bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the influence of different machining parameters and cooling and lubrication methods on the change of chip color on tool life
Authors: Chen S H , Liao T H , Chen J Y , Li Y J , Yang Z W , Lai H W 
Published: October 2022

Abstract
Cutting fluid has always been a commonly used cooling and lubrication method in machining. However, the traditional flood cooling method is not environmentally friendly, and the purchase of cutting fluid and disposal of waste fluid also create a lot of costs for employers. The emergence of MQL and air cooling can provide Due to the advantages of environmental protection and cost, this study uses three cutting conditions, dry, cold air gun and MQL, and two high and low cutting speeds to conduct experiments to record tool wear and analyze chip chromaticity. The results show that the two cooling methods are better than dry cutting. It can improve the tool life by about 40%, and with the increase of tool wear, the chip chromaticity also has a clear trend of change. The chip chromaticity data is predicted by the back-transmission neural network (BPNN), and the average absolute error percentage of the model is 11.12%. According to the prediction ability of the mean absolute percentage error (MAPE), this model has good prediction ability, and the relevant color and tool wear data will help to establish a tool wear prediction model for related materials and cooling methods in the future.
Study on friction properties of different abrasive materials and polylactic acid materials
Authors: Liu C T , Chang Y P , Yeh J W 
Published: October 2022

Abstract
In recent years, 3D printing technology is often used in various fields such as industry, medical care, and academia, because it can produce components with complex shapes at a lower cost than traditional processing. However, the size of 3D products is often limited by the printable range of printing equipment, so large objects often need to be disassembled and printed before joining. Friction stir welding is used to join different thermoplastics and has considerable potential for industrial applications, and the influence of the design of the welding tool on the formation of the welding zone is an important key. In this study, different abrasive materials and polylactic acid materials were used for friction, and the changes of friction coefficient and friction temperature during the friction process were discussed. The experimental results show the surface roughness of the abrasive tool has a significant effect on the coefficient of friction and temperature rise. As increasing the roughness of the abrasive tool, the wear scars, the cracks below the wear scar are both significant. It can be inferred from the crack shape that the PLA softens at high temperatures and then solidifies again, so the cracks are seen with a streamlined appearance, which means that the softened PLA can be carried by the abrasives tool with highly rough surfaces.
A recommendation model based on Stepped Six Channel CNN feature extraction
Authors: Chen Chuang , Zheng Shanhong , Zhan Qi , Guo Jia , Chen Jia 
Published: October 2022

Abstract
In a recommendation system, users and projects often do not exist independently. There are a lot of potential factors. Although the existing mainstream models can extract the potential features between users and projects, the extracted potential features are mainly high-order features and original features. We believe that there are many features at the intermediate level and the interaction between many features. Therefore, we proposed a Stepped Six Channel CNN network model (SSCC). By using different network depths to process the interaction information of user information and project attributes, the potential characteristics of multiple layers can be extracted, and feature layers of different channels are combined to form new feature channels. In addition, the network model based on DNN is used to predict the interaction between the user and the project, and the two models are combined in parallel to form a new model which name is Stepped Six Channel CNN&DNN(SSCCD). Our proposed model is clearly superior to some of today’s mainstream models through experimental tests on publicly available standard data sets.
Evaluation of climate change as a major determinant of crop yield improvement in Nigeria
Authors: Ologeh I , Adesina F 
Published: October 2022

