bluuebunny/crossref_metadata_2025 huggingface dataset:
Large language models and bariatric surgery patient education: a comparative readability analysis of GPT-3.5, GPT-4, Bard, and online institutional resources
Authors: Srinivasan Nitin , Samaan Jamil S. , Rajeev Nithya D. , Kanu Mmerobasi U. , Yeo Yee Hui , Samakar Kamran
Published: March 2024

Background

The readability of online bariatric surgery patient education materials (PEMs) often surpasses the recommended 6th grade level. Large language models (LLMs), like ChatGPT and Bard, have the potential to revolutionize PEM delivery. We aimed to evaluate the readability of PEMs produced by U.S. medical institutions compared to LLMs, as well as the ability of LLMs to simplify their responses.

Methods

Responses to frequently asked questions (FAQs) related to bariatric surgery were gathered from top-ranked health institutions. FAQ responses were also generated from GPT-3.5, GPT-4, and Bard. LLMs were then prompted to improve the readability of their initial responses. The readability of institutional responses, initial LLM responses, and simplified LLM responses were graded using validated readability formulas. Accuracy and comprehensiveness of initial and simplified LLM responses were also compared.

Results

Responses to 66 FAQs were included. All institutional and initial LLM responses had poor readability, with average reading levels ranging from 9th grade to college graduate. Simplified responses from LLMs had significantly improved readability, with reading levels ranging from 6th grade to college freshman. When comparing simplified LLM responses, GPT-4 responses demonstrated the highest readability, with reading levels ranging from 6th to 9th grade. Accuracy was similar between initial and simplified responses from all LLMs. Comprehensiveness was similar between initial and simplified responses from GPT-3.5 and GPT-4. However, 34.8% of Bard's simplified responses were graded as less comprehensive compared to initial.

Conclusion

Our study highlights the efficacy of LLMs in enhancing the readability of bariatric surgery PEMs. GPT-4 outperformed other models, generating simplified PEMs from 6th to 9th grade reading levels. Unlike GPT-3.5 and GPT-4, Bard’s simplified responses were graded as less comprehensive. We advocate for future studies examining the potential role of LLMs as dynamic and personalized sources of PEMs for diverse patient populations of all literacy levels.
The role of the waste sector in the sustainable development goals and the IPCC assessment reports
Authors: Kopecká Romana , Hrad Marlies , Huber-Humer Marion
Published: March 2024

The management of waste plays a pivotal role in achieving the Sustainable Development Goals (SDGs) set by the United Nations through both direct and indirect linkages. Directly, waste management issues are addressed in four SDGs (6, 11, 12, 14), while landfilling issues are only mentioned in SDG 6 reflecting water quality in connection with waste dumping. However, inadequate management and disposal of waste pose environmental, health and safety risks; thereby undermining more SDGs. Indirectly, waste management and landfilling influence various SDGs ranging from 4 to all 17 SDGs depending on the literature reference.

Although not directly addressed in SDG 13 (Climate action), the waste sector contributes to climate change, with the biggest share of greenhouse gases emitted from landfills and waste dumps. According to the latest assessment report by the IPCC (Intergovernmental Panel on Climate Change), waste management—and thereby mainly landfills—are responsible for 64 Mt of CH4 per year worldwide.

A waste-related assessment of the IPCC report series from 1990 to 2023 revealed a paradigm shift in the covered waste management strategies, transitioning from conventional technical disposal methods towards holistic approaches that align with the principles of sustainability encapsulated in the SDGs. The focus in the reports moves upwards the “waste management hierarchy”, fostering circular economy. Indirectly, this leads to seemingly less focus on landfills and waste dumps despite their high share of greenhouse gas emissions and particularly their strong representation in low/lower middle-income countries, which is still expected to increase during the next years.
Multinational Association of Supportive Care in Cancer (MASCC) expert opinion/guidance on the use of clinically assisted hydration in patients with advanced cancer
Authors: Hayes Jo , Bruera Eduardo , Crawford Gregory , Fleury Mapi , Santos Marcos , Thompson Jo , Davies Andrew
Published: March 2024

Purpose

The provision of clinically assisted hydration (CAH) in patients with advanced cancer is controversial, and there is a paucity of specific guidance and so a diversity in clinical practice. Consequently, the Palliative Care Study Group of the Multinational Association of Supportive Care in Cancer (MASCC) formed a sub-group to develop evidence-based guidance on the use of CAH in patients with advanced cancer.

Methods

This guidance was developed in accordance with the MASCC Guidelines Policy. A search strategy for Medline was developed, and the Cochrane Database of Systematic Reviews and the Cochrane Central Register of Controlled Trials were explored for relevant reviews/trials, respectively.

Results

Due to the paucity of evidence, the sub-group was not able to develop a prescribed guideline, but was able to generate a number of “expert opinion statements”: these statements relate to assessment of patients, indications for CAH, contraindications for CAH, procedures for initiating CAH, and reassessment of patients.

