bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anatomy of an educational change: The safe learning model, Sierra Leone
Authors: Sugrue Ciaran , Samonova Elena , Capistrano Daniel , Devine Dympna , Sloan Seaneen , Symonds Jennifer , Smith Aimee 
Published: August 2022

AbstractThis paper undertakes a critical analysis of a planned change, the Safe Learning Model (SLM), devised over time by Concern Worldwide, and implemented in 100 primary or elementary schools in a rural district of Sierra Leone. We situate the documentation pertaining to the SLM (micro) within its wider national (meso) and international (macro) context of influential policy texts. We undertake a mixed methods analysis of these macro, meso and micro documents, interrogated through the prism of various change paradigms (scientific management, progressivism, critical theory, teacher professionalism and social movement) and in doing establish where these various document clusters, their explicit and implicit influences, may be located along the arc of change paradigms, thus surfacing their ideological assumptions, intent and influences. The paper concludes that in seeking to improve the quality of teaching, learning, and living in this instance, scientific management casts long shadows. The power, perspectives and financial influence of international agencies dominate change discourses whereby ‘learning crises’ require urgent responses in the form of testing and measuring that prevail over more expansive pedagogical capacity building. Consequently, perpetuating a ‘weighing the pig’ mindset downplays or ignores the ecology of teaching and learning, particularly the centrality of teachers, as professionals and role models, more likely to be compliant than transformative.
Detector Array Readout with Traveling Wave Amplifiers
Authors: Giachero A. , Barone C. , Borghesi M. , Carapella G. , Caricato A. P. , Carusotto I. , Chang W. , Cian A. , Gioacchino D. Di , Enrico E. , Falferi P. , Fasolo L. , Faverzani M. , Ferri E. , Filatrella G. , Gatti C. , Giubertoni D. , Greco A. , Kutlu C. , Leo A. , Ligi C. , Maccarrone G. , Margesin B. , Maruccio G. , Matlashov A. , Mauro C. , Mezzena R. , Monteduro A. G. , Nucciotti A. , Oberto L. , Pagano S. , Pierro V. , Piersanti L. , Rajteri M. , Rizzato S. , Semertzidis Y. K. , Uchaikin S. , Vinante A. 
Published: August 2022

AbstractReducing noise to the quantum limit over a large bandwidth is a fundamental requirement for future applications operating at millikelvin temperatures, such as the neutrino mass measurement, the next-generation X-ray observatory, the CMB measurement, the dark matter and axion detection, and the rapid high-fidelity readout of superconducting qubits. The read out sensitivity of arrays of microcalorimeter detectors, resonant axion-detectors, and qubits, is currently limited by the noise temperature and bandwidth of the cryogenic amplifiers. The Detector Array Readout with Traveling Wave Amplifiers project has the goal of developing high-performing innovative traveling wave parametric amplifiers with a high gain, a high saturation power, and a quantum-limited or nearly quantum-limited noise. The practical development follows two different promising approaches, one based on the Josephson junctions and the other one based on the kinetic inductance of a high-resistivity superconductor. In this contribution, we present the aims of the project, the adopted design solutions and preliminary results from simulations and measurements.
Value is King: The MECForge Deep Reinforcement Learning Solution for Resource Management in 5G and Beyond
Authors: Poltronieri Filippo , Stefanelli Cesare , Suri Niranjan , Tortonesi Mauro 
Published: August 2022

AbstractMulti-access edge computing (MEC) is a key enabler to fulfill the promises of a new generation of immersive and low-latency services in 5G and Beyond networks. MEC represents a defining function of 5G, offering significant computational power at a reduced latency, allowing to augment the capabilities of user equipments while preserving their battery life. However, the demands generated by a plethora of innovative and concurrent IT services requiring high quality of service and quality of experience levels will likely overwhelm the—albeit considerable—resources available in 5G and Beyond scenarios. To take full advantage of its potential, MEC needs to be paired with innovative resource management solutions capable of effectively addressing the highly dynamic aspects of the scenario and of properly considering the heterogeneous and ever-changing nature of next generation IT services, prioritizing the assignment of resources in a highly dynamic and contextual fashion. This calls for the adoption of Artificial Intelligence based tools, implementing self-* approaches capable of learning the best resource management strategy to adapt to the ever changing conditions. In this paper, we present MECForge, a novel solution based on deep reinforcement learning that considers the maximization of total value-of-information delivered to end-user as a coherent and comprehensive resource management criterion. The experimental evaluation we conducted in a simulated but realistic environment shows how the Deep Q-Network based algorithm implemented by MECForge is capable of learning effective autonomous resource management policies that allocate service components to maximize the overall value delivered to the end-users.
Getting lost in the matrix? On how the characteristics and arrangement of linear landscape elements influence ecological connectivity
Authors: Anderson Calum , Travis Justin M. J. , Palmer Stephen C. F. , Crick Humphrey Q. P. , Lancaster Lesley T. 
Published: August 2022

