bluuebunny/crossref_metadata_2025_split huggingface dataset:
Process and materials design for laser cladded inconel-625/tungsten carbide wear-resistant composite coatings
Authors: Olakanmi Eyitayo Olatunde , Hoosain Shaik , Lawal Sunday Albert , Pityana Sisa Lesley 
Published: June 2022

Abstract
Tailoring materials’ microstructural characteristics to meet mechanical functional requirements is quite critical in designing wear resistant coatings. To the best of our knowledge, no study had related carbide dissolution ratio (CDR) in laser cladded (LC) Inconel 625 coating and its microstructural parameters to its wear performance. Hence, this study explores how laser processing and materials parameters influence CDR, microhardness (MH) and volume of materials loss (𝑉𝑀𝐿) of fiber-laser deposited Inconel 625 composite coatings reinforced with tungsten carbide (WC-86) by employing response surface methodology (RSM) via central composite design (CCD). Furthermore, the nature of inter-relationship between the CDR in laser cladded Inconel 625 composite coatings, microstructural parameters (average mean free path and size of retained particles, and MH) as well as 𝑉𝑀𝐿 was explored to determine appropriate process and materials parameters to optimise the wear resistance of the coatings. A fully consolidated composite coating characterised with uniformly distributed retained WC-86 particle size of 40 𝜇m; mean free path of 30𝜇m within the Inconel 625 matrix; MH = 852 HV0.5; CDR = 77.08% has the most desirable wear resistance (VML = 9.42mm3) when processed with appropriate laser energy density (19.70 J/mm2), inconel content (70wt%) and shielding gas flow rates (6.00 l/min). This study provides new insight, for coating manufacturers, on how CDR and microstructural parameters can be manipulated as LC process and materials variables are altered with a view to designing most desirable wear resistant composite coating.
A Biomimetic Laminated Strategy Enabled Durable and Ultra-Sensitive MXene-based Flexible Electronics for Temperature Monitoring with Strain-Tolerant Performance
Authors: hao sanwei , Fu Qingjin , Meng Lei , Xu Feng , Yang Jun 
Published: June 2022

Abstract
The development of flexible thermistor epidermal electronics (FTEE) to satisfy high temperature resolution without strain induced signal distortion is of great significance but still challenging. Inspired by the nacre microstructure capable of restraining the stress concentration, we exemplified a versatile MXene-based thermistor elastomer sensor (TES) platform that significantly alleviated the strain interference by the biomimetic laminated strategy combining with the in-plane stress dissipation and nacre-mimetic hierarchical architecture, delivering competitive advantages of superior thermosensitivity (-1.32% °C− 1), outstanding temperature resolution (~ 0.3°C), and unparalleled mechanical durability (20000 folding fatigue cycles), together with considerable improvement in strain-tolerant thermosensation over commercial thermocouple in exercise scenario. By a combination of theoretical model simulation, microstructure observation, and superposed signal detection, the authors further revealed the underlying temperature and strain signal decoupling mechanism that substantiated the generality and customizability of the nacre-mimetic strategy, possessing insightful significance of fabricating FTEE for static and dynamic temperature detection.
Study on the learning curve during the transition from direct lateral to direct anterior approach in total hip arthroplasty : a consecutive one hundred and twenty-seven case series
Authors: Chu Miao , Zhou Jiangang , Wang Yong , Jiang Tao , Bao Weiguo 
Published: June 2022