Conclusions

This guidance provides a framework for the use of CAH in advanced cancer, although every patient requires individualised management.
Unsupervised domain adaptation of dynamic extension networks based on class decision boundaries
Authors: Chen Yuanjiao , Wang Diao , Zhu Darong , Xu Zhe , He Bishi
Published: March 2024

In response to the problems of inaccurate feature alignment, loss of source domain information, imbalanced sample distribution, and biased class decision boundaries in traditional unsupervised domain adaptation methods, this paper proposes a class decision boundary-based dynamic expansion network unsupervised domain adaptation method called CDE-Net. Specifically, our method dynamically expands the autoencoder-based network structure, which can preserve source domain feature information while gradually adapting to the target domain data distribution and learning useful feature information from the target domain. Meanwhile, by minimizing clustering loss and conditional entropy loss, CDE-Net can explore the intrinsic structure of the data and push class decision boundaries away from dense data areas. We experimentally verify our method on three medical image datasets, chest X-rays, intracranial hemorrhage, and mammography, and achieve an average AUC improvement of 25.8% or more compared to non-transfer methods. In addition, we compare our method with previous unsupervised domain adaptation methods, and the experimental results show that our method achieves better classification accuracy and generalization performance.
Mental and physical health in children of women with a history of anorexia nervosa
Authors: Dobrescu Sandra Rydberg , Dinkler Lisa , Gillberg Carina , Gillberg Christopher , Råstam Maria , Wentz Elisabet
Published: March 2024

Few studies have investigated the offspring of women with anorexia nervosa (AN). The aim of this study was to examine perinatal status, mental and physical health in the offspring of mothers with a history of AN. Fifty-one individuals with adolescent-onset AN and 51 matched controls (COMP) have been followed prospectively. Presently, 30 years after AN onset, at a mean age of 44 years, female participants who had given birth (nAN = 40, nCOMP = 40) were interviewed regarding psychiatric health in their offspring using the Developmental and Well-Being Assessment and the MINI International Neuropsychiatric Interview. In addition, information on the offspring’s perinatal status, psychiatric- and physical health was obtained from the Swedish Medical Birth Register and The Swedish National Patient Register. Data regarding mental and physical health were available for 83 and 86 offspring in the AN and COMP groups, respectively. At birth, all of weight, length, head circumference and ponderal index were significantly reduced in the offspring of mothers with a history of AN. In adolescence, parental interviews indicated an overrepresentation of current psychiatric diagnoses in the offspring of mothers with AN. Compared with the offspring in the COMP group, endocrinological, immune and metabolic disorders were much more common in the offspring of the AN group. In conclusion, a history of AN increases the risk of worse perinatal outcome of the offspring. Later on, in childhood and adolescence, psychiatric and physical morbidity may be overrepresented in the offspring of women with AN.
Structural fluctuations in thin cohesive particle layers in powder-based additive manufacturing
Authors: Roy Sudeshna , Xiao Hongyi , Angelidakis Vasileios , Pöschel Thorsten
Published: March 2024

Producing dense and homogeneous powder layers with smooth free surface is challenging in additive manufacturing, as interparticle cohesion can strongly affect the powder packing structure and therefore influence the quality of the end product. We use the Discrete Element Method to simulate the spreading process of spherical powders and examine how cohesion influences the characteristics of the packing structure with a focus on the fluctuation of the local morphology. As cohesion increases, the overall packing density decreases, and the free surface roughness increases, which is calculated from digitized surface height distributions. Local structural fluctuations for both quantities are examined through the local packing anisotropy on the particle scale, obtained from Voronoï tessellation. The distributions of these particle-level metrics quantify the increasingly heterogeneous packing structure with clustering and changing surface morphology.
Place attachment, storms, and climate change in the Faroe Islands
Authors: Kongsager Rico , Baron Nina
Published: March 2024

Globally, people have always had to deal with climate-related hazards, and in the majority of places, they have adapted gradually. However, these gradual adaptations may not be enough to withstand the expected intensity of climate-related hazards in the future. In this paper, our focus is on the effect of storms in the Faroe Islands. The islands are highly exposed to storms, which are projected to increase in intensity and potentially also in frequency in this region. The islands are characterized by being small, remote, and with a rough terrain, which makes it difficult for external actors to provide assistance. As a result, the civilian population—especially in the outer regions—often have to deal with storms and their consequences themselves. The geographical focus in this paper is the Northern Islands, and in particular the communities of Viðareiði and Hvannasund. The approach applied is qualitative, and the central question this paper tries to answer is how aspects of place attachment (social, physical, functional) affect the way in which the local population handle storms. The findings show communities that are impacted by storms, but also that their previous experiences with storms have led to an improved adaptation level, which today enables them to cope with more severe storms. The attachment they have to where they live will assist them in coping with future storms, although it can also be a hindrance to the implementation of the necessary adaptation and preparedness measures, since they presume that they are already safe.
Long-Run Linkages Between us Stock Prices and Cryptocurrencies: A Fractional Cointegration Analysis
Authors: Caporale Guglielmo Maria , de Dios Mazariegos José Javier , Gil-Alana Luis A.
Published: March 2024

This paper applies fractional integration and cointegration methods to examine respectively the univariate properties of the four main cryptocurrencies in terms of market capitalization (BTC, ETH, USDT, BNB) and of four US stock market indices (S&P500, NASDAQ, Dow Jones and MSCI for emerging markets) as well as the possible existence of long-run linkages between them. Daily data from 9 November 2017 to 28 June 2022 are used for the analysis. The results provide evidence of market efficiency in the case of the cryptocurrencies but not of the stock market indices considered. The results also indicate that in most cases there are no long-run equilibrium relationships linking the assets in question, which implies that cryptocurrencies can be a useful tool for investors to diversify and hedge when required in the case of the US markets.
Bainite Formation in a Carbon-Free Fe–Cr–N System
Authors: König Philip , Lentz Jonathan , Weber Sebastian
Published: March 2024

