A new type of single–conversion–step wide–input–range versatile step–up/down three–voltage–level power–factor correction stage is presented in this manuscript. The rectifier can operate both in continuous–conduction mode and discontinuous–conduction mode. First, the rectifier’s principle of operation is described, and then the innovative rectifier is analyzed in continuous and discontinuous–conduction modes. After, an average model for the innovative rectifier is developed. Lastly, the proposed theory is experimentally validated using a multiplier–less dual–control–loop mode at discontinuous–conduction modes. It is shown that although no multiplier is used in the control circuitry, the power factor is near unity. It is revealed that the rectifier can swing the output voltage from 50 V to 900 V while the input voltage is 230 Vrms. Although the rectifier output has a split DC bus with three voltage levels, the required control effort is low, and the output voltage is balanced. The innovative topology suits any standard power–factor correction rectifier application, dual–stage low–voltage power supply, and three–level voltage supplement for low–harmonic inverters. Since the rectifier’s output–voltage swing is extremely wide, energy storage systems and electric vehicle batteries are suitable applications.

The competition among cities to host a sports team or a large-scale international sports event is modeled as a winner-pay contest with an entry fee. In the first stage, each contestant (city) decides whether to pay the entry fee (infrastructure required by the team, for example), which allows it to participate in the second stage, that is, the actual contest. We show that the contest organizer’s choice of the optimal entry fee does not depend on the number of contestants. Furthermore, in some cases, the result is a form of zero-sum game, in which the sports team or event organizer is the main beneficiary. The findings shed light on this type of competition and under what conditions on the entry fee a city might benefit from hosting a sports team or large-scale international sports event.

AbstractA contest's organizational structure or mechanism is often determined by the organizer's goal. While most contest organizers are interested in maximizing the effort expended by the contestants, some are interested in maximizing social welfare. We examine the corresponding contest mechanisms using a Tullock contest (standard and winner‐pay) combined with the yardstick approach, which in some cases can achieve both goals simultaneously. Two cases are considered. The first is the yardstick approach that takes the form of a payoff scheme in a standard Tullock contest where the contestants (winners or losers) are reimbursed according to the average effort of the other contestants. In the second, the yardstick approach is introduced into a winner‐pay contest, in which the winner pays the average cost of the other contestants' efforts.

Delivery systems are ubiquitous in today’s economy. However, those systems usually operate through purpose-built vehicles, which are inefficient, expensive, and highly harmful to the environment. We propose an optimal route crowd-shipping (OR-CS) system, a delivery service based on crowd transportation. The OR-CS system utilizes service points (SPs) and occasional couriers (OCs) to transfer deliveries. Senders drop packages at SPs, while receivers collect them from different SPs. The system is based on a new algorithm that assigns to each package an optimal route. The route is chosen individually for the package and is personally tailored according to the sender’s preferences and to the predefined routes of the OCs. To assess the real-life feasibility of the system, we developed a general simulator that emulates a city environment with authentic service points specifically selected based on desired attributes. The routes of OCs and the origins and destinations of packages were generated using a random process that differed between simulations. The results indicate that the system can be implemented and utilized. In addition, it yields positive results when the number of OCs surpasses a minimum threshold, which is feasible in most cities, given existing traffic loads. By adopting OR-CS, we can expect lowered delivery costs, reduced traffic congestion, and enhanced environmental sustainability.

