bluuebunny/crossref_metadata_2025 huggingface dataset:
Practical Verification of Smart Contracts using Memory Splitting
Authors: Grossman Shelly , Toman John , Bakst Alexander , Arora Sameer , Sagiv Mooly , Nandi Chandrakana
Published: October 2024

SMT-based verification of low-level code requires modeling and reasoning about memory operations. Prior work has shown that optimizing memory representations is beneficial for scaling verification—pointer analysis, for example can be used to split memory into disjoint regions leading to faster SMT solving. However, these techniques are mostly designed for C and C++ programs with explicit operations for memory allocation which are not present in all languages. For instance, on the Ethereum virtual machine, memory is simply a monolithic array of bytes which can be freely accessed by Ethereum bytecode, and there is no allocation primitive.

In this paper, we present a memory splitting transformation guided by a conservative memory analysis for Ethereum bytecode generated by the Solidity compiler. The analysis consists of two phases: recovering memory allocation and memory regions, followed by a pointer analysis. The goal of the analysis is to enable memory splitting which in turn speeds up verification. We implemented both the analysis and the memory splitting transformation as part of a verification tool, CertoraProver, and show that the transformation speeds up SMT solving by up to 120x and additionally mitigates 16 timeouts when used on 229 real-world smart contract verification tasks.
When Your Infrastructure Is a Buggy Program: Understanding Faults in Infrastructure as Code Ecosystems
Authors: Drosos Georgios-Petros , Sotiropoulos Thodoris , Alexopoulos Georgios , Mitropoulos Dimitris , Su Zhendong
Published: October 2024

Modern applications have become increasingly complex and their manual installation and configuration is

no longer practical. Instead, IT organizations heavily rely on Infrastructure as Code (IaC) technologies, to automate the provisioning, configuration, and maintenance of computing infrastructures and systems. IaC systems typically offer declarative, domain-specific languages (DSLs) that allow system administrators and developers to write high-level programs that specify the desired state of their infrastructure in a reliable, predictable, and documented fashion. Just like traditional programs, IaC software is not immune to faults, with issues ranging from deployment failures to critical misconfigurations that often impact production systems used by millions of end users. Surprisingly, despite its crucial role in global infrastructure management, the tooling and techniques for ensuring IaC reliability still have room for improvement.

In this work, we conduct a comprehensive analysis of 360 bugs identified in IaC software within prominent IaC ecosystems including Ansible, Puppet, and Chef. Our work is the first in-depth exploration of bug characteristics in these widely-used IaC environments. Through our analysis we aim to understand: (1) how these bugs manifest, (2) their underlying root causes, (3) their reproduction requirements in terms of system state (e.g., operating system versions) or input characteristics, and (4) how these bugs are fixed. Based on our findings, we evaluate the state-of-the-art techniques for IaC reliability, identify their limitations, and provide a set of recommendations for future research. We believe that our study helps researchers to (1) better understand the complexity and peculiarities of IaC software, and (2) develop advanced tooling for more reliable and robust system configurations.
A Case for First-Class Environments
Authors: Tan Jinhao , Oliveira Bruno C. d. S.
Published: October 2024

Formalizations of programming languages typically adopt the

substitution model from the lambda calculus. However, substitution

creates notorious complications for reasoning and implementation. Furthermore,

it is disconnected from practical implementations, which normally adopt

environments and closures.

In this paper we advocate for formalizing programming languages using

a novel style of
small-step environment-based semantics
, which avoids

substitution and is closer to implementations.

We present a call-by-value statically typed calculus, called λ
E
, using

our small-step environment semantics. With our

alternative environment semantics

programming language constructs for
first-class environments
arise naturally, without creating significant additional

complexity. Therefore, λ
E
also adopts first-class environments,

adding expressive power that is not available in conventional lambda

calculi. λ
E
is a conservative

extension of the call-by-value Simply Typed Lambda Calculus (STLC),

and employs de Bruijn indices for its formalization, which fit

naturally with the environment-based semantics.

Reasoning about λ
E
is simple, and in many cases

simpler than reasoning about the traditional STLC. We show an abstract

machine that implements the semantics of λ
E
, and has an easy

correctness proof. We also extend λ
E
with references. We show that

λ
E
can model a simple form of first-class modules, and suggest using first-class

environments as an alternative to objects for modelling capabilities.

All technical results are formalized in the Coq proof assistant. In summary, our work shows that the small-step environment semantics that we adopt has three main and orthogonal benefits: 1) it simplifies the notorious binding problem in

formalizations and proof assistants; 2) it is closer to implementations;

and 3) additional

expressive power is obtained from first-class environments almost for free.
Automated Robustness Verification of Concurrent Data Structure Libraries against Relaxed Memory Models
Authors: Nagar Kartik , Sahoo Anmol , Chowdhury Romit Roy , Jagannathan Suresh
Published: October 2024

