bluuebunny/crossref_metadata_2025_split huggingface dataset:
Image-assisted Collision Detection for Calculation of Assembly Interference Matrix
Authors: JIA KANG , Liu Hao , Ma Tao , Guo Junkang , Zhang Lei , Hong Jun 
Published: October 2022

Abstract
Assembly interference matrix is one of foundation information model for assembly process planning like assembly sequence planning and assembly path planning, which supports the digital assembly simulation, intelligent assembly, digital twins based assembly etc. Assemble interference matrix represents each two parts are collision or not when they moving along specific directions. Traditional assembly interference matrix construction adopts geometric collision detections on approximate swept volume of part which composed by moving part step by step. This manner not only leads to heavy computational loading since small moving step but also easy to misjudging contact as collide as well as missing collide due to discrete spatial moving of part. To overcome the drawbacks, this work equivalent the collision detection of parts during assembly interference matrix establishing as visibility judgement, and develop an image-assisted calculation method to process the collision between part’s swept volume as occlusion of images via computer graphic rendering. This method is implemented on OpenGL to ensure its generality, and the implicit calculating is finished in computer graphic rendering process by arranging proper rendering conditions with adopting depth testing and stencil testing. Furthermore, the erosion operation of image process is employed to distinguish whether contact or collide. At last, an examples for gear box assembly validates the effectiveness of this method.
A study of Uropathogenic Escherichia coli from men in regional NSW (Australia) with special emphasis on antibiotic resistance
Authors: Kudinha Timothy , Kong Fanrong 
Published: October 2022

Abstract
Background
Escherichia coli is an important uropathogen, responsible for most urinary tract infections (UTIs). Most studies on E. coli UTI pathogenesis have been in females, with limited studies on urinary isolates from men. Understanding UTI epidemiology in men is important in UTI management in this gender, including formulation of empirical treatment guidelines.
Methods
We studied the distribution of 310 uropathogenic E. coli isolates from men by uro-clinical syndrome, hospitalisation status, age group, and antibiotic susceptibility.
Results
Most of the E. coli isolates were from the outpatient setting (189, 61%), with the various age groups generally evenly distributed. In the inpatient setting, the 0-10 years age group was not represented, and the remaining 3 age groups were evenly represented (22-27%). Most of the isolates (74%) were from cystitis cases. For pyelonephritis isolates, the majority (65%) were confined to the 21-40 years age group, and the least in the 11-20 years age group (12%). Antibiotic (and multidrug) resistance was higher in pyelonephritis vs. cystitis isolates (73% vs. 58% ; P = 0.023, for multidrug resistance).
Overall, antibiotic resistance differed significantly by age; highest in the 21-40 years age range (69%), and lowest in the 0-10 years group (39%). Likewise, ESBL production was highest in the 21-40 years age range (10%), and lowest in the 0-10 years age (0%).
Conclusion
We documented a significant difference in the distribution of antibiotic resistance by age group amongst UPEC isolates from men in regional NSW, Australia, in the 0-60 years age group.
β-glucan alleviates goal-directed behavior in mice infected with Toxoplasma gondii
Authors: Cui Zeyu , Gong Yuying , Luo Xiaotong , Zheng Niuyi , Tan Shimin , Liu Shuxi , Li Youwei , Wang Qingling , Sun Fenfen , Hu Minmin , Pan Wei , Yang Xiaoying Yang 
Published: October 2022

