bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental and theoretical investigation of thermal properties of natural soil based geopolymer composites
Authors: Nadeem Muhammad , Zain-ul-Abdein Muhammad , Ahmed Furqan , Haq Ehsan U. , Khan Wajid A. , Ibn Shamsah Sami M.
Published: December 2020

Geopolymer composites have found numerous thermal management applications in the construction industry due to their low thermal conductivity. In this work, geopolymer foams were produced using natural soil with varying fractions of sodium silicate solution. The extent of geopolymerization was evaluated based on qualitative and X-ray diffraction analyses. Scanning electron microscopy was performed to characterize the shape morphology. Thermal properties were measured using a hot disk analyzer. The effect of shape morphology and porosity on the thermal conductivity of the composites was discussed using several theoretical models. Yan- He, Hamilton-Crosser and geometric mean models showed good comparison with experimental observations. It was revealed that the geopolymerization reactions affect the porosity level, which, in turn, influences the effective thermal conductivity of the medium.
Assessing the Consequences of the Pandemic for the Russian Economy Through an Input-Output Model
Authors:   Bank of Russia, Ponomarenko Aleksey , Popova Svetlana ,   Bank of Russia, Sinyakov Andrey ,   Bank of Russia, Turdyeva Natalya ,   Bank of Russia, Chernyadyev Dmitry
Published: December 2020

This paper evaluates the impact of anti-coronavirus measures on the dynamics of economic activity. In addition to primary shocks directly caused by restrictive measures, we assess their secondary effects through inter-industry relationships. Our assessments show that secondary effects impact more industries than primary effects do. The overall impact of secondary effects on the economy proves to be of a larger scale than the impact of primary effects with high heterogeneity of dynamics by industry.
Modelling the Effects of a Health Shock on the Armenian Economy
Authors:   Central Bank of Armenia, Ani Ani , Davtyan Vahagn ,   Central Bank of Armenia, Igityan Haykaz ,   Central Bank of Armenia, Kartashyan Hasmik ,   Central Bank of Armenia, Manukyan Hovhannes ,   Central Bank of Armenia
Published: December 2020

This paper extends the closed economy DSGE model in order to evaluate the impact of the coronavirus on the economy. Our model makes it clear that people,s decisions to reduce consumption and working hours due to the health crisis lead to an economic recession. As a result, the spread of the virus declines. Expansionary monetary policy decreases the size of GDP decline, but it is costly in terms of public health. This result shows that there is a trade-off between the output loss caused by the epidemic and the health consequences of the epidemic.
Financial Shocks and Credit Cycles
Authors:   Institute for International Studies, MGIMO University, Mamonov Mikhail ,   CERGE-EI, Pankova Vera ,   Centre for Macroeconomic Analysis and Short-term Forecasting (CMASF), Akhmetov Renat ,   Centre for Macroeconomic Analysis and Short-term Forecasting (CMASF), Pestova Anna ,   Institute for International Studies, MGIMO University,   CERGE-EI
Published: December 2020

This paper compares the contribution of internal and external financial shocks to the formation of credit cycle phases using cross- country quarterly data for 27 countries, including advanced and emerging economies, for the period from 1990 through 2019. To conduct comparative analysis, we apply IV Probit models of the credit cycle which take into account the relationship between the credit and business cycles the inertia of the cycles and the non-linearity of the transmission of internal and external financial shocks to the economy through the credit market. In our sample of countries, the transmission of shocks to credit cycle phases proves to be non-linear (a switching effect is observed depending on the time elapsed since the shocks occurred); with the economic effect of the external capital inflow shock being in absolute value twice stronger than that of the bank credit supply shock (on average for the current and subsequent quarters); in turn, the bank credit supply shock is twice stronger than the monetary policy shock. A counterfactual analysis of the role of financial shocks in the formation of the credit cycle in Russia indicates an increase in the effectiveness of the monetary authorities in terms of their ability to control the phases of the credit cycle and, accordingly, a relative decrease in the role of credit supply shocks, while the global financial cycle retains its dominance.
Forecasting Russian Macroeconomic Indicators Based on Information from News and Search Queries
Authors:   Russian Presidential Academy of National Economy and Public Administration, Ulyankin Filipp
Published: December 2020

Modern economic literature features quite a number of various indices of economic activity. Some of them are based on public opinion polls (‘manual’ indices), while others are based on unstructured data from the Internet (‘automatic’ indices). However, the question as to which of these approaches is the most effective remains open. In this paper, we compare several different indices of economic activity in terms of their explanatory and predictive power. We build ‘automatic’ indices using machine learning methods. Search queries, news articles and user comments under news posts from social media are used as source data. The analysis of the resulting indices of economic activity shows that the search and news indices Granger-cause ‘manual’ indices and also better explain and predict the set of macroeconomic variables selected for research. The good explanatory power of the current values of macroeconomic indicators by means of current indices of economic activity with a lag in the output of macroeconomic statistics makes them suitable for nowcasting.
Select Teaching: authoring tool for building Learning Objects for language teachers´ training and teaching support
Authors: da Silva Medola Larissa , de Oliveira Barbosa Gomes Celina , Felippsen Eduardo Alberto
Published: December 2020

The use of technological instruments in educational environments and contexts was facilitated by the popularization of technology in general, which significantly supported the teaching-learning process. This fact highlights the importance of teachers´ training to use these tools, as well as the presence of softwares and other appropriate tools for specific educational approaches. Thus, the present paper presents the creation of a didactic tool, the "Select Teaching", to be applied in the production of didactic material in the format of electronic handouts with foreign language content. The research is mainly characterized by the feasibility of considering these handouts as Learning Objects to be used by the language teachers of the Federal Institute of Paraná (IFPR) - Campus Assis Chateaubriand.

