bluuebunny/crossref_metadata_2025_split huggingface dataset:
Turbulence Structure and Mixing in Strongly Stable Boundary-Layer Flows over Thermally Heterogeneous Surfaces
Authors: Mironov Dmitrii V. , Sullivan Peter P. 
Published: January 2023

AbstractDirect numerical simulations (DNS) at bulk Reynolds number Re $$=10^4$$

=

10
4

and bulk Richardson number Ri $$=0.25$$

=
0.25

of plane Couette flow are performed with the results used to analyze the structure and mixing intensity in strongly stable boundary-layer flows. The Couette flow set-up is used as a proxy for a real-world stable boundary layer flow with surface thermal heterogeneity. Along the upper and lower walls, the temperature is either homogeneous or varies sinusoidally, but the horizontal-mean surface temperature is the same in all cases. Over homogeneous surfaces, the strong stratification always quenches turbulence resulting in linear velocity and temperature profiles. However, over a heterogeneous surface turbulence survives. Molecular diffusion and turbulence contribute to down-gradient momentum transfer. The total (diffusive plus turbulent) heat flux is directed downward, but its turbulent contribution is positive, i.e., up the mean temperature gradient. Analysis of covariances of velocity and temperature, their skewness, and the flow structure suggests that counter-gradient heat transport is due to quasi-organized cell-like vortical motions generated by surface thermal heterogeneity. These motions transfer heat upwards similar to their counterparts in highly convective boundary layers. Thus, the flow over heterogeneous surface features local convective instabilities and upward eddy heat transport, although the overall stratification remains stable with downward mean heat transfer. The DNS results are compared to the results from large-eddy simulations of weakly stable boundary layers (Mironov and Sullivan in J Atmos Sci 73:449–464, 2016). The DNS findings corroborate the key role of temperature variance in setting the structure and transport properties of stably stratified flow over heterogeneous surfaces, and the importance of third-order transport of the temperature variance.
Evaluation and refinement of a fish movement model for a tropical Australian stream subject to mine contaminant egress
Authors: Crook David A. , Wedd Dion , Adair Brendan J. , Mooney Thomas J. , Harford Andrew J. , Humphrey Chris L. , Morrongiello John R. , King Alison J. 
Published: January 2023

Abstract
The impacts of mine contaminants on ecological connectivity in rivers and streams are poorly documented globally. We used acoustic telemetry to evaluate and refine conceptual models of fish movement in Magela Creek, a stream in the wet-dry tropics of Australia. This creek receives wastewater discharge from a nearby uranium mine, and a secondary objective was to describe behavioural responses of fish to one such discharge event. Of 55 fish (black bream Hephaestus fuliginosus, saratoga Scleropages jardinii, sharp-nose grunter Syncomistes butleri) tagged in dry season refuge pools 18 km upstream of the mine lease area (RPA [Ranger Project Area]), 16 (29%) moved downstream after the first wet season flows, using the RPA as habitat for 3–5 months before moving upstream to their previous locations as flows receded. Of 39 fish (spangled perch Leiopotherapon unicolor, barred grunter Amniataba percoides, black catfish Neosilurus ater) tagged ~ 8–12 km downstream of the RPA in the late wet season, only two were subsequently detected in the RPA. Direct and camera-based observations of 12 species of upstream-migrating fish during mine-water discharge in the late wet season showed no evidence of mine-water avoidance. Our results demonstrate that Magela Creek provides wet season habitat for fish within the RPA and acts as a migration pathway that connects lowland reaches and floodplains to upstream dry season refuges. Use by fish of waterbodies within the RPA highlights the need to manage the site to ensure that future contaminant egress and water quality do not adversely affect fish migration and habitat suitability.
Estimating spatial disease rates using health statistics without geographic identifiers
Authors: Cortes-Ramirez Javier , Wilches-Vega Juan D. , Michael Ruby N. , Singh Vishal , Paris-Pineda Olga M. 
Published: January 2023