Clients reason about the behavior of concurrent data structure libraries such as sets, queues, or stacks using specifications that capture well-understood correctness conditions, such as linearizability. The implementation of these libraries, however, focused as they are on performance, may additionally exploit relaxed memory behavior allowed by the language or underlying hardware that weaken the strong ordering and visibility constraints on shared-memory accesses that would otherwise be imposed by a sequentially consistent (SC) memory model. As an alternative to developing new specification and verification mechanisms for reasoning about libraries under relaxed memory model, we instead consider the orthogonal problem of
library robustness
, a property that holds when all possible behaviors of a library implementation under relaxed memory model are also possible under SC. In this paper, we develop a new
automated
technique for verifying robustness of library implementations in the context of a C11-style memory model. This task is challenging because a most-general client may invoke an unbounded number of concurrently executing library operations that can manipulate an unbounded number of shared locations. We establish a novel inductive technique for verifying library robustness that leverages prior work on the robustness problem for the C11 memory model based on the search for a non-robustness witness under SC executions. We crucially rely on the fact that this search is carried out over SC executions, and use high-level SC specifications (including linearizability) of the library to verify the absence of a non-robustness witness. Our technique is compositional - we show how we can safely preserve robustness of multiple interacting library implementations and clients using additional SC fences to guarantee robustness of entire executions. Experimental results on a number of complex realistic library implementations demonstrate the feasibility of our approach.
The ART of Sharing Points-to Analysis: Reusing Points-to Analysis Results Safely and Efficiently
Authors: Halalingaiah Shashin , Sundaresan Vijay , Maier Daryl , Nandivada V. Krishna
Published: October 2024

Data-flow analyses like points-to analysis can vastly improve the precision of other analyses, and enable powerful code optimizations. However, whole-program points-to analysis of large Java programs tends to be expensive – both in terms of time and memory. Consequently, many compilers (both static and JIT) and program-analysis tools tend to employ faster – but more conservative – points-to analyses to improve usability. As an alternative to such trading of precision for performance, various techniques have been proposed to perform precise yet expensive fixed-point points-to analyses ahead of time in a static analyzer, store the results, and then transmit them to independent compilation/program-analysis stages that may need them. However, an underlying concern of safety affects all such techniques – can a compiler (or program analysis tool) trust the points-to analysis results generated by another compiler/tool?

In this work, we address this issue of trust in the context of Java, while accounting for the issue of performance. We propose ART: Analysis-results Representation Template – a novel scheme to efficiently and concisely encode results of flow-sensitive, context-insensitive points-to analysis computed by a static analyzer for use in any independent system that may benefit from such a precise points-to analysis. ART also allows for fast regeneration of the encoded sound analysis results in such systems. Our scheme has two components: (i) a producer that can statically perform expensive points-to analysis and encode the same concisely, (ii) a consumer that, on receiving such encoded results (called artwork), can regenerate the points-to analysis results encoded by the artwork if it is deemed “safe”. The regeneration scheme completely avoids fixed-point computations and thus can help consumers like static analyzers and JIT compilers to obtain precise points-to information without paying a prohibitively high cost. We demonstrate the usage of ART by implementing a producer (in Soot) and two consumers (in Soot and the Eclipse OpenJ9 JIT compiler). We have evaluated our implementation over various benchmarks from the DaCapo and SPECjvm2008 suites. Our results demonstrate that using ART, a consumer can obtain precise flow-sensitive, context-insensitive points-to analysis results in less than (average) 1% of the time taken by a static analyzer to perform the same analysis, with the storage overhead of ART representing a small fraction of the program size (average around 4%).
HierGP: Hierarchical Grid Partitioning for Scalable Geospatial Data Analytics
Authors: Oje Olufunso , Stirewalt Tashi , Amram Ofer , Hystad Perry , Amiri Solmaz , Gebremedhin Assefaw
Published: October 2024

Application domains such as environmental health science, climate science, and geosciences—where the relationship between humans and the environment is studied—are constantly evolving and require innovative approaches in geospatial data analysis. Recent technological advancements have led to the proliferation of high-granularity geospatial data, enabling such domains but posing major challenges in managing vast datasets that have high spatiotemporal similarities. We introduce the Hierarchical Grid Partitioning (HierGP) framework to address this issue. Unlike conventional discrete global grid systems, HierGP dynamically adapts to the data’s inherent characteristics. At the core of our framework is the Map Point Reduction (MPR) algorithm, designed to aggregate and then collapse data points based on user-defined similarity criteria. This effectively reduces data volume while preserving essential information. The reduction process is particularly effective in handling environmental data from extensive geographical regions. We structure the data into a multilevel hierarchy from which a reduced representative dataset can be extracted. We compare the performance of HierGP against several state-of-the-art geospatial indexing algorithms and demonstrate that HierGP outperforms the existing approaches in terms of runtime, memory footprint, and scalability. We illustrate the benefits of the HierGP approach using two representative applications: analysis of over 289 million location samples from a registry of participants and efficient extraction of environmental data from large polygons. While the application demonstration in this work has focused on environmental health, the methodology of the HierGP framework can be extended to explore diverse geospatial analytics domains.
Cooperative Advisory Residual Policies for Congestion Mitigation
Authors: Hasan Aamir , Chakraborty Neeloy , Chen Haonan , Cho Jung-Hoon , Wu Cathy , Driggs-Campbell Katherine
Published: October 2024

