bluuebunny/crossref_metadata_2025 huggingface dataset:
Uwagi o szczepieniach w czasie pandemii w Polsce
Authors: Włodarczyk Włodzimierz C.
Published: May 2022

The Vaccinations during COVID-19 pandemics in Poland

When pandemics Covid 19 hit Poland, the people’s readiness to observe the recommended rules of rational healthy behaviour was partially hampered by the lasting activities of anti-vaccination circles which were appearing at grass root level and among parliamentary politicians. These activities were supported by a component the medical persons who provided an impression of professional authority. This situation to the growing scepticism in the face of rational sanitary recommendations, the fact what was revealed the social attitudes investigations. Decision-makers’ negligence who implemented many inappropriate legislative measures also contributed to the disappointing effects. Sometimes the authorities tried to withdraw partly from this mistake - obligatory masks wearing is an example - but such facts did not strengthen people’s willingness to follow recommendations. The authorities abandoned its concern of employees and clients health and refused to equip the management with the rights to check up their vaccination status. Following the same line the Government confirmed the Universities could not verify the students’ vaccination status or implement any restrictions for unvaccinated. The rectors trying to undertake any measures were criticised.

It is justified to assert that decision-makers’ mistakes contributed at least partially to smaller efficiency anti-pandemic interventions, than this was potentially possible.
Ocena wpływu pandemii Covid-19 na realizację świadczeń rehabilitacyjnych finansowanych przez NFZ w Polsce w 2020 roku
Authors: Mrożek-Gąsiorowska Magdalena A. , Okarmus Paulina
Published: May 2022

Assessment of the impact of the Covid-19 pandemic on the realization of rehabilitation services financed by NFZ in Poland in 2020.

The National Health Fund finances rehabilitation services contracted in two scopes, therapeutic rehabilitation and health resort treatment. The aim of the study is to assess the impact of the Covid-19 pandemic on the realization of rehabilitation services financed by the National Health Fund in Poland in 2020 compared to the previous years (2016-2019). The paper also discusses the implementation of successive regulations regarding rehabilitation during Covid-19 pandemic in Poland in 2020. Based on the analysis, it was shown that the number of patients who benefited from rehabilitation services in Poland financed by the National Health Fund decreased by 17% in the case of services in the field of therapeutic rehabilitation in 2020 compared to 2019 (the largest decrease, amounting to 80%, was observed in the case of pulmonary rehabilitation provided in the conditions of a day center or ward) and by 50% in the case of health resort treatment services.
On the degree of approximation of continuous functions by a linear transformation of their Fourier series
Authors: Krasniqi Xhevat Z.
Published: May 2022

In this paper, we have proved four theorems on the degree of approximation of
continuous functions by matrix means of their Fourier series which is expressed
in terms of the modulus of continuity and a non-negative mediate function.
EXTRINSIC UPPER BOUNDS THE FIRST EIGENVALUE OF THE p-STEKLOV PROBLEM ON SUBMANIFOLDS
Authors: Roth Julien
Published: May 2022

We prove Reilly-type upper bounds for the first non-zero eigen-value of the Steklov problem associated with the p-Laplace operator on sub-manifolds with boundary of Euclidean spaces as well as for Riemannian products R × M where M is a complete Riemannian manifold.
Invariance analysis and some new exact analytic solutions of the time-fractional coupled Drinfeld-Sokolov-Wilson equations
Authors: Chauhan Astha  , Arora Rajan
Published: May 2022

In this work, the fractional Lie symmetry method is used to find the exact solutions of the time-fractional coupled Drinfeld-Sokolov-Wilson equations with the Riemann-Liouville fractional derivative. Time-fractional coupled Drinfeld-Sokolov-Wilson equations are obtained by replacing the first-order time derivative to the fractional derivatives (FD) of order $\alpha$ in the classical Drinfeld-Sokolov-Wilson (DSW) model. Using the fractional Lie symmetry method, the Lie symmetry generators are obtained. With the help of symmetry generators, FCDSW equations are reduced into fractional ordinary differential equations (FODEs) with Erd$\acute{e}$lyi-Kober fractional differential operator. Also, we have obtained the exact solution of FCDSW equations and shown the effects of non-integer order derivative value on the solutions graphically. The effect of fractional order $\alpha$ on the behavior of solutions is studied graphically. Finally, new conservation laws are constructed along with the formal Lagrangian and fractional generalization of Noether operators. It is quite interesting the exact analytic solutions are obtained in explicit form.
A generalization of certain associated Bessel functions in connection with a group of shifts
Authors: Choi J. , Shilin I. A.
Published: May 2022

Considering the kernel of an integral operator intertwining two realizations
of the group of motions of the pseudo-Euclidian space, we derive two formulas
for series containing Whittaker's functions or Weber's parabolic cylinder
functions. We can consider this kernel as a special function. Some particular
values of parameters involved in this special function are found to coincide
with certain variants of Bessel functions. Using these connections, we also
establish some analogues of orthogonality relations for Macdonald and Hankel
functions.
Non-monotone target sets for threshold values restricted to $0$, $1$, and the vertex degree
Authors: Baste Julien , Ehard Stefan , Rautenbach Dieter
Published: May 2022