In order to promote the understanding of bainitic transformation in nitrogen alloyed steels, the microstructure, transformation kinetics, and diffusion/precipitation characteristics of an isothermally heat-treated carbon-free system Fe–5Cr–N were investigated. Quenching dilatometry was used to perform heat treatments at temperatures between 400 °C and 500 °C and simultaneously receive information about the transformation kinetics. Scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) investigations indicate a plate- to lenticular-like, fully ferritic microstructure with nanometer scale CrN. In order to analyze the diffusion and precipitation behavior of nitrogen, atom probe tomography measurements were performed. On the one hand, nitrogen segregation was found, and on the other hand, the presence of CrN precipitates and preliminary stages of CrN nitrides were validated.
Complex Symmetry of Linear Combinations of Composition Operators on the McCarthy–Bergman Space of Dirichlet Series
Authors: Huang Cheng-shi , Jiang Zhi-jie
Published: March 2024

The complex symmetric linear combinations of composition operators on the McCarthy–Bergman spaces of Dirichlet series are completely characterized. The normality and self-adjointness of complex symmetric linear combinations of composition operators on such spaces are also characterized. Some images are given in order to find some interesting phenomena of $${\mathcal {J}}$$
J
-symmetric such combinations.
A numerical investigation of the influence of ozone on combustion to improve the performance of spark ignition engines
Authors: D’Amato Marco , Cantiani Antonio , Basso Angelo , Magi Vinicio , Viggiano Annarita
Published: March 2024

The aim of this work is to exploit the influence of using ozonized air to achieve stable and efficient combustion of lean mixtures in a gasoline-fuelled Spark-Ignition (SI) engine. The influence of ozone on the combustion of near-stoichiometric mixtures, which are typical of SI engines, has also been assessed. A Computational Fluid Dynamics (CFD) model has been employed to simulate compression, combustion, and expansion of a spark ignition, axisymmetric engine fuelled with iso-octane/air/ozone mixtures. The aim is to assess how ozone improves the engine performance under different engine speeds, ignition timings and equivalence ratios. The model has been validated against experimental data available in the literature. Parametric analyses have been carried out by considering three values of engine speeds (800, 1000 and 1200 rpm), three different ozone concentrations at Intake Valve Closure (IVC) (0, 100 and 200 ppm) and two equivalence ratios (0.9 and 0.7). The results show that ozone enables reactions in the Low Temperature Combustion (LTC) regime, modifies the mixture chemical composition and the auto-ignition tendency. Specifically, for all the cases under examination, the addition of ozone to the air/fuel mixture reduces the combustion duration, leading to an increase in terms of work output and a reduction of the specific fuel consumption. Moreover, the advantage of using ozone is greater for lean mixtures than for near-stoichiometric mixtures. Finally, for the near-stoichiometric cases, when the residence time of the mixture is high enough, auto-ignition occurs in the end gases.
Bevacizumab improved prognosis for advanced EGFR-mutant lung adenocarcinoma with brain metastasis receiving cerebral radiotherapy
Authors: Zhou Yuanliang , Li Jingchao , Li Yankang , Deng Guangchuan , Wang Qi , Qin Hongyue , Li Jianbin , Li Zhenxiang
Published: March 2024

Objective

This study aimed to determine whether the combined use of bevacizumab could improve overall survival (OS) in patients with brain metastasis (BM), epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) undergoing cerebral radiotherapy.

Materials and methods

A total of 237 patients with EGFR-mutant lung adenocarcinoma and BM met the inclusion criteria for this retrospective study, including 102 patients in the bevacizumab treatment group and 135 in the non-bevacizumab group. The Kaplan–Meier method was used for survival analysis. Univariate and multivariate analyses were performed to identify EGFR-mutated BM prognostic factors for these patients.

Results

At the end of the last follow-up period, 176 patients (74.3%) had died, and the median overall survival (OS) was 34.2 months. We observed a significant difference in the median OS between the bevacizumab and non-bevacizumab groups (45.8 months vs 30.0 months, P < 0.0001). Among the 178 (75.1%) patients who received cerebral radiotherapy, the median OS of patients in the bevacizumab + cerebral radiotherapy group was 45.8 months versus 32.0 months in the non-bevacizumab + cerebral radiotherapy group, respectively (P = 0.0007). Patients treated with bevacizumab after cerebral radiotherapy had a longer median OS than patients treated with bevacizumab before cerebral radiotherapy (59.4 months vs 33.7 months, P = 0.0198). In the univariate analysis, smoking status, Lung-molGPA scores, and bevacizumab therapy showed correlations (HR = 1.450, P = 0.045; HR = 0.700, P = 0.023; HR = 0.499, P < 0.001). Multivariate analysis showed that bevacizumab therapy alone (hazard ratio [HR] = 0.514; P < 0.001) was independently associated with improved OS.

