bluuebunny/crossref_metadata_2025 huggingface dataset:
Adherence to tuberculosis (TB) treatment in high compared to low TB burden countries: study protocol for a systematic review and meta-analysis with a qualitative meta-synthesis of themes
Authors: Eyawo Oghenowede , Lyzwinski Lynnette Nathalie , Ugoji Uchechukwu Chidiebere , Pan Shenyi , Sorkpor Setor Kofi , Tawari-Fufeyin Prekeyi , Hogg Robert S
Published: January 2025

Introduction

Non-adherence to tuberculosis (TB) treatment poses a significant challenge to effective TB management globally and is a major contributor to the emergence of multidrug-resistant TB. Although adherence to TB treatment has been widely studied, a comprehensive evaluation of the comparative levels of adherence in high- versus low-TB burden settings remains lacking. The objective of this systematic review and meta-analysis is to assess the levels of adherence to TB treatment in high-TB burden countries compared to low-burden countries. Additionally, it seeks to identify the unique facilitators and barriers to treatment adherence in these distinct settings.

Methods and analysis

This systematic review and meta-analysis will be conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols Statement. Using key medical subject heading terms and free-text terms related to TB treatment adherence, a systematic search of the literature will be performed in Medline, Embase, CINAHL, Scopus, Global Health and the Cochrane Databases of Systematic Reviews. A medical librarian will assist with developing the search strategy. Two independent reviewers will independently screen studies against predefined inclusion and exclusion criteria at both the title/abstract and full-text stages. Working in duplicate, the same two reviewers will independently extract relevant study and outcomes data, including study descriptors, TB burden, adherence levels and adherence measures, from eligible studies. Countries will be classified according to TB burden based on the WHO’s high-burden country list from the post-2015 era (2015–2025). The quality of the included studies will be appraised using the Cochrane Risk of Bias tool and the Newcastle-Ottawa Scale. Qualitative data will be appraised using the Critical Appraisal Skills Programme tool. Studies will be pooled using the DerSimonian-Laird random-effects meta-analysis. Additionally, a meta-synthesis of the qualitative data from the included studies may be conducted to identify emergent themes related to facilitators and barriers of TB treatment adherence in high- vs low-TB burden countries.

Ethics and dissemination

Ethics approval is not required for this study as it does not involve the recruitment or collection of data from participants. The findings from this systematic review and meta-analysis will be disseminated through publication in peer-reviewed journals, presentations at scientific conferences, and via social media channels to enhance visibility, particularly within programmatic and policy spheres.

PROSPERO registration number

CRD42021273336
Introducing and establishing birth companionship in labour ward of a tertiary care centre in North India: a quality improvement journey through and beyond COVID-19 pandemic
Authors: Singh Meenakshi , Puri Manju , Bessy Saji , Ranvir Singh Geeta , George Susan , Singh Abha , Yadav Reena
Published: January 2025

Background

Allowing a birth companion is the basic right of a mother and is identified as an important component of respectful maternity care. The implementation of this intervention has been a challenge in heavy-load public health facilities in India.

Local problem

Despite the proven benefits of the presence of birth companions on maternal–fetal outcomes, there was no policy of allowing birth companions in our hospital.

Methods and interventions

We aimed to introduce and establish the practice of allowing birth companions for all eligible mothers admitted to the labour ward from 0% to 70% in 8 weeks duration. The study was conducted in the Department of Obstetrics and Gynecology, Lady Hardinge Medical College and Smt. Sucheta Kriplani Hospital, New Delhi. A quality improvement (QI) team was formed. After collecting the baseline data and observing the process flow, fishbone analysis was done to identify the main problems. Various change ideas were listed and tested in the form of plan-do-study-act (PDSA) cycles and ideas were either adapted or adopted. Simple interventions such as antenatal sensitisation and counselling of the mother and the family, WhatsApp groups, and monthly labour room induction classes for residents helped achieve the target. During COVID-19 pandemic, the practice of allowing birth companions was suspended temporarily but was rolled out again after the second wave of COVID-19 in COVID-19-negative and COVID-19 suspect labour wards.

Results

The median value of the percentage of mothers accompanied by birth companions marginally increased to 20% after the first PDSA cycle. Finally, after multiple PDSA cycles, we could achieve our goal in 8 weeks. During a pandemic, the project was suspended temporarily during the first two waves but was revived again and we succeeded in reaching the desired goal and sustaining the policy after fewer PDSA cycles compared with the first phase.

Conclusion

The application of QI methodology and teamwork is pivotal in implementing any novel idea for patient care without additional infrastructure, manpower or financial resources.
Effects of medication procurement reforms and extended prescription duration on medication coverage for hypertension in India’s public health system: a modelling study
Authors: Marklund Matti , Mattingly T Joseph , Sahoo Swagata Kumar , Kaur Prabhdeep , Moran Andrew E , Appel Lawrence J , Matsushita Kunihiro
Published: January 2025

Objectives

To estimate the effects of procurement reforms and extended prescription duration on medication coverage for hypertension in India’s public health system.

Design

Simulation study incorporating data from governmental medication price lists, prescription pattern analyses, and market sales surveys.

Setting

Simulated hypothetical public healthcare facility in India treating 1000 patients with hypertension.

Participants

Patients with medication-treated hypertension.

