bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Ecological Perspective on Classroom‐Based Assessment
Authors: Chong Sin Wang , Isaacs Talia 
Published: January 2023

AbstractClassroom‐based assessment (CBA) takes place in learning environments influenced by myriad individual and contextual factors. Nevertheless, factors related to individual differences and learner psychology are seldom considered in creating instructional environments designed to facilitate learners' use of CBA. This article introduces the concept oflanguage assessment ecology(LAE)—a dynamic classroom environment where learners' needs are addressed through deliberate and informed orchestration of a language learning environment so that learners can make effective use of assessment for their learning. Informed by Ecological Systems Theory, we postulate that LAE is a multi‐layered system, where learners' engagement with CBA is an outcome of alignment between learning contexts and learners' cognitive‐psychological needs. At the outset of this article, we provide a review of current CBA frameworks to underscore the merits of LAE. Contextual and learner variables that need to be considered in an LAE are then identified and discussed. From a complex dynamic systems perspective, the versatility and complexity of the interplay among these variables will be stressed. The article concludes with the implications of LAE for conducting CBA research.
Effects of maternal exposure to procymidone on hepatic metabolism in the offspring of mice
Authors: Wang Xiaofang , Hu Lingyu , Jin Cuiyuan , Qian Mingrong , Jin Yuanxiang 
Published: January 2023

AbstractAs an effective fungicide widely used in agricultural production, the excessive procymidone (PRO) residue has been detected in the environment and food. Our previous study demonstrated that PRO could destroy the intestinal barrier in mice and has a joint toxic effect. To explore the cross‐generational impact of maternal exposure, 10‐week‐old C57BL/6 female mice were orally administrated to 10 and 100 mg/kg body weight/day of PRO during pregnancy and lactation. The offspring obtained nutrients from the maternal through the placenta and breast milk, and PRO residues were detected in the liver, intestine, and feces of F1 generation. Fecal examination found that the residual PRO had been completely metabolized when the offspring mice grew to 35 days. The drug residue of F1 generation male mice was higher than that of female mice. We attributed this result to the difference in cytochrome P450 (CYP450) enzyme expression between male and female mice. The transcriptional levels of CYP1A1, CYP1A2, CYP2D9, and CYP3A4, and CYP450 protein expression levels, were higher in female mice. Furthermore, targeted MS of plasma revealed abnormal amino acid levels. In addition, PRO‐induced hepatic metabolite changes in F0 and F1‐7w mice. KEGG pathway analysis further showed that PRO jointly changed the amino acid biosynthesis pathway of the maternal and offspring. In summary, these results indicated that maternal exposure to PRO during a special period would interfere with self metabolism, and offspring will also have metabolic disorders.
Changes in the gene expression profile of the mammary gland lipogenic enzymes in Saanen goats in response to dietary fats
Authors: Javaheri Barfourooshi Hoda , Sadeghipanah Hassan , Asadzadeh Nader , Seyedabadi Hamidreza , Borazjani Marjan , Javanmard Arash 
Published: January 2023

AbstractBackgroundThe second half of the first pregnancy is a critical period in the growth and development of the mammary gland. The use of functional compounds during this period may positively impact livestock performance.ObjectivesIn this study, changes in lipogenic enzyme gene expression in the mammary gland of Saanen goats in response to different dietary fat sources were analysed.MethodsGoats from four groups (10 each) received these diets from the last two months of pregnancy through four months of lactation: C−, no added fat (negative control group), C+, with saturated palm oil (positive control group), SB, with roasted soybeans (omega‐6 group) and FS, with extruded flaxseed (omega‐3 group). The fat content was about 4% of dry matter. Milk yield, milk fatty acid profile, milk health index (HI) and gene expression of four lipogenic enzymes in mammary tissue were measured.ResultsThe FS group had significantly higher milk production with lower omega‐6 to omega‐3, monounsaturated to polyunsaturated, and total saturated fatty acids compared to other groups. The shorter and longer than16‐carbon chain of total milk fatty acid indicates significantly higher values for the C− and C+ groups, respectively. The milk HI for the SB group was significantly higher. The gene expression profile for acetyl‐coenzyme A carboxylase was higher in the C− group than other experimental groups.ConclusionsThe results show that manipulation of the diet with unsaturated fat supplements improved milk production, synthesis of milk fat and molecular expression of lipogenic enzymes in mammary tissue in primiparous Saanen goats.
In‐depth rheological study of acrylic processing aids in rigid polyvinyl chloride applications
Authors: Nerkar Manoj 
Published: January 2023

