Hasil untuk "Special industries and trades"

Qingkai Liu, Haitao Jing, Xueying Wen et al.

Accurate, near real-time soybean phenology information is critical for crop management and breeding. Previous approaches relying on satellite remote sensing time-series data suffer from temporal delays, limiting their usefulness for in-season decision-making. To overcome this limitation, this study reframes phenology identification as a near real-time classification task using single-timepoint Unmanned Aerial Vehicle (UAV) imagery collected from 420 soybean germplasm resources across three experimental sites, and proposes an innovative multi-modal dynamic Gating Fusion Model that integrates two optimized pathways. one based on machine learning (ML) and the other on deep learning (DP). In the ML branch, systematic benchmarking of tabular-feature models identified the Soft Voting ensemble as the best classifier. In the DL branch, an enhanced BC-ConvNeXt model equipped with BiFPN and CBAM modules was developed to strengthen visual feature extraction. Building on these two optimal classifiers, the dynamic gating fusion model achieved the highest F1-score of 94.3% across seven key growth stages (V1, V2, R1, R2, R6, R7, R8). This result represents a significant improvement of 1.5% and 10.6% over the best performing ML and DL models, respectively. The superior performance arises from the intelligent arbitration of complementary strengths, with gating-weight analysis revealing a strategy that prioritizes ML predictions while leveraging DL for error correction. This work establishes a complete framework for near real-time crop phenology detection and demonstrates the strong potential of intelligent multi-modal fusion in high-throughput phenotyping.

Zhenyu Wang, Jing Sun, Zixiao Guo et al.

Vanadium redox flow batteries (VRFBs) face a significant challenge during high-temperature operation, as the precipitation of V2O5 on the positive side obstructs electrolyte flow, drastically diminishes battery capacity, and eventually leads to battery failure. While various additives have been explored to mitigate V2O5 precipitation, it continues to occur at temperatures exceeding 40 ℃. Unfortunately, there is a lack of research focused on effective methods for removing V2O5 from the battery system. The conventional approach requires disassembling the battery stacks to eliminate V2O5, a process that is not only labor-intensive and costly but also risks damaging the performance and components of the battery. In this study, we introduce an additive free strategy that enables the removal of V2O5 from the battery without the need for disassembly, thereby fully restoring battery capacity. This method is both efficient and simple, offering a cost-effective solution for V₂O₅ dissolution while potentially simplifying VRFB electrolyte manufacturing.

Yijia Xiao, Edward Sun, Tong Chen et al.

Developing professional, structured reasoning on par with human financial analysts and traders remains a central challenge in AI for finance, where markets demand interpretability and trust. Traditional time-series models lack explainability, while LLMs face challenges in turning natural-language analysis into disciplined, executable trades. Although reasoning LLMs have advanced in step-by-step planning and verification, their application to risk-sensitive financial decisions is underexplored. We present Trading-R1, a financially-aware model that incorporates strategic thinking and planning for comprehensive thesis composition, facts-grounded analysis, and volatility-adjusted decision making. Trading-R1 aligns reasoning with trading principles through supervised fine-tuning and reinforcement learning with a three-stage easy-to-hard curriculum. Training uses Tauric-TR1-DB, a 100k-sample corpus spanning 18 months, 14 equities, and five heterogeneous financial data sources. Evaluated on six major equities and ETFs, Trading-R1 demonstrates improved risk-adjusted returns and lower drawdowns compared to both open-source and proprietary instruction-following models as well as reasoning models. The system generates structured, evidence-based investment theses that support disciplined and interpretable trading decisions. Trading-R1 Terminal will be released at https://github.com/TauricResearch/Trading-R1.

Marina Morgado Garcia, Mariana Michel Barbosa, Augusto Afonso Guerra Júnior et al.

