bluuebunny/crossref_metadata_2025 huggingface dataset:
Nondeterministic Strategies and their Refinement in Strategy Logic
Authors: De Giacomo Giuseppe , Maubert Bastien , Murano Aniello
Published: August 2020

Nondeterministic strategies are strategies (or protocols, or plans) that, given a history in a game, assign a set of possible actions, all of which are winning. An important problem is that of refining such strategies. For instance, given a nondeterministic strategy that allows only safe executions, refine it to, additionally, eventually reach a desired state of affairs. We show that strategic problems involving strategy refinement can be solved elegantly in the framework of Strategy Logic (SL), a very expressive logic to reason about strategic abilities. Specifically, we introduce an extension of SL with nondeterministic strategies and an operator expressing strategy refinement. We show that model checking this logic can be done at no additional computational cost with respect to standard SL, and can be used to solve a variety of problems such as synthesis of maximally permissive strategies or refinement of Nash equilibria.
Token-based Execution Semantics for Multi-Agent Epistemic Planning
Authors: Engesser Thorsten , Mattmüller Robert , Nebel Bernhard , Ritter Felicitas
Published: August 2020

Epistemic planning has been employed as a means to achieve implicit coordination in cooperative multi-agent systems where world knowledge is distributed between the agents, and agents plan and act individually. However, recent work has shown that even if all agents act with respect to plans that they consider optimal from their own subjective perspective, infinite executions can occur. In this paper, we analyze the idea of using a single token that can be passed around between the agents and which is used as a prerequisite for acting. We show that introducing such a token to any planning task will prevent the existence of infinite executions. We furthermore analyze the conditions under which solutions to a planning task are preserved under our tokenization.
Fixed-Parameter Tractability of Dependency QBF with Structural Parameters
Authors: Ganian Robert , Peitl Tomáš , Slivovsky Friedrich , Szeider Stefan
Published: August 2020

We study dependency quantified Boolean formulas (DQBF), an extension of QBF in which dependencies of existential variables are listed explicitly rather than being implicit in the order of quantifiers. DQBF evaluation is a canonical NEXPTIME-complete problem, a complexity class containing many prominent problems that arise in Knowledge Representation and Reasoning. One approach for solving such hard problems is to identify and exploit structural properties captured by numerical parameters such that bounding these parameters gives rise to an efficient algorithm. This idea is captured by the notion of fixed-parameter tractability (FPT). We initiate the study of DQBF through the lens of fixed-parameter tractability and show that the evaluation problem becomes FPT under two natural parameterizations: the treewidth of the primal graph of the DQBF instance combined with a restriction on the interactions between the dependency sets, and also the treedepth of the primal graph augmented by edges representing dependency sets.
On Finite Entailment of Non-Local Queries in Description Logics
Authors: Gogacz Tomasz , Gutiérrez-Basulto Víctor , Gutowski Albert , Ibáñez-García Yazmín , Murlak Filip
Published: August 2020

We study the problem of finite entailment of ontology-mediated queries. Going beyond local queries, we allow transitive closure over roles. We focus on ontologies formulated in the description logics ALCOI and ALCOQ, extended with transitive closure. For both logics, we show 2EXPTIME upper bounds for finite entailment of unions of conjunctive queries with transitive closure. We also provide a matching lower bound by showing that finite entailment of conjunctive queries with transitive closure in ALC is 2EXPTIME-hard
Treewidth-aware Reductions of Normal ASP to SAT - Is Normal ASP Harder than SAT after All?
Authors: Hecher Markus
Published: August 2020

Answer Set Programming (ASP) is a paradigm and problem modeling/solving toolkit for KR that is often invoked. There are plenty of results dedicated to studying the hardness of (fragments of) ASP. So far, these studies resulted in characterizations in terms of computational complexity as well as in fine-grained insights presented in form of dichotomy-style results, lower bounds when translating to other formalisms like propositional satisfiability (SAT), and even detailed parameterized complexity landscapes. A quite generic and prominent parameter in parameterized complexity originating from graph
theory is the so-called treewidth, which in a sense captures structural density of a program. Recently, there was an increase in the number of treewidth-based solvers related to SAT. While there exist several translations from (normal) ASP to SAT, yet there is no reduction preserving treewidth or at least
being aware of the treewidth increase. This paper deals with a novel reduction from normal ASP to SAT that is aware of the treewidth, and guarantees that a slight increase of treewidth is indeed sufficient. Then, we also present a new result establishing that when considering treewidth, already the fragment
of normal ASP is slightly harder than SAT (under reasonable assumptions in computational complexity). This also confirms that our reduction probably cannot be significantly improved and that the slight increase of treewidth is unavoidable.
On the Decidability of Expressive Description Logics with Transitive Closure and Regular Role Expressions
Authors: Jung Jean Christoph , Lutz Carsten , Zeume Thomas
Published: August 2020

We consider fragments of the description logic SHOIF extended with regular expressions on roles. Our main result is that satisfiability and finite satisfiability are decidable in two fragments SHOIF^1 and SHOIF^2, NExpTime-complete for the former and in 2NExpTime for the more expressive latter fragment. Both fragments impose restrictions on regular role expressions of the form r*. SHOIF^1 encompasses the extension of SHOIF with transitive closure of roles (when functional roles have no subroles) and the modal logic of linear orders and successor, with converse. Consequently, these logics are also decidable and NExpTime-complete.
Symbolic Solutions for Symbolic Constraint Satisfaction Problems
Authors: Andrade de Melo Alexsander , De Oliveira Oliveira Mateus
Published: August 2020