Interventions

(1) Focused procurement by reducing antihypertensive medication classes from 5 to 3 and selecting one medication within class; (2) Increased use of single-pill combinations (SPC) and (3) Only SPC dispensation. The base scenario consisted of procurement of multiple medications across classes, 1-month prescription duration and no use of SPC. We repeated all scenarios with extended prescription duration (3 months vs 1 month).

Main outcome measures

Medication coverage is defined as the maximum number of patients with adequate medication without exceeding the base scenario budget.

Results

With 1-month prescriptions, focused procurement alone was estimated to increase medication coverage by 17.8% (95% uncertainty interval: 16.2%; 19.6%) compared with the base scenario. Medication coverage improved by 3.6% (2.8%; 4.4%) with increased SPC use and by 10.3% (8.3%; 12.3%) with only SPC dispensation. Combining focused procurement and increased SPC use increased medication coverage by 20.2% (18.3%; 22.1%). When the prescription duration was extended to 3 months, the medication coverage was further increased by ~40% (eg, net improvement of ~60% with focused procurement, increased SPC use and 3-month prescriptions vs the base scenario).

Conclusions

With a fixed budget for medication procurement and dispensation, the combination of focused procurement, increased SPC use and extended prescription periods could substantially increase the number of patients who receive hypertension medications in India’s public health system. Our study highlights the benefits of implementing these reforms to scale up medication coverage for hypertension in India and potentially elsewhere.
What all physicians should know about women’s health: a Delphi study
Authors: de Heer-Koster Merel H , Benedetto Chiara , Bjegović-Mikanović Vesna , Banaitytė-Baleišienė Indre , Perdiou Mary , Gerdts Eva , Kautzky-Willer Alexandra , Mazières Julien , McGregor Alyson , Newman Connie , Price Susanna , Roeters van Lennep Jeanine , Stankevičiūtė Simona , Sommer Iris E , Stadler Gertraud , Thibaut Florence , van 't Land Karine , Wermer Marieke , Wilbur Kerry , Scheele Fedde
Published: January 2025

Objectives

Over the past few decades, knowledge of women’s health regarding sex and gender differences in health has increased but transfer of these new insights into medical education and clinical practice is lagging, resulting in substandard care for women compared with men. This study aimed to reach consensus on what all physicians taking care of women should know about women’s health.

Methods

A Delphi study was executed involving statements prepared by experts in women’s health across 10 medical specialties and a patient advisory board. Participants were recruited from Europe and Northern America through the experts’ networks and snowball sampling. Participants voted IN/OUT on each statement based on its perceived relevance and feasibility for general physician knowledge, regardless of specialty. The statements were ranked according to a >80% consensus in the first Delphi round and a 4-point Likert scale in the second Delphi round.

Results

In the first round, 44 participants fully completed the survey. 18 statements progressed to the second round, in which four additional statements were included based on participant suggestions. In the final round, 35 responses on the 22 selected statements resulted in consensus on 18 statements of the highest importance, within the following domains: the societal position of women in health, patient perception of disease and treatment, differences in symptomatology, pharmacological considerations and the impact of the female life cycle on health and disease.

Conclusion

Consensus was reached on the top priority clinical conditions and public health issues in women’s health, resulting in a list of 18 statements on women’s health that every physician caring for women should know, regardless of specialty. There was also consensus on the importance of incorporating these insights into medical education. The next step involves implementing women’s health education in medical schools, postgraduate education and continuing education for medical specialists.
Urine proteomics defines an immune checkpoint-associated nephritis signature
Authors: Long James P , Singh Shailbala , Dong Yanlan , Yee Cassian , Lin Jamie S
Published: January 2025

Immune checkpoint inhibitor (ICI) therapy is a cornerstone treatment for many cancers, but it can induce severe immunotoxicity, including acute interstitial nephritis (AIN). Currently, kidney biopsy is required to differentiate ICI-AIN from other causes of acute kidney injury (AKI). However, this invasive approach can lead to morbidity, delayed glucocorticoid treatment for patients with AIN, and unnecessarily prolonged suspension of ICI therapy in non-AIN patients. Delayed or incorrect diagnosis of ICI-AIN is particularly detrimental, as over 50% of patients are at risk of permanent renal damage. Thus, there is an urgent need for non-invasive biomarkers that can rapidly and accurately distinguish ICI-AIN from other causes of AKI.

The urine and plasma proteome contain actively secreted proteins that provide real-time insights into dynamic physiological processes. However, identification of effective biomarkers of disease using established technologies such as proximity ligation assays (PLA) and bead-based immunoassays is challenging due to their limited sensitivity and loss of precision in multiplex analysis.

To address this, we employed cutting-edge NUcleic acid Linked Immuno-Sandwich Assay (NULISA) technology to measure protein expression in urine and plasma samples from AKI patients undergoing ICI therapy. NULISA offers 10,000-fold greater precision than PLA, enabling quantification of over 200 inflammatory proteins with unprecedented precision. Our analysis revealed that urine was more sensitive and specific than plasma in distinguishing ICI-AIN from non-AIN cases. Pathway analyses highlighted the involvement of JAK-STAT and tumor necrosis factor (TNF) signaling in ICI-AIN pathogenesis. We identified several novel urine biomarkers, including IL-5, Fas, TNFSF4, CD274, IL-20, TNFSF15, TSLP, TREM1 and CCL1 while confirming previously reported markers such as CXCL9 and TNF-α. Using statistical and machine learning methods, we constructed a novel urine biomarker signature—IL-5+Fas—that achieved an area under the curve of 0.94 for diagnosing ICI-AIN.