Abstract
Climate change has adversely affected agricultural productivity leading to decline in food production. The influence of climate change on crops and livestock persists despite irrigation, improved plant and animal hybrids. The continued dependence of agricultural production on climatic factors and the relative dependence of human existence on agricultural products create the need for a comprehensive consideration of the relationship between climate and crop production. This study measured the relationship between annual maize/yam yield as dependent variable and seasonal rainfall as independent variables in four states in Nigeria. It has been proven in the past that yearly rainfall value has no influence on annual crop yield, but seasonal or monthly rainfall does. There is a positive and significant relationship between summed up rainfalls of June/July/August and annual maize yields for the thirty-five years under study. The bi-monthly rainfall values did not influence a major part of total annual maize yield, as it records weak relationship with annual maize yield. On the other hand, bi-monthly rainfall values (May/June and July/August) have positive and significant relationship with annual yam yield. The first quarter- March/April/May rainfall values for each of the states have a positive and significant relationship with annual yam yield. This implies that the rainfall value for this quarter is very essential for annual yam yield for each of the states.
Integrated management of limited water resources in Smart Cities
Authors: Šulyová D , Kubina M 
Published: October 2022

Abstract
The trend of urbanization and unsustainable consumption is causing a rapid decrease in limited water resources, which are a strategic source of sustainable development of the city. The aim of the article is i) to identify what technologies, strategies and models are used in the management of water resources in the concept of current Smart Cities, ii) according to the main findings of the analysis, to design own general model of integrated water resources management in the Smart City concept. The paper has used the secondary analysis, summarization method, comparison, induction, deduction and scientific controversy. The results of the analysis show that the strategic management of Smart Cities uses the technologies of the Internet of Things and machine learning in order to effectively manage water resources, in the management of water resources, prefers models containing feedback and an element of participation, from a strategy perspective, it is important to build a sensitive city through a well-defined vision. A city that manages water resources on these principles is a sensitive and sustainable territory that respects current conditions and responds to new challenges. The main output of the article is a general model of limited resource management in Smart City.
Analysis of Organic Flocculants in Lead and Cadmium Biosorption in Laboratory-Level Samples
Authors: Sernaque Fernando , Auccahuasi Wilver , Herrera Lucas , Rojas Karin , Ovalle Christian , Revilla Jorge Figueroa , Loza Ana Barrera 
Published: October 2022

Abstract
The intention of the work is to evaluate the absorption of lead and cadmium in water, by means of controlled tests, by means of a protocol based on the preparation of 3 types of concentrations of the indicated metals, in a water sample of 1 liter, the used dose of flocculants was made in 5 groups, with varied times of rest of are from 5 minutes to 30 minutes, the method that is presented to evaluate these concentrations, is characterized in being able to use different concentrations, with situations of controlled environment, the most encouraging result was the one that presents a level of concentration of 2. 5 grams of natural flocculant. In order to eliminate cadmium, we have a better response using flocculants based on coconut, grapefruit, tangerine, cucumber and apple fruits.
The Rise and Volatility of Russian Winter Wheat Production
Authors: Abys Christian , Skakun Sergii , Becker-Reshef Inbal 
Published: October 2022

Abstract
The Russian wheat industry experienced massive growth in the past two decades however, volatility in production and its subsequent impact on the global commodities market persists. In addition to significant growth, Russia surpassed the European Union as the top global exporter of wheat in 2016 and in 2020 winter wheat exports amounted to roughly $8 billion USD. The aim of this research is to investigate the observed trends and patterns of the growth in the Russian wheat production through the use of reported data on production, cropland area, yield and its associated yearly volatility. To conduct this research, statistical analysis was applied to data published by the Russian Ministry of Agriculture (RMA) and the United States Department of Agriculture Foreign Agriculture Service (USDA FAS). Statistics concerning Ukraine and Kazakhstan are included to gain a regional perspective. Results regarding Russia indicate a 149% increase in wheat production and a 35% increase in wheat farmland area with winter wheat accounting for a growing majority of this increase from 2000 to 2020. Of particular focus is yearly volatility in production of wheat, both spring and winter, which experienced significant yearly fluctuations of up to ±50% in both Russia and Ukraine. In addition, uncertainty in monthly forecasting of crop production published by the USDA FAS persists in both area and yield estimations. In Russia and Kazakhstan, USDA FAS wheat area forecasting was found to be the larger contributor to uncertainty in forecasting yearly production than yield and vice versa with Ukraine. Surging growth in the Russian wheat industry coupled with large volatility in yearly production have significant impacts on the global wheat market as well as lasting implications for land use and land cover change.
Improving parametric neural networks for high-energy physics (and beyond)
Authors: Anzalone Luca , Diotalevi Tommaso , Bonacorsi Daniele 
Published: October 2022

