bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptable scaffolding of mathematical argumentation skills: The role of self-regulation when scaffolded with CSCL scripts and heuristic worked examples
Authors: Vogel Freydis , Kollar Ingo , Fischer Frank , Reiss Kristina , Ufer Stefan 
Published: March 2022

AbstractCollaboration scripts and heuristic worked examples have been described as powerful scaffolds to support skill acquisition in CSCL. While CSCL scripts particularly facilitate argumentative discourse within groups, heuristic worked examples provide heuristics and worked out pathways to solve domain-specific tasks. Yet, both scripts and heuristic worked examples are often designed in a one-size-fits-all fashion. Granting learners the opportunity to adapt these scaffolds to their self-perceived needs might be a way to further enhance their effects. We tested this assumption in two experiments. In experiment 1, we compared the effects of learning with adaptable and non-adaptable CSCL scripts. In experiment 2, we compared the effects of learning with adaptable and non-adaptable heuristic worked examples. University students (N = 167) learned repeatedly in pairs with either adaptable or non-adaptable scaffolding in the context of mathematical conjecture problems. Results show that adaptable CSCL scripts were partly helpful for students with higher levels of self-regulation skills. Non-adaptable maximal scaffolding supported learning of distinctive skill components. Social-discursive components were best facilitated by maximal heuristic worked examples through content knowledge scaffolds. In contrast, CSCL scripts best facilitated domain-specific skill components by scaffolding learners’ engagement in social discourse about domain knowledge. The study provides recommendations for designing adaptable scaffolding by taking into account the relation between the targeted skill component and the activities scaffolded in the learning process. We suggest conducting future studies on adaptable scaffolding with a focus on supporting learning regulation and group awareness to improve learners’ success in CSCL environments.
Micro-segmental hair analysis: detailed procedures and applications in forensic toxicology
Authors: Kuwayama Kenji , Miyaguchi Hajime , Kanamori Tatsuyuki , Tsujikawa Kenji , Yamamuro Tadashi , Segawa Hiroki , Okada Yuki , Iwata Yuko T. 
Published: March 2022

Abstract
Purpose
Since the 1980s, the detection sensitivity of mass spectrometers has increased by improving the analysis of drugs in hair. Accordingly, the number of hair strands required for the analysis has decreased. The length of the hair segment used in the analysis has also shortened. In 2016, micro-segmental hair analysis (MSA), which cuts a single hair strand at a 0.4-mm interval corresponding to a hair growth length of approximately one day, was developed. The advantage of MSA is that the analytical results provide powerful evidence of drug use in the investigation of drug-related crimes and detailed information about the mechanism of drug uptake into hair. This review article focuses on the MSA technique and its applications in forensic toxicology.

Methods
Multiple databases, such as SciFinder, PubMed, and Google, were utilized to collect relevant reports referring to MSA and drug analysis in hair. The experiences of our research group on the MSA were also included in this review.

Results
The analytical results provide a detailed drug distribution profile in a hair strand, which is useful for examining the mechanism of drug uptake into hair in detail. Additionally, the analytical method has been used for various scenarios in forensic toxicology, such as the estimation of days of drug consumption and death.

Conclusions
The detailed procedures are summarized so that beginners can use the analytical method in their laboratories. Moreover, some application examples are presented, and the limitations of the current analytical method and future perspectives are described.
Trajectories of cognitive symptoms and associated factors in cancer survivors after return to work: an 18-month longitudinal cohort study
Authors: Ehrenstein Johanna K. , van Zon Sander K. R. , Duijts Saskia F. A. , Stewart Roy E. , Almansa Josué , Amick Benjamin C. , Schagen Sanne B. , Bültmann Ute 
Published: March 2022

Abstract

Purpose
Cognitive symptoms affect cancer survivors’ functioning at work. To date, cognitive symptoms trajectories in working cancer survivors and the factors associated with these trajectories have not been examined.

