bluuebunny/crossref_metadata_2025_split huggingface dataset:
A protocol for analysing the effects on health and greenhouse gas emissions of implemented climate change mitigation actions
Authors: Hassan Syreen , Cuevas Garcia-Dorado Sol , Belesova Kristine , Murage Peninah , Whitmee Sarah , Huxley Rachel , Green Rosemary , Haines Andrew 
Published: May 2022

Background: It is crucial to understand the benefits to human health from decarbonisation to galvanise action among decision makers. Most of our existing evidence comes from modelling studies and little is known about the extent to which the health co-benefits of climate change mitigation actions are realised upon implementation. We aim to analyse evidence from mitigation actions that have been implemented across a range of sectors and scales, to identify those that can improve and sustain health, while accelerating progress towards a zero-carbon economy. Objectives: To understand the implementation process of actions and the role of key actors; explain the contextual elements influencing these actions; summarise what effects, both positive and negative, planned and unplanned they may have on emissions of greenhouse gases and health; and to summarise environmental, social, or economic co-benefits. Data: We will review evidence collected through partnership with existing data holders and an open call for evidence. We will also conduct a hand search of reference lists from systematic reviews and websites of organisations relevant to climate change mitigation. Screening: Screening will be done by two reviewers according to a pre-defined inclusion and exclusion criteria. Analysis: We will identify gaps where implementation or evaluation of implementation of mitigation actions is lacking. We will synthesise the findings to describe how actions were implemented and how they achieved results in different contexts, identifying potential barriers and facilitators to their design, implementation, and uptake. We will also synthesise their effect on health outcomes and other co-benefits. Quantitative synthesis will depend on the heterogeneity of outcomes and metrics. Conclusions: Findings will be used to identify lessons that can be learned from successful and unsuccessful mitigation actions, to make inferences on replicability, scalability, and transferability and will contribute to the development of frameworks that can be used by policy makers.
Survival outcomes with warfarin compared with direct oral anticoagulants in cancer-associated venous thromboembolism in the United States: A population-based cohort study
Authors: Khan Adeel M. , Chiasakul Thita , Redd Robert , Patell Rushad , McCarthy Ellen P. , Neuberg Donna , Zwicker Jeffrey I. 
Published: May 2022

Background
Direct oral anticoagulants (DOACs) have comparable efficacy with low-molecular-weight heparin (LMWH) for the treatment of cancer-associated venous thromboembolism (VTE). Whether there is a mortality benefit of DOACs compared with warfarin in the management of VTE in cancer is not established.

Methods and findings
Utilizing the United States’ Surveillance, Epidemiology, and End Results (SEER)-Medicare linked databases from 2012 through 2016, we analyzed overall survival in individuals diagnosed with a primary gastric, colorectal, pancreas, lung, ovarian, or brain cancer and VTE who received a prescription of DOAC or warfarin within 30 days of VTE diagnosis. Patients were matched 1:2 (DOAC to warfarin) through exact matching for cancer stage and propensity score matching for age, cancer site, cancer stage, and time interval from cancer to VTE diagnosis. The analysis identified 4,274 patients who received a DOAC or warfarin for the treatment of VTE within 30 days of cancer diagnosis (1,348 in DOAC group and 2,926 in warfarin group). Patients were of median age 75 years and 56% female. Within the DOAC group, 1,188 (88%) received rivaroxaban, and 160 (12%) received apixaban. With a median follow-up of 41 months, warfarin was associated with a statistically significantly higher overall survival compared to DOACs (median overall survival 12.0 months [95% confidence interval (CI): 10.9 to 13.5] versus 9.9 months [95% CI: 8.4 to 11.2]; hazard ratio (HR) 0.85; 95% CI: 0.78 to 0.91; p < 0.001). Observed differences in survival were consistent across subgroups of cancer sites, cancer stages, and type of VTE. The study limitations include retrospective design with potential for unaccounted confounders along with issues of generalizability beyond the cancer diagnoses studied.

Conclusions
In this analysis of a population-based registry, warfarin was associated with prolonged overall survival compared to DOACs for treatment of cancer-associated VTE.
The impact of working in academia on researchers’ mental health and well-being: A systematic review and qualitative meta-synthesis
Authors: Nicholls Helen , Nicholls Matthew , Tekin Sahra , Lamb Danielle , Billings Jo 
Published: May 2022

Objective
To understand how researchers experience working in academia and the effects these experiences have on their mental health and well-being, through synthesizing published qualitative data.

