bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Deep Learning Based Holistic Diagnosis System for Immunohistochemistry Interpretation and Molecular Subtyping
Authors: Fan Lin , Liu Jiahe , Ju Baoyang , Tian Yushen 
Published: June 2023

Abstract
Purpose: Breast cancer in different molecular subtypes, which is determined by the overexpression rates of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), progesterone receptor (PR) and Ki67, exhibit distinct symptom characteristics and sensitivity to different treatment. Immunohistochemical method, one of the most common detecting tool for tumour markers, is heavily relied on artificial judgment and in clinical practice, with an inherent limitation in interpreting stability and operating efficiency. Here, a holistic intelligent breast tumour diagnosis system has been developed for tumour-markeromic analysis, combining the automatically interpretation and clinical suggestion.
Methods: The holistic intelligent breast tumour diagnosis system included two main modules. The interpreting modules were constructed based on convolutional neural network, for comprehensively extracting and analyzing the multi-features of immunostaining. Referring to the clinical classification criteria, the interpreting results were encoded in a low-dimensional feature representation in the subtyping module, to efficiently output a holistic detecting result of the critical tumour-markeromic with a diagnosis suggestions on molecular subtypes.
Results: The overexpression rates of HER2, ER, PR and Ki67, as well as an effective determination on molecular subtypes were successfully obtained by this diagnosis system, with an average sensitivity of 97.6% and an average specificity of 96.1%, among those, the sensitivity and specificity for interpreting HER2 were up to 99.8% and 96.9%.
Conclusion: The holistic intelligent breast tumour diagnosis system shows improved performance in the interpretation of immunohistochemical images over pathologist-level, which can be expected to overcame the limitations of conventional manual interpretation in efficiency, precision and repeatability.
The causality between CD8 + NKT cells and CD16 - CD56 on NK cells with hepatocellular carcinoma: a Mendelian randomization study
Authors: Lu Zhengmei , pan yong , chai xiaowei , li shibo 
Published: June 2023

Abstract
Background Hepatocellular carcinoma (HCC), which is featured with high morbidity and mortality worldwide, is a primary malignant tumor of the liver. Recently, there is a wealth of supporting evidence revealing that NK cell-related immune traits are strongly associated with the development of HCC, but the causality between them has not been proven.Methods Two-sample Mendelian randomization (MR) study was performed to probe the causal correlation between NK cell-related immune traits and HCC. Genetic variations in NK cell-related immune traits were extracted from recent genome-wide association studies (GWAS) of individuals with European blood lineage. HCC data were derived from the UK Biobank Consortium's GWAS summary count data, including a total of 372184 female and male subjects, with 168 cases and 372016 controls, all of whom are of European ancestry. Sensitivity analysis was mainly used for heterogeneity and pleiotropy testing.Results Our research indicated the causality between NK cell-related immune traits and HCC. Importantly, CD8+NKT cells had protective causal effects on HCC (OR = 0.9996;95%CI,0.9993–0.9999; P = 0.0489). CD16−CD56 caused similar effects on NK cells (OR = 0.9997;95%CI,0.9996–0.9999; P = 0.0117) as CD8+NKT cells. Intercepts from Egger showed no pleiotropy and confounding factors. Furthermore, insufficient evidence was found to support the existence of heterogeneity by Cochran's Q test.Conclusion MR analysis elucidated that low CD8+NKT cells and CD16−CD56 expression on NK cells were linked with a higher risk of HCC.
Designing for Sustainability and Safety in Urban Micro-mobility: A Novel Helmet Concept
Authors: Serra Gabriel , Sousa Guilherme Antunes e , Fernandes Fábio António Oliveira , de Sousa Ricardo José Alves , Noronha Eduardo Jorge Henriques 
Published: June 2023