Fleets of autonomous vehicles can mitigate traffic congestion through simple actions, thus improving many socioeconomic factors such as commute times and gas costs. However, these approaches are limited in practice as they assume precise control over autonomous vehicle fleets, incur extensive installation costs for a centralized sensor ecosystem, and fail to account for uncertainty in driver behavior. To this end, we develop a class of learned residual policies that can be used in cooperative advisory systems and only require the use of a single vehicle with a human driver. Our policies advise drivers to behave in ways that mitigate traffic congestion while accounting for diverse driver behaviors, particularly drivers’ reactions to instructions, to provide an improved user experience. To realize such policies, we introduce an improved reward function that explicitly addresses congestion mitigation and driver attitudes to advice. We show that our residual policies can be personalized by conditioning them on an inferred driver trait that is learned in an unsupervised manner with a variational autoencoder. Our policies are trained in simulation with our novel instruction adherence driver model and evaluated in simulation and through a user study (N = 16) to capture the sentiments of human drivers. Our results show that our approaches successfully mitigate congestion while adapting to different driver behaviors, with up to 20% and 40% improvement as measured by a combination metric of speed and deviations in speed across time over baselines in our simulation tests and user study, respectively. Our user study further shows that our policies are human-compatible and personalized to drivers.
Formal Security Analysis of the OpenID FAPI 2.0 Family of Protocols: Accompanying a Standardization Process
Authors: Hosseyni Pedram , Küsters Ralf , Würtele Tim
Published: October 2024

FAPI 2.0 is a suite of Web protocols developed by the OpenID Foundation’s FAPI Working Group (FAPI WG) for third-party data sharing and digital identity in high-risk environments. Even though the specifications are not completely finished, several important entities have started to adopt the FAPI 2.0 protocols, including Norway’s national HelseID, Australia’s Consumer Data Standards, as well as private companies like Authlete and Australia-based connectID; the predecessor FAPI 1.0 is in widespread use with millions of users.

The FAPI WG asked us to accompany the standardization of the FAPI 2.0 protocols with a formal security analysis to proactively identify vulnerabilities before widespread deployment and to provide formal security guarantees for the standards. In this paper, we report on our analysis and findings.

Our analysis is based on a detailed model of the Web infrastructure, the so-called Web Infrastructure Model (WIM), which we extend to be able to carry out our analysis of the FAPI 2.0 protocols including important extensions like FAPI-CIBA. Based on the (extended) WIM and formalizations of the security goals and attacker model laid out in the FAPI 2.0 specifications, we provide a formal model of the protocols and carry out a formal security analysis, revealing several attacks. We have worked with the FAPI WG to fix the protocols, resulting in several amendments to the specifications. With these changes in place, we have adjusted our protocol model and formally proved that the security properties hold true under the strong attacker model defined by the FAPI WG.
A Proof of the Nisan-Ronen Conjecture --- An Overview
Authors: Christodoulou George , Koutsoupias Elias , Kovacs Annamaria
Published: October 2024

This note presents an overview of our recent publication, which validates a conjecture proposed by Nisan and Ronen in their seminal paper [Nisan and Ronen 2001]. We show that the optimal approximation ratio for deterministic truthful mechanisms for makespan-minimization by a set of
n
unrelated machines is
n.
Welfare-Maximizing Pooled Testing
Authors: Finster Simon , Amador Michelle González , Lock Edwin , Marmolejo-Cossío Francisco , Micha Evi , Procaccia Ariel D.
Published: October 2024

This letter provides an overview of our recent work on COVID-19 testing mechanisms that appeared at EC'23. Large-scale testing is crucial in pandemics but resources are often prohibitively constrained. We study a scenario in which a population under lockdown utilizes a limited budget of tests to allow healthy individuals to resume in-person activities. Our work explores the optimal allocation of pooled tests in populations that are heterogeneous with respect to individual infection probabilities and utilities that materialize if included in a negative test (and being permitted to resume in-person activities). Non-overlapping allocations of tests, where no individual in the population is included in more than one pooled test, are both conceptually and logistically simpler to implement. We show that the welfare gain from overlapping testing over non-overlapping testing is bounded. Moreover, we design a heuristic mechanism for finding test allocations that is fast and empirically near-optimal. We also implement our mechanism in practice and provide experimental evidence on the benefits of utility-weighted pooled testing in a real-world setting. Our randomized trial at a higher education research institute in Mexico suggests that performance and mental health outcomes of participants under our testing mechanism are no worse than under the counterfactual of full access for individuals without testing.
Generative AI as Economic Agents
Authors: Immorlica Nicole , Lucier Brendan , Slivkins Aleksandrs
Published: October 2024

Traditionally, AI has been modeled within economics as a technology that impacts payoffs by reducing costs or refining information for human agents. Our position is that, in light of recent advances in generative AI, it is increasingly useful to model AI itself as an economic agent. In our framework, each user is augmented with an AI agent and can consult the AI prior to taking actions in a game. The AI agent and the user have potentially different information and preferences over the communication, which can result in equilibria that are qualitatively different than in settings without AI.
VQEG Column: VQEG Meeting December 2022
Authors: Gutiérrez Jesús , Brunnström Kjell
Published: October 2024

