bluuebunny/crossref_metadata_2025 huggingface dataset:
Entwurf und Tragwerksanalyse der Stahl‐ und Glaskuppel des Academy Museum of Motion Pictures
Authors: Meier Florian
Published: July 2021

Die 45 m weit spannende Gitterschale des Academy Museum of Motion Pictures in Los Angeles, entworfen von Renzo Piano Building Workshop (Genua) in Zusammenarbeit mit Knippers Helbig (Stuttgart, New York), ist das Herzstück des im Frühjahr 2021 fertiggestellten Filmmuseums. Die Konstruktion versteht sich einerseits geometrisch als Fortsetzung des kugelförmigen Neubaus aus Stahlbeton, setzt sich jedoch andererseits aufgrund der filigranen Stahlrundrohr‐ und Vollprofile, diagonalen Seilverspannung und schindelartigen Glaseindeckung als hochtransparenter, architektonischer Kontrast vom restlichen Baukörper ab. Die Kuppel überdacht die sogenannte „Dolby“‐Terrasse, ein Ort für besondere Ausstellungen und Veranstaltungen, und ist das Ergebnis einer komplexen Komposition vielfältiger tragender und nicht tragender Bauteile: Stahltragwerk, Beschattungssysteme, Belichtung, Elektrizitätsleitungen, Sprinklerrohre, Wartungszugänge. In der Ausarbeitung der zur Schau gestellten Funktionalität des Tragwerks, bei gleichzeitiger Bewahrung der visuellen Leichtigkeit, lag das Hauptaugenmerk des mehrjährigen Entwurfsprozesses in Zusammenarbeit mit den Architekten. Der vorliegende Aufsatz beschreibt wichtige Meilensteine im Entwurfs‐ und Berechnungsprozess, von strategischen Weichenstellungen in der grundlegenden Konzeption der Gitterschale bis zur Detaillierung des Stahl‐Leichtbaus.
Die Neue Nationalgalerie in Berlin
Authors: Hauke Bernhard
Published: July 2021

Die Neue Nationalgalerie in Berlin und insbesondere die Stahlkonstruktion der Eingangshalle zählt zu den bekanntesten Bauten der Moderne. Fertiggestellt 1968, wird sie im August 2021 nach der Sanierung wiedereröffnet. Die Neue Nationalgalerie zählt als eines der letzten Meisterwerke des Architekten Ludwig Mies van der Rohe. Hier wird jedoch die damalige Ingenieurleistung dahinter betrachtet, der Statiker Prof. Dr.‐Ing. H. Dienst und G. Richter aus Berlin, der Prüfingenieure Prof. Dr.‐Ing. Karlheinz Roik und Dipl.‐Ing. Gerhard Sedlacek – zu der Zeit beide TU Berlin – sowie die Arbeit der Stahlbauer wie H. Oeter und H. Sontag.
Movement Ecology of a Potamodromous Top Predator in a Large Lake: Synchrony and Coexistence of Distinct Migratory Patterns
Authors: Ivanova Silviya V. , Johnson Timothy B. , Fisk Aaron T.
Published: July 2021

Migrations are a critical component of the life histories of many highly mobile animals. Potamodromous migrations that occur within large lakes are poorly understood for most species. This lack of understanding hampers restoration efforts and adaptive management because the movement of species and underlying patterns and mechanisms help scientists identify important habitats and quantify species’ roles in the ecosystem. This study quantified the spatiotemporal movements and migratory patterns of Lake Trout Salvelinus namaycush, an iteroparous, potamodromous predator, in eastern Lake Ontario. The lake is highly managed and supports a diverse fish community of native and nonnative species. The movements of 41 Lake Trout were quantified over 2.4 years (December 2016 to April 2019) across a large array of 196 acoustic receivers in eastern Lake Ontario. An analysis of individual movements revealed a potential annual convergence occurring in the fall at a location other than the spawning grounds, followed by a synchronized migration to spawning areas. Consistent with divergent migrations, return migration was asynchronous among individuals but consistent in timing interannually, stretching over a longer period than did prespawning movements and across multiple routes. The data suggest the existence of three groups (i.e., contingents) of Lake Trout with distinct migratory behaviors. This study provides important information on the migratory patterns and routes and a potential staging area for a potamodromous top predator population in a large lake. This information can help managers understand the potential success and implications of employing different rehabilitation strategies, such as diversifying populations of Lake Trout through selective strain stocking in large deep lakes to aid reestablishment across habitats. In addition, our results have the potential to improve community dynamics modeling, understanding of nutrient cycling, and overall ecosystem function of large lakes.
Luteolin mitigates potassium dichromate‐induced nephrotoxicity, cardiotoxicity and genotoxicity through modulation of Kim‐1/Nrf2 signaling pathways
Authors: Awoyomi Omolola Victoria , Adeoye Yemisi Dorcas , Oyagbemi Ademola Adetokunbo , Ajibade Temitayo Olabisi , Asenuga Ebunoluwa Rachael , Gbadamosi Idayat Titilayo , Ogunpolu Blessing Seun , Falayi Olufunke Olubunmi , Hassan Fasilat Oluwakemi , Omobowale Temidayo Olutayo , Arojojoye Oluwatosin Adetola , Ola‐Davies Olufunke Eunice , Saba Adebowale Benard , Adedapo Adeolu Alex , Oguntibeju Oluwafemi Omoniyi , Yakubu Momoh Audu
Published: July 2021