AbstractMorbidity statistics can be reported as grouped data for health services rather than for individual residence area, especially in low-middle income countries. Although such reports can support some evidence-based decisions, these are of limited use if the geographical distribution of morbidity cannot be identified. This study estimates the spatial rate of Acute respiratory infections (ARI) in census districts in Cúcuta -Colombia, using an analysis of the spatial distribution of health services providers. The spatial scope (geographical area of influence) of each health service was established from their spatial distribution and the population covered. Three levels of spatial aggregation were established considering the spatial scope of primary, intermediate and tertiary health services providers. The ARI cases per census district were then calculated and mapped using the distribution of cases per health services provider and the proportion of population per district in each level respectively. Hotspots of risk were identified using the Local Moran’s I statistic. There were 98 health services providers that attended 8994, 18,450 and 91,025 ARI cases in spatial levels 1, 2 and 3, respectively. Higher spatial rates of ARI were found in districts in central south; northwest and northeast; and southwest Cúcuta with hotspots of risk found in central and central south and west and northwest Cucuta. The method used allowed overcoming the limitations of health data lacking area of residence information to implementing epidemiological analyses to identify at risk communities. This methodology can be used in socioeconomic contexts where geographic identifiers are not attached to health statistics.
The effects of physical disturbance and sediment refuge on the growth of young native freshwater mussels Elliptio complanata (Eastern Elliptio)
Authors: Forbes-Green Marcus J. , Cyr Hélène 
Published: January 2023

AbstractNative freshwater mussels form a critical component of benthic foodwebs, but are endangered worldwide, making their study an important conservation issue. Many unionids live in shallow environments where they are potentially vulnerable to natural disturbances, but the impact of physical forces on their growth and the role of sediments as a refuge is poorly understood. Here, we validate the use of two types of shell internal lines (nacreous, prismatic) as indicators of physical disturbance and shell coloration as an indicator of sedimentary habitat. We use these indicators to test (1) whether the sediments provide an effective refuge for juvenile and young adult mussels from natural disturbances and (2) whether disturbance events affect their growth.Elliptio complanata(Eastern Elliptio) emerge from the sediments when they are 20–50 mm in size and 2.5–7 years old. Juvenile and young adults lay down more disturbance lines at more exposed nearshore sites, but also in small lake basins with dense mussel populations. Disturbance lines are produced during both endo- and epibenthic growth periods, but in contrast to adults, they are not associated with growth anomalies. Sediments accumulating in shallow nearshore areas of lakes provide an imperfect but effective refuge for native mussels that warrant protection.
Immunodetection of Pyruvate Carboxylase Expression in Human Astrocytomas, Glioblastomas, Oligodendrogliomas, and Meningiomas
Authors: Gondáš Eduard , Kráľová Trančíková Alžbeta , Dibdiaková Katarina , Galanda Tomáš , Hatok Jozef , Račay Peter , Dobrota Dušan , Murín Radovan 
Published: January 2023

AbstractPyruvate carboxylase (PC) is an enzyme catalyzing the carboxylation of pyruvate to oxaloacetate. The enzymatic generation of oxaloacetate, an intermediate of the Krebs cycle, could provide the cancer cells with the additional anaplerotic capacity and promote their anabolic metabolism. Recent studies revealed that several types of cancer cells express PC. The gained anaplerotic capability of cells mediated by PC correlates with their expedited growth, higher aggressiveness, and increased metastatic potential. By immunohistochemical staining and immunoblotting analysis, we investigated PC expression among samples of different types of human brain tumors. Our results show that PC is expressed by the cells in glioblastoma, astrocytoma, oligodendroglioma, and meningioma tumors. The presence of PC in these tumors suppose that PC could support the anabolic metabolism of their cellular constituents by its anaplerotic capability.
Moment-based density estimation of confidential micro-data: a computational statistics approach
Authors: Wakefield Bradley , Lin Yan-Xia , Sarathy Rathin , Muralidhar Krishnamurty 
Published: January 2023

