bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ice thickness monitoring for cryo-EM grids by interferometry imaging
Authors: Hohle Markus Matthias , Lammens Katja , Gut Fabian , Wang Bingzhi , Kahler Sophia , Kugler Kathrin , Till Michael , Beckmann Roland , Hopfner Karl-Peter , Jung Christophe 
Published: September 2022

AbstractWhile recent technological developments contributed to breakthrough advances in single particle cryo-electron microscopy (cryo-EM), sample preparation remains a significant bottleneck for the structure determination of macromolecular complexes. A critical time factor is sample optimization that requires the use of an electron microscope to screen grids prepared under different conditions to achieve the ideal vitreous ice thickness containing the particles. Evaluating sample quality requires access to cryo-electron microscopes and a strong expertise in EM. To facilitate and accelerate the selection procedure of probes suitable for high-resolution cryo-EM, we devised a method to assess the vitreous ice layer thickness of sample coated grids. The experimental setup comprises an optical interferometric microscope equipped with a cryogenic stage and image analysis software based on artificial neural networks (ANN) for an unbiased sample selection. We present and validate this approach for different protein complexes and grid types, and demonstrate its performance for the assessment of ice quality. This technique is moderate in cost and can be easily performed on a laboratory bench. We expect that its throughput and its versatility will contribute to facilitate the sample optimization process for structural biologists.
Diabetes prevalence and risk factors, underestimated without oral glucose tolerance test, in rural Gombe-Matadi Adults, Democratic Republic of Congo, 2019
Authors: Muyer Muel Telo Marie-Claire , Botomba Steve , Poka Nickson , Mpunga Dieudonné , Sibongwere Deogratias Katsuva , Peñalvo José Luis , Sagastume Diana , Mapatano Mala Ali 
Published: September 2022

AbstractAn increase in the diabetes prevalence is reported worldwide. We aimed to determine the diabetes prevalence and its risk factors among adults in a rural area of the Democratic Republic of Congo. A cross-sectional study was conducted in 1531 inhabitants, selected by five stages, in the Health Zone of Gombe-Matadi. Diabetes was defined according to the American Diabetes Association and the International Diabetes Federation. Fasting glycemia and/or an oral glucose tolerance test were collected. We measured body mass index, waist circumference and blood pressure. Mann Whitney's and chi-square tests compared respondents with non-respondents. Multivariable logistic regression measured associations between diabetes and its risk factors. Crude and standardized prevalence of diabetes were 6.7% and 5.3%, respectively. Undiagnosed diabetes accounted for 58.8%. The oral glucose tolerance test alone diagnosed 2.6% of cases. Diabetes was more frequent in males, unemployed, obese and hypertensive (p < 0.05). Risk factors for diabetes were being male, aged ≥ 40 years, general and abdominal obesity associated with elderly, family history of diabetes, and hypertension. Diabetes in rural areas of the Democratic Republic of Congo appears to be underdiagnosed. The oral glucose tolerance test provides an opportunity to screen individuals for diabetes in this setting.
Frost resistance investigation of fiber reinforced recycled brick aggregate cementitious materials
Authors: Ji Yongcheng , Zhang Hongrui 
Published: September 2022

AbstractIn order to solve the problem of environmental pollution caused by construction waste, one typical waste of red bricks was selected as raw material in recycled concrete. This study presented recycled concrete by substituting some natural aggregates with treated red brick aggregates to study and analyze the degradation law mechanism of recycled brick aggregates concrete in the cold region. A total of fifteen categories of specimens and three experimental parameters were considered, which included numbers of freeze–thaw cycles (0, 50, and 100), steel fiber admixtures (0, 1, and 2%), and brick aggregate substitution rates (0, 25, 50, 75, and 100%), respectively. The quick freeze–thaw test method was selected to investigate recycled concrete's degradation mass loss rate and relative dynamic elastic modulus under various freeze–thaw cycles. The digital microscope and SEM were used to observe the internal microstructural changes in the specimens under different freeze–thaw times. In addition, the specimens’ microscopic damage morphology and damage mechanism were analyzed. Finally, the flexural strength of the frost-damaged specimens was tested to analyze the mechanical deterioration of the recycled concrete, and the numerical model corresponding to steel fiber dosing and recycled aggregate replacement rate was presented. The gray correlation analysis was used to quantify the influence of each experimental variable on the corresponding experimental indexes under various freeze–thaw cycles. Results showed that the specimen's mass decreased after freeze–thaw cycles, and the highest mass loss was found for the specimens with 50 and 75% brick substitution rates. In addition, the specimens showed the best relative dynamic modulus and the maximum flexural strength when the steel fiber doping was 1%. The numerical model agreed with experimental data and effectively predicted the specimens' mass loss rate, relative dynamic modulus, and flexural strength after freeze–thaw cycles. The gray correlation analysis showed that the steel fiber contents had a maximum correlation with the flexural strength, the brick substitution rates for the relative dynamic modulus, and mass loss controls the freeze–thaw cycles.
Predicting the risk of acute kidney injury after hematopoietic stem cell transplantation: development of a new predictive nomogram
Authors: Gan Zhaoping , Chen Liyi , Wu Meiqing , Liu Lianjin , Shi Lingling , Li Qiaochuan , Zhang Zhongming , Lai Yongrong 
Published: September 2022

