bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of variables in relational thinking: an interview study with kindergarten and primary school children
Authors: Lenz Denise 
Published: August 2022

AbstractRelational thinking and dealing with variables are two essential aspects of algebraic thinking. Relational thinking means viewing mathematical expressions and equations as a whole rather than as individual computing processes. It is characterized by using relationships between mathematical objects, and refers to the relations of equality and inequality. In this study, to examine the relational thinking of kindergarten and primary school children, this perspective was applied using non-symbolic representations in the form of boxes and marbles. Using multiple variables is a very powerful but also difficult tool of algebra. The study had the aim of examining how kindergarten children and primary school children establish relationships between several variables which are represented with real materials. The interview study was conducted with children aged 5–10 years. Marbles and different colored boxes represented equations with unknowns and quantities depending on each other. Initially, two approaches could be differentiated, namely, number-oriented and structure-oriented approaches. It could be shown that certain conceptualizations of variables were related to children’s ability to show relational thinking. Kindergarteners are stimulated to think relationally by unknown quantities which can be determined. This process was observed in primary school children dealing with quantities that depended on each other. In addition, the conceptualization of the variables represented as boxes was examined. The concepts of general number and variable as changing quantity were categorized. Further conceptualizations resulted from the interview data, namely, categories of the undeterminable, the specific number, and the quasi-general.
The Supplement of Magnesium Element to Inhibit Colorectal Tumor Cells
Authors: Li Heng , Feng Xiaonan , Li Hai , Ma Shuo , Song Wei , Yang Bao , Jiang Tao , Yang Chun 
Published: August 2022

Abstract
Magnesium ions are essential elements to the human body, with a daily intake of about 350 mg for an adult. Recently, a meta-analysis reported that magnesium ion intake is related to a reduced risk of colorectal tumors. In addition, implantation of biodegradable magnesium pins after colorectal tumor resection could potentially inhibit the residual tumor cells. These impressive results implied that magnesium ions possess inhibitory properties against colorectal carcinoma. However, this hypothesis has yet to be confirmed by experimental results. In this work, different concentrations of magnesium ions were modulated to investigate their inhibitory effects on cell viability through cell cycle arrest, subsequently inducing apoptosis by activating the caspase-3 pathway. The animal experiments revealed that magnesium injection restricted tumor growth after 3 weeks of treatment compared to the control group. According to the immunohistochemistry and transmission electron microscopy results, the remarkable effect may be attributed to promoting the apoptotic rate of tumor cells. The evidence highlights the potential for the clinical use of magnesium implants to inhibit the growth of residual cells after colorectal tumor surgery.
Prognosis factors of predicting survival in spontaneously ruptured hepatocellular carcinoma
Authors: Wang Peng , Moses Abraham S , Li Chao , Chen Song , Qi Xun , Xu Ke , Shao Hai-bo , Han Xiang-jun 
Published: August 2022

Abstract
Aim
To investigate predictors affecting survival in patients with spontaneously ruptured hepatocellular carcinoma (srHCC).

Methods
One-hundred-and-twenty-seven patients experiencing srHCC between January 2010 and December 2020 were enrolled. The clinical features, treatments, and outcomes were reviewed. Statistics included univariate analysis, Kaplan–Meier analysis, multivariate analysis using Cox proportional hazards model and logistic regression model, and receiver operating characteristic (ROC) curve analysis.

Results
Of the 127 srHCC patients, 24, 42, and 61 patients received conservative treatment, surgical treatment, and transarterial chemoembolization/embolization (TACE/TAE) treatment at HCC rupture, respectively. The largest tumor size [hazard ratio (HR) 1.127; p < 0.001], Barcelona-Clinic Liver Cancer (BCLC) stage (HR 2.184, p = 0.023), international normalized ratio (INR; HR 3.895; p = 0.012), total bilirubin level (TBil; HR 1.014; p = 0.014), TACE after rupture (compared with conservative treatment) (HR 0.549; p = 0.029), TACE/TAE and surgery at rupture, and albumin level (HR 0.949; p = 0.017) were independent predictors affecting overall survival. A survival predictive model for HCC rupture (SPHR) using these predictors was created. ROC analysis showed that the area under the curve (AUC) of the SPHR model for 30 day survival was 0.925, and the AUCs of the model for end-stage liver disease (MELD) score and Child–Pugh score for 30 day survival were 0.767 and 0.757, respectively.

