bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of motor imagery‐based brain‐computer interface combined with virtual reality on enhancing attention, executive function, and lower‐limb function in stroke: A pilot study
Authors: Wan Chunli , Zhang Wenting , Nie Yao , Qian Yingzhou , Wang Jian , Xu Haifeng , Li Zhongxuan , Su Bin , Zhang Yuting , Li Yongqiang
Published: February 2025

Background

Brain–computer interface combined with virtual reality (BCI‐VR) can reduce the difficulty of motor imagery execution and improve training performance. Few studies have focused on the effects of BCI‐VR on attention, executive function, and lower‐limb function in stroke.

Objective

To evaluate feasibility and preliminary efficacy of BCI‐VR pedaling training on the attention, executive function, and lower‐extremity function in people after stroke. It will also provide data support for future research, especially sample size calculations.

Design

A single group before‐after trial design was used. All participants had a stable level of function over a 2‐week period to ensure that their functional recovery was all attributable to BCI‐VR training.

Setting

The study was conducted in a specialized rehabilitation hospital.

Participants

Twelve participants with stroke, a certain level of motor imagery ability, capable of walking 10 meters continuously.

Interventions

All participants received a 4‐week BCI‐VR pedaling training program, 5 days per week, 30 minutes each session.

Outcome Measures

Primary outcomes are feasibility and safety. Secondary outcomes were lower‐extremity mobility, attention, and executive functions.

Results

Twelve patients were recruited from inpatient rehabilitation and nine completed the study (six males/three females; 56.6 ± 11.6 years). Recruitment and retention rates were 34% and 75%, respectively. Excellent adherence rate (97.7%) was obtained. No adverse events or equipment issues were reported. Following the intervention, significant improvements were found in the lower‐extremity strength, balance, walking stability, attention, and general cognitive function (p < .05). A significant correlation was found between improved Berg balance scale change values and symbol digit modalities test change values (p < .05, r = 0.677).

Conclusions

BCI‐VR pedaling training provides a depth of feasibility and safety data, methodological detail, and preliminary results. This could provide a useful basis for future studies of BCI‐VR pedaling training for stroke rehabilitation.

ClinicalTrials.gov registration number: ChiCTR2300071522 (http://www.chictr.org.cn).
Radiomic Analysis of Contrast‐Enhanced CT Predicts Recompensation in Hepatitis B‐Related Decompensated Cirrhosis
Authors: Chen Qiaofeng , Fan Yuanping , Wu Kaini , Cai Tianpan , Lan Chunyu , Yu Mingju , Fu Yunfeng , Zhu Qi , Qiu Jianhao , Zhou Xiaodong
Published: February 2025

Aims

Accurately predicting recompensation in patients with decompensated hepatitis B‐related cirrhosis is crucial for guiding treatment strategies. As a reliable model for accurately predicting recompensation is currently lacking, this study aimed to develop a contrast‐enhanced computed tomography (CECT) radiomics model specifically for assessing recompensation outcomes in this patient population.

Methods

A retrospective cohort of 218 patients with decompensated hepatitis B‐related cirrhosis was included. Patients were randomly divided into training (n = 152) and testing cohorts (n = 66) at a 7:3 ratio by random number generator. Radiomic features (N = 2922) were extracted from arterial phase (AP), venous phase, and delayed phase CECT images. Three machine‐learning algorithms were used to develop radiomic signatures. Independent clinical factors were identified using logistic regression. A combined model integrating radiomic signatures and clinical factors was then constructed. The Shapley Additive Explanation (SHAP) method was employed to visualize and interpret model predictions for individual patients. Model performance was evaluated based on calibration, discrimination, and clinical utility.

Results

A radiomic signature comprising 10 selected features extracted from AP images using logistic regression showed a significant association with recompensation outcomes (p < 0.001). This signature demonstrated strong discrimination, with an area under the curve (AUC) of 0.929 (95% confidence interval [CI], 0.882–0.968) in the training cohort and 0.853 (95% CI, 0.756–0.960) in the testing cohort. Serum total bilirubin and serum albumin levels were independently associated with recompensation outcomes (p = 0.033 and p < 0.001, respectively). The combined model incorporating both radiomic signatures and clinical factors exhibited comparable predictive performance to the radiomic signature alone, with AUCs of 0.925 (95% CI, 0.871–0.964; p = 0.487) in the training cohort and 0.865 (95% CI, 0.762–0.963; p = 0.669) in the testing cohort. SHAP analysis provided insights into the interpretability of the radiomics model, highlighting the importance of specific radiomic features in predicting recompensation. All prediction models demonstrated good calibration. Decision curve analysis confirmed the clinical utility of the radiomic signature.