Conclusion

In patients with BM from EGFR-mutated NSCLC, cerebral radiotherapy with bevacizumab markedly improved OS. This improvement was more evident after cerebral radiotherapy.
Sleep, depression, anxiety, stress and circadian preferences among women in the third trimester. Are these variables related to mother’s expectations about their child’s sleep?
Authors: Manková Denisa , Švancarová Soňa , Štenclová Eliška
Published: March 2024

Pregnancy is a period of significant physical and psychological changes. Pregnant women often struggle with poor sleep quality which can increase the risk of developing depression and anxiety. Additional factors can affect sleep quality and vice versa. We focused on an understudied topic: pregnant women`s expectations about how their infant will sleep. This study aims to describe the potential correlates and predictors of women`s sleep quality and their expectations about child sleep in a broader context. In total, 250 women participated in the research. Participants completed questionnaires PSQI, MEQ, DASS-21 and BISQ-R. To verify the set aims, we used Pearson’s correlation coefficient, t-test and general linear model (GLM), including methods for determining the effect size (Hedges’ g, r2, ε2). The results showed that sleep quality is related to circadian preference, depression, anxiety and stress. Women with poor sleep quality were more evening type and scored higher on these variables. Anxiety, circadian preference and the week of pregnancy were the most significant predictors of sleep quality. Women with at least one child and women who did not prepare for childbirth and motherhood and had not encountered information about a child’s sleep scored higher in BISQ-R. A hypothesis can be put forward that sufficient information before childbirth and earlier maternal experiences can affect expectations about a child’s sleep. This hypothesis would need to be verified in future research.
Efficient Edge-AI Models for Robust ECG Abnormality Detection on Resource-Constrained Hardware
Authors: Huang Zhaojing , Herbozo Contreras Luis Fernando , Leung Wing Hang , Yu Leping , Truong Nhan Duy , Nikpour Armin , Kavehei Omid
Published: March 2024

This study introduces two models, ConvLSTM2D-liquid time-constant network (CLTC) and ConvLSTM2D-closed-form continuous-time neural network (CCfC), designed for abnormality identification using electrocardiogram (ECG) data. Trained on the Telehealth Network of Minas Gerais (TNMG) subset dataset, both models were evaluated for their performance, generalizability capacity, and resilience. They demonstrated comparable results in terms of F1 scores and AUROC values. The CCfC model achieved slightly higher accuracy, while the CLTC model showed better handling of empty channels. Remarkably, the models were successfully deployed on a resource-constrained microcontroller, proving their suitability for edge device applications. Generalization capabilities were confirmed through the evaluation on the China Physiological Signal Challenge 2018 (CPSC) dataset. The models’ efficient resource utilization, occupying 70.6% of memory and 9.4% of flash memory, makes them promising candidates for real-world healthcare applications. Overall, this research advances abnormality identification in ECG data, contributing to the progress of AI in healthcare.

Graphical Abstract
CA-CAS-01-A: A Permissive Cell Line for Isolation and Live Attenuated Vaccine Development Against African Swine Fever Virus
Authors: Lee Seung-Chul , Kim Yongkwan , Cha Ji-Won , Chathuranga Kiramage , Dodantenna Niranjan , Kwon Hyeok-Il , Kim Min Ho , Jheong Weonhwa , Yoon In-Joong , Lee Joo Young , Yoo Sung-Sik , Lee Jong-Soo
Published: March 2024

African swine fever virus (ASFV) is the causative agent of the highly lethal African swine fever disease that affects domestic pigs and wild boars. In spite of the rapid spread of the virus worldwide, there is no licensed vaccine available. The lack of a suitable cell line for ASFV propagation hinders the development of a safe and effective vaccine. For ASFV propagation, primary swine macrophages and monocytes have been widely studied. However, obtaining these cells can be time-consuming and expensive, making them unsuitable for mass vaccine production. The goal of this study was to validate the suitability of novel CA-CAS-01-A (CAS-01) cells, which was identified as a highly permissive cell clone for ASFV replication in the MA-104 parental cell line for live attenuated vaccine development. Through a screening experiment, maximum ASFV replication was observed in the CAS-01 cell compared to other sub-clones of MA-104 with 14.89 and log10 7.5 ± 0.15 Ct value and TCID50/ml value respectively. When CAS-01 cells are inoculated with ASFV, replication of ASFV was confirmed by Ct value for ASFV DNA, HAD50/ml assay, TCID50/ml assay, and cytopathic effects and hemadsoption were observed similar to those in primary porcine alveolar macrophages after 5th passage. Additionally, we demonstrated stable replication and adaptation of ASFV over the serial passage. These results suggest that CAS-01 cells will be a valuable and promising cell line for ASFV isolation, replication, and development of live attenuated vaccines.
Using structure from motion for analyzing change detection and flood events in the context of flood preparedness: a case study for the Laufer Muehle area at the Aisch river in Germany for conducting near real-time analyses
Authors: Kögel Michael , Carstensen Dirk
Published: March 2024