A fundamental drawback that arises when one is faced with the task of deterministically certifying solutions to computational problems in PSPACE is the fact that witnesses may have superpolynomial size, assuming that NP is not equal to PSPACE. Therefore, the complexity of such a deterministic verifier may already be super-polynomially lower-bounded by the size of a witness. In this work, we introduce a new symbolic framework to address this drawback. More precisely, we introduce a PSPACE-hard notion of symbolic constraint satisfaction problem where both instances and solutions for these instances are implicitly represented by ordered decision diagrams (i.e. read-once, oblivious, branching programs). Our main result states that given an ordered decision diagram D of length k and width w specifying a CSP instance, one can determine in time f(w,w')*k whether there is an ODD of width at most w' encoding a solution for this instance. Intuitively, while the parameter w quantifies the complexity of the instance, the parameter w' quantifies the complexity of a prospective solution. We show that CSPs of constant width can be used to formalize natural PSPACE hard problems, such as reachability of configurations for Turing machines working in nondeterministic linear space. For such problems, our main result immediately yields an algorithm that determines the existence of solutions of width w in time g(w)*n, where g:N->N is a suitable computable function, and n is the size of the input.
Bipolar Abstract Argumentation with Dual Attacks and Supports
Authors: Potyka Nico
Published: August 2020

Bipolar abstract argumentation frameworks allow modeling decision problems by defining pro and contra arguments and their relationships. In some popular bipolar frameworks, there is an inherent tendency to favor either attack or support relationships. However, for some applications, it seems sensible to treat attack and support equally. Roughly speaking, turning an attack edge into a support edge, should just invert its meaning. We look at a recently introduced bipolar argumentation semantics and two novel alternatives and discuss their semantical and computational properties. Interestingly, the two novel semantics correspond to stable semantics if no support relations are present and maintain the computational complexity of stable semantics in general bipolar frameworks.
Choosing What to Believe - New Results in Selective Revision
Authors: Resina Fillipe , Garapa Marco , Wassermann Renata , Fermé Eduardo , Reis Maurício
Published: August 2020

Selective Revision was proposed by Fermé and Hansson as a belief revision operation in which it is possible to accept only a part of the input information. In this paper, we extend Selective Revision to belief bases and also to logics not closed under negation.
A (Simplified) Supreme Being Necessarily Exists, says the Computer: Computationally Explored Variants of Gödel's Ontological Argument
Authors: Benzmüller Christoph
Published: August 2020

An approach to universal (meta-)logical reasoning in classical higher-order logic is employed to explore and study simplifications of Kurt Gödel's modal ontological argument. Some argument premises are modified, others are dropped, modal collapse is avoided and validity is shown already in weak modal logics K and T. Key to the gained simplifications of Gödel's original theory is the exploitation of a link to the notions of filter and ultrafilter in topology.

The paper illustrates how modern knowledge representation and reasoning technology for quantified non-classical logics can contribute new knowledge to other disciplines. The contributed material is also well suited to support teaching of non-trivial logic formalisms in classroom.
WOLED: A tool for Online Learning Weighted Answer Set Rules for Temporal Reasoning Under Uncertainty
Authors: Katzouris Nikos , Artikis Alexander
Published: August 2020

Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. Logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine uncertainty-resilient reasoning with time and change, with machine learning, thus alleviating the cost of manual event pattern authoring. We present WOLED, a system based on Answer Set Programming (ASP), capable of probabilistic reasoning with complex event patterns in the form of weighted rules in the Event Calculus, whose structure and weights are learnt online. We compare our ASP-based implementation with a Markov Logic-based one and with a crisp version of the algorithm that learns unweighted rules, on CER datasets for activity recognition, maritime surveillance and fleet management. Our results demonstrate the superiority of our novel implementation, both in terms of efficiency and predictive performance.
Explainable and Argumentation-based Decision Making with Qualitative Preferences for Diagnostics and Prognostics of Alzheimer's Disease
Authors: Zeng Zhiwei , Shen Zhiqi , Tan Benny Toh Hsiang , Chin Jing Jih , Leung Cyril , Wang Yu , Chi Ying , Miao Chunyan
Published: August 2020

Argumentation has gained traction as a formalism to make more transparent decisions and provide formal explanations recently. In this paper, we present an argumentation-based approach to decision making that can support modelling and automated reasoning about complex qualitative preferences and offer dialogical explanations for the decisions made. We first propose Qualitative Preference Decision Frameworks (QPDFs). In a QPDF, we use contextual priority to represent the relative importance of combinations of goals in different contexts and define associated strategies for deriving decision preferences based on prioritized goal combinations. To automate the decision computation, we map QPDFs to Assumption-based Argumentation (ABA) frameworks so that we can utilize existing ABA argumentative engines for our implementation. We implemented our approach for two tasks, diagnostics and prognostics of Alzheimer's Disease (AD), and evaluated it with real-world datasets. For each task, one of our models achieves the highest accuracy and good precision and recall for all classes compared to common machine learning models. Moreover, we study how to formalize argumentation dialogues that give contrastive, focused and selected explanations for the most preferred decisions selected in given contexts.
Temporal Logic Monitoring Rewards via Transducers
Authors: De Giacomo Giuseppe , Favorito Marco , Iocchi Luca , Patrizi Fabio , Ronca Alessandro
Published: August 2020