Conclusions

This study demonstrates the strong potential of a CECT‐based computational approach, integrating clinical factors and radiomic features, for predicting recompensation outcomes in patients with hepatitis B‐related decompensated cirrhosis. However, the addition of clinical factors did not provide statistically significant improvement in predictive performance compared to the radiomic signature alone.
On the Origins of Out‐of‐Plane Auxetic Response in Paper
Authors: Verma Prateek , Griffin Anselm C. , Shofner Meisha L.
Published: February 2025

Previously, several commercially available papers were examined and an increase in thickness upon stretching in certain types was found. A mechanistic explanation for the origin of this auxetic response was also devised, utilizing earlier reports. In this article, the understanding of this mechanism is applied to examine auxeticity in lab‐produced paper handsheets. Only bleached kraft wood fiber pulp is employed, with no fillers, additives, or coatings incorporated. In this way, the contribution of a small number of structural factors to any auxetic response in the handsheets can be directly examined. Key structural parameters of a nonwoven cellulose fiber network in paper—staple fiber length, bulk density, and fiber contact spacing—which are predicted to affect the magnitude and sign of Poisson's ratio previously, are altered by using softwood and hardwood pulps with and without refining to produce a range of handsheets. It is found that longer fibers favor auxeticity while refining hampers it.
Heavy summer rainfall in southeastern Australia
Authors: Henderson Cameron R. , Barnes Michael A. , Reeder Michael J. , Quinting Julian F. , Jakob Christian
Published: February 2025

In the austral summer, parts of southeastern Australia are prone to heavy rainfall that causes major riverine flooding and fatalities. Easterly flow associated with an anticyclone in the Tasman Sea, large moisture transports from the Coral Sea, and upper tropospheric cyclonic disturbances all contribute to these heavy rainfall episodes. However, questions regarding their synoptic dynamics remain, including which of these ingredients are the most critical. These questions are addressed by comparing composite pressure and moisture fields of heavy rainfall days over selected regions with non‐heavy rainfall days that have a similar synoptic pattern. A synoptic climatology is constructed for this purpose by ‐means cluster analysis of 500 hPa geopotential height anomalies from the European Centre for Medium‐range Weather Forecasts Reanalysis v5, for all December to March days over a period of 40 years. Heavy rainfall days in the wettest clusters have negative 500 hPa geopotential height anomalies immediately west of the affected region that are stronger on average than those of non‐heavy rainfall days. Their accompanying distributions of surface pressure, precipitable water, and vertical motion are consistent with cyclonic baroclinic development and are preceded by anticyclonic Rossby wave breaking. Heavy rainfall days also show an increased frequency of blocking near E; however, this peaks 1–2 days after the onset of heavy rain. Regional rainfall in these clusters shows strong sensitivity to lower pressure immediately westward but little sensitivity to high pressure in the Tasman Sea until after the commencement of rain. A companion study using the same cluster analysis illustrated the link between anticyclonic Rossby wave breaking and heatwaves in southeastern Australia. These latest results highlight the upper cyclonic anomalies that often form on the equatorward flank of anticyclonic Rossby wave breaking as the key ingredient separating days with a favourable synoptic‐scale pattern of surface high pressure into those that rain heavily and those that do not.
Minimum Round‐Trip Time Prediction for Low Earth Orbit Satellite Networks
Authors: Chen Jiayi , Li Ye , Chai Haoye , Wang Jue , Wu Sheng , Pan Jianping
Published: February 2025

Low Earth orbit (LEO) satellite networks, characterized by wide coverage, low latency, and high bandwidth, will be a key component of the future 6G mobile communication networks. However, the periodic handover of satellites in LEO networks will lead to dynamic path changes and fluctuations in propagation delay, affecting the end‐to‐end performance. Establishing a minimum round‐trip time (minRTT) prediction model for LEO satellite networks is crucial for optimizing the design of related mechanisms such as routing, congestion control, and loss recovery. To this end, this paper first conducts a Starlink measurement to collect real‐life data and then proposes a novel model combining hybrid attention (HA) mechanisms with multiscale convolutional neural networks (MCNN) and long short‐term memory networks (LSTM) to explore minRTT prediction. The method utilizes HA to highlight important positional features in the minRTT sequence, while the MCNN and LSTM are exploited to capture the variation patterns of minRTTs, thereby enhancing the prediction accuracy. Experimental results show that the proposed HA‐MCNN‐LSTM model outperforms existing methods.
Is the Implementation of Cocoa Companies' Forest Policies on Track to Effectively and Equitably Address Deforestation in West Africa?
Authors: Addoah Thomas , Lyons‐White Joss , Cammelli Federico , Kouakou Keessy Maria‐Prisca , Carodenuto Sophia , Thompson William J. , Renier Cécile , Garrett Rachael D.
Published: February 2025

Tropical forests play a crucial role in achieving the sustainable development goals by contributing to climate stability, conserving biodiversity and sustaining livelihoods. However, forests are disappearing due to agricultural expansion. In West Africa, cocoa production is a major driver of deforestation. This study examines the design and implementation of forest‐focused supply chain policies (FSPs) in cocoa supply chains in Côte d'Ivoire and Ghana, the world's two leading cocoa producers. FSPs are voluntary policies of companies to combat deforestation, restore forests, and improve farmers' livelihoods. Drawing on 91 stakeholder interviews, we developed a conceptual framework to examine FSPs' theory of change, implementation and potential effectiveness and equity. Our findings reveal shortcomings in FSPs' design and implementation. FSPs are mostly narrowly focused on preventing illegal deforestation and only target farmers in companies' ‘direct’ supply chains, neglecting important landscape‐scale approaches and processes. Companies also fail to include smallholder farmers sufficiently in policy design and implementation. Lastly, FSPs prioritise productivity enhancement but overlook the importance of addressing farmers' social norms and values. We provide recommendations on how to address the shortcomings to achieve sustainable cocoa production.
Molecular 3D Characterisation of Drug Distribution and Mg‐Stearate Coating on Lactose Carrier Particles by ToF‐SIMS and XPS
Authors: Sjövall Peter , Ernstsson Marie , Mahlin Denny , Thalberg Kyrre
Published: February 2025

