bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differences in spermatozoa acquisition rates between patients with non-obstructive azoospermia of different etiologies
Authors: Xiao-ting Zheng , Ling Ma , Sheng-hui Chen , Yao Wen-liang , zhang ming-liang , Zhou Yu-liang 
Published: May 2022

Abstract
Objective: This study aimed to investigate and compare the sperm acquisition rates achieved by microdissection testicular sperm extraction in patients with different causes of non-obstructive azoospermia. Methods: The medical records of 225 non-obstructive azoospermia patients who underwent microdissection testicular sperm extraction after January 2018 in the Reproductive Andrology Department of the Reproductive Hospital affiliated to Jiangxi University of Traditional Chinese Medicine were retrospectively analyzed. We investigated whether age, testicular volume, reproductive endocrine hormone levels, and etiological differences were correlated with sperm acquisition rates. Results: The patients were divided into two groups: those from whom sperm was successfully acquired and those from whom it was not. In the sperm acquisition group, there were 107 patients; in the non-acquisition group, there were 118 patients. There were no significant differences in age, testicular volume, endocrine hormone levels, body mass index, or inhibin B antigen levels between the two groups. A significant difference was found between the acquisition group (2.32±1.334) and the non-acquisition group (3.16±1.680) in levels of anti-Müllerian hormone (p<0.01). The patients were then classified based on the etiology of their non-obstructive azoospermia. Those patients whose condition was caused by a history of mumps, surgery for cryptorchidism, Klinefelter syndrome, and AZFc deletion had significantly higher sperm retrieval rates than patients with idiopathic non-obstructive azoospermia. Conclusion: Microdissection testicular sperm extraction is an established and effective treatment for infertility resulting from non-obstructive azoospermia. No correlation was found between testicular sperm extraction rates and age, obesity, testicular volume, endocrine hormone levels, or inhibin B levels. Anti-Müllerian hormone can be used to predict sperm retrieval rates but should be used alongside other indicators where possible. Sperm acquisition rates were found to be significantly correlated to the etiological origins of non-obstructive azoospermia. This can be used to predict the surgical sperm acquisition rates of non-obstructive azoospermia patients.
The Shift to Personal Learning Environment has been FruitfulPredicting Performance in Future Tasks Based on Personal Learning Environment Management during the Corona Epidemic
Authors: ibrahem usama mohamed , alharbi badr , Moussa Mahmoud , Alrashidi Muna , Radi Bahgat 
Published: May 2022

Abstract
The study aimed to study the performance expectation in future tasks based on personal learning management during the Corona epidemic. A random sample of 871 students from the University of Hail was selected. The study samples were from humanities, engineering, and medical colleges. The study was based on a cross-sectional study design. The study prepared a measure of future expectation of performance on the tasks. The scale is 28 items. Factor analysis was used to verify the validity of the scale, and the scale achieved acceptable indicators of good fit. The scale achieved acceptable stability using Cronbach's alpha coefficient for emotional factor 0.57, cognitive factor 0.94, and behavioral factor 0.90. The results revealed that there are differences in the future expectation on performance because of gender and type of college. The results revealed that there are positive correlations between future expectation of cognitive and emotional performance, as well as a positive relationship between emotional and behavioral performance. There was also a negative relationship between behavioral and cognitive performance.
Social inequality and barriers to healthcare-seeking with lung cancer symptoms – a population-based study
Authors: Sætre Lisa , Rasmussen Sanne , Balasubramaniam Kirubakaran , Søndergaard Jens , Jarbøl Dorte 
Published: May 2022

