bluuebunny/crossref_metadata_2025 huggingface dataset:
Analisis Toksisitas Akut LC50-96 Jam Limbah Laundri Terhadap Ikan Mujair (Oreochromis sp.)
Authors: Kartikasari Nur Azizah , Suprayogi Dedy , Amrullah Amrullah
Published: November 2022

Laundry waste is one of the wastes that is wasted when it is disposed of continuously and continuously. This results in the destruction of aquatic ecosystems, especially fish. This study aims to determine the value of LC50-96 hours of laundry waste on tilapia fish (Oreochromis sp.). This study begins by knowing the parameters of BOD, COD, TSS, NH3, and detergent at the stage of Range Finding Test and Acute Toxicity Test. In addition, pH, temperature, and DO parameters were also tested every day. After that, acclimatization was carried out for 7 days without feeding the fish. Then continued with the range Finding test stage for 96 hours with variations of 0% (control), 5%, 10%, 20%, 40%, 60%, 80%, and 100%. The range obtained in the range Finding test stage is 20%. So that the variations in the acute toxicity test stageused include 6%, 9%, 12%, 15%, and 18%. After observing fish mortality approaching 50%, then these results were analyzed using Microsoft Excel. The LC50 value obtained in this test is 60002,5.
Visual Arts Tourism in Malaysia: A Literature Review
Authors: SER ShawHong
Published: November 2022

This article documented the development of visual arts tourism as a new field of Malaysia's tourism. Since the new millennium, the union of visual arts and tourism has been celebrated by the Ministry of Tourism, Arts & Culture as a marketing strategy to promote Malaysia as a top-of-the-mind destination art tourism destination. The research result has shown that currently there are three significant visual arts programs which are known as (1) One Malaysia Contemporary Art Tourism, (2) Art Expo Malaysia, and (3) Kuala Lumpur Biennale has been developed along with the government's strategies for partnership between visual arts, tourism and economic development. It is hoped that this paper will provide insights into an understanding of the tourism industry in Malaysia, particularly for visual arts tourism development.
Analysis of Potassium Ion (K+), Sodium Ion (Na+), and Proteins from Coconut Water Variety of Coconut and Hybrid Coconut
Authors: Alva Sagir
Published: November 2022

Analysis of potassium ion (K+), sodium ion (Na+), and proteins of Dalam coconut varieties water and Hybrid coconut varieties water have been done. The sample is green coconut which was taken simple random from Deli Tua Barat village in the regency of Deli Tua. Analysis of potassium ion (K+) and sodium ion (Na+) was determined by Atomic Absorption Spectrophotometry method (AAS) and analysis of protein was determined by the Kjeldahl method. From the result analysis of Dalam coconut varieties water contain amount potassium ion 321.60 mg/100 mL + 0,77 mg/100 mL, sodium ion 33.17 mg/100 mL + 1.85 mg/100 mL, and protein 0,18 % + 0.05 %. Whereas Hybrid coconut varieties water contain amount potassium ion 278.67 mg/100 mL + 1.53 mg/100 mL, sodium ion 31.33 mg/100 mL + 0.83 mg/100 mL, and protein 0.48 % + 0.3 %.
Dopamina: síntesis, liberación y receptores en el Sistema Nervioso Central.
Authors:   Departamento de Fisiología, Biofísica y Neurociencias, Centro de Investigación y de Estudios Avanza- dos (CINVESTAV), México, D.F., México., Bahena-Trujillo Ricardo , Flores Gonzalo ,   Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, Puebla, Puebla, México., Arias-Montaño José A.
Published: November 2022

La dopamina es el neurotransmisor catecolaminérgico más importante del Sistema Nervioso Central (SNC) de los mamíferos y participa en la regulación de diversas funciones como la conducta motora, la emotividad y la afectividad así como en la comunicación neuroendócrina. La dopamina se sintetiza a partir del aminoácido L-tirosina y existen mecanismos que regulan de manera muy precisa su síntesis y liberación. Las técnicas de clonación molecular han permitido la identificación de 5 tipos de receptores dopaminérgicos, todos ellos acoplados a proteínas G y divididos en dos familias farmacológicas denominadas D1 y D2. Los receptores de la familia D1 (subtipos D1 y D5) están acoplados a proteínas Gs y estimulan la formación de AMPc como principal mecanismo de transducción de señales. Los subtipos pertenecientes a la familia D2 (D2, D3 y D4) inhiben la formación de AMPc, activan canales de K+ y reducen la entrada de iones de Ca2+ a través de canales dependientes del voltaje, efectos mediados también por proteínas G (Gαi y Gαo). Los receptores dopaminérgicos se encuentran ampliamente distribuidos en diversas áreas del SNC (aunque de manera diferencial de acuerdo al subtipo) donde son responsables de las diversas acciones fisiológicas de la dopamina. El estudio de los sistemas y receptores dopaminérgicos del SNC ha generado gran interés, debido a que diversas alteraciones en la transmisión dopaminérgica han sido relacionadas, directa o indirectamente, con transtornos severos como la enfermedad de Parkinson y la esquizofrenia, así como con la adicción a drogas (anfetaminas y cocaína por ejemplo).
ASV-Network structure and roadmap
Authors: Cianca Andres , Barrera Carlos , Borges de Sousa Joao , Burris James , Waldmann Christoph
Published: November 2022