A common type of inhalation medicine uses a dry powder formulation where the active pharmaceutical ingredient (API) is attached on the surface of carrier particles, often in combination with additional components. The spatial distribution of the API on the carrier particle is critical for the release into the lungs and thus for the efficacy of the drug. In this work, we use ToF‐SIMS imaging in combination with argon gas cluster sputtering to determine the 3D distributions of budesonide (the API) and magnesium stearate (Mg‐stearate) on the surface of lactose carrier particles in a so‐called adhesive mixture formulation. The results show that the carrier particles are largely covered by Mg‐stearate, with only small spots showing exposed lactose or budesonide. Upon sputtering, Mg‐stearate is rapidly removed to expose flat regions of lactose as well as discrete budesonide particles distributed over the lactose surface. Depth profiles also indicate some smearing of budesonide on the lactose surface. These results provide clear evidence that budesonide, as well as lactose, is largely covered with Mg‐stearate on the drug particle surface. Subsequent SEM analyses of the sample areas provide detailed microstructural information, including identification of budesonide and lactose fine particles attached on the lactose surface. Furthermore, the thickness of the Mg‐stearate overlayer was estimated by XPS to be approximately 5 nm. The detailed information obtained about the 3D distribution of Mg‐stearate serves to clarify the mechanisms behind its performance‐enhancing effect in adhesive mixtures and also to improve formulation optimization with regard to Mg‐stearate load and application process.
A Novel Approach to Assess the Predictiveness of a Continuous Biomarker in Early Phases of Drug Development
Authors: Serra Alessandra , Geronimi Julia , Guilleminot Sandrine , Hadjur Hugo , Riviere Marie‐Karelle , Saint‐Hilary Gaëlle , Mozgunov Pavel
Published: February 2025

Identifying and quantifying predictive biomarkers is a critical issue of personalized medicine approaches and patient‐centric clinical development strategies. In early stages of the development process, significant challenges and numerous uncertainties arise. One of the challenges is the ability to assess the predictive value of a biomarker, i.e., the difference in primary outcomes between experimental and placebo arms above and below a certain threshold of the biomarker. Indeed, when the accumulated information is very limited and the sample size is small, preliminary conclusions about the predictive properties of the biomarker might be misleading. To date, the majority of investigations regarding the predictiveness of biomarkers were in the setting of moderate‐to‐large sample sizes. In this work, we propose a novel flexible approach inspired by the Kolmogorov‐Smirnov Distance in order to assess the predictiveness of a continuous biomarker in a clinical setting where the sample size is small. Via simulations we show that the proposed method allows to achieve a higher power to declare predictiveness compared to the existing methods under a range of scenarios, whilst still maintaining a control of the type I error at a pre‐specified level.
Synthesis, In Vitro Anticancer Evaluation and Computational Screening of Novel Imidazo [4,5‐c] Pyridine Derivatives
Authors: Rejinthala Swathi , Endoori Srinivas , Thumma Vishnu , Mondal Tanmoy
Published: February 2025

Two libraries of hybrid molecules combining imidazo[4,5‐c]pyridine with isoxazole and urea functional groups were synthesized and characterized using techniques such as ¹H NMR, 13C NMR, ¹⁹F NMR, HRMS, MS, FT‐IR, and elemental analysis. These compounds were evaluated for in vitro anticancer activity using the MTT assay against MCF‐7 (human breast adenocarcinoma) and A‐549 (lung cancer) cell lines. Several compounds showed significant anticancer potential, with IC₅₀ values ranging from 11.56 to 34.64 µM for A‐549 and 17.88 to 48.77 µM for MCF‐7, compared to standard drugs cisplatin and doxorubicin. Notably, a compound with a 3‐CF3‐phenyl group (3h) in the urea series demonstrated strong inhibition with an IC₅₀ of 11.56 ± 0.187 µM against A‐549 cells and moderate activity against MCF‐7 cells (IC₅₀ of 17.88 ± 0.235 µM). Molecular docking studies indicated favorable binding affinity to VEGFR2, EGFR and topoisomerase II, whereas pharmacokinetic evaluations confirmed favorable drug‐like properties, aligning with Lipinski's rule. Our study highlights these hybrid molecules as promising candidates for cancer therapy, underscoring their potential in medicinal chemistry.
Boosting the Application of Spent Catalysts in Waste Plastic Catalytic Pyrolysis: Maximizing Gasoline Product Selectivity and Quality
Authors: Zhang Jinqing , Wang Xiaodong , Sun Kun , Wang Ting , Zhao Hui , Chen Xiaobo , Zhang Xingong , Yang Chaohe
Published: February 2025