Conclusion
The largest tumor size, advanced BCLC stage, higher INR and TBil, lower albumin, and conservative treatment were negative independent predictors for overall survival. The SPHR model may be more suitable than the MELD score and Child–Pugh score for predicting 30 day survival in srHCC.
Targeted timing of hairy vetch cover crop termination with roller crimper can eliminate glyphosate requirements in no-till sunflower
Authors: Antichi Daniele , Carlesi Stefano , Mazzoncini Marco , Bàrberi Paolo 
Published: August 2022

AbstractNo-till cropping systems with cover crops can improve soil health, but often rely on glyphosate, which is a contentious herbicide. In this study, we investigated whether a system based on the direct sowing of sunflower (Helianthus annuus) in the dead mulch of a roller-crimped hairy vetch (Vicia villosa) could be competitive with a system where glyphosate is also sprayed to terminate the cover crop and to control weeds. We hypothesized that optimum timing of roller-crimping would be key to eliminate glyphosate requirements while maintaining sunflower performance. In a 3-year on-farm experiment, we compared three vetch termination stages (early: pre-flowering; Intermediate: beginning of flowering; late: 70% flowering) and three glyphosate rates (Nil, half and full, i.e. 1440 g of active ingredient per hectare). Vetch biomass increased progressively from early to late termination stages, and ranged between 414 and 658 g m−2. Higher vetch biomass was correlated with lower weed biomass. Treatments had inconsistent effects on weed diversity and composition, largely determined by the interactions between treatments and seasonal (different years) or local factors (different fields). Glyphosate-based treatments seemed to select for aggressive weed species, but no clear species filtering effect based on ecological or functional traits was detected. Shannon H’ was positively correlated with sunflower grain yield below a weed dry biomass threshold of 150 g m−2. Crop yield with early termination stage was a failure without glyphosate application. However, crop yield with late vetch termination was acceptable, being at par or 15% higher (mean of first and second years) in no-glyphosate compared with glyphosate-based treatments. Crop gross margins showed the same trend (+33% for no-glyphosate compared with glyphosate-based treatments). This study, for the first time, shows that targeted timing of roller-crimped hairy vetch in no-till sunflower can result in equal agronomic and economic performances as addition of glyphosate.
The Causes and Effects of Mercury and Methylmercury Contamination in the Marine Environment: A Review
Authors: Al-Sulaiti Maetha M. , Soubra Lama , Al-Ghouti Mohammad A. 
Published: August 2022

Abstract
Purpose of Review
The concern of mercury pollution and the impact that it poses on the marine environment were studied heavily since the case of the poison from Minamata bay in the 1960s. The present study provides an insight into the cycle of mercury and methylmercury in the marine environment and the bioindicators that reflect the exposure levels. The paper also used the driving forces, pressures, states, impacts, and responses (DPSIR) analysis to evaluate the global mercury and methylmercury contamination problem.

Recent Findings
The high global budgets of atmospheric total mercury influence the ocean surface water. Therefore, the aquatic environment contamination level is in turn affected by the surrounding emission sources such as industrial and petroleum activities in addition to the transport and fate of mercury across the environmental compartments. This will increase the mercury levels in fish species and will cause an adverse risk to human health through biomagnification.

Summary
This review presents a thorough description of mercury sources and emissions and their fate and transport across the different environmental compartments, despite the fact that serious mitigation measures were taken and guidelines were applied. The risk from fish consumption is still a serious concern as a result of the current mercury emissions and stability and persistent characteristics.
Exploiting lexical patterns for knowledge graph construction from unstructured text in Spanish
Authors: Rios-Alvarado Ana B. , Martinez-Rodriguez Jose L. , Garcia-Perez Andrea G. , Guerrero-Melendez Tania Y. , Lopez-Arevalo Ivan , Gonzalez-Compean Jose Luis 
Published: August 2022

AbstractKnowledge graphs (KGs) are useful data structures for the integration, retrieval, dissemination, and inference of information in various information domains. One of the main challenges in building KGs is the extraction of named entities (nodes) and their relations (edges), particularly when processing unstructured text as it has no semantic descriptions. Generating KGs from texts written in Spanish represents a research challenge as the existing structures, models, and strategies designed for other languages are not compatible in this scenario. This paper proposes a method to design and construct KGs from unstructured text in Spanish. We defined lexical patterns to extract named entities and (non) taxonomic, equivalence, and composition relations. Next, named entities are linked and enriched with DBpedia resources through a strategy based on SPARQL queries. Finally, OWL properties are defined from the predicate relations for creating resource description framework (RDF) triples. We evaluated the performance of the proposed method to determine the degree of elements extracted from the input text and to assess their quality through standard information retrieval measures. The evaluation revealed the feasibility of the proposed method to extract RDF triples from datasets in general and computer science domains. Competitive results were observed by comparing our method regarding an existing approach from the literature.
Custom CornerNet: a drone-based improved deep learning technique for large-scale multiclass pest localization and classification
Authors: Albattah Waleed , Masood Momina , Javed Ali , Nawaz Marriam , Albahli Saleh 
Published: August 2022

