bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Interaction Relationship between Support and Surrounding Rock in Fault Structural Area and Its Application
Authors: Wu Fengfeng , Yu Xin , Zhang Jian , Zhou Qingcong , Gao Zhiqiang , Liu Shibao 
Published: June 2022

Abstract
In order to solve the problem of support crushing, rib spalling, and partial roof fall in working face crossing fault structure area, taking II1023 working face of Haizi Mine as the engineering background, the numerical simulation, theoretical analysis, and field measurement were used to simulate the rock activity law in the process of working face crossing fault. Based on this, the mechanical model of the interaction between the support and the surrounding rock in the fault area was established, and the calculation formula of the support strength required by the support under different equilibrium criteria was deduced, which provides a basis for the reasonable selection of hydraulic support. The results show that the rock stress of the working face passing through the fault zone is divided into high-stress section when it is gradually close to the fault and low-stress section after passing through the fault. In the high-stress section, the rock stress increases in front of the working face, and the distribution form is similar to the stress distribution of the narrow coal pillar. The roof easily forms a long hanging roof and slip along the fault surface, which is prone to rib spalling and partial roof fall and support crushing. The support strength is mainly related to fault dip angle, fault cohesion, support beam length, length of the main roof rock beam, and the distance between working face and fault. The reasonable support strength should be determined by the calculation results under different equilibrium criteria. When the working face advances in the high-stress section, the required support strength of the support increases with the increase of the fault dip angle and the length of the main roof rock beam and decreases with the increase of the fault cohesion, the length of support beam, and the distance between working face and fault. With the increase of the fault dip angle, the form of rotary instability changes and the probability increases. The field practice shows that during the fault crossing of the II1023 working face, the working resistance of the support shows the characteristics of high-pressure area and low-pressure area, but it does not exceed the rated working resistance of the selected support. The fully mechanized coal face passed through the fault area safely, and there were no accidents such as support crushing, rib spalling, and partial roof fall.
3D S-Wave Velocity Model of the Crust and Upper Mantle beneath the Sea of Okhotsk and the Kamchatka Peninsula
Authors: Corchete Victor 
Published: June 2022

Abstract
A 3D S-wave velocity model (from 0 to 350 km depth) is determined for the region of the Sea of Okhotsk and the Kamchatka peninsula, through Rayleigh wave analysis applied to the traces of 278 earthquakes registered by 12 seismic stations, both located within (and nearby) of the study area. This model reveals the principal geological and tectonics features present in the study area, e.g., the presence of two lower-crust hot plumes located at the northwest of the Sea of Okhotsk, which are shown as two zones of low S-wave velocity (from 20 to 30 km depth). Also, a conspicuous low S-wave velocity zone is determined at the southwest of the Sea of Okhotsk (from 35 to 60 km depth), which can be matched up with a high conductivity layer previously determined from 30 to 65 km depth. For the Kamchatka peninsula, low S-velocities are determined beneath the volcanic belt from the upper crust (~5 km-depth) down to a depth of ~60 for the southern part, and down to a depth of ~140 km for the northern part. This low S-wave velocity pattern is enlarged in size at the northwest (north of ~55°N), following the location of the Kliuchevskoi and Sheveluch volcanoes, which confirms that these volcanoes must be a part of the same subduction-induced volcanic process. The present model shows that the subducting Pacific slab terminates near to the Aleutian-Kamchatka junction, i.e., no relict slab underlies the extinct northern Kamchatka volcanic arc. This model shows that this slab shoals towards north, and there exists a gap associated with the loss of this slab beneath Sheveluch and Kliuchevskoi volcanoes. The low S-wave velocity pattern determined at northwest of the slab edge confirms the presence of the asthenospheric flow, which would pass through this gap to the northwest around the north slab edge. Finally, the present model shows the precise location and detailed structure of the asthenosphere, which is a new result that has not been determined in other previous studies.
Eocene Volcanic Complex from Central British Columbia: The Role of Fractional Crystallization during the Magmatic Evolution
Authors: Dostal Jaroslav , Shellnutt J. Gregory 
Published: June 2022