Abstract
Healthcare-seeking with lung cancer symptoms is a prerequisite for improving timely diagnosis of lung cancer. In this study we aimed to explore barriers to healthcare-seeking with lung cancer symptoms, and to analyse the impact of social inequality. The study is based on a nationwide survey with 69,060 individuals aged ≥40 years, randomly selected from the Danish population. Survey information on lung cancer symptoms, healthcare-seeking, and smoking status. Information about socioeconomics by linkage to Danish Registers. “Being too busy” and “Being worried about wasting the doctor’s time” were the most frequent barriers to healthcare-seeking with lung cancer symptoms. Individuals out of workforce and current smokers more often reported “Being worried about what the doctor might find” and “Being too embarrassed” about the symptoms. The social inequality in barriers to healthcare-seeking with lung cancer symptoms is noticeable, which emphasises the necessity of focus on vulnerable groups at risk of postponing relevant healthcare-seeking.
Effect of processing temperatures on decarbonisation of calcium carbonate in sodium hydroxide solutions at ambient conditions
Authors: Simoni Marco , Hanein Theodore , Woo Chun Long , Nyberg Magnus , Provis John L. , Kinoshita Hajime , Tyrer Mark 
Published: May 2022

Abstract
The CO2 released upon calcination of limestone (process CO2 and combustion CO2) accounts for the largest portion of the emissions from the cement manufacturing industry. Our previous works highlighted the possibility for a no-combustion decarbonisation of CaCO3 through reaction with NaOH solutions to produce Ca(OH)2 at ambient conditions, while sequestrating the process CO2 in a stable mineral Na2CO3∙H2O/Na2CO3. In this study, the effect of temperature was assessed within the range of 45–80°C, highlighting a higher impact at short residence times. The proportioning of the precipitated phases Na2CO3∙H2O /Na2CO3 was also assessed at varying conditions, and the data was supported with related simulation. Experiments performed on targeted CaCO3:NaOH:H2O compositions also allowed for the detection of the Arrhenius parameters characterising each ternary system. An increasing activation energy (Ea) was found to be correlated to lower NaOH concentrations initially reacting with CaCO3. The present work offers a further understanding of the effect of temperature on the process with the potential to minimise the GHG emissions from cement and lime industries, and correctly assess eventual industrial applicability.
DRD1 signaling enhances recovery after traumatic brain injury via an autophagy dependent pathway.
Authors: Lin Chao , Chang Hanxiao , Bao Zhongyuan , Luo Hui , Xu Lei , Wu Wei , Liu Ning , Ji Jing 
Published: May 2022

Abstract
Although the neurotransmitter dopamine (DA) plays a crucial pathophysiologic role after traumatic brain injury (TBI), its function and specific underlying mechanisms of action remain unclear. In this study, DA inhibits neural death induced by TBI or stretch injury, which is mediated via the dopamine receptor D1 (DRD1). Our results showed that DRD1 signaling promotes receptor interacting protein kinase 1 (RIPK1) ubiquitination via the E3 ubiquitin ligase Chip and degradation through autophagy. Importantly, in vivo data revealed that DRD1 signaling prevented neuronal death, suppressed neuroinflammation, and restored many TBI-related functional sequelae through an autophagy-dependent mechanism. These data reveal a novel mechanism involving dopamine, and suggest that DRD1 activation positively regulates Chip-mediated ubiquitylation of RIPK1—leading to its autophagic degradation.
A Bayesian network optimization method for ranked search under constraints
Authors: Jinhua WANG , XUN Ming rui , Jie ，CAO 
Published: May 2022

Abstract
Bayesian networks can deal with uncertainty and polymorphism and are widely used in the field of fault diagnosis. However, the directed acyclic graph (DAG) space is large, and it is an NP-hard problem to get the optimal BN structure from the data. The current research combines constraint-based and search-based methods to search for the optimal BN structure in the DAG to solve this problem. However, when the constraint space is constant and imprecise, the optimal solution is most likely to be lost, resulting in low model accuracy. In addition, the search space expands with the increase of the number of nodes, which leads to the structure quickly falling into local optimum and low learning efficiency. Therefore, this paper proposes a Bayesian Network Modeling for Ranking Search under Constrained Conditions (BNMRSCC) method to find a BN structure that fits the data set in the constrained search space. Firstly, in the constraint phase, the MIC algorithm and CI test are used as double constraints to limit the search space and two estimatorsB anda are introduced in the original MIC algorithm to change the search space during the operation to reduce the computation time and improve the learning efficiency. Secondly, in the search phase, the XGboost algorithm is used to calculate the feature importance scores and rank them, and the search space is further determined based on the ranking under the double constraint. Finally, the feature ranking is used as the input of the K2 algorithm to improve the accuracy of network inference. The experimental results show that the model built by this algorithm is better and more effective for learning BN structures.
Convolutional neural network based portable computer vision system for freshness assessment of crayfish (Prokaryophyllus clarkii)
Authors: Wang Chao , Liu Yan , Xia Zhenzhen , Wang Qiao , Duan Shuo , Gong Zhiyong , Chen Jiwang 
Published: May 2022