Report on ASV-Network structure and roadmap
Determinants of energy consumption in BRICS-T
countries
Authors: Duran Mahmut Sami , Acar Mustafa
Published: November 2022

With the emergence of globalization borders are fading out and economies are getting ever more interdependent with increasing trade volumes. As global population goes up, consumption demand reinforces increases in output. In this regard, energy can be regarded as one of the most critical inputs in the process of development and growth. Accordingly, the process of growth and industrialization has been gradually increasing the dependence of world economies on energy. Energy consumption has been steadily growing with each passing year, hence increasing the dependence on energy even further. This study examines the factors that determine energy consumption. For this purpose, the factors that determine energy consumption in BRICS-T countries (Brazil, Russia, India, China, South Africa, and Turkey) are analyzed for the period of 1992-2018. Foreign direct investments, energy prices and economic growth are taken to be the potential factors determining energy consumption. Error Correction Method (ECM) proposed by Westerland and LM Boostrap cointegration tests suggested by Westerland and Edgerton is used to test the existence of long term relationship between the series. Long term cointegration coefficients have been estimated using Common Correlated Effects Mean Group (CCEMG) estimator and Augmented Mean Group (AMG) estimator. The findings obtained from the analysis confirm that, firstly, all three variables (foreign direct investments, prices of energy, and economic growth) are critical and have a long-term relationship with energy consumption. Secondly, the series of foreign direct investments is significant in all countries subject to our panel data analysis. Economic growth series is only significant for Turkey and China. Energy prices series are found to be significant in Russia, S. Africa, and China.
Disaggregating population data for assessing progress of SDGs: methods and applications
Authors: Qiu Yue , Zhao Xuesheng , Fan Deqin , Li Songnian , Zhao Yijing
Published: November 2022

Rapid population growth has had a significant impact on society, economy and environment, which will challenge the achievement of the United Nations Sustainable Development Goals (SDGs). Spatially accurate and detailed population distribution data are essential for measuring the impact of population growth and tracking progress on the SDGs. However, most population data are evenly distributed within administrative units, which seriously lacks spatial details. There are scale differences between the population statistical data and geospatial data, which makes data analysis and needed research difficult. The disaggregation method is an effective way to obtain the spatial distribution of population with greater granularity. It can also transform the statistical population data from irregular administrative units into regular grids to characterize the spatial distribution of the population, and the original population count is preserved. This paper summarizes the research advances of population disaggregation in terms of methodology, ancillary data, and products and discusses the role of spatial disaggregation of population statistical data in monitoring and evaluating SDG indicators. Furthermore, future work is proposed from two perspectives: challenges with spatial disaggregation and disaggregated population as an Essential SDG Variable (ESDGV). 
Geospatial Disaggregation of Population Data in Supporting SDG Assessments: A Case Study from Deqing County, China
Authors: Qiu Yue , Zhao Xuesheng , Fan Deqin , Li Songnian
Published: November 2022

Quantitative assessments and dynamic monitoring of indicators based on fine-scale population data are necessary to support the implementation of the United Nations (UN) 2030 Agenda and to comprehensively achieve its 17 Sustainable Development Goals (SDGs). However, most population data are collected by administrative units, and it is difficult to reflect true distribution and uniformity in space. To solve this problem, based on fine building information, a geospatial disaggregation method of population data for supporting SDG assessments is presented in this paper. First, Deqing County in China, which was divided into residential areas and nonresidential areas according to the idea of dasymetric mapping, was selected as the study area. Then, the town administrative areas were taken as control units, building area and number of floors were used as weighting factors to establish the disaggregation model, and population data with a resolution of 30 m in Deqing County in 2016 were obtained. After analyzing the statistical population of 160 villages and the disaggregation results, we found that the global average accuracy was 87.08%. Finally, by using the disaggregation population data, indicators 3.8.1, 4.a.1, and 9.1.1 were selected to conduct an accessibility analysis and a buffer analysis in a quantitative assessment of the SDGs. The results showed that the SDG measurement and assessment results based on the disaggregated population data were more accurate and effective than the results obtained using the traditional method. 
A review of the use of geosocial media data in agent-based models for studying urban systems
Authors: Wen Richard , Li Songnian
Published: November 2022

Since the rapid growth of urban populations, the study of urban systems has gained considerable attention from researchers, decision makers, governments, and organizations. Urban systems are complex and dynamic such that they produce emergent patterns such as self-organization and nonlinearity. Agent-based modelling presents an approach to simulating and abstracting urban systems to reveal and study emergent patterns from urban-related entities. However, agent-based models are difficult to effectively optimize and validate without high quality real-world data. Geosocial media data provides agent-based models with location-enabled data at high volumes and frequencies. Integrating agent-based models with geosocial media data presents opportunities in advancing and developing studies in urban systems. This paper provides a general overview of concepts, review of recent applications, and discussion of challenges and opportunities in the context of using geosocial media data in agent-based models for urban systems. We argue that ABMs focused on studying urban systems can benefit greatly from geosocial media data, given that research moves towards standard guidelines that enable the comparison and effective use of ABMs, and geosocial media data under appropriate circumstances and applications. 
Las literacidades históricas en el campo de las prácticas sociales
Authors: Luna Solano María Elízabeth , Marín Zavala José Gabriel , López Meraz Óscar Fernando
Published: November 2022