Abstract
The past few years have witnessed a remarkable surge in urban mobility with the proliferation of micro-mobility sharing services. The advent of e-scooters and e-bikes has revolutionized the urban landscape across the globe. However, this transformation has also led to a worrisome increase in severe accidents associated with these new modes of transportation. The primary factors contributing to this trend are the inability of governments to swiftly adapt regulations to match evolving mobility trends and the unsuitability of traditional bicycle helmets for the spontaneous nature of micro-mobility. Moreover, in an era of resource scarcity and escalating global warming concerns, prioritizing sustainable development has become imperative for the modern economy. Unfortunately, conventional helmets significantly lack in terms of sustainability, not only due to their predominantly petroleum-derived materials but also because their manufacturing process combines the protective foam and outer shell, rendering them difficult to recycle or repurpose after disposal. This paper outlines the development of an innovative helmet concept designed for micro-mobility. The comprehensive research encompasses the design process, material selection, experimental testing, ergonomics, life cycle assessment, and design for manufacturing. The resulting helmet can be flattened to the size of a laptop, enabling convenient storage in a backpack. Additionally, it exhibits a 42% lower carbon footprint compared to standard helmets and can be fully disassembled and recycled. This novel helmet concept not only advances aesthetics and functionality but also meets three goals outlined by the UN 2030 agenda for sustainable development, making it a significant milestone for the helmet industry.
Enhanced Coalescence Backdoor Attack Against DNN Based on Pixel Gradient
Authors: Yin Jianyao , Chen Honglong 
Published: June 2023

Abstract

Deep learning has been widely used in many applications such as face recognition, autonomous driving, etc. However, deep learning models are vulnerable to various adversarial attacks, among which backdoor attack is emerging recently. Most of the existing backdoor attacks use the same trigger or the same trigger generation approach to generate the poisoned samples in the training and testing sets, which is also commonly adopted by many backdoor defense strategies. In this paper, we develop an enhanced backdoor attack (EBA) that aims to reveal the potential flaws of existing backdoor defense methods. We use a low-intensity trigger to embed the backdoor, while a high-intensity trigger to activate it. Furthermore, we propose an enhanced coalescence backdoor attack (ECBA) where multiple low-intensity incipient triggers are designed to train the backdoor model, and then, all incipient triggers are gathered on one sample and enhanced to launch the attack. Experiment results on three popular datasets show that our proposed attacks can achieve high attack success rates while maintaining the model classification accuracy of benign samples. Meanwhile, by hiding the incipient poisoned samples and preventing them from activating the backdoor, the proposed attack exhibits significant stealth and the ability to evade mainstream defense methods during the model training phase.
Social Excluder’s Face Reduces Gaze-Triggered Attention Orienting
Authors: Yang Jiajia , Zhou Li , Hu Zhonghua 
Published: June 2023

Abstract
Social ostracism, a negative affective experience in interpersonal interactions, is thought to modulate the gaze-cueing effect (GCE). However, it is unclear whether the impact of social exclusion on the GCE is related to the identity of the cueing face. Therefore, the present study employed a two-phase paradigm to address this issue. In the first phase, two groups of participants were instructed to complete a Cyberball game with two virtual avatars to establish a binding relationship between a specific face’s identity and the emotions of social exclusion or inclusion. In the second phase, these two virtual avatars (exclusion faces/inclusion faces) and two new faces (control faces) were used as cueing faces in the gaze-cueing task. The results found that, for the exclusion group, the magnitudes of the GCEs for the exclusion and exclusion-control faces were similar in the 200 ms stimulus onset asynchrony (SOA) condition, while the exclusion face’s GCE was significantly smaller than that of the exclusion-control face in the 700 ms SOA condition. In contrast, for the inclusion group, the GCEs for inclusion and inclusion-control faces in both the 200 ms SOA and 700 ms SOA conditions were no significant difference. This study reveals that the effect of social exclusion on the GCE is related to the identity of the cueing face, with individuals more reluctant to follow the gaze direction of excluder and shift their attention and provides experimental evidence that the perception of higher social relations can exert a top-down impact on the processing of social spatial cues.
Inspecting the quality of care: a comparison of CUSUM methods for inter hospital performance
Authors: Gomon Daniel , Sijmons Julie , Putter Hein , Dekker Jan Willem T , Tollenaar Rob AEM , Wouters Michel WJM , Tanis Pieter J , Fiocco Marta , Signorelli Mirko 
Published: June 2023