Abstract
Context
Linear landscape elements (LLEs) such as ditches and hedgerows can increase the ecological connectivity of habitat embedded within agricultural areas by acting as corridors for animal movement. However, we lack knowledge on how the spatial arrangement of LLEs influence dispersal, impeding our ability to offer robust advice on how best to add new LLEs to improve connectivity.

Objectives
To examine how the width and spatial orientations of LLEs composing an intersecting network might influence connectivity across landscapes.

Methods
We used an individual-based dispersal model to simulate the stochastic movement of small organisms through stylised LLEs of different characteristics. Landscapes were composed of two habitat patches separated by a grid-like network of LLEs composed of two types: (1) connecting-edges (touching patches on either end) and (2) transecting-edges (running perpendicular to connecting-edges). By altering numbers and widths of each LLE type we sought to understand the effect of these variables on inter-patch dispersal rates.

Results
Increasing the number or width of connecting-edges improved connectivity but, conversely, increasing numbers or widths of transecting-edges reduced it. The greater freedom of movement offered by increasing numbers of transecting-edges may have inhibited connectivity, as individuals with limited perceptual-range were more likely to become trapped in complex networks and thus fail to navigate to suitable habitat patches.

Conclusions
Orientation of LLEs with respect to landscape resources greatly affects their impact on connectivity. The addition of LLEs to landscapes may decrease their connectivity for small, flightless species if they do not directly channel dispersers toward landscape resources.
SleepReplacer: a novel tool-based approach for replacing thread sleeps in selenium WebDriver test code
Authors: Olianas Dario , Leotta Maurizio , Ricca Filippo 
Published: August 2022

AbstractAssuring quality of web applications is fundamental, given their relevance in the today’s world. A possible way to reach this goal is through end-to-end (E2E) testing, an approach in which a web application is automatically tested by performing the actions that a user would do. With modern web applications (for example, single-page applications), it is of great importance to properly handle asynchronous calls in the test suite. In E2E Selenium WebDriver test suites, asynchronous calls are usually managed in two ways: using thread sleeps or explicit waits. The first is easier to use, but is inefficient and can lead to instability (also called flakiness, a problem often present in test suites that makes us lose confidence in the testing phase), while the second is usually more efficient but harder to use because, if the correct kind of wait is not carefully selected, it can introduce flakiness too. To help Testers, who often opt for the first strategy, we present in this work a tool-based approach to automatically replace thread sleeps with explicit waits in an E2E Selenium WebDriver test suite without introducing new flakiness. We empirically validated our tool named SleepReplacer on four different test suites, and we found that it can correctly replace in an automatic way from 81 to 100% of thread sleeps, leading to a significant reduction of the total execution time of the test suite (i.e., from 13 to 71%).
miR-22 alleviates sepsis-induced acute kidney injury via targeting the HMGB1/TLR4/NF-κB signaling pathway
Authors: Zhang Jie , Chen Qi , Dai Zhuquan , Pan Huibin 
Published: August 2022

Abstract
Background
Acute kidney injury (AKI) is a severe complication of sepsis, and is strongly correlated with MicroRNAs (miRNAs). However, the mechanism of miR-22 on sepsis-induced AKI is not clearly understood. The study aimed to explore the role and mechanism of miR-22 on AKI.

Methods
The AKI models were established by cecal ligation and puncture (CLP) surgery in SD rats and lipopolysaccharide (LPS) induction in HBZY-1 cells. In AKI rats, the content of serum creatinine (SCr) and blood urea nitrogen (BUN) were detected. Kidney tissues were pathologically examined by H&E and PAS staining. The LPS-induced HBZY-1 cells were transfected with mimics miR-22, si-HMGB1, or oe-HMGB1. miR-22 and HMGB1 expression was detected in vivo and in vitro. In transfected cells, HMGB1/TLR4/NF-κB pathway-related protein expressions were measured by Western blot. The relationship between miR-22 and HMGB1 was assessed by a dual-luciferase gene report. Inflammatory cytokine levels in serum and cells were assessed by ELISA.

