bluuebunny/crossref_metadata_2025_split huggingface dataset:
Justification of the methods of material and technical maintenance and repair of agricultural machines
Authors: Toigambayev S , Martinova N , Shavazov K , Telovov N 
Published: June 2022

Abstract
This work substantiates the rational structure of the repair and maintenance base of agricultural machinery, methods for determining the needs for material and technical means, taking into account the appropriate proportions between the links of the repair network. The maintenance and restoration of the operability of tractors and other agricultural machines in sufficient limits is ensured, as is known, with the help of a system of maintenance and repair, which provides for the implementation of preventive maintenance operations and the conduct of routine and major repairs of machines in a planned manner. The established system of maintenance and repair, the creation of a material and technical basis for its implementation, as well as a continuous process of improving the qualifications of machine operators and repair personnel, contribute to the effective use of equipment in agriculture. At the same time, there are significant disadvantages in the use of tractors and agricultural machines. The analysis of the results of numerous studies of VIMa, ChIMESXa and other organizations made it possible to identify and systematize the loss of time due to machine downtime. In particular, machine downtime for regulated maintenance is 10-15% of the shift time, for technical malfunctions - from 5-8% for plowing, up to 30% for harvesting crops. The volume of work on the repair of cars in the country as a whole is more than 2 times higher than the standard. The efficiency of maintenance and repair of machines largely depends on the level of the material and technical base of these works - the availability of modern equipment and tooling, industrial buildings, warehouses, and other structures, inventories, means of transport and communications.
Mathematical modeling of energy consumption in the production of hydrogen
Authors: Klyuev R V , Guzueva E R , Kunitsyn A G 
Published: June 2022

Abstract
The article discusses the technological process of hydrogen production at metallurgy. Mathematical models of the dependence of power consumption and specific consumption depending on various parameters have been obtained, which make it possible to calculate and predict. In the electrolyzer, the change in the component of the specific power consumption by the amount of potassium dichromate (chromium peak) over time is analyzed. Therefore, the analysis of the dependence of the specific power consumption in time was carried out directly on the basis of the results of an experimental study of the dependence of the change in time of the voltage on the electrolyzer when the electrolyzer was loaded with chromium peak. The most important issue of reducing electricity consumption due to the use of a gas holder in the mode of consumer-regulator has been investigated. Controlling the level of deviations in power consumption (±2%) in comparison with the normative (±5%) allows increasing the margin of "safety" in terms of load regulation time, reducing the likelihood of it going beyond the normative level and, accordingly, reducing the payment for deviations in the volume of electrical energy consumption.
Methodological support for increasing the technological potential in industry according to technological potential level and cyclical development
Authors: Sokolov A A , Samonova K V , Umarkhadzhiev M-Kh. R 
Published: June 2022

Abstract
The article discusses the issues of increasing the level of technological potential on the example of the Russian economy in the form of targeted state intervention during the implementation of import substitution. In the paper, the increase in technological capabilities is investigated taking into account the life cycle of the industry. The practical application of methods for assessing the level and vector of technological potential, as well as a dynamic model of organizational decision-making, is displayed.
Particle Image Velocimetry measurements in a turbulent channel flow laden with elongated particles
Authors: Capone Alessandro , Felice Fabio Di , Pereira Francisco Alves 
Published: June 2022

Abstract
Particle Image Velocimetry is employed to investigate the turbulence modulation induced by dispersed elongated, rod-like particles in a turbulent channel flow. Particles with two different aspect ratios AR=40,80 are tested, at a volume fraction of 10-5. Carrier flow velocimetry data and distribution and orientation data of dispersed particles are obtained by an ad-hoc single-camera phase-discrimination technique. Carrier flow data shows that in the near-wall region turbulence modulation by particle occurrs as well as a decrease of average streamwise velocity. Analysis of conditional probability density function of particles location reveals that particles locations statistically match flow regions with instantaneous low vorticity and high streamwise velocity, in particular in the near-wall region.
Estimation of Equivalent Conicity from Contactless Measurements of Wheel and Rail Profiles
Authors: Pugi L. , Bocciolini L. , Piccioli F. , Massini D. , Cherici G. , Lo Scalzo L. 
Published: June 2022

