bluuebunny/crossref_metadata_2025 huggingface dataset:
Accessibility of TB diagnostic services at primary healthcare clinics in the eThekwini district, South Africa: a geospatial analysis
Authors: Dlangalala Thobeka , Musekiwa Alfred , Mckelly David , Baloyi Ethel , Mashamba-Thompson Tivani Phosa
Published: September 2024

Background

Improving geographic access can aid in managing tuberculosis (TB) by enabling early diagnosis and treatment initiation. Although geospatial techniques have been used to map the transmission patterns of drug-resistant TB in South Africa, fewer studies have investigated the accessibility of TB diagnostic services. This study evaluated the accessibility of TB diagnostic services and disease distribution in the eThekwini district of South Africa.

Methods

In this cross-sectional study, population data for 2021 were disaggregated into smaller analysis units and then re-aggregated through the dasymetric mapping technique. Data on notified TB patients, including Global Positioning System coordinates of clinics, were obtained from the District of Health Information System, exported to ArcGIS 10.8.2 and used to calculate distances to the nearest clinics and hospitals.

Results

92% of the population (3 730 494 people) in eThekwini could access TB diagnostic services within 5 km. Patients travelled an average distance of 4.7 km (range: 0.1–26.9 km). TB diagnostic services were highly accessible in the Northern and Central regions and moderately accessible in the predominately rural Western and Southern regions. The smallest population of eThekwini resides in rural areas; however, 40.7% of its residents live >5 km from a diagnosing facility, with patients in the South having to travel up to 44.5 km. TB incidence was higher in the predominately rural West and South regions compared with the Central and North regions which are mainly comprised of urban and suburban areas. Our findings also showed that 98.4% of the clinics in eThekwini were located within 30 km of a hospital at an average distance of 9.6 km within the district. However, the distribution of these hospitals does not demonstrate equitable access as the majority are located within the Central region, and fewer are found in the other three regions of eThekwini.

Conclusions

Addressing the disparities in access to TB diagnostic services is required in the eThekwini district. Leveraging the existing mobile health clinics can assist with this, particularly, in rural areas with inadequate access. Additionally, active-case finding should be intensified in these regions since they had a higher TB burden per population. Prioritising interventions in these areas is crucial for reducing the impact of the disease on affected communities.
Hostel support workers’ experiences navigating healthcare alongside people experiencing homelessness: a qualitative study in the UK
Authors: Muzafar Iman , Cunningham Oliver
Published: September 2024

Objectives

This study aimed to explore how hostel support workers (HSWs) experience navigating healthcare alongside people experiencing homelessness (PEH). PEH experience poor health outcomes, increased mortality and face many barriers when accessing healthcare. HSWs have a dynamic and holistic role, working with PEH to navigate access to health and social care, whilst facilitating independence. HSWs have been described as important in addressing barriers to access and linking healthcare and PEH. However, HSWs’ experiences navigating this role across sectors remains underexplored.

Design

In this qualitative study, semistructured interviews were conducted, and phenomenological thematic analysis was performed.

Setting

Interviews were conducted with participants from 13 hostels across four UK counties.

Participants

17 HSWs were interviewed, with experience in their role ranging from 3 months to over 10 years.

Results

Three themes were identified.

HSWs feeling stigmatised by healthcare staff (HCS), including power inequalities between HSWs and HCS, and the impact of stigma against PEH in healthcare on HSWs.

Working across sectors, including both collaborative and disconnected experiences.

In-reach and its role in linking PEH and healthcare. This included the contrasting subthemes of in-reach as an effective link versus in-reach being an impractical and unsustainable solution.

Conclusions

Cross-sector collaboration has been recognised as an effective way to increase healthcare access and improve outcomes for Inclusion Health Groups, including PEH. This has been further highlighted by the formation of Integrated Care Systems, which strive to bring sectors together to tackle inequalities in outcomes, experience and access. Collaborative relationships between sectors, that is, hostels and healthcare, are vital for increasing healthcare access for PEH. We explored the experiences of HSWs navigating healthcare access for this marginalised population. Recognising and understanding these experiences are the first steps in building collaborative cross-sector relationships to improve healthcare accessibility, experiences and outcomes for PEH.
Cohort profile: the Swiss Mother and Child HIV Cohort Study (MoCHiV)
Authors: Paioni Paolo , Capaul Murezi , Brunner Anja , Traytel Anna , Aebi-Popp Karoline , Crisinel Pierre-Alex , Duppenthaler Andrea , Günthard Huldrych , Martinez De Tejada Begona , Kottanattu Lisa , Stöckle Marcel , Rauch Andri , Wagner Noemie , Hösli Irene , Rudin Christoph , Scherrer Alexandra , Kusejko Katharina , Kahlert Christian R
Published: September 2024

Purpose

Prospective, multicentric observational cohort study in Switzerland investigating measures to prevent mother-to-child transmission in pregnant women with HIV (WWH) and assessing health and development of their exposed children as well as of children with HIV (CWH) in general.

Participants

Between January 1986 and December 2022, a total of 1446 mother–child pairs were enrolled. During the same period, the study also registered 187 CWH and 521 HIV-exposed but uninfected children (HEU), for whom detailed maternal information was not available. Consequently, the cohort comprises a total of 2154 children.