In Markov Decision Processes (MDPs), rewards are assigned according to a function of the last state and action. This is often limiting, when the considered domain is not naturally Markovian, but becomes so after careful engineering of extended state space. The extended states record information from the past that is sufficient to assign rewards by looking just at the last state and action. Non-Markovian Reward Decision Processes (NRMDPs) extend MDPs by allowing for non-Markovian rewards, which depend on the history of states and actions. Non-Markovian rewards can be specified in temporal logics on finite traces such as LTLf/LDLf, with the great advantage of a higher abstraction and succinctness; they can then be automatically compiled into an MDP with an extended state space. We contribute to the techniques to handle temporal rewards and to the solutions to engineer them. We first present an approach to compiling temporal rewards which merges the formula automata into a single transducer, sometimes saving up to an exponential number of states. We then define monitoring rewards, which add a further level of abstraction to temporal rewards by adopting the four-valued conditions of runtime monitoring; we argue that our compilation technique allows for an efficient handling of monitoring rewards. Finally, we discuss application to reinforcement learning.
Comparing Weak Admissibility Semantics to their Dung-style Counterparts -- Reduct, Modularization, and Strong Equivalence in Abstract Argumentation
Authors: Baumann Ringo , Brewka Gerhard , Ulbricht Markus
Published: August 2020

Semantics based on weak admissibility were recently introduced to overcome a problem with self-defeating arguments that has not been solved for more than 25 years. The recursive definition of weak admissibility mainly relies on the notion of a reduct regarding a set E which only contains arguments which are neither in E, nor attacked by E. At first glance the reduct seems to be tailored for the weaker versions of Dung-style semantics only. In this paper we show that standard Dung semantics can be naturally reformulated using the reduct revealing that this concept is already implicit. We further identify a new abstract principle for semantics, so-called modularization describing how to obtain further extensions given an initial one. Its importance for the study of abstract argumentation semantics is shown by its ability to alternatively characterize classical and non-classical semantics. Moreover, we tackle the notion of strong equivalence via characterizing kernels and give a complete classification of the weak versions regarding well-known properties and postulates known from the literature.
Analyzing Differentiable Fuzzy Implications
Authors: van Krieken Emile , Acar Erman , van Harmelen Frank
Published: August 2020

Combining symbolic and neural approaches has gained considerable attention in the AI community, as it is argued that their strengths and weaknesses are complementary. One trend in the literature are weakly supervised learning techniques that employ operators from fuzzy logics. They use prior background knowledge described in such logics to help training neural networks from unlabeled and noisy data. By interpreting logical symbols using neural networks (or grounding them), this background knowledge can be added to regular loss functions, hence making reasoning a part of learning. We investigate how implications from the fuzzy logic literature behave in a differentiable setting. In this setting, we analyze the differences between the formal properties of these fuzzy implications. It turns out that various fuzzy implications, including some of the most well-known, are highly unsuitable for use in a differentiable learning setting.
A further finding shows a strong imbalance between gradients driven by the antecedent and the consequent of the implication. Furthermore, we introduce a new family of fuzzy implications (called sigmoidal implications) to tackle this phenomenon. Finally, we empirically show that it is possible to use Differentiable Fuzzy Logics for semi-supervised learning, and show that sigmoidal implications outperform other choices of fuzzy implications.
Modeling Affordances and Functioning for Personalized Robotic Assistance
Authors: Umbrico Alessandro , Cortellessa Gabriella , Orlandini Andrea , Cesta Amedeo
Published: August 2020

A key aspect of robotic assistants is their ability to contextualize their behavior according to different needs of assistive scenarios. This work presents an ontology-based
knowledge representation and reasoning approach supporting the synthesis of personalized behavior of robotic assistants. It introduces an ontological model of health state
and functioning of persons based on the International Classification of Functioning, Disability and Health. Moreover, it borrows the concepts of affordance and function from the literature of robotics and manufacturing and adapts them to robotic (physical and cognitive) assistance domain. Knowledge reasoning mechanisms are developed
on top of the resulting ontological model to reason about stimulation capabilities of a robot and health state of a person in order to identify action opportunities and achieve personalized assistance. Experimental tests assess the performance of the proposed approach and its capability of dealing with different profiles and stimuli.
Hot-filament CVD Growth of Vertically-aligned Carbon Nanotubes on Support Materials for Field Electron Emitters
Authors: Thanh Hai Nguyen , Nhat Minh Dang , Nhat Minh Do , Dinh Dung Nguyen , Nhu Hai Luong , Ngoc Hong Phan , Tuan Hong Nguyen
Published: August 2020