Environmental and occupational exposure to chromium compounds has become potential aetiologic agent for kidney disease with excessive generation of free radicals, apoptosis, and inflammatory. These pathophysiologic mechanisms of potassium dichromate (K2Cr2O7) have been well correlated with nephrotoxicity and cardiotoxicity. The cardioprotective and nephroprotective effects of Luteolin, a known potent antioxidant were evaluated in this study with 40 healthy rats in four experimental groups: Group A (normal saline), Groups B (30 mg/kg K2Cr2O7), Group C (Luteolin 100 mg/kg and K2Cr2O7 30 mg/kg), and Group D (Luteolin 200 mg/kg and K2Cr2O7 30 mg/kg), respectively. Markers of antioxidant defense system, oxidative stress, blood pressure and micronucleated polychromatic erythrocytes (MnPEs), immunohistochemistry of Kidney, injury molecule (Kim‐1), nuclear factor erythroid 2‐related factor 2 (Nrf2), and cardiac troponin I were determined. Administration of K2Cr2O7 increased blood pressure parameters in systolic, diastolic and mean arterial blood pressures, markers of oxidative stress, and frequency of micronucleated polychromatic erythrocytes, together with reduction in serum nitric oxide level. Renal Kim‐1 and cardiac troponin I expressions were higher, but lower expressions of renal and cardiac Nrf2 were recorded with immunohistochemical analysis. Pre‐treatment with Luteolin restored blood pressure parameters, with concomitant reduction in oxidative stress indicators, augmented antioxidant mechanisms and serum Nitric oxide level, lowered the expressions of Kim‐1, cardiac troponin I and up‐regulated of both cardiac and renal Nrf2, reduced the frequency of micronucleated polychromatic erythrocytes. Taken together, this study therefore demonstrates the cardioprotective, nephro protective and antigenotoxic effects of Luteolin through antioxidantive and radical scavenging mechanisms.
Curcumin functions as an anti‐inflammatory and antioxidant agent on arsenic‐induced hepatic and kidney injury by inhibiting MAPKs/NF‐κB and activating Nrf2 pathways
Authors: Xu Guowei , Gu Yuqin , Yan Nan , Li Yongfang , Sun Lin , Li Bing
Published: July 2021

Chronic arsenic exposure has been associated with various toxic effects, especially to the organs of liver and kidney. As a plant polyphenol, curcumin is the most vital bioactive ingredient of turmeric and has a wide range of pharmacological activities. In the present study, we investigated the potential roles of curcumin against arsenic‐induced liver and kidney dysfunctions in mice. Curcumin treatment (200 mg/kg) not only decreased the deposition of arsenic in liver and kidney, but also relieved the hepatic and nephritic biochemical indexes (Glutamic oxaloacetic transaminase [AST], Alanine aminotransferase [ALT], albumin, and creatinine) altered by arsenic at doses of 10 and 25 mg/L via drinking water. What's more, curcumin exerted influences on the activities of myeloperoxidase and on the secretion of inflammatory cytokines in liver and kidney tissues. In addition, the levels of mitogen‐activated protein kinases (MAPKs) and nuclear factor kappa B (NF‐κB) phosphorylation were declining while NRF2‐signaling targets were increasing in mice liver and kidney by curcumin administration. In conclusion, our results here suggest that curcumin could exert both anti‐inflammatory and antioxidant functions on arsenic‐induced hepatic and kidney injury by inhibiting MAPKs/NF‐κB and activating Nrf2 pathways cooperatively.
Refining Literacy Pedagogy through Practitioner Inquiry Partnerships
Authors: Johnston Kelly C. , Harper Tracy
Published: July 2021

Practitioner inquiry partnerships offer a method of professional learning that positions teachers as experts and supports their culturally, linguistically, and racially diverse students through the cultivation of responsive pedagogical practices. This article builds on the research base around practitioner inquiry in literacy classrooms and contributes further understanding of what it looks like to partner with teachers to engage in inquiry as professional learning, how this process leads to refined literacy pedagogy and shifts toward student‐centered practices, and why it is humanizing to embrace expansive notions of literacy. By attuning to sociocultural and affective approaches to literacy, the authors discuss inquiry partnerships with two teachers and provide insight into how other teachers might also engage with practitioner inquiry to refine their literacy pedagogy. The authors argue the inquiry process supports shifts in literacy pedagogy that not only help teachers navigate constraints but also lead to centering students’ responses and engagement.
Concentration of 2,3 bisphosphoglycerate in cattle affected with acute ruminal acidosis
Authors: Moosa Dhiyaa A. , Al‐Obaidi Qaes T. , Mustafa Nashaat G. , Dahl Mohammad O.
Published: July 2021