By leveraging high-sensitivity proteomics, we developed a non-invasive strategy for diagnosing ICI-AIN. This approach will enable earlier intervention to mitigate immunotoxicity, preservation of antitumor efficacy of ICI therapy in non-AIN patients, and safe rechallenge of ICI therapy in patients previously treated for ICI-AIN.
Stretching, isometrics, and aerobic exercise for decreasing blood pressure post-exercise: a randomized crossover study
Authors: Keller Charlie , Chilibeck Philip D.
Published: January 2025

We compared stretching, isometrics, and aerobic exercise for effectiveness in decreasing blood pressure post-exercise. Using a randomized crossover design, 5 males and 4 females (21.3 years; normotensive) participated in four 30 min sessions on separate days: static stretching (30 s stretches, major muscle groups), isometric exercise, aerobic cycling (75% VO2peak), and control (rest), with blood pressure and heart rate measured before exercise (or rest) and for 60 min post-exercise (or rest). Aerobic exercise and stretching decreased post-exercise systolic blood pressure (∼10 mmHg each) ( p < 0.05), whereas isometric exercise and the control condition did not significantly decrease post-exercise blood pressure. Stretching is similar to aerobic exercise for reducing blood pressure post-exercise. ClinicalTrials.gov Identifier: NCT06628635.
Reproductive contribution of lake sturgeon transferred upstream of dams on a Great Lakes tributary
Authors: Forsythe Patrick S. , Sard Nicholas M. , Tucker Stefan , Atler Lexi , Kanefsky Jeannette , Johnson Jennifer , Isermann Daniel A. , Elliott Robert F. , Donofrio Michael , Scribner Kim T.
Published: January 2025

Dam construction contributes to declines in the distribution and abundance of many fishes. Increasing connectivity through adult transfer can be demographically and genetically beneficial, but assessing the effects resulting from transfer can be difficult if resident fish exist upstream. Genotypes of adult and larval lake sturgeon ( Acipenser fulvescens) were used to quantify contributions to larval recruitment from adults transferred upstream of dams on the Menominee River, USA. We evaluated whether transfer timing, sex, and adult size were associated with the odds of reproduction. Elevator transfer operations in Fall 2019, Fall 2020, and Spring 2021 resulted in 152 male and 81 female lake sturgeon transferred upstream. In 2020 and 2021, 580 and 518 larvae were genotyped. We found that 86% (201/233) of adults reproduced and 62.3% (684/1098) of offspring had transferred parents. In total, we estimated that 392 resident adults contributed to offspring production. Mixed matings accounted for 53% of offspring genotyped, increasing levels of offspring genetic diversity relative to offspring produced from resident-only matings. Transferring adults may be a viable restoration alternative for other iteroparous fish in river systems where connectivity to spawning areas has been impeded.
Relative measurement and extrapolation of the scintillation quenching factor of $$\alpha $$-particles in liquid argon using DEAP-3600 data
Authors:   DEAP Collaboration, Adhikari P. , Alpízar-Venegas M. , Amaudruz P.-A. , Anstey J. , Auty D. J. , Batygov M. , Beltran B. , Bina C. E. , Bonivento W. , Boulay M. G. , Bueno J. F. , Cai B. , Cárdenas-Montes M. , Choudhary S. , Cleveland B. T. , Crampton R. , Daugherty S. , DelGobbo P. , Di Stefano P. , Dolganov G. , Doria L. , Duncan F. A. , Dunford M. , Ellingwood E. , Erlandson A. , Farahani S. S. , Fatemighomi N. , Fiorillo G. , Ford R. J. , Gahan D. , Gallacher D. , García Abia P. , Garg S. , Giampa P. , Giménez-Alcázar A. , Goeldi D. , Gorel P. , Graham K. , Hallin A. L. , Hamstra M. , Haskins S. , Hu J. , Hucker J. , Hugues T. , Ilyasov A. , Jigmeddorj B. , Jillings C. J. , Kaur G. , Yazdi M. Khoshraftar , Kemp A. , Kuźniak M. , La Zia F. , Lai M. , Langrock S. , Lehnert B. , Levashko N. , Lissia M. , Luzzi L. , Machulin I. , Maru A. , Mason J. , McDonald A. B. , McElroy T. , McLaughlin J. B. , Mielnichuk C. , Mirasola L. , Moharana A. , Monroe J. , Murray A. , Ng C. , Oliviéro G. , Olszewski M. , Pal S. , Papi D. , Park B. , Perry M. , Pesudo V. , Pollmann T. R. , Rad F. , Rethmeier C. , Retière F. , Roszkowski L. , Santorelli R. , Schuckman II F. G. , Seth S. , Shalamova V. , Skensved P. , Smirnova T. , Sobotkiewich K. , Sonley T. , Sosiak J. , Soukup J. , Stainforth R. , Stringer M. , Tang J. , Vázquez-Jáuregui E. , Viel S. , Vyas B. , Walczak M. , Walding J. , Ward M. , Westerdale S. , Wormington R.
Published: January 2025