Palavras-chave: Modern foreign language teaching. Digital didactic material. Learning Objects.
Aprender a brincar ao ar livre num jardim de infância em Portugal: um Estudo de Caso
Authors: Martins Carla , Neves Ivone
Published: December 2020

O presente trabalho é o resultado da pesquisa desenvolvida no âmbito do estágio profissionalizante do mestrado em Educação Pré-Escolar e Ensino do 1º Ciclo do Ensino Básico, que foi realizado na Escola Superior de Educação Paula Frassineti (Porto). Essa pesquisa tem como objetivo perceber de que modo as crianças desenvolvem as suas capacidades, através das brincadeiras no espaço ao ar livre, bem como compreender de que forma os educadores privilegiam situações e experiências com a natureza, permitindo a exploração livre e conduzida, para promover o desenvolvimento das crianças em vários níveis. O presente estudo é sobre o brincar ao ar livre no jardim de infância, caracterizando-se como uma investigação-ação. Dessa forma, as entrevistas com os educadores de infância, a discussão focada nas crianças, e os registos de observação foram coletados de modo a dar resposta ao estudo. Os dados evidenciam que os profissionais da educação promovem momentos de brincadeira ao ar livre, como um meio essencial de aprendizagem. Da mesma forma, as crianças avaliam brincar ao ar livre como momentos de satisfação, liberdade e partilha.

Palavras-chave: Brincar. Natureza. Aprendizagem.
Análise de falha por fratura de eixo do sistema de rodado de um distribuidor de fertilizante orgânico líquido
Authors: Grotto André Carlos , Dias de Meira Junior Agenor , Walber Márcio
Published: December 2020

Este trabalho apresenta uma avaliação de falha por fratura de eixo do sistema de rodado de um implemento agrícola Distribuidor de Adubo Orgânico Líquido (DAOL). É realizada uma avaliação da falha, sob ponto de vista metalúrgico, por meio de avaliações macrográficas, micrográficas, determinação da composição química e dureza do material e microscopia eletrônica de varredura (MEV). Também se apresenta a avaliação da falha à ótica estrutural, através de uma análise de falha por fadiga, utilizando o método dos elementos finitos, determinando coeficiente de segurança e vida do eixo. Determina-se que a característica da fratura corresponde a de uma falha por fadiga, vê-se o ponto de início da falha, avalia-se a região rugosa e a região polida da seção transversal fraturada. Além disso, apresenta-se o valor da vida do eixo em número de ciclos de carga máxima e o coeficiente de segurança para uma falha por fadiga.

Palavras-chave: Fadiga. Método dos elementos finitos. Micrografia/macrografia.
Caracterização das trocas térmicas de aço médio-carbono resfriado sob concentrações distintas de polivinilpirolidona
Authors: da Rosa Vieira Eduardo , Macedo Rodrigo Jorge , Machado Costa Vagner , Schumacher da Silva Guilherme , Volcanoglo Biehl Luciano , Braz Medeiros Jorge Luis
Published: December 2020

A têmpera é um procedimento térmico que busca a obtenção da microestrutura martensítica, visando melhoria nas propriedades dos materiais metálicos. O tratamento ocorre pelo aquecimento da peça, até que austenita seja obtida na sua composição, seguido de resfriamento, que deve ser rápido, impedindo que o carbono seja difundido no material. Esse resfriamento ocorre geralmente pela imersão do corpo sob alta temperatura em fluidos refrigerantes. Nesse sentido, existe a necessidade de taxas de resfriamento elevadas do corpo, provocadas pelo contato com o fluido, minimizando rapidamente sua temperatura. Atualmente, os fluidos poliméricos diluídos em água vêm sendo utilizadas para esse tratamento, posto que apresentam avanços em relação às demais classes de fluidos. Esses fluidos variam de forma relevante os níveis de transferência de calor, conforme a concentração é alterada na solução. Neste trabalho, as variações de temperaturas e taxas de variação térmica entre corpo e fluido foram avaliadas, empregando quatro concentrações de solução polimérica de polivinilpirolidona (PVP), com percentuais entre 10 e 25%.