Abstract
Background: Direct anterior approach (DAA) for primary hip arthroplasty has received increasing attention recently. However, there have been no reports focused on the learning curve when transitioning from direct lateral approach(DLA) to DAA. This study evaluates a single surgeon’s learning curve by examining Procedure Time (PT), Operation Preparation Time (OPT), Operating Room Time(ORT) and other data. Methods: From 2019 to 2021, a single surgeon’s first 100 cases with DAA and 27 cases with DLA between the learning cure were reviewed. PT, OPT, ORT and other data were analyzed. Results: Compared with DLA, PT, OPT and ORT had a sharp rise in the first 10 cases. There was no statistical significance in PT after 20 cases, ORT after 30 cases, and OPT after 50 cases. The difference of PT and ORT between group 1(DLA) and group 2(DAA, 1-51 cases), group 2 and group 3(DAA, 51-100 cases) were statistically significant. OPT of Group 1 was the shortest, increased significantly in group 2, gradually decreased in group 3. There were significant differences in blood loss between group 1 and group 3, between group 2 and group 3. 4 complications in total, 1 case in group 1, 3 cases in group 2. There were no significant differences in blood transfusion, length of stay and complication rate. Conclusions: When transitioning from DLA to DAA, an experienced surgeon may be low efficient, with longer PT, OPT and ORT. Great changes appeared after DAA 50 cases, complications and blood loss could be controlled within the safe range.
Low-frequency electrical stimulation of bilateral ankles by belt electrodes is effective for preventing denervation-induced atrophies in multiple skeletal muscle groups
Authors: Uno Hiroyuki , Kamiya Shohei , Akimoto Ryuji , Hosoki Katsu , Kouzaki Karina , Tamura Yuki , Kotani Takaya , Isemura Mako , Nakazato Koichi , Tadano Shunta 
Published: June 2022

Abstract
Belt electrode skeletal muscle electrical stimulation (B-SES) is a stimulation method that can simultaneously contract multiple muscle groups. Although the beneficial effects of B-SES in clinical situations have been elucidated, its molecular mechanism remains unknown. Here, we developed a novel rodent B-SES ankle stimulation system to test whether low-frequency stimulation prevents denervation-induced muscle atrophy.Electrical stimulations (7‒8 Hz, 30 min) with ankle belt electrodes were applied to Sprague–Dawley rats, daily for one week. All animals were assigned to control (CONT), denervation-induced atrophy (DEN), and DEN + electrical stimulation (ES) groups. The tibial anterior (TA) and gastrocnemius (GAS) muscles were used to examine the effects of ES treatment.Seven days of continuous stimulation induced significantly higher muscle wet weights and muscle fiber cross-sectional areas(CSA) in both TA and GAS muscles compared to those in the DEN group. B-SES suppressed the decrease in mitochondrial biosynthesis, quantity, and enzyme activity in TA and GAS muscles. mRNAs levels of muscle proteolytic molecules Atrogin-1 and Murf1 were largely increased by denervation, but B-SES repressed their expression.In conclusion, low-frequency electrical stimulation of bilateral ankles by belt electrodes is effective for preventing denervation-induced atrophy in multiple muscles by maintaining mitochondrial quantity, enzyme activity, and suppressing muscle protein degradation.
Splitting Tensile Strength of Fly Ash-Rectified Loose-Grained Sand at Various Pairs of Saturation and Curing Time
Authors: Simatupang Minson , Putra Heriansyah , Yanto Dede Heri Yuli 
Published: June 2022

Abstract
Currently, a soil stabilization approach using fly ash as an effective choice for increasing soil stiffness and strength has emerged. With the presence of water, the lime in the fly ash would be separated, generating cementitious materials binding the grains of sand. In the present study, the influence of curing time and saturation during specimen preparation on the behavior of fly ash-rectified loose-grained sand was observed by performing a series of splitting tensile strength tests. It was found that the splitting tensile strength increases with fly ash content and curing time and decreases with porosity and saturation. The increase in splitting tensile strength due to the reduction in saturation was clarified using microscopic image observations. Fly ash bonds congregate at the contact surface between the grains of sand at a low saturation of 30% and spread evenly on the whole sand surface at a high saturation of 100%. The splitting tensile strength produced at 30% saturation was approximately twofold higher than that at 100% saturation, particularly at one month of curing time. However, the splitting tensile strength at higher saturations approaches that at lower saturations, especially at longer curing times. Porewater evaporation accelerates the self-hardening occurring over time during curing, helping to achieve optimal strength. A reduction in porosity of approximately 0.6% caused by adding fly ash to the mixture can increase the splitting tensile strength by up to twenty-fold in the present study. An equation has been proposed as a function of porosity/volumetric fly ash content, curing time, and saturation during the preparation of the specimen. That equation can be applied convincingly to determine the splitting tensile strength of fly ash-rectified sand.
Percutaneous full-endoscopic C2 ganglionectomy for the treatment of intractable occipital neuralgia: technical feasibility and preliminary results
Authors: Li Chen , Jiang Ye , Wang Qiong , Xu Fulin , Yuan Lutao , Mao Yuhang , Liu Tengfei , Yang Liangliang , Liu Shuang , Yu Yong 
Published: June 2022