AbstractAcrylic processing aids are used widely in rigid polyvinyl chloride (PVC) applications. Key functions of processing aids in terms of processing and performance are discussed in the paper. Effect of molecular weight of acrylic processing aids on their functions are studied. Additionally, effect of processing conditions, such as temperature and shear on fusion characteristics of PVC formulations are investigated. Shear rate in the processing was varied by means of rotor speed in torque rheometer. Processing aids of comprehensive molecular weight range are evaluated in the study. It was observed that relatively lower molecular weight processing aids have different response to change in shear and temperature than higher molecular weight processing aids. Depending upon fusion conditions PVC formulations can yield either a single or double fusion peak. Generally, it was considered that ultra‐high molecular weight processing aids yield a double fusion peak, however, it was demonstrated in the studies that it is not true. Fusion conditions, temperature, and shear are the main driving forces of fusion dynamics, resulting in either a single or double fusion peak. Relatively low molecular weight acrylic processing aids can also yield double fusion peak. Melt viscosity and shear thinning properties are also examined. Relatively lower molecular weight processing aids showed higher shear thinning behavior. Effect of temperature and shear on degree of fusion was studied. It was shown that optimum processing parameters can increase the degree of fusion by ~10%.
Locality Estimates for Complex Time Evolution in 1D
Authors: Pérez-García David , Pérez-Hernández Antonio 
Published: January 2023

AbstractIt is a generalized belief that there are no thermal phase transitions in short range 1D quantum systems. However, the only known case for which this is rigorously proven is for the particular case of finite range translationally invariant interactions. The proof was obtained by Araki in his seminal paper of 1969 as a consequence of pioneering locality estimates for the time-evolution operator that allowed him to prove its analyticity on the whole complex plane, when applied to a local observable. However, as for now there is no mathematical proof of the absence of 1D thermal phase transitions if one allows exponential tails in the interactions. In this work we extend Araki’s result to include exponential (or faster) tails. Our main result is the analyticity of the time-evolution operator applied on a local observable on a suitable strip around the real line. As a consequence we obtain that thermal states in 1D exhibit exponential decay of correlations above a threshold temperature that decays to zero with the exponent of the interaction decay, recovering Araki’s result as a particular case. Our result however still leaves open the possibility of 1D thermal short range phase transitions. We conclude with an application of our result to the spectral gap problem for Projected Entangled Pair States (PEPS) on 2D lattices, via the holographic duality due to Cirac et al.
Three-dimensional microCT imaging of mouse heart development from early post-implantation to late fetal stages
Authors: Li-Villarreal Nanbing , Rasmussen Tara L. , Christiansen Audrey E. , Dickinson Mary E. , Hsu Chih-Wei 
Published: January 2023

AbstractComprehensive detailed characterization of new mouse models can be challenging due to the individual focus involved in developing these models. Often models are engineered to test a specific hypothesis in a limited number of tissues, stages, and/or other contexts. Whether or not the model produces the desired phenotypes, phenotyping beyond the desired context can be extremely work intensive and these studies are often not undertaken. However, the general information resulting from broader phenotyping can be invaluable to the wider scientific community. The International Mouse Phenotyping Consortium (IMPC) and its subsidiaries, like the Knockout Mouse Project (KOMP), has made great strides in streamlining this process. In particular, the use of microCT has been an invaluable resource in examining internal organ systems throughout fetal/developmental stages. Here, we provide several novel vignettes demonstrating the utility of microCT in uncovering cardiac phenotypes both based on human disease correlations and those that are unpredicted.
Work-related head injury and industry sectors in Finland: causes and circumstances
Authors: Heimonen Aura , Nousiainen Kari , Lassila Heikki , Kaukiainen Ari 
Published: January 2023

Abstract
Objective
Despite the continuous development of occupational safety, the prevalence of work-related head injuries is excessive. To promote prevention, we conducted a study evaluating the risks and pathways that precede head injuries in different economic activity sectors.