Palavras-chave: Curvas de Resfriamento. Têmpera. Polivinilpirolidona.
A potential antiviral and food-derived healthy ingredient: Resveratrol
Authors: Arslaner Ayla , Türkoğlu Zehra
Published: December 2020

Polyphenols are the secondary metabolites of plants and has an important role in human nutrition as the leading antioxidants. According to the carbon number-based classification of polyphenols, resveratrol is a natural polyphenol in the stilbene group with antioxidant and anticarcinogenic effects. Its beneficial effects on cardiovascular diseases have also been reported. It was first identified in 1940 and has recently gained importance especially in medicine and pharmacy. Researchers have carried out various studies on resveratrol and its time-honored use in traditional eastern medicine has been reported. Resveratrol is a food ingredient that has the potential to be used in the treatment of various diseases, but also has antiviral effects. The study focuses on resveratrol’s physical and chemical properties, effects on health, antiviral effects and use in foods as a functional component.
Resident evaluations in the age of competency-based medical education: faculty perspectives on minimizing burdens
Authors: Rabski Jessica E. , Saha Ashirbani , Cusimano Michael D. , DABNS FRCSC
Published: December 2020

OBJECTIVE

Competency-based medical education (CBME), an outcomes-based approach to medical education, continues to be implemented across many postgraduate medical education programs worldwide, including a recent introduction into Canadian neurosurgical training programs (July 2019). The success of this educational paradigm shift requires frequent faculty observation and evaluation of residents performing defined tasks of the specialty. A main challenge involves providing residents with frequent performance evaluations and feedback that are feasible for faculty to complete. This study aims to define what is currently happening and what changes are needed to make CBME successful for the certification of neurosurgeons' competence.

METHODS

A 55-item questionnaire was emailed nationwide to survey Canadian neurosurgical faculty.

RESULTS

Fifty-two complete responses were received and achieved a distribution highly correlated with the number of faculty neurosurgeons practicing in each Canadian province (Pearson's r = 0.94). Two-thirds (35/52) of faculty reported currently taking a median of 10 minutes to complete evaluation forms at the end of a resident's rotation block. Regardless of the faculty's province of practice (p = 0.50) or years of experience (p = 0.06), they reported 3 minutes (minimum 1 minute, maximum 10 minutes, interquartile range [IQR] 3 minutes) as a feasible amount of time to spend completing an evaluation form following an observation of a resident's performance of an entrustable professional activity (EPA). If evaluation forms took 3 minutes to complete, 85% of respondents (44/52) would complete EPA evaluations weekly or daily. The faculty recommended 5 minutes as a feasible amount of time to provide oral feedback (minimum 1 minute, maximum 20 minutes, IQR 3.25 minutes), which was significantly higher (p = 0.00099) than their recommended amount of time for completing evaluation forms. The majority of faculty (71%) stated they would prefer to access resident evaluation forms through a mobile application compared to a paper form (12%), an evaluation website (8%), or through a URL link sent via email (10%; p = 0.0032).

CONCLUSIONS

To facilitate the successful implementation of CBME into a neurosurgical training curriculum, resident EPA assessment forms should take 3 minutes or less to complete and be accessible through a mobile application.
Impact of Michigan’s new opioid prescribing laws on spine surgery patients: analysis of the Michigan Spine Surgery Improvement Collaborative
Authors: Park Paul , Chang Victor , Yeh Hsueh-Han , Schwalb Jason M. , Nerenz David R. , Schultz Lonni R. , Abdulhak Muwaffak M. , Easton Richard , Perez-Cruet Miguelangelo , Kashlan Osama N. , Oppenlander Mark E. , Szerlip Nicholas J. , Swong Kevin N. , Aleem Ilyas S.
Published: December 2020

OBJECTIVE

In 2017, Michigan passed new legislation designed to reduce opioid abuse. This study evaluated the impact of these new restrictive laws on preoperative narcotic use, short-term outcomes, and readmission rates after spinal surgery.

METHODS

Patient data from 1 year before and 1 year after initiation of the new opioid laws (beginning July 1, 2018) were queried from the Michigan Spine Surgery Improvement Collaborative database. Before and after implementation of the major elements of the new laws, 12,325 and 11,988 patients, respectively, were treated.

RESULTS

Patients before and after passage of the opioid laws had generally similar demographic and surgical characteristics. Notably, after passage of the opioid laws, the number of patients taking daily narcotics preoperatively decreased from 3783 (48.7%) to 2698 (39.7%; p < 0.0001). Three months postoperatively, there were no differences in minimum clinically important difference (56.0% vs 58.0%, p = 0.1068), numeric rating scale (NRS) score of back pain (3.5 vs 3.4, p = 0.1156), NRS score of leg pain (2.7 vs 2.7, p = 0.3595), satisfaction (84.4% vs 84.7%, p = 0.6852), or 90-day readmission rate (5.8% vs 6.2%, p = 0.3202) between groups. Although there was no difference in readmission rates, pain as a reason for readmission was marginally more common (0.86% vs 1.22%, p = 0.0323).

CONCLUSIONS

There was a meaningful decrease in preoperative narcotic use, but notably there was no apparent negative impact on postoperative recovery, patient satisfaction, or short-term outcomes after spinal surgery despite more restrictive opioid prescribing. Although the readmission rate did not significantly increase, pain as a reason for readmission was marginally more frequently observed.
Analisis Kesulitan Belajar Siswa Pada Mata Pelajaran IPA di Kelas VII SMP Negeri 4 Terbanggi Besar
Authors: Wahyuni Wahyuni
Published: December 2020