The main objective of the study conducted here was to estimate the concentration of 2,3‐Bisphosphoglycerate (2,3‐BPG), 1,3‐Bisphosphoglycerate (1,3‐BPG), bisphospho‐glycerate mutase (BPGM) and 3‐phosphoglycerate (3PG) in cattle clinically diagnosed with acute ruminal acidosis. A secondary objective was to examine the physical and chemical characteristics of the ruminal fluid in affected cattle. A total of 20 cattle clinically diagnosed with acute ruminal acidosis and eight clinically normal cattle were included in this study. The results showed that decrease of ruminal pH changed the ruminal fluid colour, odour and consistency, as well as decreased the sedimentation time, increased the methylene blue reduction time, and decreased ruminal microflora motility. The study indicated that the concentration of 2,3‐BPG, BPGM and BPGP decreased with the decrease of ruminal pH, while 3‐PG concentration was not affected with the decrease of ruminal pH. In conclusion, 2,3‐BPG could play a role in the pathogenesis of ruminal acidosis, and thus, the intravenous administration of sodium bicarbonate is important, particularly in severe cases, to correct any systemic acidosis that can decrease 2,3‐BPG concentration and results in tissue hypoxia.
E-STEM in Everyday Life: How Families Develop a Caring Motive Orientation Towards the Environment
Authors: Almeida Sylvia Christine , Fleer Marilyn
Published: July 2021

Internationally there is growing interest in how young children engage with and learn concepts of science and sustainability in their everyday lives. These concepts are often built through nature and outdoor play in young children. Through the dialectical concept of everyday and scientific concept formation (Vygotsky LS, The collected works of L.S. Vygotsky. Problems of general psychology, V.1, (Trans. N Minick). Editor of English Translation, RW Rieber, and AS Carton, New York: Kluwer Academic and Plenum Publishers, 1987), this chapter presents a study of how families transformatively draw attention to STEM and sustainability concepts in the everyday practices of the home. The research followed a focus child (4–5 year old) from four families as they navigated everyday life and talked about the environments in which they live. Australia as a culturally diverse community was reflected in the families, whose heritage originated in Europe, Iran, India, Nepal and Taiwan. The study identified the multiple ways in which families introduce practices and conceptualise imagined futures and revisioning (Payne PG, J HAIA 12:2–12, 2005a). About looking after their environment. It was found that young children appear to develop concepts of STEM, but also build agency in exploration, with many of these explorations taking place in outdoor settings. We conceptualise this as a motive orientation to caring for the environment, named as E-STEM. The study emphasises for education to begin with identifying family practices and children’s explorations, as a key informant for building relevant and locally driven pedagogical practices to support environmental learning.
Toddlers’ Outdoor Play, Imagination and Cultural Formation
Authors: Ridgway Avis , Quiñones Gloria , Li Liang
Published: July 2021

Discussion on toddlers’ outdoor play practices in various cultural spaces is rare in literature. In Australia, toddlers’ physical development and well-being is promoted but less attention is given to cultural nuances of outdoor play. We ask the question: How does outdoor play impact on toddlers’ imagination and cultural formation? Conducted in three Australian long day care (LDC) sites, an ethically approved project “Studying babies and toddlers: Cultural worlds and transitory relationships” examines the process of three Australian toddlers’ outdoor enculturation. The concepts of imagination and play from Vygotsky’s cultural-historical theory are drawn upon in relation to Hedegaard’s institutional practices model, to link contextual relations between society, community and family. Cultural formation processes in toddlers’ outdoor play, we argue, are more completely understood when daily life across home and local community is acknowledged. Data findings illustrate complexity of movement and experimentations in cultural conditions, where different spaces hold possibilities for imaginative transformations in toddler’s play. Implications suggest toddlers’ imaginative and culturally responsive outdoor play aligns with availability of interested adult/peers, shared family and community values, and varied local spaces. In this way, affective and dynamic outdoor interactions imbue cultural formation of toddler’s play and imagination with local personal meaning.
Verisig 2.0: Verification of Neural Network Controllers Using Taylor Model Preconditioning
Authors: Ivanov Radoslav , Carpenter Taylor , Weimer James , Alur Rajeev , Pappas George , Lee Insup
Published: July 2021

This paper presents Verisig 2.0, a verification tool for closed-loop systems with neural network (NN) controllers. We focus on NNs with tanh/sigmoid activations and develop a Taylor-model-based reachability algorithm through Taylor model preconditioning and shrink wrapping. Furthermore, we provide a parallelized implementation that allows Verisig 2.0 to efficiently handle larger NNs than existing tools can. We provide an extensive evaluation over 10 benchmarks and compare Verisig 2.0 against three state-of-the-art verification tools. We show that Verisig 2.0 is both more accurate and faster, achieving speed-ups of up to 21x and 268x against different tools, respectively.
Robustness Verification of Semantic Segmentation Neural Networks Using Relaxed Reachability
Authors: Tran Hoang-Dung , Pal Neelanjana , Musau Patrick , Lopez Diego Manzanas , Hamilton Nathaniel , Yang Xiaodong , Bak Stanley , Johnson Taylor T.
Published: July 2021