Results
In AKI rats, kidney injury was observed, accompanied by the down-regulated miR-122 expression and up-regulated HMBG1 expression. The dual-luciferase report found miR-22-3p could targetly regulate HMBG1. Furthermore, both in vitro and in vivo experiments revealed that the releases of inflammatory cytokine were increased after AKI modeling, but the situation was reversed by mimics miR-22 or si-HMGB1 in vitro. In HBZY-1 cells, mimics miR-22 could suppress LPS-induced overexpression of HMGB1/TLR4/NF-κB signaling pathway-related proteins. However, the oe-HMGB1 addition reversed the effect of mimics miR-22.

Conclusion
miR-22 can inhibit the inflammatory response, target the HMGB1, and inhibit the HMGB1/TLR4/NF-kB pathway, to attenuate the sepsis-induced AKI, which indicates that miR-22 may serve as a potential treatment target in sepsis-induced AKI.
Information-Theoretic Odometry Learning
Authors: Zhang Sen , Zhang Jing , Tao Dacheng 
Published: August 2022

AbstractIn this paper, we propose a unified information theoretic framework for learning-motivated methods aimed at odometry estimation, a crucial component of many robotics and vision tasks such as navigation and virtual reality where relative camera poses are required in real time. We formulate this problem as optimizing a variational information bottleneck objective function, which eliminates pose-irrelevant information from the latent representation. The proposed framework provides an elegant tool for performance evaluation and understanding in information-theoretic language. Specifically, we bound the generalization errors of the deep information bottleneck framework and the predictability of the latent representation. These provide not only a performance guarantee but also practical guidance for model design, sample collection, and sensor selection. Furthermore, the stochastic latent representation provides a natural uncertainty measure without the needs for extra structures or computations. Experiments on two well-known odometry datasets demonstrate the effectiveness of our method.
Improving medical experts’ efficiency of misinformation detection: an exploratory study
Authors: Nabożny Aleksandra , Balcerzak Bartłomiej , Morzy Mikołaj , Wierzbicki Adam , Savov Pavel , Warpechowski Kamil 
Published: August 2022

AbstractFighting medical disinformation in the era of the pandemic is an increasingly important problem. Today, automatic systems for assessing the credibility of medical information do not offer sufficient precision, so human supervision and the involvement of medical expert annotators are required. Our work aims to optimize the utilization of medical experts’ time. We also equip them with tools for semi-automatic initial verification of the credibility of the annotated content. We introduce a general framework for filtering medical statements that do not require manual evaluation by medical experts, thus focusing annotation efforts on non-credible medical statements. Our framework is based on the construction of filtering classifiers adapted to narrow thematic categories. This allows medical experts to fact-check and identify over two times more non-credible medical statements in a given time interval without applying any changes to the annotation flow. We verify our results across a broad spectrum of medical topic areas. We perform quantitative, as well as exploratory analysis on our output data. We also point out how those filtering classifiers can be modified to provide experts with different types of feedback without any loss of performance.
RETRACTED ARTICLE: Cognitively stimulating maternal language as predictor for vocabulary growth
Authors: Möwisch Dave , Konrad-Ristau Kira , Weinert Sabine 
Published: August 2022

AbstractMaternal interaction behavior, particularly maternal language input, is considered to be one of the key factors for child vocabulary development. Previous studies have shown that a higher quantity and diversity of maternal language input is associated with faster vocabulary development. In the present study, we examined cognitive-verbal stimulation as a specific aspect of maternal input, controlling for other relevant internal child characteristics and external environmental influences. Additionally, we compared the effects of cognitive stimulation on vocabulary development with a standard measurement of maternal language input, such as its quantity, to identify specific the effects of cognitive-verbally stimulating interaction behavior. We used data from the Newborn Cohort Study of the German National Educational Panel Study (N = 1127 families) and conducted latent growth curve modeling to examine the vocabulary growth of children between 3 and 7 years of age. As control variables, we also included maternal education and household income in the analyses as well as the children’s age, gender, and initial vocabulary level when they were 2 years old, their phonological working memory, and whether they were learning another native language other than German. The results indicated that general aspects of maternal input, such as the quantity and length of the utterances of maternal language input for 2‑years-olds, were relevant in the earlier stages of vocabulary development, while cognitive stimulation was an important predictor of growth across the later stages of vocabulary development in 3‑ to 7‑year-olds.
Evaluation of the obturator foramen as a sex assessment trait
Authors: Rennie Samuel R. , Eliopoulos Constantine , Gonzalez Silvia 
Published: August 2022