Abstract
Background During the past 14 years, a clinical audit has been used in the Netherlands to provide hospitals with data on their performance in colorectal cancer care. Continuous feedback on the quality of care provided at each hospital is essential to improve patient outcomes. It is unclear which methods should be used to generate most informative output for the identification of potential quality issues. Our aim is to compare the commonly employed funnel plot with existing cumulative sum (CUSUM) methodology for the evaluation of postoperative survival and hospital stay outcomes of patients who underwent colorectal surgery in the Netherlands.
Methods Data from the Dutch ColoRectal Audit on 25367 patients in the Netherlands who underwent surgical resection for colorectal cancer between 2019 and 2021 is used to compare four methods for the detection of deviations in the quality of care. Two methods based on binary outcomes (funnel plot, binary CUSUM) and two CUSUM charts based on survival outcomes (BK-CUSUM and CGR-CUSUM) are considered. A novel approach for determining hospital specific control limits for CUSUM charts is proposed. The ability to detect deviations as well as the time until detection are compared for the four methods. Charts were constructed for the inspection of both postoperative survival and hospital stay.
Results Methods using survival outcomes always yielded faster detection times compared to approaches employing binary outcomes. Detections between methods mostly coincided for postoperative survival. For hospital stay detections varied strongly, with methods based on survival outcomes signalling over half the hospitals. Further pros and cons as well as pitfalls of all methods under consideration are discussed.
Conclusions Methodology for the continuous inspection of the quality of care should be tailored to the specific outcome. Properly understanding how the mechanism of a control chart functions is crucial for the correct interpretation of results. This is particularly true for CUSUM charts, which require the choice of a parameter that greatly influences the results. When applying CUSUM charts, consideration of these issues is strongly recommended.
Short flexible peptides linking non-interacting protein domains appear to resist proteolysis by facilitating domain motions that sterically inhibit protease approach
Authors: Waghmare Snehal , Guptasarma Purnananda 
Published: June 2023

Abstract
Our objective in this paper was to identify any general characteristics of linker peptides that could potentially facilitate their escape from proteolytic degradation in fusion proteins, following their placement between two evolutionarily-unrelated, non-interacting, proteolytically-resistant protein domains. We selected Coh2 [an all-beta cohesin domain from C. thermocellum CipA], and BSX [a beta/alpha barrel xylanase domain from Bacillus sp. NG-27], and joined these domains through five different linker peptide sequences: (i) Rigid [3 repeats of N-EAAAK-C], (ii) Flexible [two repeats of N-SGGGG-C], (iii) Nat-Full [42 residues of a Coh2-adjacent linker in CipA], (iv) Nat-Half [a 21 residues-long derivative of Nat-Full] and (v) Nat-Quarter [a 9 residues-long derivative of Nat-Full]. The fusion proteins were produced, and size-exclusion chromatography and denaturing as well as non-denaturing electrophoresis were performed to assess the proteolytic susceptibilities of linkers peptide sequences during (a) storage of the fusion proteins at 4 ᵒC, through proteolysis effected by trace amounts of proteases naturally present in solution, and (b) exposure at room temperature to Subtilisin A, a non-sequence-specific protease. In both cases, proteolytic degradation of the linker was observed in Rigid, Nat-Full, Nat-Half and Nat-Quarter, but not in Flexible. Our further data and analyses suggest that, unlike with the other four other linkers, Flexible is able to escape proteolysis by using its conformational flexibility to facilitate motions in its flanking (non-interacting) domains to deflect approaching proteases, thus allowing such freely-moving domains to sterically protect the linker’s backbone, in ways that would be unlikely if the flanking domains were to interact.
Above and belowground carbon stock of pine plantations and native oak forests coexisting in central Spain
Authors: Bor Bram , Castro-Díez Pilar , Alonso Álvaro 
Published: June 2023