Method
A systematic review and qualitative meta-synthesis was conducted to gain a comprehensive overview of what is currently known about academic researchers’ mental health and well-being. Relevant papers were identified through searching electronic databases, Google Scholar, and citation tracking. The quality of the included studies was assessed and the data was synthesised using reflexive thematic analysis.

Results
26 papers were identified and included in this review. Academic researchers’ experiences were captured under seven key themes. Job insecurity coupled with the high expectations set by the academic system left researchers at risk of poor mental health and well-being. Access to peer support networks, opportunities for career progression, and mentorship can help mitigate the stress associated with the academic job role, however, under-represented groups in academia are at risk of unequal access to resources, support, and opportunities.

Conclusion
To improve researchers’ well-being at work, scientific/academic practice and the system’s concept of what a successful researcher should look like, needs to change. Further high-quality qualitative research is needed to better understand how systemic change, including tackling inequality and introducing better support systems, can be brought about more immediately and effectively. Further research is also needed to better understand the experiences and support needs of post-doctoral and more senior researchers, as there is a paucity of literature in this area.

Trial registration
The review protocol was registered on PROSPERO (CRD42021232480).
Weed Management in Direct Seeded Rice under Different Row Spacing
Authors: Ul Abidin Muhammad Zain , Muskan Komal , Alim Danish , Khalid M Armaghan , Adnan Muhammad , Abbas Waheed 
Published: May 2022

A field study to evaluate the weed management in direct seeded rice under different row spacing was carried out at Agronomic Research Area, University of Agriculture, Faisalabad during summer 2018. Two herbicides Butachlor @ 118.61 g a.i. ha-1 (pre-emergence) was applied within 24 hours of sowing of direct seeded rice and combination of two herbicides Butachlor @ 118.61 g a.i. ha-1 (pre-emergence) within 24 hours after sowing sequentially followed by Bispyribac Sodium + Bensulfurin Methyl @ 26.7 g a.i. ha-1 + 17.8 g a.i. ha-1 (post-emergence) was applied 15 days after sowing. Bispyribac Sodium @ 26.7 g a.i. ha-1 was applied 15 days after sowing. A weedy check and weed free treatment were also run for comparison. A fine rice cultivar (Basmati 515) was sown during the last week of June in 22.5 cm and 11.25 cm spaced rows using a seed rate of 29 kg ha-1. To fulfill the requirement of nutrients 135 kg N, 88 kg P and 61 kg ha-1 K were applied. The experiment was replicated thrice in a randomized complete block design under split plot arrangement. The net plot size was 3 m × 2.25 m. Date regarding weed density (15, 30 and 45 DAS), weed biomass before harvesting and yield components of rice were recorded by following standard procedures and statistically analyzed by applying Fisher’s analysis of variance technique. Least significant difference test (LSD) at 5% probability was used to compare treatments means. Results of the study showed that total weed density and weed dry weight were significantly influenced by different row spacing and weed control treatments. Significantly lower weed density and weed biomass were observed under narrow row spacing (11.25 cm) as compared to wider row spacing (22.5 cm). Among weed control treatments application of Butachlor @ 118.61 g a.i. ha-1 (pre-emergence) within 24 hrs after sowing of DSR and Bispyribac Sodium @ 26.7 g a.i. ha-1 (15 DAS) reduced the total weed density and weed dry weight. Similarly, paddy yield was also significantly influenced by different row spacing and weed control treatments as weed free at 11.25 cm row spacing gave maximum paddy yield (4.0 t ha-1).
Auditory sEMG biofeedback for reducing muscle co‐contraction during pedaling
Authors: Kibushi Benio , Okada Junichi 
Published: May 2022