A partir del concepto de literacidades, entendidas como prácticas sociales que abarcan todas las capacidades necesarias para el uso eficaz del lenguaje en una comunidad discursiva, mismas que representan el vínculo entre lo individual y lo social, y que varían generalmente entre grupos y sociedades, surge la necesidad de elaborar un constructo teórico en torno a las literacidades y su relación con la historia. En este ejercicio abordamos la diferencia entre literacidad en historia y literacidad histórica, centrándonos en este último concepto. Debido a que el tema ha sido poco explorado en América Latina, nos enfocamos en el diseño de un constructo que describe su significado, los elementos que la integran, y las potenciales utilidades que puede aportar en el campo educativo. Específicamente nos referimos a siete elementos que desagregamos para su análisis: lenguaje histórico, identidad histórica, memoria histórica, conciencia histórica, cultura histórica, empatía histórica y resonancia histórica. Con estos elementos proponemos un cuadro explicativo para llevar a efecto un ejercicio de tamizaje, utilizado como metáfora, a través de cuyos filtros es posible visualizar de mejor manera a las literacidades históricas.
RANCANG BANGUN APLIKASI PARIWISATA NIAS BARAT BERBASIS ANDROID MENGGUNAKAN METODE LOCATION BASED SERVICE (LBS)
Authors: Nugraha Hagi
Published: November 2022

Kabupaten Nias Barat merupakan salah satu tempat tujuan wisata di Indonesia, dimana berbagai macam wisata dapat dinikmati oleh wisatawan. Berbagai macam wisatawan datang ke Nias Barat, ada wisatawan domestik maupun wisatawan mancanegara. Selama ini rekomendasi tujuan wisata biasanya harga berasal dari informasi agen wisata atau paket wisata yang dijual oleh mereka. Penelitian ini menawarkan sebuah aplikasi android yang dapat memberikan informasi dan kemudahan pada wisatawan yang ingin mengunjungi tempat wisata, hotel dan kuliner dengan menggunakan metode Location Based Service. Aplikasi ini bertujuan untuk membuat suatu aplikasi wisata yang beroperasi pada platform Android dan berbasis lokasi sehingga mampu memberikan informasi dan rute menuju tempat-tempat wisata. Hasilnya Aplikasi ini dapat meningkatkan potensi wisatawan untuk datang berwisata ke Kabupaten Nias Barat dan mempermudah akses bagi wisatawan untuk menemukan informasi dan lokasi wisata, hotel dan kuliner.
Isolation Valve Placement Optimization of Water Distribution Networks to Reduce Vulnerability
Authors: Wéber Richárd , Huzsvár Tamás , Hős Csaba
Published: November 2022

Due to the growing pace of urbanization and the rapid expansion of the population, the utilities nowadays are facing a more challenging task than ever before, to maintain the functionality of their massive Water Distribution Networks. In this paper, three different techniques are presented for the maximization of network robustness against random pipe-bursts. This paper analyses the vulnerability of segments of WDNs from the viewpoint of the consumers that is the product of the failure rate and the relative demand loss. Topological parameters could approximate the vulnerability. During the investigation, 27 real-life WDNs were analyzed from the region of Western Hungary. In two networks, a complete isolation valve replacement optimization is presented using these low-cost topological parameters as fitness functions. It is proved that by rearranging the isolation valves of the WDN, using a standard genetic algorithm and a fast-evaluated fitness function, the nature of the vulnerability distribution can be changed to a more favorable one. This means that it is possible to increase the robustness of a WDN even without using a calibrated hydraulic model; since these topological parameters can be extracted from simple databases.
DIDÁTICA DE ORIENTAÇÃO DIALÉTICA: A DIDÁTICA NAS INSURGÊNCIAS AO NEOLIBERALISMO E NEOTECNICISMO
Authors: Braga Arruda Lilliane , Garcia Barbosa Ivone
Published: November 2022

Diante do contexto atual de retrocessos à educação brasileira, da intensificação do trabalho docente, quais são as insurgências da didática ao neoliberalismo e neotecnicismo? Para tentar responder a nossa problemática de estudo, abordamos nesse texto a didática na contemporaneidade, tendo por base uma perspectiva orientada pelo materialismo histórico (Marx, 1983; Kosik, 1969) a partir do qual dialogamos com varios autores da educação e, em especial da Didática. Reconhecemos aquela em sua especificidade, totalidade, importância e significação enquanto uma ciência da educação e do exercício profissional docente, na relação da práxis, na constituição histórica social e cultural que se consolidou historicamente como um campo ontológico e epistemológico necessário na formação docente e nas ações didático pedagógicas.  Objetivamos compreender a didática de orientação dialética e sua relação com o ensino e a aprendizagem e a didática nas insurgências do neoliberalismo e neotecnicismo, contribuindo com os estudos, as produções e os diálogos sobre a didática e sua importância na formação humana, nas ações cotidianas em instituições educativas. Compreende-se que dessa perspectiva a didática pode contribuir efetivamente na organização do trabalho pedagógico, no planejamento, como uma possibilidade de emancipação, autonomia, consciência crítica e libertadora.