Recent flood events (FE) in Germany have shown that the extent and impact of extreme flood events cannot be estimated solely based on numerical models. For analyzing the development of such an event and to develop and implement safety measures more efficiently, additional data must be collected during the event. Within the scope of this research, the possibilities of near real-time recording using an unmanned aerial vehicle (UAV) and data processing with the Structure from Motion (SfM) method were tested in a case study. Different recording parameter combinations were tested in the Laufer Muehle area on the Aisch river in Germany. The focus of the investigations was the identification of a parameter combination that allows a short recording interval for aerial imagery. Based on these findings, the identification of changes in the study area by comparing multitemporal photography (flood prevention), as well as the recording of flooded areas during a FE should be possible. The accuracy analysis of the different parameter combinations between two point clouds as well as the process of change detection was done by a Multiscale Model to Model Cloud Comparison (M3C2) and including ground control points. As a result, a parameter combination was identified which led to the desired results in the study area. The processes were transformed into fully automated and scripted workflows. The results serve as a basis for establishing a workflow for near real-time analyses in future studies.
Role of long non-coding RNA ELFN1-AS1 in carcinogenesis
Authors: HajiEsmailpoor Zanyar , Fayazi Alireza , Teymouri Mohammadhossein , Tabnak Peyman
Published: March 2024

As one of the leading causes of death worldwide, cancer significantly burdens patients and the healthcare system. The role of long non-protein coding RNAs (lncRNAs) in carcinogenesis has been extensively studied. The lncRNA ELFN1-AS1 was discovered recently, and subsequent studies have revealed its aberrantly high expression in various cancer tissues. In vitro and in vivo experiments have consistently demonstrated the close association between increased ELFN1-AS1 expression and malignant tumor characteristics, particularly in gastrointestinal malignancies. Functional assays have further revealed the mechanistic role of ELFN1-AS1 as a competitive endogenous RNA for microRNAs, inducing tumor growth, invasive features, and drug resistance. Additionally, the investigation into the clinical implication of ELFN1-AS1 has demonstrated its potential as a diagnostic, therapeutic, and, notably, prognostic marker. This review provides a comprehensive summary of evidence regarding the involvement of ELFN1-AS1 in cancer initiation and development, highlighting its clinical significance.
Dynamic multi-label feature selection algorithm based on label importance and label correlation
Authors: Chen Weiliang , Sun Xiao
Published: March 2024

Multi-label distribution is a popular direction in current machine learning research and is relevant to many practical problems. In multi-label learning, samples are usually described by high-dimensional features, many of which are redundant or invalid. This paper proposes a multi-label static feature selection algorithm to solve the problems caused by high-dimensional features of multi-label learning samples. This algorithm is based on label importance and label relevance, and improves the neighborhood rough set model. One reason for using neighborhood rough sets is that feature selection using neighborhood rough sets does not require any prior knowledge of the feature space structure. Another reason is that it does not destroy the neighborhood and order structure of the data when processing multi-label data. The method of mutual information is used to achieve the extension from single labels to multiple labels in the multi-label neighborhood; through this method, the label importance and label relevance of multi-label data are connected. In addition, in the multi-label task scenario, features may be interdependent and interrelated, and features often arrive incrementally or can be extracted continuously; we call these flow features. Traditional static feature selection algorithms do not handle flow features well. Therefore, this paper proposes a dynamic feature selection algorithm for flow features, which is based on previous static feature selection algorithms. The proposed static and dynamic algorithms have been tested on a multi-label learning task set and the experimental results show the effectiveness of both algorithms.
Morphology, Crystal Structure and Thermal Properties of Nano-Sized Amorphous Colemanite Synthesis
Authors: Kutuk Sezai
Published: March 2024

It is important to utilize the raw colemanite (RC) mineral, which has abundant reserves in the world, and to reduce its particles to smaller sizes for nanotechnology. However, not only the particle size of the produced colemanite powder but also its other properties need to be elucidated. By using the Taguchi design, the RC mineral was ground in a high-energy ball mill. From signal-to-noise (S/N) ratio, the smallest average particle size was found to be 3.10 µm for the experiment E04/nano-sized amorphous colemanite (NAC) powder. The characteristics of as-received RC mineral and synthesized NAC material were investigated using laser particle size analyzer, optical microscopes, SEM–EDS, XRD, TEM, HRTEM, and TGA–DTA devices. It was found that the NAC powder was not homogeneous, a small peak within the 300–20 nm range appeared, and d90, d50, d10, and dmin values were, respectively, 14.6 µm, 3.08 µm, 232 nm, and 26 nm. In the XRD analysis, the pure colemanite, calcite, and silica minerals were determined. The crystal structure of the NAC powder almost turned amorphous, and the crystallite size of (031) peak was reduced to 7.3 nm. It was deduced that the average particle size was 8.29 nm (R2 = 0.86), and the d-spacing value was 0.307 nm. This significant finding was attributed to the mobility of balls and moreover it was interpreted with an equation. An unknown transition in TGA–DTA was referred to the calcite mineral. Finally, it is believed that the synthesized NAC material will be beneficial to engineering studies as a natural/mineral additive.
Effect of Heat Treatment and Reinforcement Content on the Wear Behavior of Al–4Cu/Al2O3–CNT Nanocomposites
Authors: Özer Emre , Ayvaz Mehmet , Übeyli Mustafa , Sarpkaya İbrahim
Published: March 2024