Abstract
Signal-background classification is a central problem in high-energy physics, that plays a major role for the discovery of new fundamental particles. A recent method—the parametric neural network (pNN)—leverages multiple signal mass hypotheses as an additional input feature to effectively replace a whole set of individual classifiers, each providing (in principle) the best response for the corresponding mass hypothesis. In this work we aim at deepening the understanding of pNNs in light of real-world usage. We discovered several peculiarities of parametric networks, providing intuition, metrics, and guidelines to them. We further propose an alternative parametrization scheme, resulting in a new parametrized neural network architecture: the AffinePNN; along with many other generally applicable improvements, like the balanced training procedure. Finally, we extensively and empirically evaluate our models on the HEPMASS dataset, along its imbalanced version (called HEPMASS-IMB) we provide here for the first time, to further validate our approach. Provided results are in terms of the impact of the proposed design decisions, classification performance, and interpolation capability, as well.
Pharmacokinetics of a single dose of novel curcumin formulations mixed with fish oils in healthy humans
Authors: Kanae Haruna , Teshima Koji , Shiroma Tamotsu , Noguchi Kazuo 
Published: October 2022

ABSTRACT
The pharmacokinetics of novel formulations of curcumin mixed with squalene (CSQU) and of curcumin mixed with docosahexaenoic acid (CDHA) was investigated and compared with a standardized unformulated curcumin extract (StdC) and a solid lipid curcumin particle (SLCP) formulation in a randomized, open-label, crossover study. A total of 10 healthy subjects consumed a single dose of each formulation, and blood samples were collected over 8 h. Plasma concentrations of curcumin, demethoxycurcumin (DMC), and bisdemethoxycurcumin (BDMC) were measured. The dose-normalized AUC0-8h of curcumin was significantly higher for SLCP (2.2-fold), CSQU (2.3-fold) and CDHA (2.8-fold) than for StdC. The dose-normalized AUC0-8h of DMC and BDMC did not significantly change, but their Tmax was significantly shortened for SLCP, CSQU, and CDHA. In conclusion, compared with StdC, both fish oil formulations, CSQU and CDHA, significantly improved curcumin absorption as well as SLCP, and CDHA was bioequivalent or superior to SLCP. No sex differences were observed in curcumin absorption.
Present and future of machine learning in breast surgery: systematic review
Authors: Soh Chien Lin , Shah Viraj , Arjomandi Rad Arian , Vardanyan Robert , Zubarevich Alina , Torabi Saeed , Weymann Alexander , Miller George , Malawana Johann 
Published: October 2022

Abstract

Background
Machine learning is a set of models and methods that can automatically detect patterns in vast amounts of data, extract information, and use it to perform decision-making under uncertain conditions. The potential of machine learning is significant, and breast surgeons must strive to be informed with up-to-date knowledge and its applications.

Methods
A systematic database search of Embase, MEDLINE, the Cochrane database, and Google Scholar, from inception to December 2021, was conducted of original articles that explored the use of machine learning and/or artificial intelligence in breast surgery in EMBASE, MEDLINE, Cochrane database and Google Scholar.

Results
The search yielded 477 articles, of which 14 studies were included in this review, featuring 73 847 patients. Four main areas of machine learning application were identified: predictive modelling of surgical outcomes; breast imaging-based context; screening and triaging of patients with breast cancer; and as network utility for detection. There is evident value of machine learning in preoperative planning and in providing information for surgery both in a cancer and an aesthetic context. Machine learning outperformed traditional statistical modelling in all studies for predicting mortality, morbidity, and quality of life outcomes. Machine learning patterns and associations could support planning, anatomical visualization, and surgical navigation.