Carbon nanotubes are used in applications such as energy storages, electronic devices. For these applications, direct assembly of the well aligned and densely packed CNTs (VACNTs) on electrically conducting substrates is of interest. In this paper, we report a direct growth of the VACNTs on several substrates by using hot-filament chemical vapor deposition (hot-filament CVD) and a catalytic buffer-layer structure. The buffer layer was the Aluminum (Al) thin film used together with iron (Fe) as the catalyst. It was found that the underneath layer (Al) was critical for obtaining the VACNT forests with high purity and good contact. The as-fabricated VACNT/support-material structures are object to test field electron emission properties. Testing results of the VACNT samples demonstrated promising field emission characteristics in term of high emitting currents.
H_∞ Finite-time Boundedness for Discrete-time Delay Neural Networks via Reciprocally Convex Approach
Authors: Tuan Le Anh
Published: August 2020

This paper addresses the problem of finite-time boundedness for discrete-time neural networks with interval-like time-varying delays. First, a delay-dependent finite-time boundedness criterion under the finite-time  performance index for the system is given based on constructing a set of adjusted Lyapunov–Krasovskii functionals and using reciprocally convex approach. Next, a sufficient condition is drawn directly which ensures the finite-time stability of the corresponding nominal system. Finally, numerical examples are provided to illustrate the validity and applicability of the presented conditions.

Keywords: Discrete-time neural networks,  performance, finite-time stability, time-varying delay, linear matrix inequality.
Indonesian Defense Management Models Are Adaptive And Competitive
Authors: Wulan Hendra , Martharaharja Januar Arief , Sutrasna Yudi , Sugiyono Ahmad
Published: August 2020

This research aims to study and describe the existing conditions of Indonesia's current defense management and analyze and develop an adaptive and competitive Indonesian defense management model. This research is a descriptive type with a qualitative approach. The nature of this research is exploratory and qualitative analysis techniques which consist of five stages, namely data collection and assessment, data reduction, data presentation, data validity checking, and drawing conclusions. The results of this study are that currently the defense management carried out by Indonesia still has some gaps and weaknesses where the defense management model has not been developed holistically, where the management of national defense and security has not been interpreted as a whole system. Considering that the implementation of security and defense must be comprehensively carried out as an integrated security and defense system, whose output is of course in addition to the realization of a component of the national defense and security force, including citizens who have strong national resilience. Then, the national defense management model that is found can improve coordination and cooperation between the Ministry of Defense and related institutions in strengthening defense and improving national security as a whole.
The Influence Of Transformational Leadership, Work Environment And Workloads On Intention To Leave And Employee Performance
Authors: Puspita Vida Indira , Mujanah Siti , Nugroho Mulyanto
Published: August 2020

This research aims to analyze the influence of transformational leadership, work environment, and workloads on an intention to leave and employee performance in Bank Jatim Headquarters. The sample in this study is 84 employees of Bank Jatim headquarters using simple random sampling. Method of data collection using survey technique with questioners as instruments and methods of data analysis using PLS (Partial Least Square). The results of this study indicate that transformational leadership applied in the company has a significant effect on the intention to leave employees. However, the work environment and Workload gave to employees considerable impact does not affect the intention to leave of employees. Otherwise, transformational leadership does not significantly influence employee performance, and work environment, workloads, and intention to leave employees have a significant effect on employee performance.
The Effectiveness of Behavioral Counseling to Reduce Student Learning Anxiety
Authors: Fauzi Taty
Published: August 2020

This is a continuing study of a development behavioral model to help students reduce their learning anxiety. 192 students involved as study population after filled self-report scale of learning anxiety, but only 30 students who had meet the learning anxiety criteria and they were given counseling interventions. Through quasi-experiment pretest-posttest control group design, 30 students divided into two groups, 15 students in the experiment group with behavioral counseling and 15 students in the control group with no specific approach. Overall, there are significant differences between experiment and control group (t = -27.65, p < 0.05). The results of the proposed study prove that the behavioral counseling model showed higher impact to reduce learning anxiety rather than the conventional counseling with no specific approach. Therefore, the author concludes that behavioral counseling is one of the effective interventions to reduce students learning anxiety. The implication of this research to counseling practice will be discussed.
Incidência de lesões musculoesqueléticas entre os trabalhadores dos serviços gerais do campus Dom Bosco da Universidade Federal de São João Del-Rei
Authors: Reis Viviane Felícia dos , Alves Felipe Rezende Ferreira , Moraes Mariana Maurício , Paiva Taynara Gabriele Aparecida de , Guimarães Andréa Carmen , Chiavegato Filho Luiz Gonzaga , Damázio Laila Cristina Moreira
Published: August 2020