Methods
In Finland, more than 90% of employees are covered by inclusive statutory workers’ compensation. We obtained data on occupational head injuries in 2010–2017 from an insurance company database. The European Statistics on Accidents at Work (ESAW) variables represented the characteristics of the accidents and the injury. We analysed the risk factors, contributing events and injury mechanisms in 20 industry sectors, based on the Statistical Classification of Economic Activities in the European Community (NACE).

Results
In the 32,898 cases, the most commonly affected area was the eyes (49.6%). The highest incidence of head injuries was in construction (15.7 per 1000 insurance years). Construction, manufacturing, and human health and social work activities stood out due to their distinctive ESAW category counts. ‘Working with hand-held tools’ [risk ratio (RR) 2.23, 95% confidence interval (CI) 2.14–2.32] in construction and ‘operating machines’ (RR 3.32, 95% CI 3.01–3.66) and ‘working with hand-held tools’ (1.99, 1.91–2.07) in manufacturing predicted head injury. The risk related to parameters of violence and threats in health and social work activities was nearly ninefold the risk of other sectors.

Conclusion
The risks and pathways preceding head injuries varied considerably. The highest head injury rates were in construction and manufacturing. Violence emerged as a major risk factor in human health and social work activities.
Systemic immune-inflammation index during treatment predicts prognosis and guides clinical treatment in patients with nasopharyngeal carcinoma
Authors: Yuan Xiaofei , Feng Huiru , Huang Haoran , Li Junzheng , Wu Shuting , Yuan Yue , Cui Linchong , Lin Danfan , Chen Zilu , Lu Wenxuan , Liu Xiong , Peng Xiaohong , Wang Fan 
Published: January 2023

Abstract
Purpose
Systemic immune-inflammation index (SII) has been demonstrated to be closely associated with the poor prognosis of nasopharyngeal carcinoma (NPC). However, the role of SII during treatment of NPC has not been reported. This study aimed to determine the prognostic value of SII during treatment for NPC patients.

Methods
A total of 759 patients diagnosed with NPC were included in this retrospective study (393 in training cohort and 366 in validation cohort). The correlation between variables was analyzed by the chi-squared test, the Fisher’s exact test or the likelihood test. Kaplan–Meier method and log-rank test were used to analyze progression-free survival (PFS) and overall survival (OS). The independent prognostic factors were determined by multivariate analysis of Cox proportional hazards regression model. The uncontrolled risk was analyzed by Logistic regression. Receiver operating characteristic (ROC) curves were used to assess prognostic value.

Results
The optimal cut-off point for the SII during treatment was 937.32. High SII during treatment group had higher uncontrolled risk than low SII during treatment group (p = 0.008). In multivariate Cox proportional hazard models analysis, SII during treatment was an independent prognostic factor for 5-year PFS (p < 0.001) and 5-year OS (p < 0.001). All results were found in the training cohort and confirmed in the validation cohort.