AbstractProviding access to synthetic micro-data in place of confidential data to protect the privacy of participants is common practice. For the synthetic data to be useful for analysis, it is necessary that the density function of the synthetic data closely approximate the confidential data. Hence, accurately estimating the density function based on sample micro-data is important. Existing kernel-based, copula-based, and machine learning methods of joint density estimation may not be viable. Applying the multivariate moments’ problem to sample-based density estimation has long been considered impractical due to the computational complexity and intractability of optimal parameter selection of the density estimate when the true joint density function is unknown. This paper introduces a generalised form of the sample moment-based density estimate, which can be used to estimate joint density functions when only the information of empirical moments is available. We demonstrate optimal parametrisation of the moment-based density estimate based solely on sample data by employing a computational strategy for parameter selection. We compare the performance of the moment-based estimate to that of existing non-parametric and parametric density estimation methods. The results show that using empirical moments can provide a reasonable, robust non-parametric approximation of a joint density function that is comparable to existing non-parametric methods. We provide an example of synthetic data generation from the moment-based density estimate and show that the resulting synthetic data provides a reasonable disclosure-protected alternative for public release.
How should we promote transient diversity in science?
Authors: Wu Jingyi , O’Connor Cailin 
Published: January 2023

AbstractDiversity of practice is widely recognized as crucial to scientific progress. If all scientists perform the same tests in their research, they might miss important insights that other tests would yield. If all scientists adhere to the same theories, they might fail to explore other options which, in turn, might be superior. But the mechanisms that lead to this sort of diversity can also generate epistemic harms when scientific communities fail to reach swift consensus on successful theories. In this paper, we draw on extant literature using network models to investigate diversity in science. We evaluate different mechanisms from the modeling literature that can promote transient diversity of practice, keeping in mind ethical and practical constraints posed by real epistemic communities. We ask: what are the best ways to promote an appropriate amount of diversity of practice in scientific communities?
Therapeutic uses and applications of bovine lactoferrin in aquatic animal medicine: an overview
Authors: Abdelnour Sameh A. , Ghazanfar Shakira , Abdel-Hamid Mahmoud , Abdel-Latif Hany M.R. , Zhang Zhaowei , Naiel Mohammed A.E. 
Published: January 2023

AbstractAquaculture is an important food sector throughout the globe because of its importance in ensuring the availability of nutritious and safe food for human beings. In recent years, this sector has been challenged with several obstacles especially the emergence of infectious disease outbreaks. Various treatment and control aspects, including antibiotics, antiseptics, and other anti-microbial agents, have been used to treat farmed fish and shrimp against diseases. Nonetheless, these medications have been prohibited and banned in many countries because of the development of antimicrobial-resistant bacterial strains, the accumulation of residues in the flesh of farmed fish and shrimp, and their environmental threats to aquatic ecosystems. Therefore, scientists and researchers have concentrated their research on finding natural and safe products to control disease outbreaks. From these natural products, bovine lactoferrin can be utilized as a functional feed supplement. Bovine lactoferrin is a multi-functional glycoprotein applied in various industries, like food preservation, and numerous medications, due to its non-toxic and ecological features. Recent research has proposed multiple advantages and benefits of using bovine lactoferrin in aquaculture. Reports showed its potential ability to enhance growth, reduce mortalities, regulate iron metabolism, decrease disease outbreaks, stimulate the antioxidant defense system, and recuperate the overall health conditions of the treated fish and shrimp. Besides, bovine lactoferrin can be considered as a safe antibiotic alternative and a unique therapeutic agent to decrease the negative impacts of infectious diseases. These features can be attributed to its well-known antibacterial, anti-parasitic, anti-inflammatory, immunostimulatory, and antioxidant capabilities. This literature review will highlight the implications of bovine lactoferrin in aquaculture, particularly highlighting its therapeutic features and ability to promote immunological defensive pathways in fish. The information included in this article would be valuable for further research studies to improve aquaculture’s sustainability and the functionality of aquafeeds.
Experimental Investigation of Phase Relations and Thermodynamic Modelling of the Fe-Mn-Zr System
Authors: Kuprava A. , Saenko I. , Fischer P. , Fabrichnaya O. 
Published: January 2023