AbstractThe purpose was to predict the risk of acute kidney injury (AKI) within 100 days after hematopoietic stem cell transplantation (HSCT) in patients with hematologic disease by using a new predictive nomogram. Collect clinical data of patients with hematologic disease undergoing HSCT in our hospital from August 2012 to March 2018. Parameters with non-zero coefficients were selected by the Least Absolute Selection Operator (LASSO). Then these parameters were selected to build a new predictive nomogram model. Receiver operating characteristic (ROC) curve, calibration curve, C-index, and decision curve analysis (DCA) were used for the validation of the evaluation model. Finally, the nomogram was further evaluated by internal verification. According to 2012 Kidney Disease Improving Global Guidelines (KDIGO) diagnostic criteria, among 144 patients, the occurrence of AKI within 100 days after HSCT The rate was 29.2% (42/144). The C-index of the nomogram was 0.842. The C-value calculated by the internal verification was 0.809. The AUC was 0.842, and The DCA range of the predicted nomogram was from 0.01 to 0.71. This article established a high-precision nomogram for the first time for predicting the risk of AKI within 100 days after HSCT in patients with hematologic diseases. The nomogram had good clinical validity and reliability. For clinicians, it was very important to prevent AKI after HSCT.
A polymeric nitrogen N$$_6$$–N$$_2$$ system with enhanced stability at low pressure
Authors: Benchafia El Mostafa , Wang Xianqin , Iqbal Zafar , Abedrabbo Sufian 
Published: September 2022

AbstractPostulated in 1992 and synthesized in 2004 above 2000 K and 110 GPa, the singly-bonded nitrogen cubic gauche crystal (cg-PN) is still considered to be the ultimate high energy density material (HEDM). The search however has continued for a method to synthesize cg-PN at more ambient conditions or find HEDMs which can be synthesized at lower pressure and temperature. Here, using ab initio evolutionary crystal prediction techniques, a simpler nitrogen-based molecular crystal consisting of N$$_6$$

6

and N$$_2$$

2

molecules is revealed to be a more favorable polynitrogen at lower pressures. The energetic gain of 534 meV/atom over cg-PN and 138 meV/atom over the N$$_8$$

8

molecular crystal at zero pressure makes the N$$_6$$

6

–N$$_2$$

2

system more appealing. Dynamical and mechanical stabilities are investigated at 5 and 0 GPa, and vibrational frequencies are assessed for its Raman and IR spectra. The prospects of an experimental synthesis of the N$$_6$$

6

–N$$_2$$

2

polymeric system compared to cg-PN is higher because the C$$_{2h}$$

2
h

symmetry of N$$_6$$

6

within this crystal would be easier to target from the readily available N$$_3^-$$

3
-

azides and the observed N$$_{3}^+$$

3

+

and N$$_{3}^*$$

3

∗

radicals.
The ratio model between throughput and delay based on payload transmission time in wireless blockchain network
Authors: Shi Chun , Shan Chun 
Published: September 2022