Conclusions
The SII during treatment is a promising indicator of predicting the survival in NPC patients, especially the risk of uncontrolled occurrence. By monitoring the SII during treatment, it is possible to better evaluate the treatment effect and formulate personalized treatment.
COVID-19 – Treiber für die Digitalisierung des Einzelhandels?
Authors: Herb Christopher , Friedrich Carla , Neiberger Cordula 
Published: January 2023

ZusammenfassungDie COVID-19-Pandemie hat nicht nur die Gesellschaft, sondern auch die Wirtschaft, darunter speziell den Einzelhandel, vor große Herausforderungen gestellt. Während Onlinehändler von der Schließung lokaler Geschäfte profitierten, wurde dem stationären Einzelhandel plötzlich die Haupteinnahmequelle entzogen. Dieser befindet sich seit Jahrzehnten in einem Strukturwandel, der sich zuletzt durch die umfassende gesellschaftliche und wirtschaftliche Digitalisierung neuen Herausforderungen stellen musste. Unser Beitrag beschäftigt sich mit der Frage, inwieweit Handelsunternehmen sich gezwungen sahen, eine verstärkte Digitalisierung, hier untersucht als Präsenz im Internet, durch die Coronalockdowns vorzunehmen. Wir betrachten unterschiedliche Onlinestrategien, die von einer kompletten Inaktivität bis hin zu einer umfassenden Onlinestrategie (Onlineshops, unterstützt durch Social-Media-Aktivitäten) reichen. Um die Entwicklung in den letzten Jahren sowie über drei COVID-19-Lockdowns sichtbar zu machen, stellt die Untersuchung einen Vergleich zwischen zwei Erhebungszeitpunkten (2017/18 und 2021) anhand vierer Mittelstädte in Nordrhein-Westfalen (Baesweiler, Düren, Eschweiler, Heinsberg) dar. Es zeigt sich, dass der Digitalisierungsprozess grundsätzlich voranschreitet, wenngleich das Ausmaß der digitalen Aktivitäten stark von der jeweiligen Organisationsform abhängt. Zudem lassen sich auch Unterschiede hinsichtlich der Größe der Mittelstädte erkennen.
Traffic information interpolation method based on traffic flow emergence using swarm intelligence
Authors: Suga Satoshi , Fujimori Ryu , Yamada Yuji , Ihara Fumito , Takamura Daiki , Hayashi Ken , Kurihara Satoshi 
Published: January 2023

AbstractTraffic congestion has become one of the most pressing social problems in today’s society, and research into appropriate traffic signal control is actively underway. At present, most traffic signal control methods define traffic signal parameters on the basis of traffic information such as the number of passing vehicles. Installing sensors at a vast number of intersections is necessary for more precise and real-time adaptive control, but this is unrealistic from the viewpoint of cost. As an alternative, we propose a swarm intelligence-based methodology that creates routes with a similar traffic volume using the traffic information from intersections already equipped with sensors and interpolates this information in the intersections without sensors in real time. Our simulation results show that the proposed methodology can effectively create similar traffic routes for main traffic flows with high traffic volumes. The results also show that it has an excellent interpolation performance for heavy traffic flows and can adapt and interpolate to situations where traffic flow changes suddenly. Moreover, the interpolation results are highly accurate at a road link where traffic flows confluence. We also developed an interpolation algorithm that is adaptable to traffic patterns with confluence traffic flows. Experiments were conducted with a simulation of merging traffic flows and the proposed method showed good results.
Tropospheric parameters from multi-GNSS and numerical weather models: case study of severe precipitation and flooding in Germany in July 2021
Authors: Wilgan Karina , Dick Galina , Zus Florian , Wickert Jens 
Published: January 2023