AbstractPhase equilibria in the Fe-Mn-Zr system have been studied experimentally using SEM/EDX methods, EBSD and powder x-ray diffraction. Quasi binary section of ZrFe2-ZrMn2has been constructed. Invariant reactions were studied using differential thermal analysis followed by SEM/EDX. Using obtained experimental results at 1073 K, ternary isothermal section has been constructed. A self-consistent thermodynamic description of the Fe-Mn-Zr system has been developed using the CALPHAD method based on the new experimental information.
Molecular Mechanics of Disordered Solids
Authors: Bamer Franz , Ebrahem Firaz , Markert Bernd , Stamm Benjamin 
Published: January 2023

AbstractDisordered solids are ubiquitous in engineering and everyday use. Although research has made considerable progress in the last decades, our understanding of the mechanics of these materials is, at best, in an embryonic state. Since the nature of disorder complicates the realization of physically meaningful continuum-mechanical models, particle-based molecular descriptions provide a powerful alternative. This paper reviews the numerical realization of classical molecular dynamics from an engineer’s perspective, starting with selecting potential functions, boundary conditions, time integration, and thermodynamic ensembles. Then, we discuss the concept of the potential energy landscape and the computational realization of the most suitable minimization methods. Subsequently, we discuss the algorithms necessary to numerically generate disordered materials, considering their thermodynamic properties and structural identification. We comprehensively and critically review computational methods and strategies available to mimic disordered materials on a molecular level and discuss some intriguing phenomena that are, to date, mostly ignored when applying models based on continuum-mechanical frameworks. We present the crucial difference between the shear response of a crystalline and a disordered structure. In this context, we elaborate on why it is beneficial to use an overdamped, athermal description to disentangle the complex deformation mechanics of disordered solids and comprehensively discuss the theory of the mechanics of disordered materials, including the problems of prediction and reversibility. Furthermore, we examine the fracture process on the nanoscale and investigate the response behavior to more complex deformation protocols. Finally, we provide critical conclusions, including challenges and future perspectives for engineers.
Modularity in Nervous Systems—a Key to Efficient Adaptivity for Deep Reinforcement Learning
Authors: Schilling Malte , Hammer Barbara , Ohl Frank W. , Ritter Helge J. , Wiskott Laurenz 
Published: January 2023

AbstractModularity as observed in biological systems has proven valuable for guiding classical motor theories towards good answers about action selection and execution. New challenges arise when we turn to learning: Trying to scale current computational models, such as deep reinforcement learning (DRL), to action spaces, input dimensions, and time horizons seen in biological systems still faces severe obstacles unless vast amounts of training data are available. This leads to the question: does biological modularity also hold an important key for better answers to obtain efficient adaptivity for deep reinforcement learning? We review biological experimental work on modularity in biological motor control and link this with current examples of (deep) RL approaches. Analyzing outcomes of simulation studies, we show that these approaches benefit from forms of modularization as found in biological systems. We identify three different strands of modularity exhibited in biological control systems. Two of them—modularity in state (i) and in action (ii) spaces—appear as a consequence of local interconnectivity (as in reflexes) and are often modulated by higher levels in a control hierarchy. A third strand arises from chunking of action elements along a (iii) temporal dimension. Usually interacting in an overarching spatio-temporal hierarchy of the overall system, the three strands offer major “factors” decomposing the entire modularity structure. We conclude that modularity with its above strands can provide an effective prior for DRL approaches to speed up learning considerably and making learned controllers more robust and adaptive.
Student motivation and engagement in maker activities under the lens of the Activity Theory: a case study in a primary school
Authors: Nikou Stavros A. 
Published: January 2023