Catalytic pyrolysis is identified as a superior method for the disposal of waste plastics providing enhanced efficiency and environmental advantages compared to conventional techniques. However, the high cost of the catalytic process limits the enhancement of economic benefits. This study investigates the utilization of cost‐effective spent catalysts specifically Y zeolite, ZSM‐5 zeolite, and silica powder within a fixed‐bed/fluidized‐bed combination reactor setup to optimize the conversion of waste plastics into valuable products. The results show that the remarkable selectivity of spent Y zeolite for gasoline production achieving a yield of 52% with its pore characteristics inclined towards gasoline generation and moderate acidity sites being distinctive features. By implementing a thermal driving strategy with Y zeolite, the research further increases the C4 fraction by 1.5 times and significantly enhances olefin isomerization within gasoline representing crucial advancements that improve both the quantity and quality of the potential gasoline. These findings provide essential insights and support for the effective reuse of spent catalysts in the catalytic pyrolysis of waste plastics underscoring the potential for sustainable waste management and resource recovery.
Enhanced Microbial Desalination Cell Performance Utilizing Polyurethane‐Modified Bio‐Based Polymeric Membrane
Authors: Maheshwari Karishma , Sogani Monika , Sonu Kumar , Syed Zainab
Published: February 2025

The current study employs the microbial desalination cell (MDC) and uses cost‐effective bio‐based polymeric membranes. The membrane was developed using the flowering plant Delonix regia flower pod powder (DRF), which was then mixed with polyurethane (PU) (Control MDC). The addition of filler material, glass powder derived from waste (DRFG), to the DRF: PU (50:50 v/v) mixture in a ratio of 1:1 (Test MDC) was done due to the presence of silicates in the elemental composition of glass powder, which will lead to improved hydration, power densities, and ion exchange capabilities. The study revealed that the DRF and DRFG membranes had an ion exchange capacity of 0.078 and 0.098 mmol H+/g, respectively. The analysis revealed that adding recycled glass powder increased the ion exchange capability by 1.25 times as compared to the control MDC. The membranes developed for the MDC system were used to treat the RO‐reject water collected from a household RO system in Varanasi, India. The results showed that the power densities of control and test MDC systems were 55 and 230 mW/m2, respectively. Additionally, after 30 days of operation, the ion exchange capacity recorded was 0.040 and 0.095 mmol H+/g for control and test MDC systems, respectively.
When (not) to talk politics in business: Experimental evidence
Authors: Bondi Tommaso , Burbano Vanessa C. , Dell'Acqua Fabrizio
Published: February 2025

Research Summary

Chief executive officer (CEO) political activism is increasing, but its strategic implications remain unclear. We conduct two survey‐based experiments to shed light on how individuals respond to CEO activism. We differentiate between communicating an apolitical stance versus saying nothing ‐ an unexplored distinction to date. We furthermore examine whether characteristics which could influence perceived credibility of the stance ‐ whether it is consistent with expectations and whether it is backed by monetary commitment ‐ influence responses. We thus contribute to a deeper understanding of whether and how individuals’ perceptions of the firm are affected by CEO activism.

Managerial Summary

It is critical for managers to understand the implications of engaging in CEO political activism, a practice which has been on the rise in recent decades. Actively communicating an apolitical stance versus passively staying silent about an issue are two separate strategic choices available to managers which have been unexplored in the literature to date. This paper sheds light on how individuals respond to firms' communicating an apolitical stance, saying nothing, or taking an ideological stance in either direction on a political issue; and how this varies depending on whether the stance is perceived as consistent with expectations and whether it is backed by monetary commitment. It thus helps managers navigate stance‐taking on political issues.
Fluorinated Deep Eutectic Polymer Electrolytes with Hydrogen Bonds‐Rich Networks: Realizing Targeted Management of Primary Solvation Sheath Migration
Authors: Mo Yankui , Gao Yuqing , Li Mianrui , Qi Shengguang , Zhang Weifeng , Su Yufeng , Song Huiyu , Cui Zhiming , Du Li
Published: February 2025

The exploration of Li+ transport mechanism in the bulk and the interface holds the key to achieving rapid Li+ transport and desolvation kinetics. However, little is still known about that in gel polymer electrolytes enriched with hydrogen bond networks. Here, fluorinated gel‐deep eutectic solvated (FG‐DES) polymer electrolytes are fabricated for exploring the aforementioned mechanism by spectroscopy and molecular dynamics (MD) simulation. The observation provides an insight into the formation of [Li+···solvent] primary solvation sheath and the migration of the sheath along the polymer backbone in a fast and oriented manner through dissociation and complexation of the hydrogen bonds between solvents and polymer skeletons. Furthermore, the polymer backbone exerts a targeted management by pulling and anchoring effect on protonic solvent molecules, accelerating the desolvation process and reducing side reactions. Based on this, the capacity retention of the assembled LFP||Li is 94.7% after 600 cycles at 1 C, and the retention of NCM622||Li is 87.1% after 200 cycles, which demonstrats its excellent compatibility in lithium metal cells. This work offers a design basis for achieving rapid Li+ mobility and deposition in a hydrogen bonds‐rich environment.
Characterization of Deformation and Failure of Fomes fomentarius Hymenium by Synchrotron Phase‐Contrast Enhanced Micro‐Computed Tomography, In situ Compression Testing and Three‐Dimensional Optical Flow
Authors: Klemm Sophie , Nogatz Tessa , Perrin Jonathan , Weitkamp Timm , Redenbach Claudia , Fleck Claudia
Published: February 2025