Methods
Data from a heterogeneous group of working cancer survivors (n = 379) of the longitudinal “Work-Life-after-Cancer” study, linked with Netherlands Cancer Registry data, were used. The Cognitive Symptom Checklist-Work was administered at baseline (within the first 3 months after return to work), 6-, 12-, and 18-month follow-up to measure self-perceived memory and executive function symptoms. Data were analyzed using group-based trajectory modeling.

Results
Four trajectories of memory and executive function symptoms were identified. All memory symptoms trajectories were stable and labeled as “stable-high” (15.3% of the sample), “stable-moderately high” (39.6%), “stable-moderately low” (32.0%), and “stable-low” (13.0%). Executive function symptoms trajectories changed over time and were labeled as “increasing-high” (10.1%), “stable-moderately high” (32.0%), “decreasing-moderately low” (35.5%), and “stable-low” (22.4%). Higher symptoms trajectories were associated with older age, longer time from diagnosis to return to work, more quantitative work demands, and higher levels of depressive symptoms at baseline.

Conclusions
In cancer survivors who returned to work, four cognitive symptoms trajectory subgroups were identified, representing different but relatively stable severity levels of cognitive symptoms.

Implications for Cancer Survivors
To identify cancer survivors with higher symptoms trajectories, health care providers should assess cognitive symptoms at baseline after return to work. In case of cognitive symptoms, it is important to also screen for psychological factors to provide appropriate guidance.
Die Bayerische Kinderschutzambulanz
Authors: Dittmann-Wolf Aline , Raabe Sarah , Seckinger Mike 
Published: March 2022

ZusammenfassungDie Evaluation der Bayerischen Kinderschutzambulanz hat gezeigt, dass eine landesweite Beratungsstelle Sensibilität und Handlungssicherheit auf ärztlicher Seite verbessern hilft, für Jugendämter eine wichtige Anlaufstelle ist und einen Beitrag zur Vernetzung von Ärzt_innen sowie der Kinder- und Jugendhilfe im Kinderschutz leisten kann. Hilfreich dabei sind ein Aktivitätenprofil, das Beratung und Fortbildung kombiniert sowie das Bestreben, die Beratung sowohl aus einer medizinischen als auch sozialpädagogischen Perspektive durchzuführen.
Hemophagocytic lymphohistiocytosis: a rare disease unveiling the diagnosis of EBV-related large B cell lymphoma in a patient with HIV
Authors: Noveihed Alexandra , Liang Shiochee , Glotfelty Joel , Lawrence Ibiyonu 
Published: March 2022

Abstract
Background
Hemophagocytic lymphohistiocytosis (HLH) is a rare disease resulting from the overactivation of the immune system due to under regulation of cytotoxic lymphocytes, macrophages and natural killer (NK) cells. HLH is associated with malignancies, infections, autoimmune disorders and rarely AIDS and is rapidly fatal.

Case presentation
This case report identified a 53 year old male with acquired immunodeficiency syndrome (AIDS) who presented with neutropenic fever of unknown origin. He had two previous hospitalizations prior to the hospitalization diagnosing HLH. The first led to a diagnosis of drug fevers in the setting of treatment for thrombotic thrombocytopenic purpura and subsequent hospitalization led to empiric treatment of hospital acquired pneumonia after workup for intermittent fevers was negative. He was discharged but readmitted 10 days after for recurrence of neutropenic fevers. During this final hospitalization, he was found to have elevated liver enzymes, ferritin, triglycerides and soluble IL-2 receptor with persistent fevers, new splenomegaly and bicytopenia meeting the 2004 HLH criteria. Bone marrow biopsy confirmed the diagnosis of HLH as well as EBV associated large B-cell lymphoma. The patient improved on treatment with steroids, rituximab, tocilizumab, and chemotherapy but ultimately passed away due to refractory septic shock from multi-drug resistant Klebsiella pneumoniae.