Abstrak: Latar belakang penelitian ini adalah rendahnya prestasi belajar siswa khususnya pada mata pelajaran IPA karena adanya faktor-faktor kesulitan belajar yang dialami siswa kelas VII, terutama pada faktor psikologis. Kesulitan belajar yang dialami siswa berakibat pada prestasi yang kurang pada mata pelajaran IPA. Penelitian yang dilakukan untuk mengetahui fakor kesulitan belajar yang dialami siswa kelas VII. Penelitian ini merupakan penelitian deskriptif kualitatif. Subjek penelitian adalah siswa kelas VII yang mengalami kesulitan belajar yakni siswa yang memiliki nilai KKM yang tidak memenuhi berjumlah 30 orang. Pengumpulan data dilakukan dengan observasi dan wawancara. Berdasarkan hasil penelitian dan pembahasan yang telah dipaparkan tentang kesulitan belajar siswa pada mata pelajaran IPA di kelas VII SMP Negeri 4 Terbanggi Besar. Hasil presentase angket faktor kesulitan belajar siswa kelas VII SMP Negeri 4 Terbanggi Besar mata pelajaran IPA minat 23,33% (rendah), motivasi 30% (Rendah), konsentrasi 43,44% (cukup), kebiasaan belajar 40% (Rendah), Intelegensi 30% (rendah). Hasil wawancara yang dilakukan siswa penyebab kesulitan belajar yakni minat, motivasi, konsentrasi, kebiasaan belajar, dan intelegensi. Abstract:  The background of this research is the low of student achievement especially on the subject of science because of the factors of learning difficulties experienced by grade VII students, especially on psychological factors. Learning difficulties experienced by students result in less achievement in science subjects. Research conducted to find out the learning difficulties experienced by students of grade VII. This research is a qualitative descriptive study. The subjects of the study were the seventh grade students who experienced learning difficulties ie students who had KKM scores that did not meet 30 people. Data collection was done by observation and interview. Based on the results of research and discussion that has been presented about the difficulties students learn on science subjects in class VII SMP Negeri 4 Terbanggi Besar. The result of the percentage of questionnaires of students' learning difficulties class VII SMP Negeri 4 Terbanggi Besar Science subjects 23.33% (low), motivation 30% (low), concentration 43.44% (enough), 40% (low) study habits, Intelligence 30% (low). The results of interviews by students that cause learning difficulties such as interest, motivation, concentration, study habits, and intelligence.
Effect of Make A Match Learning Model on Student Learning Outcomes on Statistical Materials
Authors: Nurfiati Nurfiati , Mandailina Vera , Mahsup Mahsup , Syaharuddin Syaharuddin , Abdillah Abdillah
Published: December 2020

Abstract: The lowest average daily repeat score data is 65 and has not met the minimum completed criteria of 75. The Make a Match model is very helpful in creating an effective learning environment by utilizing the elements that exist in students. This learning model is a game in the form of question cards and answer cards. The purpose of the study was to determine the influence of the Make a Match learning model on students' math learning outcomes. The research design is quasi-experimental with post-test only. Sampling using random sampling method was taken as many as 2 classes as control class and experimental class. Hypothesis testing used t-test, calculation result obtained t-count of 1,688 while t-table value of 1,645, because t_hitung>t_(table) then H_O rejected and hypothesis received. It is concluded that there are differences in learning outcomes between the control class and the experimental class. It is recommended that teachers can continue to develop the Make a Match model. Abstrak: Data nilai ulangan harian siswa rata-rata paling rendah yaitu 65 dan belum mencampai kriteria ketuntasan minimal yaitu 75. Model Make a Match sangat membantu menciptakan lingkungan belajar yang efektif dengan memanfaatkan unsur-unsur yang ada pada siswa. Model pembelajaran ini berupa permainan berbentuk kartu soal dan kartu jawaban. Tujuan penelitian untuk mengetahui pengaruh model pembelajaran Make a Match terhadap hasil belajar matematika siswa. Rancangan penelitian adalah quasi eksperiment dengan post-test only. Pengambilan sampel menggunakan cara random sampling diambil sebanyak 2 kelas sebagai kelas kontrol dan kelas eksperimen. Pengujian hipotesis digunakan uji t, hasil perhitungan diperoleh t-hitung sebesar 1.688 sedangkan nilai t-tabel sebesar 1.645 karena  maka  ditolak dan hipotesis di terima. Disimpulkan terdapat perbedaan hasil belajar antara kelas kontrol dengan kelas eksperiment. Disarankan guru dapat terus mengembangkan model Make a Match.
Statistical Methods in Building Industry to Determine Prices Indices
Authors: Ellingerová Helena , Petráková Zora , Skalíková Ingrida
Published: December 2020

Tender price is often affected by the location of the construction, which is usually determined by the investor, and it has an impact on the traffic in the particular location. Individual time of supply and the method of realization play an important role as well. They both are determined by the investor along with the designer of the particular construction. Contractors often complain about the lack of time needed for the preparation of their tender prices. Therefore, it is necessary to look for the possibilities how to reliably speed up this process at the same time taking into account all of the specific features of a structure. This article deals with the application of two statistical methods. The Pareto analysis, which can be used during the design of the tender price, and the extrapolation method, which can be used for the estimation of the price development, based on the regression analysis of the time series. The results of the article particularly serve to contractors in the building industry to better prepare their price offers in tenders. The findings of this document may also be applicable in other countries which have a similar economic profile as Slovakia.
The Importance of SD Goals Indicators 7, 8, 9 and 12 in the Industry Development by Using Multi Criteria and Decision Making Method
Authors: Osmani Fisnik , Kochov Atanas , Shabani Betim , Ilazi Mirjeta
Published: December 2020