Abstract
Background
Toxoplasma gondii (T. gondii) is a neuroinvasive parasite causing neuroinflammation, which is associated with a higher risk for several psycho-behavioral disorders. There is an urgent need to identify drugs capable of improving cognitive deficits induced by T. gondii infection. (1, 3)/(1, 6)-β-glucan, an active ingredient in mushrooms, could significantly enhance immunity. However, the effects of β-glucan against neuroinflammation and cognitive decline induced by T. gondiiinfection remain unknown. The present study aimed to investigate the neuroprotective effect of β-glucan on goal-directed behavior of mice chronically infected by T. gondii Wh6 strain.
Methods
A mice model of chronic T. gondii Wh6 infection was established by gavage of 10 cysts. Intraperitoneal injection of β-glucan was manipulated two weeks before T. gondiiinfection. Y-maze test and temporal order memory (TOM) test were performed to assess the goal-directed behavior. Golgi-Cox staining, transmission electron microscopy, immunofluorescence, Real-Time PCR and western blot assays were used to detect prefrontal cortex-associated pathological change and neuroinflammation.
Results
We reported that administration of β-glucan significantly prevented T. gondii Wh6-induced goal-directed behavioral impairment assessed behaviorally by Y-maze test and TOM test. In the prefrontal cortex, β-glucan could counter T. gondii Wh6 -induced degeneration of neurites, impairment of synaptic ultrastructure, and decrease of pre- and postsynaptic protein levels. Also, β-glucan significantly prevented the hyperactivation of pro-inflammatory microglia and astrocytes, as well as the upregulation of proinflammatory cytokines caused by chronic T. gondii Wh6 infection.
Conclusion
This study revealed that β-glucan prevents goal-directed behavioral impairment induced by chronic T. gondii infection in mice. These findings suggested that β-glucan may be an effective drug candidate to prevent T. gondii-associated psycho-behavioral disorders including goal-directed behavioral injury.
An image-processing-based technique for detecting quantitative fluorescence in plant cells
Authors: Feng Jun , Zhang Zhenshi , Bao Chun , Li Zhenting , Chen Bolei , Wang Bing , Zheng Yu 
Published: October 2022

Abstract
Biologists can now solve complex environmental problems by fabricate practical plant organisms, difficulties related to characterisation of cellular architectures of plant cells are often encountered which constrained the application of plant cells in synthetic biology. The objective of this study was to develop a automated, accurate and high-throughput quantitative analysis method ACFVA for single plant cell identification. ACFVA can address a variety of biological questions quantitatively of large number of plant cells automatically including standard assays (for example, cell localiztion, count and size) and complex morphological assays (for example, different fluorescence in cells). These assays can be used in a wide range of synthetic biology directions.
Tinaspora cordifolia acted as green corrosion inhibitor on mild steel in presence of 1M HCl solution
Authors: Gayakwad Netravati 
Published: October 2022

Abstract

Corrosion is a natural process which mainly occurs in metals. There are so many methods which inhibit the rate of corrosion. Inhibitors are organic compounds which added in a small concentration that retards the either anodic or cathodic, sometimes both. Synthetic inhibitors are non biodegradable, not easily available and toxic in nature. Considered to this point selection, some naturally available plant leaves extract that inhibit the rate of corrosion. Plant leaves extract mainly contains aromatic, aliphatic and cyclic chain compounds in their phytochemical constituents. These are abundantly easily available in nature, biodegradable, non toxic. Tinaspora cordilicia plant is rich in medicinal property as well acted as good inhibitor on mild steel in presence of 1M HCl solution. Present study investigates weight loss method at 303K.
Iterative Dual Regression Network for Blind Image Super-resolution
Authors: Lei Chunting , Yang Sihan , Yang Xiaomin , Yan Binyu , Jeon Gwanggil 
Published: October 2022

Abstract
Previous single-image super-resolution (SISR) methods assume that the blur kernel is known (e.g.,bicubic) when degrading from high-resolution (HR) images to low-resolution (LR) images. They usea single degradation to train a model to restore HR images. However, the actual degradation inreal-world is often unknown. It is difficult to deal with LR images caused by different degradations.To cope with the above situation, previous methods attempt to restore SR images using a blurkernel estimation structure that combines with a non-blind SR network. There are two problemsthat should be earnestly considered: (1) For accurate blur kernel estimation, insufficient correlation of consecutive kernels lead to an unsatisfied reconstruction result. (2) For ill-posed issue ofimage rebuild, a more efficient constraint condition is worth trying. To solve the two problems, wepropose an iterative dual regression network for an adaptive and precision blur kernel estimation, which improves the speed of kernel estimation by learning a dual mapping. Specifically, we design aPredictor-Generator structure: the Predictor, through several iterations, searching for accurate kernelsthrough intermediate kernels and generated SR images; the Generator, generating final SR images with the help of the predicted kernels. More importantly, the elaborately designed dual learningstrategy can not only provide additional constraints for accurate kernel estimation but also reducethe domain gap between SR images and HR images. Experiments on synthetic degraded imagesand real-world images, our network is competitive in performance and superior in visual results.
Selinexor for the treatment of recurrent or metastatic salivary gland tumors: results from the GEMS-001 clinical trial.
Authors: Hernando-Calvo Alberto , Malone Eoghan , Day Daphne , Prawira Amy , Weinreb Ilan , Wong Horace , Rodriguez Angela , Jennings Sarah , Eliason Anneli , Wang Lisa , Spreafico Anna , Siu Lillian L. , Hansen Aaron 
Published: October 2022