AbstractCorrectly assessing sex from skeletal remains is one of the main elements of creating a biological profile. Many traits allow for this, the obturator foramen being one. However, research on its accuracy has provided mixed results. This study examines the obturator foramen using a 5-point grading scale to assess the degree of sexual dimorphism in four known age and sex skeletal collections from the UK and South Africa. Overall, sexual dimorphism was found in the obturator foramen when using the new scoring system; however, accuracies for correct sex classification ranged from ~ 46 to ~ 75%. Considering its wide range in accuracy rates across the four samples and difficulty in identifying the subtle changes in morphology, the obturator foramen should only be used as part of a multifactorial assessment of sex.
Low-energy ion channeling in nanocubes
Authors: Choupanian Shiva , Möller Wolfhard , Seyring Martin , Ronning Carsten 
Published: August 2022

AbstractFocused ion beam (FIB) processing with low-energy ions has become a standard technique for the manipulation of nanostructures. Many underlying ion beam effects that deviate from conventional high-energy ion irradiation of bulk systems are considered today; however, ion channeling with its consequence of significant deeper penetration depth has been only theoretically investigated in this regime. We present here an experimental approach to determine the channeling of low-energy ions in crystalline nanoparticles by measuring the sputter yield derived from scanning electron microscopy (SEM) images taken after irradiation under various incident ion angles. Channeling maps of 30 and 20 keV Ga+ ions in Ag nanocubes have been identified and fit well with the theory. Indeed, channeling has a significant impact on the transport of energetic ions in crystals due to the large critical angle at low ion energies, thus being relevant for any FIB-application. Consequently, the obtained sputter yield clearly differs from amorphous materials; therefore, it is recommended not to rely only on, e.g., ion distribution depths predicted by standard Monte-Carlo (MC) algorithms for amorphous materials.
PTEN-induced kinase 1 enhances the reparative effects of bone marrow mesenchymal stromal cells on mice with renal ischaemia/reperfusion-induced acute kidney injury
Authors: Lin Chenyu , Chen Wen , Han Yong , Sun Yujie , Zhao Xiaoqiong , Yue Yuan , Li Binyu , Fan Wenmei , Zhang Tao , Xiao Li 
Published: August 2022

AbstractAcute kidney injury (AKI) is a common severe acute syndrome caused by multiple factors and is characterized by a rapid decline in renal function during a short period. Bone marrow mesenchymal stromal cells (BMSCs) are effective in treating AKI. However, the mechanism of their beneficial effects remains unclear. PTEN-induced kinase 1 (PINK1) may play an important role in kidney tissue repair. In this study, we explored the effect of PINK1 overexpression on enhancing BMSC-mediated repair of AKI. In this study, ischaemia/reperfusion-induced AKI (IRI-AKI) in mice and a hypoxia-reoxygenation model in cells were established, and the indices were examined by pathology and immunology experiments. After ischaemia/reperfusion, PINK1 overexpression reduced apoptosis in injured kidney tissue cell, decreased T lymphocyte infiltration, increased macrophage infiltration, and alleviated the inflammatory response. PINK1 relieved the stress response of BMSCs and renal tubular epithelial cells (RTECs), reduced apoptosis, altered the release of inflammatory factors, and reduced the proliferation of peripheral blood mononuclear cells (PBMCs). In conclusion, BMSCs and RTECs undergo stress responses in response to hypoxia, inflammation and other conditions, and overexpressing PINK1 in BMSCs could enhance their ability to resist these stress reactions. Furthermore, PINK1 overexpression can regulate the distribution of immune cells and improve the inflammatory response. The regulation of mitochondrial autophagy during IRI-AKI maintains mitochondrial homeostasis and protects renal function. The results of this study provide new strategies and experimental evidence for BMSC-mediated repair of IRI-AKI.
Eine kurze kulturpsychologische Anleitung für zukünftige Freunde
Authors: von Fircks Enno 
Published: August 2022