Sustainable Development and Decision Making are just two of the many processes that affect the industry sector. SDG7, SDG8, SDG9 and SDG 12 as four goals of sustainable development show the indicators we have to deal with, given that the energy, industry, economy and production are closely connected. This research focuses on promoting sustainable development in the industry, by testing very important indicators using the MCDM method. Our analysis was carried out with the help of a multi-criteria decision-making method - the Hierarchical Analytical Process. Through this method, we have identified specific areas that need improvement, the importance of the indicators separately, ranking so by their importance and impact in the industry, economy and production.
Case Study: Six Sigma Project for Reducing Manual Handling of Materials in Real Manufacturing Company
Authors: Kochov Atanas , Argilovski Aleksandar
Published: December 2020

This paper presents a case study that is focusing on the improvement of the process of materials handling in real manufacturing company. Before the implementation of this project, the company was in a concerning state of incidents and learning events towards the ergonomics, health and safety of the operators who manually handled materials as part of their daily activities. It was proposed to use the Six Sigma framework in order to improve the process or design new process for performing the task that included manual handling of materials. In this study, through selecting suitable Six Sigma framework, mapping the current process, setting key performance indicators and using various design tools and techniques, process improvement is proposed; it will solve the problem, increase ergonomics and safety, but also increase the speed of the process and reduce the cost of spilled materials that were manually handled.
Récords olímpicos: humanos vs insectos
Authors: Zenner de Polanía Ingeborg
Published: December 2020

Basado en observaciones, en mediciones y en literatura acerca de las habilidades deportivas de los insectos, en los tres deportes reconocidos de los Juegos Olímpicos de Verano, el atletismo, la gimnasia y la natación, se comparan algunas marcas deportivas, recientemente establecidas por hombres y por mujeres con aquellos que, determinados insectos, sostienen desde hace millones de años. Estos artrópodos, si compitiesen con los humanos, ganarían en la mayoría de las justas, en las que, por sus características, podrían participar, ya sea a nivel mundial o en juegos olímpicos. En el levantamiento de pesas, en cualquiera de las modalidades, compiten los escarabajos peloteros y las hormigas con los insectos; ganarían los cucarrones, reconocidos también como los insectos sagrados de los antiguos egipcios. Disputa con ellos la medalla, el escarabajo hércules o rinoceronte, Dynastes hercules, cucarrón emblemático de las selvas tropicales de Suramérica, incluyendo a Colombia. Las chinches acuáticas de las familias Notonectidae y Corixidae son nadadores por excelencia de dos estilos, espalda y pecho y no es la pulga, que se pensaba sostenía el récord mundial de salto alto y largo, sino un insecto salivazo o mión (Cercopidae), plaga de alfalfa. Igualmente, y como ocurre casi siempre en los juegos olímpicos, donde alguien le quita el récord a un atleta, hace poco, otro insecto le quitó la marca de corredor más rápido a la cucaracha americana. Afortunadamente, los humanos no compiten en deportes con los insectos, pero sí luchan con algunos de ellos, con éxito limitado, principalmente, por alimentos.
Iniciación y formación deportiva: una reflexión siempre oportuna
Authors: Acosta Edgar Raúl
Published: December 2020

Ampliamente se encuentra documentado y desde hace varias décadas, que la iniciación deportiva, entendida como un proceso multifacético, es la base para el desarrollo deportivo de un país, pero más importante aun, para la formación de ciudadanos físicamente activos y con altos valores de convivencia social y ambiental. Este proceso como tal, no es bien conocido y comprendido no solo por la mayoría de personas sino por los dirigentes deportivos, los políticos, los comunicadores y la mayoría de profesionales quienes trabajan en el área del deporte, generando procesos sin coherencia ni continuidad, que garanticen procesos deportivos y de convivencia socio-ambiental. Es imperativa la revisión teórica y de prácticas sobre la iniciación y la formación deportiva que se realiza en la actualidad, para fortalecer políticas claras, a nivel nacional, que permitan la consolidación de la cultura deportiva nacional.
Familie und Normalität
Authors: Fitz-Klausner Sebastian
Published: December 2020

Normalität wird als gesellschaftliche Anforderung erlebt und zugleich selbst hergestellt. Der Band versammelt Beiträge zu Aushandlungsprozessen, Positionierungen und Erfahrungen mit Normalitätsvorstellungen sowohl im pädagogischen Kontext als auch im Alltag von Familien, die der klassischen Norm nicht entsprechen. Die Beiträge fokussieren die Bereiche der frühen Kindheit, Jugendhilfe, Schule sowie neuer Technologien und diskutieren Aushandlungsprozesse in Verhältnissen von Migration, (Dis)Ability, Gender, Care und diversifizierter Elternschaft.
Zur scientific literacy angehender Erzieher*innen
Authors: Krewitt Marion
Published: December 2020