This paper introduces robustness verification for semantic segmentation neural networks (in short, semantic segmentation networks [SSNs]), building on and extending recent approaches for robustness verification of image classification neural networks. Despite recent progress in developing verification methods for specifications such as local adversarial robustness in deep neural networks (DNNs) in terms of scalability, precision, and applicability to different network architectures, layers, and activation functions, robustness verification of semantic segmentation has not yet been considered. We address this limitation by developing and applying new robustness analysis methods for several segmentation neural network architectures, specifically by addressing reachability analysis of up-sampling layers, such as transposed convolution and dilated convolution. We consider several definitions of robustness for segmentation, such as the percentage of pixels in the output that can be proven robust under different adversarial perturbations, and a robust variant of intersection-over-union (IoU), the typical performance evaluation measure for segmentation tasks. Our approach is based on a new relaxed reachability method, allowing users to select the percentage of a number of linear programming problems (LPs) to solve when constructing the reachable set, through a relaxation factor percentage. The approach is implemented within NNV, then applied and evaluated on segmentation datasets, such as a multi-digit variant of MNIST known as M2NIST. Thorough experiments show that by using transposed convolution for up-sampling and average-pooling for down-sampling, combined with minimizing the number of ReLU layers in the SSNs, we can obtain SSNs with not only high accuracy (IoU), but also that are more robust to adversarial attacks and amenable to verification. Additionally, using our new relaxed reachability method, we can significantly reduce the verification time for neural networks whose ReLU layers dominate the total analysis time, even in classification tasks.
Computing Bottom SCCs Symbolically Using Transition Guided Reduction
Authors: Beneš Nikola , Brim Luboš , Pastva Samuel , Šafránek David
Published: July 2021

Detection of bottom strongly connected components (BSCC) in state-transition graphs is an important problem with many applications, such as detecting recurrent states in Markov chains or attractors in dynamical systems. However, these graphs’ size is often entirely out of reach for algorithms using explicit state-space exploration, necessitating alternative approaches such as the symbolic one.

Symbolic methods for BSCC detection often show impressive performance, but can sometimes take a long time to converge in large graphs. In this paper, we provide a symbolic state-space reduction method for labelled transition systems, calledinterleaved transition guided reduction(ITGR), which aims to alleviate current problems of BSCC detection by efficiently identifying large portions of the non-BSCC states.

We evaluate the suggested heuristic on an extensive collection of 125 real-world biologically motivated systems. We show that ITGR can easily handle all these models while being either the only method to finish, or providing at least an order-of-magnitude speedup over existing state-of-the-art methods. We then use a set of synthetic benchmarks to demonstrate that the technique also consistently scales to graphs with more than$$2^{1000}$$21000vertices, which was not possible using previous methods.
Synthesis with Asymptotic Resource Bounds
Authors: Hu Qinheping , Cyphert John , D’Antoni Loris , Reps Thomas
Published: July 2021

We present a method for synthesizing recursive functions that satisfy both a functional specification and an asymptotic resource bound. Prior methods for synthesis with a resource metric require the user to specify aconcreteexpression exactly describing resource usage, whereas our method uses big-Onotation to specify theasymptoticresource usage. Our method can synthesize programs with complex resource bounds, such as a sort function that has complexity$$O(n\log (n))$$O(nlog(n)).

Our synthesis procedure uses a type system that is able to assign an asymptotic complexity to terms, and can track recurrence relations of functions. These typing rules are justified by theorems used in analysis of algorithms, such as the Master Theorem and the Akra-Bazzi method. We implemented our method as an extension of prior type-based synthesis work. Our tool,SynPlexity, was able to synthesize complex divide-and-conquer programs that cannot be synthesized by prior solvers.
DNNV: A Framework for Deep Neural Network Verification
Authors: Shriver David , Elbaum Sebastian , Dwyer Matthew B.
Published: July 2021

Despite the large number of sophisticated deep neural network (DNN) verification algorithms, DNN verifier developers, users, and researchers still face several challenges. First, verifier developers must contend with the rapidly changing DNN field to support new DNN operations and property types. Second, verifier users have the burden of selecting a verifier input format to specify their problem. Due to the many input formats, this decision can greatly restrict the verifiers that a user may run. Finally, researchers face difficulties in re-using benchmarks to evaluate and compare verifiers, due to the large number of input formats required to run different verifiers. Existing benchmarks are rarely in formats supported by verifiers other than the one for which the benchmark was introduced. In this work we present DNNV, a framework for reducing the burden on DNN verifier researchers, developers, and users. DNNV standardizes input and output formats, includes a simple yet expressive DSL for specifying DNN properties, and provides powerful simplification and reduction operations to facilitate the application, development, and comparison of DNN verifiers. We show how DNNV increases the support of verifiers for existing benchmarks from 30% to 74%.
BDD4BNN: A BDD-Based Quantitative Analysis Framework for Binarized Neural Networks
Authors: Zhang Yedi , Zhao Zhe , Chen Guangke , Song Fu , Chen Taolue
Published: July 2021

Verifying and explaining the behavior of neural networks is becoming increasingly important, especially when they are deployed in safety-critical applications. In this paper, we study verification and interpretability problems for Binarized Neural Networks (BNNs), the 1-bit quantization of general real-numbered neural networks. Our approach is to encode BNNs into Binary Decision Diagrams (BDDs), which is done by exploiting the internal structure of the BNNs. In particular, we translate the input-output relation of blocks in BNNs to cardinality constraints which are in turn encoded by BDDs. Based on the encoding, we develop a quantitative framework for BNNs where precise and comprehensive analysis of BNNs can be performed. We demonstrate the application of our framework by providing quantitative robustness analysis and interpretability for BNNs. We implement a prototype tool and carry out extensive experiments, confirming the effectiveness and efficiency of our approach.
Brain-Inspired Algorithms for Processing of Visual Data
Authors: Strisciuglio Nicola , Petkov Nicolai
Published: July 2021

The study of the visual system of the brain has attracted the attention and interest of many neuro-scientists, that derived computational models of some types of neuron that compose it. These findings inspired researchers in image processing and computer vision to deploy such models to solve problems of visual data processing.