Conclusion
This novel case highlights a patient diagnosed with HLH in the setting of several risk factors for the disease, including AIDS, B-cell lymphoma and EBV. Additionally, this case highlights the importance of early consideration of HLH in the setting of neutropenic fever without clear infectious etiology and search for malignancy associated reasons for HLH especially in immunocompromised patients.
Combining high resolution input and stacking ensemble machine learning algorithms for developing robust groundwater potentiality models in Bisha watershed, Saudi Arabia
Authors: Mallick Javed , Talukdar Swapan , Ahmed Mohd. 
Published: March 2022

AbstractThe present research aims to build a unique ensemble model based on a high-resolution groundwater potentiality model (GPM) by merging the random forest (RF) meta classifier-based stacking ensemble machine learning method with high-resolution groundwater conditioning factors in the Bisha watershed, Saudi Arabia. Using high-resolution satellite images and other secondary sources, twenty-one parameters were derived in this study. SVM, ANN, and LR meta-classifiers were used to create the new stacking ensemble machine learning method. RF meta classifiers were used to create the new stacking ensemble machine learning algorithm. Each of these three models was compared to the ensemble model separately. The GPMs were then confirmed using ROC curves, such as the empirical ROC and the binormal ROC, both parametric and non-parametric. Sensitivity analyses of GPM parameters were carried out using an RF-based approach. Predictions were made using six hybrid algorithms and a new hybrid model for the very high (1835–2149 km2) and high groundwater potential (3335–4585 km2) regions. The stacking model (ROCe-AUC: 0.856; ROCb-AUC: 0.921) beat other models based on ROC's area under the curve (AUC). GPM sensitivity study indicated that NDMI, NDVI, slope, distance to water bodies, and flow accumulation were the most sensitive parameters. This work will aid in improving the effectiveness of GPMs in developing sustainable groundwater management plans by utilizing DEM-derived parameters.
Groundwater quality assessment using geospatial and statistical approaches over Faridabad and Gurgaon districts of National Capital Region, India
Authors: Swain Sabyasachi , Sahoo Sashikanta , Taloor Ajay Kumar 
Published: March 2022

AbstractThis study presents an assessment of groundwater quality over the two constituent districts (Faridabad and Gurgaon) of the National Capital Region (NCR), India, using geospatial and statistical approaches. These districts have been subjected to rapid urbanization and industrialization in recent years. The groundwater quality parameters viz., pH, electrical conductivity (EC), carbonate (CO32−), bicarbonate (HCO3−), chloride (Cl−), sulphate (SO42−), nitrate (NO3−), fluoride (F−), calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+), silica (SiO2), and total hardness (TH) are obtained for the year of 2017 from 28 sites over the study area. The suitability for human drinking purposes is assessed by comparing the concentration of parameters at each site with respect to their permissible limits recommended by the Bureau of Indian Standards (IS 10500: 2012). The geospatial mapping of the water quality parameters is carried out to visualize their variations, whereas their risk assessment is accomplished by the statistical approaches viz., water quality index (WQI), correlation, and principal component analysis (PCA). The number of sites exceeding the permissible limits of pH, EC, Cl−, SO42−, NO3−, F−, Ca2+, Mg2+, Na+, K+, and TH is obtained to be 7, 15, 5, 6, 8, 3, 5, 7, 18, 3, and 8, respectively. The WQI analysis revealed 10 out of the 28 sites to be unsuitable for drinking purposes. The parameters mostly exhibited positive correlations except for pH that showed a negative correlation with other parameters. The results of PCA revealed the first principal component (PC1) to explain more than 95% of the total variance, thereby significantly reducing the dimensionality. The deteriorated water quality may be mainly attributed to anthropogenic activities, i.e., reckless industrial growth, population explosion, and rapid urbanization. This study emphasizes the need for regular water quality monitoring, and the information reported will certainly help for water resources planning and management, especially over the industrial regions of NCR, India.
Dynamic Rollover of Gyroplanes during Landing—Cause and Prevention
Authors: Duda Holger , Sachs Falk , Seewald Jörg , Lorenz Sven 
Published: March 2022