Introdução: A avaliação de serviços de saúde é compreendida como fator qualificador de gestão e tem papel fundamental como indicador de melhorias. A satisfação é entendida como a percepção do usuário, e quando utilizada para ponderar o acesso aos medicamentos, pode ser considerada um componente da avaliação da qualidade dos serviços, representando uma importante ferramenta de estratégias de gestão pública. Objetivo: avaliar a satisfação dos usuários em relação ao acesso aos medicamentos, na região metropolitana de Belo Horizonte, nas suas 5 dimensões: disponibilidade, acessibilidade geográfica, adequação, capacidade aquisitiva e aceitabilidade. Metodologia: Foi realizado estudo epidemiológico descritivo do tipo inquérito. O questionário foi aplicado em locais de ampla circulação com distintos públicos na região metropolitana de Belo Horizonte. A coleta de dados foi realizada com consumidores, com 18 ou mais anos, que utilizavam serviços privados e/ou públicos de saúde. Para mensurar a satisfação em relação às dimensões de acesso, foi utilizada a escala de Likert. Resultados e Discussão: Foram entrevistados 580 indivíduos, dos quais pouco mais da metade tinha plano de saúde e relatavam utilizar exclusivamente os serviços privados. Com uma diferença estatisticamente significante, um maior número de usuários que acessavam exclusivamente o serviço público estavam insatisfeitos ou muito insatisfeitos quando comparados aos usuários que utilizavam exclusivamente o setor privado, em relação a todas as dimensões de acesso a medicamentos: disponibilidade (31,4% versus 14,9%), acomodação (22,9% versus 9,09%) e acessibilidade geográfica (17,2% versus 10,0%), capacidade aquisitiva (31,5% versus 20,91%) e aceitabilidade (11,4% versus 8,79%), respectivamente. Considerações finais: Os resultados revelam que os indivíduos que acessam exclusivamente os serviços públicos, estão em sua maioria mais insatisfeitos que os indivíduos que acessam exclusivamente os serviços privados. Além disso, os dados indicam o nível mediano de satisfação em relação às diferentes dimensões que constituem acesso a medicamentos.

Zhengxin Zhao, Zongyang Li, Yao Li et al.

Maize-soybean intercropping systems are widespread in North China. However, the combined effects of supplementary irrigation and different nitrogen (N) application rates on the productivity, water use efficiency (WUE), and N use efficiency (NUE) of such systems remain unclear. A field experiment was conducted in a semi-humid drought-prone region in Northwest China in 2022 and 2023 to assess the interaction effects of supplemental irrigation and different N application rates on the crop yields, WUE, and NUE of a maize-soybean intercropping system and a monoculture system. Three cropping systems were used: maize-soybean intercropping, maize monoculture, and soybean monoculture, with two irrigation treatment scenarios (rainfed and supplementary irrigation at 30 mm) and three N fertilizer rates for maize (240, 180, and 120 kgN ha−1). The land equivalent ratio (LER), ∆water productivity (WP), ∆N harvest index (NHI), and ∆N partial factor productivity (NPFP) of the maize-soybean intercropping system ranged from 1.06 to 1.11, 1.03–1.11, 1.17–1.34, and 1.16–1.28, respectively, demonstrating higher yields and resource of the intercropping system Supplementary irrigation significantly improved yield and resource use by improving the N complementarity effect and increased the economic by 17.24–31.16 %. A 25 % reduction in the N application rate (180 kgN ha−1) for maize increased the NPFP without decreasing the crop yield and WP whereas, a 50 % reduction (120 kgN ha−1) significantly decreased the crop yield and the economic benefits. In summary, supplementary irrigation can improve the productivity and resource use efficiency, and appropriate reduction of N fertilizer will not reduce the yield of intercropping system. This study provides practical insights for enhancing sustainable agriculture by improving water and N use efficiency in maize-soybean intercropping systems in the semi-humid arid-prone regions of China.

Jonathan Weiping Li, Ren-Wei Liang, Cheng-Han Yeh et al.

This paper examines the phenomenon of probabilistic robustness overestimation in TRADES, a prominent adversarial training method. Our study reveals that TRADES sometimes yields disproportionately high PGD validation accuracy compared to the AutoAttack testing accuracy in the multiclass classification task. This discrepancy highlights a significant overestimation of robustness for these instances, potentially linked to gradient masking. We further analyze the parameters contributing to unstable models that lead to overestimation. Our findings indicate that smaller batch sizes, lower beta values (which control the weight of the robust loss term in TRADES), larger learning rates, and higher class complexity (e.g., CIFAR-100 versus CIFAR-10) are associated with an increased likelihood of robustness overestimation. By examining metrics such as the First-Order Stationary Condition (FOSC), inner-maximization, and gradient information, we identify the underlying cause of this phenomenon as gradient masking and provide insights into it. Furthermore, our experiments show that certain unstable training instances may return to a state without robust overestimation, inspiring our attempts at a solution. In addition to adjusting parameter settings to reduce instability or retraining when overestimation occurs, we recommend incorporating Gaussian noise in inputs when the FOSC score exceed the threshold. This method aims to mitigate robustness overestimation of TRADES and other similar methods at its source, ensuring more reliable representation of adversarial robustness during evaluation.