In this paper, we review approaches for image processing and computer vision, the design of which is based on neuro-scientific findings about the functions of some neurons in the visual cortex. Furthermore, we analyze the connection between the hierarchical organization of the visual system of the brain and the structure of Convolutional Networks (ConvNets). We pay particular attention to the mechanisms of inhibition of the responses of some neurons, which provide the visual system with improved stability to changing input stimuli, and discuss their implementation in image processing operators and in ConvNets.
Einleitung
Authors: Kalisch Markus , Meier Lukas
Published: July 2021

In der Einführung wird anhand von Beispielen und den damit verbundenen Fragestellungen motiviert, wieso und wann man ein logistisches Regressionsmodell verwenden kann und wieso das lineare Regressionsmodell dazu nicht geeignet ist.
Das logistische Regressionsmodell
Authors: Kalisch Markus , Meier Lukas
Published: July 2021

Das lineare Regressionsmodell wird zu Kapitelbeginn als zweistufiges Modell neu interpretiert. Darauf aufbauend wird das logistische Regressionsmodell äquivalent als Modell für binäre Zielgrößen eingeführt. Dabei wird gezeigt, dass die logistische Regression ein Spezialfall der verallgemeinerten linearen Modelle (GLM) ist. Als wichtige Komponenten solcher Modelle werden Verteilung, Erwartungswert, linearer Prädiktor und Linkfunktion besprochen. Als Alternative zu dieser Herangehensweise wird die logistische Regression als latentes Variablenmodell vorgestellt. Anschließend wird die Interpretation der Modellparameter auf der Skala der Log-Odds, Odds und Wahrscheinlichkeit ausführlich besprochen. Den Abschluss bildet ein kurzer Ausblick auf Modelle mit mehreren Variablen und Methoden der Parameterschätzung bzw. Inferenz.
Ausblick
Authors: Kalisch Markus , Meier Lukas
Published: July 2021

Im Ausblick geht es um die Überprüfung der Modellannahmen und häufige Probleme der logistischen Regression. Zusätzlich wird darauf eingegangen, wie die logistische Regression auf mehr als zwei Klassen erweitert werden kann.
Supersymmetry, T-duality and heterotic α′-corrections
Authors: Lescano Eric , Núñez Carmen A. , Rodríguez Jesús A.
Published: July 2021

Abstract

Higher-derivative interactions and transformation rules of the fields in the effective field theories of the massless string states are strongly constrained by space-time symmetries and dualities. Here we use an exact formulation of ten dimensional $$ \mathcal{N} $$
N
= 1 supergravity coupled to Yang-Mills with manifest T-duality symmetry to construct the first order α′-corrections of the heterotic string effective action. The theory contains a supersymmetric and T-duality covariant generalization of the Green-Schwarz mechanism that determines the modifications to the leading order supersymmetry transformation rules of the fields. We compute the resulting field-dependent deformations of the coefficients in the supersymmetry algebra and construct the invariant action, with up to and including four-derivative terms of all the massless bosonic and fermionic fields of the heterotic string spectrum.
Estimation of conditional distribution functions from data with additional errors applied to shape optimization
Authors: Hansmann Matthias , Horn Benjamin M. , Kohler Michael , Ulbrich Stefan
Published: July 2021

We study the problem of estimating conditional distribution functions from data containing additional errors. The only assumption on these errors is that a weighted sum of the absolute errors tends to zero with probability one for sample size tending to infinity. We prove sufficient conditions on the weights (e.g. fulfilled by kernel weights) of a local averaging estimate of the codf, based on data with errors, which ensure strong pointwise consistency. We show that two of the three sufficient conditions on the weights and a weaker version of the third one are also necessary for the spc. We also give sufficient conditions on the weights, which ensure a certain rate of convergence. As an application we estimate the codf of the number of cycles until failure based on data from experimental fatigue tests and use it as objective function in a shape optimization of a component.
Exploring the potential of cranial non-metric traits as a tool for personal identification: the never-ending dilemma
Authors: Palamenghi Andrea , Borlando Alessia , De Angelis Danilo , Sforza Chiarella , Cattaneo Cristina , Gibelli Daniele
Published: July 2021