The knowledge of scintillation quenching of

$$\alpha $$

α

-particles plays a paramount role in understanding

$$\alpha $$

α

-induced backgrounds and improving the sensitivity of liquid argon-based direct detection of dark matter experiments. We performed a relative measurement of scintillation quenching in the MeV energy region using radioactive isotopes (

$$^{222}$$

222

Rn,

$$^{218}$$

218

Po and

$$^{214}$$

214

Po isotopes) present in trace amounts in the DEAP-3600 detector and quantified the uncertainty of extrapolating the quenching factor to the low-energy region.
Theoretical study of the open-flavored tetraquark $$T_{c\bar{s}}(2900)$$ in the process $$\bar{B}_s^0 \rightarrow K^0 D^0 \pi ^0$$
Authors: Lyu Wen-Tao , Duan Man-Yu , Wang Xiaoyu , Chen Dian-Yong , Wang En
Published: January 2025

Recently, the LHCb Collaboration has measured two decay processes

$$B^0\rightarrow \bar{D}^0D_s^+\pi ^-$$

B
0

→

D

¯

0

D
s
+

π
-

and

$$B^+\rightarrow D^-D_s^+\pi ^+$$

B
+

→

D
-

D
s
+

π
+

related to isospin symmetry, where two new open-flavored tetraquark states

$$T_{c\bar{s}}(2900)^0$$

T

c

s

¯

(
2900
)

0

and

$$T_{c\bar{s}}(2900)^{++}$$

T

c

s

¯

(
2900
)

+
+

that belong to an isospin triplet were observed in the

$$D_s^+\pi ^-$$

D
s
+

π
-

and

$$D_s^+\pi ^+$$

D
s
+

π
+

invariant mass distributions. In this work, we have investigated the validity of the process

$$\bar{B}_s^0\rightarrow K^0D^0\pi ^0$$

B

¯

s
0

→

K
0

D
0

π
0

as the promising process to confirm the existence of

$$T_{c\bar{s}}(2900)^0$$

T

c

s

¯

(
2900
)

0

resonance. Taking into account the tetraquark state

$$T_{c\bar{s}}(2900)$$

T

c

s

¯

(
2900
)

, as well as intermediate resonances

$$K^*(892)$$

K
∗

(
892
)

,

$$K_0^*(1430)$$

K
0
∗

(
1430
)

, and

$$K_2^*(1430)$$

K
2
∗

(
1430
)

, it has been shown that a clear peak of the open-flavored tetraquark

$$T_{c\bar{s}}(2900)$$

T

c

s

¯

(
2900
)

appears in the

$$K^0D^0$$

K
0

D
0

invariant mass distribution of the process

$$\bar{B}_s^0\rightarrow K^0D^0\pi ^0$$

B

¯

s
0

→

K
0

D
0

π
0

, which could be tested by future experiments.
Higgs alignment from multicritical-point principle in two Higgs doublet models
Authors: Kawai Hikaru , Kawana Kiyoharu , Oda Kin-ya , Yagyu Kei
Published: January 2025

In models with non-minimal Higgs sectors, enforcing (near) Higgs alignment, necessary to prevent significant deviations in the Higgs boson coupling from the standard model prediction, causes a serious fine-tuning problem. We demonstrate that the Higgs alignment is naturally deduced from the multicritical point principle (MPP) in the general two Higgs doublet model while keeping non-zero CP-violating phases. Furthermore, we discuss the possibility of realizing the Yukawa alignment from the MPP, which is necessary to prevent flavor-changing neutral currents mediated by Higgs bosons at tree level, and find that it seems difficult to realize it by the MPP due to the non-diagonal structure of the CKM matrix.
Drop-off characteristics of film flow on inclined fibers
Authors: Pour Karimi Atefeh , Hormann Bernhard , Askarizadeh Hossein , Rohlfs Wilko , Scheid Benoit , Kneer Reinhold
Published: January 2025

This paper presents an empirical analysis of a film flow dropping-off from an inclined fiber substrate, where the fiber diameter is on the order of the capillary length. The investigation aims to elucidate the dynamics of beads traveling down the inclined fibers. We explore the parameters influencing the bead’s final shape and their stability on the substrate (in terms of detaching or not detaching) in a flow driven by gravity and affected by surface tension and inertia. Three different growth modes and their connection to the two main existing drop-off mechanisms of beads on inclined fibers, namely drop-off due to unsaturated growth and drop-off due to coalescence events, are established and demonstrated. A new parameter,

$$\Phi$$

Φ

, is introduced, which includes information about the shape of the beads and its connection to the flow conditions. If

$$\Phi >1$$

Φ
>
1

, the bead exhibits a rather sinusoidal shape, indicating that its formation is predominantly influenced by surface tension. If

$$\Phi < 1$$

Φ
<
1

, the bead is subjected to front-steepening due to an inertia-dominated flow. If

$$\Phi =1$$

Φ
=
1

, the bead’s tail aligns with the direction of gravity, experiencing unsaturated growth until it drops off, which indicates a flow condition driven primarily by gravitational forces. Furthermore, this study offers a quantitative experimental basis for flow parameters on inclined fibers, including Nusselt film thickness, healing length within the unperturbed film and rate of growth of beads at the end of healing length, beads crest height, beads velocity, and parameter

$$\Phi$$

Φ

for future comparison to theoretical and numerical modelling.
Construction of an English Oral Pronunciation Evaluation Model Based on Deep Learning Algorithms
Authors: Zhang Zhe
Published: January 2025