O presente estudo teve por objetivo avaliar a presença de LER/DORT (lesões por esforços repetitivos/distúrbios osteomusculares relacionados ao trabalho) entre os funcionários dos serviços gerais do Campus Dom Bosco da Universidade Federal de São João del-Rei. Trata-se de um estudo original, com delineamento transversal, em que a amostra foi composta por 24 funcionários, os quais foram submetidos à aplicação de uma ficha de anamnese, avaliação postural e realização de testes clínico-ortopédicos específicos. Os dados foram analisados pelo programa GrhamPrism 5.0, considerando o nível de significância de 5%. Os resultados demonstraram que existe alta incidência de distúrbios musculoesqueléticas entre os funcionários avaliados. As alterações posturais mais encontradas foram: as protrusões e inclinações da cabeça, elevações dos ombros, escápulas elevadas e aladas, hipercifose torácica, retificação torácica, hiperlordose lombar, escoliose, joelhos em valgo, varo e recurvatum e calcâneosem valgo. Deste modo, infere-se que a alta incidência de alterações posturais pode estar relacionada a atividade exercida pelo servidor, bem como a postura que este adota ao realizar tais atividades. Tal fato aponta a necessidade da realização de intervenções terapêuticas e preventivas que visem minimizar e prevenir tais danos nessa população.
Estresse, depressão e a relação com o “coping” em acadêmicos de medicina
Authors: Erinaldo Leite Pereira Francisco , Pereira Charlene de Oliveira , Da Costa Anacleto Estrela Yoshyara , Do Carmo Ribeiro Rafaella , Cibelle Costa Rezende Ariany , Aguila Toledo Miguel , Bezerra André Luiz Dantas , Suárez Larissa de Araújo Batista , Holanda de Souza Joelly , Sousa Milena Nunes Alves de
Published: August 2020

Objetivo: Analisar os problemas de estresse e depressão e sua relação com uso de coping em estudantes de Medicina. Métodos: Pesquisa de caráter transversal, quantitativa realizada com estudantes do curso de Medicina do Centro Universitário de Patos, Patos-PB. Para a coleta de dados utilizou-se três questionários validados no Brasil sobre coping, estresse e depressão. Os dados foram analisados a partir de estatísticas descritivas de frequência relativa e absoluta e de testes inferenciais de Correlações de Pearson. Resultados: A estratégia “confronto” se correlacionou diretamente com as fases de alerta e de resistência (ρ = 0,20; ρ = 0,18; p <0,05), a estratégia “fuga e esquiva” diretamente com a fase de resistência do estresse e a depressão (ρ = 0,20; ρ = 0,27; p <0,05). Conclusão: A relação entre os problemas de saúde mental e a utilização de coping entre estudantes de Medicina foi importante para subsidiar reflexões, discussões e ações direcionadas para o cuidado dos alunos.
Desafios da educação permanente no acolhimento em saúde
Authors: Gouvea Mariane Pereira de , Carnevalle Claúdia Vieira , Moura Roudom Ferreira
Published: August 2020

Objetivo: Identificar as contribuições da educação permanente, a partir do acolhimento qualificado, para a melhoria da qualidade do atendimento aos usuários do Sistema Único de Saúde. Revisão Bibliográfica: A partir da análise de 20 artigos, ficou evidenciado que a educação permanente para profissionais de saúde é de suma importância, seja para os profissionais atuantes na produção de serviços como para os gestores e profissionais de apoio, tendo em vista que a educação no trabalho é considerada como instrumento estratégico para transformações efetivas para a melhoria da qualidade dos serviços de saúde. O Programa Nacional de Educação Permanente em Saúde visa promover saúde com base em preceitos do acolhimento. Considerações finais: Entende-se que educar de maneira que traga ao profissional de saúde a capacidade de reflexão crítica, baseada na realidade do cenário de saúde brasileiro, é o que se espera da educação permanente. Porém, a educação permanente está em segundo plano em ambiente desfavorável no cenário de saúde.
A ilusão da máscara côncava percebida por idosos
Authors: Carvalho Mateus Lopes de , Quaglia Maria Amélia Cesari , Oliveira Marcos Santos de
Published: August 2020

Objetivo: Investigar diferenças na percepção visual de idosos, comparativamente a pessoas de faixa etária menor em relação à ilusão da máscara côncava. Métodos: Utilizou-se o delineamento pré-experimental de comparação com grupo estático. As amostras foram selecionadas acidentalmente. Participaram 42 idosos e 73 pessoas de faixa etária menor. A máscara côncava foi apresentada binocularmente aos participantes a uma distância de três metros e em duas condições de iluminação: por cima e por baixo. A análise dos dados foi feita com um software estatístico e o nível de significância considerado foi 5%.  O estudo foi aprovado por Comissão de Ética. Resultados: Não houve diferenças significativas entre os grupos no primeiro indicador da percepção visual de profundidade (côncavo ou convexo), independentemente da condição de iluminação (por cima, p = 0,26; por baixo, p = 0,37). No segundo indicador (julgamento categórico), não houve diferenças significativas entre os grupos (por cima, p = 0,97; por baixo, p = 0,26). No terceiro indicador (estimativa métrica), os resultados foram semelhantes (por cima, p = 0,48; por baixo, p = 0,67). Conclusão: As pessoas de faixa etária menor, tanto quanto os idosos, foram suscetíveis à ilusão da máscara côncava.
Inexpensive Open Source Laser Cut Model Kits for the Teaching of Molecular Geometry
Authors: Adams Sean , McIndoe J Scott
Published: August 2020