Conclusion
Machine learning demonstrated promising applications for improving breast surgery outcomes and patient-centred care. Neveretheless, there remain important limitations and ethical concerns relating to implementing artificial intelligence into everyday surgical practices.
Impact of the first wave of COVID-19 on outcomes following emergency admissions for common acute surgical conditions: analysis of a national database in England
Authors: Hutchings Andrew , Moonesinghe Ramani , Moler Zapata Silvia , Cromwell David , Bellingan Geoff , Vohra Ravinder , Moug Susan , Smart Neil , Hinchliffe Robert , Grieve Richard 
Published: October 2022

AbstractBackgroundThis study assessed the impact of the first COVID-19 wave in England on outcomes for acute appendicitis, gallstone disease, intestinal obstruction, diverticular disease, and abdominal wall hernia.MethodsEmergency surgical admissions for patients aged 18 years and older to 124 NHS Trust hospitals between January and June in 2019 and 2020 were extracted from Hospital Episode Statistics. The risk of 90-day mortality after admission during weeks 11–19 in 2020 (national lockdown) and 2019 (pre-COVID-19) was estimated using multilevel logistic regression with case-mix adjustment. The primary outcome was all-cause mortality at 90 days.ResultsThere were 12 231 emergency admissions and 564 deaths within 90 days during weeks 11–19 in 2020, compared with 18 428 admissions and 542 deaths in the same interval in 2019. Overall, 90-day mortality was higher in 2020 versus 2019, with an adjusted OR of 1.95 (95 per cent c.i. 0.78 to 4.89) for appendicitis, 2.66 (1.81 to 3.92) for gallstone disease, 1.99 (1.44 to 2.74) for diverticular disease, 1.70 (1.13 to 2.55) for hernia, and 1.22 (1.01 to 1.47) for intestinal obstruction. After emergency surgery, 90-day mortality was higher in 2020 versus 2019 for gallstone disease (OR 3.37, 1.26 to 9.02), diverticular disease (OR 2.35, 1.16 to 4.73), and hernia (OR 2.34, 1.23 to 4.45). For intestinal obstruction, the corresponding OR was 0.91 (0.59 to 1.41). For admissions not leading to emergency surgery, mortality was higher in 2020 versus 2019 for gallstone disease (OR 2.55, 1.67 to 3.88), diverticular disease (1.90, 1.32 to 2.73), and intestinal obstruction (OR 1.30, 1.06 to 1.60).ConclusionEmergency admission was reduced during the first lockdown in England and this was associated with higher 90-day mortality.
SPONGE-assisted versus Trendelenburg position surgery in laparoscopic sigmoid and rectal cancer surgery (SPONGE trial): randomized clinical trial
Authors: Fahim Milad , Couwenberg Alice , Verweij Maaike E , Dijksman Lea M , Verkooijen Helena M , Smits Anke B 
Published: October 2022

Abstract

Background
In minimally invasive surgery of the sigmoid colon and rectum a retractor sponge has been introduced as an alternative to the Trendelenburg position. This randomized clinical trial (RCT) compared postoperative duration of hospital stay and perioperative outcomes in patients with sigmoid or rectal cancer undergoing sponge-assisted versus Trendelenburg position surgery.

Methods
The SPONGE trial is a single-centre RCT nested within the Dutch nationwide prospective observational cohort of patients with colorectal cancer, and follows the Trials within Cohorts (TwiCs) design. Patients with sigmoid or rectal cancer undergoing elective laparoscopic or robotic surgery were randomized to either sponge-assisted or Trendelenburg surgery on a 1:1 basis using block randomization. Duration of postoperative hospital stay was the primary outcome and was compared using the Mann–Whitney U test. Secondary endpoints included the proportion of complications, readmissions, or mortality versus the χ2 test in intention-to-treat and per-protocol analyses. This trial was not blinded for patients in the intervention arm or physicians.

