bluuebunny/crossref_metadata_2025 huggingface dataset:
Ethics round table: choice and autonomy in obstetrics
Authors: Wilkinson Dominic , Teli Safoora , Litchfield Claire , Madeley Anna , Kelly Brenda , Impey Lawrence , Brown Rebecca CH , Kingma Elselijn , Turnham Helen Lynne
Published: November 2024

Decisions about how and where they deliver their baby are extremely important to pregnant women. There are very strong ethical norms that women’s autonomy should be respected, and that plans around birth should be personalised. However, there appear to be profound challenges in practice to respecting women’s choices in pregnancy and labour. Choices carry risks and consequences—to the woman and her child; also potentially to her caregivers and to other women.

What does it mean for women’s autonomy to be respected in obstetrics? How should health professionals respond to refusals of treatment or requests for care outside normal guidelines? What are the ethical limits to autonomy? In this clinical ethics round table, service users, midwives, obstetricians, philosophers and ethicists respond to two hypothetical cases drawn from real-life scenarios.
Interferon-α as a biomarker to predict renal outcomes in lupus nephritis
Authors: Whittall Garcia Laura Patricia , Gladman Dafna D , Urowitz Murray , Bonilla Dennisse , Schneider Raphael , Touma Zahi , Wither Joan
Published: November 2024

Objective

To determine if serum interferon (IFN)-α levels at the time of a lupus nephritis (LN) flare are associated with renal outcomes.

Methods

Patients with an LN flare who had a preflare estimated glomerular filtration rate (eGFR) ≥60 mL/min were included in the study. The following outcomes were ascertained: (1) Time to first and second LN flares during follow-up, (2) Time to a sustained decline in eGFR by 30% and 50%, and progression to end-stage renal disease (ESRD, <15 mL/min), and (3) Time to an adverse renal event (≥2 renal flares and/or at least a 30% sustained decline in eGFR during follow-up). Serum IFN-α was measured by Simoa.

Results

92 patients with active LN were included in the study. Elevated serum baseline levels of IFN-α predicted poor renal outcomes. Patients with higher baseline IFN-α had a greater risk of having two or more subsequent LN flares (HR: 1.31 (1.08–1.59), p=0.006), sustained 30% decline in eGFR (HR: 1.27 (1.14–1.40), p<0.001), 50% decline in eGFR (HR: 1.27 (1.12–1.33), p<0.001) and progressing to ESRD (HR: 1.29 (1.14–1.47), p<0.001). Receiver operating characteristic analysis identified an IFN-α cut-off, 0.6 pg/ml, for predicting an adverse renal event.

Conclusions

Elevated serum IFN-α levels measured at the time of an LN flare are associated with poor renal outcomes, including the development of ≥2 LN flares, and a clinically meaningful decline in kidney function.
Deaf-led alarm design: technology and disability in home, work and parenthood
Authors: Von Koenig Gretchen
Published: December 2024

Domestic alarms are highly personal technological appendages that help us achieve an individual sense of safety and familial well-being—like baby monitors that help us care for children and alarm clocks that ensure a daily routine and help us get to work on time. Alarms can be understood as technologies that extend our eyes, ears, and memory to monitor our homes and ourselves in various ways beyond typical human capacity. The designs of domestic alarms tend to favour audible forms of alerting, and disabled users and inventors have hacked and redesigned alarms to fit their own families’ needs. Alarm design can tell us what type of domestic futures designers and technologists have imagined, casting visions about who is fit for parenthood and who is a reliable worker, and what types of futures disabled users imagined for themselves. As the future of these technologies becomes subsumed into smartphones and other IoT devices, a look into their predigital material forms uncovers episodes of disability agencies that assert a right to disability futures of domestic bliss and safety. Through the archives of The Deaf American and other deaf community publications, this research reviews the postwar alarm designs of Emerson Romero, a Cuban-American deaf activist and engineer, to show how deaf-led alarm designs are forms of material rhetoric that assert a right to a domestic future for disabled parents and workers.
‘Authentic’ or ‘corny’: LGBTQ+ young adults respond to visual, thematic and semantic elements of culturally targeted tobacco public education advertisements
Authors: Ennis Alysha C , Meadows Ashley , Jankowski Emma , Miller Caitlin , Curran Hayley , Elson Elle , Galusha Sydney , Turk Grace , Stanwick Monica , Patterson Joanne G
Published: November 2024

Background

Lesbian, gay, bisexual, transgender and queer (LGBTQ+) young adults (YA) experience disparities in nicotine and tobacco use. Mass-reach health communications can prevent nicotine and tobacco initiation and progression, but LGBTQ+adults report low engagement. Although cultural targeting (CT) could reach LGBTQ+YA, we know little about the strategies that resonate with this population. We probed how LGBTQ+YA perceived CT content to inform tobacco public education campaigns on strategies to engage this population.

Methods

We conducted six focus groups with N=20 LGBTQ+YA (18–35) who had ever used vapes, cigarettes or both. We showed participants examples of CT tobacco public education campaigns, probed their opinions and perceptions and coded transcripts using a data-driven inductive approach.

