bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preoperative prediction of the need for arterial and central venous catheterization using machine learning techniques
Authors: Suh Jungyo , Lee Sang-Wook 
Published: July 2022

AbstractSome surgical patients require an arterial or central venous catheterization intraoperatively. This decision relied solely on the experience of individual anesthesiologists; however, these decisions are not easy for clinicians who are in an emergency or inexperienced. Therefore, applying recent artificial intelligence techniques to automatically extractable data from electronic medical record (EMR) could create a very clinically useful model in this situation. This study aimed to develop a model that is easy to apply in real clinical settings by implementing a prediction model for the preoperative decision to insert an arterial and central venous catheter and that can be automatically linked to the EMR. We collected and retrospectively analyzed data from 66,522 patients, > 18 years of age, who underwent non-cardiac surgeries from March 2019 to April 2021 at the single tertiary medical center. Data included demographics, pre-operative laboratory tests, surgical information, and catheterization information. When compared with other machine learning methods, the DNN model showed the best predictive performance in terms of the area under receiver operating characteristic curve and area under the precision-recall curve. Operation code information accounted for the largest portion of the prediction. This can be applied to clinical fields using operation code and minimal preoperative clinical information.
Pancreatic adenocarcinoma associated immune-gene signature as a novo risk factor for clinical prognosis prediction in hepatocellular carcinoma
Authors: Dai Lei , Mugaanyi Joseph , Cai Xingchen , Lu Caide , Lu Changjiang 
Published: July 2022

AbstractPancreatic adenocarcinoma (PAAD) has high mortality and a very poor prognosis. Both surgery and chemotherapy have a suboptimal therapeutic effect, and this caused a need to find new approaches such as immunotherapy. Therefore, it is essential to develop a new model to predict patient prognosis and facilitate early intervention. Our study screened out and validated the target molecules based on the TCGA-PAAD dataset. We established the risk signature using univariate and multivariate Cox regression analysis and used GSE62452 and GSE28735 to verify the accuracy and reliability of the model. Expanded application of PAAD-immune-related genes signature (-IRGS) on other datasets was conducted, and the corresponding nomograms were constructed. We also analyzed the correlation between immune-related cells/genes and potential treatments. Our research demonstrated that a high riskscore of PAAD-IRGS in patients with PAAD was correlated with poor overall survival, disease-specific survival and progression free interval. The same results were observed in patients with LIHC. The models constructed were confirmed to be accurate and reliable. We found various correlations between PAAD-IRGS and immune-related cells/genes, and the potential therapeutic agents. These findings indicate that PAAD-IRGS may be a promising indicator for prognosis and of the tumor-immune microenvironment status in PAAD.
Development of a screening algorithm for borderline personality disorder using electronic health records
Authors: Zang Chengxi , Goodman Marianne , Zhu Zheng , Yang Lulu , Yin Ziwei , Tamas Zsuzsanna , Sharma Vikas Mohan , Wang Fei , Shao Nan 
Published: July 2022

AbstractBorderline personality disorder (BoPD or BPD) is highly prevalent and characterized by reactive moods, impulsivity, behavioral dysregulation, and distorted self-image. Yet the BoPD diagnosis is underutilized and patients with BoPD are frequently misdiagnosed resulting in lost opportunities for appropriate treatment. Automated screening of electronic health records (EHRs) is one potential strategy to help identify possible BoPD patients who are otherwise undiagnosed. We present the development and analytical validation of a BoPD screening algorithm based on routinely collected and structured EHRs. This algorithm integrates rule-based selection and machine learning (ML) in a two-step framework by first selecting potential patients based on the presence of comorbidities and characteristics commonly associated with BoPD, and then predicting whether the patients most likely have BoPD. Leveraging a large-scale US-based de-identified EHR database and our clinical expert’s rating of two random samples of patient EHRs, results show that our screening algorithm has a high consistency with our clinical expert’s ratings, with area under the receiver operating characteristic (AUROC) 0.837 [95% confidence interval (CI) 0.778–0.892], positive predictive value 0.717 (95% CI 0.583–0.836), accuracy 0.820 (95% CI 0.768–0.873), sensitivity 0.541 (95% CI 0.417–0.667) and specificity 0.922 (95% CI 0.880–0.960). Our aim is, to provide an additional resource to facilitate clinical decision making and promote the development of digital medicine.
Comparison of resistive capacitive energy transfer therapy on cadaveric molars and incisors with and without implants
Authors: Pérez-Bellmunt Albert , Caballé-Serrano Jordi , Rodríguez-Sanz Jacobo , Hidalgo-García César , González-Rueda Vanessa , Gassó-Villarejo Sergi , Zegarra-Chávez Daniel , López-de-Celis Carlos 
Published: July 2022