Forensic anthropologists tasked with identification of skeletal remains often have to set up new strategies to overcome the limitations of conventional individualizing markers. A sound acquaintance with non-metric traits is essential for a reliable distinction between normal variations and pathological or traumatic conditions, yet the role of cranial variants in the identification process is still somehow ill-defined. One hundred crania (50 males and 50 females) of known sex and age were selected from the Collezione Antropologica LABANOF (a documented contemporary skeletal collection) and non-metric traits were scored as present or absent and by side. The frequencies of 13 traits were used to calculate the compound probabilities to find an individual with an exact combination of cranial features in the worldwide population. The probabilities of the majority of the individuals (53%) are within the 1 out of 10 million–1 out of 1 million interval. However, a fair number of subjects (25%) of the sample have the probabilities falling into the 1 out of 1 billion–1 out of 100 million interval, while the probabilities of a small portion of the sample (10%) are less than 1 out of 1 billion. This pilot study illustrates that some combinations of cranial variants are quite rare and may represent potential evidence to discern presumptive identifications, when an appropriate set of traits is selected and antemortem data are available for comparison. However, further research on larger and various samples is needed to confirm or discard the use of combinations of cranial non-metric traits as individualizing markers.
Risk of intracranial haemorrhage and ischaemic stroke after convexity subarachnoid haemorrhage in cerebral amyloid angiopathy: international individual patient data pooled analysis
Authors: Hostettler Isabel Charlotte , Wilson Duncan , Fiebelkorn Catherine Arnold , Aum Diane , Ameriso Sebastián Francisco , Eberbach Federico , Beitzke Markus , Kleinig Timothy , Phan Thanh , Marchina Sarah , Schneckenburger Romain , Carmona-Iragui Maria , Charidimou Andreas , Mourand Isabelle , Parreira Sara , Ambler Gareth , Jäger Hans Rolf , Singhal Shaloo , Ly John , Ma Henry , Touzé Emmanuel , Geraldes Ruth , Fonseca Ana Catarina , Melo Teresa , Labauge Pierre , Lefèvre Pierre-Henry , Viswanathan Anand , Greenberg Steven Mark , Fortea Juan , Apoil Marion , Boulanger Marion , Viader Fausto , Kumar Sandeep , Srikanth Velandai , Khurram Ashan , Fazekas Franz , Bruno Veronica , Zipfel Gregory Joseph , Refai Daniel , Rabinstein Alejandro , Graff-Radford Jonathan , Werring David John
Published: July 2021

Objective

To investigate the frequency, time-course and predictors of intracerebral haemorrhage (ICH), recurrent convexity subarachnoid haemorrhage (cSAH), and ischemic stroke after cSAH associated with cerebral amyloid angiopathy (CAA).

Methods

We performed a systematic review and international individual patient-data pooled analysis in patients with cSAH associated with probable or possible CAA diagnosed on baseline MRI using the modified Boston criteria. We used Cox proportional hazards models with a frailty term to account for between-cohort differences.

Results

We included 190 patients (mean age 74.5 years; 45.3% female) from 13 centers with 385 patient-years of follow-up (median 1.4 years). The risks of each outcome (per patient-year) were: ICH 13.2% (95% CI 9.9–17.4); recurrent cSAH 11.1% (95% CI 7.9–15.2); combined ICH, cSAH, or both 21.4% (95% CI 16.7–26.9), ischemic stroke 5.1% (95% CI 3.1–8) and death 8.3% (95% CI 5.6–11.8). In multivariable models, there is evidence that patients with probable CAA (compared to possible CAA) had a higher risk of ICH (HR 8.45, 95% CI 1.13–75.5, p = 0.02) and cSAH (HR 3.66, 95% CI 0.84–15.9, p = 0.08) but not ischemic stroke (HR 0.56, 95% CI 0.17–1.82, p = 0.33) or mortality (HR 0.54, 95% CI 0.16–1.78, p = 0.31).

Conclusions

Patients with cSAH associated with probable or possible CAA have high risk of future ICH and recurrent cSAH. Convexity SAH associated with probable (vs possible) CAA is associated with increased risk of ICH, and cSAH but not ischemic stroke. Our data provide precise risk estimates for key vascular events after cSAH associated with CAA which can inform management decisions.
Influence of Annealing Treatments on Welded CuNi Sheets on the Corrosion Behaviour in Sea Water
Authors: Biezma Maria Victoria , Linhardt Paul , Strobl Susanne , Haubner Roland
Published: July 2021

Due to their good corrosion resistance in seawater, tubes, rods, and forgings made from copper-nickel alloys (Cu-Ni) are widely used in ship building, offshore platforms, desalination plants, and numerous other applications. Welding is a major technology for joining this material. Since the microstructures of base material, weld seam, and heat affected zone may be quite different, the consequences with respect to corrosion must be considered. In this study the influence of microstructure on corrosion behaviour was investigated using welded test coupons of CuNi10Fe1.6 Mn, as-welded and after heat-treatment, by metallographic examination and electrochemical corrosion tests in synthetic seawater.
Stable films of zinc-hexacyanoferrate: electrochemistry and ion insertion capabilities
Authors: Sciacca Rosalinda , Zamponi Silvia , Berrettoni Mario , Giorgetti Marco
Published: July 2021

A stable film of zinc hexacyanoferrate is deposited on a GC (glassy carbon) substrate following a specific electrochemical protocol. The electrode maintains its characteristic even after dry and wet processes. SEM characterization confirms the cubic morphology of the materials and the IR suggests the presence of the FeII-C-N-ZnII structural unit. The electrochemical characterization indicates a very good stability of the film, thus opening application in ion exchange system. The focus is on monovalent, divalent, and trivalent ions. These results, the zinc low toxicity, and cost make zinc hexacyanoferrate films a promising candidate for many electrochemical applications.
Formal testing of timed graph transformation systems using metric temporal graph logic
Authors: Schneider Sven , Maximova Maria , Sakizloglou Lucas , Giese Holger
Published: July 2021