AbstractInsect pests are among the most critical factors affecting crops and result in a severe reduction in food yield. At the same time, early and accurate identification of insect pests can assist farmers in taking timely preventative steps to reduce financial losses and improve food quality. However, the manual inspection process is a daunting and time-consuming task due to visual similarity between various insect species. Moreover, sometimes it is difficult to find an experienced professional for the consultation. To deal with the problems of manual inspection, we have presented an automated framework for the identification and categorization of insect pests using deep learning. We proposed a lightweight drone-based approach, namely a custom CornerNet approach with DenseNet-100 as a base network. The introduced framework comprises three phases. The region of interest is initially acquired by developing sample annotations later used for model training. A custom CornerNet is proposed in the next phase by employing the DenseNet-100 for deep keypoints computation. The one-stage detector CornerNet identifies and categorizes several insect pests in the final step. The DenseNet network improves the capacity of feature representation by connecting the feature maps from all of its preceding layers and assists the CornerNet model in detecting insect pests as paired vital points. We assessed the performance of the proposed model on the standard IP102 benchmark dataset for pest recognition which is challenging in terms of pest size, color, orientation, category, chrominance, and lighting variations. Both qualitative and quantitative experimental results showed the effectiveness of our approach for identifying target insects in the field with improved accuracy and recall rates.
Semi-enclosed experimental system for coal spontaneous combustion for determining regional distribution of high-temperature zone of coal fire
Authors: Zhao Jingyu , Ming Hanqi , Guo Tao , Zhang Yuxuan , Deng Jun , Song Jiajia , Zeng Qiang , Shu Chi-Min 
Published: August 2022

AbstractTemperature variation and gas generation at different depths and positions in the coal combustion process were studied to determine the propagation and evolution of high temperature regions in the process of coal spontaneous combustion. This study selected coal samples from Mengcun, Shaanxi Province, People’s Republic of China, and developed a semi-enclosed experimental system (furnace) for simulating coal combustion. The thermal mass loss of coal samples under various heating rates (5, 10, and 15 °C/min) was analyzed through thermogravimetric analysis, and the dynamic characteristics of the coal samples were analyzed; the reliability of the semi-enclosed experimental system was verified through the equal proportional method of fuzzy response. The results reveal that the high-temperature zone is distributed nonlinearly from the middle to the front end of the furnace, and the temperatures of points in this zone decreased gradually as the layer depth increased. The apparent activation energy of the coal samples during combustion first increased and then decreased as the conversion degree increased. Furthermore, the proportion of mass loss and the mass loss rate in the coal samples observed in the thermogravimetric experiment is consistent with that observed in the first and second stages of the experiment conducted using the semi-enclosed system. The research findings can provide a theoretical basis for the prevention and control of high-temperature zones in coal combustion.
Performance assessment of CORDEX regional climate models in wind speed simulations over Zambia
Authors: Libanda Brigadier 
Published: August 2022

AbstractThere is no single solution to cutting emissions, however, renewable energy projects that are backed by rigorous ex-ante assessments play an important role in these efforts. An inspection of literature reveals critical knowledge gaps in the understanding of future wind speed variability across Zambia, thus leading to major uncertainties in the understanding of renewable wind energy potential over the country. Several model performance metrics, both statistical and graphical were used in this study to examine the performance of CORDEX Africa Regional Climate Models (RCMs) in simulating wind speed across Zambia. Results indicate that wind speed is increasing at the rate of 0.006 m s− 1 per year. RCA4-GFDL-ESM2M, RCA4-HadGEM2-ES, RCA4-IPSL-CM5A-MR, and RCA4-CSIRO-MK3.6.0 were found to correctly simulate wind speed increase with varying magnitudes on the Sen’s estimator of slope. All the models sufficiently reproduce the annual cycle of wind speed with a steady increase being observed from April reaching its peak around August/September and beginning to drop in October. Apart from RegCM4-MPI-ESM and RegCM4-HadGEM2, the performance of RCMs in simulating spatial wind speed patterns is generally good although they overestimate it by ~ 1 m s− 1 in the western and southern provinces of the country. Model performance metrics indicate that with a correlation coefficient of 0.5, a root mean square error of 0.4 m s− 1, an RSR value of 7.7 and a bias of 19.9%, RCA4-GFDL-ESM2M outperforms all other models followed by RCA4-HadGEM2, and RCA4-CM5A-MR respectively. These results, therefore, suggest that studies that use an ensemble of RCA4-GFDL-ESM2M, RCA4-HadGEM2, and RCA4-CM5A-MR would yield useful results for informing future renewable wind energy potential in Zambia.
Additive manufacturing by digital light processing: a review
Authors: Chaudhary Rajat , Fabbri Paride , Leoni Enrico , Mazzanti Francesca , Akbari Raziyeh , Antonini Carlo 
Published: August 2022