This column provides an overview of the last Video Quality Experts Group (VQEG) plenary meeting, which took place from 12 to 16 December 2022. Around 100 participants from 21 different countries around the world registered for the meeting that was organized online by Brightcove (United Kingdom). During the five days, there were more than 40 presentations and discussions among researchers working on topics related to the projects ongoing within VQEG. All the related information, minutes, and files from the meeting are available online on the VQEG meeting website, and video recordings of the meeting are available on Youtube.
Harmonizing Multisource Data to Inform Vector-Borne Disease Risk Management Strategies
Authors: Lowe Rachel , Codeço Claudia Torres
Published: October 2024

In the last few decades, we have witnessed the emergence of new vector-borne diseases (VBDs), the globalization of endemic VBDs, and the urbanization of previously rural VBDs. Data harmonization forms the basis of robust decision-support systems designed to protect at-risk communities from VBD threats. Strong interdisciplinary partnerships, protocols, digital infrastructure, and capacity-building initiatives are essential for facilitating the coproduction of robust multisource data sets. This review provides a foundation for researchers and practitioners embarking on data harmonization efforts to (a) better understand the links among environmental degradation, climate change, socioeconomic inequalities, and VBD risk; (b) conduct risk assessments, health impact attribution, and projection studies; and (c) develop robust early warning and response systems. We draw upon best practices in harmonizing data for two well-studied VBDs, dengue and malaria, and provide recommendations for the evolution of research and digital technology to improve data harmonization for VBD risk management.
How Do People Feel About Mates?
Authors: Eastwick Paul W. , Joel Samantha
Published: October 2024

Where do positive feelings about a romantic or sexual partner come from? This article offers an overview of—and imposes some structure on—the enormous literature on mate evaluation, from initial attraction to long-term relationship settings. First, we differentiate between research that identifies the factors that predict positive evaluation on average (i.e., normative desirability) and research that attempts to document for whom certain factors are more versus less positive (i.e., heterogeneity in desirability). Second, we review the positive biases that tend to dominate the evaluative process, as well as the promising (and sorely needed) new methods in this research space. Third, we cover contemporary perspectives on the mechanisms that explain how evaluations shift and change over the entire relationship arc. Fourth and finally, we discuss how diversifying the samples and perspectives in mate evaluation research will address novel and generative questions about culture, stigma, and socioeconomic status.
MRI-based Zero Echo Time and Black Bone Pseudo-CT Compared with Whole-Body CT to Detect Osteolytic Lesions in Multiple Myeloma
Authors: Lecouvet Frederic E. , Zan Deniz , Lepot Darius , Chabot Caroline , Vekemans Marie-Christiane , Duchêne Gaëtan , Chiabai Ophélye , Triqueneaux Perrine , Kirchgesner Thomas , Taihi Lokmane , Poujol Julie , Gheysens Olivier , Michoux Nicolas
Published: October 2024

Both zero echo time and black bone pseudo-CT MRI sequences had high diagnostic accuracy in detecting osteolytic myeloma lesions; black bone outperformed zero echo time in the spine.
Retrieval-Augmented Generation for Large Language Models in Radiology: Another Leap Forward in Board Examination Performance
Authors: Bhayana Rajesh , Fawzy Aly , Deng Yangqing , Bleakney Robert R. , Krishna Satheesh
Published: October 2024

Perplexity (Perplexity AI), which uses web-based retrieval-augmented generation (RAG) and prioritizes authoritative sources, with GPT-4 Turbo (OpenAI) outperformed default GPT-4 Turbo on a radiology board–style examination, illustrating the utility of RAG optimization to generate radiology answers.
Assessing Benthic Recovery Below the United Kingdom’s First Large‐Scale, Offshore, Longline Mussel Farm
Authors: Mascorda-Cabre Llucia , Hosegood Phil , Attrill Martin J. , Sheehan Emma V.
Published: October 2024

The recent expansion of the aquaculture industry into the offshore marine environment is perceived to have a comparatively low environmental impact coupled with a high growth potential as a sustainable, large‐scale source of healthy protein. This study assessed changes in sediment characteristics and infauna assemblages following the development of the first large‐scale offshore longline mussel farm in the United Kingdom. By evaluating the effects of the farm on the sediment ecosystem and by studying infaunal sediment environmental parameters along a distance gradient away from the farm, the first before–after control–impact (BACI) study of an offshore shellfish farm is presented. Sediment grabs from the farm and control sites were analysed for sediment parameters (organic matter content (OM), particle size (PS), oxidation–reduction or redox potential (ORP) and trace elements) and infauna assemblages. There was no difference in sediment organic matter levels between the farm and control sites. Within the farm, the mean sediment grain size and ORP increased over time. Trace element concentrations were the lowest within farm sites compared to outside; concentrations increased with increasing distance from the farm. A total of 76 benthic macrofauna taxa were identified, with polychaetes being the dominant class. Over time, the number of taxa significantly increased within the farm while remaining relatively constant in control samples. Biodiversity metrics, including abundance and Shannon and Pielou’s index, were all greater within the farm compared to control areas. Overall, measures of assemblage health were higher within the farm than outside. This study demonstrates the long‐term aquaculture–environment interactions that offshore shellfish farming can have on the seabed and its significance in terms of ecosystem services.
Evaluation of Type III Adhesive Mortar (ACIII) and Gypsum as Precipitating Agents of Copper and Lead
Authors: Marinho Jefferson Luiz Alves , Coutinho Henrique Douglas Melo , Teixeira Raimundo Nonato Pereira , Menezes Jorge Marcell Coelho , Filho Francisco José de Paula , Cunha Francisco Assis Bezerra da
Published: October 2024