Abstract
Promoting nature-based carbon sinks is one of the effective ways to minimise global warming. Different types of forests, resulting from different land-use histories, may coexist under similar macro-environmental conditions, but their efficiency as carbon sinks may differ. In central Spain, many areas are covered by coexisting patches of monospecific plantations of Pinus halepensis, established since the 1950’s, and native Quercus forest coppiced up to the 1960´s. We aimed to compare the carbon stock between both types of forests, considering both above and belowground compartments, in La Alcarria region (central Spain). In each plot, the diameter at breast height and height were measured in every adult tree, along with shrub cover. Three subsamples of litter and soil were collected per plot. The carbon pool of trees and shrubs was calculated using allometric equations, and for roots, litter, and soil, using the carbon content analysed in a laboratory or obtained from the literature. Carbon pools were analysed separately for three independent variables: plot type (Quercus/Pinus), tree basal area (m2/ha) and slope (°). Overall, Quercus forests stored more carbon than Pinus plantations. The carbon allocation pattern across compartments greatly varied between the two forest types, Pinus plots storing more than half (55%) of its carbon in the aboveground biomass of trees, while Quercus storing more carbon belowground (60%) in roots and soil. We conclude that native Quercus forests are more suitable for a long-term carbon storage, as belowground compartments represent an important part of its carbon storage capacity.
The Genetic Basis of Galactosemia in Iranian Patients: Identification of Twenty Novel Mutations in GALT, GALK1 and GALE Gene
Authors: moody Mehrnoosh , Hosseini Mojgan , Deezagi Abdolkhalegh , Yaghmaei Parichehreh , Houshmand Seyyed Massoud 
Published: June 2023

Abstract
Introduction:
Galactosemia is a metabolic disorders that affects newborns. The enzyme deficiency of GALT, GALK and GALE are implicated with galactose metabolic disorders. The aim of this study is identify the profile mutations of GALT, GALK1 and GALEgene in the Iranian patients with galactosemia.
Method and materials:
In this study, 93 patients who have the diagnosis of galactosemia were investigated for mutation of the GALT, GALK1 and GALE gene. Genomic DNA was extracted from peripheral blood via kit and the PCR–Sequencing method was used to identify mutation of the GALT, GALK1 and GALE gene.
Results:
DNA Sequencing analysis identified 9 novel different mutations on the GALT gene, including: five missense mutations p.M177V (3/22%), R204Q (2/69%), L218V (2/15%), T268N (2/15%) and A379T (2/15%) and also, four synonymous mutations c.498T>A, c.876G>A, c.945T>C and c.1128A>T with 0/53% frequency. The most common mutations of GALTgene was p.Q188R (37/7%), K285N (4/9%) and R148W (4/3%). We detected 8 new different mutations on the GALK1 gene, including six missense mutations p.A198V (6/44%), R287C (2/15%), K217R (2/15%), E284D (2/69%), R228H (2/15%) and A387T (2/15%) two synonymous mutations c.840 C›T and c.1152C>T with 0/53% frequency. Also, in this study we identified 3 new synonymous mutations on the GALE gene including: c.957G›A (1/07%), c.879G›C (0/53%) and c.285C>T (1/07%).
Conclusion:
Identification of mutations involved in the development of galactosemia and designing a suitable diagnostic panel based on the detected mutations in GALT, GALK1 and GALE genes, can play an important role in neonatal screening program and early diagnosis.
Electrocardiogram Signal Classification Based on Deep Learning Techniques
Authors: Ahmed Amira 
Published: June 2023

Abstract
One of the most often used diagnostic tools in medicine and healthcare is the electrocardiogram (ECG). When it comes to healthcare prediction problems requiring ECG data, deep learning techniques seem promising. This paper aims to apply deep learning techniques to classify MIT-BIH arrhythmias on publicly available datasets. A new electrocardiogram classification for employing a spectrogram of signals algorithm is proposed. The proposed model depends on convolutional neural networks to automatically learn the characteristics of features and has used convolutional neural networks to detect normal and abnormal ECG heartbeats, with an average detection accuracy of 99.22%.
Solid state synthesis of ternary semiconductor zinc titanate-metal organic framework composite as photoanode material: Electronic properties and photovoltaic performance
Authors: Santhiya S. , Greena Mary , P Ram Kumar , X Sahaya Shajan , P Sri Renganathan 
Published: June 2023