Abstract
Background
Salivary gland tumors (SGT) are rare with limited systemic treatments. We aimed to evaluate the activity of selinexor, an oral selective inhibitor of nuclear export, in patients with recurrent unresectable or metastatic SGT.
Methods
GEMS-001 is an open-label phase 2 study for patients with recurrent or metastatic SGT with two parts. In part 1 of the protocol, patients had tumor samples profiled with targeted next generation sequencing as well as immunohistochemistry for androgen receptor, HER-2 and ALK. For part 2, patients with no targetable alterations identified or no matched agents available are eligible to receive selinexor 60 mg given twice weekly every 28 days. The primary endpoint was objective response rate. Secondary endpoints included progression-free survival (PFS) and prevalence of druggable alterations across SGT.
Results
Between July 2014 and September 2021, 100 patients were enrolled in GEMS-001 and underwent genomic and proteomic profiling. A total of 21 patients (12 female) with a median age of 61 years (range 36–79) who lacked actionable alterations or available matched therapies were treated with selinexor. Histological subtypes (World Health Organization classification) included adenoid cystic carcinoma (n = 10), salivary duct carcinoma (n = 3), acinic cell carcinoma (n = 2) and other (n = 6). Fourteen patients were treatment naïve and 7 patients had received 1 or more lines of treatment prior to enrollment. Of 18 evaluable patients, stable disease as best response was observed in 17 patients (94%) (stable disease ≥ 6 months in 7 patients (39%)). Tumor reduction of target lesions was observed in 11 patients (61%). However, no partial or complete responses were observed. The median PFS was 4.9 months (95% confidence interval, 3.4–10). The most common treatment-related grade 1–2 adverse events were nausea [17 patients (81%)], fatigue [16 patients (76%)] and dysgeusia [12 patients (57%)]. Most common treatment-related grade 3–4 adverse events were hyponatremia [3 patients (14%)], neutrophil count decrease [3 patients (14%)] and cataracts [2 patients (10%)]. No treatment-related deaths were observed.
Conclusions
Although tumor reduction was observed across participants single agent selinexor antitumor activity was limited.
Trial registration
This clinical trial is registered at ClinicalTrials.gov (NCT02069730) first posted February 24 2014.
Hierarchical pores in degradable polymers-based aerogel for CO2 adsorption
Authors: Gan Lin , Zheng Shuyu , Huang Jin 
Published: October 2022

Abstract
Gas adsorption materials, such as active carbon and zeolite, usually cause second pollution after being used, due to their non-degradability. Here, we prepared a degradable aerogel material based on cellulose nanocrystals (CNCs) and poly vinyl alcohol (PVA) with hierarchical pores and excellent CO2-adsorption performance. The micropores, whose specific area is 442 m2·g−1, are obtained via in-situ growing MIL-100(Fe) on CNCs and concurrently assembling those CNC particles. The obtained aggregation is further introduced into degradable PVA aerogels, who offer mesopores and macropores. Such a degradable material is as light as 0.216 g·cm−3 and can adsorb 0.357 mmol CO2 per gram, which can hopefully be used in preparing light-weight CO2 collectors.
Differential DNA methylation of steatosis and non-alcoholic fatty liver disease in adolescence.
Authors: Melton Phillip E , Burton Mark A , Lillycrop Karen , Godfrey Keith M , Rauschert Sebastian , Anderson Denise , Burdge Graham C , Mori Trevor A , Beilin Lawrence J , Ayonrinde Oyekoya T , Craig Jeffery M , Olynyk John K , Holbrook Joanna D , Pennell Craig E , Oddy Wendy H , Moses Eric K , Adams Leon A , Huang Rae-Chi 
Published: October 2022