Efficient design strategies found in nature have led to innovative materials and technologies. One promising blueprint for lightweight applications is the hymenium of Fomes fomentarius, a cellular, hierarchically structured, light, strong, and failure‐resistant biological tissue. Phase‐contrast enhanced micro‐computed tomography is used to investigate deformation and failure during in situ compression testing of the tubular honeycomb structure. Specimens are loaded parallel or transverse to the long axis of the tubes , in wet or dry condition. Displacements are evaluated between defined loading steps with three‐dimensional optical flow and morphological image analysis is used to correlate the micro‐ and mesostructure with local strains and structural damage. Key findings include that displacements are about five times larger in transverse than parallel loading, with greater displacements in regions of lower density. Higher hyphae density is found in struts compared to vertices, which leads to uniform displacements without significant local strain concentration. While cracks are observed in both struts and vertices, surprisingly, fracture is more catastrophic in the struts. Parallel loading results in plastic buckling and delamination in dry samples, while their wet counterparts show telescopic shortening from the first loading step and fewer fatal cracks, probably due to greater hyphae elasticity.
Molecular and Seroprevalence of Mycoplasma gallisepticum in Turkeys in Sylhet District of Bangladesh
Authors: Tipu Jahid Hasan , Miah Rijon , Islam Obaidul , Rahman Md. Mukidur , Talukdar Lucky , Miah Rubel , Hussain Md. Safwan , Islam Md. Ashraful , Ahsan Md. Irtija , Raquib Ahsan , Noor Monira
Published: February 2025

Mycoplasma gallisepticum (MG) poses a significant threat to Bangladesh's poultry industry, causing substantial economic losses every year. This study aimed to determine the prevalence of MG infection in turkeys using serum plate agglutination (SPA), enzyme‐linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) in Sylhet, Bangladesh from December 2019 to November 2020. In addition, we evaluated the diagnostic accuracy of these tests and identified potential risk factors associated with MG infection. A total of 250 blood samples and 250 tracheal swabs were collected from suspected turkeys across 25 farms from three sub‐districts of Sylhet namely Sylhet Sadar, Golapganj and Beanibazar. Blood samples were tested with SPA and ELISA, while tracheal swabs were analysed by PCR targeting the 16S rRNA gene of MG. The overall prevalence of MG was 35.2%, 29.2% and 25.6% for SPA, ELISA and PCR respectively. Higher infection rates were observed in turkeys aged 0–4 months (SPA 57.1%, ELISA 52%, PCR 42.8%), during winter (SPA 43.1%, ELISA 37.8%, PCR 30%) and among female turkeys (SPA 54.5%, ELISA 49.5%, PCR 45.5%). Geographically, the Beanibazar had the highest prevalence (SPA 54.2%, ELISA 48.6%, PCR 41.4%), compared to the Sylhet Sadar and Golapganj sub‐districts. Both SPA and ELISA tests showed 100% sensitivity, with specificity of 87.1% and 95.2%, respectively using PCR as a gold standard. Overall, these findings provide valuable insights for developing effective control measures for MG infections in the poultry industry of Bangladesh.
Social Practices and Health Risks
Authors: Burton-Jeangros Claudine
Published: February 2025

Risk implies choices over different scenarios to avert future harm. In parallel to the norms formulated on predictions defining a preferred course of action, personal responsibility toward health is regularly emphasized. The analysis of how recommendations reflecting risk evidence are actually endorsed, or not, by individuals provides insights into the respective role of social structures and their agency. In their health practices, people and communities indeed express various forms of autonomy when they select which risks they want to avoid and which ones they are ready to take or ignore. I examine the range of justifications they use to align with or to question public health recommendations. These include references to pleasure, moderation, a sense of personal immunity, and critiques of institutions, which helps us understand the multiple forms of practical responses adopted in the face of health risks.
Social Structures as Determinants of Health Risks
Authors: Burton-Jeangros Claudine
Published: February 2025

Experiences of health risks are shaped by social structures. Exposure to danger and resources to avoid or cope with adverse events are not evenly distributed across society, as evidenced by health inequality research. This chapter examines the role of social stratification factors in health risk experiences, bringing together empirical findings regarding their influence on risk interpretations and actions. Variations in responses to health risks across social groups also reflect power relations between those who define risks and implement mitigation measures and those who experience them amidst their daily circumstances. The discussion suggests that by not considering the influence of social positions and resources, the dominant risk model exacerbates inequalities rather than reducing them.
The Who, What, When, Where and Why of Social Impact Data
Authors: Aebi Carol
Published: February 2025