Abstract
Developing novel techniques for freshness assessment are of the utmost importance in yield and trade of aquatic products. The crayfish (Prokaryophyllus clarkii) is one of the most popular freshwater products in China and its food safety should be seriously concerned. In this study, a convolutional neural network (CNN) based portable computer vision system for freshness assessment of crayfish method was proposed. A portable microscope was utilized to collect the microscopic images of crayfish with different freshness levels. The convolutional neural network was constructed and then optimized to extract features from the microscopic images. For the pictures from the portable microscope, the prediction accuracies of freshness could be 86.5% and 83.3% when the optimized networks were applied. The results indicate that the convolutional neural network based portable computer vision system may provide an alternative way for the freshness assessment in crayfish industrial chain.
Study on local bifurcation of nonlinear energy sink with inerter and grounded stiffness
Authors: Sui Peng , Shen Yong-Jun , Wang Xiaona 
Published: May 2022

Abstract
Novel and efficient vibration control units such as inerter and grounded stiffness have contributed significantly to structural vibration reduction. However, as the performance of vibration suppression systems gradually improves, their structures become more complex. And the coupling effects among complex structures, as well as the effects on the system dynamics, are hazy. This aims to investigate the influence of combined structure of inerter and grounded stiffness on the bifurcation behaviors of nonlinear energy sink. The damping of the primary system, a parameter that has been neglected in the majority of studies, is also included in the model. The closed-form solutions of the system steady-state response are derived by the complexification-averaging method and verified numerically. Then, the control equations of stability judgment, saddle-node bifurcation, and Hopf bifurcation are calculated. Sensitivity analysis is performed for each parameter and is visualized in the form of two-dimensional and three-dimensional bifurcation diagrams. It is found that two kinds of bifurcation boundaries on the ( ξ 2 , f ) plane move slightly up and Hopf bifurcation boundaries become complicated both owing to the introduction of the damping in the primary system. The bifurcation zones on the ( ξ 2 , f ) and ( K 2 , f ) planes enlarge with the increase of inerter coefficient. Increasing grounded stiffness has the opposite influence on areas of the bifurcation boundary about ( ξ 2 , f ) and ( μ , f ), except for the special case that the area of saddle-node bifurcation on the ( μ , f ) plane increases accordingly. The amplitude of external force leading to bifurcations will increase when the inerter and grounded stiffness get greater jointly.
Hydroclimatic impacts of ‘8.2-ka event’ in western Indo-Pacific Warm Pool
Authors: Dixit Yama , Chua Stephen , Yan Yu Ting , Switzer Adam 
Published: May 2022

Abstract

The most prominent abrupt climate event during the Holocene, the ‘8.2 ka event’, was characterized by severe cooling at high northern latitudes causing diverse hydroclimate shifts globally. To date, a precise understanding of the hydroclimate response of the Indo-Pacific Warm Pool (IPWP) region to abrupt climate changes in the North Atlantic around 8.2 ka remains elusive. Here we present a high-resolution stable carbon isotope record on foraminifera species Asterorotalia pulchella and sediment characteristics of a marine sediment core from the Kallang River Basin, Singapore. Foraminifer stable isotope data in concert with sedimentological proxies provide coherent evidence of weakened rainfall for ~ 180 years in the western tropical Indo-Pacific region from ~ 8.14 ka to 7.96 ka BP. A robust age model suggests that the timing of the onset of reduced convective activity in the western IPWP region lags the cooling in the North Atlantic and the synchronous droughts in the Asian and Indian monsoon regions, by ~ 100years possibly implying a north-south signal propagation via oceanic route that operates on centennial scales. The termination of the ‘8.2 ka event’, however may have occurred near synchronously between high and low tropical regions at ~ 7.96ka BP possibly linked via both atmospheric and oceanic processes.
Chemical composition, toxicity and physiological effects of thyme oil and its two components on mulberry pyralid moth
Authors: Goharrostami Maryam , Sendi Jalal Jalali , Hosseini Reza , Mahmoodi Nosrat O Allah 
Published: May 2022