Abstract
BACKGROUND AND AIMS: Epigenetic modifications are associated with hepatic fat accumulation and non-alcoholic fatty liver disease (NAFLD). However, few epigenetic modifications directly implicated in such processes have been identified during adolescence, a critical developmental window where physiological changes could influence future disease trajectory. To investigate the association between DNA methylation and NAFLD in adolescence we undertook discovery and validation of novel methylation marks, alongside replication of previously reported marks.
APPROACH & RESULTS: We performed a DNA methylation epigenome-wide association study (EWAS) on DNA from whole blood from 707 Raine Study adolescents phenotyped for steatosis score and NAFLD by ultrasound at age 17. Next, we performed pyrosequencing validation of loci within the most 100 strongly associated differentially-methylated CpG sites (dmCpGs) for which ≥2 probes per gene remained significant across four statistical models with a nominal p-value <0.007. EWAS identified dmCpGs related to three genes (ANK1, MIR10a, PTPRN2) that met our criteria for pyrosequencing. Of the dmCpGs and surrounding loci that were pyrosequenced (ANK1 n=6, MIR10a n=7, PTPRN2 n=3), three dmCpGs in ANK1 and two in MIR10a were significantly associated with NAFLD in adolescence. After adjustment for waist circumference only dmCpGs in ANK1 remained significant. These ANK1 CpGs were also associated with γ-glutamyl transferase and alanine aminotransferase concentrations. Three of twenty-two differentially methylated dmCpGs previously associated with adult NAFLD were associated with NAFLD in adolescence (all adjusted p<2.3 x 10-3).
CONCLUSIONS: We identified novel DNA methylation loci associated with NAFLD and serum liver biochemistry markers during adolescence, implicating putative dmCpG/gene regulatory pathways and providing insights for future mechanistic studies.
Is transoral endoscopic thyroidectomy via vestibular approach safe for total thyroidectomy compared to open thyroidectomy? A propensity-score matched cohort study of 101 matched patient pairs with papillary thyroid carcinoma.
Authors: Li Yujun , Liu Zhaodi , Wang Yong , Yu Xing , Wang Tiantian , Xiang Cheng , Wang Ping 
Published: October 2022

AbstractBackground Transoral endoscopic thyroidectomy via vestibular approach (TOETVA) has become increasingly popular in the treatment of papillary thyroid cancer. This study aimed to describe the safety and feasibility of total thyroidectomy between the TOETVA and open thyroidectomy (OT) approaches for the treatment of patients with papillary thyroid cancer (PTC). Methods We retrospectively reviewed 780 consecutive patients suffering from PTC that had undergone total thyroidectomy using TOETVA (n = 107) and OT (n = 673) between April 2016 and October 2021 at our institute. Afterward, A total of 101 matched patients’ surgical outcomes were compared using propensity score matching (PSM) analysis. Results Before PSM, the patients in the TOETVA group were younger (p < 0.001), had a lower BMI (p < 0.001) and a greater female population (p < 0.001). After PSM, the TOETVA group was associated with significantly longer operative time (p < 0.001), greater blood loss (p < 0.001), total drainage amount (p < 0.001), higher WBC count (p < 0.001) and CRP (p < 0.001), better cosmetic satisfaction (p < 0.001) and quality of life (p < 0.001) and lower scar self-consciousness (p < 0.001). There was no statistical difference between the groups in the attenuation or disappearance of RLN signal, rate of parathyroid autotransplantation and bilateral lymph node dissection, the positivity of lymph node metastasis, number of dissected lymph nodes and positive lymph nodes, multifocality, postoperative level of blood calcium and PTH, rate of PTH < 15ng/mL, VAS score, duration of hospital stay, complications, mean TSH-stimulated Tg level before RAI, mean Tg level without TSH stimulation, and the proportion of serum Tg level of < 1. Conclusion TOETVA is a safe and feasible technique for better cosmetic effects and similar surgical outcomes compared to conventional open surgery for the studied patients that required total thyroidectomy.
MSCDP: Multi-Step Crowd Density Predictor in Indoor Environment
Authors: Wang Shuyu , Lyu Yan , Xu Yuhang , Wu Weiwei 
Published: October 2022