This chapter delves into the interconnection of social sustainability assessment information and data. The chapter starts by introducing the interconnection of Social Impact and Sustainability within assessments providing context to societal automation. The remainder of the chapter is structured in accordance with a landscape theory review of existing social value and social impact assessment literature including theories, metrics, measurements, and tools. This investigations considers social value for business and or societal institutions. It highlights the challenges of inconsistency when machines attempt to process and apply the data then unravels and unifies definitions to address this challenge. The investigation further explores the relationships between the data and maps the symbiotic relationship between the data and stakeholders measuring social impact. This chapter concludes with requirements for the systemic alignment of social sustainability information in a technological network that are further applied to the conceptual modeling of the Stigmergic Information System Network for Social Sustainability Information elaborated in subsequent chapters.
From Concepts to Coherence: Modeling Social Impact Data for Societal Systemic Alignment
Authors: Aebi Carol
Published: February 2025

This chapter presents a conceptual model of a stigmergic information system network for social sustainability data. It recognizes the omnipresence of technology in contemporary society and acknowledges the dynamic landscape of society. The interaction between humans and systems can be harmonized, leveraging collective intelligence to foster social sustainability. The Conceptual Model for a Stigmergic Information System Network for Social Sustainability proposes a structure that unifies and leverages social sustainability data from diverse societal activities to support alleviating social problems by design. This base model considers predictive, corrective, and retrospective analytics with system dynamic feedback loops applied against control module parameters to act as systemic thermostats for social stability, reduce perception bias, and monitor exploitative effects. The distributed architecture operates with self-organizing communication micro-processes. It introduces the capacity for increased transparency, data comparability, and social information sharing. The intended audience includes academics, business managers, policymakers, computer scientists, and sustainability practitioners, indicating the proposed concepts’ diverse applicability and relevance.
Panoptic Semantic Mapping Method for Tomato Growing Environment Based on K-Net and OctoMap
Authors: Zhang Junxiong , Zhang Yu , Xie Jinyi , Zheng Xiajun , Zhang Fan , Rao Weijie , Guo Jiayang
Published: February 2025

In modern greenhouses, complicated tasks and unstructured environments generate the imperious demand for advanced semantic information about each object at work scenes. A significant problem that mainstream methods intend to resolve is that the refinement and understanding of environmental information cannot efficiently cover the entire task in real time. Therefore, this paper proposes a panoptic semantic mapping method to identify each object that is supposed to be concerned in greenhouses. This method builds grid maps with advanced semantic information based on RGB and depth images. For the agricultural task with tomato as the working object, the categories of various objects in the grid map are divided into four groups: fruits, pedicels, stems and obstacles. This method consists of three steps: semantic segmentation from RGB images with K-Net, reconstruction of point cloud data based on depth images and semantic masks and transformation of the point cloud data into OctoMap. Experimental results show the semantic segmentation algorithm reaches a mean precision of semantic segmentation of 93.83%, a mean IoU of 88.39% and an average accuracy of 98.28%. Meanwhile, the refresh frequency of publishing point cloud data with advanced semantic information holds steady at 2 Hz with the resolution of 8 mm.
Research and Analysis of the Green Vision Rate of Street Space Based on Information Visualization Technology
Authors: Wang Jun , Zhang Hua , Yan Zhulong
Published: February 2025

Taking the research results of China National Knowledge Network (CNKI) from 1998 to 2023 as the data source, with the help of CiteSpace V and VOSviewer digital technology, the knowledge map on the research of China street space is drawn. The visualization technology shows the structure, evolution of street space, and the interrelationship of green vision rate research, and intuitively shows the research hotspot and frontier dynamics of green vision rate of street space in China. Research has learned that before 2017, the green vision rate of street space was in the bud, and then began to develop rapidly. At present, the street space green rate is mainly concentrated in the street roaming, street walkability, measurement method, evaluation index, healing environment, restorative environment, public space security, street image research, VR virtual reality research and green rate, green rate, green rate, etc. Through the visual map analysis of the green vision rate literature in the street space, it shows that the use of new technologies and cross-field integration will become the future research trend.
Research on Intelligent Monitoring System for Double-Boom Floor-Standing Derrick Based on Distributed Wireless Monitoring Technology
Authors: Sun Lijiang , Xia Yongjun , Meng Fanhao , Zhou Wei
Published: February 2025

Employing double-boom floor-standing derrick in tower erection construction involves complexities in tension and challenges in achieving real-time perception, potentially complicating construction tasks or leading to accidents. In order to enhance the safety of tower erection construction with the use of double-boom floor-standing derrick, this paper proposes an intelligent, information-based wireless monitoring system based on distributed wireless monitoring technology. Through an analysis of the tower erection construction process with the use of double-boom floor-standing derrick, this study identifies safety factors and monitoring parameters that impact the working conditions of double-boom floor-standing derrick. Given the extensive and dispersed nature of monitoring points within the holding pole system, a wireless, distributed, and multi-level monitoring scheme is adopted, which can satisfy the construction requirements on tower erection construction sites while ensuring safety and stability throughout the construction process.
A Configurable and Automated Testing Framework for Hardware Trojan Detection in FPGAs
Authors: Li Xiaodong , Chai Song , Wang Liwei , Wang Hua
Published: February 2025