AbstractWhile new-generation gyroplanes are very stable during flight, the susceptibility to roll over briefly after touching down is still the issue due to incorrectly applied landing procedure. A tendency to dynamically roll over is also known from helicopters but rarely from airplanes. The main cause for rotary wing aircraft’s risk to rollover is the rotor force which is still relevant after touching down. The triangular wheel system of a gyroplane in combination with high centre of gravity is another factor for gyroplane’s rollover susceptibility during landing. Typical situations provoking a rollover are landings during severe crosswind or taxiing at too high ground speeds with a rotating rotor. Both situations are related to incorrect piloting techniques. In this paper, the forces acting on the gyroplane during landing were investigated to understand the physical principles. Analytical equations were evaluated using the data of a reference gyroplane in combination with a single-track model known from road vehicle dynamics. It appeared that a steering oversensitivity may occur if the pilot moves the stick forward too early after touching down. Non-linear simulations with a validated model of the reference gyroplane confirmed these analyses. Design parameter studies were conducted to analyse the impact on rollover susceptibility. Finally, this study confirmed that a rollover of a gyroplane during landing is most unlikely if the pilot applies the correct technique, which means pulling the control stick back properly after touching down.
Oil, export diversification and economic growth in Sudan: evidence from a VAR model
Authors: Ali Sabna , Murshed Syed Mansoob , Papyrakis Elissaios 
Published: March 2022

Abstract
There is an extensive literature demonstrating a positive link between export diversification and economic growth. In parallel, the resource curse thesis posits export concentration as an important mechanism curtailing growth in mineral-rich countries. Our analysis contributes to this literature by empirically investigating the interaction between oil dependence captured by the share of oil rents in GDP and export diversification and economic growth for Sudan. We do this with the help of a VAR model using annual data between 1960 and 2018. In comparison to earlier studies, our dataset covers also Sudan’s post-oil boom period, which coincided with a substantial drop in oil dependence after the 2011 secession of South Sudan. We find that oil rents appear to have a statistically significant and negative effect on export diversification, although contemporaneously rather than in the long-term. However, we find no evidence of a statistically significant impact of either oil dependence or export diversification on economic growth, as suggested by the resource curse hypothesis.
Islamic Studies in Australian Islamic schools: educator voice
Authors: Abdalla Mohamad , Chown Dylan , Memon Nadeem 
Published: March 2022

AbstractThis paper responds to calls for renewal in Islamic schooling and education. In doing so, it provides insight into educators’ views on Islamic Studies (IS) in five Australian Islamic schools, with a focus on senior years (years 10, 11 and 12). The study offers a ‘dialogic alternative’ of ‘speaking with’ rather than ‘speaking for’ educators in Islamic educational research, planning, and renewal within K-12 Australian Islamic schools. It privileges educators’ voice and enables an insight into their experience with one of the most important and distinct features of Islamic schools – IS. Using phenomenology as a methodological framework, educators’ voice was elicited through focus groups where eighteen educators provided information describing their experience with IS. The study identified “strengths” and “challenges” of IS. Strengths includes parents’ desire for IS, educators’ personal connection with learner, knowledge of subject-matter, autonomy in teaching IS and unity among IS educators. The challenges outweigh the strengths and include insufficient time for IS, lack of resources, absence of a clear vision leading to a tokenistic and fragmented approach to the teaching of IS, low-level respect and recognition of IS educators and more.
A Fixed-Point Fast Sweeping WENO Method with Inverse Lax-Wendroff Boundary Treatment for Steady State of Hyperbolic Conservation Laws
Authors: Li Liang , Zhu Jun , Shu Chi-Wang , Zhang Yong-Tao 
Published: March 2022