Lucas V. S. Oliveira, Daniel P. Marques, Luan C.A. Rocha et al.

Introdução: Ferramentas para determinação de causalidade de Reações Adversas a Medicamentos (RAM) são essenciais para o exercício da farmácia clínica; sobretudo considerando a complexidade terapêutica e vulnerabilidade do neonato sob terapia intensiva. O algoritmo de Naranjo é considerado padrão-ouro, contudo, ao contrário do algoritmo de Du, não foi desenvolvido para UTI neonatal (UTIN). Objetivo: Avaliar a correlação entre dois instrumentos de causalidade na avaliação de RAM suspeitas em NICU e sua reprodutibilidade intravaliadores. Métodos: Este estudo observacional e prospectivo foi desenvolvido em neonatos internados na Unidade de Terapia Intensiva de uma maternidade referência para gestação de alto risco em Natal/Brasil entre janeiro de 2019 e dezembro de 2020. Os casos de RAM suspeitas foram disponibilizados por três farmacêuticas independentes e experientes que aplicaram os algoritmos de causalidade Naranjo et al. e Du et al. O desempenho dos instrumentos foi mensurado pelo Kappa de Cohen (k) aplicado entre os avaliadores e entre os instrumentos. O estudo foi aprovado pelo Comitê de Ética e Pesquisa do Hospital Universitário Onofre Lopes sob nº 2.591.495/2018. Resultados: As farmacêuticas aplicaram os instrumentos em 79 casos de RAM que foram observadas em 57 neonatos do sexo feminino em sua maioria (30; 56,6%), com média de idade gestacional de 30±4 semanas e peso ao nascer de 1.446,0±1.179,3g. As reações mais comuns foram Taquicardia envolvendo Cafeína (14; 17,7%) e Dobutamina (5; 6,3%) e Hipertermia relacionada ao Alprostadil (5; 6,3%). Os métodos não apresentaram correlação significativa quanto a classificação da causalidade de RAM (k global = -0,031; IC95% -0,049 – 0,065). Contudo, o algoritmo de Naranjo apresentou melhor reprodutibilidade interavaliadores (k global = 0,402; IC95% 0,379 – 0,429. Correlação moderada) comparado a Du (k global = 0,108; IC95% 0,064 – 0,149. Correlação fraca). Conclusão: Não houve concordância entre os métodos testados, mas a determinação de causalidade de RAM em neonatos via Algoritmo de Naranjo apresentou melhor reprodutibilidade entre diferentes avaliadores.

Virda Fauziah, Ujang Setoko, Abdurrahman Salim et al.

The cotton plant is a fiber plant that is commonly used as a raw material for textiles, beauty, and health products. To increase cotton production, the development of superior varieties using plant breeding methods in cross-analysis is necessary. The cross-analysis method is used to determine the agronomic traits that affect cotton production, by selecting yield through several other characteristics related to yield. The aim of this study was to identify which agronomic characters can be used as selection criteria to increase cotton production using cross-analysis. The research was conducted at Politeknik Negeri Jember, and included 12 independent variables and one response variable, namely cotton production. The method used in this study was to perform correlation analysis, cross-analysis, calculate direct and residual contributions, and select agronomic characters that can be used as selection criteria. The results showed that the number of fruit characters had the highest correlation with cotton production (RX9Y = 0.835). Cross-analysis was carried out, and the highest direct effect was found between the number of fruit characters and cotton production (PX9Y = 0.971). The highest direct contribution was found in the character of the number of fruit, which had a total contribution of 98.321% and residue of 1.679%. Therefore, the agronomic character that can be used as a direct selection criterion is the number of fruits.