Wissenschaftliche Bildung ist nicht nur notwendig, um mit der unbelebten und belebten Natur umzugehen, sie ist eine grundlegende Kulturtechnik. Sie ist darüber hinaus essenziell für umfassende Teilhabe an einer modernen Wissenschaftsgesellschaft. Scientific Literacy als naturwissenschaftliche Grundbildung spielte in den Pisa-Studien eine entscheidende Rolle. Ausgehend vom „Pisa-Schock“ und den daraus resultierenden Änderungen in der Bildungseinrichtung Kita wird die Bedeutung der Scientific Literacy für Individuum und Gesellschaft herausgearbeitet. Die Autorin untersucht, über welche Kompetenzen (angehende) pädagogische Fachkräfte in diesem Bereich verfügen.
Surface Labeling with Adhesion Protein FimH Improves Binding of Immunotherapeutic Agent Salmonella Ty21a to the Bladder Epithelium
Authors: Burggraaf Maroeska J. , Waanders Lisette , Verlaan Mariska , Maaskant Janneke , Houben Diane , Luirink Joen , Bitter Wilbert , Kuijl Coen , Molthoff Carla F.M.
Published: December 2020

BACKGROUND:

Bladder cancer is the ninth most common cancer in men. 70% of these tumors are classified as non-muscle invasive bladder cancer and those patients receive 6 intravesical instillations with Mycobacterium bovis BCG after transurethral resection. However, 30% of patients show recurrences after treatment and experience severe side effects that often lead to therapy discontinuation. Recently, another vaccine strain, Salmonella enterica typhi Ty21a, demonstrated promising antitumor activity in vivo. Here we focus on increasing bacterial retention in the bladder in order to reduce the number of instillations required and improve antitumor activity.

OBJECTIVE:

To increase the binding of Ty21a to the bladder wall by surface labeling of the bacteria with adhesion protein FimH and to study its effect in a bladder cancer mouse model.

METHODS:

Binding of Ty21a with surface-labeled FimH to the bladder wall was analyzed in vitro and in vivo. The antitumor effect of a single instillation of Ty21a+FimH in treatment was determined in a survival experiment.

RESULTS:

FimH-labeled Ty21a showed significant ( p < 0.0001) improved binding to mouse and human cell lines in vitro. Furthermore, FimH labeled bacteria showed ∼5x more binding to the bladder than controls in vivo. Enhanced binding to the bladder via FimH labeling induced a modest improvement in median but not in overall mice survival.

CONCLUSIONS:

FimH labeling of Ty21a significantly improved binding to bladder tumor cells in vitro and the bladder wall in vivo. The improved binding leads to a modest increase in median survival in a single bladder cancer mouse study.
Recovery of Hippocampal-Dependent Learning Despite Blunting Reactive Adult Neurogenesis After Alcohol Dependence
Authors: Nickell Chelsea G. , Thompson K. Ryan , Pauly James R. , Nixon Kimberly
Published: December 2020

Background: The excessive alcohol drinking that occurs in alcohol use disorder (AUD) causes neurodegeneration in regions such as the hippocampus, though recovery may occur after a period of abstinence. Mechanisms of recovery are not clear, though reactive neurogenesis has been observed in the hippocampal dentate gyrus following alcohol dependence and correlates to recovery of granule cell number. Objective: We investigated the role of neurons born during reactive neurogenesis in the recovery of hippocampal learning behavior after 4-day binge alcohol exposure, a model of an AUD. We hypothesized that reducing reactive neurogenesis would impair functional recovery. Methods: Adult male rats were subjected to 4-day binge alcohol exposure and two approaches were tested to blunt reactive adult neurogenesis, acute doses of alcohol or the chemotherapy drug, temozolomide (TMZ). Results: Acute 5 g/kg doses of EtOH gavaged T6 and T7 days post binge did not inhibit significantly the number of Bromodeoxyuridine-positive (BrdU+) proliferating cells in EtOH animals receiving 5 g/kg EtOH versus controls. A single cycle of TMZ inhibited reactive proliferation (BrdU+ cells) and neurogenesis (NeuroD+ cells) to that of controls. However, despite this blunting of reactive neurogenesis to basal levels, EtOH-TMZ rats were not impaired in their recovery of acquisition of the Morris water maze (MWM), learning similarly to all other groups 35 days after 4-day binge exposure. Conclusions: These studies show that TMZ is effective in decreasing reactive proliferation/neurogenesis following 4-day binge EtOH exposure, and baseline levels of adult neurogenesis are sufficient to allow recovery of hippocampal function.
Order-sorted Homeomorphic Embedding Modulo Combinations of Associativity and/or Commutativity Axioms*
Authors: Alpuente María , Cuenca-Ortega Angel , Escobar Santiago , Meseguer José
Published: December 2020

The Homeomorphic Embedding relation has been amply used for defining termination criteria of symbolic methods for program analysis, transformation, and verification. However, homeomorphic embedding has never been investigated in the context of order-sorted rewrite theories that support symbolic execution methods modulo equational axioms. This paper generalizes the symbolic homeomorphic embedding relation to order–sorted rewrite theories that may contain various combinations of associativity and/or commutativity axioms for different binary operators. We systematically measure the performance of different, increasingly efficient formulations of the homeomorphic embedding relation modulo axioms that we implement in Maude. Our experimental results show that the most efficient version indeed pays off in practice.
Selective Unification in (Constraint) Logic Programming*
Authors: Mesnard Fred , Payet Étienne , Vidal Germán
Published: December 2020