We consider a non-monotone activation process $(X_t)_{t\in\{ 0,1,2,\ldots\}}$
on a graph $G$, where $X_0\subseteq V(G)$, $X_t=\{ u\in V(G):|N_G(u)\cap
X_{t-1}|\geq \tau(u)\}$ for every positive integer $t$, and $\tau:V(G)\to
\mathbb{Z}$ is a threshold function. The set $X_0$ is a so-called non-monotone
target set for $(G,\tau)$ if there is some $t_0$ such that $X_t=V(G)$ for every
$t\geq t_0$. Ben-Zwi, Hermelin, Lokshtanov, and Newman [Discrete Optimization 8
(2011) 87-96] asked whether a target set of minimum order can be determined
efficiently if $G$ is a tree. We answer their question in the affirmative for
threshold functions $\tau$ satisfying $\tau(u)\in \{ 0,1,d_G(u)\}$ for every
vertex~$u$. For such restricted threshold functions, we give a characterization
of target sets that allows to show that the minimum target set problem remains
NP-hard for planar graphs of maximum degree $3$ but is efficiently solvable for
graphs of bounded treewidth.
Separating layered treewidth and row treewidth
Authors: Bose Prosenjit , Dujmović Vida , Javarsineh Mehrnoosh , Morin Pat , Wood David R.
Published: May 2022

Layered treewidth and row treewidth are recently introduced graph parameters
that have been key ingredients in the solution of several well-known open
problems. It follows from the definitions that the layered treewidth of a graph
is at most its row treewidth plus 1. Moreover, a minor-closed class has bounded
layered treewidth if and only if it has bounded row treewidth. However, it has
been open whether row treewidth is bounded by a function of layered treewidth.
This paper answers this question in the negative. In particular, for every
integer $k$ we describe a graph with layered treewidth 1 and row treewidth $k$.
We also prove an analogous result for layered pathwidth and row pathwidth.
Analysis of the implicit Euler time-discretization of passive linear descriptor complementarity systems
Authors: Brogliato Bernard , Rocca Alexandre
Published: May 2022

paper 7269

This article is largely concerned with the time-discretization of descriptor-variable systems coupled to with complementarity constraints. They are named descriptor-variable linear complementarity systems (DVLCS). More speci cally passive DVLCS with minimal state space representation are studied. The Euler implicit discretization of DVLCS is analysed: the one-step non-smooth problem (OSNSP), that is a generalized equation, is shown to be well-posed under some conditions. Then the convergence of the discretized solutions is studied. Several examples illustrate the applicability and the limitations of the developments.
Enumerating Answers to First-Order Queries over Databases of Low Degree
Authors: Durand Arnaud , Schweikardt Nicole , Segoufin Luc
Published: May 2022

A class of relational databases has low degree if for all $\delta>0$, all but
finitely many databases in the class have degree at most $n^{\delta}$, where
$n$ is the size of the database. Typical examples are databases of bounded
degree or of degree bounded by $\log n$.
It is known that over a class of databases having low degree, first-order
boolean queries can be checked in pseudo-linear time, i.e.\ for all
$\epsilon>0$ in time bounded by $n^{1+\epsilon}$. We generalize this result by
considering query evaluation.
We show that counting the number of answers to a query can be done in
pseudo-linear time and that after a pseudo-linear time preprocessing we can
test in constant time whether a given tuple is a solution to a query or
enumerate the answers to a query with constant delay.
Circular Proofs as Session-Typed Processes: A Local Validity Condition
Authors: Derakhshan Farzaneh , Pfenning Frank
Published: May 2022

Proof theory provides a foundation for studying and reasoning about
programming languages, most directly based on the well-known Curry-Howard
isomorphism between intuitionistic logic and the typed lambda-calculus. More
recently, a correspondence between intuitionistic linear logic and the
session-typed pi-calculus has been discovered. In this paper, we establish an
extension of the latter correspondence for a fragment of substructural logic
with least and greatest fixed points. We describe the computational
interpretation of the resulting infinitary proof system as session-typed
processes, and provide an effectively decidable local criterion to recognize
mutually recursive processes corresponding to valid circular proofs as
introduced by Fortier and Santocanale. We show that our algorithm imposes a
stricter requirement than Fortier and Santocanale's guard condition, but is
local and compositional and therefore more suitable as the basis for a
programming language.
Educational Leadership: Islamic Religious, Philosophy, Psychology, and Sociology Perspectives
Authors:   Lecturer, Islamic Education Study Program, Faculty of Islamic Religion, Universitas Majalengka, West Java, Indonesia, Pratomo Herdianto Wahyu
Published: May 2022

Leadership is a complex and challenging task requiring a thorough study in this area. The quality of leadership determines educational outcomes in schools. Quality leadership indicators understand the meaning of leadership based on Islamic religious, philosophy, psychology, and sociology perspectives. This study examines educational leadership based on Islamic religious, philosophy, psychology, and sociology perspectives. This study used a library research design by studying references from books and journals related to leadership. In the Islamic religious perspective, educational leadership is a mandate that must be carried out correctly and accounted for by humans and Allah. Leadership that does not work professionally and proportionately is a betrayal of Allah and the Prophet. According to a philosophical perspective, in making decisions, educational leaders must use the right way of thinking to avoid missed decisions that affect school education outcomes. Psychologically a person's leadership style affects the process he lives in everyday life because it is a fundamental human nature from birth to death, so factors from within himself heavily influence his leadership style. Based on a sociological perspective, educational leadership must be able to answer the social challenges of the academic community as the times change.
Penggunaan Flipped Classroom Dalam Pengajaran dan Pembelajaran Matematik : Suatu Tinjauan Sistematik
Authors: Apparao Nageswari Yellapa , Maat Siti Mistima
Published: May 2022