Ali Kaan Kurbanzade, Ansaar M. Baig, Sanjay Mehrotra

Unmanned aerial vehicles, commonly known as drones, have emerged as a disruptive technology with the potential to revolutionize operations across various industries. Drones are the fast-growing internet-of-things technology and are estimated to have a $100 billion market value in the next decade. Exploring drone operations through research has the potential to yield innovative academic insights and create significant practical effects in diverse industries, offering a competitive edge. Drawing insights from both academic and industry literature, this article describes how technological advancements in UAVs may disrupt traditional operational practices in different industries (e.g., commercial last-mile delivery, commercial pickup and delivery, telecommunication, insurance, healthcare, humanitarian, environmental, urban planning, homeland security), identifies the value of this evolving disruptive technology from sustainability and operational innovation perspectives, argues the significance of this area for operations management by conceptualizing a research agenda. The current state of the art focuses on the computing aspect of analytical models to tackle a variety of synthetic drone-related problems, with mixed integer optimization being the primary tool. There is a very significant research gap that should focus on drone operations management with industry know-how by partnering with actual stakeholders and using a variety of tools (i.e., econometrics, field experiments, game theory, optimal control, utility functions). This article aims to promote research on UAVs from operations management and industry-specific point of view.

Maritza Paola Maisincho Asqui, María Hipatia Delgado Demera, Carlos Alfredo Cedeño Palacios

Introducción: A nivel industrial la utilización de enzimas se ha ido incrementando a medida que se han optimizado sus procesos de producción, estabilización y condiciones operativas de la mano de la minimización de los costos asociados a su uso y de la sustentabilidad ambiental. El uso de la modelación matemática ha sido un factor clave para este avance, por lo que es un área de gran interés científico. Objetivo: Conocer el estado del arte en esta área del conocimiento, resaltando los hallazgos más exitosos y promisorios publicados recientemente. Materiales y Métodos: Se realizó una búsqueda sistemática de publicaciones recientes de alto impacto entre el 2015 y el 2021 en bases de datos reconocidas internacionalmente, y se llevó a cabo un análisis cualitativo/comparativo de los enfoques y contribuciones de la literatura seleccionada. Resultados y Discusión: Se evidenció que la mayoría de los modelos matemáticos desarrollados parten de la ecuación cinética de Michaelis-Menten pero las simplificaciones asumidas, las condiciones operativas evaluadas y los métodos utilizados para la resolución de estos sistemas, definen la singularidad y complejidad de cada investigación, lo que hace compleja su comparación o implementación de manera estandarizada. Conclusiones: En todos los casos, los modelos planteados se ajustaron a resultados experimentales o se observó concordancia al utilizar diferentes métodos de resolución matemática, lo que puede aportar valiosa información en la mejora de procesos y en el diseño de equipos, minimizando costos y tiempo de experimentación, a través de estrategias más amigables con el medio ambiente.

Michael O. Asare, Michal Hejcman

Abstract Wood ashes obtained from household heating and cooking are often applied to home gardens and arable fields by farmers. The effect of tree species and their locations on the elemental composition of wood ashes derived from domestic cooking and heating is unknown. The study aimed to discover the fertilizer values of wood ashes obtained from Betula pendula, Carpinus betulus, Fagus sylvatica, Larix decidua, Picea abies, Pinus sylvestris, Quercus robur, and Tilia cordata from two different localities, Hlinsko and Mšec, Czech Republic. The total element content in the ashes of dry wood samples (wood and bark) burnt at 460°C with a wood stove interfaced with a thermometer was determined using portable x‐ray spectrometry. The content (in g kg−1) of P (3.23–20.53), K (26.79–136.22), Ca (94.89–295.56), and S (2.97–11.75) in the ashes varies according to the tree species, locality, parent rock, and anthropogenic activities in the location of trees. Additionally, trace element contents ranged from 0.63–32.07 g Mn kg−1, 0.34–4.6 g Fe kg−1, 32.4–2062 mg Zn kg−1, 47.61–193.09 mg Cu kg−1, 3.99–21.53 mg Mo kg−1, and 1.50–6.62 mg Se kg−1. The pH of the ashes ranged from 8.71 to 11.54, suitable to alleviate soil acidity and a condition satisfying soil additive. A significant positive correlation between the contents of Cu, Sr, and Pb with the ashes of Picea abies, Larix decidua, Pinus sylvestris, and Betula pendula at Hlinsko is indicative of ancient anthropogenic activities input in the soil. The combustion of wood under home heating temperatures resulted in the concentration of most risk metal(loid)s, below permissible limits in agricultural soils. Application of wood ashes on arable fields requires considerable caution due to potentially toxic elements (Zn and Pb).