Abstract
Measurement of Equivalent Conicity is quite important index to properly evaluate geometric quality of rails and wheels. The way in which this index is evaluated is evaluated is described by the standard EN 15302 from online contactless measurement of rail profiles performed by a dedicated measurement coach. The numerical treatment of large amount of data derived by the acquisition of a huge number of measured rail profiles should be performed with great accuracy but also with a great numerical efficiency to assure a near to real time evaluation of performed analysis. In this work authors describe an efficient procedure developed using open-source software that has been developed to meet accuracy, efficiency, and portability specifications. Paper investigates how different integration and smoothing should affect efficiency and accuracy of performed operations. Proposed approach is first validated on numerical synthetic inputs and then validated on experimental data, also comparing performances of the proposed software with a commercial one. Results are encouraging, demonstrating the feasibility of the proposed approach for the realization of flexible and efficient tools for Real-Time implementation of the estimation of equivalent conicity for railway applications.
Potentially Automated Mechanical Characterization of Metal Components by Means of Hardness Test Complemented by Non-Contact 3D Measurement
Authors: Bolzon Gabriella 
Published: June 2022

Abstract
Metal structures and infrastructures subjected to demanding working conditions must be carefully monitored throughout their entire life cycle. In fact, high operating temperatures and interaction with aggressive environments produce significant variation of the mechanical characteristics of the materials, and eventually compromise the overall structural integrity. The evolution over time of metal properties can be determined in fast, cheap and non-destructive manner by hardness tests, processing the data that describe the geometry of the residual deformation left on the indented surface. The required equipment can be mounted on the arms of collaborative robots, and/or on frames that move on wheels or rails, to detect the material characteristics automatically, over large distances and with high spatial resolution. The reliability of such a diagnostic approach depends on the accuracy of the information that can be collected, in situ, by portable devices that perform 3D contactless measurement, and on the robustness of the data filtering and interpretation procedures. These issues are illustrated in this contribution.
Digital Image Correlation analysis on the bone displacement during split crest: an ex vivo study
Authors: Lugas A T , Terzini M , Stacchi C , Lombardi T , Di Donato D , Baldi D , Schierano G , Bignardi C 
Published: June 2022

Abstract
The split crest is an established surgical technique for horizontal bone augmentation. It allows to place implants of adequate diameter in sites where the bone would be too thin for the implantation. In this study, two split crest techniques (using threaded bone expanders or ultrasonic bone surgery) were performed ex vivo on bovine ribs, and dental implants were then inserted in the so prepared implantation sites. Digital image correlation was used to measure the bone external surface displacement throughout the surgical procedures. Both techniques provided an adequate bone volume for implant insertion, and no significant differences were highlighted regarding the displacement. However, bone accidental fracture only occurred during split crest with threaded bone expanders, suggesting differences in the internal strain distribution induced by the two techniques.
Plastic Flow Characteristics of Micro Single-Crystal Copper
Authors: Li Sheng , Su Ting , Yan Yabin 
Published: June 2022

Abstract
In order to study the plastic flow characteristics of micro single-crystal Cu, an in-situ uniaxial loading test was carried out. The slip direction of the test is determined by the Schmidt factor, which is at 1μm~4μm. Within the micropillar size range, the sample has an obvious size effect. This is essentially due to the continuous proliferation of dislocations in the micropillar flowing out of the surface. The smaller the size, the more difficult it is to store dislocations, and the easier dislocations flow out. Therefore, the yield stress significantly increases with the increment of sample diameter. This study provides guidance for the reliability evaluation of microscale components based on the single-crystal Cu.
Axial segragation in 3D rotating drums with spherical particles: Experiments
Authors: Tang Linglong 
Published: June 2022

Abstract
Despite the wide research of powder and solid mixing in science and industry, a majority of researches focus on numerical simulation. Theory on the actual mixing of solid particles in 3D rotary drums is needed. In this work, the axial segregation of binary spherical granular particle is studied experimentally in a 3D tumbler to find the effect of key outer parameters on the mixing results. Experiment results indicate the outer parameter-rotational speed will have significant effect on axial segregation and there is some kind of competition between axial segregation and radial segregation. In addition, The initial loading method has noting to do with axial segregation. These results will provide guidance for particle mixing in cylinder mixer.
Clusters and cooperatives as a tool of sustainable food security: a comparative analysis
Authors: Mindlin Yury , Novikov Mikhail , Ignatyeva Olga 
Published: June 2022