Pelbagai kaedah teknologi telah digunakan secara meluas untuk membantu dalam pendidikan matematik. Salah satu kaedah terkini ialah Flipped Classroom yang merupakan satu inovasi dalam pengajaran dan pembelajaran Matematik. Justeru, kajian literatur yang sistematik ini dijalankan untuk mensintesiskan data empirikal yang berkaitan tentang pelaksanaan kaedah flipped classroom dalam pendidikan matematik dalam tempoh 2017 - 2021. Tujuan kajian ini adalah untuk mengenal pasti tahap pencapaian pelajar serta persepsi guru dan pelajar terhadap penggunaan flipped classroom dalam matematik. Pangkalan data SCOPUS dan WOS digunakan untuk mendapatkan artikel yang berkaitan tentang penggunaan flipped classroom dalam pendidikan matematik. Lima kriteria dalam kajian ini adalah tahun penerbitan, jenis bahan rujukan, bahasa, metodologi serta bidang kajian artikel jurnal. Terdapat 21 artikel dianalisis dan telah dipilih berlandaskan lima kriteria tersebut. Kata kunci seperti flipped classroom, mathematics flipped classroom dan inverted classroom digunakan dalam kajian ini. Persepsi guru dan pelajar turut dikaji dari segi penggunaan, sikap, amalan dan penglibatan dalam penggunaan flipped classroom bagi mata pelajaran matematik. Analisis kajian menunjukkan penggunaan flipped classroom dalam matematik banyak dikaji di negara-negara luar seperti Indonesia, Spain dan Switzerland. Dapatan kajian menunjukkan bahawa penggunaan flipped classroom meningkatkan pencapaian pelajar dalam matematik. Guru dan pelajar turut menunjukkan persepsi yang positif terhadap penggunaan flipped classroom dalam matematik. Hasil kajian ini diharapkan memberi maklumat yang jelas tentang keberkesanan penggunaan flipped classroom dalam pengajaran dan pembelajaran matematik.
Do Crime Rates Spike After a Democrat Is Elected President?
Authors: Shaughnessy Giulia , Beadle Katherine D. , O'Dell Sarah F. , Smith Raeanne N. , Sommers Paul M.
Published: May 2022

The authors examine state-level violent and property crime rates (as well as rates for murder, rape, and burglary) across all 50 states (including the District of Columbia) and within the four Census regions one year before and after U.S. presidential elections in 2008, 2012, and 2016.  Violent and property crime rates in all states decreased significantly after Barack Obama’s (a Democrat’s) election in 2008 and re-election in 2012.  Murder rates decreased significantly after both election years and burglary rates decreased significantly after 2012.  Property crime rates also decreased significantly the year after Donald J. Trump’s (a Republican’s) election in 2016.  But, rape rates were significantly higher in all states and murder rates were significantly higher in the West.
Давлат – жамият ижтимоий ҳаёти ва фаолияти ташкил этилишининг ноёб шакли
Authors: Тўхтасинов Бобомурод
Published: May 2022

Ушбу мақолада давлат ва жамият ўртасидаги ўзаро ички боғлиқлик ҳамда мулоқот, ўзаро бурч ва бу ҳолатда давлат олдида турган муҳим вазифалар, жамият ижтимоий ҳаёти ва фаолиятини уюштиришда давлатнинг муҳим ўрни ҳақида сўз боради.
Оммавий-маданий тадбирларнинг назарий асослари
Authors: Нажметдинова Мавлуда
Published: May 2022

Мақолада оммавий-маданий тадбирларнинг назарий асослари, тадбирларнинг мазмун-моҳияти ва уларнинг жамиятдаги ўрни ҳамда уларнинг мақсад ва вазифалари атрофлича таҳлил қилинади. Шу билан бирга, оммавий-маданий тадбирларнинг ёшлар маънавий дунёқарашиги таъсири масаласи кўриб чиқилади.
Assessing the Levels of Anger and Coping Behaviour among BSc Assessing the Levels of Anger and Coping Behaviour among BSc Assessin Assessing the Levels of Anger and Coping Behaviour among BSc i h l f dC i h i S g gp the Levels of Anger and Co Si hi png g Behaviour among BSc Nursing and GNM Students in MOH College of Nursing, Nursing and GNM Students in MOH College of Nursing, Nursing and GNM Students in MOH College of Nursing, i d G S d i O C ll f i g g and GNM Students in MOH Colle G S OC d i O C ge of Nursing, Ludhiana, Punjab
Authors: Sharma Kanika , Preet Kaur Komal , Kaur Manpreet
Published: May 2022

The study was undertaken to assess the anger and coping behaviours adopted by nursing students. A comparative study was conducted among 90 BSc Nursing students and 90 GNM students. Simple random sampling technique by lottery method was used for selecting the sample. Level of anger was assessed by Clinical Anger Scale (CAS) and Structured Coping Behaviour Checklist was used to assess the coping behaviours adopted by nursing students. The finding revealed that majority of BSc Nursing and GNM students had minimal level of anger and adopt the adaptive behaviours to tide over the angry feelings. There was moderately negative correlation between anger and coping behaviours. Gender had statistically significant effect on anger and coping behaviours in both the groups at the level of p<0.05.
Magnitude of Nurse Quackery in Private Healthcare Facilities in Punjab
Authors: K Sharma Suresh , Parihar Silvia
Published: May 2022