Jandir Ferrera de Lima, jandir Ferreira de Lima

Ivan Letteri, Giuseppe Della Penna, Giovanni De Gasperis et al.

Stock market forecasting is a lucrative field of interest with promising profits but not without its difficulties and for some people could be even causes of failure. Financial markets by their nature are complex, non-linear and chaotic, which implies that accurately predicting the prices of assets that are part of it becomes very complicated. In this paper we propose a stock trading system having as main core the feed-forward deep neural networks (DNN) to predict the price for the next 30 days of open market, of the shares issued by Abercrombie & Fitch Co. (ANF) in the stock market of the New York Stock Exchange (NYSE). The system we have elaborated calculates the most effective technical indicator, applying it to the predictions computed by the DNNs, for generating trades. The results showed an increase in values such as Expectancy Ratio of 2.112% of profitable trades with Sharpe, Sortino, and Calmar Ratios of 2.194, 3.340, and 12.403 respectively. As a verification, we adopted a backtracking simulation module in our system, which maps trades to actual test data consisting of the last 30 days of open market on the ANF asset. Overall, the results were promising bringing a total profit factor of 3.2% in just one month from a very modest budget of $100. This was possible because the system reduced the number of trades by choosing the most effective and efficient trades, saving on commissions and slippage costs.

Golnaz Shahtahmassebi, Lascelles Wright

Online trading has attracted millions of people around the world. In March 2021, it was reported there were 18 million accounts from just one broker. Historically, manipulation in financial markets is considered to be fraudulently influencing share, currency pairs or any other indices prices. This article introduces the idea that online trading platform technical issues can be considered as brokers manipulation to control traders profit and loss. More importantly it shows these technical issues are the contributing factors of the 82% risk of retail traders losing money. We identify trading platform technical issues of one of the world's leading online trading providers and calculate retail traders losses caused by these issues. To do this, we independently record each trade details using the REST API response provided by the broker. We show traders log activity files is the only way to assess any suspected profit or loss manipulation by the broker. Therefore, it is essential for any retail trader to have access to their log files. We compare our findings with broker's Trustpilot customer reviews. We illustrate how traders' profit and loss can be negatively affected by broker's platform technical issues such as not being able to close profitable trades, closing trades with delays, disappearance of trades, disappearance of profit from clients statements, profit and loss discrepancies, stop loss not being triggered, stop loss or limit order triggered too early. Although regulatory bodies try to ensure that consumers get a fair deal, these attempts are hugely insufficient in protecting retail traders. Therefore, regulatory bodies such as the FCA should take these technical issues seriously and not rely on brokers' internal investigations, because under any other circumstances, these platform manipulations would be considered as crimes and connivingly misappropriating funds.

Boris Čulina

The concept of inertial frame of reference in classical physics and special theory of relativity is analysed. It has been shown that this fundamental concept of physics is not clear enough. A definition of inertial frame of reference is proposed which expresses its key inherent property. The definition is operational and powerful. Many other properties of inertial frames follow from the definition, or it makes them plausible. In particular, the definition shows why physical laws obey space and time symmetries and the principle of relativity, it resolves the problem of clock synchronization and the role of light in it, as well as the problem of the geometry of inertial frames.