Heavy metals exhibit characteristics such as nonbiodegradable nature, toxic character, bioaccumulation capability, and ability to transit over long distances. The widespread application of these metal ions in various industrial sectors has led to an increase in their release into the environment. Chemical precipitation has been one of the technologies used to remove heavy metals from wastewater, involving a process in which chemical agents are added to wastewater with dissolved toxic metal ions, which react with the metals, forming insoluble precipitates. Therefore, the present study aimed to assess the potential of gypsum and adhesive mortar type III (ACIII) as precipitating agents for lead (Pb) and copper (Cu) ions, as well as to evaluate the toxicity of precipitation products on Drosophila melanogaster. Experiments using ACIII mortar waste as a precipitating agent for Cu ions were obtained using a glass filter composed of 04 chambers and 04 antechambers, while the potential of gypsum as a Pb ion precipitant was evaluated by adding gypsum powder to a beaker containing a Pb ions solution. The toxicity of the precipitation products was evaluated by observing the mortality and negative geotaxis parameters on D. melanogaster. In the tests using ACIII mortar as a precipitating agent for Cu, retention percentages progressively varied, obtaining 98.82% at a concentration of 30 mg/L. Meanwhile, gypsum obtained retention percentages that varied from 32.83 to 98.61% for Pb. It was found that the precipitates of Cu and Pb resulted in alterations in the survival and locomotion rates of D. melanogaster only at the highest evaluated concentrations. In conclusion, the results obtained indicated that geomaterials such as ACIII mortar and gypsum have potential for the removal of Cu and Pb from aqueous solutions. Moreover, the precipitation stages by these materials also impact in decreasing the toxicity of metal ions to the evaluated model organism.
Optimizing Bacterial Cellulose Production From Kombucha Tea Utilizing Molasses and Tea Dust in Growth Medium
Authors: Selvaraj Suriyapriya , Gurumurthy Kalaichelvan
Published: October 2024

Kombucha, a potentially probiotic beverage renowned for its health benefits, was brewed using sweetened tea and a microbial consortium known as symbiotic culture of bacteria and yeast (SCOBY). This study is aimed at optimizing SCOBY production media using economical substrates through the Taguchi method of response surface methodology (RSM). Kombucha production was optimized for SCOBY yield by utilizing tea dust as a nitrogen source instead of tea leaves and blackstrap molasses as a carbon source. The cost per liter of the optimized medium was reduced to $0.027 (optimized) from $0.075 (unoptimized). The SCOBY yield was higher in the optimized condition (2.56%) compared to the control (2.44%) by Day 10. Optimal conditions for maximal SCOBY yield (2.56%) included 75 g/L molasses, 10 g/L tea dust, 20 g/L SCOBY seeding, pH 5, and an incubation temperature of 30°C. The growth rate (μ) of SCOBY was marginally higher in the test sample (1.142 kg/day) compared to the control (1.136 kg/day). The cost difference in SCOBY production between control and test samples was 97.8%, considering current raw material prices. Utilizing cost‐effective substrates, bacterial cellulose from kombucha fermentation could be feasibly commercialized within a short timeframe.
A Method of Constructing Superpotentials by Combining Two Functions Based on Shape Invariance
Authors: Qiu Wenxin , Yin Yin , Cheng Wei , Liu Yao , Luo Guang
Published: October 2024

Supersymmetric quantum mechanics (SUSYQM) plays an important role in solving the Schrödinger equation, and it is also important to find more superpotentials that can be solved accurately. On the basis of studying the characteristics of existing superpotentials, the authors find a missing superpotential and put forward a method by combining two functions to construct all existing solvable superpotentials and prove the existence of the missing superpotential. First, based on the idea of SUSYQM, this paper studies the shape invariance of the partner potentials with the form of two functions and obtains the energy spectrum in many different cases. Second, according to the results of solving differential equations satisfied by two functions, the authors not only construct most existing solvable superpotentials successfully but also generate a missing solvable superpotential. Third, for the missing solvable superpotential, some discussions are made, such as the corresponding partner potentials, energy spectrum, ground state wave function, and excited state wave functions. Lastly, the summary is made, and the prospects are projected.
Effectiveness of Educational and Psychoeducational Self‐Management Interventions in Children and Adolescents With Type 1 Diabetes: A Systematic Review and Meta‐Analysis
Authors: Cockcroft Emma. J. , Clarke Ross , Dias Renuka. P. , Lloyd Jenny , Mann Robert H. , Narendran Parth , Reburn Charlotte , Smith Ben , Smith Jane R. , Andrews Robert. C.
Published: October 2024

Aim: Type 1 diabetes (T1D) is one of the most common chronic conditions in children and adolescents. Approximately 1.5 million young people are currently living with T1D throughout the world. Despite recent improvement in overall indices of metabolic control in children and adolescents with T1D, control remains suboptimal and additional approaches are needed. The aim of the study was to conduct a systematic review and meta‐analysis of educational and psychoeducational self‐management interventions, to help optimize future interventions including physical activity support.