AbstractMuscle co‐contraction between the agonist and antagonist muscles often causes low energy efficiency or movement disturbances. Surface electromyography biofeedback (sEMG‐BF) has been used to train muscle activation or relaxation but it is unknown whether sEMG‐BF reduces muscle co‐contraction. We hypothesized that auditory sEMG‐BF improves muscle co‐contraction. Our purpose was to investigate whether auditory sEMG‐BF is effective in improving muscle co‐contraction. Thirteen participants pedaled on a road bike using four different auditory sEMG‐BF conditions. We measured the surface electromyography at the lower limb muscles. The vastus lateralis (VL) and the semitendinosus (ST) activities were individually transformed into different beep sounds. Four feedback conditions were no‐feedback, VL feedback, ST feedback, and both VL and ST feedback. We compared the co‐contraction index (COI) of the knee extensor‐flexor muscles and the hip flexor‐extensor muscles among the conditions. There were no significant differences in COIs among the conditions (p = 0.83 for the COI of the knee extensor‐flexor; p = 0.32 for the COI of the hip flexor‐extensor). To improve the muscle co‐contraction by sEMG‐BF, it may be necessary to convert muscle activation into a muscle co‐contraction. We concluded that individual sEMG‐BF does not immediately improve muscle co‐contraction during pedaling.
Non-woven textiles for medical implants: mechanical performances improvement
Authors: Lequeux Amandine , Maze Benoit , Laroche Gaetan , Heim Frederic 
Published: May 2022

Abstract
Non-woven textile has been largely used as medical implant material over the last decades, especially for scaffold manufacturing purpose. This material presents a large surface area-to-volume ratio, which promotes adequate interaction with biological tissues. However, its strength is limited due to the lack of cohesion between the fibers. The goal of the present work was to investigate if a non-woven substrate can be reinforced by embroidery stitching towards strength increase. Non-woven samples were produced from both melt-blowing and electro-spinning techniques, reinforced with a stitching yarn and tested regarding several performances: ultimate tensile strength, burst strength and strength loss after fatigue stress. Several stitching parameters were considered: distance between stitches, number of stitch lines (1, 2 or 3) and line geometry (horizontal H, vertical L, cross X). The performance values obtained after reinforcement were compared with values obtained for control samples. Results bring out that reinforcement can increase the strength by up to 50% for a melt-blown mat and by up to 100% for an electro-spun mat with an X reinforcement pattern. However, after cyclic loading, the reinforcement yarn tends to degrade the ES mat in particular. Moreover, increasing the number of stitches tends to fragilize the mats.
Assessment of urine sample quality by the simultaneous measurement of urinary γ-glutamyltransferase and lactate dehydrogenase enzyme activities: possible application to unravel cheating in drugs of abuse testing
Authors: Friess Anna , Friess Ulrich , Shipkova Maria , Wieland Eberhard 
Published: May 2022

Abstract

Objectives
Evaluation of the simultaneous measurement of urinary γ-glutamyltransferase (γGT) and lactate dehydrogenase (LDH) to discriminate fresh from previously frozen specimens in urine drug monitoring.

Methods
Two widely available photometric tests (Siemens Healthineers Atellica) were used to determine the range of urinary γGT and LDH excretion and to study the decay in urinary enzyme activity under various storage conditions (room temperature, 4–8 °C, −18 °C, −80 °C). From these data, cut-off values were established and evaluated in split (fresh/frozen) specimens.

Results
Both assays allow robust, reliable, and simultaneous determination of urinary γGT and LDH. In healthy subjects, the 95% reference intervals for enzyme activity in native urine were γGT: 24.4–100.4 U/g Crea (creatinine) and LDH: 2.5–45.8 U/g Crea. Frozen storage for at least 7 days at −18 °C resulted in a loss of activity to less than 50% in both enzymes. Cut-offs for frozen samples were γGT≤33.2 U/g Crea and LDH≤ 8.4 U/g Crea. When applied to 100 sample pairs (fresh/frozen), 86.5% (173/200) of the measurements were conclusive and the combination of concordant enzyme measurements (low γGT/low LDH or high γGT/high LDH) was able to predict the mode of storage with a sensitivity of 96.3% and a specificity of 96.7%.

