Demands for uplink on mobile networks are increasing with the rapid development of social media platforms, 4K/8K content creation, IoT applications, and Fixed Wireless Access (FWA) broadband. As a result, Uplink MIMO (UL-MIMO) and Uplink Carrier Aggregation (UL-CA) have been widely deployed for the first time on commercial 5G networks. UL-MIMO enables the transmission of two data streams on one frequency band in strong RF conditions, theoretically doubling throughput and efficiency. On the other hand, UL-CA allows for simultaneous upload on greater channel widths, allowing more resources to be assigned to a single UE for higher throughput. In the United States, T-Mobile USA, a mobile network operator (MNO), has deployed network-wide 5G Standalone (SA), along with UL-MIMO on Time Division Duplex (TDD) band n41 and UL-CA between TDD and Frequency Division Duplex (FDD) NR bands. In this paper, the uplink throughput performance of UL-MIMO and UL-CA will be evaluated on the commercial T-Mobile 5G network on a variety of RF environments and modes of transportation. It was found that, even with the efficiency gains, UL-MIMO yields slower uplink throughput in most scenarios. However, in stronger RF conditions, UL-MIMO can provide an adequate user experience, so capacity can be conserved by reserving UL-CA for UE in weaker RF conditions.
Jose Miguel Campillo-Robles, Xabier Artetxe, Karmele del Teso Sánchez
et al.
Modelling and numerical simulations play a vital role in the design and optimization of electrochemical energy storage devices. In this study, a general physics-based model is developed to describe Hybrid Asymmetric Capacitors (HACs). A one-dimensional cell is constructed with one faradaic electrode, a separator and a capacitive electrode. The model is validated using a commercial Lithium Ion Capacitor (LIC). Galvanostatic charge and discharge processes are simulated with a maximum mean relative error of 7.8 %. This suggest that this simple Ohmic model captures the key electrochemical phenomena occurring inside the LIC cell.
This paper investigates the impact of financial technology (FinTech) on the financial sustainability (FS) of commercial banks. We employ a three-stage network DEA-Malmquist model to evaluate the FS performance of 104 Chinese commercial banks from 2015 to 2023. A two-way fixed effects model is utilized to examine the effects of FinTech on FS, revealing a significant negative relationship. Further mechanistic analysis indicates that FinTech primarily undermines FS by eroding banks' loan efficiency and profitability. Notably, banks with more patents or listed status demonstrate greater resilience to FinTech disruptions. These findings help banks identify external risks stemming from FinTech development, and by elucidating the mechanisms underlying FS, enhance their capacity to monitor and manage FS in the era of rapid FinTech advancement.
Natural disasters are increasing in frequency and severity, causing hundreds of billions of dollars in damage annually and posing growing threats to infrastructure and human livelihoods. Accurate data on roofing materials is critical for modeling building vulnerability to natural hazards such as earthquakes, floods, wildfires, and hurricanes, yet such data remain unavailable. To address this gap, we introduce RoofNet, the largest and most geographically diverse novel multimodal dataset to date, comprising over 51,500 samples from 184 geographically diverse sites pairing high-resolution Earth Observation (EO) imagery with curated text annotations for global roof material classification. RoofNet includes geographically diverse satellite imagery labeled with 14 key roofing types -- such as asphalt shingles, clay tiles, and metal sheets -- and is designed to enhance the fidelity of global exposure datasets through vision-language modeling (VLM). We sample EO tiles from climatically and architecturally distinct regions to construct a representative dataset. A subset of 6,000 images was annotated in collaboration with domain experts to fine-tune a VLM. We used geographic- and material-aware prompt tuning to enhance class separability. The fine-tuned model was then applied to the remaining EO tiles, with predictions refined through rule-based and human-in-the-loop verification. In addition to material labels, RoofNet provides rich metadata including roof shape, footprint area, solar panel presence, and indicators of mixed roofing materials (e.g., HVAC systems). RoofNet supports scalable, AI-driven risk assessment and serves as a downstream benchmark for evaluating model generalization across regions -- offering actionable insights for insurance underwriting, disaster preparedness, and infrastructure policy planning.