Abstract
Background
The treatment algorithm for occipital neuralgia follows the ladder principle. For intractable occipital neuralgia, C2 ganglionectomy can be an effective treatment option. Advancements in percutaneous endoscopic spinal surgery make it possible to accomplish C2 ganglionectomy using a full-endoscopic uniportal surgical technique.
Methods
From March 2020 to April 2021, three consecutive patients with intractable occipital neuralgia underwent percutaneous full-endoscopic C2 ganglionectomy. All the patients were followed up for more than 12 months. Previous treatment measures, operative time, blood loss, length of hospital stay, and complications were recorded. Finally, the visual analog score (VAS) and Headache Disability Inventory (HDI) were utilized to evaluate surgical efficacy.
Results
All the patients were successfully treated with a percutaneous full-endoscopic C2 ganglionectomy. Both the postoperative VAS scores and the HDI scores improved after C2 ganglionectomy in the three patients. There was no CSF leakage, incision infection, neck deformity, or other complications.
Conclusions
Patients suffering from intractable occipital neuralgia may benefit from percutaneous endoscopic C2 ganglionectomy, which possesses several advantages such as excellent visualization and reducing surgery-related trauma, blood loss, and length of stay.
Bladder cancer organoids as a functional system to model different disease stages and therapy response
Authors: Minoli Martina , Cantore Thomas , Kiener Mirjam , Fedrizzi Tarcisio , Manna Federico La , Karkampouna Sofia , Genitsch Vera , Rodriguez Antonio , Klima Irena , Gasperini Paola , Kiss Bernhard , Seiler Roland , Demichelis Francesca , Thalmann George , de Julio Marianna Kruithof 
Published: June 2022

Abstract
Bladder Cancer (BLCa) inter-patient heterogeneity is the primary cause of treatment failure, suggesting that patients could benefit from a more personalized treatment approach. Patient-derived organoids (PDOs) have been successfully used as a functional model for predicting drug response in different cancers. In our study, we established PDO cultures from different BLCa stages. PDOs preserve the histological and molecular heterogeneity of the parental tumors (PT), including their multiclonal genetic landscapes, and consistently share key genetic alterations detected in PTs, mirroring tumor evolution in longitudinal sampling. Our drug screening pipeline was implemented using PDOs, testing both standard-of-care and FDA-approved compounds for other tumors. Integrative analysis of drug response profiles with matched PDO genomic analysis was used to determine enrichment thresholds for candidate markers of therapy response and resistance. Finally, by assessing the clinical history of longitudinally sampled cases, the disease clonal evolution could be determined and matched with drug response.
Factors Influencing Consumption of Traditional Diets: Stakeholder Views regarding Sago Consumption among the Indigenous Peoples of West Papua
Authors: Sidiq Fathir Fajar , Coles David , Hubbard Carmen , Clark Beth , Frewer Lynn J 
Published: June 2022

Abstract
Background
The indigenous people living in the province of West Papua may experience potential food insecurity, in part attributable to increased local adoption of, and reliance on, imported foods such as rice. At the same time, the consumption of sago, a traditional local food, is lower than other types of carbohydrate foods such as wheat and cassava. Various factors may act as influential drivers of local diets and related agricultural practices, which in turn may be influenced by the attitudes and opinions of stakeholders with interests in the supply chain.
Methods
Qualitative methodology (semi-structured interviews) was applied to understand the various factors perceived by a selected number of stakeholders that influence sago consumption among the indigenous peoples of West Papua. These stakeholders included politicians, local and national civil servants, academics, sago farmers, and food activists (n = 18). Thematic analysis was used to analyse the data.
Results
The results indicate that the stakeholders perceive that the majority of the West Papuan people regard sago as a traditional food that is critical to, and inseparable from, local culture and food production practices. The results suggest that the stakeholders interviewed support the consumption of sago to improve food security for the indigenous people in West Papua, with a need for future policy to be developed to support this.
Conclusions
The evidence presented here suggests a diverse range of local stakeholders support the continuation of sago production and consumption, both from the perspective of improved food security, and in order to conserve cultural associations and activities within local communities. According to the stakeholders interviewed, this can be best achieved through improved engagement of local communities with sago production policies, innovation in current practices, and agronomic management. Local policies should be developed to ensure that sago remains an integral component of the Papuan people's culture, and develops into a significant commodity with economic value which simultaneously contributes to environmental targets.
Characterization of a petrographic microscope for potential use with image processing techniques
Authors: Profitis E. , Chatzitheodoridis E. 
Published: June 2022