Conclusions
The additional measurements of urinary γGT and LDH can be used to detect previously frozen urine specimens. A simple protocol is proposed to provide additional information on sample quality when deceit is suspected. The procedure can be easily integrated into the standard workflow of urinary drug monitoring.
Qualitative Properties of Space-Dependent SIR Models with Constant Delay and Their Numerical Solutions
Authors: Takács Bálint M. , Faragó István , Horváth Róbert , Repovš Dušan 
Published: May 2022

Abstract
In this article, a space-dependent epidemic model equipped with a constant latency period is examined.
We construct a delay partial integro-differential equation and show that its solution possesses some biologically reasonable features.
We propose some numerical schemes and show that, by choosing the time step to be sufficiently small, the schemes preserve the qualitative properties of the original continuous model.
Finally, some numerical experiments are presented that confirm the aforementioned theoretical results.
Anisotropic Adaptive Finite Elements for an Elliptic Problem with Strongly Varying Diffusion Coefficient
Authors: Dubuis Samuel , Passelli Paride , Picasso Marco 
Published: May 2022

Abstract
The elliptic problem

-

div
⁡

(

μ
⁢

∇
⁡
u

)

=
f

-\operatorname{div}(\mu\nabla u)=f

is considered, where

μ
>
0

\mu>0

is smooth but strongly varying.
Anisotropic a posteriori error estimates are derived, the effectivity index being bounded above and below by two constants independent of the data 𝑓, 𝜇, the mesh size and aspect ratio, up to higher order terms.
Numerical experiments on non-adapted and adapted anisotropic meshes confirm these predictions.
Sign language identification and recognition: A comparative study
Authors: Sultan Ahmed , Makram Walied , Kayed Mohammed , Ali Abdelmaged Amin 
Published: May 2022

AbstractSign Language (SL) is the main language for handicapped and disabled people. Each country has its own SL that is different from other countries. Each sign in a language is represented with variant hand gestures, body movements, and facial expressions. Researchers in this field aim to remove any obstacles that prevent the communication with deaf people by replacing all device-based techniques with vision-based techniques using Artificial Intelligence (AI) and Deep Learning. This article highlights two main SL processing tasks: Sign Language Recognition (SLR) and Sign Language Identification (SLID). The latter task is targeted to identify the signer language, while the former is aimed to translate the signer conversation into tokens (signs). The article addresses the most common datasets used in the literature for the two tasks (static and dynamic datasets that are collected from different corpora) with different contents including numerical, alphabets, words, and sentences from different SLs. It also discusses the devices required to build these datasets, as well as the different preprocessing steps applied before training and testing. The article compares the different approaches and techniques applied on these datasets. It discusses both the vision-based and the data-gloves-based approaches, aiming to analyze and focus on main methods used in vision-based approaches such as hybrid methods and deep learning algorithms. Furthermore, the article presents a graphical depiction and a tabular representation of various SLR approaches.
The Social Foundations of Public Support for Political Compromise
Authors: Wolak Jennifer 
Published: May 2022

AbstractIn a time of deeply divided political parties, how do Americans think political decisions should be made? In surveys, most Americans say that politicians should be willing to find compromises with the other side. I propose that people endorse compromise because they see it as both a political and a social norm. Conflict is inevitable in politics and in life. People must find ways to navigate the disagreements they have with family, friends, and coworkers – and they expect the same from members of Congress. Using survey evidence from the 2020 American National Social Network Survey, I show that people’s experiences navigating political differences in their social lives sharpens their support for compromise. When people have stronger social ties and more conversations with those who do not share their views, they are more likely to endorse compromise in politics.
Study on the technical parameters model of the functional components of cone crushers
Authors: Yu Luo-jian , Tong Xin 
Published: May 2022

Abstract
A cone crusher is a machine that crushes rock materials with high efficiency and low power consumption; it is one of the typical road construction equipment. To improve the production efficiency, mechanical performance, and crushing performance of the cone crusher, thus increasing profit, this study used Discrete element method (DEM) particle analysis software to optimize the structure of the moving cone, studied the crushing effect of the crusher, and carried out kinetics analyses. Based on DEM, the structure of the cone crusher cavity was analyzed and optimized. A Y51 cone crusher was selected as a representative example to study its moving cone structure. By analyzing the factors that affect the performance and efficiency of the crusher, the precession angle, base angle, shape, and rotational speed of the moving cone were optimized. Using the Genetic Algorithm-Support Vector machine method (GA-SVW), the optimal combination of parameters was determined, and the key parts of the crusher were thus optimized.
Thermal analysis characterisation of solar-powered ship using Oldroyd hybrid nanofluids in parabolic trough solar collector: An optimal thermal application
Authors: Shahzad Faisal , Jamshed Wasim , Safdar Rabia , Hussain Syed M. , Nasir Nor Ain Azeany Mohd , Dhange Mallinath , Nisar Kottakkaran Sooppy , Eid Mohamed R. , Sohail Muhammad , Alsehli Mishal , Elfasakhany Ashraf 
Published: May 2022