In the study, the effects of hybrid reinforcement (nano-alumina and MWCNT) and heat treatment on the wear behavior of the Al–4Cu nanocomposites were investigated under dry sliding condition against W–6Co ball by means of a ball-on-disk type tribometer. The load and the sliding speed were kept constant and selected to be 10 N and 0.1 m s−1, respectively, in the course of the wear tests. Meanwhile, the wear tests were completed after a total sliding distance of 1500 m was reached for each case. During these tests, the wear loss of the nanocomposites was measured at every 250 m. The worn surfaces of the nanocomposites were examined with the help of stereo and scanning electron microscopes. The volumetric wear rates, wear coefficients and wear mechanisms were identified for the nanocomposites to clarify the influence of reinforcement content and heat treatment on their wear resistance. The volume loss at the wear distance of 1500 m was obtained as 24.9 and 8.2 mm3 for the annealed and aged Al–4Cu alloy, respectively. On the other hand, it decreased to 4.6 and 3.2 mm3 in the case of the nanocomposites with 15% hybrid reinforcement in the annealed and aged conditions, successively. Moreover, increasing the hybrid reinforcement amount decreased the wear loss of the aged nanocomposites substantially in such a way that it resulted in the mild wear.
Identification of a novel gene signature related to prognosis and metastasis in gastric cancer
Authors: Elizazu Joseba , Artetxe-Zurutuza Aizpea , Otaegi-Ugartemendia Maddalen , Moncho-Amor Veronica , Moreno-Valladares Manuel , Matheu Ander , Carrasco-Garcia Estefania
Published: March 2024

Background

Gastric Cancer (GC) presents poor outcome, which is consequence of the high incidence of recurrence and metastasis at early stages. GC patients presenting recurrent or metastatic disease display a median life expectancy of only 8 months. The mechanisms underlying GC progression remain poorly understood.

Methods

We took advantage of public available GC datasets from TCGA using GEPIA, and identified the matched genes among the 100 genes most significantly associated with overall survival (OS) and disease free survival (DFS). Results were confirmed in ACRG cohort and in over 2000 GC cases obtained from several cohorts integrated using our own analysis pipeline. The Kaplan-Meier method and multivariate Cox regression analyses were used for prognostic significance and linear modelling and correlation analyses for association with clinic-pathological parameters and biological hallmarks. In vitro and in vivo functional studies were performed in GC cells with candidate genes and the related molecular pathways were studied by RNA sequencing.

Results

High expression of ANKRD6, ITIH3, SORCS3, NPY1R and CCDC178 individually and as a signature was associated with poor prognosis and recurrent disease in GC. Moreover, the expression of ANKRD6 and ITIH3 was significantly higher in metastasis and their levels associated to Epithelial to Mesenchymal Transition (EMT) and stemness markers. In line with this, RNAseq analysis revealed genes involved in EMT differentially expressed in ANKRD6 silencing cells. Finally, ANKRD6 silencing in GC metastatic cells showed impairment in GC tumorigenic and metastatic traits in vitro and in vivo.

Conclusions

Our study identified a novel signature involved in GC malignancy and prognosis, and revealed a novel pro-metastatic role of ANKRD6 in GC.
A Deep Convolutional Spiking Neural Network for embedded applications
Authors: Javanshir Amirhossein , Nguyen Thanh Thi , Parvez Mahmud M. A. , Kouzani Abbas Z.
Published: March 2024

Deep neural networks (DNNs) have received a great deal of interest in solving everyday tasks in recent years. However, their computational and energy costs limit their use on mobile and edge devices. The neuromorphic computing approach called spiking neural networks (SNNs) represents a potential solution for bridging the gap between performance and computational expense. Despite the potential benefits of energy efficiency, the current SNNs are being used with datasets such as MNIST, Fashion-MNIST, and CIFAR10, limiting their applications compared to DNNs. Therefore, the applicability of SNNs to real-world applications, such as scene classification and forecasting epileptic seizures, must be demonstrated yet. This paper develops a deep convolutional spiking neural network (DCSNN) for embedded applications. We explore a convolutional architecture, Visual Geometry Group (VGG16), to implement deeper SNNs. To train a spiking model, we convert the pre-trained VGG16 into corresponding spiking equivalents with nearly comparable performance to the original one. The trained weights of VGG16 were then transferred to the equivalent SNN architecture while performing a proper weight–threshold balancing. The model is evaluated in two case studies: land use and land cover classification, and epileptic seizure detection. Experimental results show a classification accuracy of 94.88%, and seizure detection specificity of 99.45% and a sensitivity of 95.06%. It is confirmed that conversion-based training SNNs are promising, and the benefits of DNNs, such as solving complex and real-world problems, become available to SNNs.
Outpatient parenteral antimicrobial therapy (OPAT) in Germany: insights and clinical outcomes from the K-APAT cohort study
Authors: Schmidt-Hellerau Kirsten , Baade Nina , Günther Marina , Scholten Nadine , Lindemann Christoph Heinrich , Leisse Charlotte , Oberröhrmann Charlotte , Peter Sophie , Jung Norma , Suarez Isabelle , Horn Carola , Ihle Peter , Küpper-Nybelen Jutta , Hagemeier Anna , Hellmich Martin , Lehmann Clara
Published: March 2024

Purpose

Outpatient parenteral antimicrobial therapy (OPAT) offers several key advantages, including enhanced patient quality of life, reduced healthcare costs, and a potential reduction of nosocomial infections. It is acknowledged for its safety and effectiveness. This study provides the first systematic clinical data for Germany, where OPAT has not yet been widely adopted. The aim is to establish a foundational reference point for further research and integration of OPAT into the German healthcare system.