Abstract
The polarising microscope is the most common and basic tool for geologists to study rocks and minerals in thin sections. The analysis and processing are mainly qualitatively when conventional methods are used. Nevertheless, due to technological development and evolution, the use of digital methods makes the petrographic studies much easier, reliable, and quantitative. In this paper, we describe a method to characterise the petrographic microscope based on its setup (i.e., nicols, lenses, light source). For the characterization procedure, a spectrometer has been used in order to acquire the spectrum of microscope’s light source, based on the different microscope’s components and setups, including the use of plane polarised, crossed polarised and circular polarised light conditions, from which the Correlated Colour Temperature (CCT) was computed. It is shown that the individual microscope setups have a direct effect on light source spectrum and therefore on the CCT value. This procedure is vital when image processing techniques are combined with traditional petrography interpretations for quantitative measurements. Technological applications can also be on materials showing birefringence, such as liquid crystals, polymeric fluids, thin films, plastics, optical fibres, and biological samples such as collagen and some proteins.
Fully Automated Measurement on Coronal Alignment of Lower Limbs using Deep Convolutional Neural Networks on Radiographic Images
Authors: Meng Xianghong , Wang Zhi , Ma Xinlong , Liu Xiaoming , Ji Hong , Cheng Jie-zhi , Dong Pei 
Published: June 2022

Abstract
Background
A deep convolutional neural network (DCNN) system is proposed to measure the lower limb parameters of the mechanical lateral distal femur angle (mLDFA), medial proximal tibial angle (MPTA), lateral distal tibial angle (LDTA), joint line convergence angle (JLCA), and mechanical axis of the lower limbs.
Methods
Standing X-rays of 1000 patients’ lower limbs were examined for the DCNN and assigned to training, validation, and test sets. A coarse-to-fine network was employed to locate 20 key landmarks on both limbs that first recognized the regions of hip, knee, and ankle, and subsequently outputted the key points in each sub-region from a full-length X-ray. Finally, information from these key landmark locations was used to calculate the above five parameters.
Results
The DCNN system showed high consistency (ICC > 0.91) for all five lower limb parameters. Additionally, the mean absolute error (MAE) and root mean squared error (RMSE) of all angle predictions were lower than 3° for both the left and right limbs. The MAE of the mechanical axis of the lower limbs was 1.124 mm and 1.416 mm and the RMSE was 1.032 mm and 1.321 mm, for the right and left limbs, respectively. The measurement time of the DCNN system was 1.8 ± 1.3 s, which was significantly shorter than that of experienced radiologists (616.8 ± 48.2 s, t = -180.4, P༜0.001).
Conclusions
The proposed DCNN system can automatically measure mLDFA, MPTA, LDTA, JLCA, and the mechanical axis of the lower limbs, thus helping physicians manage lower limb alignment accurately and efficiently.
Artificial Neural Network modelling for yield enhancement of L-Glutaminase free L-Asparaginase from Bacillus sp. associated with marine red alga Gracilaria dura
Authors: Mathew Doniya Elze , Vala Anjana K , Dineshkumar Ramalingam , Niharika Jayashree , Singh Ravindra Pal , Shinde Pramod B. , Mantri Vaibhav A. 
Published: June 2022