The rapid advancement of creating Zero-Knowledge (ZK) programs has led to the development of numerous tools designed to support developers. Popular options include being able to write in general-purpose programming languages like Rust from Risc Zero. Other languages exist like Circom, Lib-snark, and Cairo. However, developers entering the ZK space are faced with many different ZK backends to choose from, leading to a steep learning curve and a fragmented developer experience across different platforms. As a result, many developers tend to select a single ZK backend and remain tied to it. This thesis introduces zkSDK, a modular framework that streamlines ZK application development by abstracting the backend complexities. At the core of zkSDK is Presto, a custom Python-like programming language that enables the profiling and analysis of a program to assess its computational workload intensity. Combined with user-defined criteria, zkSDK employs a dynamic selection algorithm to automatically choose the optimal ZK-proving backend. Through an in-depth analysis and evaluation of real-world workloads, we demonstrate that zkSDK effectively selects the best-suited backend from a set of supported ZK backends, delivering a seamless and user-friendly development experience.
Organized crime and related economic crime are the focus of interest for all modern, well-organized states. Theoreticians generally agree that organized crime has closely followed the development of modern states, while economic crime has evolved with the development of the economy and business, both at national and supranational levels, alongside the expansion of information and communication technologies. Despite being viewed as two distinct types of crime, economic and organized crime are highly interdependent and interconnected. While a small number of economic crime offenses lack the characteristics of organized crime, a significant number of criminal activities exhibit organized elements within the realm of the economy and economic activities. Thus, the relationship between these two types of crime is directly proportional, wherein the development of organized crime follows the development of economic crime, and vice versa. In addition to the introduction and conclusion, the paper consists of three interconnected and interrelated parts. The first part elucidates the philosophy of organized crime. It highlights the problems of defining, the lack of a unique definition, and its multidisciplinary nature. Additionally, it presents the most significant characteristics and manifestations of organized crime in theory and practice. The second part deals with the issues of economic crime. Similarly to the first part, it discusses the process of determining and defining the concept of economic crime, presenting its basic characteristics and contemporary types. Finally, the third part of the paper examines the relationship between these two categories of crime.
Europa's surface exhibits many regions of complex topography termed 'chaos terrains'. One set of hypotheses for chaos terrain formation requires upward migration of liquid water from perched water bodies within the icy shell formed by convection and tidal heating. However, consideration of the behavior of terrestrial ice sheets suggests the upwards movement of water from englacial water bodies is uncommon. Instead, rapid downwards hydrofracture from supraglacial lakes - unbounded given a sufficient volume of water - can occur in relatively low tensile stress states given a sufficiently deep initial fracture due to the negative relative buoyancy of water. I suggest that downwards, not upwards, fracture may be more reasonable for perched water bodies but show that full hydrofracture is unlikely if the perched water body is located beneath a mechanically strong icy lid. However, full hydrofracture is possible in the event of lid break up over a perched water body and likely in the event of a meteor impact that generates sufficient meltwater and a tensile shock. This provides a possible mechanism for the transfer of biologically important nutrients to the subsurface ocean and the formation of chaos terrains.
This paper presents a speculative model exploring the behavior of quantum information for particles entering closed timelike curves (CTCs) in Kerr-Newman spacetime. We apply Gavassino's restoration principle to derive a theoretical framework for cyclic information dynamics within these extreme gravitational environments. Our model focuses specifically on particles that enter CTCs near the inner horizon of a Kerr-Newman black hole, examining how such curves might affect quantum state evolution, entanglement preservation, and information retention.
La República de Colombia, consciente del apogeo del crimen a nivel global y del modo como emplean los regímenes aduaneros, expidió con la nueva regulación aduanera una serie de modificaciones al régimen de tránsito y transporte multimodal. Esto con el fin de alcanzar un margen de eficacia, seguridad y confiabilidad en las operaciones que a diario se llevan a cabo en el país y rumbo al exterior. De ahí la importancia de examinar el contenido de esas disposiciones con este artículo de investigación.
Despite numerous chimeric antigen receptor T‐cell (CAR‐T) trials conducted in China, no CAR‐T has been registered in the country. Furthermore, China law and regulations restrict the export of patient material for CAR‐T manufacture abroad. Relma‐cel (JWCAR029), an anti‐CD19 product produced with a commercial‐ready process in China, was evaluated in the first prospective, single‐arm, multicenter, pivotal study of CAR‐T therapy conducted under Chinese IND to support an NMPA‐accepted BLA submission in relapsed/refractory (r/r) LBCL (NCT04089215).