Abstract
Monitoring and predicting crowd movements in indoor environments are of great importance in crowd management to prevent crushing and trampling. Existing works mostly focused on individual trajectory forecasting in a less crowded scene, or crowd counting and density estimation. Only a very few works predict the crowd density distribution. However, this study is failing to realize multi-step prediction or exploiting only density heatmaps modality ignores the information complementation with corresponding video frames. Therefore, we are motivated to predict crowd density distribution in multiple time steps to facilitate long-term prediction. In this paper, a Multi-Step Crowd Density Predictor (MSCDP) to fuse video frame sequences and corresponding density heatmaps, is proposed to accurately forecast the future crowd density heatmaps. To capture long-term periodic movement features, the long-term optical flow context memory (LOFCM) module is designed to store learnable patterns. We conducted extensive experiments on two real-world datasets. Evaluation results show that our MSCDP outperforms the state-of-the-art baseline techniques and MSCDP variants in terms of various prediction errors, demonstrating the effectiveness of MSCDP and each of its key components in multi-step crowd density prediction.
Investigation of Denoising of Speech Signal using WaveShrink Method in Deaf Persons
Authors: J Nirmaladevi , S Poornachandra , RM Mahalakame , P Jayavardhini , V Ragsana R 
Published: October 2022

Abstract

Speech is vital parameter in human cognitive and socio-emotional development. Deaf speech is even more complex to understand unless the noise is removed and improved its fidelity. Denoising of speech signal is an important pre-processing stage in speech signal processing. Denoising of speech signal not only removes the redundant coefficients (leads to data compression) but also improve the quality of speech signal. Waveshrink is a technique used to in this paper to suppress the redundant wavelet coefficient through threshold concept. Denoising concept find application in both signal and image processing. Denoising of the signal will improve in processing the deaf signal speech with any assistive technologies. Digital devices can use this denoised speech to compare and reproduce the deaf speech signal for emotional analysis and comparison of various speech parameters in real time environment.
Medication Regimen Complexity and Medication Adherence among Patients with Multimorbidity Treated at University of Gondar Compressive Specialized Hospital
Authors: Kassaw Abebe Tarekegn , Minyihun Amare , Gebreslassie Begashaw Melaku 
Published: October 2022

Abstract
Background
Assessing the medication regimen complexity and treatment adherence of a patient is important to tailor medication related outcomes of patients with multimorbidity. Therefore, this study aimed to assess medication regimen complexity and level of medication adherence in patients with multimorbidity.
Methods
A hospital-based cross-sectional study was conducted from May to June, 2021. A systematic random sampling technique was used to enroll participants. Descriptive statistics such as mean, percent, and frequency were used to summarize patients' demographic and clinical characteristics. Ordinal logistic regression and Pearson chi-square tests were performed to identify associations between variables with the outcome variable. The Adjusted Odds Ratio (AOR) with 95% (CI) at P < 0.05 was reported for potential determinant factors of adherence level.
Results
A total of 416 subjects were participated in the study. The mean (SD) age was 56.12(± 13.75) years. The majority of the participants (57%) were classified under high medication regimen complexity index (MRCI) score. Nearly half of the patients (49%) were poor adherent to their medication regimens. In the multivariable ordinal regression analysis; number of medications (AOR = 0.63[0.41, 0.97]), income level (AOR = 4.59 [2.14, 9.83]), follow up duration (AOR = 2.31[1.09, 4.86]) and Charlson comorbidity index (CCI) (AOR = 0.36 [0.16, 0.83]) were significantly associated with low level of adherence.
Conclusion
Medication regimens for patients with multimorbidity were high and complex. Almost half of the study populations were classified as non-adherent. Hence, health care professionals and other stakeholders should seek interventions aimed at simplifying drug regimens complexity and improving adherence.
Span-based Joint Entity and Relation Extraction with Light Attention Encoder
Authors: Wang Yixuan , Wu Zhengyang 
Published: October 2022

Abstract
The construction and updating of the knowledge graph need to obtain a lot of knowledge in time. Text data generated continuously on the Internet is an important source of this knowledge. Especially for the knowledge graph related to public opinion monitoring, it is necessary to quickly extract entities and relations from the text. Although the entity and relation extraction (ERE) method based on the pre-training model can obtain good performance, the training efficiency is low due to the complexity of the model, and it needs to perform better on large datasets. In order to reduce the model complexity and better apply related models to small datasets and apply the ERE task on the edge devices, this work proposes a novel span-based joint ERE model with a light attention encoder. The specific operation is to discard the Value transform matrix originally possessed by the self-attention mechanism, modify it to an identity map, and change the calculation method of dot product similarity to the cosine similarity calculation method. Through experiments on three public datasets, it is verified that the proposed approach can greatly reduce the training cost on the basis of ensuring the good performance of the model.