AbstractMakerspaces are an area that is of increasing interest in education. While studies exist about makerspaces in tertiary education, not many studies have explored makerspaces in primary and secondary education. The current study focuses on pupils’ motivation and engagement in makerspace activities—digital fabrication and physical computing—in the context of a primary school, using the Activity Theory as its theoretical framework. The study follows an explanatory sequential mixed methods design. Primary school pupils participated in a six-week design-based makerspace programme in a Fablab and a school computer lab, and they completed a survey and participated in focus group discussions afterwards. Both quantitative and qualitative findings showed that pupils perceive maker activities as being motivating (in terms of perceived ease of use, perceived usefulness, interest/enjoyment, satisfaction) and engaging (in terms of behavioural, cognitive, emotional, and social engagement). The Activity Theory provides further insights on how motivation and engagement in makerspaces relate to the components of the activity system. The study advocates for the use of maker activities in the primary classroom. Implications on educational practices and future research are discussed.
Electronic Health Records That Support Health Professional Reflective Practice: a Missed Opportunity in Digital Health
Authors: Janssen Anna , Kay Judy , Talic Stella , Pusic Martin , Birnbaum Robert J. , Cavalcanti Rodrigo , Gasevic Dragan , Shaw Tim 
Published: January 2023

Abstract
A foundational component of digital health involves collecting and leveraging electronic health data to improve health and wellbeing. One of the central technologies for collecting these data are electronic health records (EHRs). In this commentary, the authors explore intersection between digital health and data-driven reflective practice that is described, including an overview of the role of EHRs underpinning technology innovation in healthcare. Subsequently, they argue that EHRs are a rich but under-utilised source of information on the performance of health professionals and healthcare teams that could be harnessed to support reflective practice and behaviour change. EHRs currently act as systems of data collection, not systems of data engagement and reflection by end users such as health professionals and healthcare organisations. Further consideration should be given to supporting reflective practice by health professionals in the design of EHRs and other clinical information systems.
Application of hybrid SFLA-ACO algorithm and CAM softwares for optimization of drilling tool path problems
Authors: Mehmood Nasir , Umer Muhammad , Asgher Umer 
Published: January 2023

Abstract
In drilling process almost seventy percent time is spent in tool switching and moving the spindle from one hole to the other. This time travel is non productive as it does not take part in actual drilling process. Therefore, this non productive time needs to be optimized. Different metaheuristic algorithms have been applied to minimize this non productive tool travel time. In this study, two metaheuristic approaches, shuffled frog leaping algorithm (SFLA) and ant colony optimization (ACO) have been hybridized. In industry, the CAM softwares are employed for minimization of non productive tool travel time and it is considered that the path obtained by using the CAM softwares is the optimized path. However this is not the case in all problems. In order to show the contribution of the SFLA-ACO algorithm and to prove that results achieved through CAM softwares are not always optimized, hybrid SFLA-ACO algorithm has been applied to two drilling problems as case studies with the main objective of minimization of non productive tool travel time. The drilling problems which are taken from the manufacturing industry include ventilator manifold problem and lift axle mounting bracket problem. The results of hybrid SFLA-ACO algorithm have been compared with the results of commercially available computer aided manufacturing (CAM) software. For comparison purpose, the CAM softwares used are Creo 6.0, Pro E, Siemens NX and Solidworks. The comparison shows that the results of proposed hybrid SFLA-ACO algorithm are better than commercially available CAM softwares in both real world manufacturing problems.

Article highlights

Different optimization techniques are being used for optimization of drilling tool path problems. In this paper two techniques SFLA and ACO has been combined to form a hybrid SFLA-ACO algorithm and has been applied to the real world industrial problems.

Two real world problems have been taken from the local manufacturing industries. In both the problems the objective is to optimize the tool traveling time through hybrid SFLA-ACO and compare it with CAM software.

Four CAM softwares have been used for comparison purpose. The problems undertaken are solved through these CAM software and compared with the results of hybrid SFLA-ACO results. As result of comparison it is found that in both the problems the performance of hybrid SFLA-ACO algorithm remains outclass. This signifies that results of CAM software in case of optimization of drilling tool path are not always optimal and these can be improved by using different optimization techniques.