In recent years, with the development of the mobile Internet, big data, and cloud computing, the mobile medical platforms such as Ding Xiang Yuan aggregating platform ecological resources have played an irreplaceable role in improving efficiency, optimizing resource allocation, and even promoting the transformation and upgrading of the medical industry. Despite all this, most mobile medical platforms in China still face many problems, including the immature business model, the stagnation of the interaction of knowledge and information among platform members, and the weak platform competitiveness. Based on a review of the platform and commercial ecosystems, this paper adopts the evolutionary game method and simulation to analyze the evolutionary stability strategy of operators, partners, and users in the core layer of the platform during preflow and postflow periods of a mobile medical platform, hence, to construct a beneficial dynamic equilibrium model of a platform business ecosystem under the optimal decisions made by all parties involved in the platform: the goal in the early stage (preflow period) is to increase platform user flow. Hence, the knowledge/information sharing of platform users is needed to enhance platform’s visibility. While in the late period (postflow period), when the platform user flow reaches a certain scale, platform’s goal is to promote revenue, which relies mainly on the pricing strategy. It is critical to promote the stability of the platform and the dynamic balance of interests at the core layer in the pricing process. This paper applies the platform business ecosystem theory and the evolutionary game theory to mobile medical platform development, contributing theoretically and practically in the following: (1) providing a more solid theoretical support for the mobile medical platform research and enriching the theoretical framework of the platform business ecosystem; (2) proposing the dynamic equilibrium model based on the optimal decisions of the platform core layers, which help to reveal the inherent law of the evolution of the mobile medical platform; (3) providing policy suggestions and management implications in constructing an appropriate business ecosystem and achieving sustainable development in mobile medical platforms.
The Hermite-Taylor method, introduced in 2005 by Goodrich, Hagstrom and Lorenz, is highly efficient and accurate when applied to linear hyperbolic systems on periodic domains. Unfortunately its widespread use has been prevented by the lack of a systematic approach to implementing boundary conditions. In this paper we present the Hermite-Taylor Correction Function method, which provides exactly such a systematic approach for handing boundary conditions. Here we focus on Maxwell's equations but note that the method is easily extended to other hyperbolic problems.
We present BotSIM, a data-efficient end-to-end Bot SIMulation toolkit for commercial text-based task-oriented dialog (TOD) systems. BotSIM consists of three major components: 1) a Generator that can infer semantic-level dialog acts and entities from bot definitions and generate user queries via model-based paraphrasing; 2) an agenda-based dialog user Simulator (ABUS) to simulate conversations with the dialog agents; 3) a Remediator to analyze the simulated conversations, visualize the bot health reports and provide actionable remediation suggestions for bot troubleshooting and improvement. We demonstrate BotSIM's effectiveness in end-to-end evaluation, remediation and multi-intent dialog generation via case studies on two commercial bot platforms. BotSIM's "generation-simulation-remediation" paradigm accelerates the end-to-end bot evaluation and iteration process by: 1) reducing manual test cases creation efforts; 2) enabling a holistic gauge of the bot in terms of NLU and end-to-end performance via extensive dialog simulation; 3) improving the bot troubleshooting process with actionable suggestions. A demo of our system can be found at https://tinyurl.com/mryu74cd and a demo video at https://youtu.be/qLi5iSoly30. We have open-sourced the toolkit at https://github.com/salesforce/botsim
A corporate entity which is in financial distress can resolve its predicament in two broad approaches. The first is by engaging in a formal bankruptcy procedure, which commonly involves a court, and enables the debtor to deal with creditors collectively. Alternatively, it can engage in an out of court restructuring based around negotiations with individual creditors. This article focuses on the engagements of corporate restructuring outside the formal statutory insolvency procedure and in particular prenegotiated deals, private workouts and pre-packs. The first section of the article provides a background to the out of court restructuring and underscores the many advantages it holds as compared to the formal insolvency proceedings. It then explores the development and usage of selected informal approaches to corporate restructuring. It concludes with an analysis of the place of informal strategies in Kenya. It is argues for the need to develop a functional equivalent of a workout which allows for the possibility of having mechanisms tailored on realities of a developing economy. However, having an effective workout is hugely dependent on the existence of reliable formal mechanisms to at least act as a threat of enforceable legal approach, and the weaknesses inherent in the Kenya formal mechanisms may be an impediment.