Abstract
The Challis-Kamloops belt of south-central British Columbia is a regionally extensive (&gt;65,000 km2) magmatic province that erupted within the North American Cordillera during the Eocene (55-45 Ma). The inland volcanic belt runs parallel to the coast, and the rocks were emplaced mainly within extensional basins indicating volcanism was attributed to rift-related decompressional melting. The rocks include both calc-alkaline and tholeiitic mafic and intermediate types (i.e., low-Fe, medium-Fe, and high-Fe suites). Voluminous volcanic units (Buck Creek, Goosly Lake, Swans Lake) of the Buck Creek volcanic complex (~3,000 km2 in area) within the Nechako plateau erupted within 1-2 million years and show significant internal chemical variability. All rock types have similar Sr-Nd isotopic (87Sr/86Sri=0.70435-0.70487; εNdt=+2.6-+4.0) ratios indicating they originated from the same sub-Cordilleran mantle source. Petrological modeling using the most primitive rocks of the Buck Creek, Goosly Lake, and Swans Lake magmatic pulses demonstrates that the chemical variability observed in each system can be explained by hydrous fractional crystallization in the upper crust (≤0.1 GPa) under moderately oxidizing to oxidizing conditions (ΔFMQ 0 to +0.7). The primary difference between the low-Fe to medium-Fe (calc-alkaline) Buck Creek suite model and the high-Fe to medium-Fe (tholeiitic) Swans Lake suite model is water content as the Swans Lake model has lower (H2O=0.75 wt.%) starting water than the Buck Creek and also the Goosly Lake models (H2O=1.25-2.00 wt.%). Moreover, the intermediate to silicic rocks of the complexes are compositionally similar to rocks associated with “slab failure” suggesting that rifting and mantle melting were related to asthenospheric upwelling through a slab tear. The implications are that the chemical variability of the rock suites are primarily related to fractional crystallization and that the mantle source is heterogeneous with respect to water content which is likely due to heterogeneities in the processes related to pre-Eocene subduction.
Genetic diversity analysis and variety identification using SSR and SNP markers in melon
Authors: Wen Changlong , Zhang Jian , Yang Jingjing , Lv Yanling , Zhang Xiaofei , Xia Changxuan , Zhao Hong 
Published: June 2022

Abstract
Melon is an important horticultural crop with a pleasant aromatic flavor and abundance of health-promoting substances. Numerous melon varieties have been cultivated worldwide in recent years, but the high number of varieties and the high similarity between them poses a major challenge for variety evaluation, discrimination, as well as innovation in breeding. Recently, simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs), two robust molecular markers, have been utilized as a rapid and reliable method for variety identification. To elucidate the genetic structure and diversity of melon varieties, we screened out 138 perfect SSRs and 164 perfect SNPs from the resequencing data of 149 accessions, including the most representative lines worldwide. This study established the DNA fingerprint of 259 widely-cultivated melon varieties in China using Target-seq technology. The results showed four subgroups in the melon varieties, including ssp. melo and ssp. agrestis, and two types of intermediate subgroups. Compared with ssp. melo, the ssp. agrestis varieties might be exposed to a high risk of genetic erosion due to their extremely narrow genetic background. Increasing the gene exchange between ssp. melo and ssp. agrestis is therefore necessary in the breeding procedure. In addition, analysis of the DNA fingerprints of the 259 melon varieties showed a good linear correlation (R2 = 0.9722) between the SSR genotyping and SNP genotyping methods in variety identification. The pedigree analysis based on the DNA fingerprint of ‘Jingyu’ and ‘Jingmi’ series melon varieties was consistent with their breeding history. Based on the SNP index analysis, ssp. agrestis had low gene exchange with ssp. melo in chromosome 4, 7, 10, 11and 12, two specific SNP loci were verified to distinguish ssp. agrestis and ssp. melon varieties. Finally, 23 SSRs and 40 SNPs were selected as the core sets of markers for application in variety identification, which could be efficiently applied to variety authentication, variety monitoring, as well as the protection of intellectual property rights in melon.
Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time
Authors: Yin Bojian , Corradi Federico , Bohte Sander 
Published: June 2022

