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The rapid development of Artificial Intelligence (AI) technology must be connected to the arithmetic support of high-performance hardware. However, when the deep neural network (DNN) accelerator performs inference tasks at the edge end, the sensitive data of DNN will generate leakage through side-channel information. The adversary can recover the model structure and weight parameters of DNN by using the side-channel information, which seriously affects the protection of necessary intellectual property (IP) of DNN, so the hardware security of the DNN accelerator is critical. In the current research of Side-channel attack (SCA) for matrix multiplication units, such as systolic arrays, the linear multiplication operation leads to a more extensive weights search space for the SCA, and extracting all the weight parameters requires higher attack conditions. This article proposes a new power SCA method, which includes a Collision-Correlation Power Analysis (Collision-CPA) and Correlation-based Weight Search Algorithm (C-WSA) to address the problem. The Collision-CPA reduces the attack conditions for the SCA by building multiple Hamming Distance (HD)-based power leakage models for the systolic array. Meanwhile, the C-WSA dramatically reduces the weights search space. In addition, the concept of a Side-channel star map (SCSM) is proposed for the first time in this article, and the adversary can quickly and accurately locate the correct weight information in the SCSM. Through experiments, we recover all the weight parameters of a $3\times 3$ systolic array based on 100000 power traces, in which the weight search space is reduced by up to 97.7%. For the DNN accelerator at the edge, especially the systolic array structure, our proposed novel SCA aligns more with practical attack scenarios, with lower attack conditions, and higher attack efficiency.

Despite considerable economic growth and development over decades in large developing economies, there remain substantial intra-country regional disparities. An increasing body of literature suggests that improving aggregate state capacity is critical in delivering efficient and effective development outcomes and last-mile delivery of public services. However, the role of enhancing local state capacity targeting such regional imbalances and activating a catch-up effect, in terms of economic development, is understudied. We examine this in the context of India’s ‘Backward Regions Grant Fund’ (BRGF) policy, an intervention aimed at enhancing the capabilities and effectiveness of local governments and village councils. We use a synthetic difference-in-differences (SDiD) econometric technique to estimate the causal effects of this policy on average luminosity density and growth in total night-time lights. We find that there is a 5–7 per cent increase in the average night-time lights and a 3–4 p.p. growth in total night-time lights. We provide supportive empirical evidence that improved provision of public goods, such as the availability of schools and road infrastructure, and enhanced local state capacity, serve as a potential mechanism causing this effect. [ABSTRACT FROM AUTHOR]

Several machine learning algorithms have been developed for the prediction of Alzheimer’s disease and related dementia (ADRD) from spontaneous speech. However, none of these algorithms have been translated for the prediction of broader cognitive impairment (CI), which in some cases is a precursor and risk factor of ADRD. In this paper, we evaluated several speech-based open-source methods originally proposed for the prediction of ADRD, as well as methods from multimodal sentiment analysis for the task of predicting CI from patient audio recordings. Results demonstrated that multimodal methods outperformed unimodal ones for CI prediction, and that acoustics-based approaches performed better than linguisticsbased ones. Specifically, interpretable acoustic features relating to affect and prosody were found to significantly outperform BERTbased linguistic features and interpretable linguistic features, respectively. All the code developed for this study is available at https://github.com/JTColonel/catch.

In demersal trawls, ground gears are typically fixed to the fishing line to protect against the seabed and ensure seabed contact. Rockhoppers (RH) are among the most applied types of ground gears, especially in fisheries with rough seabed. However, their use has earlier been associated with substantial loss of catch under the fishing line and low catch efficiency. A new ground gear concept known as the semicircular spreading gear (SCSG) has been documented to reduce this loss, but the catch efficiency of RH and SCSG gears has never been directly compared in a systematic commercial scale trial. Using twin trawl configuration, the present study compared the catch efficiency of a RH gear and a SCSG gear with both size selective and blinded trawls. Eighteen hauls were conducted in the Barents Sea demersal trawl fishery where cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) are target species and redfish (Sebastes spp.) is an important commercial bycatch species. Using size selective trawls, the catches with the trawl equipped with the SCSG resulted in an average increase of 25.44 for cod, 32.04 for haddock and 64.34% for redfish compared to the trawl equipped with the RH gear. With blinded trawls, the increase changed to 41.35, 65.76 and 44.23% for cod, haddock and redfish, respectively. Despite the significant increase in catch efficiency observed for the trawl equipped with the SCSG, it also caught significantly more undersized fish than the trawl equipped with the RH gear. This increase illustrates the importance of size selective devices, especially if the use of the SCSG is widely adopted by industry.