The article analyzes the novelties of recent years in the ield of tax law, as well as the ideas under discussion through the prism of the implementation of the idea of justice. In this context, their assessment was made, the advantages and disadvantages were identiied. The author notes some problematic aspects that may arise in the process of their implementation and proposed measures to overcome them. It was concluded that it was the proportional scale of taxation that was more consistent with the principle of equity, since it implied equality of legal position of persons in accordance with their economic situation. In this regard, counterarguments were given to the positions of opponents of such a transformation, which are reduced to the growth of the "shadow sector', the complication of tax administration and the decrease in the purchasing power of the population. We also analyzed the modified algorithm of taxation of citizens' property and noted the problems of its practical approbation. Although we approved the idea of calculating this tax on the basis of cadastral value instead of inventory value, since from now on the tax is directly due to the real value based on the commercial properties of the object and the general role in the market infrastructure, in practice, the "fair' implementation of this novel is still problematic due to the unavailability of the uniied real estate cadastre and the unity of methodology, which leads to frequent cases of contesting the value of property. Further, with regard to the resort collection, we concluded that the legislator, following foreign experience, decided to borrow the experience of the introduction of such a collection, but did not take into account the speciics of the "Russian soil", because it does not take into account the contingent of tourists visiting the experimental sites, and will not accept a differentiated approach to the amount of the tax. As a potentially possible consequence, there is a decrease in the tourist flow to the official tourist sector of Russian resorts, which will result in the loss of all taxes from this part. Finally, with regard to the taxation of self-employed, we concluded that this idea, being generally progressive, is unlikely to lead to a massive "way out of the shadow", because even the proposed advantages of such a step are not yet able to outweigh the risks and threats to this category of citizens. In conclusion, the prospects of further development of these ideas and concepts and their impact on strengthening the principle of justice in the tax law of Russia are evaluated.
Law, History of scholarship and learning. The humanities
Gopi Krishnan Rajbahadur, Erika Tuck, Li Zi
et al.
Publicly available datasets are one of the key drivers for commercial AI software. The use of publicly available datasets is governed by dataset licenses. These dataset licenses outline the rights one is entitled to on a given dataset and the obligations that one must fulfil to enjoy such rights without any license compliance violations. Unlike standardized Open Source Software (OSS) licenses, existing dataset licenses are defined in an ad-hoc manner and do not clearly outline the rights and obligations associated with their usage. Further, a public dataset may be hosted in multiple locations and created from multiple data sources each of which may have different licenses. Hence, existing approaches on checking OSS license compliance cannot be used. In this paper, we propose a new approach to assessing the potential license compliance violations if a given publicly available dataset were to be used for building commercial AI software. We conduct a case study with our approach on 6 commonly used publicly available image datasets. Our results show that there exists potential risks of license violations associated with all of the studied datasets if they were used for commercial purposes.
Let $A$ be a finite-dimensional algebra over a field of characteristic $p>0$. We use a functorial approach involving torsion pairs to construct embeddings of endomorphism algebras of basic projective $A$--modules $P$ into those of the torsion submodules of $P$. As an application, we show that blocks of both the classical and quantum Schur algebras $S(2,r)$ and $S_q(2,r)$ are Morita equivalent as quasi-hereditary algebras to their Ringel duals if they contain $2p^k$ simple modules for some $k$.
We consider a sparse high-dimensional varying coefficients model with random effects, a flexible linear model allowing covariates and coefficients to have a functional dependence with time. For each individual, we observe discretely sampled responses and covariates as a function of time as well as time invariant covariates. Under sampling times that are either fixed and common or random and independent amongst individuals, we propose a projection procedure for the empirical estimation of all varying coefficients. We extend this estimator to construct confidence bands for a fixed number of varying coefficients.
Abstract Wild animals and their derivatives are traded worldwide. Consequent poaching has been a main threat to species conservation. As current interventions and law enforcement cannot circumvent the resulting extinction of species, an alternative approach must be considered. It has been suggested that commercial breeding can keep the pressure off wild populations, referred to as wildlife farming. During this review, it is argued that wildlife farming can benefit species conservation only if the following criteria are met: (i) the legal products will form a substitute, and consumers show no preference for wild-caught animals; (ii) a substantial part of the demand is met, and the demand does not increase due to the legalized market; (iii) the legal products will be more cost-efficient, in order to combat the black market prices; (iv) wildlife farming does not rely on wild populations for re-stocking; (v) laundering of illegal products into the commercial trade is absent. For most species encountered in the wildlife trade, these criteria are unlikely to be met in reality and commercial breeding has the potential to have the opposite effect to what is desired for conservation. For some species, however, none of the criteria are violated, and wildlife farming can be considered a possible conservation tool as it may help to take the pressure off wild populations. For these species, future research should focus on the impact of legal products on the market dynamics, effective law enforcement that can prevent corruption, and wildlife forensics that enable the distinction between captive-bred and wild-caught species.