Analisis Analisis Peran dan Tantangan Sukuk Hijau Bagi Ketahanan Perubahan Iklim Pada Wilayah Rentan Selama Pandemi Covid-19

Sovereign Sukuk has become a promising instrument for a country to overcome difficulties in financing government projects. Sukuk is a financial instrument for the Islamic capital market with a low level of risk. Green sukuk becomes popular since most of the conventional investment activities ignore the environment aspect. Starting in 2018, Indonesian government has developed a green sukuk scheme as a financing instrument for environmentally friendly projects to reduce the impact of global climate change. This study aims to analyze the role and challenges of green sukuk for climate change resilience in highly vulnerable areas during the Covid-19 crisis. This study is conducted through a qualitative method with a phenomenological approach. Data collections are carried out through literature studies and case studies on some climate projects in highly vulnerable areas in Indonesia. The results show that during the Covid-19 pandemic, green sukuk has contributed an important impact for climate change resilience in highly vulnerable areas. There are some challenges in the development of green sukuk. The lack of awareness of social risks as well as environmental risks have become main challenges. In the future, the decision policy makers should provide greater incentives and a more inclusive legal umbrella for green financing schemes.

FILER: a framework for harmonizing and querying large-scale functional genomics knowledge

ABSTRACT Querying massive functional genomic and annotation data collections, linking and summarizing the query results across data sources/data types are important steps in high-throughput genomic and genetic analytical workflows. However, these steps are made difficult by the heterogeneity and breadth of data sources, experimental assays, biological conditions/tissues/cell types and file formats. FILER (FunctIonaL gEnomics Repository) is a framework for querying large-scale genomics knowledge with a large, curated integrated catalog of harmonized functional genomic and annotation data coupled with a scalable genomic search and querying interface. FILER uniquely provides: (i) streamlined access to >50 000 harmonized, annotated genomic datasets across >20 integrated data sources, >1100 tissues/cell types and >20 experimental assays; (ii) a scalable genomic querying interface; and (iii) ability to analyze and annotate user’s experimental data. This rich resource spans >17 billion GRCh37/hg19 and GRCh38/hg38 genomic records. Our benchmark querying 7 × 109 hg19 FILER records shows FILER is highly scalable, with a sub-linear 32-fold increase in querying time when increasing the number of queries 1000-fold from 1000 to 1 000 000 intervals. Together, these features facilitate reproducible research and streamline integrating/querying large-scale genomic data within analyses/workflows. FILER can be deployed on cloud or local servers (https://bitbucket.org/wanglab-upenn/FILER) for integration with custom pipelines and is freely available (https://lisanwanglab.org/FILER).

Participatory surveillance for COVID-19 trends detection in Brazil

The ongoing COVID-19 pandemic has emphasized the necessity of a well-functioning surveillance system to detect and mitigate disease outbreaks. Traditional surveillance (TS) usually relies on healthcare providers and generally suffers from reporting lags that prevent immediate response plans. Participatory surveillance (PS), an innovative digital approach whereby individuals voluntarily monitor and report on their own health status via Web-based surveys, has emerged in the past decade to complement traditional data collections approaches. This study compares novel PS data on COVID-19 infection rates across nine Brazilian cities with official TS data to examine the opportunities and challenges of using the former, and the potential advantages of combining the two approaches. We find that high participation rates are key for PS data to adequately mirror TS infection rates. Where participation was high, we document a significant trend correlation between lagged PS data and TS infection rates, suggesting that the former could be used for early detection. In our data, forecasting models integrating both approaches increased accuracy up to 3% relative to a 14-day forecast horizon model based exclusively on TS data. Furthermore, we show that the PS data captures a population that significantly differs from the traditional observation. These results corroborate previous studies when it comes to the benefits of an integrated and comprehensive surveillance system, but also shed lights on its limitations, and on the need for additional research to improve future implementations of PS platforms.