In this exploratory study, conducted in 53 private nursing homes of randomly selected cities of Punjab State, a total of 218 participants were interviewed face-to-face. Data was analysed and presented using descriptive and inferential statistics. Surprisingly half of the subjects (50.9%) had not obtained any nursing qualification / training. Out of them, 60.3 percent were having lesser than higher secondary qualification, 9.9 percent were academic graduates and 29.7 percent were having paramedical training. Out of all the nurses working in these private healthcare facilities, 18.7 percent of them were not registered with State Nursing Council and only 10.1 percent were having nursing association membership because of the unawareness. Moreover, nurses and nurse quacks were enjoying nearly equal amount of pay wages, allowances and fringe benefits. It is concluded that significant numbers of nurse quacks are practicing nursing in private healthcare facilities. Therefore, it is recommended that either Government of India passes a bill on nurse practice Act or empowers the existing nursing statuary / regulatory bodies such as Indian Nursing Council to control this menace in a country where more than 75 percent people depend on private healthcare facilities.
Effects of Mindfulness-Based Stress Reduction on Blood Pressure (MBSR) Among Patients with Type-2 Diabetes - A Randomised Pilot Study
Authors: Kumar Sasi , Lathif Fathima , Raghavan Vijaya
Published: May 2022

Hypertension affects approximately 70 percent of patients with diabetes. Diabetic mellitus with elevated blood pressure is a stressful health problem for middle aged and older adults. Mindfulness-Based Stress Reduction (MBSR) has been shown to decrease the blood pressure for individual with diabetes. Therefore the randomised pilot study was conducted to evaluate the effects of MBSR on blood pressure among type 2 diabetes, aged 35-60 years in a selected rural community, Bangalore. Forty participants were selected by simple random sampling method and equally randomised into experimental and control groups. Blood pressure was measured at baseline and at the end of the intervention. Experimental group had undergone MBSR training session, whereas control group did not receive any training. The study results showed that MBSR was effective in reducing the systolic blood pressure and it was found statistically significant (p=0.018). But there was no change in diastolic blood pressure in both groups. Hence it was statistically not significant (p=0.119). The study concluded that MBSR programme was effective in controlling blood pressure of individuals with type 2 diabetes.
Content Based Image Retrieval Using Artificial Neural Network
Authors: Prof. Dr. D. R. Dhotre  , Disha Gupta  , Prajwal Gawhale  , Gunjan Bhagat  , Ayush Rathod  , Bharatkumar Kedia
Published: May 2022

Digital Image Processing domain is constantly contributing to make digital era more concise. Specifically Image Retrieval is the trending research area now-a-days. The main problem is, with the increasing volume of digital data the complexity of searching a specific image and retrieving the particular data associated with it is increasing. In recent years the content based image retrieval system has been developing at enormous speed. This paper color , gray level co-occurrence and histogram features are obtain better retrieval efficiency from large database using these feature vectors near about similarly matched images are retrieved. We have retrieved using Euclidian distance and ANN, among of both ANN Shows better result compare to Euclidian Distance based image retrieval.
Performance Evaluation of 256 PSK Modulation over Various Channels for MIMO –OFDM Wireless System using Receive Beamforming
Authors: Prof. Praveen P. Likhitkar
Published: May 2022

The smart antennas are widely used for wireless communication, because it has a ability to increase the coverage and capacity of a communication system. Smart antenna performs two main functions such as direction of arrival estimation (DOA) and beam forming. Using beam forming algorithm smart antenna is able to form main beam towards desired user and null in the direction of interfering signals. In this project Direction of arrival (DOA) is estimated by using MUSIC algorithm. Receive Beam forming is performed by using LMS and LLMS algorithm .In this Paper, in order to perform secure transmission of signal over wireless communication we have used chaotic sequences. This paper evaluates the performance 256PSK over Different channels for MIMO-OFDM wireless system using beam forming with and without LMS and LLMS algorithm. The simulations are carried out using MATLAB.
Deep Learning for Diabetic Retinopathy Disease
Authors: Aditya Hingmire  , Swati Thite
Published: May 2022

Diabetic Retinopathy (DR) is a human eye disease that affects diabetics and damages their retina, potentially leading to blindness in the long term. DR has been manually tested by ophthalmologists until now and is a time- consuming process. As a result, this job (project) will focus on analyzing various DR levels using Deep Learning (DL), which is a derivative of Artificial Intelligence (AI). We used an enormous dataset of around 3662 train images to train a model called DenseNet to automatically detect the DR point, which is then categorized into high resolution fundus images. The dataset we're using is free to use on Kaggle. There are five different DR stages: 0, 1, 2, 3, and 4. the input parameters in this paper are the patient's fundus eye pictures. The features of fundus images of the eye will be extracted by a qualified model (DenseNet Architecture), and then the activation function will provide the output. The precision of this architecture for DR detection was 0.9611 (quadratic weighted kappa score of 0.8981). Finally, we compare the two CNN architectures, the VGG16 architecture and the DenseNet121 architecture.
Clinical presentation, radiological findings and treatment options in Hughes-Stovin syndrome
Authors: Kechida Melek , Daadaa Syrine , Jomaa Walid
Published: May 2022

Hughes-Stovin syndrome is a rare disease characterized by thrombophlebitis associated with arterial or bronchial aneurysms. Even though it was described first in 1911, it is scarcely reported in the literature. Hughes-Stovin syndrome diagnosis is based on clinical manifestations as well as radiological findings. There are no validated criteria or specific laboratory findings to confirm the diagnosis. Computed tomography pulmonary angiography remains the gold standard for the diagnosis and follow-up of radiological findings, as they were recently described in a critical analysis of the largest cohort in the literature.