Findings to date

During these 37 years, research by the Swiss Mother and Child HIV Cohort Study (MoCHiV) and its international collaborators has strongly influenced the prevention of vertical transmission of HIV (eg, introduction and discontinuation of elective caesarean section, neonatal postexposure prophylaxis and breastfeeding). Contributions have also been made to the management of diagnostics (eg, p24 antigen assay) and the effects of antiretroviral treatment (eg, prematurity, growth) in HEU and CWH.

Future plans

Most children present within the cohort are now HEU, highlighting the need to investigate other vertically transmitted pathogens such as hepatitis B and C viruses, cytomegalovirus orTreponema pallidum. In addition, analyses are planned on the longitudinal health status of CWH (eg, resistance and prolonged exposure to antiretroviral therapy), on social aspects including stigma in CWH and HEU, and on interventions to further optimise antenatal and postpartum care in WWH.
Acustimulation combined with pharmacological prophylaxis versus pharmacological prophylaxis alone in postoperative nausea and vomiting (PONV) prophylaxis among patients undergoing laparoscopy abdominal surgery: a research protocol for a randomised controlled trial
Authors: Chen Junjie , Che Lu , Cui Quexuan , Lang Jiaxin , Zhang Yuelun , Zhu Bo , Huang Yuguang
Published: September 2024

Introduction

This study evaluates the efficacy of integrating percutaneous electrical nerve stimulation at the pericardium 6 (PC6) acupuncture point through a wearable acustimulation device with standard pharmacological prophylaxis to prevent postoperative nausea and vomiting (PONV) compared with pharmacological prophylaxis alone in patients undergoing laparoscopic abdominal surgery.

Method and analysis

This prospective study will enrol 302 patients scheduled for elective laparoscopic surgery. Participants will be randomly allocated to one of two groups: acustimulation combined with pharmacological prophylaxis or sham stimulation combined with pharmacological prophylaxis. Randomisation will involve a computer-generated sequence, with allocation concealment implemented through sealed envelopes. The acustimulation group will receive electrical stimulation at the PC6 point starting 30 min before surgery and continuing until discharge from the postanaesthesia care unit. Sham group will wear a wristband that does not provide stimulation. The primary outcome is the incidence of PONV. Secondary outcomes include the severity of PONV, incidence rates of nausea and vomiting at different postoperative intervals and indices of gastrointestinal functional recovery. Exploratory outcomes will assess haemodynamic parameters, baroreflex sensitivity, hospital stay duration, costs and both short-term and long-term postoperative recovery.

Ethics and dissemination

All participants will provide written informed consent. The study has been approved by the Ethics Committee of Peking Union Medical Hospital (approval number: I-23PJ1712). Results will be published open access.

Trial registration number

NCT06241547.
Frailty is independently associated with subclinical cardiovascular disease in patients with systemic lupus erythematosus
Authors: Pappa Maria , Keramiotou Kyriaki , Sfikakis Petros P , Tektonidou Maria G
Published: September 2024

Objectives

Cardiovascular disease is a leading cause of mortality in systemic lupus erythematosus (SLE). Frailty has been associated with an increased cardiovascular disease risk (CVR) in the general population. We aimed to examine the association between frailty and subclinical cardiovascular disease in patients with SLE.

Methods

In this cross-sectional study, we included all patients with SLE who underwent carotid/femoral artery ultrasound in our unit between 2016 and 2018. Clinical and laboratory data were collected at the time of ultrasound testing. Frailty was measured using the Systemic Lupus International Collaborating Clinics-Frailty Index (SLICC-FI). CVR (low, moderate, high, very high) was evaluated by the Systematic COronary Risk Evaluation (SCORE) model. Determinants of atherosclerotic plaque presence were assessed by logistic regression analyses, adjusting for potential confounders.

Results

202 patients were included in the study. Atherosclerotic plaques (20.8% carotid, 17.3% femoral) were observed in 52/202 (25.7%) patients (89.1% women, mean (±SD) age 46.7±12.6). Median (IQR) SLICC-FI was 0.08 (0.04–0.10). 39 (19.3%) patients were classified as robust, 91 (45%) as relatively less fit, 59 (29.2%) as least fit and 13 (6.4%) as frail. In univariate analysis, plaque presence was significantly associated with age, disease duration, smoking, hypertension, systolic blood pressure, dyslipidaemia, SCORE, CVR class and SLICC-FI. CVR class (OR 5.16, p=0.000) and SLICC-FI (OR 1.34, p=0.03 per 0.05 point increase) remained significant in multivariate analysis after adjustment for traditional and disease-related CVR factors.

Conclusions

SLICC-FI is independently associated with plaque presence. Further studies are warranted to determine whether frailty-specific interventions can reduce CVR in patients with SLE.
Quantifying maternal reproductive output of chondrichthyan fishes
Authors: Harry Alastair V. , Baremore Ivy E. , Piercy Andrew N.
Published: September 2024

For the live-bearing and egg-laying class of chondrichthyan fishes a three parameter logistic ‘maternity’ function with a variable upper asymptote, PMax, can be used to predict the average probability of a female giving birth or laying eggs in a season. Although fundamental to calculating the reproductive capacity of a population, few studies report maternity functions, with maturity functions often used as a proxy. Applying logistic models to simulated and empirical data showed that it was feasible to estimate PMax from maternal data and that accuracy, bias, and confidence interval coverage often improved compared to when a fixed value was used. However, sample sizes of 100–200 maternal females were typically required for accurate estimation of PMax. While maturity parameters could be estimated with greater accuracy, substituting them for maternity parameters overestimated lifetime reproductive output. Greater use of maternity functions has the potential to improve calculation of reproductive output in quantitative populations models. In addition to improvements in parameter estimation, this method involves fewer assumptions and enables statistical inferences to be made on frequency of reproduction.
Cyber-attack Detection and Mitigation Process under Big Data Consideration: Improved Recursive Feature Elimination-based Feature Selection
Authors: Babu D. Raghunath Kumar , Packialatha A.
Published: September 2024