We recently published an article in the Journal of Chemical Education on VSEPR model kits for helping teach molecular geometry. We have used these transparent acrylic models for several years now at the University of Victoria, but the challenges of COVID-19 meant that this year we needed to make a faster, less expensive version that could be easily mailed out to our students, without requiring any sorting and packaging steps. Accordingly, we designed a version that can be cut out of 2 mm thick recycled “chipboard” cardboard, in which all 26 parts for the 13 different models fit in one piece of card 175 × 120 mm (and 16 of these kits can be cut from one sheet in the laser cutter). The material cost is less than $0.25 per kit and the cutting time on our machine (Trotec Speedy360, 130 W) is 1 minute and 45 seconds per kit. These files are made freely available for all interested users as supporting information for this contribution, in CorelDraw, Adobe Illustrator, pdf and dxf formats.
Multifunctional [(CH₃)₃S][FeCl4] Plastic Crystal for Solar Thermal and Electric Energy Storage
Authors: Salgado-Beceiro Jorge , Bermudez Garcia Juan Manuel , Llamas-Saiz Antonio , Castro-Garcia Socorro , Señaris-Rodriguez Maria Antonia , Rivadulla Francisco , Sanchez-Andujar Manuel
Published: August 2020

In this work, we report a new halometallate [(CH3)3S][FeCl4] with plastic crystal behaviour as a new material for multi-energy storage. This material undergoes a first-order solid-solid plastic crystal phase transition near room temperature with a relatively large latent heat (~40 kJ kg-1) and an operational temperature for storing and releasing thermal energy between 42 oC (315 K) and 29 oC (302 K), very appropriate for solar thermal energy storage. In addition, the dielectric, magnetization and electron spin resonance studies reveal that this material exhibits multifunctional properties with temperature-induced reversible changes in its dielectric, conducting and magnetic behaviour associated with the phase transition. Also, the dielectric permitivity increases sharply up to 5 times when inducing the phase transition, which can be exploited to store electric energy into a capacitor. Therefore, [(CH3)3S][FeCl4] is a very interesting compound with coexistence of multifunctional properties that can be useful for both solar thermal and electric energy storage.
An Improved Route to Osmium(IV) Tetraaryl Complexes
Authors: Parr Joseph , Haiges Ralf , Inkpen Michael
Published: August 2020

Air-stable, redox-active osmium(IV) tetraaryl complexes can be prepared in yields ≤76% from the novel precursor (Oct4N)2[OsBr6], facilitating the synthesis of Os(mesityl)4 for the first time. This complex exhibits a distorted tetrahedral geometry and three reversible redox events including a 1+/2+ feature not previously observed in this family of materials.
Biolayer Interferometry Provides a Robust Method for Detecting DNA-Binding Small Molecules in Microbial Extracts
Authors: Overacker Ross D. , Plitzko Birte , Loesgen Sandra
Published: August 2020

DNA replication is an exceptional point of therapeutic intervention for many cancer types and several small molecules targeting DNA have been developed into clinically used antitumor agents. Many of these molecules are naturally occurring metabolites from plants and microorganisms, such as the widely used chemotherapeutic doxorubicin. While natural product sources contain a vast number of DNA binding small molecules, isolating and identifying these molecules is challenging. Typical screening campaigns utilize time-consuming bioactivity-guided fractionation approaches, which use sequential rounds of cell-based assays to guide the isolation of active compounds. In this study, we explore the use of Biolayer Interferometry (BLI) as a tool for rapidly screening natural products sources for DNA targeting small molecules. We first verified that BLI robustly detected DNA binding using designed GC and AT rich DNA oligonucleotides with known DNA intercalating, groove-, and covalent-binding agents including actinomycin D (1), doxorubicin (2), ethidium bromide (3), propidium iodide (4), Hoechst 33342 (5), netropsin (6), and cisplatin (7). Although binding varied with the properties of the oligonucleotides, measured binding affinities agreed with previously reported values. We next utilized BLI to screen over 100 bacterial extracts from our microbial library for DNA binding activity and found three highly active extracts. Binding-guided isolation was used to isolate the active principle component from each extract, which were identified as echinomycin (8), actinomycin V (9), and chartreusin (10). This biosensor-based DNA binding screen is a novel, low cost, easy to use, and sensitive approach for medium-throughput screening of complex chemical libraries.
Real-Time Analysis of Methylalumoxane Formation
Authors: Joshi Anuj , Zijlstra Harmen S. , Liles Elena , Concepcion Carina , Linnolahti Mikko , McIndoe J Scott
Published: August 2020

Methylalumoxane (MAO), a perennially useful activator for olefin polymerization precatalysts, is famously intractable to structural elucidation, consisting as it does of a complex mixture of oligomers generated from hydrolysis of pyrophoric trimethylaluminum (TMA). Electrospray ionization mass spectrometry (ESI-MS) is capable of studying those oligomers that become charged during the activation process. We’ve exploited that ability to probe the synthesis of MAO in real time, starting less than a minute after the mixing of H2O and TMA and tracking the first half hour of reactivity. We find that the process does not involve an incremental build-up of oligomers; instead, oligomerization to species containing 12-15 aluminum atoms happens within a minute, with slower aggregation to higher molecular weight ions. The principal activated product of the benchtop synthesis is the same as that observed in industrial samples, namely [(MeAlO)16(Me3Al)6Me]–, and we have computationally located a new sheet structure for this ion 94 kJ mol-1 lower in Gibbs energy than any previously calculated.
Knowledge and awareness about low Covid-19 mortality rate in Germany - A survey
Authors: Arun Kishore R N  , Gayatri Devi R
Published: August 2020