The aim of this review is to draw attention to this rare but potentially fatal disease and to discuss its therapeutic options.
Tocilizumab as a first-line biologic treatment in rheumatoid
arthritis patients – the impact of concomitant methotrexate
treatment and Rheumatic Disease Comorbidity Index on
the clinical response – results from the multicenter observational
ACT-POL study
Authors: Stajszczyk Marcin , Jeka Sławomir , Juś Anna , Pawlak-Buś Katarzyna
Published: May 2022

Objectives

According to the EULAR recommendations, remission or low disease activity (LDA) in rheumatoid arthritis should be achieved by a maximum of 6 months (M6) of treatment. Data on the use of tocilizumab (TCZ) as first-line biologic treatment in rheumatoid arthritis (RA) in routine clinical practice in Poland are lacking.

Material and methods

This multicenter, non-interventional, prospective, observational study recruited adults, presenting with moderate-to-severe RA, showing an inadequate response or intolerance to disease-modifying antirheumatic drugs, where TCZ was the first-line biologic treatment. The effectiveness of TCZ was assessed by the proportion of patients achieving remission and low disease activity following 6 months of treatment with intravenous TCZ. The impact of comorbidities on treatment outcomes was measured using the Rheumatic Disease Comorbidity Index (RDCI).

Results

Total remission rates at months 3 and 6 were 6% and 31%, respectively. Low disease activity was reported in 10% and 92% of the patients at 3 and 6 months, respectively. The response was comparable between TCZ as monotherapy and in combination with methotrexate. Mean DAS28 decreased from 6.61 at baseline to 4.27 at the scheduled time of the assessment (3 and 6 months). The Rheumatic Disease Comorbidity Index was not correlated with the number of patients achieving LDA at M3 and M6 or remission rates at M6. Remission rates correlated with RDCI at M3. A total of 114 adverse events were reported in 61 patients, among which five were considered as serious.

Conclusions

The study confirms the effectiveness and safety of TCZ in real-world settings as a first-line biologic treatment in patients with moderate-to-severe RA. Importantly, comorbidities do not affect the results of 6-month treatment with TCZ, that is, the optimal time to achieve at least LDA. Our results may improve the effects of RA therapy in Poland, especially in patients with comorbidities and those who, for various reasons, cannot receive optimal treatment with methotrexate.
Prophylaxis of occipital pressure sores in patients after elective spinal surgery in a pandemic condition
Authors: Tederko Piotr , Perovic-Kaczmarek Victoria , Gasik Robert , Tarnacka Beata
Published: May 2022

Background

Occipital pressure sores (OPS) are complications of the use of cervical collars. Prophylaxis of OPS in patients after cervical spinal surgery (CCS) appears to be neglected.

Material and methods

Cochrane Central, EMBASE, PubMed, SCOPUS, and Web of Science databases were searched for studies on OPS after CCS.

Results

We present the case of a patient with rheumatic arthritis who was secured with a hard collar after revision CCS and was not seen by a health professional due to the COVID-19 outbreak. The result was an OPS leading to deep tissue infection. The patient required a prolonged hospital stay and long-term antibiotic therapy. We found a lack of literature on OPS prevention in patients after CCS.

Conclusions

Patients with rheumatoid arthritis using collars after CCS are at risk of OPS. Protocols of prevention of OPS should be reviewed with respect to challenges resulting from epidemiological restrictions and accessibility of telemedical technologies.
A UNIÃO DO CONSTRUCIONISMO E INSTRUCIONISMO PARA O DESENVOLVIMENTO DE UM JOGO EDUCATIVO
Authors: Wisnieski Ramiro Tadeu , Sverzut Lacyr João , Mendez Barbara
Published: May 2022

Esse artigo relatou como as abordagens tecnológica educacionais do construcionismo e instrucionismo podem ser empregadas de forma conjunta no desenvolvimento de um jogo educativo. A união e lapidação de ambas as teorias propostas por Seymour Papert, já foi objeto de estudo em artigo recente, inclusive foi apresentada na ocasião o surgimento de uma nova teoria, ou ainda abordagem tecnológica educacional, denominada consinstrucionismo. Por conseguinte, este trabalho tem por objetivo demonstrar como um objeto de aprendizagem (OA) do tipo jogo educativo digital, pode empregar os elementos constituintes do consinstrucionismo. Portanto, são elementos fundamentais e essenciais o tetraedro da aprendizagem e as gerações do conhecimento. Nesse contexto, é apresentado o jogo denominado Consinstru, ele é um dos componentes chave da tese que está sendo desenvolvida pelos autores. Em suma, este artigo apresenta as características do jogo denominado Consinstru que aludem e se relacionam diretamente com as premissas do consinstrucionismo, em especial os pilares do tetraedro de aprendizagem: instrução, construção, reflexão, correção/otimização.
De QUAIS QUALIDADE E INOVAÇÃO ESTAMOS FALANDO?
Authors: Paniago Maria Cristina Lima , Dorsa Arlinda Cantero , Santos Rosimeire Martins Régis dos , Brum Miriam
Published: May 2022

Inovação e qualidade são termos utilizados com frequência nos documentos, normativas e designação de práticas da educação. Nos propomos a entender os conceitos a partir dos quais esses termos vêm sendo traduzidos e empregados nos discursos dos atores da cena educativa. Este artigo tem como objetivo apresentar os conceitos emergentes nos textos escolhidos sobre inovação e qualidade a partir da análise da base de dados de teses e dissertações construída pelos pesquisadores da Pesquisa intitulada “Políticas de Expansão da Educação a Distância (EaD) no Brasil: Regulação, Qualidade e Inovação em Questão”, discuti-los e problematizá-los a partir da análise do discurso de Van Dijk (2008a, 2008b, 2013). Como resultados, apontamos que não há meios de simplificar o conceito de qualidade à construção de novos espaços e estruturas bem equipadas com dispositivos tecnológicos digitais de última geração, sem a consideração dos aspectos humanos presentes na relação de trabalho e estudo de professores e alunos no que se refere ao tempo, espaço, formação dentro do horário de trabalho ou estudo, valorização dos saberes e fazeres de cada ator do processo de aprendizagem, a partir de movimentos do micro para o macro nas relações dos contextos educativos com o mundo.
Inverse modeling of the 2021 spring super dust storms in East Asia
Authors: Jin Jianbing , Pang Mijie , Segers Arjo , Han Wei , Fang Li , Li Baojie , Feng Haochuan , Lin Hai Xiang , Liao Hong
Published: May 2022

Abstract. Last spring, super dust storms reappeared in East Asia after being absent for one and a half decades. The event caused enormous losses in both Mongolia and China. Accurate simulation of such super sandstorms is valuable for the quantification of health damage, aviation risks, and profound impacts on the Earth system, but also to reveal the climatic driving force and the process of desertification. However, accurate simulation of dust life cycles is challenging, mainly due to imperfect knowledge of emissions.
In this study, the emissions that lead to the 2021 spring dust storms are estimated through assimilation of MODIS AOD and ground-based PM10 concentration data simultaneously. With this, the dust concentrations during these super storms could be reproduced and validated with concentration observations. The multi-observation assimilation is also compared against emission inversion that assimilates AOD or PM10 concentration measurements alone, and the added values are analyzed.
The emission inversion results reveal that wind-blown dust emissions originated from both China and Mongolia during spring 2021. Specifically, 19.9×106 and 37.5×106 t of particles were released in the Chinese and Mongolian Gobi, respectively, during these severe dust events. By source apportionment it was revealed that the Mongolian Gobi poses more severe threats to the densely populated regions of the Fenwei Plain (FWP) and the North China Plain (NCP) located in northern China than does the Chinese Gobi. It was estimated that 63 % of the dust deposited in FWP was due to transnational transport from Mongolia. For NCP, the long-distance transport dust from Mongolia contributes about 69 % to the dust deposition.
Homogenization of the Observatoire de Haute Provence electrochemical concentration cell (ECC) ozonesonde data record: comparison with lidar and satellite observations
Authors: Ancellet Gérard , Godin-Beekmann Sophie , Smit Herman G. J. , Stauffer Ryan M. , Van Malderen Roeland , Bodichon Renaud , Pazmiño Andrea
Published: May 2022

Abstract. The Observatoire de Haute Provence (OHP) weekly electrochemical concentration cell (ECC) ozonesonde data have been homogenized for the period 1991–2021 according to the recommendations of the Ozonesonde Data Quality Assessment (O3S-DQA) panel. The assessment of the ECC homogenization
benefit has been carried out using comparisons with other ozone-measuring ground-based instruments at the same station (lidar, surface measurements)
and with colocated satellite observations of the O3 vertical profile by Microwave Limb Sounder (MLS). The major differences between
uncorrected and homogenized ECC data are related to a change of ozonesonde type in 1997, removal of the pressure dependency of the ECC background
current and correction of internal pump temperature. The original 3–4 ppbv positive bias between ECC and lidar in the troposphere is
corrected with the homogenization. The ECC 30-year trends of the seasonally adjusted ozone concentrations are also significantly improved in both
the troposphere and the stratosphere after the ECC homogenization, as shown by the ECC/lidar or ECC/surface ozone trend comparisons. A −0.19 % yr−1 negative trend of the normalization factor (NT) calculated using independent measurements of the total ozone column (TOC) at
OHP disappears after homogenization of the ECC data. There is, however, a remaining −3.7 % negative bias in the TOC which is likely related to
an underestimate of the ECC concentrations in the stratosphere above 50 hPa. Differences between TOC measured by homogenized ECC and
satellite observations show a smaller bias of −1 %. Comparisons between homogenized ECC and OHP stratospheric lidar and MLS observations below 26 km are slightly negative (−2 %) or positive (+2 %), respectively. The comparisons with both lidar and satellite observations
suggest that homogenization increases the negative bias of the ECC to values lower than −6 % above 28 km. The reason for this bias is still unclear, but a possible explanation might be related to freezing or evaporation of the sonde solution in the stratosphere.
Reviews and syntheses: A framework to observe, understand, and project ecosystem response to environmental change in the East Antarctic Southern Ocean
Authors: Gutt Julian , Arndt Stefanie , Barnes David Keith Alan , Bornemann Horst , Brey Thomas , Eisen Olaf , Flores Hauke , Griffiths Huw , Haas Christian , Hain Stefan , Hattermann Tore , Held Christoph , Hoppema Mario , Isla Enrique , Janout Markus , Le Bohec Céline , Link Heike , Mark Felix Christopher , Moreau Sebastien , Trimborn Scarlett , van Opzeeland Ilse , Pörtner Hans-Otto , Schaafsma Fokje , Teschke Katharina , Tippenhauer Sandra , Van de Putte Anton , Wege Mia , Zitterbart Daniel , Piepenburg Dieter
Published: May 2022

Abstract. Systematic long-term studies on ecosystem dynamics are largely lacking for the East Antarctic Southern Ocean, although it is well recognized that such investigations are indispensable to identify the ecological impacts and risks of environmental change. Therefore, here we develop a framework for establishing a long-term cross-disciplinary study and argue why the eastern Weddell Sea and the easterly adjacent sea off Dronning Maud Land (WSoDML) is a well suited area for such an initiative. As in the Eastern Antarctic in general, climate and environmental change have so far been comparatively muted in this area. A systematic long-term study of its environmental and ecological state can thus provide a baseline of the current situation, an assessment of future changes, and sound data can act as a model to develop and calibrate projections. Establishing a long-term observation (LTO) and long-term ecological research (LTER) programme now would allow the study of climate-driven ecosystem changes and interactions with impacts arising from other anthropogenic activities, from their very onset. Through regular autonomous and ship-based LTO activities, changes in ocean dynamics, geochemistry, biodiversity and ecosystem functions and services can be systematically explored and mapped. This observational work should be accompanied by targeted LTER efforts, including experimental and modelling studies. This approach will provide a level of long-term data availability and ecosystem understanding that are imperative to determine, understand, and project the consequences of climate change and support a sound science-informed management of future conservation efforts in the Southern Ocean.
A Flexible Algorithm for Network Design Based on Information Theory
Authors: Thompson Rona , Pisso Ignacio
Published: May 2022

Abstract. A novel method for atmospheric network design is presented, which is based on Information Theory. The method does not require calculation of the posterior uncertainty (or uncertainty reduction) and, therefore, is computationally more efficient than methods that require this. The algorithm is demonstrated in two examples, the first looks at designing a network for monitoring CH4 sources using observations of the stable carbon isotope ratio in CH4 (δ13C), and the second looks at designing a network for monitoring fossil fuel emissions of CO2 using observations of the radiocarbon isotope ratio in CO2 (∆14CO2).
Mistranslating refuge crops: analyzing policy mobilities in the context of Indian Bt cotton production
Authors: Najork Katharina , Keck Markus
Published: May 2022

Abstract. In light of recent pink bollworm (PBW) pest infestations in several cotton-producing states in India, farmers of genetically engineered Bt cotton (Bt for Bacillus thuringiensis) have faced fierce criticism for their noncompliance with the national insect resistance management (IRM) strategy. We argue that this criticism is short-sighted and one-dimensional. Building upon the literature on policy assemblages we show that the implementation of the IRM strategy in India was seriously flawed due to government-induced mistranslations of foreign strategies in the form of policy-diluting alterations. We first show that India's IRM strategy differs substantially from successful strategies pursued in the USA or China. Second, we present results from a representative survey in the state of Telangana (n= 457) and show that India's IRM strategy neglects moral economic considerations and entrepreneurial agricultural logic that Indian cotton farmers strive for. We conclude that pink bollworm pest infestations in India are not the fault of farmers but rather the result of a mismanaged biotechnology project undertaken by the Indian government and its associated responsible ministries.
Transfer learning for landslide susceptibility modelling using domain adaptation and case-based reasoning
Authors: Wang Zhihao , Goetz Jason , Brenning Alexander
Published: May 2022

Abstract. Transferability of knowledge from well-investigated areas to a new study region is gaining importance in landslide hazard research. Considering the time-consuming compilation of landslide inventories as a prerequisite for landslide susceptibility mapping, model transferability can be key to making hazard-related information available to stakeholders in a timely manner. In this paper, we compare and combine two important transfer-learning strategies for landslide susceptibility modelling: case-based reasoning (CBR) and domain adaptation (DA). CBR gathers knowledge from previous similar situations (source areas) and applies it to solve a new problem (target area). DA, which is widely used in computer vision, selects data from a source area that has a similar distribution to the target area. We assess the performances of single- and multiple-source CBR, DA and CBR-DA strategies to train and combine landslide susceptibility models using generalized additive models (GAMs) for 10 study areas with various resolutions (1 m, 10 m and 25 m) located in Austria, Ecuador, and Italy. The performance evaluation shows that CBR and combined CBR-DA based on our proposed similarity criterion was able to achieve performances comparable to benchmark models trained in the target area itself. Particularly the CBR strategies yielded favourable results in both single- and multi-source strategies. DA tended to have overall lower performances than CBR; yet, it had promising results in scenarios when the source-target similarity was low. We recommend that future transfer learning research for landslide susceptibility modelling can build on the similarity criterion we used, as it successfully helped to achieve landslide susceptibility model transfers by discovering suitable training datasets from various regions.
EXPLORING LABEL INITIALIZATION FOR WEAKLY SUPERVISED ALS POINT CLOUD SEMANTIC SEGMENTATION
Authors: Wang P. , Yao W.
Published: May 2022