AbstractAdditive manufacturing is a layer-by-layer strategy enabling the advanced design and fabrication of complex 3D objects and structures, overcoming geometry limitations and reducing waste production compared to conventional technologies. Among various additive manufacturing technologies, digital light processing (DLP), is an additive manufacturing technology used to print photopolymer parts, using a projected light source to cure an entire layer at once. Initially developed for pure resins, recent advances have demonstrated the potential of DLP in the polymerization of ceramic and metal-loaded suspensions, enabling the fabrication of ceramic and metal components after proper debinding and sintering. Such flexibility increases the potential of DLP for different applications, ranging from dental implants and bone scaffolds to smart biomaterials for soft robotics, smart wearables, and microfluidic devices. The review provides an overview of DLP technology and its recent advances; specifically, the review covers the photopolymer properties, the ceramic and metallic feedstock preparation, and the light-matter interaction mechanism underpinning the printing and post-processing steps. Finally, a description of the current application is provided and complemented with future perspectives.
Collaboration effectiveness-based complex operations allocation strategy towards to human–robot interaction
Authors: Zhang Fuqiang , Zhang Yanrui , Xu Shilin 
Published: August 2022

AbstractUnder the background of the fourth industrial revolution driven by the new generation information technology and artificial intelligence, human–robot collaboration has become an important part of smart manufacturing. The new “human–robot–environment” relationship conducts industrial robots to collaborate with workers to adapt to environmental changes harmoniously. How to determine a reasonable human–robot interaction operations allocation strategy is the primary problem, by comprehensively considering the workers’ flexibility and industrial robots’ automation. In this paper, a human–robot collaborative operation framework based on CNC (Computer Number Control) machine tool was proposed, which divided into three stages: pre-machining, machining and post-machining. Then, an action-based granularity decomposition method was used to construct the human–robot interaction hierarchical model. Further, a collaboration effectiveness-based operations allocation function was established through normalizing the time, cost, efficiency, accuracy and complexity of human–robot interaction. Finally, a simulated annealing algorithm was adopted to solve preferable collaboration scheme; a case was used to verify the feasibility and effectiveness of the proposed method. It is expected that this study can provide useful guidance for human–robot interaction operations allocation on CNC machine tools.
The impact of ESG on financial performance: a revisit with a regression discontinuity approach
Authors: Xu Ziwei , Hou Wenxuan , Main Brian G. M. , Ding Rong 
Published: August 2022

AbstractThis study revisits the question of “whether firms are doing well by doing good?”. We examine shareholders-sponsored corporate socially responsible (CSR) proposals related to Environmental, Social, and Governance (ESG) that are voted to pass or fail by a small margin. The adoption of those “close call” proposals is regarded as equivalent to a random assignment of CSR policies and, therefore, provides a quasi-experimental setting to capture the causal influence of CSR on firm performance. We apply the regression discontinuity design (RDD) and find that CSR proposals’ passage leads to a significant positive abnormal return on the voting day. The results are robust with both parametric and nonparametric approaches of RDD and different polynomial orders. However, we fail to identify a significant change in financial performance in the long-term. One possible reason is that passing a CSR proposal could be symbolic, rather than substantial.
TranZap: A Transgender Resource for Identifying Gender-Affirming Providers
Authors: Chiang Taylor , Bachmann Gloria A. 
Published: August 2022

Abstract

Introduction
Many transgender individuals seeking healthcare have had at least one negative experience related to being transgender. As a result, transgender patients may forego seeking healthcare treatment atall, leading to adverse long-term health outcomes. With barriers to care and oftentimes suboptimal care provided to transgender individuals, TranZap, in collaboration with the PROUD Gender Center of NJ, was commenced.

Objectives
To provide a review on the current transgender resources to finding healthcare, and the impetus behind creating a transgender health app to streamline this process. The vision of this app, TranZap, is to empower transgender individuals who are seeking healthcare such that they are better educated and knowledgeable regarding available healthcare providers.

Methods
With no data available from usual sources, such as Google Scholar, social media, as well as input from the transgender community through social media and word of mouth was utilized to identify the current resources for transgender patients seeking healthcare. This online search was done to identify any type of transgender focused healthcare databases that were community driven.

Results
Four resources were identified: TransBucket, TransAtlas, TransHealthCare, and Erin's Informed Consent hormone replacement therapy map of the US. Noting that there are limited resources, an app that is community driven and provides information on all types of healthcare providers, not exclusively surgeons or endocrinologists, was developed.

Conclusion
Seeking gender-affirming healthcare providers is a strenuous task filled with uncertainty and few reliable resources. Resources that provide the input of transgender individuals on their experiences with healthcare providers is one step in addressing this issue. Resources, such as TranZap, must be developed to close the gaps in access to healthcare by providing a platform for transgender patients to share experiences about healthcare providers in the hopes that those using the app will be able to find a welcoming gender-affirming provider.