Oral pronunciation refers to the way words are spoken aloud, encompassing aspects like accent, intonation, and clarity. It plays a crucial role in effective communication, influencing listeners to understand the speaker. The purpose of this research is to construct an English oral pronunciation evaluation model based on a deep learning algorithm. In this research, we propose a novel Dung Beetle Optimization-driven Customized Deep Belief Network (DBO-CDBN) for accurate detection and evaluation of English oral pronunciation. We obtain a dataset that comprises audio recordings of English speech, including both correct and mispronounced samples to train and evaluate the suggested pronunciation evaluation model. Data normalization is used to pre-process the gathered raw audio data, it enhances the overall quality of the data. The Gammatone Frequency Cepstral Coefficients (GFCC) algorithm is employed to extract the crucial features from the obtained audio data. In our proposed model, the DBO optimization algorithm iteratively finetunes the CDBN architecture to enhance the evaluation accuracy. The approach, which is executed in python, is shown to be more successful in pronunciation evaluation and to provide prospective advances in the area when its performance is examined and compared to other approaches in terms of precision (96.78%), recall (93.65%), and [Formula: see text]-measure (94.53%). The established model is implemented using Python software. During the outcome analysis phase, we evaluate our model’s performance across various parameters. In addition, we also performed a comparative analysis using diverse existing methodologies. The findings demonstrate the excellence and effectiveness of the suggested future economic forecasting model.
Dynamical investigation of the new (3+1)-dimensional Kadomtsev–Petviashvili–Sawada–Kotera–Ramani equation with conformable fractional derivative
Authors: Şenol Mehmet , Erol Meliha Özlem , Çelik Furkan Muzaffer , Das Nilkanta
Published: January 2025

This paper examines the conformable version of a recently proposed novel [Formula: see text]-dimensional Kadomtsev–Petviashvili–Sawada–Kotera–Ramani equation. First, some basic definitions and properties of the conformable derivative are provided. To find exact solutions to this problem, the modified extended tanh-function, exp([Formula: see text]-expansion, and Kudryashov R function methods are applied. The results are illustrated by utilizing some of the gathered data’s physical 3D, contour, and 2D surfaces, which sheds light on how geometric patterns are physically comprehended. These solutions contribute to understanding the potential practical applications of the examined model and other nonlinear representations in the physical sciences. These techniques can provide significant solutions for various fractional differential equations.
Dense Uniform Li–Yorke Chaos for Linear Operators on a Banach Space
Authors: Li Jian , Wang Xinsheng
Published: January 2025

This paper focuses on the dense uniform Li–Yorke chaos for linear operators on a Banach space. Some sufficient conditions and equivalent conditions are established under which the dynamical system is densely uniformly Li–Yorke chaotic. It is shown that there are plenty of densely uniformly Li–Yorke chaotic operators. For unilateral backward weighted shifts and bilateral backward weighted shifts on [Formula: see text], it is shown that Li–Yorke chaos is equivalent to dense uniform Li–Yorke chaos.
Architectural modelling of the fractal-like Ediacaran rangeomorph
Charnia masoni
Authors: McIlroy D.
Published: January 2025

The frondose Rangeomorpha are a poorly understood group of Ediacaran, fractal-like organisms, with a body plan that is unknown among modern organisms. The first described rangeomorph
Charnia masoni
is one of the most iconic members of the Ediacaran biotas, first described from Charnwood Forest in Leicestershire. The complex branching of the Rangeomorpha in three dimensions is a challenge to understand, previous work by the late Martin Brasier sought to explain architectural concepts with simplified diagrams. The present work builds on that earlier work using 3D sculpting to reconstruct the fractal-like branching, while also honouring the shapes seen in the type material of
Charnia masoni
. The resulting forms are surprisingly complex and have enormous surface areas. If the surfaces of
Charnia
as reconstructed were covered with simple choanocytes, it could be considered as a potentially highly effective full-body suspension feeding metazoan organism.
RAD-FS: Remote Timing and Power SCA Security in DVFS-augmented Ultra-Low-Power Embedded Systems
Authors: Dobkin Daniel , Cever Nimrod , Levi Itamar
Published: January 2025

High-performance crypto-engines have become crucial components in modern System-On-Chip (SoC) architectures across platforms, from servers to edge-IoTs’. Alas, their secure operation faces a significant obstacle caused by information-leakage accessed through Side-Channel Analysis (SCA). Adversaries exploit statistical-analysis techniques on measured (e.g.,) power and timing signatures generated during (e.g.,) encryption, extracting secrets. Mathematical countermeasures against such attacks often impose substantial power-performance-area overheads. Dynamic Voltage and Frequency Scaling (DVFS) techniques provide power-efficiency by varying power consumption according to workload; these modulations are called power-states. Unintentionally, DVFS introduces new inherent weaknesses exploitable by malicious actors: power-states
leak
information in both power and timing side-channels, measurable in software and hardware. We introduce a method to increase side-channel resistance using integrated voltage regulators and DVFS: (1) Pushing known prior-art in the topic to Ultra Low Power (ULP) regime (2) For the first time introducing a mechanism to aid in counteracting the inherent weakness of DVFS in SCA (3) Providing measurements performed on 40 nm process ULP PLS15 test-chip down at 580
mV
power-supply (4) Offering improved and parameterized resistance to
remote
-timing vulnerabilities inherent to DVFS. We present various results and perform a detailed analysis while comparing performance and security to prior-art. Importantly, our solution is configurable in terms of security, maintaining degrees-of-freedom for power-optimization of DVFS.
A Container Security Survey: Exploits, Attacks, and Defenses
Authors: Jarkas Omar , Ko Ryan , Dong Naipeng , Mahmud Redowan
Published: January 2025