Abstract
Thymus vulgaris is a plant with known insecticidal properties. In order to explore its use in the control of the mulberry snout moth, the essential oil this plant and two of its major components, thymol and carvacrol, were evaluated in laboratory bioassays. GC-MS analysis of the oil depicted thymol (26.9%) and carvacrol (5.7%) as the major constituents. The estimated LD50 values for thyme essential oil, thymol and carvacrol were 2.82, 32.18 and 56.54 µg/larva, respectively. However, the thyme essential oil was more toxic than its two main compounds.The activity of certain detoxifying enzymes such as α- and β-esterase, glutathione S-transferase and cytochrome P450 were significantly inhibited in thymol-treated larvae compared to the control group. Similarly, the activity of alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase and alkaline phosphatases enzymes in thymol-treated larvae decreased while the activity of acid phosphatases increased. Our results suggest that thyme essential oil and its components have potential for the control of G. pyloalis larvae in mulberry orchards, where no synthetic chemicals are allowed.
A novel guide for minimally invasive genioplasty
Authors: Macedo Diogo de Vasconcelos , Monnazzi Marcelo Silva , de Almeida Matheus Spinella , Claus Jonathas Daniel Paggi 
Published: May 2022

Abstract
Mentoplasty or genioplasty is a simple procedure to enhance facial aesthetics. While usually considered simple, it might present certain difficulties during execution, especially when a minimally invasive approach is preferred. Drilling and cutting guides are a valuable tool to overcome such challenges but usually require larger incision and dissection to allow adequate positioning and bone rigid fixation. In this article, we describe a novel guide design that permits adequate bone repositioning while preserving minimally invasive protocols.
A Self-Organizing Topological Multilayer Perceptron for Improving the Prediction of Extreme Values of the PM2.5
Authors: López-Gonzales Javier Linkolk , Lamus Ana María Gómez , Torres Romina , Salas Rodrigo 
Published: May 2022

Abstract
The prediction of air pollutant levels plays an essential role in regulatory plans focused on controlling and mitigating air pollutants, such as particulate matter (PM). Even when elevated pollution episodes may be rare, they recirculate within an area where more people may present significant adverse health consequences. Thus, even when they are difficult to predict, pollution peaks prediction of air pollution particulate matter (PM2.5) is a crucial problem to address. Several machine learning (ML) approaches have been used to predict a set of air pollutants using different combinations of predictor parameters. Unfortunately, they are still not enough to generate accurate predictions of extreme values. This paper proposes a new hybrid method that combines the unsupervised learning Self-Organizing Maps with the supervised multilayer perceptron. The proposed method is applied for the prediction of extreme values of PM2.5, using five-year pollution data obtained from nine weather stations located in the metropolitan area of Santiago, Chile. Simulation results show that the hybrid method improves the performance metrics when predicting extreme values of PM2.5.
Harnessing plasma absorption in silicon MOS modulators
Authors: Zhang Weiwei , Ebert Martin , Li Ke , Chen Bigeng , Yan Xingzhao , Du Han , Banakar Mehdi , Tran Dehn , Littlejohns Callum , Scofield Adam , Yu Guomin , Shafiiha Roshanak , Zilkie Aaron , Reed Graham , Thomson David 
Published: May 2022