Methods

This prospective observational study descriptively analyses data obtained from a cohort of patients receiving OPAT. Both in- and outpatients from all medical specialties could be recruited. Patients administered the anti-infective medications themselves at home using elastomeric pumps.

Results

77 patients received OPAT, with a median duration of 15 days and saving 1782 inpatient days. The most frequently treated entities were orthopaedic infections (n = 20, 26%), S. aureus bloodstream infection (n = 16, 21%) and infectious endocarditis (n = 11, 14%). The most frequently applied drugs were flucloxacillin (n = 18, 23%), penicillin G (n = 13, 17%) and ceftriaxone (n = 10; 13%). Only 5% of patients (n = 4) reported to have missed more than one outpatient dose (max. 3 per patient). Only one catheter-related adverse event required medical intervention, and there were no catheter-related infections.

Conclusion

The study demonstrates that OPAT can be safely conducted in Germany. In preparation for its broader implementation, crucial next steps include creating medical guidelines, fostering interdisciplinary and inter-sectoral communication, as well as creating financial and structural regulations that facilitate and encourage the adoption of OPAT.

Trial registration number

NCT04002453.
Role of source control in critically ill candidemic patients: a multicenter retrospective study
Authors: Marangos Markos , Ioannou Petros , Senn Laurence , Spiliopoulou Anastasia , Tzalis Sotiris , Kolonitsiou Fevronia , Valta Maria , Kokkini Sofia , Pagani Jean-Luc , Stafylaki Dimitra , Paliogianni Fotini , Fligou Fotini , Kofteridis Diamantis P. , Lamoth Frédéric , Papadimitriou-Olivgeris Matthaios
Published: March 2024

Purpose

Candidemia is associated with high mortality especially in critically ill patients. Our aim was to identify predictors of mortality among critically ill patients with candidemia with a focus on early interventions that can improve prognosis.

Methods

Multicenter retrospective study.

Setting

This retrospective study was conducted in Intensive Care Units from three European university hospitals from 2015 to 2021. Adult patients with at least one positive blood culture for Candida spp. were included. Patients who did not require source control were excluded. Primary outcome was 14-day mortality.

Results

A total of 409 episodes of candidemia were included. Most candidemias were catheter related (173; 41%), followed by unknown origin (170; 40%). Septic shock developed in 43% episodes. Overall, 14-day mortality rate was 29%. In Cox proportional hazards regression model, septic shock (P 0.001; HR 2.20, CI 1.38–3.50), SOFA score ≥ 10 points (P 0.008; HR 1.83, CI 1.18–2.86), and prior SARS-CoV-2 infection (P 0.003; HR 1.87, CI 1.23–2.85) were associated with 14-day mortality, while combined early appropriate antifungal treatment and source control (P < 0.001; HR 0.15, CI 0.08–0.28), and early source control without appropriate antifungal treatment (P < 0.001; HR 0.23, CI 0.12–0.47) were associated with better survival compared to those without neither early appropriate antifungal treatment nor source control.

Conclusion

Early source control was associated with better outcome among candidemic critically ill patients.
The Role of Reconstructive Surgery in Lower Extremity Soft Tissue Sarcoma
Authors: Rinkel W. D. , Martin E. , Krijgh D. D.
Published: March 2024

Purpose of Review

Soft tissue sarcomas (STS) are relatively rare cancers, commonly occurring in the extremities. Over the last decades a shift in the treatment of extremity STS has occurred, from limb amputations toward so-called limb salvage surgery (LSS). This review provides an overview of the current surgical treatment options for lower extremity STS and how the role of reconstructive surgery may evolve in the coming years toward optimizing functional outcomes and improving the quality of life in these patients.

Recent Findings

Recent research has shown that having a low threshold for advanced reconstructive techniques, with the goal of bringing well-vascularized tissue to the defect, may lower the wound complication rates, especially in preoperatively irradiated tumors. Careful preoperative planning should not only include an optimal balance between complete surgical resection and preservation of vital structures, but also the possibilities of restoring anticipated loss of function. Such functional reconstructions may include the use of free functional muscle transfers but also tendon transfers and any type of nerve reconstruction. A more recent development is lymphatic surgery for STS patients to prevent or treat lymphorrhea and lymphedema. Future prospective studies should further study the indications, the timing of the surgery, and measure the outcomes of the lymphatic surgical techniques to further gain insights into the efficacy.

Novel techniques such as functional reconstructions, nerve transfers, and lymphatic surgery are within the realms of reconstructive options and therefore, it is important that patients with a STS are taken care of in centers that have a multidisciplinary team with a reconstructive surgeon as a member.
Spatter reduction in deep penetration welding of pure copper using blue-IR hybrid laser
Authors: Fujio Shumpei , Sato Yuji , Sudo Mao , Takenaka Keisuke , Tojo Koji , Pasang Timotius , Tsukamoto Masahiro
Published: March 2024