Due to the rapid growth of network technology, huge volume and distinct data sent via networks is expanding constantly. The situation shows how complex and dense cyber attacks and hazards are developing. Due to the rapid advancement in network density, cyber security specialists find it difficult to monitor all network activity. Due to frequent and sophisticated cyber attacks, it is becoming more challenging to detect and identify abnormalities in network events. The use of deep learning provides a variety of tools and strategies for automated cyber-attack detection as well as quick attack-type prediction as well as evaluation. This work introduces a novel cyber-attack detection and mitigation process under the following phases including preprocessing, feature extraction via the Map Reduce framework that handles the big data, feature selection, attack detection and mitigation. The Improved Normalisation process is achieved on the preprocessing phase. The work is examined from a big data perspective; hence Map Reduce framework is utilised for this. As a result, the framework will manage the feature extraction process, where features including statistical features, raw features, improved correlation-based features, and info gain-based features will be extracted. Following feature extraction, the Improved Recursive Feature Elimination procedure is processed that selects the relevant features. The hybrid detection model, which combines Recurrent Neural Networks (RNN) Deep and Belief Networks (DBN) is used to detect the attacks. Once an attack has been detected, the attacker must be mitigated. To accomplish this, an improved BAIT-based mitigation procedure is used. The two datasets used in this work are, namely, Intrusion Detection Systems (IDS) 2018 Intrusion CSVs (CSE-CIC-IDS2018) and UNSW_NB15. Finally, the suggested model and the alternative methods are contrasted using a variety of measures such as accuracy, sensitivity, specificity, precision, FDR, FNR and FPR.
Realized Stock Market Volatility of the United States: The Role of Employee Sentiment
Authors: Gupta Rangan , Hall Savanah , Pierdzioch Christian
Published: September 2024

Using data for the United States (US) stock market covering the sample period from 2008:06 to 2020:12, we study the incremental predictive value of employee sentiment for the realized volatility of stock returns. In doing so, we control four different measures of investor sentiment and various macroeconomic and financial factors and uncertainties. We report results for several combinations of forecast horizons and estimation windows and find that employee sentiment contributes to forecast accuracy for several combinations.
3D printing, modelling and simulation for dental implant: A comprehensive review
Authors: Sahai Nitin , Sunil BDY , Chandrashekar Rakesh
Published: September 2024

The implementation of three-dimensional printing technology has revolutionised dentistry over the past decade. The desired object is scanned by a 3D scanner or built using computer-aided design (CAD)/computer-aided manufacturing (CAM) software. CAD designs of dental implants can be analysed by the finite element method (FEM). Finite element analysis (FEA) is done by discretising the geometrically developed model into smaller and simpler elements and analysing the 3D model using different boundary conditions on different nodes. Depending on the materials of choice, various printing methods are available, such as selective laser sintering (SLS), stereolithography, fused deposition modelling, and laminated object manufacturing. Dental implants are designed with the help of different biomaterials, such as polymers, metals, and ceramics. Clinicians should know the latest implant materials for successful implant therapy. This review article investigates 3D printing on various dental implants, designs, simulations, and limitations. The last part of the article discusses different properties of the implant materials used in the designs.
Investigation of the attributes of multi-walled carbon nanotubes in cryogenic environments after epoxy matrix curing
Authors: Nataraj Manikandan , Baskaran Babu , Ezhilvannan Rathinam , Nagaprasad Nagaraj , Krishnaraj Ramaswamy , Revathi V. , Vijay Krishna B. , Gupta Manish
Published: September 2024

The enhancement of mechanical properties in composite materials at cryogenic temperatures is a critical challenge addressed in this study, particularly targeting applications in aerospace engineering, such as the development of materials for spacecraft structures and in the storage and transportation of liquefied gases, representing a significant advancement in the field of cryogenic engineering materials. Using multi-walled carbon nanotubes (MWNTs) in epoxy matrixes, this study addresses a long-standing issue of poor interfacial adhesion while setting a new benchmark for composite mechanical performance under extreme conditions, focusing on the integration of MWNTs into epoxy resin matrixes. Poor interfacial adhesion between matrix and reinforcing nanomaterials results in up to 50% lower reinforcing efficiency than in composites without these interfacial challenges. Aerospace and cryogenic storage materials will become more durable and efficient by addressing this challenge. New research avenues are opened, particularly in developing advanced composite materials for extreme environments. The results of this study lay the groundwork for further investigation into the optimization of nanomaterial integration and novel material combinations, which could lead to breakthrough material science advancements. An ultrasonic dispersion technique is used to strengthen the interfacial bonding of MWNTs. The results demonstrate that optimal concentrations of MWNTs enhance the tensile strength, elongation at break, and fracture toughness of composites. A cryogenic mechanical property enhancement is achieved with MWNTs by epoxy-based composites. This study suggests that composite materials containing MWNTs could be used for cryogenic applications to improve mechanical integrity under extreme conditions. This offers a promising path to developing materials with cryogenic properties.
Thermal properties of Oreochromis fish scale powder-reinforced composites for sustainable engineering applications
Authors: Chennaiah Mallapuram Bala , Ravi Kumar K. , Sreenivasulu Reddy , Sharma Tarunika , Somaiah A. , Sastry M. Naga Phani , Kumar Pankaj
Published: September 2024