Abstract
High bandwidth, low power and compact silicon electro-optical modulators are essential for future energy efficient and densely integrated optical data communication circuits. The all-silicon plasma dispersion effect ring resonator modulator is an attractive prospect. However its performance is currently limited by the trade-off between modulation depth and switching speed dictated by its quality factor. Here we introduce a mechanism to leap beyond this limitation by harnessing the significant plasma absorption induced in a silicon MOS waveguide to enhance the extinction ratio of a low quality factor, high-speed ring modulator. Fabricated devices have demonstrated 20dB of electro-absorption modulation at the resonance with a 3.5V bias change and a total modulation depth of 27dB with the concurrent carrier refraction induced wavelength shift. Modulation enhancement has been observed from kHz to GHz operation with data modulation up to 100Gbit/s on-off keying demonstrated, paving the evolution of optical interconnects to 100Gbaud and beyond per wavelength.
Geometric Algebra based 2D-DOA Estimation for Non-circular Signals With an Electromagnetic Vector Array
Authors: Wang Xiangyang , Lv Xiaolu , Wang Rui 
Published: May 2022

Abstract
This paper presents two novel methods based on geometric algebra (GA) to estimate two-dimensional (2D) direction-of-arrival (DOA) of non-circular (NC) signals for uniform rectangular array (URA). Traditional methods treat the received NC signals as a long vector which will inevitably lose orthogonality inside each electromagnetic vector sensor (EMVS) and thus miss some information of second-order statistical properties. Furthermore, the computational complexity will also increase. By contrast, the GA-based estimating signal parameter via rotational invariance techniques (ESPRIT) and propagation method (PM) algorithms are proposed to estimation DOA of NC signals. Taking advantage of GA, the relationship among multidimensional signals can be maintained. First, the six components of the EMVS are represented as a multivector in GA space. Then, we construct the GA-based extended covariance matrix to utilize the signal information more completely. The DOA parameters can be estimated through the ESPRIT and PM principle. The proposed GA-based estimation of signal parameter via rotational invariance techniques for NC signals processing (GANC-ESPRIT) can estimate DOA with high estimation accuracy. The proposed GA-based propagation method for NC signals estimation (GANC-PM) uses linear transformation to calculate angle parameters. Our model has much lower memory requirements and less computational burden compared with long vector models. Simulation results demonstrate the robustness and superiority of the proposed GANC-ESPRIT algorithm in terms of angular resolution. Complexity analysis shows that the proposed GANC-PM algorithm performances better with less computations.
‘I can’t make perfect choices all the time’: Perspectives on Tobacco Harm Reduction among SGM Young Adults
Authors: Antin Tamar M.J. , Sanders Emile , Lipperman-Kreda Sharon , Peterkin Elaina 
Published: May 2022

Abstract
Background: Cigarette smoking is among the most harmful ways to consume nicotine and, troublingly, tends to be concentrated among socially marginalized groups of people, including those who identify their sexualities and genders in ways that classify them as sexual and gender minorities (SGM). Though some approaches to tobacco control in the United States may be considered harm reduction strategies (e.g. smoke-free environments), often abstinence is an explicitly-stated goal and discussions of reducing harm in the absence of cessation are controversial, particularly when it comes to young people. Despite the controversy of tobacco harm reduction (THR), emerging research suggests that interest in and reliance on THR strategies may be gaining momentum as a “community-led” rather than ‘public health-led’ health practice. To date, little is known about how SGM young adults negotiate their use of tobacco products, particularly in terms of minimizing the harms associated with smoking. Methods: We conducted 100 in-depth interviews with SGM young adults ages 18-25 living in the San Francisco Bay Area, to better understand participant perceptions and everyday practices related to THR. Results: A thematic analysis of interview narratives revealed the ways in which participants employed various individual-level, ad-hoc THR strategies while negotiating their wellbeing within the context of broader socio-structural harms. Analysis also underscored beliefs about the importance of pragmatic, nonjudgmental approaches to drug use that are guided by a person-centered ethos of respect and compassion. Conclusions: Findings from this study represent a significant departure from the mainstream discourse surrounding tobacco harm reduction in the United States. Analysis of participants’ narratives highlights the ways in which understanding the practice of THR among SGM young adults who use nicotine and tobacco can be instrumental in shaping alternative approaches to tobacco control policy and prevention efforts, ultimately helping to reduce inequities in tobacco-related illnesses.