KATALOGISASI KOLEKSI PERPUSTAKAAN KECIL DAERAH SINDANGLAYA

Library services are an illustration of the fulfillment of library functions. One of the services that must be provided in the library is a catalog service. A service that makes it easier for users to find the collection they need in addition to asking a reference service. The catalog has three objects as mentioned by Cutter, namely the find function, the collect function, and the select function. In addition, the existence of a catalog can facilitate librarians in the collection development process. Therefore, a catalog should be in every library. The purpose of writing is to find out whether the use of catalogs in the intended library has been effective? Has the library implemented a catalog service? Is the SLiMS application in the Library effective to use? The author uses qualitative research methods so that the results obtained can be in accordance with the facts that appear and are seen when researchers observe the state of the object, namely the Sindanglaya Small Library. With the results of the study that the Sindanglaya Regional Small Library has not applied catalog services properly, only relying on the arrangement on the bookshelves so that researchers work with managers to use online catalogs by inputting data collections from the library using the SLiMS application. , ,

La sociología a través de sus publicaciones en revistas de impacto mediante el uso de big data

La sociología como disciplina ha sido definida de formas diversas que intentan abarcar sus dominios y métodos, aunque también se ha considerado inútil intentar definirla e incluso ha sido acusada de estar fragmentada y falta de uniformidad. Al igual que las demás disciplinas científicas, la sociología se puede observar como un sistema social al estar compuesta de complejas relaciones entre actores que incluyen a investigadores, instituciones, revistas y editoriales. Esas relaciones se forman a través de comunicaciones conceptuales y conforman redes que establecen como se organiza la disciplina. Actualmente, el fenómeno del big data ofrece la posibilidad de usar grandes colecciones de datos que permiten analizar la información de los procesos sociales. En concreto, a través de las grandes fuentes de datos bibliométricas la sociología tiene a su alcance ingentes cantidades de datos para mapear y estudiar la evolución de las disciplinas científicas. En este artículo describimos la sociología de los últimos treinta años a través de las publicaciones en las revistas de impacto. Para hacer esto, se emplean datos de revistas de sociología del Journal Citation Reports ampliados con la información de los artículos del Microsoft Academic Graph. Realizamos un análisis descriptivo de las revistas, sus países de origen, lenguas, editoriales y décadas de aparición e impacto. A continuación, evaluamos la evolución temporal del número de artículos y citas, así como la coautoría y el género de los autores. Tras esto, establecemos cuatro grupos de tipos de revistas y estudiamos sus diferencias en las dimensiones anteriores mediante contrastes de hipótesis. Finalmente, representamos las relaciones entre autores y revistas usando una red de afiliación que nos permite detectar grupos de revistas que forman interesantes comunidades temáticas y geográficas. Sociology as a discipline has been defined in diverse ways that attempt to cover the breadth of its domains and methods. Nonetheless, others have considered futile trying to define the discipline and many have accused sociology to be fragmented and lacking unity. Like the other scientific disciplines, sociology can be observed as a social system made up of researchers, institutions, journals and publishers. These relationships are established via conceptual communications which form networks that establish the way in which disciplined are organized. At present, the big data phenomena offers the capacity to use large data collections to analyse social processes. Big scholarly data sources offer sociology immense quantities of data useful to map and study the evolution of scientific disciplines. In this article we characterised the last thirty years of sociology through its publications in impact factor journals. To do this, we use data about the sociology journals from Journal Citation reports augmented with article information from Microsoft Academic Graph. The analysis starts by describing the journals, countries of origin, languages, publishers, the decades in which they appeared and their impact factor. After this, we evaluate the evolution of numbers of articles and citations as well as co-authorship and gender proportion. Subsequently, we establish four groups of journal types and study their differences in the previous dimensions using hypothesis tests. Finally, we represent the relationships between authors and journals using an affiliation network that allows us to detect groups of journals that form interesting thematic and geographic communities.