Abstract
A ternary semiconductor zinc titanate (ZT)-metal-organic framework (MOF) composite is synthesized for photovoltaic applications to overcome the shortcomings of both materials when they behave separately including electronic conductivity and specific surface area. As a result, ZTMOF composite is synthesized and employed in making photoanode for dye-sensitized solar cells (DSSCs). The amount of MOF in the composite varies from 0.5, 1 and 2%. The chemisorbed MOF on ZT surface is strongly supported by the PXRD and FT-IR data. It is found that a high surface area of the MOF increases the amount of dye adsorption. The photovoltaic performance and electronic properties of the composite are investigated. Electrochemical impedance analysis of the DSSCs based on MOF reveals that the electronic transport is better than bare titania photoanode, and the photo-generated electrons are less likely to recombine.
Cybersecurity Resilience Maturity Assessment Tool for Critical National Information Infrastructure
Authors: Kulugh Victor , Mbanaso Uche , Chukwudebe Gloria 
Published: June 2023

Abstract
Cybersecurity resilience maturity assessment of critical national information infrastructure (CNII) is an important process in ensuring that organisations’ capability for resilience are measured and gaps determined vis-à-vis targeted resilience for the purpose of improvements. However, existing solutions do not provide an automated quantitative tool to enable organisation conduct the assessment of their cybersecurity resilience posture at defined regular intervals. This paper presents the cybersecurity resilience maturity assessment tool (CRMAT). The CRMAT is built on the cybersecurity resilience maturity assessment framework and the cybersecurity resilience maturity assessment model (CRMAM). While the CRMAF and CRMAM provide requirements and computational algorithms for the tool respectively. The agile methodology of the software development life cycle (SDLC) was adopted with the MVC (model-view-controller) architectural pattern to implement the software. The software tool has two interfaces, namely; admin interface that enables the setup of the cybersecurity controls and other parameters that will form the basis for the assessment and a report generation interface for all the cybersecurity controls. CRMAT was demonstrated on 31 CNIII organisations and result showed its capability to successfully and accurately compute the CNII resilience index (CNIIRI) and the indexes of other cybersecurity controls indicated in the CRMAF. Comparative analysis of the results showed that 5 (16.13%) of the organisations are in Q4, 9 (29.03%) are in Q3 while 13 (41.94%) and 4 (12.90%) are in Q2 and Q1 respectively. The implication is that the organisations in Q4 has optimised resilience while those in Q1 have the weakest cybersecurity resilience.
Discontinuation of Implants and associated factors among women in health facilities of Bahir Dar city, Northwest Ethiopia: A cross-sectional study
Authors: Melesse Yilkal Dagnaw 
Published: June 2023

Abstract
Background
Discontinuation of Implants is the removal or switch to other methods before completion of duration due to any reason. This exposes a woman to unwanted pregnancy, unsafe abortions, and unplanned births that affect millions of women worldwide. Inspite of the improvement in availability and utilization of Implants, discontinuation is becoming high. There is limited study conducted on implants discontinuation and factors in Bahir Dar City, Ethiopia.
Objective
The purpose of this research was to evaluate the proportion and explanatory variables of discontinuation of implants among users in selected health facilities of Bahir Dar City, Ethiopia, from April 1 to May 30/ 2021.
Methods
Health facility based cross-sectional design was conducted on 415 respondents. Data were collected through face-to-face interview questionnaires using a systematic random sampling method. Epi Data version 3.1 and Statistical Package for Social Sciences were used to data entry and formal analysis respectively. Bivariate and multivariate logistic regression analyzes were used. A P-value less than 0.05 was considered a statistically significant factor for discontinuation.
Results
The overall proportion of discontinuation of implants was 55.3% (95% CI: 61.42–69.13). Have no formal education (AOR = 0.49; 95% CI: 0.30–0.82), have primary education (AOR = 0.39; 95% CI: 0.18–0.81), wish to become pregnant in the near future (AOR = 2.57; 95% CI: 1.64) to 4.02), no history of contraceptive use (AOR = 2.01; 95% CI: 1.19 to 3.38), no counselling on benefit (AOR = 1.68; 95% CI: 1.08–2.62) and Side effects (AOR = 1.95; 95 CI: 1.21–3.16) were the factors associated with implant discontinuation.
Conclusion
The overall discontinuation of Implants among women was low compared to Ethiopian Demographic Health Survey 2016. Education, desire of pregnancy in the near future, no past history of contraceptive utilization, lack of counseling about the benefits, and side effects were factors for discontinuation. Hence health professionals should give adequate counseling, manage side effects and reassure women for any issues related with Implants.