Palavras chave: Didática Dialética. Neoliberalismo. Neotecnicismo.

ABSTRACT

Given the current context of setbacks to Brazilian education, of the intensification of teaching work, what are the insurgencies of didactics to neoliberalism and neotechnicism? To try to answer our problem of study, we approach in this text the didactics in contemporaneity, based on a perspective guided by historical materialism (Marx, 1983; Kosik, 1969) from which we dialogue with several authors of education and, in particular, of Didactics. We recognize that in its specificity, totality, importance and significance as a science of education and professional teaching practice, in the relationship of praxis, in the historical social and cultural constitution that has historically been consolidated as an ontological and epistemological field necessary in teacher training and in pedagogical didactic actions. We aim to understand dialectically oriented didactics and its relationship with teaching and learning and didactics in the insurgencies of neoliberalism and neotechnicism, contributing to studies, productions and dialogues about didactics and its importance in human formation, in everyday actions in educational institutions. It is understood that from this perspective, didactics can effectively contribute to the organization of pedagogical work, in planning, as a possibility of emancipation, autonomy, critical and liberating consciousness.

Keywords: Dialectical Didactics. Neoliberalism. Neotechnicism.
On Lindsay Paterson: Discipline, Method or Field? The Place of Education in the Social Sciences
Authors: McCrone David , Iannelli Cristina , Deary Ian J.
Published: November 2022

This article is the first of two relating to an event at the University of Edinburgh to mark the coming retirement of Lindsay Paterson, Professor of Education Policy. Here three of Paterson’s close colleagues outline the very substantial contribution he has made to the study of Scotland, to understanding social inequality, and measuring the contribution of education to social mobility.
Cultural Histories, Reproductive Rights and Collective Remembering: Contemporary Ireland and Scotland in a Post-Roe v. Wade World
Authors: O’Shea Helen
Published: November 2022

This contribution to the theme of ‘Scotland and the Two Irelands’ focusses upon how we collectively remember – or forget - women’s experiences around reproductive rights to contraception, sexual health, and abortion. In the context of a global backlash against women’s rights, such remembering has never been more needed.
Disturbance observer based adaptive fuzzy synchronization controller design for uncertain fractional-order chaotic systems
Authors: Chen Youjun , Wang Feng
Published: November 2022

This study premeditated the synchronization of two fractional-order chaotic systems (FOCSs) with uncertainties and external disturbances. We utilized fuzzy logic systems (FLSs) to estimate unknown nonlinearities, and implemented disturbance observers to estimate unknown bounded external disturbances. Then, a robust control term was devised to compensate for the unavoidable approximation error of the fuzzy system. In addition, a sliding mode surface was devised to construct an adaptive fuzzy sliding mode controller (AFSMC) that can guarantee that the synchronization error converges to a small neighborhood of zero. Finally, the validity of the proposed control strategy was verified via a numerical simulation.
Extracellular vesicles biogenesis, isolation, manipulation and genetic engineering for potential in vitro and in vivo therapeutics: An overview
Authors: Hadizadeh Nastaran , Bagheri Diba , Shamsara Mehdi , Hamblin Michael R. , Farmany Abbas , Xu Mengdi , Liang Zhuobin , Razi Farideh , Hashemi Ehsan
Published: November 2022

The main goals of medicine consist of early detection and effective treatment of different diseases. In this regard, the rise of exosomes as carriers of natural biomarkers has recently attracted a lot of attention and managed to shed more light on the future of early disease diagnosis methods. Here, exosome biogenesis, its role as a biomarker in metabolic disorders, and recent advances in state-of-art technologies for exosome detection and isolation will be reviewed along with future research directions and challenges regarding the manipulation and genetic engineering of exosomes for potential in vitro and in vivo disease diagnosis approaches.
Studies of functional properties of espin 1: Its interaction to actin filaments
Authors: Yang Jeong Bin , Kim Kwang Sub , Heo Jiwon , Chung Jeong Min , Jung Hyun Suk
Published: November 2022

Actin is a multifunctional biomolecule that forms not only basic structural bodies such as filopodia and lamellipodia, but also large microvilli-like organelles like stereocilia. Actin consists of four sub-domains (S1, S2, S3, and S4), and the “target-binding groove” formed between S1 and S3 is the major binding site for various actin binding proteins. Actin filament dynamics are regulated by numerous actin binding proteins with different mechanisms of actin binding, assembly, and disassembly such as actin severing, branching, and bundling. Ectoplasmic specialization protein 1 (espin 1) is an actin binding and bundling protein that is specifically implicated in the elongation and stabilization of stereocilia as a binding partner with myosin III. However, little is known about the molecular structure, actin bundling, and stabilizing mechanism of espin 1; hence, we investigated the interaction between actin and espin 1 through structural data. In this study, we first purified human espin 1 in an E. coli system following a new detergent-free approach and then demonstrated the 2D structure of full-length espin 1 using transmission electron microscopy along with Nickel nitrilotriacetic acid nanogold labeling and 2D averaging using SPIDER. Furthermore, we also determined the espin 1 binding domain of actin using a co-sedimentation assay along with gelsolin and myosin S1. These findings are not only beneficial for understanding the actin binding and bundling mechanism of espin 1, but also shed light on its elongation, stabilization, and tip-localization mechanisms with myosin III. This study thus provides a basis for understanding the molecular structure of espin 1 and can contribute to various hearing-related diseases, such as hearing loss and vestibular dysfunction.
Assessing oxygen limiting fermentation conditions for 2,3-butanediol production from Paenibacillus polymyxa
Authors: Stoklosa Ryan J. , Latona Renee J. , Johnston David B.
Published: November 2022