R. Jaczkowski, E. Uhlmann, Sven Anders et al.

High-performance materials offer enormous potential for increasing the efficiency of many complex and highly stressed systems in the aerospace industry. However, due to their special material properties, most of these materials are very difficult to machine using conventional machining processes such as turning, milling and drilling. In comparison, water jet cutting technology offers all the prerequisites to bring high-performance materials to their final contour and to efficiently realize a large portion of the material removal. Because of the complex geometry of 3D components used in the aerospace industry, a further development of existing system technology as well as the generation of cutting paths, which are usually designed for pure 2D machining, is required. The aim of the study is the implementation of an automated pre-contouring for difficult to machine materials using abrasive water jet cutting for industrial 3D applications. This is achieved by using an innovative workpiece clamping as well as a new cutting technology, the trimming, in order to reduce the costs of the pre-contouring process as well as the time and resource consumption of the entire process chain. During trimming, a continuous cut takes place and the semi-finished product is brought closer and closer to the required component geometry by cutting off the outer material areas. For this purpose, tests were carried out on workpieces made of stainless steel X5CrNi18 (EN 1.4301) with cutting conditions that are demanding for the abrasive water jet cutting process, such as high cutting depths with simultaneously low cutting angles. It was possible to use these findings to extend existing material models and thus ensure an error-free path generation for cutting processes. The investigations are the basis for the future use of waterjet cutting for near-net-shape machining of workpieces with complex 3D geometry. The experiments showed promising results in terms of the economic efficiency of the trimming process and provide a basis for subsequent investigations with difficult-to-machine workpieces for the aerospace industry.

de Lima Silva Paulo H., Naccache Mônica F., de Souza Mendes Paulo R. et al.

One of the main issues in the area of drilling and production in deep and ultra-deep water in the oil industry is the formation of natural gas hydrates. Hydrates are crystalline structures resembling ice, which are usually formed in conditions of high pressure and low temperature. Once these structures are formed, they can grow and agglomerate, forming plugs that can eventually completely or partially block the production lines, causing huge financial losses. To predict flow behavior of these fluids inside the production lines, it is necessary to understand their mechanical behavior. This work analyzes the rheological behavior of hydrates slurries formed by a mixture of water and Tetrahydrofuran (THF) under high pressure and low temperature conditions, close to the ones found in deep water oil exploration. The THF hydrates form similar structures as the hydrates originally formed in the water-in-oil emulsions in the presence of natural gas, at extreme conditions of high pressure and low temperature. The experiments revealed some important issues that need to be taken into account in the rheological measurements. The results obtained show that the hydrate slurry viscosity increases with pressure. Oscillatory tests showed that elasticity and yield stress also increase with pressure.

闻福岳, 卢昭禹, 曹均正 et al.

柔性直流输电换流阀所用的核心器件绝缘栅双极型晶体管（IGBT）的开关速度很快，IGBT开关过程中会产生强烈的电磁骚扰，加上雷击等瞬态骚扰，导致阀厅形成非常规的强电磁骚扰环境。子模块控制器作为子模块的控制和保护单元，属于低压信号设备，位于高压端子模块本体上，负责接收阀基控制器的开关指令和子模块本体的控制保护，因此电磁兼容（EMC）性能面临着严峻考验。为提升换流阀子模块控制器的EMC能力，对换流阀子模块周围电磁环境进行了仿真分析，并根据分析结果和相关标准，设定了控制器相关EMC试验参数，对控制器进行了针对性的电磁骚扰试验考核。系统分析并优化电路和试验方法，顺利通过浪涌抗扰度试验和射频场感应的传导骚扰抗扰度试验，并在实际工程应用中得到了验证。

乔铮, 郭庆来, 孙宏斌

随着燃气机组的广泛应用和电转气技术的快速发展，电力系统与天然气系统之间的互动日益密切，电力-天然气耦合系统是在该背景下形成的用于描述两个能源系统紧密耦合的系统形式。该耦合系统除了具有两个能源系统分别的运行特性和安全约束外，还因系统间的耦合互动产生了新的特点和约束，亟需新的分析和控制方法，近年来已经获得了国内外众多专家学者的关注和深入研究。文章从电力-天然气耦合系统的建模仿真、优化规划、运行分析（优化调度、安全评估）的角度对当前的主要研究成果进行了综述，同时总结了目前国内外学者对耦合市场的探索，最终对当前研究的不足和未来的研究方向进行了探讨。

Suneel Sarswat, Abhishek Kr Singh

We introduce a formal framework for analyzing trades in financial markets. These days, all big exchanges use computer algorithms to match buy and sell requests and these algorithms must abide by certain regulatory guidelines. For example, market regulators enforce that a matching produced by exchanges should be fair, uniform and individual rational. To verify these properties of trades, we first formally define these notions in a theorem prover and then develop many important results about matching demand and supply. Finally, we use this framework to verify properties of two important classes of double sided auction mechanisms. All the definitions and results presented in this paper are completely formalized in the Coq proof assistant without adding any additional axioms to it.