Abstract
The present model of development of the Russian agriculture, characterized by domination of large agri-food companies, creates threats for sustainable development of small agricultural business (local and family farms). Potential disappearance of these small businesses from the market would undermine the sustainability of the Russian agriculture and the food security of Russian Federation. In order to survive in this unfavorable environment, small business should combine their resources, participate in agri-food value chains and get access to Russian and global food market. The goal of the present paper is to identify potential strategies of development of small agricultural business within different models of cooperation. The paper contains a detailed analysis of key features of clusters and cooperatives. It is demonstrated that clusters as flexible structures have a higher potential of resource accumulation thanks to absence of limitations for potential members. Clusters also ensure trans-border cooperation. All these features are absent in agricultural cooperatives. Due to these facts clusters should be preferred to cooperatives as a tool of strategic development of small agricultural business. However cooperatives can be used as an additional tool. Cooperatives can participate in clusters. These conclusions constitute the contribution of the present paper for practice. In addition to this recommendation for selection of strategies of small business development, the comparative analysis of clusters and cooperatives helped to identify the key distinctive features of clusters as institutional structures. Knowledge of these features may be useful for analysis of cluster development. This result is the theoretical contribution of the present paper.
Inverse design of programmable optical frequency comb using deep learning
Authors: Ma Yunjie , Li Peili , Shi Weihua 
Published: June 2022

Abstract
Optical frequency comb (OFC) has important applications in measurement, communication, military and other fields. Usually, OFC needs to be designed according to different applications. However, the existing methods to design the operating parameters of the OFC generators are time-consuming, inefficient, and difficult to achieve optimal results. In this paper, a novel method of inversely designing OFC using deep learning, which is real-time and can improve the performance of the generated OFC, is proposed and applied to an OFC generator based on a single dual-drive Mach–Zehnder modulator. In this method, according to the required target OFC, the trained neural network can be used to inversely design the corresponding parameters. Using this inverse design method, the generated OFC not only is highly consistent with the target OFC, but also has the programmability of comb-line number, comb-line power, side mode suppression ratio, and comb spacing. Moreover, the proposed method can be utilized for more complicated OFC generator, and is an inspiration for efficient design of OFC.
The Future of Causal Inference
Authors: Mitra Nandita , Roy Jason , Small Dylan 
Published: June 2022

AbstractThe past several decades have seen exponential growth in causal inference approaches and their applications. In this commentary, we provide our top-10 list of emerging and exciting areas of research in causal inference. These include methods for high-dimensional data and precision medicine, causal machine learning, causal discovery, and others. These methods are not meant to be an exhaustive list; instead, we hope that this list will serve as a springboard for stimulating the development of new research.
Effect of Schooling on Anemia and Nutritional Status Among Women: A Natural Experiment in Ethiopia
Authors: Muchomba Felix M 
Published: June 2022

AbstractThis study estimates the effect of length of schooling on anemia and nutritional status and evaluates the cost-effectiveness of primary schooling as an anemia intervention for women of childbearing age in Ethiopia. In 1994–1995, Ethiopia abolished primary school tuition fees and embarked on a large-scale educational investment program, which increased primary school enrollment and retention. An instrumented regression-discontinuity design was used to examine the effect on anemia risk and body mass index (BMI) of an increase in length of schooling resulting from the reforms, as a natural experiment. Anemia and BMI biomarkers and demographic data for 13,984 women were obtained from the 2011 and 2016 Ethiopia Demographic and Health Surveys, with the 2019 Mini Demographic and Health Survey used for robustness checks. Results indicate that each additional year of schooling reduced anemia risk by 3 percentage points (9.2%–11.2% reduction) and increased BMI (weight (kg)/height (m)2) by 0.26–0.42. Primary education was cost-effective—based on World Health Organization cost-effectiveness thresholds—as an anemia intervention, with a cost per anemia case averted of US$1,654. The findings suggest that investment in education reduces anemia risk later in life.
Use of Cosmetic Facial Injectables After Facial Aesthetic Surgery
Authors: Talwar Ankoor A , Shulkin Jared M , Hitchner Michaela , McAuliffe Phoebe B , Desai Abhishek A , Broach Robyn B , Percec Ivona 
Published: June 2022

Abstract

Background
Over the last 2 decades, both invasive and minimally invasive aesthetic procedures have proliferated. Aesthetic surgeons often recommend injectable treatments after cosmetic facial surgery for multiple reasons. However, literature is lacking on how cosmetic surgery affects postoperative facial injectable use.

Objectives
The aim of this study was to identify predictors of facial injectable use after cosmetic facial surgery.

Methods
All adult patients operated on by a single surgeon between 2013 and 2021 were retrospectively reviewed. Patients who had any of the following cosmetic facial surgeries were included: rhytidectomy, blepharoplasty, rhinoplasty, or genioplasty. Patient demographics, clinical history, intraoperative factors, and use of cosmetic facial injectables (neurotoxin, facial fillers, deoxycholic acid, poly-l-lactic acid) were recorded.