With the widespread adoption of FPGA, the inevitable rise of security threats, including Hardware Trojan, poses significant risks. Detecting such trojan is crucial as they can lead to severe consequences. Consequently, various detection methods have been proposed. However, conventional approaches typically require extensive datasets for model training. To tackle this issue, this paper presents a customizable Hardware Trojan detection framework. This framework is designed to generate ample samples for FPGA hardware security testing, ensuring robust detection capabilities.
A Cache Scheduling Method Based on Adaptive Expiration for Data Process System
Authors: Fang Bin , Zhong Yibo , Sun Yizhen , Tu Jinjin , Jiang Guang , Xiao Yao
Published: February 2025

Cache data plays a crucial role in the operation of the power system. In practical applications, the demand for retrieval and queries has surged due to the vast amount of terminal data collected throughout the province. Placing data in the cache effectively improves query speed [1]. However, cache space is limited, and the amount of storable data is small [2]. Without proper control over the data placed in the cache, the hit rate may decrease [3]. Thus this paper proposes a new control method through adaptively setting the expiration time of cached data, which considers the historical traffic distribution and real-time query distribution. The simulation results show that the proposed method can significantly reduce the cache hit rate, which leads to the improvement of cache utilization. In addition, it avoids frequent cache replacements and reduces I/O overhead.
Research on the Application of Computer Vision Based on Deep Learning in Autonomous Driving Technology
Authors: Zhang Jingyu , Cao Jin , Chang Jinghao , Li Xinjin , Liu Houze , Li Zhenglin
Published: February 2025

This research aims to explore the application of deep learning in autonomous driving computer vision technology and its impact on improving system performance. By using advanced technologies such as convolutional neural networks (CNN), multi-task joint learning methods, and deep reinforcement learning, this article analyzes in detail the application of deep learning in image recognition, real-time target tracking and classification, environment perception and decision support, and path planning and navigation. Research results show that the proposed system has an accuracy of over 98% in image recognition, target tracking and classification, and also demonstrates efficient performance and practicality in environmental perception and decision support, path planning and navigation. The conclusion points out that deep learning technology can significantly improve the accuracy and real-time response capabilities of autonomous driving systems. Although there are still challenges in environmental perception and decision support, with the advancement of technology, it is expected to achieve wider applications and greater capabilities in the future potential.
Where is tree-level string theory?
Authors: Albert Jan , Knop Waltraut , Rastelli Leonardo
Published: February 2025

Abstract

We investigate the space of consistent tree-level extensions of the maximal supergravities in ten dimensions. We parametrize theory space by the first few EFT coefficients and by the on-shell coupling of the lightest massive state, and impose on these data the constraints that follow from 2 → 2 supergraviton scattering. While Type II string theory lives strictly inside the allowed region, we uncover a novel extremal solution of the bootstrap problem, which appears to contain a single linear Regge trajectory, with the same slope as string theory. We repeat a similar analysis for supergluon scattering, where we find instead a continuous family of extremal solutions with a single Regge trajectory of varying slope.
Probing low-reheating scenarios with minimal freeze-in dark matter
Authors: Bernal Nicolás , Fong Chee Sheng , Zapata Óscar
Published: February 2025

Abstract

The parameter space of freeze-in dark matter (DM) with mass m

χ
through light dark photon (“minimal freeze-in DM”) is currently being probed by direct detection experiments through electron and nuclear recoil. Exploring the DM production in the mass range 10
−2 MeV < m

χ
< 103 TeV, we quantify the impact of quantum statistics and the reheating dynamics (beyond the instantaneous reheating approximation) on the DM production in the early universe, in particular, the dependence on the cosmic equation of state and the scaling of the temperature of the Standard Model bath during reheating. Special cases corresponding to matter-domination and kination are carefully studied. To fit the entire observed DM relic abundance, low-temperature reheating scenarios require an increase in the coupling between dark and visible sectors which, in turn, enhances the regions of the parameter space that are already tested and will be probed by next-generation direct detection experiments for diverse reheating scenarios.
Drell-Yan transverse-momentum spectra at N3LL′ and approximate N4LL with SCETlib
Authors: Billis Georgios , Michel Johannes K. L. , Tackmann Frank J.
Published: February 2025

Abstract

We provide state-of-the-art precision QCD predictions for the fiducial W and Z boson transverse momentum spectra at the LHC at N3LL
′
and approximate N4LL in resummed perturbation theory, matched to available

$$ \mathcal{O}\left({\alpha}_s^3\right) $$

O

α
s
3

fixed-order results. Our predictions consistently combine all information from across the spectrum in a unified way, ranging from the nonperturbative region of small transverse momenta to the fixed-order tail, with an emphasis on estimating the magnitude of residual perturbative uncertainties, and in particular of those related to the matching. Parametric uncertainties related to the strong coupling, the collinear PDFs, and the nonperturbative transverse momentum-dependent (TMD) dynamics are studied in detail. To assess the latter, we explicitly demonstrate how the full complexity of flavor and Bjorken x-dependent TMD dynamics can be captured by a single, effective nonperturbative function for the resonant production of any given vector boson at a given collider. We point out that the cumulative

$$ {p}_T^Z $$

p
T
Z

cross section at the level of precision enabled by our predictions provides strong constraining power for PDF determinations at full N3LO.
The seven-point two-loop full-color all-plus helicity Yang-Mills amplitude
Authors: Dalgleish Adam R. , Dunbar David C. , Perkins Warren B. , Strong Joseph M. W.
Published: February 2025