AbstractIn wireless blockchain network (WBN), it is necessary to study the impact of delay performance on blockchain technology with different data rates, because the throughput performance is not the only goal. We propose an analysis model to evaluate network performance based on both delay performance and network performance. Firstly, we separate the communication process from business process in WBN, and package the business data into the payload in a frame. Secondly, we define throughput-time$$S_V$$SVas a ratio of throughput to data transmission rate and propose a ratio model of$$S_V$$SVto network delay. Then, we analyze the ratio model with the parameter of payload transmission time, which is defined as a ratio of payload in a frame to data transmission rate. Using the DATA/ACK type in IEEE 802.11, we learn that the optimal payload transmission time is independent of node number and only determined by some interframe space of access mechanism and propagation time. Finally, we analyze the performance of network delay and throughput between DATA/ACK type and RTS/CTS/DATA/ACK type based on payload transmission time. The simulation data verify the validity and accuracy of the proposed model.
Heterogeneous human–robot task allocation based on artificial trust
Authors: Ali Arsha , Azevedo-Sa Hebert , Tilbury Dawn M. , Robert Lionel P. 
Published: September 2022

AbstractEffective human–robot collaboration requires the appropriate allocation of indivisible tasks between humans and robots. A task allocation method that appropriately makes use of the unique capabilities of each agent (either a human or a robot) can improve team performance. This paper presents a novel task allocation method for heterogeneous human–robot teams based on artificial trust from a robot that can learn agent capabilities over time and allocate both existing and novel tasks. Tasks are allocated to the agent that maximizes the expected total reward. The expected total reward incorporates trust in the agent to successfully execute the task as well as the task reward and cost associated with using that agent for that task. Trust in an agent is computed from an artificial trust model, where trust is assessed along a capability dimension by comparing the belief in agent capabilities with the task requirements. An agent’s capabilities are represented by a belief distribution and learned using stochastic task outcomes. Our task allocation method was simulated for a human–robot dyad. The team total reward of our artificial trust-based task allocation method outperforms other methods both when the human’s capabilities are initially unknown and when the human’s capabilities belief distribution has converged to the human’s actual capabilities. Our task allocation method enables human–robot teams to maximize their joint performance.
Mathematical analysis of the effect of process conditions on the porous structure development of activated carbons derived from Pine cones
Authors: Kwiatkowski Mirosław , Gómez-Delgado Edward , Nunell Gisel Vanesa , Bonelli Pablo Ricardo , Cukierman Ana Lea 
Published: September 2022

AbstractThis paper presents the results of a study on the influence of the degree of impregnation and activation temperature on the formation of the porous structure of activated carbons (ACs) obtained from Pine cones by the chemical activation process using potassium hydroxide as an activator. The advanced new numerical clustering based adsorption analysis (LBET) method, together with the implemented unique numerical procedure for the fast multivariant identification were applied to nitrogen and carbon dioxide adsorption isotherms determined for porous structure characterization of the ACs. Moreover, the Quenched Solid Density Functional Theory (QSDFT) method was chosen to determine pore size distributions. The results showed a significant influence of the primary structure of Pine cones on the formation of the porous structure of the developed ACs. Among others, it was evidenced by a very high degree of surface heterogeneity of all the obtained ACs, irrespective of the degree of impregnation with potassium hydroxide and the activation temperature. Moreover, the analysis of carbon dioxide adsorption isotherms showed, that the porous structure of the studied ACs samples contains micropores accessible only to carbon dioxide molecules. The results also showed a significant advantage of the LBET method over those conventionally used for porous structure analysis based on Brunauer–Emmett–Teller (BET) and Dubinin–Raduskevich (DR) equations, because it takes into account surface heterogeneities. The novel analyses methods were more fully validated as a reliable characterization tool, by extending their application to the isotherms for ACs developed from the same precursor by phosphoric acid activation, and for samples arising from these ACs, further subjected to additional post-treatments. The effect of the raw material used as precursor was moreover analysed by comparison with previous reported results for other ACs. The complementarity of the results obtained with the LBET and QSDFT methods is also noteworthy, resulting in a more complete and reliable picture of the analyzed porous structures.
Semibulk RNA-seq analysis as a convenient method for measuring gene expression statuses in a local cellular environment
Authors: Muto Kyoko , Tsuchiya Issei , Kim Soo Hyeon , Nagasawa Satoi , Takishita Mariko , Tsugawa Koichiro , Saito Hiroaki , Komazaki Yusuke , Torii Toru , Fujii Teruo , Suzuki Yutaka , Suzuki Ayako , Seki Masahide 
Published: September 2022