Concolic testing is a well-known validation technique for imperative and object oriented programs. In a previous paper, we have introduced an adaptation of this technique to logic programming. At the heart of our framework lies a specific procedure that we call “selective unification”. It is used to generate appropriate run-time goals by considering all possible ways an atom can unify with the heads of some program clauses. In this paper, we show that the existing algorithm for selective unification is not complete in the presence of non-linear atoms. We then prove soundness and completeness for a restricted version of the problem where some atoms are required to be linear. We also consider concolic testing in the context of constraint logic programming and extend the notion of selective unification accordingly.
A sensor based intelligent system for classification and assistance of diabetes patients in telemedicine technology
Authors: Poonguzhali S, , Chakravarthi Rekha
Published: December 2020

Diabetes is one of the chronic metabolic disorder. Under diabetic condition, blood glucose level should be properly maintained in order to avoid various major diseases. The condition will be worse when it is not controlled at an earlier stage. Even massive heart attack cannot be identified when the patient has been affected by diabetes. Early diagnosis is required for preventing fatal diseases like cardiac problem, asthma, heart attack etc. In the proposed system measurement of glucose level and Prediction/ diagnosis of diabetes is based on the real time low complexity neural network implemented on a wearable device. A larger network is required for the diagnosis which needs to be present far-off in cloud and initiated for diagnosis and classification process of diabetes whenever it is essential. People can be able to manage and monitor the required basic parameters like heart rate, glucose level, lung condition, pressure of blood using the corresponding light weight biosensors in the wearable device designed through telemedicine technology. The quality of the disease diagnosis and Prediction is improved in this way. Using neural network feed forward prediction model in conjugation with back propagation algorithm and given training data, the system predicts whether the patient is prone to diabetes or not. The proposed work was evaluated using physic sensor data from physio net data base and also tested for real time functioning. The Proposed system found to be efficient in accuracy, sensitivity and fast operative.
Design of text sentiment analysis tool using feature extraction based on fusing machine learning algorithms
Authors: Ajitha P. , Sivasangari A. , Immanuel Rajkumar R. , Poonguzhali S.
Published: December 2020

Text Sentiment Analysis is a system where text feeling polarity is positive or negative or neutral from a series of texts or documents or public opinions on a particular product or general subject. Using machine learning and natural language processing techniques, the current work aims to gain insight into sentiment mining on tweets. Text classification is accomplished using Machine Learning Algorithm-based fusion technique. This research suggested a system for grading feelings based on a lexicon. Bag-of-words (BOW) or lexicon-based methodology is currently the main standard way of modeling text for machine learning in sentiment analysis approaches. Marketers can use sentiment analysis to analyze their business and services, public opinion, or to evaluate customer satisfaction. Organizations can even use this analysis to gather significant feedback on issues related to newly released products. The main objective of this is to resolve the data overload problem.
Research on influencing factors of stock returns based on multiple regression and artificial intelligence model
Authors: Han Ying
Published: December 2020

When choosing stock investment, there are many stock companies, and the stock varieties are also complicated. At present, there are various systems for evaluating stock performance in the market, but there is no uniform standard, so investors often cannot effectively invest in stocks. Simultaneously, stock management companies also have their own characteristics, and there are differences in shareholding structure and internal management structure. Based on this, based on multiple regression models and artificial intelligence models, this paper constructs a stock return influencing factor analysis model to statistically describe the sample data and factor data, and tests the applicability of the five-factor model for performance evaluation of mixed stocks. In addition, this article combines the actual situation to carry out data simulation analysis and uses a five-factor analysis model to carry out quantitative research on stock returns. Through data simulation analysis, we can see that the model constructed in this paper has a certain effect in the analysis of factors affecting stock returns.
Comprehensive evaluation of logistics enterprise competitiveness based on SEM model
Authors: Yaxu Yang
Published: December 2020

The loose logistics market, the weak value-added service capabilities of enterprises, and the backward construction and operation of logistics networks have led to high logistics costs and low efficiency in some enterprises. In order to improve the comprehensive evaluation effect of enterprise logistics enterprise competitiveness, this paper builds a comprehensive evaluation model of logistics enterprise competitiveness based on SEM model based on machine learning technology. Moreover, in order to more accurately grasp the law of customer logistics mode selection behavior, this paper adds the adaptive value of the latent variables of the logistics mode service characteristics obtained through the SEM model to the utility function of the logistics mode to obtain the SEM-NL integrated model. In addition, starting from the analysis of the key factors affecting the competitiveness of enterprise logistics, this paper constructs an evaluation model of enterprise logistics competitiveness, and analyzes and studies the comprehensive competitiveness of enterprise logistics through two aspects of logistics actual competitiveness and logistics future development potential. The research results show that the model constructed in this paper is suitable for the comprehensive evaluation of the competitiveness of logistics enterprises.
Model of the influence of Internet finance on monetary policy based on gibbs sampling and vector autoregression
Authors: Wang Hui , Shiwang Huang
Published: December 2020