Abstract
With recent advances in learning algorithms, recurrent networks of spiking neurons are achieving performance competitive with standard recurrent neural networks. Still, these learning algorithms are limited to small networks of simple spiking neurons and modest-length temporal sequences, as they impose high memory requirements, have difficulty training complex neuron models, and are incompatible with online learning. Here, we show how `Forward-Propagation-Through-Time' (FPTT) learning combined with novel Liquid Time-Constant spiking neurons resolves these limitations. Applying FPTT to networks of such complex spiking neurons, we demonstrate online learning of exceedingly long sequences while outperforming current online methods and approaching or outperforming offline methods on temporal classification tasks. FPTT's efficiency and robustness furthermore enables us to train in an end-to-end fashion the first deep and performant spiking neural network for object localization and recognition, demonstrating for the first time the possibility of training large-scale complex spiking neural network architectures online and on long temporal sequences.
Prediction of RNA:DNA:DNA triple helix formation using next-generation sequencing data
Authors: Warwick Timothy , Seredinski Sandra , Krause Nina , Bains Jasleen Kaur , Althaus Lara , Oo James , Bonetti Alessandro , Dueck Anne , Engelhardt Stefan , Schwalbe Harald , Leisegang Matthias , Schulz Marcel , Brandes Ralf 
Published: June 2022

Abstract
RNA:DNA:DNA triple helix (triplex) formation regulates gene expression, but is difficult to study experimentally in vivo. This makes accurate computational prediction of triplex formation highly important in the field of RNA research. Current predictive methods have used canonical Hoogsteen base pairing rules, which whilst biophysically valid, may not reflect the plastic nature of cell biology. Herein, we present TriplexAligner, a local alignment tool implementing probabilistic scoring matrices learned from triplex-forming sequences captured in published triplexRNA-seq and triplexDNA-seq experiments. Short, conserved sequence elements were found to be enriched at points of triplex formation. Probabilistic mapping codes between RNA and DNA sequences were learned by Expectation-Maximisation, and used as scoring matrices for local alignment. TriplexAligner predicts RNA-DNA interactions identified in all-to-all sequencing data more accurately than previously published tools, and also predicts previously studied triplex interactions with known regulatory functions.
Post Discharge Management of Heart Failure Patients: Clinical findings at the first medical visit in a single-center study
Authors: Sall Fatouma , Adoubi Anicet , Boka Carine , Koffi Nina , Ouattara Pinnin , Dakoi Armel , Anzouan-Kacou Jean-Baptiste 
Published: June 2022

Abstract
Background. The Post Discharge Management of patients with heart failure impact significantly their incomes. This study aims to analyze the clinical findings and management at the first medical visit of these patients in our context.Material and methods: This is a retrospective cross-sectional descriptive study on consecutive files of patients hospitalized for heart failure from January to December 2018 in our Department. We analyse data from the first post discharge medical visit. including medical visit time, clinical conditions and management. Results: Three hundred and eight patients (mean age: 53.4 ± 17.0 years, 60% males) were hospitalized on median duration of 4 days [1-22 days]. One hundred and fifty-three patients (49,67%) were presented at the first medical visit after 60 days on average, 10 (3.24%) patients died before this first medical visit and 145 (47.07%) had been lost to follow-up. The re-hospitalization and treatment non-compliance rates were 9.4% and 3.6%, respectively. Male gender (p = 0.048), renal failure (p = 0.010), and Vitamin K antagonist (VKA) /direct oral anticoagulant (DOAC) (p = 0.049) were the main lost to follow-up factors. Hyponatremia (37%), tachycardia (28%) and LVEF <25% (12%) were the major factors of poor prognosis.Conclusion: The management of patients with heart failure after discharge from hospital seems to be insufficient and inadequate. A specialized unit is required to optimize this management.
Success rate of Artificial Insemination, Reproductive Performance and Economic Impact of failure of first service insemination: A Retrospective Study
Authors: Tadesse Belege , Reda Abadi , Kassaw Nuredin , Tadeg Wodajo 
Published: June 2022