AbstractCapacitive–resistive energy transfer therapy (CRet) is used to improve the rehabilitation of different injuries. This study aimed to evaluate and compare the changes in temperature and current flow during different CRet applications on upper and lower molars and incisors, with and without implants, on ten cryopreserved corpses. Temperatures were taken on molars and incisors with invasive devices and skin temperature was taken with a digital thermometer at the beginning and after treatments. Four interventions: 15 VA capacitive hypothermic (CAPH), 8 watts resistive (RES8), 20 watts resistive (RES20) and 75 VA capacitive (CAP75) were performed for 5 min each. All treatments in this study generated current flow (more than 0.00005 A/m2) and did not generate a significant temperature increase (p > 0.05). However, RES20 application slightly increased surface temperature on incisors without implants (p = 0.010), and molar with (p = 0.001) and without implant (p = 0.008). Also, CAP75 application increased surface temperature on molars with implant (p = 0.002) and upper incisor with implant (p = 0.001). In conclusion, RES8 and CAPH applications seem to be the best options to achieve current flow without an increase in temperature on molars and incisors with and without implants.
Meniscus surface texture is associated with degenerative changes in biological and biomechanical properties
Authors: Otani Shunya , Kanamoto Takashi , Oyama Shohei , Yamakawa Satoshi , Shi Wen , Miyazaki Ryo , Aihara Masaharu , Oka Shiro , Kuroda Sanae , Nakai Tsuyoshi , Takenaka Keisuke , Sato Yuji , Tsukamoto Masahiro , Tsujii Akira , Ebina Kosuke , Okada Seiji , Nakata Ken 
Published: July 2022

AbstractMeniscal degeneration is defined by semi-quantitative assessment of multiple histological findings and has been implicated in biomechanical dysfunction, yet little is known about its relationship with biological properties. This paper aimed to quantitatively evaluate degenerative findings in human meniscus to examine their relationship with gene expression and biomechanical properties, and to extract histological findings that reflect biological properties like gene expression and cytokine secretion. This study included lateral menisci of 29 patients who underwent total knee arthroplasty. The menisci were divided into six samples. For each sample, Pauli's histological evaluation and corresponding quantitative assessment (surface roughness, DNA content, collagen orientation, and GAG content) were performed, with surface roughness showing the highest correlation with the histological evaluation in a single correlation analysis (r = 0.66,p < 0.0001) and multivariate analysis (p < 0.0001). Furthermore, surface roughness was associated with gene expression related to meniscal degeneration and with tangent modulus which decreases with increasing degeneration (r = − 0.49,p = 0.0002). When meniscal tissue was classified by surface integrity, inflammatory cytokine secretion tended to be higher in severe degenerated menisci. These results suggest that the evaluation of meniscal surface texture could predict the degree of degeneration and inflammatory cytokine secretion.
Nedaplatin-based chemotherapy or cisplatin-based chemotherapy combined with intensity-modulated radiotherapy achieve similar efficacy for stage II-IVa nasopharyngeal carcinoma patients
Authors: Deng Chao , Zhang Na , Jiang Shun , Zhang Haixia , Ma Jin’an , Zou Wen , Liu Xianling , Hu Chunhong , Hou Tao 
Published: July 2022