The investigation of Oreochromis fish scales (FS) as a sustainable and renewable resource for enhancing thermal properties in engineering applications forms the core objective of this work. Utilizing the FS powder as reinforcement within polymer matrices and focusing on creating composite materials by varying weight fractions (0%, 5%, 10%, and 15%) of FS powders. Through thermal properties, the research explores the thermal conductivity and heat resistance of these composite FS materials at temperatures ranging from 10∘ to 60∘C. The results showed the effect of incorporating different weight percentages of FS powders on the thermal performance of the composites, especially in the temperature range of 30∘C–45∘C. The findings are anticipated to provide valuable insights into the thermal properties of FS composite materials, presenting a sustainable and environmentally friendly alternative for engineering applications, particularly emphasizing thermal performance. These materials are used in various household and engineering applications for being sustainable and eco-friendly.
Harnessing geothermal energy in Hungary
Authors: Szanyi János D. , Kovács Balázs , Abdulhaq Hawkar A.
Published: September 2024

This paper provides a summary of the current status of geothermal energy utilization in Hungary, with a brief reference to geothermal potential. Approximately 1000 thermal wells are in operation, producing from two principal aquifers: carbonate aquifers (predominantly Mesozoic) and Upper Miocene siliciclastic aquifers. The utilization of geothermal energy in Hungary commenced with balneological exploitation, with documented evidence dating back to the Roman era. Of particular note is the city of Budapest, which has the distinction of being home to 16 thermal spas, a fact that has led to its designation as the spa capital of Europe. In the Hungarian portion of the Pannonian Superbasin, 26 municipalities have implemented geothermal district heating systems. Furthermore, geothermal energy plays a significant role in the agricultural sector, with approximately 300 thermal wells currently in operation. Nevertheless, the generation of geothermal electricity is still in its infancy, with only one operational geothermal power plant. However, based on the exploration permits submitted, there are significant prospects for further development. The same is true for ground source heat pumps, where there is considerable potential for growth, particularly in comparison with our neighbouring country's utilization. Recent research directions are promising, ranging from the use of geothermal energy from abandoned hydrocarbon wells as deep borehole heat exchangers, to the potential for extracting critical materials from thermal water, to exploring the possibility of underground heat storage. The favourable geothermal conditions in Hungary offer the potential to achieve up to 15–20 times the current production of 6.5 PJ, assuming the application of existing technologies. This presents a significant opportunity for the transition to a more sustainable energy source, particularly in the context of heating.
Dominant Point-Based Sequential and Parallel Algorithms for the Multiple Sequential Substring Constrained-LCS Problem
Authors: Bogning Tepiele Hermann , Kengne Tchendji Vianney , Akong Onabid Mathias , Myoupo Jean Frédéric , Nkonjoh Ngomade Armel
Published: September 2024

The Longest Common Subsequence (LCS) problem is a well-known and studied problem in computer science and bioinformatics. It consists in finding the longest subsequence that is common to two or more given sequences. In this article, we address the problem of finding all LCS for the Sequential Substring Constrained-LCS (SSCLCS) problem, called the Multiple SSCLCS problem. To solve this problem, we first propose a dominant point-based sequential algorithm, designed on a new Leveled Direct Acyclic Graph (DAG) that gives the correct evaluation order of subproblems to avoid redundancy due to overlap. Depending on whether the constraints may overlap or not, it requires

\(O(S|\Sigma |^{K+1}+r+n|\Sigma |)\)

and

\(O(S|\Sigma |^{K+1}+n|\Sigma |)\)

time with

\(O(Max\_level+n|\Sigma |)\)

space.
S
is the number of partial SSCLCS in a node,
K
is the number of DAG levels,
n
is the length of sequences,
r
is the total length of constraints,

\(Max\_level\)

is the number of nodes in the largest level of the DAG, and

\(|\Sigma |\)

is the length of the alphabet. Then, we derive a coarse-grained multicomputer parallel solution requiring

\(O(\tfrac{S|\Sigma |^{K+1}+r+n|\Sigma |}{p})\)

and

\(O(\tfrac{S|\Sigma |^{K+1}+n|\Sigma |}{p})\)

execution time,

\(O(Max\_level+n|\Sigma |)\)

memory space and

\(O(K)\)

communication rounds.
p
is the number of processors. Experimental results showed that the parallel algorithm is, respectively, 14.43× and 19.19× faster than the sequential algorithm on 32 and 64 processors.
Can You Tell Real from Fake Face Images? Perception of Computer-Generated Faces by Humans
Authors: Bozkir Efe , Riedmiller Clara , Skodras Athanassios N. , Kasneci Gjergji , Kasneci Enkelejda
Published: September 2024

With recent advances in machine learning and big data, it is now possible to create synthetic images that look real. Face generation is often of particular interest, as faces can be used for various purposes. However, improper use of such content can lead to the dissemination of false information, such as fake news, and thus pose a threat to society. This work studies whether people believe the truthfulness of faces using eye tracking and self-reports, including free-form textual explanations when participants encounter real and computer-generated faces. We used three different datasets for our evaluations, and our experimental results show that while people are relatively better at identifying the truthfulness of real faces and faces generated by earlier machine learning algorithms with different gazing behaviors in viewing and rating phases, they perform less accurately when deciding the truthfulness of synthetic face images that are generated by newer algorithms. Our findings provide important insights for society and policymakers.
Maximum Cardinality
f
-Matching in Time
O
(
n
2/3
m
)
Authors: Gabow Harold N.
Published: September 2024