Abstract

The seven-gluon two-loop full-color Yang-Mills amplitude is presented in a compact analytic form where we use the methods of four-dimensional unitarity cuts to obtain the polylogarithmic pieces and augmented recursion to obtain the rational pieces. Furthermore, an n-point form for the full-color polylogarithmic piece is presented. We use these results to probe for potential relations amongst the two-loop partial amplitudes.
Classifying Triebel–Lizorkin Capacities in Metric Spaces
Authors: Lehrbäck Juha , Mohanta Kaushik , Vähäkangas Antti V.
Published: February 2025

We study nonlocal or fractional capacities in metric measure spaces. Our main goal is to clarify the relations between relative Hajłasz–Triebel–Lizorkin capacities, potentional Triebel–Lizorkin capacities, and metric space variants of Riesz capacities. As an application of our results, we obtain a characterization of a Hajłasz–Triebel–Lizorkin capacity density condition, which is based on an earlier characterization of a Riesz capacity density condition in terms of Hausdorff contents.
Advantages of 3D printed patient-individual moulds in brachytherapy for facial skin cancer
Authors: Licher Jörg , Achenbach Julia , Köhn Janett , Diefenhardt Markus , Fleischmann Maximilian , Rödel Claus , Tselis Nikolaos , Ramm Ulla , Scherf Christian
Published: February 2025

Purpose

Facial skin cancer of 42 elderly frail patients was treated with individualised 3D-printed mould applicators for high-dose-rate (HDR) brachytherapy. The dosimetric outcome was compared to conventionally manufactured individual moulds used before.

Methods

Tumour-adapted HDR brachytherapy source paths were pre-planned and dosimetrically optimised in the brachytherapy treatment planning system (TPS) using computed tomography (CT) data and considered in the design of the patient-individual moulds. Dosimetric outcome for the planning target volumes and organs at risk were statistically evaluated and compared for pre-planning, final clinical treatment planning with TG-43 formalism and retrospective tissue, material and CT density related TG-186 calculations.

Results

Pre-planning allows reliable brachytherapy source paths design to achieve intended dosimetric clinical goals. The 3D-printed patient-specific moulds show a clear advantage in the dosimetric coverage of the target volume (improving D90 from 98.3% to 104.3%) and the protection of the relevant organs at risk (reduction up to 30% of maximum Dose). With the 3D-printed moulds only minor deviations were observed for TG-43 and TG-186 dose recalculations of the treated plans.

Conclusion

Customised 3D printed moulds offer a safe and efficient technique to treat facial skin cancer in critical locations and complex clinical situations with HDR brachytherapy. The two-step planning process results in reliable PTV dose coverage and efficient sparing of eye lenses and eyeballs. Dosimetric outcome and interfractional position reproducibility with 3D printed moulds were superior to conventionally manufactured facial moulds with respect to the clinical goals.
Exploring the correlation between design of experiments and machine learning prediction accuracy in ultra-precision hard turning of AISI D2 with CBN insert: a comparative study of Taguchi and full factorial designs
Authors: Adizue Ugonna Loveday , Takács Márton
Published: February 2025

Efficient optimization of processes involves excellent knowledge of the influence cum contributing effect on product quality, reliability, and improved productivity via precision machining in modern manufacturing technology. Thus, this research explores the correlation between design of experiment, process optimization, and predictive accuracy of machine learning models. An ultraprecision hard turning finishing experiment was carried out on an AISI D2 of 62 HRCs via a CBN insert with two different experimental designs, namely, the Taguchi design and the full factorial design. The process parameters, cutting speed (v

c
), feed (f), and depth of cut (ɑ

p
) were investigated with signal‒to‒noise ratios (S/N) and the response surface method (RSM), which are suitable for each experimental design for response parameters: surface roughness (R

ɑ
) and the material removal rate (MRR), respectively. The Bayesian regularization neural network (BRNN)–based machine learning model was implemented to estimate the surface roughness with data from each experimental design. The results show that surface roughness was strongly influenced by the feed, whereas the material removal rate was affected by all process parameters. The model performance significantly improved as additional process parameters were introduced in the full factorial design, with an R

2
of 0.99% and a MAPE of 8.14%. An empirical equation for estimating R

ɑ
is expressed in matrix form using the weights and biases from the BRNN. For the integration of the proposed model in real-time manufacturing and decision-making, an additional experimental test was performed to validate the models with a new dataset. The results show that the full factorial design has an improvement of 36% in predictive accuracy with minimum error over the Taguchi design and provides excellent interpretability of the process parameters. A dual assessment metric criterion was employed to ascertain the credibility of the models with corresponding designs.