AbstractThis retrospective study compared the efficacy and safety of nedaplatin-based chemoradiotherapy and cisplatin-based chemoradiotherapy in stage II-IVa nasopharyngeal carcinoma (NPC) patients. Patients treated with cisplatin-based or nedaplatin-based chemoradiotherapy between January 2012 and December 2015 were evaluated. Survival was estimated by the Kaplan‒Meier method and compared by the log-rank test. Multivariate analysis was performed using the Cox proportional hazards model. A cohort of 538 NPC patients was enrolled. There were no significant differences in the 5-year overall survival (OS), progression-free survival (PFS), locoregional relapse-free survival (LRRFS), or distant metastasis-free survival (DMFS) between the cisplatin and nedaplatin groups. During the whole treatment course, patients in the cisplatin group had higher incidences of grade 3‒4 vomiting and anorexia, while patients in the nedaplatin group had higher incidences of grade 3‒4 leucopenia and mucositis. In terms of late toxicities, patients in the cisplatin group had a higher incidence of xerostomia. In multivariate analysis, T stage, N stage, and clinical stage were prognostic factors for OS, PFS, and DMFS. In subgroup analyses, nedaplatin-based chemotherapy achieved comparable treatment outcomes in specific populations stratified by age, sex, ECOG PS score and clinical stage. Cisplatin and nedaplatin are effective choices for stage II-IVa NPC patients, with a different spectrum of side effects.
Assessment of angle-dependent spectral distortion to develop accurate hyperspectral endoscopy
Authors: Lee Jungwoo , Yoon Jonghee 
Published: July 2022

AbstractHyperspectral endoscopy has shown its potential to improve disease diagnosis in gastrointestinal tracts. Recent approaches in developing hyperspectral endoscopy are mainly focusing on enhancing image speed and quality of spectral information under a clinical environment, but there are many issues in obtaining consistent spectral information due to complicated imaging conditions, including imaging angle, non-uniform illumination, working distance, and low reflected signal. We quantitatively investigated the effect of imaging angle on the distortion of spectral information by exploiting a bifurcated fiber, spectrometer, and tissue-mimicking phantom. Spectral distortion becomes severe as increasing the angle of the imaging fiber or shortening camera exposure time for fast image acquisition. Moreover, spectral ranges from 450 to 550 nm are more susceptible to the angle-dependent spectral distortion than longer spectral ranges. Therefore, imaging angles close to normal and longer target spectral ranges with enough detector exposure time could minimize spectral distortion in hyperspectral endoscopy. These findings will help implement clinical HSI endoscopy for the robust and accurate measurement of spectral information from patients in vivo.
Inducing Dzyaloshinskii–Moriya interaction in symmetrical multilayers using post annealing
Authors: Ahmadi Khadijeh , Mahfouzi Farzad , Jamilpanah Loghman , Mohseni Morteza , Böttcher Tobias , Pirro Philipp , Kioussis Nicholas , Åkerman Johan , Seyyed Ebrahimi S. A. , Mohseni Seyed Majid 
Published: July 2022

AbstractThe interfacial Dzyaloshinskii-Moriya Interaction (iDMI) is an antisymmetric exchange interaction that is induced by the broken inversion symmetry at the interface of, e.g., a ferromagnet/heavy metal. Thus, the presence of iDMI is not expected in symmetrical multilayer stacks of such structures. Here, we use thermal annealing to induce the iDMI in a [Py/Pt]×10 symmetrical multilayer stack. Brillouin light scattering spectroscopy is used to directly evidence the iDMI induction in the annealed sample. Structural characterizations highlight the modified crystallinity as well as a higher surface roughness of the sample after annealing. First principles electronic structure calculations demonstrate a monotonic increase of the iDMI with the interfacial disorder due to the interdiffusion of atoms, depicting the possible origin of the induced iDMI. The presented method can be used to tune the iDMI strength in symmetric multilayers, which are the integral part of racetrack memories, magnonic devices as well as spin-orbitronic elements.
Intertwined-pulse modulation for compressive data telemetry
Authors: Farsiani Sirous , Sodagar Amir M. 
Published: July 2022