Results
A total of 227 patients who underwent facial cosmetic surgery were reviewed, of whom 158 were included. Of these, 89 patients had rhytidectomy (56.3%), 112 had blepharoplasty (70.9%), 28 had rhinoplasty (17.7%), and 7 had genioplasty (4.4%). Injectables were administered to 44.3% of patients after their surgery (n = 73), compared with only 17.7% before surgery (n = 28) (P &lt; 0.001). The most common postoperative injectables were neurotoxins (48.5%) and facial fillers (46.0%), followed by deoxycholic acid (2.7%) and poly-l-lactic acid (2.7%). Multivariate regression revealed factors positively correlated with future injectable use were index blepharoplasty or rhinoplasty, and history of preoperative neurotoxin injection (P &lt; 0.05).

Conclusions
Cosmetic facial injectables are an important consideration in achieving and maintaining optimal facial aesthetics. Their use, especially neurotoxins and facial fillers, has increased among patients postoperatively. These results highlight the contribution of injectable procedures in the context of multidimensional care for augmenting facial aesthetics.

Level of Evidence: 4
Outlier detection for multi-network data
Authors: Dey Pritam , Zhang Zhengwu , Dunson David B 
Published: June 2022

AbstractMotivationIt has become routine in neuroscience studies to measure brain networks for different individuals using neuroimaging. These networks are typically expressed as adjacency matrices, with each cell containing a summary of connectivity between a pair of brain regions. There is an emerging statistical literature describing methods for the analysis of such multi-network data in which nodes are common across networks but the edges vary. However, there has been essentially no consideration of the important problem of outlier detection. In particular, for certain subjects, the neuroimaging data are so poor quality that the network cannot be reliably reconstructed. For such subjects, the resulting adjacency matrix may be mostly zero or exhibit a bizarre pattern not consistent with a functioning brain. These outlying networks may serve as influential points, contaminating subsequent statistical analyses. We propose a simple Outlier DetectIon for Networks (ODIN) method relying on an influence measure under a hierarchical generalized linear model for the adjacency matrices. An efficient computational algorithm is described, and ODIN is illustrated through simulations and an application to data from the UK Biobank.ResultsODIN was successful in identifying moderate to extreme outliers. Removing such outliers can significantly change inferences in downstream applications.Availability and implementationODIN has been implemented in both Python and R and these implementations along with other code are publicly available at github.com/pritamdey/ODIN-python and github.com/pritamdey/ODIN-r, respectively.Supplementary informationSupplementary data are available at Bioinformatics online.
Multiple Blind Signature for e-Voting and e-Cash
Authors: Harn Lein , Hsu Chingfang , Xia Zhe , Li Zixuan 
Published: June 2022

Abstract
In this paper, we propose a new cryptographic primitive, called multiple blind signature (MBS), which is designed based on the integration of both normal blind signature scheme and dual signature. The major difference between a normal blind signature and an MBS is that using a normal blind signature, only one message, $m$, can be verified, but using an MBS, any subset, ${M}^{\prime }$, of multiple messages in a set, $M$, where ${M}^{\prime}{\subseteq} M$, can be verified. With this additional property, we will show that MBS is especially suitable for e-voting and e-cash applications. In other words, we classify these processes in two applications into two phases, on-line and off-line phases. One unique property of this design is that most time-consuming computation and interaction can be performed in advance in off-line phase. There is no cost of computation and interaction in the online phase.
Matched field processing accounting for complex Earth structure: method and review
Authors: Schippkus Sven , Hadziioannou Céline 
Published: June 2022

SUMMARYMatched field processing (MFP) is a technique to locate the source of a recorded wavefield. It is the generalization of plane-wave beamforming, allowing for curved wave fronts. In the standard approach to MFP, simple analytical Green’s functions are used as synthetic wavefields that the recorded wavefields are matched against. We introduce an advancement of MFP by utilizing Green’s functions computed numerically for Earth structure as synthetic wavefields. This allows in principle to incorporate the full complexity of elastic wave propagation without further manual considerations, and through that provide more precise estimates of the recorded wavefield’s origin. We call this approach numerical MFP (nMFP). To demonstrate the applicability and potential of nMFP, we present two real data examples, one for an earthquake in Southern California, and one for secondary microseism activity in the Northeastern Atlantic and Mediterranean Sea. In addition, we explore and clarify connections between localization approaches for the ambient seismic field, real world limitations, and identify key areas for future developments. To increase the adoption of MFP in the seismological community, tutorial code is provided.
Response to a commentary by Barr (2022) on Edoka and Stacey (2020) estimating a cost-effectiveness threshold for healthcare decision-making in South Africa
Authors: Edoka Ijeoma , Stacey Nicholas 
Published: June 2022

Abstract
Methodological issues pose significant challenges to estimating marginal cost per unit of health. In this commentary, we revisit these challenges and respond to a recent commentary on the validity of previously estimated marginal cost per unit of health in South Africa.