Methods: A systematic review and meta‐analysis were conducted according to our registered protocol (PROSPERO CRD42022295932) and are reported in line with the PRISMA 2020 guidance. We searched five databases (MEDLINE, EMBASE, PsycINFO [via Ovid], CINAHL [via EBSCO], Cochrane Library) from 1994 up to May 2024. We included randomized controlled trials assessing the effectiveness of self‐management interventions. Outcomes of interest included HbA1c and quality of life (QoL) as well as self‐care behaviors, diabetes knowledge, and self‐efficacy. Meta‐analyses were conducted using a random effects model.

Results: In total, 46 papers were included, reporting on 30 interventions. Meta‐analyses showed small short‐term improvements in HbA1c (MD = −2.58 mmol/L, 95% CI −4.44 to −0.71, p = 0.007) and QoL (mean difference [MD] = 1.37, 95% CI 0.19–2.54, p = 0.02). Prespecified subgroup analyses suggested no significant difference in effectiveness of psychoeducational and education‐only interventions. Quality of included studies was low with 27 having a high risk of bias.

Conclusion: There is a lack of robust evidence that current self‐management interventions result in clinically meaningful improvements in HbA1c and QoL. Future research should focus on redefining approaches to supporting and encouraging self‐management.
The Road Ahead: Emerging Trends, Unresolved Issues, and Concluding Remarks in Generative AI—A Comprehensive Review
Authors: S. Balasubramaniam , Chirchi Vanajaroselin , Kadry Seifedine , Agoramoorthy Moorthy , P. Gururama Senthilvel , K. Satheesh Kumar , T. A. Sivakumar
Published: October 2024

The field of generative artificial intelligence (AI) is experiencing rapid advancements, impacting a multitude of sectors, from computer vision to healthcare. This paper provides a comprehensive review of generative AI’s evolution, significance, and applications, including the foundational architectures such as generative adversarial networks (GANs), variational autoencoders (VAEs), autoregressive models, flow‐based models, and diffusion models. We delve into the impact of generative algorithms on computer vision, natural language processing, artistic creation, and healthcare, demonstrating their revolutionary potential in data augmentation, text and speech synthesis, and medical image interpretation. While the transformative capabilities of generative AI are acknowledged, the paper also examines ethical concerns, most notably the advent of deepfakes, calling for the development of robust detection frameworks and responsible use guidelines. As generative AI continues to evolve, driven by advances in neural network architectures and deep learning methodologies, this paper provides a holistic overview of the current landscape and a roadmap for future research and ethical considerations in generative AI.
Complex Anterior Supralevator Anal Fistula With Prostatic Abscess Treated With Ksharasutra: A Case Report
Authors: Bhat Punchoor Ramesh , T. A. Vipin
Published: October 2024

Anorectal diseases are a major health threat in the field of health sciences. Fistula‐in‐ano is one of the treatable complex benign lesions of the rectum and anal canal. Complex high anal fistulas can reoccur even after surgical treatment. Establishing a cure for cryptoglandular fistula‐in‐ano is problematic, as a significant percentage of these diseases persist or recur if the internal opening of the anal fistula is left untreated. Here, we report a case of complex left anterolateral supralevator anal fistula with communication to the prostate gland that forms a prostatic abscess, as it is very rare. After following Ksharasutra (Ayurvedic medicated seton) treatment with regular wound care, significant regression in the condition was observed. A follow‐up scan showed no evidence of fistula‐in‐ano. A 50‐year‐old businessman presented with complaints of discomfort deep inside the rectum and perineum associated with pain at the base of the scrotum and pus discharge from the perianal region for 1 year. He was diagnosed to have a complex left anterolateral supralevator anal fistula with communication to the prostate substance after a thorough clinical examination and transrectal ultrasonography. After undergoing Ksharasutra treatment for 4 months, pus discharge completely stopped, and sonofistulogram report showed no evidence of fistula‐in‐ano. Images of the sonofistulogram report were documented before and after the treatment. This article highlights the unique feature of Ksharasutra therapy where the fistula extending to the prostate was treated with no loss of function of the anal sphincter.
A Novel Approach to Discriminate Between Structural and Non‐Structural Post‐Earthquake Damage in RC Structures
Authors: Gultekin Beyza , Dogan Gamze
Published: October 2024

In post‐earthquake damage assessment studies of reinforced concrete (RC) buildings, the most important consideration is to determine the damage and severity of structural elements is the determination of the damage and severity of structural elements. For earthquake damage to structural elements, such as columns and shear walls, decisions can be made about strengthening or demolition. However, due to the need for rapid assessment of damaged buildings after earthquakes, these two damage mechanisms can sometimes be confused. Non‐structural damage is classified as structural, leading to uneconomic structural decisions such as demolition or strengthening, or conversely, life safety issues arise from misidentifying critical structural damage with non‐structural damage. In this study, an artificial intelligence‐based damage assessment algorithm has been developed to accurately and quickly differentiate between structural and non‐structural damage. For the damage classification model, a deep learning algorithm was developed using the 9680 damage images obtained from field studies after the recent earthquakes of Mw ≥ 5; Istanbul‐Silivri (Mw: 5.8), Elazığ‐Sivrice (Mw: 6.8) and Izmir‐Seferihisar (Mw: 6.6) in Turkey. With an accuracy rate between 93% and 96%, the models constructed by selecting the optimal values correctly detected and categorised structural and non‐structural element damages in RC structures. The method developed in this study can help experts in damage assessment studies as a decision support mechanism.
Diagnostic Panel of Three Genetic Biomarkers Based on Artificial Neural Network for Patients With Idiopathic Generalized Epilepsy
Authors: Yabacı Tak Ayşegül , Tak Nihat , Ilgen Uslu Ferda , Yucesan Emrah
Published: October 2024