AbstractThis paper presents a novel approach for anisochronous pulse-based modulation. In the proposed approach, referred to as the intertwined-pulse modulation (IPM), every pair of consecutive symbols overlap in time. This allows for shortening the time allocated for the transmission of the symbols, hence achieving temporal compaction while the data goes through the line encoding step in a digital communication system. The IPM is also uniquely superior to other existing anisochronous pulse-based modulation schemes in the fact that it exhibits robust symbol error rate against unwanted variations in both rise/fall times of the pulses in the modulated waveform, and in the threshold level used for data detection on the receiver side. An experimental setup was developed to implement an IPM encoder using standard digital hardware, and an IPM decoder as a part of the receiver system in software. According to the experimental results (supported by simulation results and theoretical studies), for the data mean value of mid-full-scale range, the proposed IPM scheme exhibits a time-domain compaction rate of up to 209.2%.
Multi-scale feature progressive fusion network for remote sensing image change detection
Authors: Lu Di , Cheng Shuli , Wang Liejun , Song Shiji 
Published: July 2022

AbstractPresently, research on deep learning-based change detection (CD) methods has become a hot topic. In particular, feature pyramid networks (FPNs) are widely used in CD tasks to gradually fuse semantic features. However, existing FPN-based CD methods do not correctly detect the complete change region and cannot accurately locate the boundaries of the change region. To solve these problems, a new Multi-Scale Feature Progressive Fusion Network (MFPF-Net) is proposed, which consists of three innovative modules: Layer Feature Fusion Module (LFFM), Multi-Scale Feature Aggregation Module (MSFA), and Multi-Scale Feature Distribution Module (MSFD). Specifically, we first concatenate the features of each layer extracted from the bi-temporal images with their difference maps, and the resulting change maps fuse richer semantic information while effectively representing change regions. Then, the obtained change maps of each layer are directly aggregated, which improves the effective communication and full fusion of feature maps in CD while avoiding the interference of indirect information. Finally, the aggregated feature maps are layered again by pooling and convolution operations, and then a feature fusion strategy with a pyramid structure is used, with layers fused from low to high, to obtain richer contextual information, so that each layer of the layered feature maps has original semantic information and semantic features of other layers. We conducted comprehensive experiments on three publicly available benchmark datasets, CDD, LEVIR-CD, and WHU-CD to verify the effectiveness of the method, and the experimental results show that the method in this paper outperforms other comparative methods.
Small-scale spontaneous dynamics in temperate beech stands as an importance driver for beetle species richness
Authors: Zumr Václav , Remeš Jiří , Nakládal Oto 
Published: July 2022

AbstractNatural dynamics in forests play an important role in the lives of many species. In the landscape of managed forests, natural disturbances are reduced by management activities. This usually has a significant effect on insect diversity. The effect of small-scale natural dynamics of protected beech stands on the richness of saproxylic and non-saproxylic beetles was investigated. Sampling was carried out by using flight interception traps in the framework of comparing different developmental stages: optimum, disintegration, and growing up, each utilizing 10 samples. We recorded 290 species in total, of which 61% were saproxylic. The results showed that the highest species richness and thus abundance was in the disintegration stage. In each developmental stage, species variation was explained differently depending on the variable. Deadwood, microhabitats, and canopy openness were the main attributes in the later stages of development for saproxylic beetles. For non-saproxylics, variability was mostly explained by plant cover and canopy openness. Small-scale disturbances, undiminished by management activities, are an important element for biodiversity. They create more structurally diverse stands with a high supply of feeding and living habitats. In forestry practice, these conclusions can be imitated to the creation of small-scale silvicultural systems with active creation or retention of high stumps or lying logs.
Thermotropic chirality enhancement of nanoparticles constructed from foldamer/bis(amino acid) complexes
Authors: Qiu Yuan , Cao Shuang , Sun Chenchen , Jiang Qian , Xie Chongmo , Wang Hong , Liao Yonggui , Xie Xiaolin 
Published: July 2022

Herein, chiral nanoparticles are constructed by mixing an artificial foldamer bearing aza-18-crown-6 pendants with l-homocystine perchlorate salt, showing a thermotropic chirality enhancement due to the binding mode changes in the heating process.
Replacing bar graphs of continuous data with more informative graphics: are we making progress?
Authors: Riedel Nico , Schulz Robert , Kazezian Vartan , Weissgerber Tracey 
Published: July 2022