We present an algorithm that finds a maximum cardinality

\(f\)

-matching of a simple graph in time

\(O(n^{2/3}m)\)

. Here,

\(f:V\to\mathbb{N}\)

is a given function and an

\(f\)

-matching is a subgraph wherein each vertex

\(v\in V\)

has degree

\(\leq f(v)\)

. This result generalizes a string of algorithms that concentrate on simple bipartite graphs. The bipartite case is based on the notion of level graph, introduced by Dinic for network flow. In general graphs this notion breaks down: Vertices no longer have unique levels, and there are too many levels to analyze the corresponding level graph like bipartite graphs (

\(\Theta(n^{2})\)

vs.

\(n\)

). We use “natural” levels to prove properties of shortest augmenting trails (e.g., formulas for trail length). We use “shortened” levels to derive the algorithm’s time bound.

The algorithm, unmodified, is also efficient on multigraphs, achieving time

\(O(\min\{\sqrt{f(V)},n\} m)\)

for

\(f(V)=\sum_{v}f(v)\)

. The special case

\(f\equiv 1\)

shows the algorithm duplicates the classic time bound for maximum cardinality matching,

\(O(\sqrt{n} m)\)

.
COSMO: Dynamic Uploading Scheduling in mmWave-Based Sensor Networks with Mobile Blockers
Authors: Sun Yifei , Lv Bojie , Tan Haisheng , Wang Rui , Lau Francis
Published: September 2024

Wireless sensor networks (WSNs) leveraging millimeter wave (mmWave) communication for bandwidth-demanding applications is considered in this article. Despite the large bandwidth, the delivery of delay-sensitive information collected by sensors may still face significant latency due to the vulnerability to intermittent link blockage. Hence, the guarantee of low age of information (AoI) in mmWave WSNs is not straightforward. In this article, the wireless sensing and dynamic programming techniques are jointly exploited to relieve the above issue. The former tracks the human blockers and predicts the chance of link blockage; the latter optimizes the transmission of multiple sensors based on the prediction. Particularly, the long-term optimization of sampling, uplink time and power allocation policies in a sensor network can be formulated as an infinite-horizon Markov decision process (MDP) with discounted cost, where the state transition probabilities can be predicted via wireless sensing. A novel low-complexity solution framework, namely COSMO, with a guaranteed performance in the worst case, is proposed. Simulations show that compared with heuristic benchmarks, benefiting from the prediction of the link blockage, COSMO can significantly suppress the average system cost, which consists of both AoI and energy consumption.
ZNF197-AS1/miR-425/GABARAPL1 axis: a novel regulatory mechanism in uveal melanoma
Authors: Zhang Chao , Wu Shuai
Published: September 2024

This study identifies the ZNF197-AS1/miR-425/GABARAPL1 axis as a novel regulatory mechanism in uveal melanoma. ZNF197-AS1 upregulates GABARAPL1 by sponging miR-425, inhibiting UM cell proliferation, migration, and invasion. This discovery highlights a potential therapeutic target, providing new insights into UM progression and patient outcomes.
Exercise and tumor proteome: insights from a neuroblastoma model
Authors: Plaza-Florido Abel , Gálvez Beatriz G. , López Juan A. , Santos-Lozano Alejandro , Zazo Sandra , Rincón-Castanedo Cecilia , Martín-Ruiz Asunción , Lumbreras Jorge , Terron-Camero Laura C. , López-Soto Alejandro , Andrés-León Eduardo , González-Murillo África , Rojo Federico , Ramírez Manuel , Lucia Alejandro , Fiuza-Luces Carmen
Published: September 2024

We used liquid chromatography with tandem mass spectrometry to explore the impact of a 5-wk exercise intervention on the tumor proteome profile in a mouse model of one of the most aggressive childhood malignancies, high-risk neuroblastoma. Exercise altered the abundance of hundreds of proteins and pathways, particularly those involved in energy metabolism and tumor suppression. These molecular changes could mediate, at least partly, the potential antitumorigenic effects of exercise.
Analysis of Concrete Dam Deformation Prediction Based on the ResNet‐GRU‐SGWO Model
Authors: Ma Ning , Niu Xiubo , Chen Xunhui , Wei Wenxiu , Zhang Ye , Kang Xinyu , Zhong Wen , Wu Jing
Published: September 2024

Concrete dam deformation prediction plays a crucial role in ensuring dam safety monitoring. Machine learning, especially recurrent neural networks, plays an important role in this, yet its predictive accuracy is not high. This paper first preprocesses time series data using successive variational mode decomposition (SVMD). Then, it combines residual network (ResNet) and gate recurrent unit (GRU), fully leveraging the excellent information extraction capability of the former and the powerful sequential data processing capability of the latter, proposing the ResNet‐GRU model for deformation prediction analysis. During the prediction process, the sanitized gray wolf optimizer (SGWO) algorithm adjusts the parameters, further enhancing the prediction accuracy and performance of the model. The model has also been successfully applied in practical cases, validating its effectiveness. The results indicate that the ResNet‐GRU‐SGWO model can accurately simulate the dynamic deformation process of concrete dams. Compared with various intelligent prediction models, it achieves the highest prediction accuracy and outstanding performance, providing a reference for the prediction of concrete dam deformation.
An Analytical Approach to the New Solution of Family of Kuramoto Sivashinsky Equation by q‐Homotopy Analysis Technique
Authors: Shah Abdullah , Hussain Safdar
Published: September 2024