Embedded real-time systems generate state sequences where time elapses between state changes. Ensuring that such systems adhere to a provided specification of admissible or desired behavior is essential. Formal model-based testing is often a suitable cost-effective approach. We introduce an extended version of the formalism of symbolic graphs, which encompasses types as well as attributes, for representing states of dynamic systems. Relying on this extension of symbolic graphs, we present a novel formalism of timed graph transformation systems (TGTSs) that supports the model-based development of dynamic real-time systems at an abstract level where possible state changes and delays are specified by graph transformation rules. We then introduce an extended form of the metric temporal graph logic (MTGL) with increased expressiveness to improve the applicability of MTGL for the specification of timed graph sequences generated by a TGTS. Based on the metric temporal operators of MTGL and its built-in graph binding mechanics, we express properties on the structure and attributes of graphs as well as on the occurrence of graphs over time that are related by their inner structure. We provide formal support for checking whether a single generated timed graph sequence adheres to a provided MTGL specification. Relying on this logical foundation, we develop a testing framework for TGTSs that are specified using MTGL. Lastly, we apply this testing framework to a running example by using our prototypical implementation in the tool AutoGraph.
Experimental evaluation of kaolin stabilised with class F fly ash
Authors: Tamang Pratistha , Sriskantharajah Arathany , Ferreira Pedro , Lopez-Querol Susana
Published: July 2021

This study aims to investigate the effectiveness of fly ash (FA) in stabilising a kaolin soil through laboratory tests. Kaolin is an example of moderate plasticity clays that require stabilisation methods for construction purposes. The influence of FA on the improvement of kaolin is studied by varying its dosages in the mixtures (0%, 10% to 20%) as well as the cement content, used as an activator in different percentages (5 and 7%). The influence of the dry unit weight and the curing time of the soil mixture is also analysed through unconfined compressive strength and indirect tensile strength tests. The experimental results show that the strength increases linearly with both FA and cement contents. Moreover, higher initial dry unit weights also yield higher final strengths. To further assess the improvement, the application of the porosity over the volumetric cement content ratio, as the main variable, succeeded in attaining a relationship with the strength and the stiffness of the studied soil. Results for the combined effect of the porosity and the volumetric cement on the secant modulus were also determined. Furthermore, a unique relationship was obtained combining porosity, volumetric cement and FA content.
Raptors, racing pigeons and perceptions of attacks
Authors: Kettel Esther F. , Yarnell Richard W. , Quinn John L. , Gentle Louise K.
Published: July 2021

Raptors are often the cause of human-wildlife conflict because they may predate economically valuable species, and it is the perceived extent of predation that may augment conflict between raptors and people who keep and race pigeons. This study uses data obtained through questionnaires and an online raptor-attack reporting feature to investigate the frequency of racing pigeon losses and the perceptions of pigeon fanciers. Responses suggest that those who kept more pigeons and entered more races lost a higher proportion of pigeons. Losses were also influenced by the predatory species: sparrowhawks (Accipter nisus) were more likely to attack pigeons at lofts, whilst peregrines (Falco peregrinus) were more likely to attack pigeons during training, with patterns linked to the raptors’ breeding seasons. Pigeon fanciers were almost unanimous in their perception that raptors threaten the future of the hobby. Previous studies show that only a small proportion of racing pigeons are likely to be lost to raptors, yet pigeon fanciers believe that raptors are the main cause of losses, highlighting a possible mismatch between the perceived and actual causes of loss. This misconception may be a main source of this human-raptor conflict, so educating pigeon fanciers about the true impact of raptors could help to alleviate the issue. A shift in the beginning of the pigeon racing season by one month, and careful sighting of pigeon lofts in gardens, are also recommended in order to reduce raptor attacks.
Has Korean growth become greener? Spatial econometric evidence for energy use and renewable energy
Authors: Hille Erik , Lambernd Bernhard
Published: July 2021

Using province-level data for South Korea, we analyze the dynamic relationship between economic growth and several energy parameters. Specifically, we decompose the growth effect into scale, composition, and technique effects, and control for regional spillovers through the use of a dynamic GMM estimator for spatial panel data models. The analyzed period, ranging from 2000 to 2017, allows us to look for changes in the regional growth effects following the implementation of the National Strategy for Green Growth in 2009. Our estimates show that the scale and composition effect tended to increase both per capita final energy use and energy intensity, outweighing reductions through the technique effect. In contrast, when considering renewable energy production, the scale and technique effect increased and the composition effect decreased the corresponding figures. Thereby, the technique effect was the main driver of increases in renewable energy production. Despite the larger, yet comparatively small share of renewables in Korea’s energy mix, no considerable change of the growth effects can be observed since 2009. Therefore, to reduce the risks for the economy and achieve the political objectives of the green growth strategy throughout the whole country and in a timely manner, a stronger commitment seems to be required.
Relativistic positioning: including the influence of the gravitational action of the Sun and the Moon and the Earth’s oblateness on Galileo satellites
Authors: Colmenero Neus Puchades , Córdoba José Vicente Arnau , Fullana i Alfonso Màrius Josep
Published: July 2021