Abstract
Background
A retrospective cohort study using a 10 year AI and cow reproductive performance data was conducted to study the success rate of AI; associations between effectiveness of AI and breed, AI season and, number of service per conception, and economic impact of failure of FSC in Dessie town, Dessie zuria and Kutaber districts. A total of 3480 dairy cows’ AI and reproductive performance records which were performed between 1995 and 2005 in the three selected districts of South Wollo were used. The economic losses and costs for cows that failed to conceive at their first AI associated with the larger number of days open were estimated.
Result
The prevalence of conception has a statistically significant difference between breeds of cows (P = 0.019). The non-return rate for first service was 58.54%. The median DFS, ISI and GL were 126, 30 and 278 days respectively. Whereas, the mean ± SD days open, CI, NOI and NSPC were 147.2 ± 60.26, 424.5 ± 60.55, 1.14 ± 0.38 and 1.15 ± 0.39 respectively. Based on AI season there was a significant difference in conception between winter and spring (P = 0.021). There is a 45.04 days extension in the mean calving to conception interval in cows that did not conceive at their first AI but conceived by 2nd and 3rd AI than in cows that did conceive at their first AI. A total of 28685.3 ETB extra costs was spent on reproductive treatment and other management for cows that failed to conceive at their first AI but conceived by second and third service. In cows that did not conceive totally the owner losses on average 473.7 ETB per cow per day extra costs until the cows will be culled.
Conclusion
Therefore to increase the conception rate and decrease the economic loss the owners of the dairy cows should supervise the cows regularly and should be trained on how to identify cows on estrous, the AI technicians should be trained to conduct the AI service accurately.
Extending the Network Calculus Algorithmic Toolbox for Ultimately Pseudo-Periodic Functions: Pseudo-Inverse and Composition
Authors: Zippo Raffaele , Nikolaus Paul , Stea Giovanni 
Published: June 2022

Abstract
Network Calculus (NC) is an algebraic theory that represents traffic and service guarantees as curves in a Cartesian plane, in order to compute performance guarantees for flows traversing a network. NC uses transformation operations, e.g., min-plus convolution of two curves, to model how the traffic profile changes with the traversal of network nodes. Such operations, while mathematically well-defined, can quickly become unmanageable to compute using simple pen and paper for any nontrivial case, hence the need for algorithmic descriptions. Previous work identified the class of piecewise affine functions which are ultimately pseudo-periodic (UPP) as being closed under the main NC operations and able to be described finitely. Algorithms that embody NC operations taking as operands UPP curves have been defined and proved correct, thus enabling software implementations of these operations. However, recent advancements in NC make use of operations, namely the lower pseudo-inverse, upper pseudo-inverse, and composition, that are well defined from an algebraic standpoint, but whose algorithmic aspects have not been addressed yet. In this paper, we introduce algorithms for the above operations when operands are UPP curves, thus extending the available algorithmic toolbox for NC. We discuss the algorithmic properties of these operations, providing formal proofs of correctness.
Parametric Simulation of Electron Backscatter Diffraction Patterns through Generative Models
Authors: De Graef Marc , Ding Zihao 
Published: June 2022

Abstract
Recently, discriminative machine learning (ML) models have been widely used to predict various attributes from Electron Backscatter Diffraction (EBSD) patterns. However, there has never been any generative model developed for EBSD pattern simulation. On one hand, the training of generative models is much harder than that of discriminative ones; On the other hand, numerous variables affecting EBSD pattern formation make the input space high-dimensional and its relationship with the distribution of backscattered electrons complicated. In this study, combining two famous generative models, we propose a framework (EBSD-CVAE/GAN) with great flexibility and scalability to realize parametric simulation of EBSD patterns. Compared with the frequently used forward model, EBSD-CVAE/GAN can take variables more than just orientation and generate corresponding EBSD patterns in a single run. The accuracy and quality of generated patterns are evaluated through multiple methods. The model developed does not only summarize a distribution of backscattered electrons at a higher level, but also offers a new idea of mitigating data scarcity in this field.
The first two years of COVID-19 in Italy: Incidence, lethality, and health policies
Authors: ferrante Pierpaolo 
Published: June 2022