The various parts of the traditional financial supervision and management system can no longer meet the current needs, and further improvement is urgently needed. In this paper, the low-frequency data is regarded as the missing of the high-frequency data, and the mixed frequency VAR model is adopted. In order to overcome the problems caused by too many parameters of the VAR model, this paper adopts the Bayesian estimation method based on the Minnesota prior to obtain the posterior distribution of each parameter of the VAR model. Moreover, this paper uses methods based on Kalman filtering and Kalman smoothing to obtain the posterior distribution of latent state variables. Then, according to the posterior distribution of the VAR model parameters and the posterior distribution of the latent state variables, this paper uses the Gibbs sampling method to obtain the mixed Bayes vector autoregressive model and the estimation of the state variables. Finally, this article studies the influence of Internet finance on monetary policy with examples. The research results show that the method proposed in this article has a certain effect.
Research on the impact of entrepreneurship policy on employment based on improved machine learning algorithms
Authors: Qing Yang , Zejun Wang
Published: December 2020

After my country’s economy has entered a new normal, in terms of employment, which has led to the coexistence of the old and new contradictions in employment in our country and the coexistence of employment expansion and stabilization of employment. In this context, it is impossible to achieve full employment and completely eliminate unemployment by relying solely on economic growth. This paper improves traditional machine learning algorithms and builds an entrepreneurial policy analysis model based on improved machine learning to analyze the impact of entrepreneurial policies on employment. Moreover, this paper uses a projection pursuit comprehensive evaluation model optimized by genetic algorithm to conduct empirical research on entrepreneurial environment conditions. In addition, this paper verifies its rationality by regression analysis of empirical results and TEA (Entrepreneurial Activity of All Employees) index, and deeply explores the inherent laws and development characteristics of entrepreneurial environmental conditions from multiple perspectives such as time series and spatial distribution. The research results show that the method proposed in this paper is effective.
Big data precision marketing and consumer behavior analysis based on fuzzy clustering and PCA model
Authors: Liu Hongping
Published: December 2020

Precision marketing is faced with multiple levels of problems, such as pollution of the data environment and unscientific algorithms, which need to be sorted out urgently. Based on neural network technology, this paper constructs a neural network-based precision marketing model and focuses on data mining to study user churn prediction and user value enhancement, which are the two most important factors affecting marketing revenue. Moreover, this paper conducts an empirical test of the product strategy and market strategy adopted by big data precision marketing. According to the characteristics of the user population and the application scenarios of the product, this paper puts the corresponding precision marketing methods in a targeted manner and analyzes the performance of the model through experimental research. The research results show that precision marketing methods based on big data information platforms need to be more detailed and more comprehensive. At the same time, precision marketing methods need to correspond to the sensitive information characteristics of target users and consider the background and current situation of actual market execution to effectively play it role.
Performance evaluation of logistics enterprises based on non-radial and non-angle network SBM model
Authors: Cui Hailei
Published: December 2020

For the logistics transshipment center, it can combine historical data to compare performance vertically to clarify its own performance level and development trend, and clarify its own development shortcomings, and finally improve its own shortcomings to improve its performance. In order to study the performance evaluation methods of logistics enterprises, this paper builds a logistics enterprise performance evaluation system based on the non-radial and non-angle network SBM model based on machine learning algorithms. Moreover, this paper combines the idea of balanced scorecard to comprehensively analyze the operating efficiency of my country’s listed logistics companies through data envelopment analysis model, Malmquist index model and Tobit regression model. In addition, this paper uses the network SBM model to conduct a static analysis of vertical comparison of listed logistics companies in different stages and different industries and combines the Malmquist index to dynamically analyze the operating efficiency of listed logistics companies in my country from a dynamic perspective. Finally, this paper analyzes the company’s operating efficiency with examples. The results show that the model constructed in this paper has a certain effect.
Analysis of the impact of inflation expectations based on machine learning intelligent models
Authors: Lin Nan
Published: December 2020

Our country’s economic growth is overly dependent on government investment, and bank credit and money supply lack a strict monitoring mechanism. Therefore, rapid economic growth is always accompanied by inflation risks. In order to study the effect of inflation impact analysis, based on machine learning algorithms, this paper combines artificial intelligence technology to analyze the impact of inflation expectations, and constructs the central bank information disclosure index and inflation expectations index. Moreover, this paper will perform ADF unit root test on the data. In addition, after confirming that the data is stable, this paper uses the Markov Regime Transfer Vector Autoregressive (MSVAR) model and state-dependent impulse response function to test and analyze the effect of China’s central bank communication in guiding the formation of inflation expectations. Through research, we can see that the machine learning algorithm constructed in this paper has significant effects, which can provide a reference for the analysis of the impact of inflation expectations.
Model of corporate bond spread based on improved neural network
Authors: Luo Qiaoshun , Liu Xinping
Published: December 2020

The reasons for credit spreads can be divided into enterprise-specific non-systematic risks and widespread macroeconomic systemic risks. The previous traditional research mainly focused on the perspective of unsystematic risk. However, at present, more and more scholars are beginning to focus on systemic risks. Based on the neural network algorithm, this paper constructs an improved neural network-based corporate bond spread model to explore the impact of macro systemic risks on credit spreads. Based on the multi-factor no-arbitrage model, the linear relationship between the credit spread and the risk premium of each factor is obtained. At the same time, based on previous research results and observations of the current market reality, this paper identifies five important macroeconomic factors: actual economic output factors, inflation factors, stock market volatility factors, stock market return factors and inter-bank funding factors. The research results show that the model constructed in this paper has excellent performance.