AbstractWhen biologically interpretation of the data obtained from the single-cell RNA sequencing (scRNA-seq) analysis is attempted, additional information on the location of the single cells, behavior of the surrounding cells, and the microenvironment they generate, would be very important. We developed an inexpensive, high throughput application while preserving spatial organization, named “semibulk RNA-seq” (sbRNA-seq). We utilized a microfluidic device specifically designed for the experiments to encapsulate both a barcoded bead and a cell aggregate (a semibulk) into a single droplet. Using sbRNA-seq, we firstly analyzed mouse kidney specimens. In the mouse model, we could associate the pathological information with the gene expression information. We validated the results using spatial transcriptome analysis and found them highly consistent. When we applied the sbRNA-seq analysis to the human breast cancer specimens, we identified spatial interactions between a particular population of immune cells and that of cancer-associated fibroblast cells, which were not precisely represented solely by the single-cell analysis. Semibulk analysis may provide a convenient and versatile method, compared to a standard spatial transcriptome sequencing platform, to associate spatial information with transcriptome information.
Comparison of cine cardiac magnetic resonance and echocardiography derived diameters of the aortic root in a large population-based cohort
Authors: Wenzel Jan-Per , Nikorowitsch Julius , bei der Kellen Ramona , Dohm Luisa , Girdauskas Evaldas , Lund Gunnar , Bannas Peter , Blankenberg Stefan , Kölbel Tilo , Cavus Ersin , Müllerleile Kai , Kaul Michael Gerhard , Adam Gerhard , Weinrich Julius Matthias 
Published: September 2022

AbstractTransthoracic echocardiography (TTE) and cine cardiac magnetic resonance imaging (CMR) are established imaging methods of the aortic root. We aimed to evaluate the comparability of measurements in TTE and standard cine CMR sequences of the aortic root. Our study included 741 subjects (mean age 63.5 ± 8 years, 43.7% female) from the Hamburg City Health Study (HCHS). Subjects underwent CMR and TTE. Aortic root measurements were performed at the level of the aortic annulus (AoAn), sinus of Valsalva (SoV), and sinotubular junction (STJ) by standard cine CMR in left ventricular long axis and left ventricular outflow tract view. Measurements were performed applying the leading-edge to leading-edge (LL) convention and inner-edge to inner-edge (II) convention in TTE and the II convention in CMR. Inter correlation coefficients (ICCs) demonstrated high inter- and intraobserver reproducibility for CMR and TTE measurements of SoV and STJ (ICCs 0.9–0.98) and moderate reproducibility for AoAn (ICCs 0.68–0.91). CMR measurements of SoV and STJ showed strong agreement with TTE: while correlations were comparable (r = 0.75–0.85) bias was lower with TTE II (bias − 0.1 to − 0.74) versus TTE LL measurements (mean bias − 1.49 to − 2.58 mm). The agreement for AoAn was fair (r = 0.51–0.57) with variable bias (mean bias 0.39–3.9). Standard cine CMR and TTE derived aortic root measurements are reproducible and comparable with higher agreement for TTE II instead of LL measurements. These results support an interchangeable application of TTE and standard CMR for screening of aortic root diseases thereby possibly reducing redundant multimodality imaging.
Multi-institution model (big model) versus single-institution model of knowledge-based volumetric modulated arc therapy (VMAT) planning for prostate cancer
Authors: Fukunaga Jun-ichi , Tamura Mikoto , Ueda Yoshihiro , Kamima Tatsuya , Shimizu Yumiko , Muraki Yuta , Nakamatsu Kiyoshi , Monzen Hajime 
Published: September 2022