The aim of this study is to evaluate the utility of an artificial neural network (ANN) model in diagnosing idiopathic generalized epilepsy (IGE) and to compare the results of the diagnostic model constructed by combining the expression levels of miR‐146a, miR‐155, and miR‐132 genes using ANN, random forest (RF), and discriminant analysis (DA). qRT‐PCR is employed to determine the expression levels of the three miRNA genes. Forty‐six IGE patients and 51 healthy controls were included in the study. Three genetic biomarkers were employed to assess the discriminative power of the disease, and they were combined using ANN. Additionally, the performance of ANN was compared with RF and DA. Compared to healthy controls, the miR‐132 gene was significantly higher (p < 0.001) and the miR‐155 and miR‐146a genes were significantly lower in IGE patients (p < 0.001). The area under the curve (AUC) for predictions made by the ANN, RF, and DA were 0.96, 0.87, and 0.75, respectively, with accuracy rates of 0.96, 0.88, and 0.76, respectively. We demonstrate that ANN exhibits the highest accuracy, AUC, sensitivity, and specificity values among the three methods. The obtained results indicate that the combination of the three genes used as markers in IGE plays a significant role in the diagnosis of the disease. Instead of assessing biomarkers individually for the disease, combining them using machine learning methods leads to improved model performance. Additionally, not relying on a single genetic biomarker for the disease enables discrimination based on the collective impact of all biomarkers.
Analysis of Food Safety Import Notifications and Relevant Standards and Regulations for Aquaculture Products With a Focus on Antimicrobial Residues and Use
Authors: Allegra S. , Loi G. , Garrido Gamarro E.
Published: October 2024

The use of antimicrobials is essential for the aquaculture sector; however, their misuse is cause for concern because it could adversely affect the environment and human health. Irresponsible use of antimicrobials can lead to antimicrobial resistance and result in the presence of unwanted residues in aquaculture products. The establishment of maximum residue limits (MRLs) for antimicrobials is of great importance for monitoring their correct use, but the lack of harmonized standards as well as the regulatory gaps for the aquatic products create a challenging situation, as it is reflected in import notifications related to food safety. This paper collects information about current MRLs for antimicrobials in aquatic commodities in the main importing and exporting countries of aquatic products and compares them with each other and with MRLs set by Codex Alimentarius. This analysis highlighted the need for Codex Alimentarius guidance regarding MRLs for nine antimicrobials in aquaculture products (chlortetracycline, doxycycline, enrofloxacin, erythromycin, florfenicol, sulfadimethoxine + ormetoprim, sulfamerazine, tetracycline, and trimethoprim). This paper shows that there is still work to do to implement exhaustive science‐based international standards for residues permitted in aquatic commodities and promote harmonization.
Targeting Matrix Metalloproteinase‐3 for Dental Caries Prevention Using Herbal Isolates: MMP3 Inhibition by Cinnamic Acids
Authors: Salman Mahdieh , Asgartooran Bahareh , Taherkhani Amir
Published: October 2024

Objectives: Dental caries, a prevalent infectious disease affecting teeth, ranks highest among 328 diseases, according to a 2017 Lancet study. In demineralized human dentin, matrix metalloproteinase‐3 (MMP3) functions as a proteoglycanase, contributing to the degradation of proteoglycan components. This process exposes collagen fibrils, thereby facilitating the demineralization of the dentin matrix. Inhibiting MMP3 shows potential for preventing dental caries.

Methods: The binding affinity of 20 cinnamic acid derivatives, namely cynarin, chlorogenic acid, rosmarinic acid, cinnamyl caffeate, phenethyl caffeate, N‐p‐coumaroyltyramine, caffeic acid 3‐glucoside, caffeic acid phenethyl ester, roscovitine, benzyl caffeate, o‐coumaric acid, artepillin C, caffeic acid, methyl caffeate, 2‐methylcinnamic acid, ferulic acid, drupanin, p‐coumaric acid, cinnamic acid, and sinapinic acid, to the MMP3 catalytic cleft, was assessed utilizing AutoDock 4.0. Molecular dynamics simulation was then employed to analyze the stability of backbone atoms in free MMP3, MMP3‐positive control inhibitor, and MMP3 complexed with the top‐ranked cinnamic acid over a 100 ns computer simulation.

Results: Four cinnamic acids demonstrated ΔGbinding scores below −10 kcal/mol, with cynarin emerging as the most potent MMP3 inhibitor, featuring a ΔGbinding score and inhibition constant value of −15.57 kcal/mol and 3.83 pM, respectively. The MMP3–cynarin complex exhibited stability after a 50 ns computer simulation, showing a root‐mean‐square deviation of 8 Å.