Bead-on-plate welding of pure copper with a blue-IR hybrid laser was conducted to achieve a spatter suppression in deep penetration welding of pure copper for the performance improvement of battery and power device of e-mobility. This hybrid laser combines an infrared (IR) laser and a blue diode laser as the welding source and preheating source, respectively. Preheating increases the light absorptivity of pure copper in the IR region. A 1.5-kW blue diode laser was employed to increase the light absorptivity by changing the phase of the preheated area from solid phase to liquid and gas phase. By experimentally investigating the influence of the blue diode laser intensity, the phase effects of the preheated area on pure copper welding with a blue-IR hybrid laser are elucidated. As a result, it was found that a liquid preheated area minimizes spatter during deep penetration welding.
Upper Marianian (Cambrian Series 2) trilobites from the Totanés–Noez area (Central Iberian Zone, Toledo province, Spain): systematics and intercontinental correlation
Authors: Sepúlveda Alexandre , Chirivella Martorell Juan B. , Collantes Luis , Mayoral Eduardo , Liñán Eladio , Gozalo Rodolfo
Published: March 2024

Marianian (Cambrian Series 2) trilobites from the area between Totanés and Noez (Central Iberian Zone) are described and their biostratigraphical significance is discussed. The trilobites come from eight localities and can be divided into two main assemblages: the first is characterised bySerrodiscus bellimarginatus,Chelediscuscf.garzoni,Atops calanus,Pseudatops reticulatusand indeterminate polymeroid trilobites. The second assemblage consists ofSerrodiscus bellimarginatus,Triangulaspiscf.fusca,Andalusiana palaciosin. sp.,Termierella totanesensisn. sp. andAcanthomicmaccasp. Both fossil associations indicate a late Marianian age in the regional stratigraphic scheme for the Cambrian of the Iberian Peninsula, asSerrodiscus,ChelediscusandPseudatopshave been recorded from the upper Marianian substage, whileTriangulaspis,Andalusiana,TermierellaandAcanthomicmaccaare indicative of the middle to upper Marianian. The taxa considered here have regional and intercontinental correlation potential. The presence of the globally distributed genusSerrodiscusallows correlation in the Cambrian Series 2. The first assemblage, composed ofSerrodiscus,Chelediscus,AtopsandPseudatops, has been reported from the Ossa-Morena Zone, Avalonia, Laurentia, Baltica and Siberia, improving the correlation between these regions. The second assemblage ofAndalusiana,Termierella,TriangulaspisandSerrodiscusis comparable to other assemblages from the Ossa-Morena Zone, the Iberian Chains and Morocco, withTriangulaspisalso reported from Newfoundland and Siberia. In addition, the proposal of the ISCS regarding the co-occurrence ofHebediscus,Calodiscus,SerrodiscusandTriangulaspisas a potential marker for the base of the Cambrian Stage 4 may imply that the upper Marianian of Iberia could be approximately correlated with the base of this stage.
Review on pressure drop through a randomly packed bed of crushed rocks
Authors: Hassan Elzubeir B. E. , Hoffmann Jaap
Published: March 2024

Predicting the pressure drop across a packed bed of crushed rock is regarded as a crucial parameter for estimating pump power and packed bed capacity. This paper critically evaluates the most prominent correlations for predicting the pressure drop across a packed bed of crushed rock, drawing from both numerical and experimental studies found in the literature. It also explores the various parameters that significantly affect the measurement of pressure drop. The study identifies that the size and shape of the particles, bed dimensions, and packing arrangement are key determinants in the measurement of pressure drop. Additionally, it is observed that the orientation of the particles within the bed plays a crucial role, indicating that traditional correlations may not provide accurate predictions for pressure drops in crushed rock. The paper demonstrates that applying the porous media approach, where the inertial and viscous terms in the pressure drop correlation are treated as tensors rather than constants, offers superior results. Finally, the study underscores the necessity for further research to comprehensively comprehend the flow within packed beds of crushed rock.
Improving Breast Cancer Diagnosis Accuracy by Particle Swarm Optimization Feature Selection
Authors: Kazerani Reihane
Published: March 2024

Breast cancer has been one of the leading causes of death among women in the world. Early detection of this disease can save patient’s lives and reduce mortality. Due to the large number of features involved in the diagnosis of this disease, the breast cancer diagnosis process can be time consuming. To reduce cost and time and improving accuracy of breast cancer diagnosis, this paper propose a feature selection algorithm based on particle swarm optimization (PSO) combined with machine learning methods for selection the most effective features for breast cancer diagnosis among all features. In order to evaluate the efficiency of the proposed feature selection method, it was tested on three most common breast cancer datasets available in the University of California, Irvine (UCI) repository named: Coimbra dataset (CD), Wisconsin Diagnostic Breast Cancer dataset (WDBC) and Wisconsin Prognostic Breast Cancer dataset (WPBC). In the Coimbra dataset with all its 9 features and without PSO feature selection algorithm the highest obtained accuracy was 87% by Support Vector Machine method, while with PSO feature selection algorithm the accuracy reached to 91% and the number of features was reduced from 9 to 4. In the WDBC dataset with all its 30 features and without PSO feature selection algorithm the highest obtained accuracy was 99% by Random Forest method, while with PSO feature selection algorithm the accuracy reached to 100% and the number of features was reduced from 30 to 19. In the WPBC dataset with all its 33 features and without PSO feature selection algorithm the highest obtained accuracy was 94% by Support Vector Machine method, while with PSO feature selection algorithm the accuracy reached to 96% and the number of features was reduced from 33 to 17. The results of this paper indicated that the proposed feature selection algorithm based on PSO algorithm can improve the accuracy of breast cancer diagnosis. While it has selected fewer and more effective features than the total number of features in the original datasets.