The current work aims to study a new analytical solution method for a family of Kuramoto–Sivashinsky equation (KSE). For this purpose, we implement the q‐homotopy analysis method (q‐HAM), a method extensively used due to its easy implementation, fast convergence, and presence of convergence‐controlling parameters. This method does not require any transformation, linearization, or discretization. The applied method offers a well‐convergent series solution. Results are obtained for some fixed values of physically significant parameters involved in the mathematical model. The computed results are compared with the travelling wave solutions and are illustrated graphically and in tabulated form for absolute error estimation. The comparison reveals the q‐HAM provides better results than the existing methods.
The Effect of Converting a Conventional Tractor into a Hybrid Drive Tractor Using the ECMS Method on Fuel Consumption and Emissions
Authors: Ozturk Mirac , Sandalci Tarkan , Buyuk Cihan , Guclu Mustafa , Karagoz Yasin
Published: September 2024

In recent years, the implementation of Tier 5 emission regulations for tractors has compelled manufacturers to conduct new research. Additionally, the process of hybridization has impacted the agricultural vehicle industry. This study focuses on the design and implementation of an energy management strategy (EMS) for a diesel–electric hybrid electric agricultural vehicle, based on real‐time optimization. Tractor drive systems, including both conventional and hybrid options, were introduced. Simulations were performed to compare fuel consumption and CO2 emissions between the two types of tractors. The data shows that hybrid vehicles produce 8.93% less CO2 than conventional vehicles. Furthermore, the fuel consumption of the tractor decreased from 1,880.2 to 1,712.5 g/km under hybrid operating conditions.
Transition Metal Dichalcogenides as Effective Dopants in Nanofiber‐Based Triboelectric Nanogenerators
Authors: Karabiber Abdulkerim , Dirik Ömer , Okbaz Abdulkerim , Yar Adem , Özen Abdurrahman , Özel Faruk
Published: September 2024

Triboelectric nanogenerators (TENGs) are advanced energy harvesters that convert mechanical energy in diverse environments into electrical energy via static electrification and electrostatic induction. However, their performance needs to be improved to expand their area of use and become more practical. In this study, we introduced molybdenum disulfide (MoS2) and tungsten disulfide (WS2) as separate additives into polyacrylonitrile (PAN) to produce composite nanofibers via electrospinning, aiming to increase the electrical output of the TENGs. This method increased contact area by narrowing the nanofiber diameters, which is a key factor in enhancing the triboelectric effect. The incorporation of MoS2 or WS2, characterized by high specific surface area, interface polarization, quantum confinement effects, and strong electron acceptance and trapping capabilities, led to a significant increase in the dielectric constant and overall electrical performance of the TENGs. Experimental evaluations, connecting the TENGs to circuits with various resistive loads, determined optimal performance at a load resistance of 4.7 MΩ. In particular, the 5 wt% WS2@PAN & polyvinylbutral (PVB) and 5 wt% MoS2@PAN & PVB TENGs exhibited a remarkable peak power output of 40.5 mW, corresponding to a power density of 25.3 W/m2 and provided open circuit voltage of 1,026 V. The integration of 5 wt% MoS2 or 5 wt% WS2 led to more than a twofold increase in electrical power density compared to pristine PAN. These outcomes demonstrate the significant impact of transition metal dichalcogenides in enhancing the energy conversion efficiency of contact–separation mode TENGs, thereby contributing to the advancement of energy harvesting technology.
Consensus for the Development of a New Early Warning Score for Predicting Patients’ Clinical Deterioration in Angola: A Delphi Study
Authors: Tomás Esmael , Escoval Ana , Antunes Maria Lina
Published: September 2024

Background: Nearly 30 years since its inception, the early warning scores (EWSs) remain pivotal, yet variations have emerged for hospital and prehospital use. Aggregated scores, reflecting multiple physiological parameters, outperform single‐parameter systems in assessing acute illness severity, though consensus on optimal approaches is lacking. Resource‐limited countries, including Angola, lack adapted EWSs, emphasizing the need for cost‐effective and adaptable solutions to enhance patient care.

Objective: To explore the perspectives of Angolan experts to identify physiological parameters suitable for incorporation into existing EWSs, allowing the development of a new tool adjusted to the healthcare context in Angola.

Methods: We conducted a three‐round Delphi survey, engaging a national expert panel comprising twenty‐five physicians and nurses with expertise in internal medicine, surgery, emergency rooms, intensive care units, and/or teachers at universities or at teaching courses in these fields. Participants were asked to rate items using a five‐point Likert scale. Consensus was achieved if the items received a rating ≥ 80% from the panel.

Results: Consensus was evident for the inclusion of standard physiological parameters, such as systolic blood pressure, heart rate, respiratory rate, temperature, oxygen saturation, neurological status, and the presence or absence of supplemental oxygen. Furthermore, there was consensus for the consideration of specific items, namely, seizures, jaundice, cyanosis, capillary refill time, and pain—typically not included in the current EWSs. Consensus was reached regarding the exclusion of both oxygen saturation and temperature measurements in healthcare settings where oximeters and thermometers might not be readily available.