Conclusions: The inhibition of MMP3 by cynarin, chlorogenic acid, rosmarinic acid, and cinnamyl caffeate holds promise as a potential preventive strategy for dental caries.
Complement Factor H Is an ICOS Ligand Modulating Tregs in the Glioma Microenvironment
Authors: Smolag Karolina I. , Olszowka Jakub , Rosberg Rebecca , Johansson Elinn , Marinko Elisabet , Leandersson Karin , O’Connell David J. , Governa Valeria , Tuysuz Emre Can , Belting Mattias , Pietras Alexander , Martin Myriam , Blom Anna M.
Published: October 2024

The survival rate of patients with glioma has not significantly increased in recent years despite aggressive treatment and advances in immunotherapy. The limited response to treatments is partially attributed to the immunosuppressive tumor microenvironment, in which regulatory T cells (Treg) play a pivotal role in immunologic tolerance. In this study, we investigated the impact of complement factor H (FH) on Tregs within the glioma microenvironment and found that FH is an ICOS ligand. The binding of FH to this immune checkpoint molecule promoted the survival and function of Tregs and induced the secretion of TGFβ and IL10 while suppressing T-cell proliferation. We further demonstrated that cancer cells in human and mouse gliomas directly produce FH. Database investigations revealed that upregulation of FH expression was associated with the presence of Tregs and correlated with worse prognosis for patients with glioma. We confirmed the effect of FH on glioma development in a mouse model, in which FH knockdown was associated with a decrease in the number of ICOS+ Tregs and demonstrated a tendency of prolonged survival (P = 0.064). Because the accumulation of Tregs represents a promising prognostic and therapeutic target, evaluating FH expression should be considered when assessing the effectiveness of and resistance to immunotherapies against glioma.
Figure S4 from Antiangiogenic Tyrosine Kinase Inhibitors have Differential Efficacy in Clear Cell Renal Cell Carcinoma in Bone
Authors: Maksimovic Stefan , Boscolo Nina C. , La Posta Ludovica , Barrios Sergio , Moussa Mohammad Jad , Gentile Emanuela , Pesquera Pedro I. , Li Wenjiao , Chen Jianfeng , Gomez Javier A. , Basi Akshay , Burks Jared K. , Alvarez-Breckenridge Christopher , Gao Jianjun , Campbell Matthew T. , Dondossola Eleonora
Published: October 2024

Effects of TKIs on blood vessels in RENCA VHL- bone and lung tumors. A) Visual representation of the experimental approach. B,C) Bone tumors: representative pictures captured at the confocal microscope and quantification of blood vessel area in tumor (green, GFP), nuclei (blue, DAPI); blood vessels (yellow, endomucin; red, laminin); dotted line, tumor edge; single channel endomucin is shown. A quantification of % blood vessels on tumor area is shown, mean + SEM, n=3-4/group; Bar, 100 µm. D,E) Lung tumors: representative pictures captured at the confocal microscope and quantification (C) of blood vessel area in tumor (green, GFP), nuclei (blue, DAPI); blood vessels (red, CD31); dotted line, tumor edge; single channel CD31 is shown. A quantification of % blood vessels on tumor area is shown, mean + SEM, n=3-4/group; Bar, 100 µm P values by one-way ANOVA with Tukey’s HSD post hoc test; p < 0.05 = *, p < 0.01 = **. BV- blood vessels. Endo-endomucin; Lam-laminin; BV-blood vessels; V-vehicle, A-axitinib, C-cabozantinib, L-lenvatinib;
Figure 2 from Antiangiogenic Tyrosine Kinase Inhibitors have Differential Efficacy in Clear Cell Renal Cell Carcinoma in Bone
Authors: Maksimovic Stefan , Boscolo Nina C. , La Posta Ludovica , Barrios Sergio , Moussa Mohammad Jad , Gentile Emanuela , Pesquera Pedro I. , Li Wenjiao , Chen Jianfeng , Gomez Javier A. , Basi Akshay , Burks Jared K. , Alvarez-Breckenridge Christopher , Gao Jianjun , Campbell Matthew T. , Dondossola Eleonora
Published: October 2024

Efficacy of TKIs on tumor growth, in vitro and in vivo. A, Dose–response curve of axitinib, cabozantinib, and lenvatinib treatment of UM-RC-3 and RENCA VHL−, mean + SD, n = 5/group; control, 0 mmol/L TKIs, 1% DMSO; IC50 values of cell viability are reported. B, Experimental design and timeline of treatment schedule. C and D, Response to TKIs by UM-RC-3 (C) and RENCA VHL− (D) tumor cells in tibiae at day 11 of treatment; representative bioluminescence images and quantification are shown, mean ± SEM, n = 16 tibiae/group. E, Response of tumor cells in lungs to TKIs at day 11 of treatment; representative bioluminescence images and quantification are shown, mean ± SEM, n = 8/group. F, Stereomicroscope images of lungs (brightfield and GFP–green); Bar, 1 cm. P values by one-way ANOVA with Tukey honestly significant difference post hoc test; *, P < 0.05; **, P < 0.01; ***, P < 0.001. Axi, axitinib; Cabo, cabozantinib; Conc, concentration; Lenv, lenvatinib; Veh, vehicle.