We support a preliminary determination of the catch-bond character of a mechanical–chemical toy model using a tweezers construction with some modifications. We discuss a theoretical analysis of the problem using Newton trajectories. We propose a two-dimensional potential energy surfaces for this model. We discuss the slip, ideal and catch-bonds for this model using the previous potential parts of Dansuk and Keten (Matter 1:911, 2019). Chemical examples of the ansatz are allosteric reactions, especially FimH proteins. We note again that Newton trajectories provide the theoretical background of mechanochemistry. Construction of a potential energy surface and use of Newton trajectories by Wolfram Mathematica. Calculation of real catch bond behavior. We get for a tweezers model the catch bond behavior.Graphical abstract: Two barriers under external force, F. The catch-bond barrier increases.

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From lowcountry writer William Baldwin comes a new edition of his 1993 Lillian Smith Award-winning novel, The Hard to Catch Mercy. Including a new introduction by the author, this Southern Revivals edition makes available once more a story that touches on the issues of religion, race, and coming-of-age in the post-Civil War South, when the lines between these issues were not always clear. Set in fictional Cedar Point, a small southern community in the early 1900s, The Hard to Catch Mercy is told through the eyes of a young boy, Willie T., who is forced to confront the changing world around him. Including a cast of incredibly outlandish characters, Baldwin's novel is a wild, darkly comic tale rich with trick mules, Christian voodoo, fire, brimstone, first love, death, and the end of the world as Willie T. knows it.

Catching objects in flight (i.e., thrown objects) is a common daily skill for humans, yet it presents a significant challenge for robots. This task requires a robot with agile and accurate motion, a large spatial workspace, and the ability to interact with diverse objects. In this paper, we build a mobile manipulator composed of a mobile base, a 6-DoF arm, and a 12-DoF dexterous hand to tackle such a challenging task. We propose a two-stage reinforcement learning framework to efficiently train a whole-body-control catching policy for this high-DoF system in simulation. The objects' throwing configurations, shapes, and sizes are randomized during training to enhance policy adaptivity to various trajectories and object characteristics in flight. The results show that our trained policy catches diverse objects with randomly thrown trajectories, at a high success rate of about 80 % in simulation, outperforming the baselines significantly. The policy trained in simulation can be deployed seamlessly to the real world with only onboard sensing and computation, which achieves catching sandbags in various shapes, randomly thrown by humans. Our video and code are available at https://mobile-dex-catch.github.io.

Mosaic Flash is the darling of the baseball diamond. Hes half-seahorse, half-amazing, but when this Most Valuable fish lets success go to his head, hell discover it doesnt matter how good you are, having a bad attitude isnt good. A folly of errors on the field sinks the seahorse supernova to the oceans abyss. After losing his confidence, friends and fin-atics, Mosaic finds Khofi, a ray of hope that will lead him back to the top of his game. A delightful story about sportsmanship, life and love.