Abstract This paper introduces a streamlined taxonomy for categorizing offensive language in Hebrew, addressing a gap in the literature that has, until now, largely focused on Indo-European languages. Our taxonomy divides offensive language into seven levels (six explicit and one implicit level). We based our work on the simplified offensive language (SOL) taxonomy introduced in (Lewandowska-Tomaszczyk et al. 2021a) hoping that our adjustment of SOL to the Hebrew language will be capable of reflecting the unique linguistic and cultural nuances of Hebrew. The study involves both linguistic and cultural analysis beyond Natural Language Processing (NLP). We employed manual linguistic analysis to understand the nuances of offensive language in Hebrew. An accompanying dataset, gathered on Twitter and manually curated by human annotators, is described in detail. This dataset was constructed to both validate the taxonomy and serve as a foundation for future research on offensive language detection and analysis in Hebrew. Preliminary analysis of the dataset reveals intriguing patterns and distributions, underscoring the complexity and specificity of offensive expressions in the Hebrew language. The aim of our work is to capture the complexity and specificity of offensive expressions in Hebrew beyond what automated NLP methods alone can provide. Our findings highlight the significance of considering linguistic and cultural variations when researching and correcting abusive language online. We believe that our streamlined taxonomy and associated dataset will be crucial in improving research in Hebrew language sociocultural studies, natural language processing, and offensive language detection. Our study also makes a substantial contribution to the study of low-resource languages and can be used as a model for future research on other languages.

Chlorella ohadii was isolated from desert biological soil crusts, one of the harshest habitats on Earth, and is emerging as an exciting new green model for studying growth, photosynthesis and metabolism under a wide range of conditions. Here, we compared the genome of C. ohadii, the fastest growing alga on record, to that of other green algae, to reveal the genomic imprints empowering its unparalleled growth rate and resistance to various stressors, including extreme illumination. This included the genome of its close relative, but slower growing and photodamage sensitive, C. sorokiniana UTEX 1663. A larger number of ribosome-encoding genes, high intron abundance, increased codon bias and unique genes potentially involved in metabolic flexibility and resistance to photodamage are all consistent with the faster growth of C. ohadii. Some of these characteristics highlight general trends in Chlorophyta and Chlorella spp. evolution, and others open new broad avenues for mechanistic exploration of their relationship with growth. This work entails a unique case study for the genomic adaptations and costs of exceptionally fast growth and sheds light on the genomic signatures of fast growth in photosynthetic cells. It also provides an important resource for future studies leveraging the unique properties of C. ohadii for photosynthesis and stress response research alongside their utilization for synthetic biology and biotechnology aims.

Abstract The issue of factual consistency in abstractive summarization has received extensive attention in recent years, and the evaluation of factual consistency between summary and document has become an important and urgent task. Most of the current metrics are adopted from the question answering (QA) or natural language inference (NLI) task. However, the application of QA-based metrics is extremely time-consuming in practice while NLI-based metrics are lack of interpretability. In this paper, we propose a cloze-based evaluation framework called ClozE and show its great potential. It inherits strong interpretability from QA, while maintaining the speed of NLI-level reasoning. We demonstrate that ClozE can reduce the evaluation time by nearly 96$\%$ relative to QA-based metrics while retaining their interpretability and performance through experiments on six human-annotated datasets and a meta-evaluation benchmark GO FIGURE\cite{gabriel2021go}. Finally, we discuss three important facets of ClozE in practice, which further shows better overall performance of ClozE compared to other metrics. The codes and models are released at https://github.com/Mr-KenLee/ClozE.

The mode of assessment is one of the most important factors influencing learning. E-assessment usually includes only checking the final answer, thus limiting teacher's ability to check the complete solution, and it does not allow inclusion of math proofs problems that constitute an important part of math content. The e-assessment module of Halomda elearning platform allows assessment of proof problems from different areas of school and high Math, like algebraic identities and inequalities, geometry proofs, trigonometrical identities, analytic geometry, vector algebra, etc. Although eassessment of a proof of a mathematical statement is generally a difficult task, in this paper we show through some working examples how guided e-assessment can be implemented using the Halomda platform.

Standard recordings of electrocardiograhic signals are contaminated by a large variety of noises and interferences, which impair their analysis and the further related diagnosis. In this article, we propose a method, based on compressive sensing techniques, to remove the main noise artifacts and to locate the main features of the pulses in the electrocardiogram (ECG). The motivation is to use trend filtering with a varying proximal parameter, in order to sequentially capture the peaks of the ECG, which have different functional regularities. The practical implementation is based on an adaptive version of the alternating direction method of multiplier (ADMM) algorithm. We present results obtained on simulated signals and on real data illustrating the validity of this approach, showing that results in peak localization are very good in both cases and comparable to state of the art approaches.