Results
Between November 2015 and June 2021, 82 patients were randomized to sponge-assisted surgery and 81 to Trendelenburg surgery. After post-randomization exclusion, 150 patients remained for analyses (75 patients per arm). There was no statistically significant difference in median duration of hospital stay (5 days versus 4 days, respectively; P = 0.06), 30-day postoperative complications (30 per cent versus 31 per cent; P = 1.00), readmission rate (8 per cent versus 15 per cent; P = 0.30), or mortality (0 per cent versus 1 per cent, P = 1.00). The per-protocol analysis showed similar results. No adverse device events were seen.

Conclusion
Sponge-assisted laparoscopic/robotic surgery does not reduce the duration of hospital stay, or perioperative morbidity or mortality.

Trial registration
NCT02574013 (http://www.clinicaltrials.gov)
Limited liver resections in the posterosuperior segments: international multicentre propensity score-matched and coarsened exact-matched analysis comparing the laparoscopic and robotic approaches
Authors: D’Silva Mizelle , Han Ho Seong , Liu Rong , Kingham Thomas Peter , Choi Gi Hong , Syn Nicholas Li Xun , Prieto Mikel , Choi Sung Hoon , Sucandy Iswanto , Chiow Adrian Kah Heng , Marino Marco Vito , Efanov Mikhail , Lee Jae Hoon , Sutcliffe Robert Peter , Chong Charing Ching Ning , Tang Chung Ngai , Cheung Tan To , Pratschke Johann , Wang Xiaoying , Park James Oh , Chan Chung Yip , Scatton Olivier , Rotellar Fernando , Troisi Roberto Ivan , D’Hondt Mathieu , Fuks David , Goh Brian Kim Poh ,   international robotic and laparoscopic liver resection study group investigators, Gastaca M , Schotte H , De Meyere C , Lai E C , Krenzien F , Schmelzle M , Kadam P , Giglio M , Montalti R , Liu Q , Lee K F , Lee L S , Jang J Y , Lim C , Labadie K P 
Published: October 2022

AbstractBackgroundLimited liver resections (LLRs) for tumours located in the posterosuperior segments of the liver are technically demanding procedures. This study compared outcomes of robotic (R) and laparoscopic (L) LLR for tumours located in the posterosuperior liver segments (IV, VII, and VIII).MethodsThis was an international multicentre retrospective analysis of patients who underwent R-LLR or L-LLR at 24 centres between 2010 and 2019. Patient demographics, perioperative parameters, and postoperative outcomes were analysed; 1 : 3 propensity score matching (PSM) and 1 : 1 coarsened exact matching (CEM) were performed.ResultsOf 1566 patients undergoing R-LLR and L-LLR, 983 met the study inclusion criteria. Before matching, 159 R-LLRs and 824 L-LLRs were included. After 1 : 3 PSM of 127 R-LLRs and 381 L-LLRs, comparison of perioperative outcomes showed that median blood loss (100 (i.q.r. 40–200) versus 200 (100–500) ml; P = 0.003), blood loss of at least 500 ml (9 (7.4 per cent) versus 94 (27.6 per cent); P &lt; 0.001), intraoperative blood transfusion rate (4 (3.1 per cent) versus 38 (10.0 per cent); P = 0.025), rate of conversion to open surgery (1 (0.8 per cent) versus 30 (7.9 per cent); P = 0.022), median duration of Pringle manoeuvre when applied (30 (20–46) versus 40 (25–58) min; P = 0.012), and median duration of operation (175 (130–255) versus 224 (155–300); P &lt; 0.001) were lower in the R-LLR group compared with the L-LLR group. After 1 : 1 CEM of 104 R-LLRs with 104 L-LLRs, R-LLR was similarly associated with significantly reduced blood loss and a lower rate of conversion to open surgery.ConclusionBased on a matched analysis of well selected patients, both robotic and laparoscopic access could be undertaken safely with good outcomes for tumours in the posterosuperior liver segments.