AbstractWe established a multi-institution model (big model) of knowledge-based treatment planning with over 500 treatment plans from five institutions in volumetric modulated arc therapy (VMAT) for prostate cancer. This study aimed to clarify the efficacy of using a large number of registered treatment plans for sharing the big model. The big model was created with 561 clinically approved VMAT plans for prostate cancer from five institutions (A: 150, B: 153, C: 49, D: 60, and E: 149) with different planning strategies. The dosimetric parameters of planning target volume (PTV), rectum, and bladder for two validation VMAT plans generated with the big model were compared with those from each institutional model (single-institution model). The goodness-of-fit of regression lines (R2 and χ2 values) and ratios of the outliers of Cook’s distance (CD) > 4.0, modified Z-score (mZ) > 3.5, studentized residual (SR) > 3.0, and areal difference of estimate (dA) > 3.0 for regression scatter plots in the big model and single-institution model were also evaluated. The mean ± standard deviation (SD) of dosimetric parameters were as follows (big model vs. single-institution model): 79.0 ± 1.6 vs. 78.7 ± 0.5 (D50) and 0.13 ± 0.06 vs. 0.13 ± 0.07 (Homogeneity Index) for the PTV; 6.6 ± 4.0 vs. 8.4 ± 3.6 (V90) and 32.4 ± 3.8 vs. 46.6 ± 15.4 (V50) for the rectum; and 13.8 ± 1.8 vs. 13.3 ± 4.3 (V90) and 39.9 ± 2.0 vs. 38.4 ± 5.2 (V50) for the bladder. The R2 values in the big model were 0.251 and 0.755 for rectum and bladder, respectively, which were comparable to those from each institution model. The respective χ2 values in the big model were 1.009 and 1.002, which were closer to 1.0 than those from each institution model. The ratios of the outliers in the big model were also comparable to those from each institution model. The big model could generate a comparable VMAT plan quality compared with each single-institution model and therefore could possibly be shared with other institutions.
A study on the influence of service robots’ level of anthropomorphism on the willingness of users to follow their recommendations
Authors: Abdi Elahe , Tojib Dewi , Seong Alexander Kenwa , Pamarthi Yamika , Millington-Palmer George 
Published: September 2022

AbstractService robots are increasingly deployed in various industries including tourism. In spite of extensive research on the user’s experience in interaction with these robots, there are yet unanswered questions about the factors that influence user’s compliance. Through three online studies, we investigate the effect of the robot anthropomorphism and language style on customers’ willingness to follow its recommendations. The mediating role of the perceived mind and persuasiveness in this relationship is also investigated. Study 1 (n = 89) shows that a service robot with a higher level of anthropomorphic features positively influences the willingness of users to follow its recommendations while language style does not affect compliance. Study 2a (n = 168) further confirms this finding when we presented participants with a tablet vs. a service robot with an anthropomorphic appearance while communication style does not affect compliance. Finally, Study 2b (n = 122) supports the indirect effect of anthropomorphism level on the willingness to follow recommendations through perceived mind followed by persuasiveness. The findings provide valuable insight to enhance human–robot interaction in service settings.
Effect of densification on the physical and mechanical properties of the inner part of oil palm trunk impregnated with methylene diphenyl diisocyanate
Authors: Mangurai Silvia Uthari Nuzaverra Mayang , Hermawan Dede , Hadi Yusuf Sudo , Sulastiningsih Ignasia Maria , Basri Efrida , Abdillah Imam Busyra , Maulana Muhammad Iqbal , Purusatama Byantara Darsan , Park Se Yeong , Lee Seung Hwan , Febrianto Fauzi , Kim Nam Hun 
Published: September 2022

AbstractOil palm (Elaeis guineensis Jacq.) plantations in Indonesia are increasing over the past few years. After economic productivity, however, the unproductive oil palm trunks are felled and mostly go to waste, especially the inner part of the oil palm trunk (IOPT). There are several modification methods to utilize IOPT, such as impregnation and densification. Methylene diphenyl diisocyanate (MDI) is a common resin used for impregnation in composite industries because it is non-toxic and has excellent physical and mechanical properties but it has never been applied for the impregnation of IOPT. This study aimed to analyze the effect of densification on the physical and mechanical properties of the inner part of oil palm trunk (IOPT) impregnated using methylene diphenyl diisocyanate (MDI) resin to obtain valuable information regarding the efficient utilization of unproductive oil palm trunks. IOPT was densified and compregnated with compression ratios (CRs) of 20% and 30%. The physical properties (density, moisture content (MC), and water absorption (WA)) and mechanical properties (modulus of elasticity (MOE), modulus of rupture (MOR), and hardness) of the compregnated samples were better than those of the densified samples. The density and mechanical properties at CR 30% were higher than those at CR 20%. The improvements in density, MC, and WA of the compregnated IOPT with CR 30% were 127%, 54%, and 70%, respectively, compared to that in untreated IOPT. Furthermore, improvements in the MOE, MOR, and hardness of the compregnated IOPT with CR 30% were 489%, 379%, and 393%, respectively. The mechanical properties of the compregnated IOPT at CR 20% and 30% increased two- to three-fold from strength class V in control IOPT to strength class III in compregnated IOPT with CR 20% and to strength class II in compregnated IOPT with CR 30%, respectively.