2,3-butanediol (2,3-BDO) is a platform chemical that can be converted to a wide array of products ranging from bio-based materials to sustainable aviation fuel. This chemical can be produced by a variety of microorganisms in fermentation processes. Challenges remain for high titer 2,3-BDO production during fermentation due to several parameters, but controlling oxygen is one of the most relevant processing parameters to ensure viable product output. This work investigated the fermentation of plant biomass sugars by the 2,3-BDO producer Paenibacillus polymyxa. Aerobic and oxygen limited fermentation conditions were initially evaluated using molasses-based media to determine cell growth and 2,3-BDO output. Similar conditions were then evaluated on hydrolysate from pretreated sweet sorghum bagasse (SSB) that contained fermentable sugars from structural polysaccharides. Fermentations in molasses media under aerobic conditions found that 2,3-BDO could be generated, but over time the amount of 2,3-BDO decreased due to conversion back into acetoin. Oxygen limited fermentation conditions exhibited improved biomass growth, but only limited suppression of 2,3-BDO conversion to acetoin occurred. Glucose depletion appeared to have a greater role influencing 2,3-BDO conversion back into acetoin. Further improvements in 2,3-BDO yields were found by utilizing detoxified SSB hydrolysate.
Reaction mechanism of atomic layer deposition of zirconium oxide using zirconium precursors bearing amino ligands and water
Authors: Xu Rui , Zhou Zhongchao , Li Jing , Zhang Xu , Zhu Yuanyuan , Xiao Hongping , Xu Lina , Ding Yihong , Li Aidong , Fang Guoyong
Published: November 2022

As a unique nanofabrication technology, atomic layer deposition (ALD) has been widely used for the preparation of various materials in the fields of microelectronics, energy and catalysis. As a high-κ gate dielectric to replace SiO2, zirconium oxide (ZrO2) has been prepared through the ALD method for microelectronic devices. In this work, through density functional theory calculations, the possible reaction pathways of ZrO2 ALD using tetrakis(dimethylamino)zirconium (TDMAZ) and water as the precursors were explored. The whole ZrO2 ALD reaction could be divided into two sequential reactions, TDMAZ and H2O reactions. In the TDMAZ reaction on the hydroxylated surface, the dimethylamino group of TDMAZ could be directly eliminated by substitution and ligand exchange reactions with the hydroxyl group on the surface to form dimethylamine (HN(CH3)2). In the H2O reaction with the aminated surface, the reaction process is much more complex than the TDMAZ reaction. These reactions mainly include ligand exchange reactions between the dimethylamino group of TDMAZ and H2O and coupling reactions for the formation of the bridged products and the by-product of H2O or HN(CH3)2. These insights into surface reaction mechanism of ZrO2 ALD can provide theoretical guidance for the precursor design and improving ALD preparation of other oxides and zirconium compounds, which are based ALD reaction mechanism.
The role of home medication storage location in increasing medication adherence for middle-aged and older adults
Authors: Gualtieri Lisa , Shaveet Eden , Estime Brandon , Patel Avi
Published: November 2022

Background

Over 50% of US adults do not take their prescriptions as prescribed, which is responsible for 33%–69% of hospital admissions and 125,000 deaths annually. Given the higher prevalence of prescription drug use among middle-aged and older adult populations, promoting medication adherence is of particular importance with these age groups. Two speculated facilitators of medication adherence are home medication storage location and the use of digital health devices.

Objective

Our objective was to use survey data to investigate the associations between medication storage location and medication adherence among adults 40 years and older. Additionally, we aimed to report preliminary findings about the associations between use of devices and medication adherence in this same population.

Methods

We conducted primary analysis of data sampled from a home medication management survey deployed in November 2021 (n = 580). We conducted exploratory analyses by way of chi2 tests and creation of bivariate logistic regression models.

Results

The most commonly used storage locations by our sample were nightstand drawers (27%), kitchen cabinets (25%), and atop bedroom nightstands (23%). Several medication storage locations were significantly associated with decreased odds of having ever forgotten to take a medication, including kitchen drawers, in refrigerators, atop bedroom nightstands, in nightstand drawers, and backpacks, purses, or bags. Two home medication storage locations were significantly associated with increased odds of having ever forgotten to take a medication: kitchen cabinets and bathroom vanities. Further, most (94%) survey respondents indicated they would be receptive to guidance about where to store their medications.

Conclusions

Given that some home medication storage locations are associated with adherence, an intervention to guide storage location selection may support increased adherence, especially with high receptivity expressed for such guidance. Increased adherence may also accrue from device usage paired with optimized home medication storage location. We plan to investigate that further, as well as how new device designs can incorporate contextual cues related to location to promote medication adherence more effectively in middle aged and older adults.
Investment opportunity of blockchain technology in the education sector of Saudi Arabia: A systematic literature review
Authors: Alshareef Nasser
Published: November 2022

The primary objective of this research is to explore the literature on blockchain technology and its investment opportunity in the education sector. Studies on the investment opportunities of blockchain technology in education have remained limited and little is known about the existing state of knowledge and practice of blockchain technology in the education sector of Saudi Arabia, especially for its sustainable development. In this study, the author tried to synthesise literature on blockchain technology to understand the difficulties and prospects of this technology in Saudi Arabia. A total of 15 empirical studies from 2017 to 2020 were reviewed. The descriptive and thematic analysis identified four types of challenges of blockchain technology in the education sector. They include leaking privacy and security, processing cost, setting the boundaries, and weakening school credentials. The review also revealed several opportunities for adopting blockchain technology such as certifying identity authentication, improving learning assessment, maintaining student records, enhancing trust, and reducing costs. Implications and recommendations related to education for sustainable development are provided accordingly.
The role of representational competencies for students’ learning from an educational video game for astronomy
Authors: Herder Tiffany , Rau Martina A.
Published: November 2022

Educational video games can engage students in authentic STEM practices, which often involve visual representations. In particular, because most interactions within video games are mediated through visual representations, video games provide opportunities for students to experience disciplinary practices with visual representations. Prior research on learning with visual representations in non-game contexts suggests that visual representations may confuse students if they lack prerequisite representational-competencies. However, it is unclear how this research applies to game environments. To address this gap, we investigated the role of representational-competencies for students’ learning from video games. We first conducted a single-case study of a high-performing undergraduate student playing an astronomy game as an assignment in an astronomy course. We found that this student had difficulties making sense of the visual representations in the game. We interpret these difficulties as indicating a lack of representational-competencies. Further, these difficulties seemed to lead to the student’s inability to relate the game experiences to the content covered in his astronomy course. A second study investigated whether interventions that have proven successful in structured learning environments to support representational-competencies would enhance students’ learning from visual representations in the video game. We randomly assigned 45 students enrolled in an undergraduate course to two conditions. Students either received representational-competency support while playing the astronomy game or they did not receive this support. Results showed no effects of representational-competency supports. This suggests that instructional designs that are effective for representational-competency supports in structured learning environments may not be effective for educational video games. We discuss implications for future research, for designers of educational games, and for educators.
CEA-FJSP: Carbon emission-aware flexible job-shop scheduling based on deep reinforcement learning
Authors: Wang Shiyong , Li Jiaxian , Tang Hao , Wang Juan
Published: November 2022

Currently, excessive carbon emission is causing visible damage to the ecosystem and will lead to long-term environmental degradation in the future. The manufacturing industry is one of the main contributors to the carbon emission problem. Therefore, the reduction of carbon emissions should be considered at all levels of production activities. In this paper, the carbon emission as a parvenu indicator is considered parallelly with the nobleman indicator, makespan, in the flexible job-shop scheduling problem. Firstly, the carbon emission is modeled based on the energy consumption of machine operation and the coolant treatment during the production process. Then, a deep reinforcement learning-based scheduling model is proposed to handle the carbon emission-aware flexible job-shop scheduling problem. The proposed model treats scheduling as a Markov decision process, where the scheduling agent and the scheduling environment interact repeatedly via states, actions, and rewards. Next, a deep neural network is employed to parameterize the scheduling policy. Then, the proximal policy optimization algorithm is conducted to drive the deep neural network to learn the objective-oriented optimal mapping from the states to the actions. The experimental results verify that the proposed deep reinforcement learning-based scheduling model has prominent optimization and generalization abilities. Moreover, the proposed model presents a nonlinear optimization effect over the weight combinations.
The analysis of the spatio-temporal differentiation characteristics of total factor productivity of maize: Introducing the perspective of financial support
Authors: Lou Sha
Published: November 2022

The problem we studied is the analysis of the spatio-temporal differentiation characteristics of total factor productivity of maize. The importance lies in that maize is one of the prominent grain crops in China, the improvement of maize production efficiency is helpful to guarantee the national food security. From the perspective of financial support, deepened the connotation of DEA model, this paper innovatively constructs the Global Malmquist index method, in view of the data of 13 major grain producing areas in China from 2007 to 2017, talks over the temporal evolution characteristics and spatial distribution modes of total factor productivity (TFP) of maize. The main results show that the TFP of maize production in China’s major grain producing areas is mostly of a high level between 2007 and 2017, revealing a fluctuating upward drift, with an average annual rate of increase of 10.7%. The conclusion we draw from the results is that as shown in the decomposition index, the variation of TFP of maize production mainly attributes to the shift of technological progress. In terms of space, the TFP of maize production in the central district is the highest, the eastern and western districts are relatively low.
A comparative analysis of telomere length maintenance circuits in fission and budding yeast
Authors: Peretz Iftah , Kupiec Martin , Sharan Roded
Published: November 2022

The natural ends of the linear eukaryotic chromosomes are protected by telomeres, which also play an important role in aging and cancer development. Telomere length varies between species, but it is strictly controlled in all organisms. The process of Telomere Length Maintenance (TLM) involves many pathways, protein complexes and interactions that were first discovered in budding and fission yeast model organisms (Saccharomyces cerevisiae, Schizosaccharomyces pombe). In particular, large-scale systematic genetic screens in budding yeast uncovered a network of ≈500 genes that, when mutated, cause telomeres to lengthen or to shorten. In contrast, the TLM network in fission yeast remains largely unknown and systematic data is still lacking. In this work we try to close this gap and develop a unified interpretable machine learning framework for TLM gene discovery and phenotype prediction in both species. We demonstrate the utility of our framework in pinpointing the pathways by which TLM homeostasis is maintained and predicting novel TLM genes in fission yeast. The results of this study could be used for better understanding of telomere biology and serve as a step towards the adaptation of computational methods based on telomeric data for human prognosis.
Experimental investigation on seismic performance of plain engineered cementitious composite beams
Authors: Tian Likang , Tan Yan , Wei Xiao-Xiao , Ouyang Li-Jun , Xu Ran , Yu Jiang-Tao
Published: November 2022

The authors proposed using plain engineered cementitious composite (ECC) in construction without aligned reinforcement. In this study, ECC with a tensile strain capacity of up to 10% was produced, which has a comparable deformability level to steel reinforcement. To demonstrate the feasibility of plain ECC construction, five plain ECC beams and two steel reinforced concrete reference beams were prepared, and four-point bending reversed cyclic loading tests were conducted on the beam specimens. The experimental tests indicated that the plain ECC beams showed more stable hysteresis loops with improved energy dissipation capacity, deformation restoring capacity, and lower stiffness degradations than normal RC beams. Two categories of failure modes were observed, i.e., flexural failure mode and shear failure mode. With the increase in the shear span ratio, the failure mode of ECC beams changed from shear failure to flexural failure. Additionally, the increase in sectional dimension had a positive influence on the stiffness and energy dissipation capacity of ECC beams. It is experimentally verified that the plain ECC beams have sufficient load-bearing capacity under static and seismic loading.
Efficient-ECGNet framework for COVID-19 classification and correlation prediction with the cardio disease through electrocardiogram medical imaging
Authors: Nawaz Marriam , Nazir Tahira , Javed Ali , Malik Khalid Mahmood , Saudagar Abdul Khader Jilani , Khan Muhammad Badruddin , Abul Hasanat Mozaherul Hoque , AlTameem Abdullah , AlKhathami Mohammed
Published: November 2022

In the last 2 years, we have witnessed multiple waves of coronavirus that affected millions of people around the globe. The proper cure for COVID-19 has not been diagnosed as vaccinated people also got infected with this disease. Precise and timely detection of COVID-19 can save human lives and protect them from complicated treatment procedures. Researchers have employed several medical imaging modalities like CT-Scan and X-ray for COVID-19 detection, however, little concentration is invested in the ECG imaging analysis. ECGs are quickly available image modality in comparison to CT-Scan and X-ray, therefore, we use them for diagnosing COVID-19. Efficient and effective detection of COVID-19 from the ECG signal is a complex and time-taking task, as researchers usually convert them into numeric values before applying any method which ultimately increases the computational burden. In this work, we tried to overcome these challenges by directly employing the ECG images in a deep-learning (DL)-based approach. More specifically, we introduce an Efficient-ECGNet method that presents an improved version of the EfficientNetV2-B4 model with additional dense layers and is capable of accurately classifying the ECG images into healthy, COVID-19, myocardial infarction (MI), abnormal heartbeats (AHB), and patients with Previous History of Myocardial Infarction (PMI) classes. Moreover, we introduce a module to measure the similarity of COVID-19-affected ECG images with the rest of the diseases. To the best of our knowledge, this is the first effort to approximate the correlation of COVID-19 patients with those having any previous or current history of cardio or respiratory disease. Further, we generate the heatmaps to demonstrate the accurate key-points computation ability of our method. We have performed extensive experimentation on a publicly available dataset to show the robustness of the proposed approach and confirmed that the Efficient-ECGNet framework is reliable to classify the ECG-based COVID-19 samples.
Diagnostic accuracy of artificial intelligence for detecting gastrointestinal luminal pathologies: A systematic review and meta-analysis
Authors: Parkash Om , Siddiqui Asra Tus Saleha , Jiwani Uswa , Rind Fahad , Padhani Zahra Ali , Rizvi Arjumand , Hoodbhoy Zahra , Das Jai K.
Published: November 2022

Background

Artificial Intelligence (AI) holds considerable promise for diagnostics in the field of gastroenterology. This systematic review and meta-analysis aims to assess the diagnostic accuracy of AI models compared with the gold standard of experts and histopathology for the diagnosis of various gastrointestinal (GI) luminal pathologies including polyps, neoplasms, and inflammatory bowel disease.

Methods

We searched PubMed, CINAHL, Wiley Cochrane Library, and Web of Science electronic databases to identify studies assessing the diagnostic performance of AI models for GI luminal pathologies. We extracted binary diagnostic accuracy data and constructed contingency tables to derive the outcomes of interest: sensitivity and specificity. We performed a meta-analysis and hierarchical summary receiver operating characteristic curves (HSROC). The risk of bias was assessed using Quality Assessment for Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Subgroup analyses were conducted based on the type of GI luminal disease, AI model, reference standard, and type of data used for analysis. This study is registered with PROSPERO (CRD42021288360).

Findings

We included 73 studies, of which 31 were externally validated and provided sufficient information for inclusion in the meta-analysis. The overall sensitivity of AI for detecting GI luminal pathologies was 91.9% (95% CI: 89.0–94.1) and specificity was 91.7% (95% CI: 87.4–94.7). Deep learning models (sensitivity: 89.8%, specificity: 91.9%) and ensemble methods (sensitivity: 95.4%, specificity: 90.9%) were the most commonly used models in the included studies. Majority of studies (n = 56, 76.7%) had a high risk of selection bias while 74% (n = 54) studies were low risk on reference standard and 67% (n = 49) were low risk for flow and timing bias.

Interpretation

The review suggests high sensitivity and specificity of AI models for the detection of GI luminal pathologies. There is a need for large, multi-center trials in both high income countries and low- and middle- income countries to assess the performance of these AI models in real clinical settings and its impact on diagnosis and prognosis.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=288360], identifier [CRD42021288360].
Endoscopic removal of a massive trichobezoar in a pediatric patient by using a variceal ligator cap: A case report and literature review
Authors: Lu Dan , Berglund Björn , Xia Yi , Jain Ajay , Gu Qing , Ji Feng
Published: November 2022

A trichobezoar is commonly formed in the gastrointestinal tract by ingestion of an individual’s own hair. A trichobezoar formed by hair and artificial materials constitutes a rare etiology scarcely reported in the current literature. A mixture with hair-like synthetic fibers not only increases the risk for trichobezoar formation but also makes it more difficult for endoscopic removal. Herein, we report on a case in which a trichobezoar, caused by the consumption of human hair and synthetic yarn, was successfully removed endoscopically with a variceal ligator cap without further complications for the patient. This case report aims to raise awareness among endoscopists that using a variceal ligator cap may be a suitable option in the management of large trichobezoars containing synthetic fibers.
Transient ciliochoroidal detachment after microhook ab interno trabeculotomy: Its frequency and potential risk factors
Authors: Miyako Fumiya , Hirooka Kazuyuki , Onoe Hiromitsu , Okada Naoki , Okumichi Hideaki , Kiuchi Yoshiaki
Published: November 2022

Purpose

To investigate ciliochoroidal detachment (CCD) frequency and risk factors after performing microhook ab interno trabeculotomy (μLOT).

Methods

A retrospective evaluation of 62 eyes of 62 patients who underwent μLOT and were subsequently examined by anterior-segment optical coherence tomography (AS-OCT) found CCD at 1 day, and 1 and 2 months after surgery.

Results

In the 62 patients (mean age 67.3 ± 13.9 years), AS-OCT detected CCD in 18 eyes (29%) at 1 day after surgery, which disappeared within 1 month. Comparisons between the CCD vs. the non-CCD group showed the mean IOPs were 11.7 ± 1.5 mmHg vs. 14.4 ± 1.0 mmHg at day 1 (P = 0.13), 12.2 ± 1.1 mmHg vs. 14.8 ± 0.7 mmHg at day 7 (P = 0.06), 12.2 ± 0.7 mmHg vs. 12.9 ± 0.5 mmHg at 1 month (P = 0.48), and 11.3 ± 0.7 mmHg vs. 12.7 ± 0.5 mmHg at 2 months (P = 0.09). For postoperative IOP, there were no significant differences observed. After undergoing μLOT, multiple regression analysis demonstrated that the CCD development might be influenced by the presence of a thinner central corneal thickness.

Conclusion

Approximately one-third of all patients exhibited CCD after μLOT. A thinner central corneal thickness was found to be a risk factor for developing CCD.
Integrative bioinformatics analysis to explore a robust diagnostic signature and landscape of immune cell infiltration in sarcoidosis
Authors: Duo Mengjie , Liu Zaoqu , Li Pengfei , Wang Yu , Zhang Yuyuan , Weng Siyuan , Zheng Youyang , Fan Mingwei , Wu Ruhao , Xu Hui , Ren Yuqing , Cheng Zhe
Published: November 2022

Background

The unknown etiology of sarcoidosis with variable clinical features leads to delayed diagnosis and limited therapeutic strategies. Hence, exploring the latent mechanisms and constructing an accessible and reliable diagnostic model of sarcoidosis is vital for innovative therapeutic approaches to improve prognosis.

Methods

This retrospective study analyzed transcriptomes from 11 independent sarcoidosis cohorts, comprising 313 patients and 400 healthy controls. The weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were performed to identify molecular biomarkers. Machine learning was employed to fit a diagnostic model. The potential pathogenesis and immune landscape were detected by bioinformatics tools.

Results

A 10-gene signature SARDS consisting of GBP1, LEF1, IFIT3, LRRN3, IFI44, LHFPL2, RTP4, CD27, EPHX2, and CXCL10 was further constructed in the training cohorts by the LASSO algorithm, which performed well in the four independent cohorts with the splendid AUCs ranging from 0.938 to 1.000. The findings were validated in seven independent publicly available gene expression datasets retrieved from whole blood, PBMC, alveolar lavage fluid cells, and lung tissue samples from patients with outstanding AUCs ranging from 0.728 to 0.972. Transcriptional signatures associated with sarcoidosis revealed a potential role of immune response in the development of the disease through bioinformatics analysis.

Conclusions

Our study identified and validated molecular biomarkers for the diagnosis of sarcoidosis and constructed the diagnostic model SARDS to improve the accuracy of early diagnosis of the disease.