Results

Participants were more inclined to view an ad as effective when they felt it was authentically created for the LGBTQ+community. Avoiding stereotyping, including diversity, using ‘subtle’ LGBTQ+iconography (ie, rainbows), and including personal experiences all contributed to the authenticity of the ad. Participants discussed the importance of visual appeal; bright colours made ads appear too corporate or like an ad for a tobacco product. Lastly, participants responded well to gain-framed messages rather than traditional risk messaging.

Conclusion

Tobacco public education ads featuring ‘every-day’ LGBTQ+people in candid or unposed shots, personal stories with gain-framed messaging, and subtle Pride iconography and colours may increase acceptability among LGBTQ+YA. Researchers should focus on cultivating authenticity in ads and avoid outdated trends by consulting with the community and moving with speed from development to implementation.
Lived experiences of stigma and altered self-perceptions among young people who are addicted to ENDS: a qualitative study from Aotearoa New Zealand
Authors: Graham-DeMello Anna , Sanders Carissa , Hosking Renee , Teddy Lani , Ball Jude , Gallopel-Morvan Karine , van der Eijk Yvette , Hammond David , Hoek Janet
Published: December 2024

Introduction

Rising use of electronic nicotine delivery system (ENDS) among young people, especially those who have never smoked, has received considerable attention from the health community. However, fewer studies have examined the mental health impacts of ENDS use. We addressed this gap by exploring the stigma, altered self-perceptions and negative affect experienced by adolescents who assessed themselves as addicted to using ENDS.

Methods

We interviewed 20 adolescents aged 16–18 who lived in Aotearoa New Zealand and assessed themselves as moderately or highly addicted to ENDS use. Using in-depth, semistructured qualitative interviews, we explored participants’ experiences of addiction and its effects on their well-being. We interpreted the data using an inductive reflexive thematic analysis approach.

Results

We identified four key themes. First, addiction to ENDS use adversely affected participants’ physical and mental health. Second, addiction greatly diminished the pleasurable effects ENDS use first provided and participants who initially enjoyed using ENDS now felt unable to stop. Third, participants felt judged, stigmatised and belittled by others who did not understand their struggle with addiction. Fourth, they experienced several negative emotions, including self-blame, regret, disappointment and embarrassment that diminished how they saw themselves.

Conclusions

We extend earlier studies by probing the mental health burden ENDS use imposes on young people, offer new insights into how they experience addiction and outline potential policy responses. Measures reducing young people’s access to ENDS are urgently needed alongside empathetic, youth-oriented cessation support.
Impact of the intensified follow-up procedure of patients lost to 6-month follow-up after an intensive smoking and nicotine cessation intervention in practice: a cohort study
Authors: Roga Nawal Fayyaz , Liljendahl Mie Sylow , Tønnesen Hanne
Published: November 2024

Background

Post-intervention follow-up is challenging in research and practice. In tobacco reports, patients with missing follow-up were considered smokers. Based on patient and staff preferences, an add-on intensified follow-up procedure after intensive tobacco and nicotine cessation interventions was developed. This study examined the impact of the new procedure on patients lost to follow-up and compared their cessation status with that of those who completed routine follow-up.

Methods

Between January and February 2023, 2114 patients participated in the Danish STOPbase for Tobacco and Nicotine after providing informed consent. Overall, 1529 (72%) patients completed routine 6-month follow-up interviews, 136 (6%) patients rejected follow-up participation and 449 (21%) patients were lost to follow-up. Of the 449 patients, 225 patients were randomly selected to undergo the new follow-up procedure with repeated information, up to four extra calls, texts and voice messages from known telephone numbers.

Results

Using the new procedure, 143/225 (64%; 95% CI: 61% to 67%) patients completed the follow-up, with a continuous quit rate of 54/225 (24%; 21% to 27%). The lost to follow-up group had a significantly lower continuous cessation rate than the group that completed the routine follow-up: 54/143 (38%; 34% to 42%) and 703/1529 (46%; 45% to 47%), respectively, (p<0.01).

Conclusion

Almost two-thirds of the patients lost to 6-month follow-up completed the intensified follow-up procedure and had substantially lower cessation rates than those completing routine follow-up. However, this finding is clinically relevant, as a high follow-up rate impacts the reliability of outcomes, with loss to follow-up reported on continuous use.
CaloQVAE: Simulating high-energy particle-calorimeter interactions using hybrid quantum-classical generative models
Authors: Hoque Sehmimul , Jia Hao , Abhishek Abhishek , Fadaie Mojde , Toledo-Marín J. Quetzalcoatl , Vale Tiago , Melko Roger G. , Swiatlowski Maximilian , Fedorko Wojciech T.
Published: December 2024

The Large Hadron Collider’s high luminosity era presents major computational challenges in the analysis of collision events. Large amounts of Monte Carlo (MC) simulation will be required to constrain the statistical uncertainties of the simulated datasets below these of the experimental data. Modelling of high-energy particles propagating through the calorimeter section of the detector is the most computationally intensive MC simulation task. We introduce a technique combining recent advancements in generative models and quantum annealing for fast and efficient simulation of high-energy particle-calorimeter interactions.
Optimization of Growth Path for Enterprises Based on Complex Network Analysis and Embedded Neural Network Integration
Authors: Qian Sun
Published: November 2024

The rapid development of the research and study market has enhanced the intensity of market competition among enterprises, making the growth path of research and study entrepreneurial enterprises more complex. In order to enhance the growth path and deeply optimize the enterprise development strategy, this paper constructs an enterprise relationship analysis model using complex network analysis to help research and learning enterprises grasp the state of the market environment. It also analyzes customer information through the on-chip system integrated with embedded neural network to provide data information for enterprise product design optimization. The experimental results show that the model can effectively analyze the strength of the correlation between the research and learning entrepreneurial enterprises and other enterprises, and help the enterprises to understand their dominance over resources and information. In addition, the enterprise model in this paper is also able to analyze the market positioning deviation rate of enterprise research and learning products, and the research and learning products adjusted according to the results of the model analysis effectively enhance the efficiency of resource utilization, strengthen the enterprise’s dominance over resources and information in the network, improve the competitiveness of the enterprise’s market, and contribute to the shortening of the enterprise’s growth path and the optimization of the development strategy.
An Innovative Research on the Integration of Literary Aesthetic Artistic Embodiment and Embedded AI System-on-Chip Based on Virtual Reality Technology
Authors: Li Yuzhi
Published: November 2024

The artistry of literary aesthetics carries the core of the artist’s thought expression and is an important connotation to attract visitors. With the pursuit of personalized and diversified artistry by visitors, the traditional way of presenting artwork can no longer meet the needs of visitors. Therefore, this paper integrates virtual reality technology and embedded AI on-chip system to construct the artistic embodiment model of literary aesthetics, and realizes the purpose of enhancing visitors’ sensory feelings through virtual reality technology. At the same time, the embedded AI on-chip system also analyzes visitors’ preferences and behavioral data to provide artists with richer artwork expression elements. The experimental results show that the model system in this paper can optimize the artwork under the condition of maintaining the original characteristics of the artwork, and strengthen the artistic performance ability of the artwork, especially in terms of artwork innovation, emotional expression of newness and diversity of performance, which has been significantly improved. In addition, the model system in this paper can better integrate virtual reality technology and embedded AI system-on-a-chip data, shorten the system’s processing of artwork interaction data and response time, improve the interaction recognition rate, and enhance the completeness and timeliness of artistic expression.
Speech Recognition Based on Mobile Biosensor Networks and Quality Evaluation of University Political Education
Authors: Huang Aiwa
Published: November 2024

For a long time, traditional methods of teaching political science in Chinese schools have been in use. Teachers with a passion for politics may discover that their classroom time is better spent analyzing and improving contemporary pedagogical practices with the use of emotive reputation tools, which analyze voice, text, and textual data. Age, illness, trauma, verbal abuse, exposure to pollutants, clinical treatments, and clinical processes all raise the likelihood of voice loss. Discovering solutions to these difficulties is the most monumental undertaking in the history of technical advancement. The purpose of this study is to provide a cellular biosensor network-based assessment strategy that is honest, medical, and practically relevant to the current state of political education among Chinese university students. Among the many applications of MBNs are learning analytics, automated assessment, student incentives, and identity control. Students majoring in political science in college could benefit from using Mobile Biosensor Networks (MBN-QE) that measure how popular a person’s speech is. New developments in the field of mobile biosensor community technology seem to be heading in the right direction. Possible future directions for voice recognition include issues of accessibility, privacy, security, accuracy, modal integration, and herbal language interpretation. To achieve these objectives, research on the educational uses of biometric technology, the factors that have hampered its otherwise stellar reputation, and the potential uses of biometric data for trend forecasting must be undertaken. The findings show that the method of comparing students’ political education that is presented in this paper is consistent with prior studies. This study’s comprehensive assessment strategy proves that cell networks are useful for enhancing college students’ political education.
Quantitative Coding and Complexity Theory of
Continuous
Data: Part I: Motivation, Definition, Consequences
Authors: Lim Donghyun , Ziegler Martin
Published: November 2024

When encoding real numbers as (necessarily infinite) bit-strings, the naïve binary/decimal expansion is well-known

[
doi:10.1112/plms/s2-43.6.544
]

computably “
un
reasonable”, rendering, for example, tripling qualitatively discontinuous on Cantor’s sequence space. Encoding reals as sequences of (finite integer numerators and denominators, in binary, of) rational approximations does make common operations qualitatively computable, yet admits no bounds on their computational complexity/quantitative continuity. Dyadic approximations, on the other hand, are known polynomially, and signed binary expansions even linearly, “reasonable” in a rigorous sense recalled in the introduction of this work. But how to distinguish between un/suitable encodings of spaces common in Calculus beyond the reals, such as Banach or Sobolev?

With respect to qualitative computability/continuity on topological spaces, the technical condition of
admissibility
had been identified

[
doi:10.1016/0304-3975(85)90208-7
]

for an encoding over Cantor space (historically called a
representation
) to be “reasonable”

[
doi:10.1007/978-3-030-59234-9_9
]

. Roughly speaking, admissibility requires the representation to be (i) continuous, and to be (ii) maximal with respect to continuous reduction. Admissible representations exist for a large class of spaces. And for (precisely) these does the Kreitz–Weihrauch—sometimes aka
Main
—Theorem of Computable Analysis hold, which characterizes continuity of functions by continuity of mappings translating codes, so-called
realizers
.

We refine qualitative computability/continuity on topological spaces to quantitative continuity/complexity on metric spaces by proposing a notion, and investigating the properties, of
polynomially/linearly admissible
representations. Roughly speaking, these are (i) close to “optimally” continuous, namely linearly/polynomially relative to the space’s entropy, and they are (ii) maximal with respect to relative linear/polynomial quantitatively continuous reductions defined in the main text.

Quantitatively admissible representations are closed under composition over generalized ground spaces beyond Cantor’s. Such representations exhibit a quantitative strengthening of the qualitative
Main Theorem
, namely now characterizing quantitative continuity of functions by quantitative continuity of realizers. A large class of compact metric spaces is shown to admit polynomially admissible representations over compact
ultra
metric spaces, and some even a generalization of the linearly admissible signed binary encoding. Quantitative admissibility thus provides the desired criterion for complexity-theoretically “reasonable” encodings.
Physics-Informed Learning Based Multiphysics Simulation for Fast Transient TSV Electromigration Analysis
Authors: Yang Xiaoman , Chen Haibao , Zhang Yuhan , Hou Tianshu , Ren Pengpeng , Wang Runsheng , Ji Zhigang , Huang Ru
Published: November 2024

Through Silicon Vias (TSVs) are vulnerable to electromigration (EM) degradation due to their high local current densities, thereby reducing the reliability of 3D ICs with stack dies and TSVs. Due to the broad application of 3D ICs, it is necessary to analyze the electromigration reliability of TSVs. To overcome the weakness of traditional method for EM modeling of TSVs, we propose a physics-informed learning approach for transient analysis of electromigration modeling in TSV by solving the conventional mass balance equation. The proposed method allows simultaneous consideration of atomic depletion and accumulation, effective resistance degradation, electric current evolution, and stress distribution. In particular, we propose a customized neural network to simulate the EM process in TSV without the need for fine grid meshing and temporal iteration in traditional methods. Considering that the loss function of the proposed model is a combination of different loss terms, we propose a modified self-adaptive loss balanced method to automatically adjust the weights of multiple loss terms to enhance network performance. Given the prediction uncertainty due to data randomness or model architecture constraints, Gaussian probabilistic model is constructed to define the self-adaptive weights and update the dynamic weights per epoch built on maximum likelihood estimation. Compared with the finite element method, the proposed physics informed neural network method can lead to a speedup with less than 0.1% mean square error. Experimental results also show that the proposed model achieves excellent performance over other competing methods and high robustness under values of initial weights, different numbers of hidden layers and neurons per layer.
PADrone: Pre-flight Abnormalities Detection on Drone via Deep RF Sensing
Authors: Hadi Ghozali Suhariyanto , Ramesh Soundarya , Chan Mun Choon
Published: November 2024

Drone delivery is envisioned to be the delivery mode of the future due to its capability to provide autonomous, end-to-end delivery. Such rapid growth of the drone market necessitates careful checks on drone flight delivery, as a failure in any of a drone’s parts can result in an overestimation of the drone’s battery life, an unexpected increase in delivery time, or even a drone crash. Prior works utilize onboard sensors to detect potential drone failures during flight, which is a reactive approach where the problem may have already occurred.

In this work, we propose  
PADrone
, a
pre-flight
and an
automated
drone abnormality detection system that leverages contactless radio frequency– (RF) based vibration sensing. 
PADrone
utilizes an end-to-end deep learning pipeline to differentiate various abnormalities in motors, propellers, and other drone’s parts, by leveraging their unique
vibration fingerprints
.
PADrone
uses a frequency-modulated continuous wave radar-based RF system to capture these unique drone vibrations using an RF bandwidth of 150 MHz in the industrial, scientific, and medical band (5.8 GHz). Our real-world evaluations show that
PADrone
can classify various drone abnormalities with an average accuracy of 97.5%.
Resource-efficient Algorithms and Systems of Foundation Models: A Survey
Authors: Xu Mengwei , Cai Dongqi , Yin Wangsong , Wang Shangguang , Jin Xin , Liu Xuanzhe
Published: November 2024

Large foundation models, including large language models, vision transformers, diffusion, and large language model based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment. However, the substantial advancements in versatility and performance these models offer come at a significant cost in terms of hardware resources. To support the growth of these large models in a scalable and environmentally sustainable way, there has been a considerable focus on developing resource-efficient strategies. This survey delves into the critical importance of such research, examining both algorithmic and systemic aspects. It offers a comprehensive analysis and valuable insights gleaned from existing literature, encompassing a broad array of topics from cutting-edge model architectures and training/serving algorithms to practical system designs and implementations. The goal of this survey is to provide an overarching understanding of how current approaches are tackling the resource challenges posed by large foundation models and to potentially inspire future breakthroughs in this field.
Certified Unlearning for Federated Recommendation
Authors: Huynh Thanh Trung , Nguyen Trong Bang , Nguyen Thanh Toan , Nguyen Phi Le , Yin Hongzhi , Nguyen Quoc Viet Hung , Nguyen Thanh Tam
Published: December 2024

Recommendation systems play a crucial role in providing web-based suggestion utilities by leveraging user behavior, preferences, and interests. In the context of privacy concerns and the proliferation of handheld devices, federated recommender systems have emerged as a promising solution. These systems allow each client to train a local model and exchange only the model updates with a central server, thus preserving data privacy. However, certain use cases necessitate the deduction of contributions from specific clients, a process known as “unlearning.” Existing machine unlearning methods are designed for centralized settings and do not cater to the collaborative nature of recommendation systems, thereby overlooking their unique characteristics. This article proposes CFRU, a novel federated recommendation unlearning model that enables efficient and certified removal of target clients from the global model. Instead of retraining the model, our approach rolls back and eliminates the historical updates associated with the target client. To efficiently store the learning process’s historical updates, we propose sampling strategies that reduce the number of historical updates, retaining only the most significant ones. Furthermore, we analyze the potential bias introduced by the removal of target clients’ updates at each training round and establish an estimation using the Lipschitz condition. Leveraging this estimation, we propose an efficient iterative scheme to accumulate the bias across all rounds, compensating for the removed updates from the global model and recovering its utility without requiring post-training steps. Extensive experiments conducted on two real-world datasets, incorporating two poison attack scenarios, have shown that our unlearning technique can achieve a model quality that is 99.3% equivalent to retraining the model from scratch while performing up to 1,000 times faster.
Adapting Constrained Markov Decision Process for OCPC Bidding with Delayed Conversions
Authors: Zhang Leping , Zhang Xiao , Wang Yichao , Li Xuan , Dong Zhenhua , Xu Jun
Published: November 2024

Nowadays, optimized cost-per-click (OCPC) has been widely adopted in online advertising. In OCPC, the advertiser sets an expected cost-per-conversion and pays per click, while the platform automatically adjusts the bid on each click to meet advertiser’s constraint. Existing bidding methods are based on feedback control, adjusting bids to keep the current cost-per-conversion close to the expected cost-per-conversion to avoid compensation. However, they overlook the conversion lag phenomenon: There always exists a time interval between the ad’s click time and conversion time. This interval makes existing methods overestimate the cost-per-conversion and results in over conservative bidding policies which finally hurts the revenue. To address the issue, this article proposes a novel bidding method, Bidding with Delayed Conversions (Bid-DC) which predicts the conversion probability of the clicked ads and used it to adjust the cost-per-conversion values. To ensure the bidding model can satisfy the advertiser’s constraint, constrained Markov decision process (CMDP) is adapted to automatically learn the optimal parameters from the log data. Both online and offline experiments demonstrate that Bid-DC outperforms the state-of-the-art baselines in terms of improving revenue. Empirical analysis also showed Bid-DC can accurately estimate the cost-per-conversion and make more stable bids.
Security Challenges, Mitigation Strategies, and Future Trends in Wireless Sensor Networks: A Review
Authors: Oztoprak Ahmet , Hassanpour Reza , Ozkan Aysegul , Oztoprak Kasim
Published: December 2024

Wireless Sensor Networks (WSNs) represent an innovative technology that integrates compact, energy-efficient sensors with wireless communication functionalities, facilitating instantaneous surveillance and data gathering from the surrounding environment. WSNs are utilized across diverse domains, such as environmental monitoring, industrial automation, healthcare, smart agriculture, home automation, and beyond. Due to the inherent characteristics of WSNs they face many security challenges ranging from resource-based attacks, such as energy depletion or computational overload, to eavesdropping, interception, and tampering. Moreover, the dynamic and often
ad hoc
deployment of sensors in varying environments increases their vulnerability to physical intrusion attacks, the distributed and collaborative nature of WSNs raises concerns about data integrity, as compromised nodes can potentially propagate misleading or malicious information throughout the network. In this article, we categorize WSN attacks, identifying vulnerabilities and corresponding mitigation strategies. We also explore current research directions in WSN security, emphasizing the challenges in addressing these issues.
METASAT's Model Based Design Solutions
Authors: Kosmidis Leonidas
Published: December 2024

METASAT is a recently started project (January 2023) in the Horizon Europe programme, in the SPACE call, coordinated by the Barcelona Supercomputing Center (BSC). METASAT will develop model-based design (MBD) solutions for high performance on-board processors such as multicores, Graphics Processing Units (GPUs) and Artificial Intelligence (AI) Accelerators. While the developed tools and methodologies are particularly focusing on the space domain, reusability to other safety critical domains is also a project goal. This talk will provide an overview of the solutions which will be developed during the project, which will be centered around the open source TASTE framework used at the European Space Agency (ESA), which leverages AADL.
A Framework for Improving Portability and Ensuring Correctness of Operating System Kernels
Authors: Manjunath Vignesh , Baunach Marcel
Published: December 2024

Traditional embedded Real-Time Operating Systems (RTOS) or Basic Software (BSW) implementations typically require manual porting to new hardware platforms. However, this approach can be time-consuming and error-prone, especially given the frequent introduction of new or upgraded hardware architectures. In addition, traditional testing methods may not fully capture the complexity and nuances of the system, making it difficult to ensure correctness and dependability. To address these challenges, we propose a comprehensive methodology that integrates formal methods, a WCET tool, and a code generation technique. We use formal methods to create models and verify their correctness against functional and non-functional specifications or properties such as safety, liveness, and timing. We use the WCET tool as a microarchitecture analyzer to analyze the low-level binary code. The intermediate results of the tool are used to verify the correctness of the software implementation against the runtime effects of the hardware, such as data/memory race conditions. Finally, the code is generated from the formal models. Our proposed framework simplifies the maintenance of RTOS or BSW implementations while ensuring their correctness and partially automating portability to new hardware architectures.
Sensor Reproducibility Analysis: Challenges and Potential Solutions
Authors: Sekhar Praveen Kumar , Billey Wayant , Begay Makeiyla , Thomas Bradley , Woody Clarencia , Soundappan Thiagarajan
Published: December 2024

The ability to repeat research is vital in confirming the validity of scientific discovery and is relevant to ubiquitous sensor research. Investigation of novel sensors and sensing mechanisms intersect several Federal and non-Federal agencies. Despite numerous studies on sensors at different stages of development, the absence of new field-ready or commercial sensors seems limited by reproducibility. Current research practices in sensors needs sustainable transformations. The scientific community seeks ways to incorporate reproducibility and repeatability to validate published results. A case study on the reproducibility of low-cost air quality sensors is presented. In this context, the article discusses (a) open source data management frameworks in alignment with findability, accessibility, interoperability, and reuse (FAIR) principles to facilitate sensor reproducibility; (b) suggestions for journals focused on sensors to incorporate a reproducibility editorial board and incentivization for data sharing; (c) practice of reproducibility by targeted focus issues; and (d) education of current and the next generation of diverse student and faculty community on FAIR principles. The existence of different types of sensors such as physical, chemical, biological, and magnetic (to name a few) and the fact that the sensing field spans multiple disciplines (electrical engineering, mechanical engineering, physics, chemistry, and electrochemistry) call for a generic model for reproducibility. Considering the available metrics, the authors propose eight FAIR metric standards to that transcend disciplines: citation standards, design and analysis transparency, data transparency, analytical methods transparency, research materials transparency, hardware transparency, preregistration of studies, and replication.
13C stable isotope tracing reveals distinct fatty acid oxidation pathways in proliferative versus oxidative cells
Authors: Ritterhoff Julia , McMillen Timothy , Foundas Hanna , Palkovacs Roland , Poschet Gernot , Caudal Arianne , Liu Yaxin , Most Patrick , Walker Matthew , Tian Rong
Published: November 2024

By using 13C stable isotope-resolved metabolomics and FA-driven oxygen consumption rate analysis, our study provides novel insights into the fate of FA carbon through β-oxidation and downstream TCA cycle in proliferative and oxidative cells. Although both proliferative and oxidative cells demonstrate robust β-oxidation, they demonstrate distinct metabolic carbon fate downstream of citrate during TCA cycle oxidation. This differential TCA cycle engagement is likely to be important to balance catabolic and anabolic demands of the cell.
Effects of Different Drying Methods on Drying Kinetic Models, Physicochemical Properties, and Drying Quality Composite Scores of Rosa roxburghii Tratt (Fruit)
Authors: Ren Wei , Xu Jian , Zhang Yongping , Miao Yanyan , Liu Yao
Published: November 2024

The aim of this study is to investigate efficient, cost‐effective, and high‐quality drying technologies for Rosa roxburghii Tratt. Five drying methods—hot air drying (HAD), microwave drying (MD), vacuum drying (VD), microwave vacuum drying (MVD), and freeze vacuum drying (FVD), were employed to dry Rosa roxburghii Tratt. The study focused on evaluating drying characteristics, colors, texture and structure, and microstructure, as well as the content of active ingredients and antioxidant activity of Rosa roxburghii Tratt. The results of drying kinetics indicated that the Wang and Singh model was the most suitable for FVD, while the Page model was optimal for the other four drying methods. Rosa roxburghii Tratt subjected to HAD exhibited the highest energy consumption per unit but the lowest ΔE and the highest TFC. The microstructure of Rosa roxburghii Tratt under different drying methods was analyzed. Rosa roxburghii Tratt dried using MD experienced serious cell rupture, resulting in a large loss of active ingredients and the worst antioxidant ability, but it had the fastest drying rate. On the other hand, Rosa roxburghii Tratt dried under VD had the microstructure with the least pore space, leading to slower drying speed and the highest total polyphenol content. Rosa roxburghii Tratt dried using MVD had the least hardness and chewiness, with slightly better ΔE and active ingredient content compared to MD. FVD Rosa roxburghii Tratt took the longest time to dry, with the greatest ΔE difference, hardness, and chewiness, but it had the highest Vitamin C content and the most powerful antioxidant ability. Principal component analysis (PCA)–entropy weighting method was used to provide comprehensive scores for the different drying methods, with FVD, HAD, VD, MVD, and MD were 0.8107, 0.7037, 0.4499, 0.2746, and 0.0586 respectively. Through comprehensive analysis, we demonstrated that the quality of Rosa roxburghii Tratt obtained via FVD and HAD is satisfactory. Additionally, HAD is characterized by its economic efficiency and convenience, providing valuable insights for the industrial production of Rosa roxburghii Tratt drying.
Optical Characterization of Polyvinyl Alcohol–Zinc Oxide Nanocomposite Films Fabricated via Spray Coating and Enhanced Through Plasma Modification: A Comprehensive Study
Authors: Hakeem Haneen S. , Muhsen Maryam F. , Taieh Nabil Kadhim
Published: November 2024

Polyvinyl alcohol (PVA) and zinc oxide (ZnO) nanocomposite films were synthesized and characterized in this study through a spray method with varying concentration of ZnO nanoparticles incorporated within the polymer. The XRD patterns exhibit significant peak broadening, indicative of a high‐purity wurtzite hexagonal structure in the nanoparticles, and exhibit notably higher intensity peaks after argon (Ar) plasma treatment which may be due to increase in crystallinity of the ZnO nanoparticles. The AFM analysis of PVA samples with varying ZnO nanoparticle concentrations reveals a clear increase in surface roughness as the ZnO content rises. The mean roughness (Sa) increases from 0.90598 nm at 0 wt % ZnO to 1.18807 nm, 1.46771 nm, 1.84988 nm, and 2.60792 nm at 1 wt %, 3 wt %, 5 wt %, and 10 wt % ZnO, respectively. FESEM images show the change in morphology with the addition of ZnO nanoparticles where the round and clustered particles noted indicate a clustered distribution on the surface, and after plasma treatment, the surface gets etched or eroded. These films were then subjected to DC glow discharge plasma with Ar gases for functioning minutes starting from 15 min to 25 min. In order to study the change in the surface chemistry of PVA and PVA–ZnO nanocomposite films, the FTIR spectroscopy test was conducted. In the FTIR spectra, typical absorption bands of monoclinic phase of nano‐ZnO were present and thus it can be said that Ar plasma treatment could slightly affect the chemical functional groups present on the surface. For plasma‐treated materials, UV‐Vis absorption spectra indicated that optical absorption increased with ZnO concentration and shifted to longer wavelengths. The calculated refractive index values for the samples, which fall within the visible range of the spectrum, ranged from 1.356 to 1.891. The extinction coefficient was found to increase for both untreated and Ar plasma–treated samples with longer treatment times. This work focuses on application of plasma technology, namely, DC glow discharge plasma, for surface treatment that can be a promising technology to improve properties of material.
Data from Single-Cell Transcriptomic Analysis Identifies Senescent Osteocytes That Trigger Bone Destruction in Breast Cancer Metastasis
Authors: Kaur Japneet , Adhikari Manish , Sabol Hayley M. , Anloague Aric , Khan Sharmin , Kurihara Noriyoshi , Diaz-delCastillo Marta , Andreasen Christina Møller , Barnes Charles Lowry , Stambough Jeffrey B. , Palmieri Michela , Reyes-Castro Olivia , Zarrer Jennifer , Taipaleenmäki Hanna , Ambrogini Elena , Almeida Maria , O’Brien Charles A. , Nookaew Intawat , Delgado-Calle Jesus
Published: December 2024

Abstract
Breast cancer bone metastases increase fracture risk and are a major cause of morbidity and mortality among women. Upon colonization by tumor cells, the bone microenvironment undergoes profound reprogramming to support cancer progression, which disrupts the balance between osteoclasts and osteoblasts and leads to bone lesions. A deeper understanding of the processes mediating this reprogramming could help develop interventions for treating patients with bone metastases. Here, we demonstrated that osteocytes (Ot) in established breast cancer bone metastasis develop premature senescence and a distinctive senescence-associated secretory phenotype (SASP) that favors bone destruction. Single-cell RNA sequencing identified Ots from mice with breast cancer bone metastasis enriched in senescence, SASP markers, and pro-osteoclastogenic genes. Multiplex in situ hybridization and artificial intelligence–assisted analysis depicted Ots with senescence-associated satellite distension, telomere dysfunction, and p16Ink4a expression in mice and patients with breast cancer bone metastasis. Breast cancer cells promoted Ot senescence and enhanced their osteoclastogenic potential in in vitro and ex vivo organ cultures. Clearance of senescent cells with senolytics suppressed bone resorption and preserved bone mass in mice with breast cancer bone metastasis. These results demonstrate that Ots undergo pathological reprogramming by breast cancer cells and identify Ot senescence as an initiating event triggering lytic bone disease in breast cancer metastases.

Significance: Breast cancer cells remodel the bone microenvironment by promoting premature cellular senescence and SASP in osteocytes, which can be targeted with senolytics to alleviate bone loss induced by metastatic breast cancer.

See related commentary by Frieling and Lynch, p. 3917
A German’s Perspective on the Way toward Ambulatory Laparoscopic Cholecystectomy: A Postoperative Questionnaire
Authors: Weber Paul Leonard , Schürheck Konstantin , Wagner Kim C. , Köhler Nadine , Hiller Wolfgang , Oldhafer Karl J.
Published: November 2024

Introduction: Ambulatory surgeries are on the rise in recent years and can offer benefits to patients as well as healthcare providers. Laparoscopic cholecystectomy is one of the procedures commonly done in an ambulatory setting, in some European countries. This study aims to gather patients’ perceptions towards ambulatory cholecystectomy after undergoing laparoscopic cholecystectomy in an inpatient setting. Methods: A total of 300 patients from two different hospitals in Germany received a postoperative questionnaire aimed at evaluating their willingness to undergo an ambulatory surgery. Surgeries were performed between January 1, 2017, and July 11, 2018. Operation setting (acute vs. elective), ASA classification, length of hospital stay, age, sex, living situation and location (city vs. rural), as well as status of employment were documented. Results: Overall, 23% of patients reported considering ambulatory laparoscopic cholecystectomy (ALC), while 77% rejected an ALC. Objections included fear of complications (69%), anticipated pain (65%), concerns about their living situation/home care (21%), other reasons (8%), nausea and vomiting (3.4%). Baseline characteristics of the participants provided no statistical significance on willingness to undergo ALC: acute versus elective (p = 0.22), ASA classification (p = 0.77), age ≥65 years versus <65 years (p = 0.60), gender (p = 0.07), living situation (p = 0.49), location (p = 0.15). Conclusion: There is a willingness for ALC, albeit still limited. Chosen criteria did not show a significant association for positive perception of ALC.
Association of preoperative nutritional status with sarcopenia in patients with gastrointestinal malignancies assessed by GLIM criteria: a prospective cohort study
Authors: Xu Yeming , Zhao Yuqiu , Wang Jiali , Gao Shuyang , Sun Qiannan , Ali Muhammad , Hua Mingbo , Wang Tianxiu , Shi Na , Wang Daorong
Published: November 2024

Introduction: The Global Leadership Initiative in Malnutrition (GLIM) consensus highlights the importance of using the GLIM criteria as a standardized approach to diagnosing malnutrition, particularly in patients with cachexia. Although many existing studies have utilized the GLIM criteria to assess the association between malnutrition and malignant tumor patients, there remains relatively little research exploring the specific relationship between malnutrition and sarcopenia. This study aimed to investigate the correlation between malnutrition under the GLIM criteria and preoperative sarcopenia in patients with gastrointestinal malignancies. By looking into the relationship, we hope to find better ways to prevent and treat sarcopenia in these patients, which will lead to better clinical outcomes.
Methods: In this study, we selected 210 patients with gastrointestinal malignant tumors from Northern Jiangsu People’s Hospital between June 2022 to July 2023. We diagnosed and graded the nutritional status of these patients using the GLIM criteria. At the same time, body composition analysis, calf circumference, and grip strength were detected in all patients to observe whether they had sarcopenia.
Results: According to GLIM criteria, 30.1% of the patients were diagnosed with malnutrition, of which 25.1% were classified as moderate malnutrition and 15% as severe malnutrition. The risk of sarcopenia in patients with severe malnutrition was 2.5 times that of patients with good nutrition, and 1.19 times that of patients with moderate malnutrition. Patients with BMI <18.5 kg/m2 were 9.12 times more likely to develop sarcopenia than those with BMI≥18.5 kg/m2. Due to inadequate nutrient intake and resultant malnutrition in patients with malignant tumors, muscle protein synthesis is affected, exacerbating muscle protein breakdown and leading to an overall decline in muscle strength and function.
Conclusion: This study highlights the urgent need for nutritional screening in early gastrointestinal tumor patients, revealing a strong link between sarcopenia and malnutrition. Higher malnutrition levels, low BMI, and high nutritional risk significantly predict sarcopenia, with risk increasing alongside worsening malnutrition and disease stage.
How many people have a Huntington's Disease expansion: A population-based prevalence study in Northern Scotland
Authors: Cruickshank Heather , Miedzybrodzka Zosia
Published: November 2024

Background
Previous work demonstrated a prevalence of 14.6 per 100,000 manifest Huntington’s disease (HD) patients and 8.3 per 100,000 identified pre-symptomatic gene expansion carriers (IPGEC) in Northern Scotland. Many of those at high risk of having a huntingtin (HTT) gene expansion remain untested with the exact number being unknown.

Objectives
To estimate how many people in Northern Scotland are at 50% risk of having a HTT gene expansion to help with HD clinic service planning and to calculate how many people could access an effective treatment if available.

Methods
Clinical and pedigree records from the North of Scotland Genetic Clinic were examined to estimate numbers of manifest HD patients, IPGEC, and individuals at 50% risk.

Results
The prevalence of those at 50% risk living in Northern Scotland was 45.2 per 100,000 people. Every manifest HD patient in Northern Scotland has 4.4 relatives at 50% risk and every patient with a HTT gene expansion has 2.9 relatives at 50% risk. There are up to 415 (46.2 per 100,000) adults who could access an effective treatment if available, but this number is likely to be an underestimate as not all manifesting individuals seek diagnosis.

Conclusions
Despite high predictive testing rates, at least 2.2 adults are living with the HTT gene expansion for every one of the 14.5 per 100,000 manifest HD patients in Northern Scotland. Regional variation in rates and ascertainment need to be factored into future service planning, including: genetic counselling and testing, management, and treatment delivery.