Abstract
Recent work has raised awareness about the need to replace bar graphs of continuous data with informative graphs showing the data distribution. The impact of these efforts is not known. The present observational meta-research study examined how often scientists in different fields use various graph types, and assessed whether visualization practices have changed between 2010 and 2020. We developed and validated an automated screening tool, designed to identify bar graphs of counts or proportions, bar graphs of continuous data, bar graphs with dot plots, dot plots, box plots, violin plots, histograms, pie charts, and flow charts. Papers from 23 fields (approximately 1000 papers/field per year) were randomly selected from PubMed Central and screened (n=227998). F1 scores for different graphs ranged between 0.83 and 0.95 in the internal validation set. While the tool also performed well in external validation sets, F1 scores were lower for uncommon graphs. Bar graphs are more often used incorrectly to display continuous data than they are used correctly to display counts or proportions. The proportion of papers that use bar graphs of continuous data varies markedly across fields (range in 2020: 4–58%), with high rates in biochemistry and cell biology, complementary and alternative medicine, physiology, genetics, oncology and carcinogenesis, pharmacology, microbiology and immunology. Visualization practices have improved in some fields in recent years. Fewer than 25% of papers use flow charts, which provide information about attrition and the risk of bias. The present study highlights the need for continued interventions to improve visualization and identifies fields that would benefit most.
Traceability model based on improved witness mechanism
Authors: Li Li , Li Tao 
Published: July 2022

AbstractTraceability system is one of the popular applications of graphic blockchains. However, there are centralisation problems and a long time for final consistency confirmation in the graphic blockchain. In addition, the blockchain system in the traceability application scenario has the problem of insufficient supervision. Therefore, a witness‐based graphic blockchain consensus mechanism is proposed. In the consensus mechanism, a verifiable random function is used to screen the publishers of the unit; an SM2 threshold signature is used to sign the unit information to improve the non‐repudiation of the traceability information uploaders to the unit information under the supervision of the witness. The improved consistency algorithm cancels the process of finding a stable main chain and makes relatively many nodes to participate in the consensus process. The experimental results show that the graphic blockchain using the improved witness mechanism can reduce the degree of centralisation, shorten the time for new units to reach consensus, and greatly ensure the security and scalability of the blockchain system.
Mixed‐attention‐based regional soft partition network for vehicle reidentification
Authors: Li Zhiyong , Luo Yunzhong , Li Qiaochu , Song Lulu , Liu Weiyi 
Published: July 2022

AbstractThe purpose of vehicle reidentification is to distinguish the same vehicle from different vehicles using different cameras. The main challenge of this task is the significant intra‐instance discrepancy of the same vehicle from different views and the subtle inter‐instance differences of similar vehicles from the same views. To address this problem, researchers have attempted to align features from different views, such as using additional metadata (colour, type, key points, mask, etc.) to improve performance. Although these attempts improve the performance of vehicle reidentification, considerable efforts are required to create additional precise annotations to the data before using these methods. This results in expensive data preparation costs, rendering these methods less convenient to use. Therefore, we propose a novel deep learning network, called a mixed‐attention‐based regional soft partition network, to address this problem. This network does not require additional metadata annotations; it only trains the identity label as a supervision signal and uses soft partition attention to identify specific vehicle regions. Experiments showed that the performance of the proposed method was comparable to that of the state‐of‐the‐art method with additional annotations on the VeRri‐776 and VERI‐Wild datasets.
Modified approach of reactive power dispatch for wind farm voltage constraints of an individual connection point
Authors: Jung Seungmin 
Published: July 2022

AbstractThis paper proposes a modification method focusing on the distance‐based reactive power dispatch method that is applied in wind farm structures. Due to the continuous expansion of grid requirements, the development of new approaches needs to be more considered. Thus, in a wind farm, considering the voltage restriction for each unit, a modified reactive power dispatch strategy is proposed, that is more advanced than the general dispatch method. In a simulation with PSCAD/EMTDC, the proposed modification demonstrated delivery improvements while complying with the required voltage conditions.