AbstractFixed-point fast sweeping WENO methods are a class of efficient high-order numerical methods to solve steady-state solutions of hyperbolic partial differential equations (PDEs). The Gauss-Seidel iterations and alternating sweeping strategy are used to cover characteristics of hyperbolic PDEs in each sweeping order to achieve fast convergence rate to steady-state solutions. A nice property of fixed-point fast sweeping WENO methods which distinguishes them from other fast sweeping methods is that they are explicit and do not require inverse operation of nonlinear local systems. Hence, they are easy to be applied to a general hyperbolic system. To deal with the difficulties associated with numerical boundary treatment when high-order finite difference methods on a Cartesian mesh are used to solve hyperbolic PDEs on complex domains, inverse Lax-Wendroff (ILW) procedures were developed as a very effective approach in the literature. In this paper, we combine a fifth-order fixed-point fast sweeping WENO method with an ILW procedure to solve steady-state solution of hyperbolic conservation laws on complex computing regions. Numerical experiments are performed to test the method in solving various problems including the cases with the physical boundary not aligned with the grids. Numerical results show high-order accuracy and good performance of the method. Furthermore, the method is compared with the popular third-order total variation diminishing Runge-Kutta (TVD-RK3) time-marching method for steady-state computations. Numerical examples show that for most of examples, the fixed-point fast sweeping method saves more than half CPU time costs than TVD-RK3 to converge to steady-state solutions.
Annealing of Monel 400 Alloy Using Principal Component Analysis, Hyper-parameter Optimization, Machine Learning Techniques, and Multi-objective Particle Swarm Optimization
Authors: Chintakindi Sanjay , Alsamhan Ali , Abidi Mustufa Haider , Kumar Maduri Praveen 
Published: March 2022

AbstractThe purpose of this paper is to investigate the effect of the annealing process at 1000 °C on machining parameters using contemporary techniques such as principal component analysis (PCA), hyper-parameter optimization by Optuna, multi-objective particle swarm optimization, and theoretical validation using the machine learning method. Results after annealing show that there will be a reduction in surface roughness values by 19.61%, tool wear by 6.3%, and an increase in the metal removal rate by 14.98%. The PCA results show that the feed is more significant than the depth of cut and speed. The higher value of the composite primary component will represent optimal factors such as speed of 80, feed of 0.2 and depth of cut of 0.3, and values of principal components like surface roughness (Ψ1 = 64.5), tool wear (Ψ2 = 22.3) and metal removal rate (Ψ3 = 13.2). Hyper-parameter optimization represents speed is directly proportional to roughness, tool wear, and metal removal rate, while feed and depth of cut are inversely proportional. The optimization history plot will be steady, and the prediction accuracy will be 96.96%. Machine learning techniques are employed through the Python language using Google Colab. The estimated values from the decision tree method for surface roughness and tool wear predictions using the AdaBoost algorithm match well with actual values. As per MOPSO (multi-objective particle swarm optimization), the predicted responses are as follows; surface roughness (2.5 μm, 100, 02, 0.45), tool wear (0.31 mm, 40, 0.40, 0.60), and MRR (material removal rate) (5145 mm3/min, 100, 0.4, 0.15). As validated by experimentation, there are small variations as the surface roughness varied by 1.56%, tool wear by 6.8%, and MRR by 2.57%.
Teaching principles of translational science to a broad scientific audience using a case study approach: A pilot course from the National Center for Advancing Translational Sciences
Authors: Faupel-Badger Jessica M. , Vogel Amanda L. , Hussain Shadab F. , Austin Christopher P. , Hall Matthew D. , Ness Elizabeth , Sanderson Philip , Terse Pramod S. , Xu Xin , Balakrishnan Krishna , Patnaik Samarjit , Marugan Juan J. , Rudloff Udo , Ferrer Marc 
Published: March 2022

Abstract
There are numerous examples of translational science innovations addressing challenges in the translational process, accelerating progress along the translational spectrum, and generating solutions relevant to a wide range of human health needs. Examining these successes through an education lens can identify core principles and effective practices that lead to successful translational outcomes. The National Center for Advancing Translational Sciences (NCATS) is identifying and teaching these core principles and practices to a broad audience via online courses in translational science which teach from case studies of NCATS-led or supported research initiatives. In this paper, we share our approach to the design of these courses and offer a detailed description of our initial course, which focused on a preclinical drug discovery and development project spanning academic and government settings. Course participants were from a variety of career stages and institutions. Participants rated the course high in overall value to them and in providing a unique window into the translational science process. We share our model for course development as well as initial findings from the course evaluation with the goal of continuing to stimulate development of novel education activities teaching foundational principles in translational science to a broad audience.