Conclusion: Angolan experts were able to identify the physiological parameters suitable for incorporation into the basic EWSs. Further study must be conducted to test and validate the impact of the newly suggested vital parameters on the discriminant and predictive capability of a new aggregated model specifically adjusted to the Angolan healthcare setting.
The Immune-Related 27-Gene Signature DetermaIO Predicts Response to Neoadjuvant Atezolizumab plus Chemotherapy in Triple-Negative Breast Cancer
Authors: Dugo Matteo , Huang Chiun-Sheng , Egle Daniel , Bermejo Begoña , Zamagni Claudio , Seitz Robert S. , Nielsen Tyler J. , Thill Marc , Antón-Torres Antonio , Russo Stefania , Ciruelos Eva Maria , Schweitzer Brock L. , Ross Douglas T. , Galbardi Barbara , Greil Richard , Semiglazov Vladimir , Gyorffy Balázs , Colleoni Marco , Kelly Catherine M. , Mariani Gabriella , Del Mastro Lucia , Blasi Olivia , Callari Maurizio , Pusztai Lajos , Valagussa Pinuccia , Viale Giuseppe , Gianni Luca , Bianchini Giampaolo
Published: September 2024

Purpose:

We assessed the 27-gene RT-qPCR–based DetermaIO assay and the same score calculated from RNA sequencing (RNA-seq) data as predictors of sensitivity to immune checkpoint therapy in the neoTRIPaPDL1 randomized trial that compared neoadjuvant carboplatin/nab-paclitaxel chemotherapy (CT) plus atezolizumab with CT alone in stage II/III triple-negative breast cancer. We also assessed the predictive function of the immuno-oncology (IO) score in expression data of patients treated with pembrolizumab plus paclitaxel (N = 29) or CT alone (N = 56) in the I-SPY2 trial.

Experimental Design:

RNA-seq data were obtained from pretreatment core biopsies from 242 (93.8%) of the 258 patients in the per-protocol-population. The DetermaIO RT-qPCR test, performed in the CAP/CLIA-accredited laboratory of Oncocyte Corp., was available for 220 patients (85.3%). A previously established threshold was used to assign DetermaIO-positive versus DetermaIO-negative status. Publicly available microarray data were used from I-SPY2.

Results:

IO scores calculated from RNA-seq and RT-qPCR data were highly concordant. In neoTRIPaPDL1, DetermaIO-positive cancers (N = 92, 41.8%) had pathologic complete response (pCR) rates of 69.8% and 46.9% in the CT + atezolizumab and CT arms, respectively. In DetermaIO-negative cases, pCR rates were similar in both arms (44.6% vs. 49.2%; interaction test P = 0.04). PDL1 protein expression and stromal tumor–infiltrating lymphocyte count were not predictive of differential benefit from atezolizumab. In I-SPY2, IO-positive cancers (45.9%) had pCR rates of 85.7% and 16%, with and without immunotherapy, respectively. In IO-negative cancers, pCR rates were 46.7% versus 16.1%.

Conclusions:

DetermaIO identified patients who benefited from neoadjuvant immunotherapy resulting in improved pCR rate, independently of PDL1.
The Role of Online Well-Being Therapy in Overcoming Allostatic Overload in Medical Workers: A Pilot Randomized Controlled Study
Authors: Liu Xiaolei , Song Penghui , Yin Lu , Wang Kun , Zhu Boheng , Huang Xiaomin , Niu Yanyan , Leng Haixia , Xue Qing , Peng Mao , Min Baoquan , Shangguan Fangfang , Zhang Peiran , Zhao Wenfeng , Wang Huang , Lv Jing , Yang Mei , Wang Ping , Li Dongning , Gao Xiaoling , Feng Kun , Yun Keming , Cosci Fiammetta , Wang Hongxing
Published: September 2024

Introduction: Stress may lead to allostatic overload. Well-being therapy (WBT) might mitigate it by enhancing psychological well-being and protecting from psychological symptoms. Since no reports are available on the use of WBT in allostatic overload, we evaluated online WBT effects in reducing allostatic overload in medical workers during the coronavirus pandemic. Methods: Sixty-six participants with allostatic overload were enrolled and randomly assigned to eight sessions of online WBT (n = 32) or eight sessions of an online psychoeducation program on healthy lifestyle (CON) (n = 34). The primary outcome was the prevalence rate of allostatic overload in the two groups at session 8 (T2). Secondary analyses were performed on changes in the PsychoSocial Index (PSI) and Psychological Well-Being (PWB) scales scores at the same time points. Generalized estimating equation models were employed. Results: The WBT group showed a significantly lower rate of allostatic overload at T2 than the CON group (28.13% vs. 70.59%, p < 0.001); similar results were found at T1, T3, and T4 (p < 0.001). Compared to CON, WBT produced a significant decrease in psychological distress (p < 0.001) and abnormal illness behavior (p = 0.031), as well as a significant improvement in PWB autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance (p < 0.001). Conclusion: Online WBT may be an effective non-pharmacological therapeutic strategy for individuals with allostatic overload. These findings need to be further validated in different clinical populations.
Blood Urea Nitrogen to Left Ventricular Ejection Ratio as a Predictor of Short-Term Outcome in Acute Myocardial Infarction Complicated by Cardiogenic Shock
Authors: Xie Linfeng , Li Yuanzhu , Chen Jing , Luo Suxin , Huang Bi
Published: September 2024