Containerization significantly boosts cloud computing efficiency by reducing resource consumption, enhancing scalability, and simplifying orchestration. Yet, these same features introduce notable security vulnerabilities due to the shared Linux kernel and reduced isolation compared to traditional virtual machines (VMs). This architecture, while resource-efficient, increases susceptibility to software vulnerabilities, exposing containers to potential breaches; a single kernel vulnerability could compromise all containers on the same host. Existing academic research on container security is often theoretical and lacks empirical data on the nature of attacks, exploits, and vulnerabilities. Studies that do look at vulnerabilities often focus on specific types. This lack of detailed data and breadth hampers the development of effective mitigation strategies and restricts insights into the inherent weaknesses of containers. To address these gaps, our study introduces a novel taxonomy integrating academic knowledge with industry insights and real-world vulnerabilities, creating a comprehensive and actionable framework for container security. We analyzed over 200 container-related vulnerabilities, categorizing them into 47 exploit types across 11 distinct attack vectors. This taxonomy not only advances theoretical understanding but also facilitates the identification of vulnerabilities and the implementation of effective mitigation strategies in containerized environments. Our approach enhances the resilience of these environments by mapping vulnerabilities to their corresponding exploits and mitigation strategies, especially in complex, multi-tenant cloud settings. By providing actionable insights, our taxonomy helps practitioners enhance container security. Our findings have identified critical areas for further investigation, thereby laying a comprehensive foundation for future research and improving container security in cloud environments.
Scalable Similarity-Aware Test Suite Minimization with Reinforcement Learning
Authors: Gu Sijia , Mesbah Ali
Published: January 2025

The Multi-Criteria Test Suite Minimization (MCTSM) problem aims to remove redundant test cases, guided by adequacy criteria such as code coverage or fault detection capability. However, current techniques either exhibit a high loss of fault detection ability or face scalability challenges due to the NP-hard nature of the problem, which limits their practical utility. We propose TripRL, a novel technique that integrates traditional criteria such as statement coverage and fault detection ability with test coverage similarity into an Integer Linear Program (ILP), to produce a diverse reduced test suite with high test effectiveness. TripRL leverages bipartite graph representation and its embedding for concise ILP formulation and combines ILP with effective reinforcement learning (RL) training. This combination renders large-scale test suite minimization more scalable and enhances test effectiveness. Our empirical evaluations demonstrate that TripRL’s runtime scales linearly with the magnitude of the MCTSM problem. Notably, for large test suites from the Defects4j dataset where existing approaches fail to provide solutions within a reasonable time frame, our technique consistently delivers solutions in less than 47 minutes. The reduced test suites produced by TripRL also maintain the original statement coverage and fault detection ability while having a higher potential to detect unknown faults.
Automated Detection and Repair of Floating-point Precision Problems in Convolutional Neural Network Operators
Authors: Liu Jiawei , Zhang Xufan , Xu Lurong , Fang Chunrong , Gu Mingzheng , Luo Weisi , Chai Dong , Wang Jiang , Zhao Zhihong , Chen Zhenyu
Published: January 2025

Convolutional Neural Network (CNN) operators, mostly based on mathematical linear computations, are of vital importance to developing CNN-based software. Existing studies reveal that these operators are prone to floating-point precision problems (FPPs). In a CNN-based application, such problems can be propagated and result in catastrophic consequences. Thus, it is highly desired to detect and repair the FPPs in CNN operators. Considering the FPPs in CNN operators are mainly caused by accumulated floating-point errors and diverse floating-point tensors instead of wrong codes or bad implementations, it requires much time cost and is difficult to tackle these FPPs.

In this paper, we propose the first method for the automated detection and repair of FPPs in CNN operators from the perspective of floating-point tensors. To generate diverse tensors with floating-point numbers, we design two levels of mutation rules, namely computation-level mutation and input-level mutation, containing a total of five mutation methods. To detect the FPPs caused by the accumulated floating-point errors, our method uses a weight matrix to guide the progressive mutation. To repair the detected FPPs, our method transforms the error-prone floating-point tensors based on the mathematical rewriting of the floating-point linear computational properties without destroying the original computation. Experimental results show that our methods can detect and repair FPPs in CNN operators effectively and efficiently and could reduce 93.32% to 100% of the FPPs in CNN operators.
We conduct a case study on six different widely-used CNN models and confirm that the proposed FPP method is generalizable and effective across a variety of tasks and architectures. Our detection and repair method offers an intuitive way to handle FPPs during development, allowing users to continue building and fine-tuning their models without being slowed down by numerical precision errors.
We believe that our method could open up a new way to enhance the quality of CNN operators and CNN-based software.
Finding Safety Violations of AI-Enabled Control Systems through the Lens of Synthesized Proxy Programs
Authors: Shi Jieke , Yang Zhou , He Junda , Xu Bowen , Kim Dongsun , Han DongGyun , Lo David
Published: January 2025

Given the increasing adoption of modern AI-enabled control systems, ensuring their safety and reliability has become a critical task in software testing. One prevalent approach to testing control systems is falsification, which aims to find an input signal that causes the control system to violate a formal safety specification using optimization algorithms. However, applying falsification to AI-enabled control systems poses two significant challenges: (1) it requires the system to execute numerous candidate test inputs, which can be time-consuming, particularly for systems with AI models that have many parameters, and (2) multiple safety requirements are typically defined as a conjunctive specification, which is difficult for existing falsification approaches to comprehensively cover.