Uncertainties in the satellite world lines lead to dominant positioning errors. In the present work, using the approach presented in Puchades and Sáez (Astrophys. Space Sci. 352, 307–320, 2014), a new analysis of these errors is developed inside a great region surrounding Earth. This analysis is performed in the framework of the so-called Relativistic Positioning Systems (RPS). Schwarzschild metric is used to describe the satellite orbits corresponding to the Galileo Satellites Constellation. Those orbits are circular with the Earth as their centre. They are defined as the nominal orbits. The satellite orbits are not circular due to the perturbations they have and to achieve a more realistic description such perturbations need to be taken into account. In Puchades and Sáez (Astrophys. Space Sci. 352, 307–320, 2014) perturbations of the nominal orbits were statistically simulated. Using the formula from Coll et al. (Class. Quantum Gravity. 27, 065013, 2010) a user location is determined with the four satellites proper times that the user receives and with the satellite world lines. This formula can be used with any satellite description, although photons need to travel in a Minkowskian space-time. For our purposes, the computation of the photon geodesics in Minkowski space-time is sufficient as demonstrated in Puchades and Sáez (Adv. Space Res. 57, 499–508, 2016). The difference of the user position determined with the nominal and the perturbed satellite orbits is computed. This difference is defined as the U-error. Now we compute the perturbed orbits of the satellites considering a metric that takes into account the gravitational effects of the Earth, the Moon and the Sun and also the Earth oblateness. A study of the satellite orbits in this new metric is first introduced. Then we compute the U-errors comparing the positions given with the Schwarzschild metric and the metric introduced here. A Runge-Kutta method is used to solve the satellite geodesic equations. Some improvements in the computation of the U-errors using both metrics are introduced with respect to our previous works. Conclusions and perspectives are also presented.
Custody and Care of Children in Spain: Can the Two Rights be Reconciled?
Authors: Jabbaz Churba Marcela
Published: July 2021

This study aims to analyse the legal decision-making process in the Community of Valencia (Spain) regarding contentious divorces particularly with respect to parental authority (patria potestas), custody and visiting arrangements for children, and the opinions of mothers and fathers on the impact these judicial measures have had on their lives. It also considers the biases in these decisions produced by privileging the rights of the adults over those of the children. Three particular moments are studied: (1) the situation before the break-up, focusing on the invisible gender gap in care; (2) the judicial process, where we observe the impact of hidden gender-based violence and gender stereotypes; and (3) the situation post-decision, showing how any existing violence continues after divorce, by means of parental authority. The concept of ‘motherhood under threat’ is placed at the centre of these issues, where children’s voices are given the least attention.
University Virtual Learning in Covid Times
Authors: Marín-Díaz Verónica , Reche Eloísa , Martín Javier
Published: July 2021

Online training is demanded in the ubiquitous society we live in, and this is especially true if we consider the current situation at universities due to the Government issuing a state of alarm decree which requests all citizens to remain at home. The goal of this study is to determine the opinion of university students from different Spanish campuses on e-learning platforms, by the means of a descriptive and correlational study design, with N = 431. The results reveal that there is still a long road ahead to ensure that these tools work optimally to enable professors to fully exert their teaching profession. We can conclude that the online teaching system needs to be improved regarding the technical service that the university offers.
The Impact of COVID-19 Restrictions on Psychological Distress in Family Caregivers of Children with Neurodevelopmental Disability in the UK
Authors: Gillespie-Smith Karri , McConachie Doug , Ballantyne Carrie , Auyeung Bonnie , Goodall Karen
Published: July 2021

Caregivers of a child with a neurodevelopmental disability are more vulnerable to mental health difficulties. These difficulties are influenced by the child’s challenging behaviours, and the caregiver’s coping strategies; factors impacted by the COVID-19 pandemic. An online mixed methods survey was conducted on caregivers of children with neurodevelopmental disabilities (n = 43) and children who are typically developing (n = 67). The results showed that presence of challenging behaviours related to neurodevelopmental disability, and caregiver coping strategies predicted caregiver psychological distress during lockdown. Themes that emerged included ‘confusing messages and guidance’, ‘loss of freedom’ and ‘unsupported and forgotten’. The results demonstrate the pressing need for the implementation of appropriate support to protect the mental health of caregivers across the UK.
Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge
Authors: Lenselink Eelke B. , Stouten Pieter F. W.
Published: July 2021

Accurate prediction of lipophilicity—logP—based on molecular structures is a well-established field. Predictions of logP are often used to drive forward drug discovery projects. Driven by the SAMPL7 challenge, in this manuscript we describe the steps that were taken to construct a novel machine learning model that can predict and generalize well. This model is based on the recently described Directed-Message Passing Neural Networks (D-MPNNs). Further enhancements included: both the inclusion of additional datasets from ChEMBL (RMSE improvement of 0.03), and the addition of helper tasks (RMSE improvement of 0.04). To the best of our knowledge, the concept of adding predictions from other models (Simulations Plus logP and logD@pH7.4, respectively) as helper tasks is novel and could be applied in a broader context. The final model that we constructed and used to participate in the challenge ranked 2/17 ranked submissions with an RMSE of 0.66, and an MAE of 0.48 (submission: Chemprop). On other datasets the model also works well, especially retrospectively applied to the SAMPL6 challenge where it would have ranked number one out of all submissions (RMSE of 0.35). Despite the fact that our model works well, we conclude with suggestions that are expected to improve the model even further.