ZusammenfassungLiebe zukünftige Freunde, dies ist ein Beitrag für euch. Er dient euch dazu, die Grundlagen von Kulturpsychologie zu verstehen und anzuwenden. Lange habe ich gebraucht, bis ich mir jene Grundlagen angeeignet habe. Nach intensivem Studieren von Standardwerken, der Teilnahme an kulturpsychologischen Seminaren und dem Vorantreiben kleinerer Forschungsprojekte fühle ich mich ermutigt, euch euren Einstieg in die Kulturpsychologie zu erleichtern. Hierbei definiere ich den Kulturbegriff: Kultur ist im Sinn Boeschs ein Handlungsfeld, das anhand von Zielen und Bedürfnissen strukturiert wird. Diese Ziele und Bedürfnisse sind natürlich einem ständigen Wandel durch die Person und durch die Umgebung unterworfen, sodass wir Kultur als etwas inhärent Dynamisches definieren müssen. Somit aktualisieren sich Handlungsfelder entweder durch Aufforderungscharaktere der Person oder der Umgebung. Sprache – so stellen wir später fest – ist dabei das Tor zum Verständnis verschiedenartiger Handlungsfelder, anhand derer wir auch den symbolischen Charakter unserer Umwelt dechiffrieren können. Und natürlich entwickelt sich jede Kultur in einem Prozess, d. h. sie zeigt genetische Elemente, die wir verstehen wollen. Hierbei zeige ich drei methodische Zugänge auf: Trajectory Equifinality Model (TEM), ambivalente Stimuli und Ethnographie, die ich anschaulich präsentiere und mit Beispielen versehe, um jene kulturpsychologischen Prozesse zu verstehen und nachzuzeichnen. Ich beende meine Anleitung mit einem Appell an euch, meine Freunde. Eignet euch die Kulturpsychologie in eurem Sinn, für eure Ziele und Bedürfnisse an und geht euren Weg. Tretet dann in Interaktion mit uns, die wir schon vermeintlich länger dabei sind, und erfrischt uns mit neuen Perspektiven. Bis dahin soll euch diese Anleitung euren Eintritt erleichtern.
-adic images of Galois for elliptic curves over (and an appendix with John Voight)
Authors: Rouse Jeremy , Sutherland Andrew V. , Zureick-Brown David 
Published: August 2022

AbstractWe discuss the$\ell $-adic case of Mazur’s ‘Program B’ over$\mathbb {Q}$: the problem of classifying the possible images of$\ell $-adic Galois representations attached to elliptic curvesEover$\mathbb {Q}$, equivalently, classifying the rational points on the corresponding modular curves. The primes$\ell =2$and$\ell \ge 13$are addressed by prior work, so we focus on the remaining primes$\ell = 3, 5, 7, 11$. For each of these$\ell $, we compute the directed graph of arithmetically maximal$\ell $-power level modular curves$X_H$, compute explicit equations for all but three of them and classify the rational points on all of them except$X_{\mathrm {ns}}^{+}(N)$, for$N = 27, 25, 49, 121$and two-level$49$curves of genus$9$whose Jacobians have analytic rank$9$.Aside from the$\ell $-adic images that are known to arise for infinitely many${\overline {\mathbb {Q}}}$-isomorphism classes of elliptic curves$E/\mathbb {Q}$, we find only 22 exceptional images that arise for any prime$\ell $and any$E/\mathbb {Q}$without complex multiplication; these exceptional images are realised by 20 non-CM rationalj-invariants. We conjecture that this list of 22 exceptional images is complete and show that any counterexamples must arise from unexpected rational points on$X_{\mathrm {ns}}^+(\ell )$with$\ell \ge 19$, or one of the six modular curves noted above. This yields a very efficient algorithm to compute the$\ell $-adic images of Galois for any elliptic curve over$\mathbb {Q}$.In an appendix with John Voight, we generalise Ribet’s observation that simple abelian varieties attached to newforms on$\Gamma _1(N)$are of$\operatorname {GL}_2$-type; this extends Kolyvagin’s theorem that analytic rank zero implies algebraic rank zero to isogeny factors of the Jacobian of$X_H$.