Introduction: Cardiogenic shock (CS) is the most critical complication after acute myocardial infarction (AMI) with mortality above 50%. Both blood urea nitrogen and left ventricular ejection fraction were important prognostic indicators. We aimed to evaluate the prognostic value of admission blood urea nitrogen to left ventricular ejection fraction ratio (BUNLVEFr) in patients with AMI complicated by CS (AMI-CS). Methods: 268 consecutive patients with AMI-CS were divided into two groups according to the admission BUNLVEFr cut-off value determined by Youden index. The primary endpoint was 30-day all-cause mortality and the secondary endpoint was the composite events of major adverse cardiovascular events (MACEs). Cox proportional hazard models were performed to analyze the association of BUNLVEFr with the outcome. Results: The optimal cut-off value of BUNLVEFr is 16.63. The 30-day all-cause mortality and MACEs in patients with BUNLVEFr≥16.63 was significantly higher than in patients with BUNLVEFr<16.63 (30-day all-cause mortality: 66.2% vs. 17.1%, p < 0.001; 30-day MACEs: 80.0% vs. 48.0%, p < 0.001). After multivariable adjustment, BUNLVEFr≥16.63 remained an independent predictor for higher risk of 30-day all-cause mortality (HR = 3.553, 95% CI: 2.125–5.941, p < 0.001) and MACEs (HR = 2.026, 95% CI: 1.456–2.820, p < 0.001). Subgroup analyses found that the effect of BUNLVEFr was consistent in different subgroups (all p-interaction>0.05). Conclusion: The admission BUNLVEFr provided important prognostic information for AMI-CS patients.
Artificial Intelligence for Contrast-Enhanced Ultrasound of the Liver: A Systematic Review
Authors: Brooks James A. , Kallenbach Michael , Radu Iuliana-Pompilia , Berzigotti Annalisa , Dietrich Christoph F. , Kather Jakob N. , Luedde Tom , Seraphin Tobias P.
Published: September 2024

Introduction: The research field of artificial intelligence (AI) in medicine and especially in gastroenterology is rapidly progressing with the first AI tools entering routine clinical practice, for example, in colorectal cancer screening. Contrast-enhanced ultrasound (CEUS) is a highly reliable, low-risk, and low-cost diagnostic modality for the examination of the liver. However, doctors need many years of training and experience to master this technique and, despite all efforts to standardize CEUS, it is often believed to contain significant interrater variability. As has been shown for endoscopy, AI holds promise to support examiners at all training levels in their decision-making and efficiency. Methods: In this systematic review, we analyzed and compared original research studies applying AI methods to CEUS examinations of the liver published between January 2010 and February 2024. We performed a structured literature search on PubMed, Web of Science, and IEEE. Two independent reviewers screened the articles and subsequently extracted relevant methodological features, e.g., cohort size, validation process, machine learning algorithm used, and indicative performance measures from the included articles. Results: We included 41 studies with most applying AI methods for classification tasks related to focal liver lesions. These included distinguishing benign versus malignant or classifying the entity itself, while a few studies tried to classify tumor grading, microvascular invasion status, or response to transcatheter arterial chemoembolization directly from CEUS. Some articles tried to segment or detect focal liver lesions, while others aimed to predict survival and recurrence after ablation. The majority (25/41) of studies used hand-picked and/or annotated images as data input to their models. We observed mostly good to high reported model performances with accuracies ranging between 58.6% and 98.9%, while noticing a general lack of external validation. Conclusion: Even though multiple proof-of-concept studies for the application of AI methods to CEUS examinations of the liver exist and report high performance, more prospective, externally validated, and multicenter research is needed to bring such algorithms from desk to bedside.
Language Learning, Representation, and Processing in Humans and
Machines: Introduction to the Special Issue
Authors: Apidianaki Marianna , Fourtassi Abdellah , Padó Sebastian
Published: September 2024

Large Language Models (LLMs) and humans acquire knowledge about language without direct supervision. LLMs do so by means of specific training objectives, while humans rely on sensory experience and social interaction. This parallelism has created a feeling in NLP and cognitive science that a systematic understanding of how LLMs acquire and use the encoded knowledge could provide useful insights for studying human cognition. Conversely, methods and findings from the field of cognitive science have occasionally inspired language model development. Yet, the differences in the way that language is processed by machines and humans—in terms of learning mechanisms, amounts of data used, grounding and access to different modalities—make a direct translation of insights challenging. The aim of this edited volume has been to create a forum of exchange and debate along this line of research, inviting contributions that further elucidate similarities and differences between humans and LLMs.
Musical Color Harmony: Application of the Principles of Musical Harmony to Produce Color Hue Sets
Authors: Cianci Philip J
Published: September 2024

Although numerous metaphysicians, philosophers, scientists, poets, artists, and musicians have speculated on the existence of a relationship between color and music for over 2000 years, the establishment of a correlation between color and musical harmony has been elusive. The author describes a framework, Musical Color Hue Harmony (MCHH), that correlates musical and color harmonic consonance and dissonance by applying the physics of aural harmonic resonance and theories of musical harmony to produce sets of “harmonious” color hues based on the mathematically defined frequency relationships between two or more musical pitches. The methodology is applicable to any musical tuning system and any color hue wheel configuration. Color attributes of brightness/luminance and saturation/chroma are presently beyond the scope of the framework.