This paper introduces
Synthify
, a falsification framework tailored for AI-enabled control systems, i.e., control systems equipped with AI controllers. Our approach performs falsification in a two-phase process. At the start,
Synthify
synthesizes a program that implements one or a few linear controllers to serve as a proxy for the AI controller. This proxy program mimics the AI controller's functionality but is computationally more efficient. Then,
Synthify
employs the

\(\epsilon\)

-greedy strategy to sample a promising sub-specification from the conjunctive safety specification. It then uses a Simulated Annealing-based falsification algorithm to find violations of the sampled sub-specification for the control system. To evaluate
Synthify
, we compare it to
PSY-TaLiRo
, a state-of-the-art and industrial-strength falsification tool, on 8 publicly available control systems. On average,
Synthify
achieves a 83.5% higher success rate in falsification compared to
PSY-TaLiRo
with the same budget of falsification trials. Additionally, our method is 12.8

\(\times\)

faster in finding a single safety violation than the baseline. The safety violations found by
Synthify
are also more diverse than those found by
PSY-TaLiRo
, covering 137.7% more sub-specifications.
With Great Power Comes Great Responsibility: The Role of Software Engineers
Authors: Betz Stefanie , Penzenstadler Birgit
Published: January 2025

The landscape of Software Engineering evolves rapidly amidst digital transformation and the ascendancy of AI, leading to profound shifts in the role and responsibilities of Software Engineers. This evolution encompasses both immediate changes, such as the adoption of Large Language Model-based approaches to coding, and deeper shifts driven by the profound societal and environmental impacts of technology. Despite the urgency, there persists a lag in adapting to these evolving roles. This roadmap paper proposes 10 research challenges to develop a new generation of Software Engineers equipped to navigate the technical and social complexities as well as ethical considerations inherent in their evolving profession. Furthermore, the challenges target role definition, integration of AI, education transformation, standards evolution, and impact assessment to equip future Software Engineers to skillfully and responsibly handle the obstacles within their transforming discipline.
MESSI: Task Mapping and Scheduling Strategy for FPGA-based Heterogeneous Real-Time Systems
Authors: Ahmadi-Pour Sallar , Saha Sangeet , McDonald-Maier Klaus , Drechsler Rolf
Published: January 2025

Continuous demands for improved performance within constrained resource budgets are driving a move from homogeneous to heterogeneous processing platforms for the implementation of today’s Real-Time (RT) embedded systems. The applications executing on such systems are typically represented as a Precedence Task Graph (PTG), where a node represents a task or algorithm for one functionality and edges represent the complex interactions between multiple functionalities. Due to RT constraints, the task graph needs to be executed within a specified deadline. Although some existing studies have looked into solving this challenge, comprehensive studies that combine the theoretical features of RT task-graph mapping and scheduling with practical runtime architectural characteristics have mostly been ignored to date. Hence, in this article, we consider the challenge of scheduling an RT application modeled as a single PTG, with the objective of minimizing the overall execution time under Hardware (HW) resource and deadline constraints for heterogeneous Central Processing Unit (CPU) + Field Programmable Gate Array (FPGA) architectures. First, we introduce an optimal solution using Integer Linear Programming (ILP). However, this ILP-based optimal solution suffers from computational complexity and does not scale well even for moderately large problem sizes. Hence, we additionally propose heuristic algorithms for task mapping and scheduling. The efficiency of the proposed scheme, named MESSI, has been evaluated through experiments using PTG on a practical CPU+FPGA system regarding current technology restrictions. Our experiments demonstrate that performance gains of 55.6% and area usage reductions of 46.3% are possible compared to full Software (SW) and HW execution, respectively.
Approach to Therapy for Chronic Pouchitis
Authors: Kayal Maia , Boland Brigid
Published: January 2025

Chronic pouchitis (CP) occurs in approximately 20% of patients with ulcerative colitis after total proctocolectomy with ileal pouch anal anastomosis and is categorized as antibiotic dependent, antibiotic refractory, or Crohn's disease–like. The management of CP is challenging because of limited evidence and few randomized controlled trials. In this review, we discuss the medical management of CP and its supporting data delineated by type of therapy.
Hidradenitis Suppurativa
Authors: McCarthy S.
Published: January 2025

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease characterized by the formation of nodules, abscesses, and fistulae at intertriginous sites. Pain, pruritus, malodor, and suppuration have a significant impact on quality of life for HS patients. Prevalence figures vary greatly in the literature from 0.05% to 4.1%, and HS is more common in females. The current understanding of the etiology and pathogenesis of HS is incomplete; numerous hypotheses concern the interplay of lifestyle factors, skin microbiota, genetics, and a dysregulated immune system. Due to its phenotypic heterogeneity and multifactorial pathogenesis, HS is a complex disease that can prove challenging to manage. Two approved biologic therapies for the management of HS have led to clinical response in approximately 50% of treated patients. New therapies targeting the interleukin (IL)-1, IL-17, IL-36, and Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathways are in ongoing clinical trials, and preliminary data offer hope for greater clinical efficacy in HS in the future.
Investigating the Compressibility of Sandy‐Clay Soil in the Laboratory Soil Bin Caused by Agricultural Tire Traffic and Analyzed by the Adaptive Neuro–Fuzzy Inference System
Authors: Kalantari Davood , Askari Mohammad , Mousavi-Seyedi Seyed Reza , Asadi Nezamedin
Published: January 2025