Abstract. Although a number of emerging point-cloud semantic segmentation methods achieve state-of-the-art results, acquiring fully interpreted training data is a time-consuming and labor-intensive task. To reduce the burden of data annotation in training, semiand weakly supervised methods are proposed to address the situation of limited supervisory sources, achieving competitive results compared to full supervision schemes. However, given a fixed budget, the effective annotation of a few points is typically ignored, which is referred to as weak-label initialization in this study. In practice, random selection is typically adopted by default. Because weakly supervised methods largely rely on semantic information supplied by initial weak labels, this studies explores the influence of different weak-label initialization strategies. In addition to random initialization, we propose a feature-constrained framework to guide the selection of initial weak labels. A feature space of point clouds is first constructed by feature extraction and embedding. Then, we develop a density-biased strategy to annotate points by locating highly dense clustered regions, as significant information distinguishing semantic classes is often concentrated in such areas. Our method outperforms random initialization on ISPRS Vaihingen 3D data when only using sparse weak labels, achieving an overall accuracy of 78.06% using 1‰ of labels. However, only a minor increase is observed on the LASDU dataset. Additionally, the results show that initialization with category-wise uniformly distributed weak labels is more effective when incorporated using a weakly supervised method.
LEARNING TO SIEVE: PREDICTION OF GRADING CURVES FROM IMAGES OF CONCRETE AGGREGATE
Authors: Coenen M. , Beyer D. , Heipke C. , Haist M.
Published: May 2022

Abstract. A large component of the building material concrete consists of aggregate with varying particle sizes between 0.125 and 32 mm. Its actual size distribution significantly affects the quality characteristics of the final concrete in both, the fresh and hardened states. The usually unknown variations in the size distribution of the aggregate particles, which can be large especially when using recycled aggregate materials, are typically compensated by an increased usage of cement which, however, has severe negative impacts on economical and ecological aspects of the concrete production. In order to allow a precise control of the target properties of the concrete, unknown variations in the size distribution have to be quantified to enable a proper adaptation of the concrete’s mixture design in real time. To this end, this paper proposes a deep learning based method for the determination of concrete aggregate grading curves. In this context, we propose a network architecture applying multi-scale feature extraction modules in order to handle the strongly diverse object sizes of the particles. Furthermore, we propose and publish a novel dataset of concrete aggregate used for the quantitative evaluation of our method.
MULTIRESOLUTION SEGMENTATION FOR EXTRACTING PLASTIC GREENHOUSES FROM DEIMOS-2 IMAGERY
Authors: Jiménez-Lao R. , Aguilar M. A. , Ladisa C. , Aguilar F. J. , Nemmaoui A.
Published: May 2022

Abstract. Accurate greenhouse mapping can support environment monitoring and resource management. In an object-based image analysis (OBIA) approach focused on plastic covered greenhouses (PCG) classification, the segmentation is a crucial step for the goodness of the final results. Multiresolution segmentation (MRS) is one of the most used algorithms in OBIA approaches, being greatly enabled by the advent of the commercial software eCognition. Therefore, in addition to the segmentation algorithm used, it is very important to count on tools to assess the quality of segmentation results from digital images in order to obtain the most similar segments to the real PCG objects. In this work, several factors affecting MRS such as the type of input image and the best MRS parameters (i.e., scale, compactness and shape), have been analysed. In this regard, more than 2800 segmentations focused on PCG land cover were conducted from four pre-processed Deimos-2 very high-resolution (VHR) satellite orthoimages taken in the Southeast of Spain (Almería). Specifically, one multispectral and one pansharpened Deimos-2 orthoimages, both with and without atmospheric correction were tested in this work. The free access AssesSeg command line tool, based on a modified version of the supervised discrepancy measure named Euclidean Distance 2 (ED2), was used to determine the best MRS parameters for all the VHR satellite images. According to both the supervised discrepancy measure ED2 and visual perception, the best segmentation on PCG was obtained over the atmospherically corrected pansharpened Deimos-2 orthoimage, achieving very good results.
ARM-NMS: SHAPE BASED NON-MAXIMUM SUPPRESSION FOR INSTANCE SEGMENTATION IN LARGE SCALE IMAGERY
Authors: Michel A. , Gross W. , Hinz S. , Middelmann W.
Published: May 2022

Abstract. Detecting objects in aerial scenes is a fundamental and critical task in remote sensing. However, state-of-the-art object detectors are susceptible to producing correlated scores in neighboring detections resulting in increased false positives. In addition, detection on large-scale images requires a tiling scheme with usually overlapping windows, consequently creating more double detections. Therefore, a non-maximum suppression (NMS) approach can be exploited as integral to the detection pipeline. NMS suppresses overlapping detections in regards to their scores. Current NMS algorithms filter detections by utilizing their corresponding bounding boxes. However, one can assume that comparing bounding boxes to determine the overlap of non-rectangular objects involves a certain degree of inaccuracy. Therefore, we propose Area Rescoring Mask-NMS (ARM-NMS), which uses object shapes for filtering. ARM-NMS exploits instance masks instead of the conventional boxes to eliminate detections and does not require retraining for instance segmentation pipelines. To exhibit the effectiveness of our approach, we evaluate our method on the large-scale aerial instance segmentation dataset iSaid. Our approach leads to considerable improvements for the COCO-style mAP metric of 3.3 points for segmentations and 3.5 points for boxes.