The recent news has all been about COVID 19. There are no vaccines or cure for this disease. The main aim of this study is to assess the knowledge and awareness about the mystery behind the low 19 Germany population Among south Indian population. COVID-19 started in December 2019, like a viral outbreak in Wuhan city of central China. Now it has become a pandemic all over the world and the world. The main aim of this study is to determine the awareness level of the mystery behind low 19 Germany mortality rates among Chennai population a survey. Questions were prepared and distributed among participants. And were distributed in an online survey. The results were later obtained and carefully . From the results obtained and the majority of the participants knew about the symptoms of COVID-19 and precautionary measures that had to be taken. The participants also have knowledge of Germans' low mortality rates during 19 pandemic. From this survey, we can conclude that the Chennai population does have knowledge and awareness about the mystery behind low COVID-19 Germans mortality rates.
General awareness about Covid-19 and the role of Convalescent plasma therapy in the treatment of Covid -19 among post graduate dental students - A KAP Survey
Authors: Deepa Viswasini R  , Abilasha R
Published: August 2020

COVID-19, caused by SARS Cov2 virus is a global pandemic and a threat to the world population and economy. It can manifest with a broad spectrum of clinical symptoms ranging from asymptomatic cases to pneumonia or even fatality. One of the treatments suggested is convalescent plasma therapy. The study aims at assessing the general awareness about Covid-19 and knowledge about the role of Convalescent plasma therapy for treatment of -19 among post graduate dental students. The survey was conducted among postgraduate dental students through an online survey tool using google forms. The survey was conducted online among postgraduate dental students on the go with 19 and convalescent plasma therapy. total of 103 participant were included in the study. The responses were collected, tabulated and using SPSS software. The knowledge regarding -19 and the awareness about the usefulness of convalescent plasma was variable. Around 90% of the participants were aware of the effectiveness of convalescent plasma therapy. Advance training, proper PPE and training on handling the patients with any infectious disease should be dealt with in detail for reducing the spread from dental clinics and dentists.
The effect of mild sleep deprivation on diet and eating behaviour in children: Protocol for the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized cross-over trial
Authors: Ward AL , Galland BC , Haszard JJ , Meredith-Jones K , Morrison S , McIntosh DR , Jackson R , Beebe DW , Fangupo L , Richards R , Te Morenga Lisa , Smith C , Elder DE , Taylor RW
Published: August 2020

© 2019 The Author(s). Background: Although insufficient sleep has emerged as a strong, independent risk factor for obesity in children, the mechanisms by which insufficient sleep leads to weight gain are uncertain. Observational research suggests that being tired influences what children eat more than how active they are, but only experimental research can determine causality. Few experimental studies have been undertaken to determine how reductions in sleep duration might affect indices of energy balance in children including food choice, appetite regulation, and sedentary time. The primary aim of this study is to objectively determine whether mild sleep deprivation increases energy intake in the absence of hunger. Methods: The Daily, Rest, Eating, and Activity Monitoring (DREAM) study is a randomized controlled trial investigating how mild sleep deprivation influences eating behaviour and activity patterns in children using a counterbalanced, cross-over design. One hundred and ten children aged 8-12 years, with normal reported sleep duration of 8-11 h per night will undergo 2 weeks of sleep manipulation; seven nights of sleep restriction by going to bed 1 hr later than usual, and seven nights of sleep extension going to bed 1 hr earlier than usual, separated by a washout week. During each experimental week, 24-h movement behaviours (sleep, physical activity, sedentary behaviour) will be measured via actigraphy; dietary intake and context of eating by multiple 24-h recalls and wearable camera images; and eating behaviours via objective and subjective methods. At the end of each experimental week a feeding experiment will determine energy intake from eating in the absence of hunger. Differences between sleep conditions will be determined to estimate the effects of reducing sleep duration by 1-2 h per night. Discussion: Determining how insufficient sleep predisposes children to weight gain should provide much-needed information for improving interventions for the effective prevention of obesity, thereby decreasing long-term morbidity and healthcare burden. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12618001671257. Registered 10 October 2018.
The effect of a diet moderately high in protein and fiber on insulin sensitivity measured using the dynamic insulin sensitivity and secretion test (DISST)
Authors: Te Morenga Lisa , Docherty P , Williams S , Mann J
Published: August 2020

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. Evidence shows that weight loss improves insulin sensitivity but few studies have examined the effect of macronutrient composition independently of weight loss on direct measures of insulin sensitivity. We randomised 89 overweight or obese women to either a standard diet (StdD), that was intended to be low in fat and relatively high in carbohydrate (n = 42) or to a relatively high protein (up to 30% of energy), relatively high fibre (>30 g/day) diet (HPHFib) (n = 47) for 10 weeks. Advice regarding strict adherence to energy intake goals was not given. Insulin sensitivity and secretion was assessed by a novel method—the Dynamic Insulin Sensitivity and Secretion Test (DISST). Although there were significant improvements in body composition and most cardiometabolic risk factors on HPHFib, insulin sensitivity was reduced by 19.3% (95% CI: 31.8%, 4.5%; p = 0.013) in comparison with StdD. We conclude that the reduction in insulin sensitivity after a diet relatively high in both protein and fibre, despite cardiometabolic improvements, suggests insulin sensitivity may reflect metabolic adaptations to dietary composition for maintenance of glucose homeostasis, rather than impaired metabolism.
Do differences in compositional time use explain ethnic variation in the prevalence of obesity in children? Analyses using 24-hour accelerometry
Authors: Taylor RW , Haszard JJ , Farmer VL , Richards R , Te Morenga Lisa , Meredith-Jones K , Mann JI
Published: August 2020

