in the development of practice-based artistic techniques. Furthermore, it explores the realization of these figures on buffalo skin, portraying the character as a respected warlord by his troops and feared by his enemies. Realization of embodiment through decorations and ornaments on beautiful leather crafts. This leathercraft works will produce artifacts in the form of the Khalid bin Walid paraga puppet. The ornaments and decorations in this work are complemented by the calligraphy of the characters' names. Then an interesting visual is created and can imply a certain message to the audience. Especially when this media is exhibited. Works that can be enjoyed by viewers. So this art can be used as education to the public, both formal and non-formal. [ABSTRACT FROM AUTHOR]

Histograms are frequently used to perform a preliminary study of data, such as finding outliers and determining the distribution's shape. It is common knowledge that choosing an appropriate number of bins is crucial to revealing the right information. It's also well known that using bins of different widths, which called unequal bin width, is preferable to using bins of equal width if the bin width is selected carefully. However this is a much difficult issue. In this research, a novel approach to AIC for histograms with unequal bin widths was proposed. We demonstrate the advantage of the suggested approach in comparison to others using both extensive Monte Carlo simulations and empirical examples. [ABSTRACT FROM AUTHOR]

The lack of suitable channel semiconductor materials has been a limiting factor in the development of tunneling field-effect transistor (TFET) architectures due to the stringent criteria of both air stability and excellent gate-tunable electronic properties. Here, we report the performance limits of sub-10-nm double-gated monolayer (ML) BiN TFETs by utilizing first-principles quantum-transport simulations. We find that ML BiN possesses an indirect bandgap of 0.8 eV and effective masses of 0.24m0 and 2.24m0 for electrons and holes, respectively. The n-type BiN TFETs exhibit better performance than the p-type ones, and the on-state current can well satisfy the requirements of the International Roadmap for Devices and Systems for both high-performance and low-power standards. Notably, we find that the BiN TFETs exhibit distinguished gate controllability with an ultra-low subthreshold swing below 60 mV/decade even with a small gate length of 6 nm, which is superior to the existing field-effect transistors, such as black phosphorus TFETs, GeSe TFETs, and BiN metal–oxide–semiconductor field-effect transistors. Furthermore, the BiN TFETs are endowed with the potential to realize high switching speed and low-power consumption applications because of their extremely short delay time and ultra-low power-delay product. Our results reveal that the ML BiN is a highly competitive channel material for the next-generation TFETs. [ABSTRACT FROM AUTHOR]

In this paper, we consider two types of semi-online problems with hierarchies. In the extensible bin-packing problem with two hierarchical bins, one bin can pack all items, while the other bin can only pack some items. The initial size of the bin can be expanded, and the goal is to minimize the total size of the two bins. When the largest item size is given in advance, we provide some lower bounds and propose online algorithms. When the total item size is given in advance, we provide some lower bounds and propose online algorithms. In addition, we also consider the relevant early-work-maximization problem on two hierarchical machines; one machine can process any job, while the other machine can only process some jobs. Each job shares a common due date, and the goal is to maximize the total early work. When the largest job size is known, we provide some lower bounds and propose two online algorithms whose competitive ratios are close to the lower bounds. [ABSTRACT FROM AUTHOR]