The red snapper Lutjanus malabaricus is an ecologically and economically important demersal fish widely distributed in the southern coastal waters of Central Java, Indonesia. This study examined L. malabaricus biological traits, catch dynamics, and management aspects to generate key information for sustainable utilisation. Field sampling was carried out from March to July 2022 in Kebumen and Cilacap using bottom longlines. A total of 812 specimens were analysed to determine length-weight relationships, gonadal maturity, fecundity, catch per unit effort (CPUE), and sustainable yield. In Kebumen, the total length (TL) of specimens ranged from 25 to 65 cm, with an average of 43.8 ± 6.2 cm, dominated by medium-sized individuals that were close to the length at first maturity (Lm50 ≈ 38 cm). By contrast, samples from Cilacap showed a higher mean TL of 46.3 ± 7.5 cm, with a greater proportion of mature fish. The length-weight relationship (W = 0.1030*L²·⁴¹⁶⁴, R² = 0.79) indicated a negative allometric growth pattern. Catch per unit effort (CPUE) fluctuated markedly over the past five years, reflecting variations in fishing intensity and environmental conditions. The maximum sustainable yield (MSY) was estimated at 8,663.7 kg yr⁻¹, with an exploitation rate of 78%, suggesting that the stock is already fully exploited. These results highlight the urgent need for stronger management measures, such as the enforcement of minimum catch sizes, stricter regulation of fishing effort, and seasonal closures, to secure the long-term sustainability of L. malabaricus fisheries in Central Java.

Catch-based methods are widely used in marine fisheries management, particularly for assessing fish stock status in data-limited fisheries. However, their reliability remains controversial, especially when only catch data are available. In fisheries with inadequate monitoring, Catch Per Unit Effort (CPUE) data are often unavailable, despite the potential availability of total fishing effort records for entire areas. Here, we evaluate the potential of a proposed proxy-CPUE indicator, defined as the ratio of total catch to total fishing effort metrics, as a substitute for CPUE to enhance catch-based methods. Using chub mackerel (Scomber japonicus) in the Yellow Sea as a case study, we developed proxy-CPUE indicators using three types of large-scale effort metrics: Gross Vessel Count (GVC), Gross Vessel Power (GVP), and Target Vessel Count (TVC). These indicators were incorporated into a Bayesian state-space Schaefer surplus production model (BSM) and their performance was compared to catch-only methods (CMSY) across key evaluation criteria, including robustness of estimation, reliability in retrospective analyses, and performance when encountering catch observation errors. Additionally, we conducted simulations to assess the impact of dynamic catchability, demonstrating that proxy-CPUE methods remain robust even when catchability varies over time. Results indicate that proxy-CPUE substantially improves the robustness of stock status estimates, especially by mitigating the impact of high catch observation errors—reducing estimate variations by 50% compared to catch-only methods. Both GVC-based and GVP-based proxy-CPUE demonstrated reliable performance in retrospective analyses. This study provides a practical and scalable solution for the management of fisheries facing similar data constraints.

Background: Depression is a prevalent disorder with significant health impacts. Physical activity is known to protect against depression, but its effects may vary in populations with disrupted sleep patterns, such as weekend catch-up sleepers, which refers to participants who sleep longer on weekends than on weekdays. This study examines the dose-response relationship between physical activity and depression in this population.Methods: Data from 1,906 participants in the National Health and Nutrition Examination Survey (2021–2023) were analyzed. Physical activity was measured in MET-minutes per week, and depression was assessed using the PHQ-9. Multivariate linear regression, restricted cubic spline, and two-part linear regression models were employed.Results: In the adjusted model, physical activity showed a negative trend with depression, though this association did not reach statistical significance in the fully adjusted model. Stratified analyses revealed stronger associations in women (OR = 0.86, 95% CI: 0.75, 0.99, P = 0.0329) and individuals aged 40–60 years (OR = 0.79, 95% CI: 0.65, 0.97, P = 0.0237). A threshold effect was observed, with physical activity below 2.48 MET-min/1000-wk showing a negative association with depression (OR = 0.69, 95% CI: 0.56, 0.85, P = 0.0006). Beyond this threshold, the relationship changed.Conclusion: A nonlinear relationship between physical activity and depression was identified in weekend catch-up sleepers, with moderate activity levels (2.48 MET-min/1000-wk) offering the greatest mental health benefits, particularly in women and individuals aged 40–60 years.Clinical trial number: Not applicable.Graphical Abstract: