bluuebunny/crossref_metadata_2025 huggingface dataset:
Kenaf/glass fiber‐reinforced polymer composites: Pioneering sustainable materials with enhanced mechanical and tribological properties
Authors: Supian A. B. M. , Asyraf M. R. M. , Syamsir Agusril , Ma Quanjin , Hazrati K. Z. , Azlin M. N. M. , Mubarak Ali M. , Ghani Aizat , Hua Lee Seng , SaifulAzry Syeed , Razman M. R. , Ramli Zuliskandar , Nurazzi N. M. , Norrrahim M. N. F. , Thiagamani Senthil Muthu Kumar
Published: July 2024

Hybrid kenaf/glass fiber reinforced polymer composites have emerged as promising structural materials, garnering significant attention due to their unique blend of natural kenaf fibers and synthetic glass fibers. However, despite their potential, there remains a gap in the comprehensive understanding of their quasi‐static mechanical behavior, creep resistance, and fatigue performance. This paper addresses this gap by presenting recent advancements in studying these key properties of hybrid composites. Studies reveal that the combination of kenaf and glass fibers results in enhanced tensile, flexural, and impact strengths compared to individual fiber composites. Additionally, the hybridization offers improved creep resistance, with the glass fibers reinforcing the polymer matrix against deformation under sustained loads. Furthermore, investigations into fatigue properties demonstrate the resilience of hybrid composites to cyclic loading, contributing to prolonged service life in high‐stress environments. By elucidating the interplay between kenaf and glass fibers, this review underscores the potential of hybrid composites in various structural applications. The synergistic effects between natural and synthetic fibers offer a balance between sustainability, performance, and durability, making hybrid kenaf/glass fiber reinforced polymer composites a compelling choice for industries seeking lightweight, high‐performance materials in which aligns with the sustainable development goals (SDGs) especially on Goal 12.

Highlights

In composite engineering, combining glass and kenaf fibers could cut production costs, yield high‐performance materials, and promote green technology.

Substituting part of the glass fiber with kenaf can enhance the strength‐to‐weight ratio and promote greater biodegradability in current synthetic composites.

Quasi‐mechanical properties of hybrid kenaf/glass‐based composites was enhanced by optimal stacking sequences, filler addition, and fiber treatment.

Failures due to fatigue and creep can be reduced by hybridizing kenaf/glass fiber composites can prevent in polymer composite due to enhance elastic modulus.

Enhanced tribological performance of hybrid kenaf/glass‐based composites due to less damage in microstructure via good interlocking of kenaf and glass in matrix.
Study of tensile‐tensile fatigue behavior of patch repaired carbon‐glass hybrid composite
Authors: Sahoo Chinmaya Kumar , Arockiarajan A.
Published: July 2024

Aside from the numerous benefits of fiber‐reinforced composites, these materials are prone to impact damage, reducing structure's strength and stiffness. In this case, composite repair offers a unique and cost‐effective alternative for restoring structural integrity. In this work, post‐repair performance of the carbon‐glass hybrid composite is investigated in tensile‐tensile fatigue loading environments. To analyze repair performance, two distinct parent configurations (H1:G2C4G2 and H2: C2G4C2) and four patch configurations (Repaired1: CG3, Repaired2: C2G2, and Repaired3: C3G, Repaired4: G4) are considered. The digital image correlation approach and acoustic emission sensors are used to examine the specimens' damage behavior. First, fatigue tests are performed for drilled specimens, the H2 specimen dissipate more energy during fatigue cycles than the drilled H1 specimen due to the early damage initiation in the H2 specimen. The repaired specimens with the parent H1 laminate performed better than the parent H2 laminate. The Repaired4 configuration with H1 parent laminate sustained 300% higher cycles than the drilled H1 without final failure, which showed the highest fatigue life among all the repaired configurations. Patches with fewer glass plies outperformed all hybrid patches. The damage events recorded by acoustic emission sensors indicate that delamination damage considerably impacts fatigue life.

Highlights

Post‐repair fatigue behavior of carbon‐glass hybrid composite was examined.

Effect of parent laminate stacking sequence and patch configuration was studied.

Fatigue performance was analyzed using the damage mode and energy loss factor.

Digital image correlation technique and acoustic emission sensors were utilized.

Delamination damage showed a higher impact on the fatigue life of the sample.
H2O2 Self‐Supplied Chemodynamic Nanosystem Enhanced by Ca2+ Interference and Starvation Strategy for Targeted Cancer Therapy
Authors: Shi Lei , Ma Yao‐Jia , Ren Xing‐Hui , Su Zheng‐Chen , He Xi‐Wen , Li Wen‐You , Zhang Yu‐Kui
Published: July 2024

Chemodynamic therapy (CDT) has received increasing attention in recent years due to its effectiveness and specificity. However, the limited endogenous hydrogen peroxide (H2O2) concentration and resistance to reactive oxygen species in cancer cells hinder the further application of CDT. Here, an H2O2 self‐supplied nanosystem FCaO2@ZIF‐67‐2‐DG‐FA (FZDF) is synthesized to achieve efficient CDT improvement by Ca2+ overload and starvation therapy. Under folic acid‐mediated tumor targeting and endocytosis, the ZIF‐67 layer of FZDF is cleaved in the mildly acidic environment, releasing Co2+ and 2‐deoxy‐D‐glucose (2‐DG). The decomposition of exposed FCaO2 generates sufficient H2O2, which further produces abundant •OH via the Fenton‐like reaction of Co2+. Simultaneously, Ca2+ overload‐triggered mitochondrial dysfunction couples with glycolysis inhibition via 2‐DG‐induced starvation, which disrupts intracellular adenosine triphosphate (ATP) synthesis and amplifies the efficacy of CDT. Silicon nanoparticles released from FCaO2 are applied as in vitro fluorescent probes to image tumor cells overexpressing folate receptors. The results have presented that FZDF can actively accumulate in tumor cells, causing the mitochondrial membrane potential abnormality and a decrease in intracellular ATP content, thereby enhancing the self‐supplied CDT with less effect on normal cells and tissues. This work provides a novel strategy for constructing effective CDT nanosystems by hindering intracellular energy supply.
Morphology Characterization and Refractive Index Analysis of Subsurface Ultrashort‐Pulsed Laser Modifications in ZnS
Authors: Einmo Eskil , Tolstik Nikolai , Grivas Christos , Demesh Maksim , Kontis Paraskevas , Sorokina Irina T. , Di Sabatino Marisa
Published: July 2024

A parameter study of ultrashort pulse laser‐induced modifications in the bulk of ZnS crystals is reported. Experimental results on these modifications and their dependence on the pulse energy, writing speed, and depth are presented, with an emphasis on cross‐sectional morphology and induced refractive index changes. Localized permanent material modifications have been inscribed in the bulk of the crystal using a laser with a center emission wavelength of 2.09 μm and a pulse duration of ≈4 ps. The morphology strongly depends on the laser and optical focusing parameters, in particular, on the pulse energy and processing speed, with a significant shift in depth dependence for short pulse‐to‐pulse separations. Depending on the applied pulse energy, distortions of the lateral profile of the refractive index changes appear in the form of oscillatory features in the transverse plane relative to the inducing laser beam. The true extent of the modified material is revealed by the alternating lateral profile with largest induced negative refractive index change, Δn, of −3.88 × 10−2 ± 0.18. Such parametric insight is of critical importance for the understanding and optimization of the fabrication process and for realizing compact 3D photonic devices in the bulk of materials in a reproducible manner.
Oedematous malnutrition among admitted low birth weight neonates receiving parenteral feeding in selected hospitals in Ethiopia
Authors: Mislu Esuyawkal , Terefe Abraraw
Published: July 2024

Background

Oedematous malnutrition is a severe form of malnutrition characterized by generalized swelling, fluid retention and nutritional deficiencies, which affects preterm and low‐birth‐weight (LBW) infants significantly. However, there is limited data among LBW neonates in low‐income countries.

Objective

To identify the prevalence and factors associated with oedematous malnutrition among LBW neonates receiving parenteral feeding in the neonatal intensive care unit (NICU) of public hospitals in Addis Ababa City.

Methods

An institution‐based cross‐sectional study was conducted from March to June 2022. A multistage sampling technique was utilized to select samples, and a pretested questionnaire and checklist were used to collect the data. Bi‐variable and multivariable logistic regression were done to identify factors associated with oedematous malnutrition. Statistical significance was declared at a p‐value less than 0.05.

Result

Two hundred eighty‐nine LBW neonates receiving parenteral feeding were evaluated for oedematous malnutrition, of which 27 (9.34%) neonates developed it. Gestational age less than 32 weeks (adjusted odd ratios [AOR]: 6.74 95% CI: 1.456−31.27) and above 37 weeks (AOR: 12.36 95% CI: 1.44−105.69), thrombocytopenia (AOR: 4.208 95% CI: 1.12−15.78), receiving parenteral feeding for 7−14 days (AOR: 8.61 95% CI: 1.33−55.52) and more than 14 days (AOR: 21.10 95% CI: 2.89−153.94) were significantly associated with oedematous malnutrition.

Conclusion

This study identified that a significant number of neonates developed oedematous malnutrition, and gestational age, thrombocytopenia and length of admission had a significant association with oedematous malnutrition among LBW neonates. It is crucial to reevaluate the quality of care in the NICU and implement an improvement project to decrease the length of parenteral feedings.
Breastfeeding mothers' awareness and experience of using the breastfeeding memory aide CHINS: An exploratory descriptive qualitative study
Authors: Shotton Lynette , Collins Tracy
Published: July 2024

Background

Breastfeeding has immediate and long‐term benefits for both mother and child, but many mothers feel unprepared for the challenges of early breastfeeding. The first letter mnemonic, close, head free, nose to nipllie, in‐line, sustainable (CHINS) was developed as a tool to help practitioners remember retain and recall the principles of positioning for effective breastfeeding and a UK‐wide evaluation shows it is used widely within the UK breastfeeding workforce. This study sought to understand the extent to which breastfeeding mothers were aware of CHINS and their experience of using it to support their breastfeeding.

Methods

An exploratory qualitative research design was used to describe and interpret the findings of individual interviews with 11 breastfeeding mothers from across the United Kingdom who were recruited via a digital flier shared via social media and breastfeeding networks. The interviews were analysed thematically.

Results

Awareness and perception of CHINS, Timing of introduction to CHINS, and Sharing CHINS were the key themes to emerge, with an overarching core theme—The Right Advice at the Right Time. All the participants in the study were aware of CHINS and found it particularly helpful during the early stages of breastfeeding. Some participants reported that others, including fathers and peers, were aware of CHINS and had used it to support breastfeeding mothers. The participants felt support for breastfeeding was variable and that it was important to ensure that the right advice was given at the right time.

Conclusion

This study included a small number of breastfeeding mothers from across the United Kingdom and whilst there were high levels of awareness and perceived value of CHINS, a larger study would be warranted to explore the value of CHINS in more depth as well as to understand the role of CHINS in the wider education of peers and significant others, including fathers.
Room temperature phosphorescence materials based on small organic molecules: Design strategies and applications
Authors: He Meixia , Ding Cong , Guo Hexiang , Li Quan
Published: July 2024

Room‐temperature phosphorescence (RTP) materials have attracted significant attention due to their applications in various fields such as information storage and encryption, organic light‐emitting diode (OLED), sensing, lighting and display, biological imaging, and photodynamic therapy. Traditionally, RTP materials can be efficiently developed using inorganic systems with noble metals or rare earth elements. Recently, many efforts have been devoted to the development of RTP materials based on small organic molecules. The strategies to construct RTP materials include hydrogen bonding, heavy atom effect, n–π* transitions, π–π stacking, donor–acceptor effect, and host–guest doping. Herein, we summarize the recent examples of RTP materials based on small organic molecules primarily focusing on their design strategies and properties. Moreover, their promising applications in information encryption, OLED, as well as bio‐imaging and phototherapy are discussed. The challenges and perspectives are given to provide inspiration toward the future development of organic RTP materials.
Psychopathology symptoms of frontline nurses under sudden public health crisis: A network analysis
Authors: Dong Mengyuan , Zhang Xuan , Cao Fenglin
Published: July 2024

Public health crises can significantly impact the emotional well‐being of healthcare workers. Network analysis is a novel approach to exploring interactions between mental disorders at the symptom level. This study aimed to elucidate the characteristics of post‐traumatic stress disorder (PTSD), anxiety, depression, and insomnia symptoms network among frontline nurses under sudden public health crisis. A cross‐sectional survey was conducted online among 556 frontline nurses through convenience sampling in Hubei Province, China, from 21 February 2020, to 10 March 2020. Symptoms of PTSD, anxiety, depression, and insomnia were assessed by the Post‐Traumatic Stress Disorder Checklist (PCL‐5), Generalized Anxiety Disorder scale (GAD‐7), Patient Health Questionnaire (PHQ‐9) and Insomnia Severity Index, respectively. Central symptoms (the most important symptoms, activation has the strongest influence the other nodes) and bridge symptoms (nodes where deactivation can prevent activation from spreading from one disorder to another) were identified via centrality and bridge centrality indices, respectively. Network stability was examined using the case‐dropping procedure. We found that the correlation between PHQ‐9 item 9 ‘suicidal thoughts’ and PCL‐5 item 16 ‘reckless or self‐destructive behaviour’ was the strongest. Moreover, ‘reckless or self‐destructive behaviour’ was the strongest central symptom, and PHQ‐9 item 3 ‘sleep problems’ was the most important bridge symptom. Other major symptoms included GAD‐7 item 6 ‘uncontrollable anxiety’ and PHQ‐9 item 2 ‘depressed or sad mood’. Timely, systemic targeting interventions on central symptoms and bridge symptoms may effectively alleviate co‐occurring experiences of psychopathological symptoms among frontline nurses.
Boron‐Doped Ti3C2Tx MXene for Effective and Durable High‐Current‐Density Ammonia Synthesis
Authors: Luo Xia , Wu Yeyu , Hu Huihui , Wei Tianran , Wu Baoshan , Ding Junyang , Liu Qian , Luo Jun , Liu Xijun
Published: July 2024

Ammonia (NH3) synthesis via the nitrate reduction reaction (NO3RR) offers a competitive strategy for nitrogen cycling and carbon neutrality; however, this is hindered by the poor NO3RR performance under high current density. Herein, it is shown that boron‐doped Ti3C2Tx MXene nanosheets can highly efficiently catalyze the conversion of NO3RR‐to‐NH3 at ambient conditions, showing a maximal NH3 Faradic efficiency of 91% with a peak yield rate of 26.2 mgh−1 mgcat.−1, and robust durability over ten consecutive cycles, all of them are comparable to the best‐reported results and exceed those of pristine Ti3C2Tx MXene. More importantly, when tested in a flow cell, the designed catalyst delivers a current density of ‒1000 mA cm−2 at a low potential of ‒1.18 V versus the reversible hydrogen electrode and maintains a high NH3 selectivity over a wide current density range. Besides, a Zn–nitrate battery with the catalyst as the cathode is assembled, which achieves a power density of 5.24 mW cm−2 and a yield rate of 1.15 mgh−1 mgcat.−1. Theoretical simulations further demonstrate that the boron dopants can optimize the adsorption and activation of NO3RR intermediates, and reduce the potential‐determining step barrier, thus leading to an enhanced NH3 selectivity.
Multi‐Component and Nanoporous Design toward RuO2‐Based Electrocatalyst with Enhanced Performance for Acidic Water Splitting
Authors: Wu Xin , Wu Jiashun , Hu Yixuan , Zhu Linshan , Cao Boxuan , Reddy Kolan Madhav , Wang Zhenbin , Qiu Hua‐Jun
Published: July 2024

Developing electrocatalysts with excellent activity and stability for water splitting in acidic media remains a formidable challenge due to the sluggish kinetics and severe dissolution. As a solution, a multi‐component doped RuO2 prepared through a process of dealloying‐annealing is presented. The resulting multi‐doped RuO2 possesses a nanoporous structure, ensuring a high utilization efficiency of Ru. Furthermore, the dopants can regulate the electronic structure, causing electron aggregation around unsaturated Ru sites, which mitigates Ru dissolution and significantly enhances the catalytic stability/activity. The representative catalyst (FeCoNiCrTi‐RuO2) shows an overpotential of 167 mV at 10 mA cm−2 for oxygen evolution reaction (OER) in 0.5 m H2SO4 solution with a Tafel slope of 53.1 mV dec−1, which is among the highest performance reported. Moreover, it remains stable for over 200 h at a current density of 10 mA cm−2. This work presents a promising approach for improving RuO2‐based electrocatalysts, offering a crucial advancement for electrochemical water splitting.
Hybrid Zwitterionic Hydrogels with Encoded Differential Swelling and Programmed Deformation for Small‐Scale Robotics
Authors: Bouzari Negin , Nasseri Rasool , Huang Junting , Ganguly Sayan , Tang Xiaowu (Shirley) , Mekonnen Tizazu H. , Aghakhani Amirreza , Shahsavan Hamed
Published: July 2024

Stimuli‐responsive shape‐morphing hydrogels with self‐healing and tunable physiochemical properties are excellent candidates for functional building blocks of untethered small‐scale soft robots. With mechanical properties similar to soft organs and tissues, such robots enable minimally invasive medical procedures, such as cargo/cell transportation. In this work, responsive hydrogels based on zwitterionic/acrylate chemistry with self‐healing and stimuli‐responsiveness are synthesized. Such hydrogels are then judiciously cut and pasted to form hybrid constructs with predetermined swelling and elastic anisotropy. This method is used to program hydrogel constructs with predetermined 2D‐to‐3D deformation upon exposure to different environmental ionic strengths. Untethered soft robotic functionalities are demonstrated, such as actuation, magnetic locomotion, and targeted transport of soft and light cargo in flooded media. The proposed hydrogel expands the repertoire of functional materials for fabricating small‐scale soft robots.
Risk Management Practices and the Performance of Indonesian and Malaysian Islamic Banks: Does Digitalization Mediate This Nexus?
Authors: Afgani Kurnia Fajar , Marzuki Marziana Madah , Majid Wan Zurina Nik Abdul , Nasser Siti Dalina Tumiran Kamal , Syukur Muhammad , Wiryono Sudarso Kaderi , Rahadi Raden Aswin , Boediman Alfred , Ali Qaisar
Published: July 2024

Despite being exceptionally regulated financial institutions, risk management practices (RMPs) of Islamic banking (IBs) have always remained under the limelight due to their impact on financial performance (FP) and the influence of digitalization (DT). This study aims to investigate the impact of RMPs on FP through the mediating effect of DT. To analyze the linkage between these constructs, we created an index for RMPs, five unique proxies (mobile [MB_DEA], big data [BD_DEA], Internet of Things [IoT], cloud computing [CC_DEA], and social media [SM_DEA]) of DT, and Tobin's Q as a proxy of FP and operationalized the theory of contingency. The data between 2009 and 2020 was collected from Indonesian and Malaysian IBs and was analyzed using the two‐step generalized method of moments (GMMs) technique. The empirical findings represent that RMPs and DT have a significant positive effect on FP. Simultaneously, RMPs have a significant positive effect on two proxies of DT (MB_DEA and SM_DEA), and an insignificant positive effect on the remaining three proxies of DT (BD_DEA, IoT_DEA, and CC_DEA). Simultaneously, DT as a mediator plays a significant role between RMPs and FP. This study contributes to systematizing the RMPs of IBs by integrating digitalization which eventually will increase the financial portfolios of IBs.
Opportunities and Challenges of Sustainable Innovation for Climate Change Mitigation in Companies: A Systematic Literature Review
Authors: Kraetzig Elda Rodrigues Steinhorst , Ávila Lucas Veiga , Sálvia Amanda Lange , Bichueti Roberto Schoproni , Brandli Luciana Londero
Published: July 2024

The escalating environmental degradation and tightening regulations worldwide since the 1990s have heightened environmental concerns among organizations, necessitating innovative and sustainable responses to climate change. This article aims to explore opportunities and challenges of sustainable innovations for mitigating climate change within companies. A systematic literature review was conducted, encompassing 42 articles from 2005 to 2022. Most studies originate from European countries, particularly from institutions like Sapienza University of Rome, Jinan University, and Amsterdam Business School. Notable authors include Rosa Maria Dangelico, Ans Kolk, and Jonatan Pinkse. The most cited journals include Business Strategy and the Environment, Journal of Cleaner Production, and Sustainability (MDPI). Identified opportunities for companies embracing climate change mitigation through innovation include enhanced image and competitiveness. Challenges comprise high implementation costs, ambiguous sustainable development guidelines, partnership scarcity, technological risk uncertainties, consumer acceptance concerns, deficient tools for low‐carbon product development, and the sociotechnical system's influence. Moreover, companies face hurdles like reliance on supply chain complementary capabilities and regulatory uncertainties. Future research should prioritize less costly sustainability practices and examine the sociotechnical factor's impact on sustainable innovation adoption. Prohibitive investment costs hinder companies from embracing these practices, highlighting the need for cost‐effective alternatives. Understanding the sociotechnical dynamic's role in driving or obstructing sustainable innovation adoption is crucial for comprehensive analysis and effective strategy development.
Nanozymes for biomedical applications: Multi‐metallic systems may improve activity but at the cost of higher toxicity?
Authors: Phan‐Xuan Thuong , Breitung Ben , Dailey Lea Ann
Published: July 2024

Nanozymes are nanomaterials with intrinsic enzyme‐like activity with selected advantages over native enzymes such as simple synthesis, controllable activity, high stability, and low cost. These materials have been explored as surrogates to natural enzymes in biosensing, therapeutics, environmental protection, and many other fields. Among different nanozymes classes, metal‐ and metal oxide‐based nanozymes are the most widely studied. In recent years, bi‐ and tri‐metallic nanomaterials have emerged often showing improved nanozyme activity, some of which even possess multifunctional enzyme‐like activity. Taking this concept even further, high‐entropy nanomaterials, that is, complex multicomponent alloys and ceramics like oxides, may potentially enhance activity even further. However, the addition of various elements to increase catalytic activity may come at the cost of increased toxicity. Since many nanozyme compositions are currently being explored for in vivo biomedical applications, such as cancer therapeutics, toxicity considerations in relation to nanozyme application in biomedicine are of vital importance for translation.

This article is categorized under:

Therapeutic Approaches and Drug Discovery > Emerging Technologies

Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials

Diagnostic Tools > Diagnostic Nanodevices
White‐Light‐Emitting Ln‐MOF as Luminescent Probe for Selective Detection of Nitroaromatic Compounds
Authors: Wang Yihui , Xiao Xitong , Liu Jiayi , Dong Zhenghong , Wang Fengqin , Wang Xiaoqing
Published: July 2024

Metal‐organic frameworks (MOFs) as an efficient and convenient sensing material for environmental pollutants have attracted widespread attention in recent years. Here in, we synthesized a series of lanthanide co‐doping MOFs, EuxTb1‐x‐MOFs (x=0, 0.005, 0.00667, 0.01, 0.02 and 1) under solvothermal conditions. The luminescence colors can be adjusted by changing metal molar mass ratios and altering excitation wavelength. Fortunately, a near white‐light‐emitting material Eu0.01Tb0.99‐MOF was obtained under the excitation at 350 nm, whose CIE coordinates of (0.3444, 0.3409) are very close to standard white light coordinates (0.3333, 0.3333). We further studied the fluorescence sensing performances of Eu‐MOF, Tb‐MOF and Eu0.01Tb0.99‐MOF towards NACs. The results indicate that all MOFs can selectively detect 4‐nitroaniline, 4‐nitrophenol and 2‐nitrophenol with good sensitivity and recyclability.
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks
Authors: Wu Haoze , Isac Omri , Zeljić Aleksandar , Tagomori Teruhiro , Daggitt Matthew , Kokke Wen , Refaeli Idan , Amir Guy , Julian Kyle , Bassan Shahaf , Huang Pei , Lahav Ori , Wu Min , Zhang Min , Komendantskaya Ekaterina , Katz Guy , Barrett Clark
Published: July 2024

This paper serves as a comprehensive system description of version 2.0 of the Marabou framework for formal analysis of neural networks. We discuss the tool’s architectural design and highlight the major features and components introduced since its initial release.
Enchanting Program Specification Synthesis by Large Language Models Using Static Analysis and Program Verification
Authors: Wen Cheng , Cao Jialun , Su Jie , Xu Zhiwu , Qin Shengchao , He Mengda , Li Haokun , Cheung Shing-Chi , Tian Cong
Published: July 2024

Formal verification provides a rigorous and systematic approach to ensure the correctness and reliability of software systems. Yet, constructing specifications for the full proof relies on domain expertise and non-trivial manpower. In view of such needs, an automated approach for specification synthesis is desired. While existing automated approaches are limited in their versatility,i.e., they either focus only on synthesizing loop invariants for numerical programs, or are tailored for specific types of programs or invariants. Programs involving multiple complicated data types (e.g., arrays, pointers) and code structures (e.g., nested loops, function calls) are often beyond their capabilities. To help bridge this gap, we presentAutoSpec, an automated approach to synthesize specifications for automated program verification. It overcomes the shortcomings of existing work in specification versatility, synthesizing satisfiable and adequate specifications for full proof. It is driven by static analysis and program verification, and is empowered by large language models (LLMs).AutoSpecaddresses the practical challenges in three ways: (1) drivingAutoSpecby static analysis and program verification, LLMs serve as generators to generate candidate specifications, (2) programs are decomposed to direct the attention of LLMs, and (3) candidate specifications are validated in each round to avoid error accumulation during the interaction with LLMs. In this way,AutoSpeccan incrementally and iteratively generate satisfiable and adequate specifications. The evaluation shows its effectiveness and usefulness, as it outperforms existing works by successfully verifying 79% of programs through automatic specification synthesis, a significant improvement of 1.592x. It can also be successfully applied to verify the programs in a real-world X509-parser project.
Verifying Global Two-Safety Properties in Neural Networks with Confidence
Authors: Athavale Anagha , Bartocci Ezio , Christakis Maria , Maffei Matteo , Nickovic Dejan , Weissenbacher Georg
Published: July 2024

We present the first automated verification technique for confidence-based 2-safety properties, such as global robustness and global fairness, in deep neural networks (DNNs). Our approach combines self-composition to leverage existing reachability analysis techniques and a novel abstraction of the softmax function, which is amenable to automated verification. We characterize and prove the soundness of our static analysis technique. Furthermore, we implement it on top of Marabou, a safety analysis tool for neural networks, conducting a performance evaluation on several publicly available benchmarks for DNN verification.
General Anticipatory Runtime Verification
Authors: Hipler Raik , Kallwies Hannes , Leucker Martin , Sánchez César
Published: July 2024

Runtime verification is a technique for monitoring a system’s behavior against a formal specification. Monitors must produce verdicts that are sound with respect to the specification. Anticipation is the ability to immediately produce verdicts when the monitor can confidently predict the inevitability of the verdict.

Stream runtime verification is a specialized form of runtime verification tailored to the monitoring and verification of data streams. In this paper we study anticipatory monitoring for stream runtime verification. More specifically, we present an algorithm with anticipation for monitoring of Lola specifications, which we then extend to exploit assumptions and tolerate uncertainties. As perfect anticipation is in general not computable, we use techniques from abstract interpretation, especially widening, to approximate anticipatory monitoring verdicts. Finally, we report on three empirical cases studies using a prototype implementation of a symbolic instantiation of our approach.
Proactive Real-Time First-Order Enforcement
Authors: Hublet François , Lima Leonardo , Basin David , Krstić Srđan , Traytel Dmitriy
Published: July 2024

Modern software systems must comply with increasingly complex regulations in domains ranging from industrial automation to data protection. Runtime enforcement addresses this challenge by empowering systems to not only observe, but also actively control, the behavior of target systems by modifying their actions to ensure policy compliance. We propose a novel approach to the proactive real-time enforcement of policies expressed in metric first-order temporal logic (MFOTL). We introduce a new system model, define an expressive MFOTL fragment that is enforceable in that model, and develop a sound enforcement algorithm for this fragment. We implement this algorithm in a tool calledWhyEnfand carry out a case study on enforcing GDPR-related policies. Our tool can enforce all policies from the study in real-time with modest overhead. Our work thus provides the first tool-supported approach that can proactively enforce expressive first-order policies in real time.
Predictive Monitoring with Strong Trace Prefixes
Authors: Ang Zhendong , Mathur Umang
Published: July 2024

Runtime predictive analyses enhance coverage of traditional dynamic analyses based bug detection techniques by identifying a space of feasible reorderings of the observed execution and determining if any reordering in this space witnesses the violation of some desired safety property. The most popular approach for modelling the space of feasible reorderings is through Mazurkiewicz’s trace equivalence. The simplicity of the framework also gives rise to efficient predictive analyses, and has been the de facto means for obtaining space and time efficient algorithms for monitoring concurrent programs.

In this work, we investigate how to enhance the predictive power of trace-based reasoning, while still retaining the algorithmic benefits it offers. Towards this, we extend trace theory by naturally embedding a class of prefixes, which we call strong trace prefixes. We formally characterize strong trace prefixes using an enhanced dependence relation, study its predictive power and establish a tight connection to the previously proposed notion of synchronization-preserving correct reorderings developed in the context of data race and deadlock prediction. We then show that despite the enhanced predictive power, strong trace prefixes continue to enjoy the algorithmic benefits of Mazurkiewicz traces in the context of prediction against co-safety properties, and derive new algorithms for synchronization-preserving data races and deadlocks with better asymptotic space and time usage. We also show that strong trace prefixes can capture more violations of pattern languages. We implement our proposed algorithms and our evaluation confirms the practical utility of reasoning based on strong prefix traces.
Wilson loops and random matrices
Authors: Bergner Georg , Gautam Vaibhav , Hanada Masanori , Holden Jack
Published: July 2024

Abstract

Linear confinement with Casimir scaling of the string tension in confining gauge theories is a consequence of a certain property of the Polyakov loop related to random matrices. This mechanism does not depend on the details of the theories (neither the gauge group nor dimensions) and explains approximate Casimir scaling below string-breaking length. In this paper, we study 3d SU(2) pure Yang-Mills theory numerically and find the same random-matrix behavior for rectangular Wilson loops. We conjecture that this is a universal feature of strongly coupled confining gauge theories.
Weak Hopf symmetry and tube algebra of the generalized multifusion string-net model
Authors: Jia Zhian , Tan Sheng , Kaszlikowski Dagomir
Published: July 2024

Abstract

We investigate the multifusion generalization of string-net ground states and lattice Hamiltonians, delving into their associated weak Hopf symmetries. For the multifusion string-net, the gauge symmetry manifests as a general weak Hopf algebra, leading to a reducible vacuum string label; the charge symmetry, serving as a quantum double of gauge symmetry, constitutes a connected weak Hopf algebra. This implies that the associated topological phase retains its characterization by a unitary modular tensor category (UMTC). The bulk charge symmetry can also be captured by a weak Hopf tube algebra. We offer an explicit construction of the weak Hopf tube algebra structure and thoroughly discuss its properties. The gapped boundary and domain wall models are extensively discussed, with these 1d phases characterized by unitary multifusion categories (UMFCs). We delve into the gauge and charge symmetries of these 1d phases, as well as the construction of the boundary and domain wall tube algebras. Additionally, we illustrate that the domain wall tube algebra can be regarded as a cross product of two boundary tube algebras. As an application of our model, we elucidate how to interpret the defective string-net as a restricted multifusion string-net.
Lattice QCD calculation of the pion distribution amplitude with domain wall fermions at physical pion mass
Authors: Baker Ethan , Bollweg Dennis , Boyle Peter , Cloët Ian , Gao Xiang , Mukherjee Swagato , Petreczky Peter , Zhang Rui , Zhao Yong
Published: July 2024

Abstract

We present a direct lattice QCD calculation of the x-dependence of the pion distribution amplitude (DA), which is performed using the quasi-DA in large momentum effective theory on a domain-wall fermion ensemble at physical quark masses and spacing a ≈ 0.084 fm. The bare quais-DA matrix elements are renormalized in the hybrid scheme and matched to $$ \overline{\textrm{MS}} $$

MS
¯

with a subtraction of the leading renormalon in the Wilson-line mass. For the first time, we include threshold resummation in the perturbative matching onto the light-cone DA, which resums the large logarithms in the soft gluon limit at next-to-next-to-leading log. The resummed results show controlled scale-variation uncertainty within the range of momentum fraction x ∈ [0.25, 0.75] at the largest pion momentum Pz ≈ 1.85 GeV. In addition, we apply the same analysis to quasi-DAs from a highly-improved-staggered-quark ensemble at physical pion mass and a = 0.076 fm. By comparison we find with 2σ confidence level that the DA obtained from chiral fermions is flatter and lower near x = 0.5.
Dynamic modelling and efficiency prediction for forging operations under a screw press
Authors: Song Heyu , Durand Camille , Baudouin Cyrille , Bigot Régis
Published: July 2024

Accurate predictions concerning a forging process can be obtained by numerical simulation, but only with a thorough knowledge of the main process variables. The material flow behavior and the interface effects are already well studied in the literature, but not the machine behavior, although it is required to estimate blow efficiency and deduce the energy actually transmitted to the workpiece. In this paper, an experimental methodology was applied to determine a spring-mass-damping model and its associated parameters for a screw press. The model and its parameters were identified with press strikes performed without billet. For validation, simulations were performed to predict blows on copper billets. The model’s predictions were in good agreement with the experimental measurements for ten consecutive blows on a copper billet. The decrease of process efficiency and the evolution from inelastic blows to elastic blows were correctly depicted by the model.
Socio-demographic determinants of myelofibrosis outcomes in an underserved center and the SEER national database
Authors: Yan John , Hammami M. Bakri , Wei John X. , Shah Nishi , Goldfinger Mendel , Mantzaris Ioannis , Kornblum Noah , Gritsman Kira , Sica Alejandro , Cooper Dennis , Feldman Eric , Konopleva Marina , Pradhan Kith , Thakur Rahul , Vegivinti Charan , Qasim Asma , Verma Amit , Goel Swati
Published: July 2024

The influence of demographic characteristics and social determinants on cancer outcomes is widely recognized in various malignancies but remains understudied in myelofibrosis (MF). This study aims to investigate social and demographic variables associated with MF survival. We retrospectively reviewed data of biopsy-proven MF patients from the Surveillance, Epidemiology and End Results (SEER) database (2000–2021) and Montefiore Medical Center (2000–2023), an underserved inner-city hospital. The SEER cohort included 5,403 MF patients and was predominantly Non-Hispanic (NH) White (82%) with a median age of 69 years. The age-adjusted incidence rate of MF was 0.32 cases per 100,000 person-years, increasing annually by 1.3% from 2000 to 2021. Two- and five- year overall survival rates were 69% and 42%, respectively. Worse cause-specific survival was associated with older age, male sex, and diagnosis before 2011 (year of Ruxolitinib approval). NH-Black ethnicity, unmarried status and lower median income were independent predictors of worse overall survival. The single-center analysis included 84 cases, with a median age of 66 years. NH-White patients comprised 37% of the sample, followed by NH-Black (28.5%). Two- and five- year overall survival rates were 90% and 61%, respectively, with NH-Black patients exhibiting the lowest median survival, although the difference was not statistically significant. Age was a significant predictor of worse survival in this cohort. NH-Black and Hispanic patients lived in areas with higher socioeconomic and demographic stress compared to NH-White patients. Overall, this study highlights the association of social and demographic factors with MF survival and emphasizes the need for equitable healthcare and further exploration of social-demographic factors affecting MF survival.
Physical Zero-Knowledge Proof Protocols for Topswops and Botdrops
Authors: Komano Yuichi , Mizuki Takaaki
Published: July 2024

Suppose that a sequence of $${\varvec{n}}$$

n

cards, numbered 1 to $${\varvec{n}}$$

n

, is placed face up in random order. Let $${\varvec{k}}$$

k

be the number on the first card in the sequence. Then take the first $${\varvec{k}}$$

k

cards from the sequence, rearrange that subsequence of $${\varvec{k}}$$

k

cards in reverse order, and return them to the original sequence. Repeat this prefix reversal until the number on the first card in the sequence becomes 1. This is a one-player card game called Topswops. The computational complexity of Topswops has not been thoroughly investigated. For example, letting $${\varvec{f}}({\varvec{n}})$$

f

(

n

)

denote the maximum number of prefix reversals for Topswops with $${\varvec{n}}$$

n

cards, values of $${\varvec{f}}({\varvec{n}})$$

f

(

n

)

for $${\varvec{n}}\ge 20$$

n

≥
20

remain unknown. In general, there is no known efficient algorithm for finding an initial sequence of $${\varvec{n}}$$

n

cards that requires exactly $$\ell $$
ℓ
prefix reversals for any integers $${\varvec{n}}$$

n

and $${\varvec{\ell }}$$

ℓ

. In this paper, using a deck of cards, we propose a physical zero-knowledge proof protocol that allows a prover to convince a verifier that the prover knows an initial sequence of $${\varvec{n}}$$

n

cards that requires $${\varvec{\ell }}$$

ℓ

prefix reversals without leaking knowledge of that sequence. We also deal with Botdrops, a variant of Topswops.
Is the third molar the most frequently extracted tooth? A population-based study utilizing dental panoramic radiographs in adults
Authors: Ventä Irja , Snäll Johanna , Rice David P , Suominen Anna Liisa
Published: July 2024

Objectives

The study aimed to examine the authenticity of the often-mentioned statement that the third molar is the most frequently extracted tooth. This finding has not been shown previously in a large population-based sample.

Materials and methods

Data comprised a nationally representative sample of 6082 panoramic radiographs taken from adults in the cross-sectional Health 2000 Survey. From the radiographs, all missing teeth were recorded. Information on congenital agenesis of individual teeth was retrieved from two published meta-analyses. Primary outcome was the frequency of missing teeth by tooth type. Explanatory variables were age, sex, and the jaw (maxilla/mandible). Statistical analyses included χ2 test and binomial logistic regression.

Results

Mean age of participants (46% men, 54% women) was 53 years (SD 14.6; range 30‒97 years). Missing teeth occurred more often in women than in men (P < 0.001). The third molar was most frequently missing and the canine least frequently. In the maxilla and mandible, the third molar was missing more often than each of the other tooth types up to the age of 80 years (P < 0.01).

Conclusions

When considering the rates of congenital agenesis of individual teeth, it is concluded that the third molar remained the most common tooth extracted up till the age of 80 years.

Clinical relevance

The third molar is the most common target for extraction, but also the most common tooth associated with malpractice claims, and therefore, calls for skills, adequate equipment, and other resources for a successful extraction.
Retrospective assessment of ICD-10/DSM-5 criteria of childhood ADHD from descriptions of academic and social behaviors in German primary school reports
Authors: Waltereit Johanna , Schulte-Rüther Martin , Roessner Veit , Waltereit Robert
Published: July 2024

Background

The diagnosis of attention-deficit/hyperactivity disorder (ADHD) in adolescence and adulthood is particularly challenging because retrospective confirmation of previous childhood ADHD is mandatory. Therefore, collecting valid diagnostic information about behavior at school is important. Primary school reports often contain descriptions of academic performance and social behaviors associated with ADHD criteria. Yet, there is no systematic approach available how to assess such reports quantitatively, and therefore, there is also no study on how valid such an approach could predict an ADHD diagnosis.

Methods

We examined primary school reports from Germany (ADHD: n = 1197, typically developing controls: n = 656) for semantic references to ICD-10/DSM-5 main and sub-criteria of ADHD. Descriptions were assessed on a quantitative scale (blinded clinical expert rating) for disorder-associated behaviors (symptoms scale) as well as for desired, adaptive behaviors (competencies scale) according to these criteria. The scores of these developed scales have been summarized to summary scores. Scores were analyzed using linear mixed models, and sensitivity and specificity were estimated using receiver operating characteristics (ROC).

Results

Ratings showed highly significant differences between school reports of children with and without ADHD. For the summary scores, both symptoms and competencies scales showed high diagnostic accuracy (ROC area under the curve at least 0.96) with best discrimination when combining both into an integrated index (sensitivity and specificity > 0.97).

Conclusions

Our findings suggest that systematic quantitative analysis of primary school reports should be further explored to construct a valid instrument for retrospective assessment of childhood ADHD criteria to aid the diagnostic process in adolescents and adults.
RadImageNet and ImageNet as Datasets for Transfer Learning in the Assessment of Dental Radiographs: A Comparative Study
Authors: Okazaki Shota , Mine Yuichi , Yoshimi Yuki , Iwamoto Yuko , Ito Shota , Peng Tzu-Yu , Nishimura Taku , Suehiro Tomoya , Koizumi Yuma , Nomura Ryota , Tanimoto Kotaro , Kakimoto Naoya , Murayama Takeshi
Published: July 2024

Transfer learning (TL) is an alternative approach to the full training of deep learning (DL) models from scratch and can transfer knowledge gained from large-scale data to solve different problems. ImageNet, which is a publicly available large-scale dataset, is a commonly used dataset for TL-based image analysis; many studies have applied pre-trained models from ImageNet to clinical prediction tasks and have reported promising results. However, some have questioned the effectiveness of using ImageNet, which consists solely of natural images, for medical image analysis. The aim of this study was to evaluate whether pre-trained models using RadImageNet, which is a large-scale medical image dataset, could achieve superior performance in classification tasks in dental imaging modalities compared with ImageNet pre-trained models. To evaluate the classification performance of RadImageNet and ImageNet pre-trained models for TL, two dental imaging datasets were used. The tasks were (1) classifying the presence or absence of supernumerary teeth from a dataset of panoramic radiographs and (2) classifying sex from a dataset of lateral cephalometric radiographs. Performance was evaluated by comparing the area under the curve (AUC). On the panoramic radiograph dataset, the RadImageNet models gave average AUCs of 0.68 ± 0.15 (p < 0.01), and the ImageNet models had values of 0.74 ± 0.19. In contrast, on the lateral cephalometric dataset, the RadImageNet models demonstrated average AUCs of 0.76 ± 0.09, and the ImageNet models achieved values of 0.75 ± 0.17. The difference in performance between RadImageNet and ImageNet models in TL depends on the dental image dataset used.