Abstract
The mathematical modeling of hybrid nanofluid flow and heat transfer with entropy generation toward parabolic trough surface collector (PTSC) inside the solar-powered ship (SPS) is performed. The mathematical model used non-Newtonian Oldroyd-B model amidst a constant inclined magnetic field influence is being considered. The mathematical model is then reduced by adopting appropriate similarity transformation into a higher-order nonlinear differential equations system. The reduced model is computed using the well-known technique called the Keller Box scheme. Physical parameters effectiveness, for instance, thermal radiation, viscous dissipation, hybrid nanoparticles, and Joule heating, is displayed in graphs. The silver-ethylene glycol (Ag-EG) characteristic performance outperformed the silver-magnetite-ethylene glycol (Ag-Fe3O4/EG). The maximum efficiency of Ag-EG is about 26.3%, while the minimum is at least 5.6%.
Wear volume estimation for a journal bearing dataset
Authors: Bote-Garcia José-Luis , Gühmann Clemens 
Published: May 2022

AbstractTo develop a system for predicting the remaining useful lifetime of a journal bearing, it is necessary to monitor the progressive wear quantitatively. For this purpose, we create a dataset where the wear volume is tracked throughout several experiments. The roundness profile is used to determine the wear volume over the entire life of the journal bearing. Therefore, a procedure for tracking the wear volume is described. The uncertainty of the procedure is analyzed. It is shown that the procedure has good accuracy and that the uncertainty is induced by the manual setting of the measuring positions. It has been shown that acoustic emission can be used to classify different friction states and identify defects in journal bearings. In addition, it has been demonstrated in experimental setups that it can be used to estimate the wear volume of sliding lubricated metallic contacts. Several experiments were carried out under different operating conditions for the dataset’s creation. Finally, the root mean square value of the acquired acoustic emission signal is used for estimation. Linear regression, random forest regressor, multilayer perceptron, and recurrent neuronal network are applied. The wear volume can be estimated with a root mean square error of 0.32 mm3and a coefficient of determination of 93 %. Neural networks have the distinct advantage of being able to estimate wear at any point during an experiment.
The Contributions of Mu-Opioid Receptors on Glutamatergic and GABAergic Neurons to Analgesia Induced by Various Stress Intensities
Authors: Du Yinan , Yu Kexin , Yan Chuanting , Wei Chunling , Zheng Qiaohua , Qiao Yanning , Liu Yihui , Han Jing , Ren Wei , Liu Zhiqiang 
Published: May 2022

AbstractThe endogenous opioid system plays a crucial role in stress-induced analgesia. Mu-opioid receptors (MORs), one of the major opioid receptors, are expressed widely in subpopulations of cells throughout the CNS. However, the potential roles of MORs expressed in glutamatergic (MORGlut) and γ-aminobutyric acidergic (MORGABA) neurons in stress-induced analgesia remain unclear. By examining tail-flick latencies to noxious radiant heat of male mice, here we investigated the contributions of MORGABAand MORGlutto behavioral analgesia and activities of neurons projecting from periaqueductal gray (PAG) to rostral ventromedial medulla (RVM) induced by a range of time courses of forced swim exposure. The moderate but not transitory or prolonged swim exposure induced a MOR-dependent analgesia, although all of these three stresses enhanced β-endorphin release. Selective deletion of MORGABAbut not MORGlutclearly attenuated analgesia and blocked the enhancement of activities of PAG-RVM neurons induced by moderate swim exposure. Under transitory swim exposure, in contrast, selective deletion of MORGlutelicited an analgesia behavior via strengthening the activities of PAG-RVM neurons. These results indicate that MOR-dependent endogenous opioid signaling participates in nociceptive modulation in a wide range, not limited to moderate, of stress intensities. Endogenous activation of MORGABAexerts analgesia, whereas MORGlutproduces antianalgesia. More importantly, with an increase of stress intensities, the efficiencies of MORs on nociception shifts from balance between MORGlutand MORGABAto biasing toward MORGABA-mediated processes. Our results point to the cellular dynamic characteristics of MORs expressed in excitatory and inhibitory neurons in pain modulation under various stress intensities.