Abstract
The bacterial flora associated with Gracilaria dura, the sole producer of natural agarose was obtained. Screening for the presence of various enzymes and bioactive compounds resulted in discerning different clinically and industrially important enzymes. Three isolates were identified to be producing L-asparaginase (LA), a potent anticancer drug. The strain 4T1-C26E registered highest LA activity (25.2 IU ml− 1) in the enzyme assay, was selected for yield improvement by optimizing process parameters through Response Surface Methodology (RSM). Various parameters like glucose concentration, L-asparagine concentration, pH of the media, and incubation period were optimized through Central Composite Design (CCD) for enhanced yield of LA by 4T1-C26E, identified as Bacillus licheniformis. The CCD table was exploited for application in artificial neural networking (ANN) for the development of optimum method of cultivation. In this study, we obtained 2.5-fold (88.4 IU ml− 1) increase in LA production by this strain through RSM optimization. Further, Artificial Neural Networking Particle Swarm Optimization (ANN-PSO) predicted the input combinations. The experimental validation of LA production was found to be 4-fold (126.4 IU ml− 1) higher with respect to the unoptimized conditions. This illustrates the effectiveness of ANN-PSO based optimization technique, the error percent between the predicted and experimental output was 4.03%. The most important benefit of LA from 4T1-C26E is that it possesses no L-glutaminase activity. Further, it is extracellularly produced which is suitable for easier downstream processing thereby reducing chances of immunogenic responses by endotoxins. However, characterization of kinetic parameters and cytotoxic studies on cell cultures are mandatory to confirm its pharmaceutical application.
VAP Risk Index: Early prediction and hospital phenotyping of ventilator-associated pneumonia using machine learning
Authors: samadani Ali , Wang Taiyao , Zon Kees van 
Published: June 2022

Abstract
Background: Ventilator-associated pneumonia (VAP) is a leading cause of morbidity and mortality in intensive care units (ICUs). Early identification of patients at risk of VAP enables early intervention, which in turn improves patient outcomes. We developed a predictive model for individualized risk assessment utilizing machine learning to identify patients at risk of developing VAP.Methods: The Philips eRI database, a multi-institution electronic medical record (EMR), was used for model development. For adult (≥18y) patients, we propose a set of criteria using indications of the start of a new antibiotic treatment temporally contiguous to a microbiological test to mark suspected infection events, of which those with a positive culture are labeled as presumed VAP if 1) the event occurs at least 48 hours after intubation, and 2) there are no indications of community-acquired pneumonia (CAP) or other hospital-acquired infections (HAI) in the patient charts. The resulting VAP and no-VAP (control) cases were then used to build an ensemble of decision trees to predict the risk of VAP in the next 24hrs using data on patient’s demographics, vitals, labs, and ventilator settings. Results: The resulting model predicts the development of VAP with an AUC of 76% and AUPRC of 75% at a lead time of 24h in advance. Additionally, we group hospitals that are similar in healthcare processes into distinct clusters and characterize VAP prediction for the identified hospital clusters. We show inter-hospital (teaching status and healthcare processes) and cohort-specific (age groups, gender, early vs late VAP, ICU mortality status) differences in VAP prediction and associated symptomologies. Conclusions: Our proposed VAP criteria provide a temporal context for the infection event and enable studying the disease course. Using the proposed criteria, we curated a patient cohort and used it to build a model to predict an impending VAP event before any clinical suspicions. We present a clustering approach to tailor the VAP prediction model for different hospital types based on their EMR data characteristics. The developed VAP prediction model provides instantaneous risk score that allows early interventions and confirmatory diagnostic actions.
Modeling electronic health record data using an end-to-end knowledge-graph-informed topic model
Authors: Zou Yuesong , Pesaranghader Ahmad , Verma Aman , Buckeridge David , Li Yue 
Published: June 2022

Abstract
The rapid growth of electronic health record (EHR) datasets opens up promising opportunities to understand human diseases in a systematic way. However, effective extraction of clinical knowledge from the EHR data has been hindered by its sparsity and noisy information. We present GAT-ETM, an end-to-end knowledge graph-based multimodal embedded topic model. GAT-ETM distills latent disease topics from EHR data by learning the embedding from a constructed medical knowledge graph. We applied GAT-ETM to a large-scale EHR dataset consisting of over 1 million patients. We evaluated its performance based on EHR reconstruction and drug imputation. GAT-ETM demonstrated superior performance over the alternative methods on both tasks. Moreover, our model learned clinically meaningful graph-informed embedding of the EHR codes. In additional, our model is also able to discover interpretable and accurate patient representations for patient stratification and drug recommendations. Our code is available at Anonymous GitHub.