© 2019, Springer Nature Limited. Background/Objectives: Whether variation in sleep and physical activity explain marked ethnic and socioeconomic disparities in childhood obesity is unclear. As time spent in one behaviour influences time spent in other behaviours across the 24-hour day, compositional analyses are essential. The aims of this study were to determine how ethnicity and socioeconomic status influence compositional time use in children, and whether differences in compositional time use explain variation in body mass index (BMI) z-score and obesity prevalence across ethnic groups. Methods: In all, 690 children (58% European, 20% Māori, 13% Pacific, 9% Asian; 66% low-medium deprivation and 34% high deprivation) aged 6–10 years wore an ActiGraph accelerometer 24-hours a day for 5 days yielding data on sedentary time, sleep, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). Height and weight were measured using standard techniques and BMI z-scores calculated. Twenty-four hour movement data were transformed into isometric log-ratio co-ordinates for multivariable regression analysis and effect sizes were back-transformed. Results: European children spent more time asleep (predicted difference in minutes, 95% CI: 16.1, 7.4–24.9) and in MVPA (6.6 min, 2.4–10.4), and less time sedentary (−10.2 min, −19.8 to −0.6) and in LPA (−12.2 min, −21.0 to −3.5) than non-European children. Overall, 10% more sleep was associated with a larger difference in BMI z-score (adjusted difference, 95% CI: −0.13, −0.25 to −0.01) than 10% more MVPA (−0.06, −0.09 to −0.03). Compositional time use explained 35% of the increased risk of obesity in Pacific compared with European children after adjustment for age, sex, deprivation and diet, but only 9% in Māori and 24% in Asian children. Conclusions: Ethnic differences in compositional time use explain a relatively small proportion of the ethnic differences in obesity prevalence that exist in children.
Wholegrain particle size influences postprandial glycemia in type 2 diabetes: A randomized crossover study comparing four wholegrain breads
Authors: Reynolds AN , Mann J , Elbalshy M , Mete E , Robinson C , Oey I , Silcock P , Downes N , Perry T , Te Morenga Lisa
Published: August 2020

© 2019 by the American Diabetes Association. OBJECTIVE: Wholegrain foods vary in the extent of processing. We investigated whether wholegrain particle size in bread influences postprandial glycemia in type 2 diabetes. RESEARCH DESIGN AND METHODS: Postprandial glycemia (incremental area under the blood glucose curve [iAUC]) was measured after consumption of three breads made with roller-milled wholegrain flour and added grains and a fourth made with stone-ground flour. All flours and grains were 100% wholegrain wheat. Breads were nutrient matched. RESULTS: Fifteen adults (64 ± 10 years, HbA1c 58 ± 13 mmol/mol) completed the study. iAUC for the three breads made with roller-milled flour ranged from 376 to 641 mmol-1min-1, inverse linear trend for grain particle size P = 0.039. The iAUC for stone-ground wholegrain bread (503) was smaller than predicted from mean particle size. CONCLUSIONS: Wholegrain structural integrity in bread is a determinant of glycemic response. These findings have implications for dietary advice and the definition of the term '"wholegrain".
Spot urine and 24-h diet recall estimates of dietary sodium intake from the 2008/09 New Zealand Adult Nutrition Survey: a comparison
Authors: McLean RM , Williams SM , Te Morenga Lisa , Mann JI
Published: August 2020

© 2018, Macmillan Publishers Limited, part of Springer Nature. Background: We aimed to test the difference between estimates of dietary sodium intake using 24-h diet recall and spot urine collection in a large sample of New Zealand adults. Methods: We analysed spot urine results, 24-h diet recall, dietary habits questionnaire and anthropometry from a representative sample of 3312 adults aged 15 years and older who participated in the 2008/09 New Zealand Adult Nutrition Survey. Estimates of adult population sodium intake were derived from 24-h diet recall and spot urine sodium using a formula derived from analysis of INTERSALT data. Correlations, limits of agreement and mean difference were calculated for the total sample, and for population subgroups. Results: Estimated total population 24-h urinary sodium excretion (mean (95% CI)) from spot urine samples was 3035 mg (2990, 3079); 3612 mg (3549, 3674) for men and 2507 mg (2466, 2548) for women. Estimated mean usual daily sodium intake from 24-h diet recall data (excluding salt added at the table) was 2564 mg (2519, 2608); 2849 mg (2779, 2920) for men and 2304 mg (2258, 2350) for women. Correlations between estimates were poor, especially for men, and limits of agreement using Bland–Altman mean difference analysis were wide. Conclusions: There is a poor agreement between estimates of individual sodium intake from spot urine collection and those from 24-hour diet recall. Although, both 24-hour dietary recall and estimated urinary excretion based on spot urine indicate mean population sodium intake is greater than 2 g, significant differences in mean intake by method deserve further investigation in relation to the gold standard, 24-hour urinary sodium excretion.