AbstractStorms and floods are the most frequent natural disaster in western and central Europe. Due to climate change, intensive storms with prolonged rain episodes will continue to cause even more destructive flooding. The good understanding and forecasting of such events are thus of uttermost importance. One of the ways to improve weather forecasts is the assimilation of external data, such as the global navigation satellite systems (GNSS). In this study, a preparation of the multi-GNSS tropospheric products—zenith total delays, tropospheric gradients and slant total delays—for future operational assimilation is shown. For a severe precipitation event in July 2021 in Germany, the GNSS parameters from three systems—GPS, GLONASS and Galileo—are compared to three Numerical Weather Models (NWMs)—ERA5 reanalysis of ECMWF, ICON run by the German Weather Service and GFS run by the US Weather Service. The flood that followed the rainfall was the deadliest natural disaster in Germany since 1962. The results show that all considered GNSS solutions have a similar level of agreement with the NWMs. However, for the flood region in western Germany, the biases from the multi-GNSS solutions are smaller compared to the GPS-only solution. From the models, ICON has the highest agreement with the GNSS data for all considered tropospheric parameters. The best agreement with the ICON is probably due to its high horizontal resolution and, thus, low representative errors and the fine tuning of DWD’s regional model for the specific region (Germany).
N-Acetylcysteine: more than preventing contrast-induced nephropathy in uremic patients—focus on the antioxidant and anti-inflammatory properties
Authors: Cepaityte Dainora , Leivaditis Konstantinos , Varouktsi Garyfallia , Roumeliotis Athanasios , Roumeliotis Stefanos , Liakopoulos Vassilios 
Published: January 2023

AbstractOxidative stress (OS) has been recognized as a pathophysiologic mechanism underlying the development and progression of chronic kidney disease (CKD). OS, which results from the disturbance of balance among pro-oxidants and antioxidants favoring the pro-oxidants, is present even in early CKD and increases progressively along with deterioration of kidney function to end-stage kidney disease (ESKD). In ESKD, OS is further exacerbated mainly due to dialysis procedures per se and predisposes to increased cardiovascular morbidity and mortality. Therefore, since OS plays a pivotal role in the pathogenesis and progression of atherosclerosis in uremic patients, several strategies aiming to ameliorate OS in these patients have been proposed. Among those, N-acetylcysteine (NAC), a thiol-containing antioxidant agent, has attracted special attention due to its pleiotropic functions and beneficial effect in various OS-related entities including paracetamol overdose and prevention of contrast-induced nephropathy. In this review, we present the currently available literature on the antioxidant and anti-inflammatory properties of NAC in CKD, including hemodialysis and peritoneal dialysis.
A Gaussian regularization for derivative sampling interpolation of signals in the linear canonical transform representations
Authors: Annaby M. H. , Al-Abdi I. A. 
Published: January 2023

AbstractThe linear canonical transform (LCT) plays an important role in signal and image processing from both theoretical and practical points of view. Various sampling representations for band-limited and non-band-limited signals in the LCT domain have been established. We focus in this paper on the derivative sampling reconstruction, where the reconstruction procedure utilizes samples of both the signal and its first derivative. Our major aim was to incorporate the reconstruction sampling operator with a Gaussian regularization kernel, which on the one hand is applicable for not necessarily band-limited signals and on the other hand hastens the convergence of the reconstruction procedure. The amplitude error is also considered with deriving rigorous estimates. The obtained theoretical results are tested through various simulated experiments.
Global environmental equities and investor sentiment: the role of social media and Covid-19 pandemic crisis
Authors: de Sousa-Gabriel Vítor Manuel , Lozano-García María Belén , Matias Maria Fernanda Ludovina Inácio , Neves Maria Elisabete , Martínez-Ferrero Jennifer 
Published: January 2023

AbstractAccording to researchers, information generated from social media provides useful data for understanding the behaviour of various types of financial assets, using the sentiment expressed by these network users as an explanatory variable of asset prices. In a context in which investment based on sustainability and environmental preservation values is vital, there is no known scientific work that analyses the relationship between social networks and environmental investment, which is closely related to the 2030 Agenda for Sustainable Development. In this study, we aim to identify how investor sentiment, generated from social networks, influences environmental investment and whether this influence depends on the time variable, as well the role of the pandemic crisis and the Russia-Ukraine war. Our results show different forms of behaviour for the different periods considered, with the proximity between the two types of variables being time-varying. For shorter periods, proximity occurred mainly during the pandemic crisis, repeatedly revealing that sentiment is a risk factor in environmental investment and in particular how important the information generated from social networks can be in pricing environmental assets. For longer periods, no common stochastic trends were identified. The mechanisms generating the series are thus characterised by a certain autonomy.