Abstract
Background: The novel coronavirus disease is an ongoing pandemic that started in China in December 2019. This paper is aimed at providing a detailed picture of the first two years of the pandemic in Italy.Design and methods: Through the negative binomial distribution, we estimated the daily incidence of infections from the resulting deaths (estimated by the weighted moving average) and the virus lethality. The original strain lethality (assessed through national sero-surveys) was daily adjusted for hazard ratios of virus variants of concern and for the cumulative distribution of vaccinated people.Results: From the 24-th of February 2020 to the 28-th of February 2022, we estimated 20,833,018 (20,728,924-20,937,375) cases distributed over 5 waves. The overall lethality was 0.73% and daily ranged from 2.78% (in the first wave) to 0.15% (in the last one). The first two waves (affected by heavy restriction measures) showed the highest daily peaks of deaths (about 710), while the last one (affected by vaccines) showed the highest daily peak of infections (220,487). Restriction measures of population mobility strongly slowed the virus’s spread. During the second pandemic year, vaccines avoided almost 10,000,000 infections and saved almost 115,000 people.Conclusion: Mobility restriction measures are effective within a suppression strategy. Distance learning and smart working are effective within a mitigation strategy. A massive test campaign allowed monitoring of the virus’ spread, in particular within the younger population. Despite the variants of concern, vaccines strongly reduced the pandemic impact on the healthcare system and avoided strong restriction measures.
Rectal suction biopsy versus incisional rectal biopsy in the diagnosis of Hirschsprung Disease
Authors: Green Nicole , Smith Caitlin A. , Bradford Miranda C. , Ambartsumyan Lusine , Kapur Raj P 
Published: June 2022

Abstract
Background
Hirschsprung disease is one of the most common congenital anomalies that affects colorectal function. Rectal biopsy demonstrating the absence of ganglion cells in the affected bowel is the gold standard for diagnosis. Suction and incisional rectal biopsies are appropriate methods for obtaining diagnostic tissue. The goal of this study is to determine if any differences in adequacy exist between suction and incisional rectal biopsies at our institution.
Methods
We conducted a retrospective review of suction and incisional rectal biopsies for inadequacy per procedure at a tertiary pediatric hospital. Each procedure for rectal biopsy was also evaluated by number of biopsies per procedure. We used two-sample test of proportions to compare inadequacy of suction vs. incisional biopsies.
Results
133 rectal suction biopsy procedures (227 biopsies) and 125 incisional biopsy procedures (140 biopsies) were analyzed. In patients 6 months of age and older, the percentage of inadequate procedures was substantially higher in the suction biopsy group (24.1% vs 0.9%, p < 0.01).
Conclusions
A substantially higher proportion of inadequacy was found in suction rectal biopsy group compared to the incisional cohort among the older patient cohort, suggesting incisional biopsies should be strongly considered as primary rectal biopsy method in patients older than 6 months.
Three machine learning techniques comparison for the prediction of the uniaxial compressive strength of carbonate rocks
Authors: Hassan Mohamed Yusuf , Arman Hasan 
Published: June 2022

Abstract
In engineering practices, it is critical and necessary to either measure or estimate the uniaxial compressive strength (UCS) of the rock. Measuring the UCS of rocks requires comprehensive studies in the field and in the laboratory for the rock block sampling, coring and testing. These studies are time-consuming, expensive and go through difficult processes. Alternatively, the UCS can either be estimated by empirical relationships or predictive models with various measured mechanical and physical parameters of the rocks. Previous studies used different methods to predict UCS, including least squares regression techniques, adaptive neuro-fuzzy inference system, artificial neuron networks and others. This study is intended to estimate the UCS of the carbonate rock by using a simple, measured Schmidt Hammer (SHVC) test on core sample and a unit weight (γn) of carbonate rock. Principal components regression, multiple regression and artificial neural networks are employed to predict the UCS. We are not aware any study compared the performance of these methods for the prediction of the UCS values. The results of those models are very close; however, based on both roots mean square error (RMSE) and mean absolute error (MAE), artificial neural networks (ANN) have a slight advantage against the other two models.