Agricultural soil compaction caused by tractors and heavy farm machines has a direct impact on farm productivity. Therefore, the effect of influencing parameters on soil compaction was studied and evaluated using a wheel tester device in the soil bin environment. Experiments were carried out at 3 levels of vertical load (170, 250, and 320 kg), 3 levels of tire inflation pressure (10, 15, and 20 psi), 3 levels of soil moisture content (2%, 7%, and 13% wet basis), and 2 levels of forward speed (0.386 and 0.879 km/h) in the form of a factorial design and a randomized complete block design in 3 replications. Next, soil compaction was predicted under the influence of investigated parameters using ANFIS. The results showed that the advance of the wheel at low speed and high soil moisture content significantly increases soil compaction. The present findings showed that the soil compaction increases linearly with the relative increase of the vertical load on the tire. Meanwhile, the relative increase of soil compaction in wet soil (7%–13% relative humidity, wb) was relatively 9.93 times higher than the soil compaction in low humidity (2%–7%). The results also show that reducing tire inflation pressure from 20 to 15 psi reduces soil compaction by 12.94%. The correlation coefficient between the measured and predicted data using ANFIS for soil compaction was equal to 1, which showed the high accuracy of ANFIS models in predicting the studied parameters. This approach provides criteria for a more appropriate selection of agricultural tires.
Table 1 from Deep Learning Predicts Subtype Heterogeneity and Outcomes in Luminal A Breast Cancer Using Routinely Stained Whole-Slide Images
Authors: Kurian Nikhil Cherian , Gann Peter H. , Kumar Neeraj , McGregor Stephanie M. , Verma Ruchika , Sethi Amit
Published: January 2025

Clinical and molecular features of PAM50 LumA breast cancers in the test set according to the quartile of the tumor area classified as LumA by the deep learning model (total n = 230)
AI and machine learning for detection and management of delirium in care home residents
Authors: Banerjee Jay , Hoger Fabian , Gordon Adam Lee
Published: January 2025

Background
Presently, diagnosing delirium in older people is a challenge. Diagnostic support tools such as the Confusion Assessment Method and 4AT provide structure but require specialist training, resources, and implementation support, while some subjectivity persists in diagnosis. This is particularly the case in people who live with dementia who often experience rapid fluctuation in cognitive abilities and behaviours. This leads to variation in diagnosis between settings and care providers, with consequent harmful impact on those experiencing delirium. These challenges become greater in care homes where dementia is prevalent, daily fluctuation is the norm and where the majority of staff are not trained healthcare professionals.

Summary
Here we outline the potential for AI-based Human Activity Recognition (HAR) approaches to identify and flag deviations from normal behaviour that may be precursors of a delirium state, enabling earlier detection and management, and better outcomes. We outline how Statistical Process Control (SPC) approaches could form the basis of diagnostic algorithms and the steps required to test the feasibility of this approach in the care home setting.

Key Messages
Delirium detection and diagnosis, difficult in any setting, is more difficult in care homes because of resident, staff and organisational factors.

Artificial intelligence, machine learning and human activity recognition have potential to make diagnosis more reliable because of their ability to recognise changes from normal patterns of behaviour at an individual level.
Grundlagen der Hidradenitis suppurativa: Ein umfassender Überblick über die diagnostischen und therapeutischen Perspektiven
Authors: Pandey Archana
Published: January 2025

Hidradenitis suppurativa (HS), auch als Akne inversa bekannt, ist eine chronisch-entzündliche Hauterkrankung, die sich durch wiederkehrende entzündliche Knoten, Abszesse, subkutane Gänge und Narbenbildung auszeichnet. Die Erkrankung kann schwere psychische Probleme verursachen und die Lebensqualität der betroffenen Patienten beeinträchtigen. Aufgrund der Unannehmlichkeiten und des übelriechenden Exsudats aus diesen Läsionen gilt sie als eine der Hauterkrankungen, die die Lebensqualität am stärksten beeinträchtigen. Obwohl die Pathophysiologie der HS noch unklar ist, wurden mehrere Faktoren, darunter Lebensstil, genetische und hormonelle Faktoren, mit der HS in Verbindung gebracht. Die Pathogenese der HS ist sehr komplex und weist ein breites Spektrum klinischer Manifestationen auf. Daher ist ihre Behandlung recht schwierig und erfordert häufig eine Kombinationstherapie, die je nach Schweregrad der Erkrankung und anderen patientenspezifischen Faktoren angepasst werden muss. Während Änderungen der Lebensweise, Gewichtsabnahme, Raucherentwöhnung, topische Behandlungen und orale Antibiotika bei leichten Fällen ausreichen, besteht die Herausforderung für das medizinische Fachpersonal in der Behandlung mittelschwerer bis schwerer HS, die häufig nicht gut auf herkömmliche Ansätze anspricht. Diese Übersichtsarbeit, die aus einem Überblick über die verschiedenen Beurteilungsinstrumente und Behandlungsstrategien besteht, die für die Diagnose und Behandlung von HS aus der veröffentlichten Literatur zur Verfügung stehen, soll praktizierenden Ärzten helfen, die mit dieser Krankheit verbundene Komplexität zu bewältigen.