PERSISTE: a mixed methods protocol to identify barriers and levers to a sustainable physical activity practice among patients with chronic disease after physical activity resumption programs

Physical activity (PA) has evidence-based benefits for physical, social and mental health, but investigation of how PA interventions for patients with chronic disease affects their PA practice up to 1 year after programmes are rare. Moreover, few studies document how the context and intervention mechanisms of PA programmes affect sustainable PA practice and its determinants. The present protocol describes a mixed methods study comparing the effectiveness and conditions for the effectiveness of two PA resumption programmes (a hospital-led and a community-based programme). Using a comparative longitudinal study, 60 patients (3-month duration) will be followed for 1 year though four data collections: before (T0) and at the end (T1) of the intervention, 6 months (T2) and 1 year (T3) after the start of the programme. The primary outcome will be PA practice in min/week and categorised as light, moderate or vigorous (using International Physical Activity Questionnaire (IPAQ)), and secondary outcomes will include sedentary time in min/week (IPAQ), quality of life evaluated though the physical and mental composite scores (‘Medical Outcome Study Short Form 12’), and enjoyment using four statements rated from 1 to 5, a high score being synonymous of enjoyment (Intrinsic Motivation Inventory). Qualitative data on further determinants of PA practice and intervention mechanisms will be collected. The expected results will offer the opportunity to understand how the intervention context contributes to a more effective, sustainable PA practice. Trial registration number: NCT04954209.

Best practices for time-resolved serial synchrotron crystallography

With recent developments in X-ray sources, instrumentation and data-analysis tools, time-resolved crystallographic experiments, which were originally the preserve of a few expert groups, are becoming simpler and can be carried out at more radiation sources, and are thus increasingly accessible to a growing user base. However, these experiments are just that: discrete experiments, not just `data collections'. As such, careful planning and consideration of potential pitfalls is required to enable a successful experiment. Here, some of the key factors that should be considered during the planning and execution of a time-resolved structural study are outlined, with a particular focus on synchrotron-based experiments.

Exploring the Teaching and Learning Indicators towards Education 4.0 in MTUN, Malaysia

MTUN has been given responsibility for producing skilled TVET workforces in the industrial sectors. Therefore, the education structure in MTUN is gradually making a transition to Education 4.0 to integrate the existing education structure with the discovery of the 4th Industrial Revolution new technologies. The impact of this shift demands changes in the implementation of teaching towards Education 4.0. Teaching towards Education 4.0 is a phenomenon in moving the change of MTUN to a higher level. However, there is an issue of a mismatch of skills between the industry's needs and graduates' quality to face the 4th Industrial Revolution in Malaysia. Therefore, this study explores how to implement Education 4.0 to produce quality and technologically skilled graduates required by the industry. Thus, this study aims to determine the indicators and elements of teaching towards Education 4.0 for Engineering Technology in MTUN. The study involved seven experts in instructional design technology and in Technical Vocational Education and Training (TVET). The interview data collections were analysed using thematic analysis to explain the subject matter of this study. Eight elements were identified to implement teaching towards Education 4.0. These include Industry 4.0 elements, courses design, projects, practical, simulation, educator readiness, up-skilling and re-skilling training, and industrial experience. These elements may be viewed in two mains constructs which are essential to implement in the Engineering Technology programme in MTUN. There are curriculum and educator professional development. Further studies, which take these variables into account will need to be undertaken.

Destabilizing effects of L2 explicit pronunciation instruction on L1 speech:

Anchored in a Complex Dynamic perspective on language development, this study explores the effects of L2 explicit pronunciation instruction on L2 English and L1 Brazilian Portuguese VOT production. To this end, 16 Brazilian intermediate users of L2 English were investigated. Volunteers were divided into control and experimental groups. The latter received explicit pronunciation instruction on the production of the English voiceless stops. The study included three data collections, a pre-test, an immediate post-test and a delayed post-test. An acoustic analysis of VOT duration is reported. The results revealed that the control group did not produce the expected VOT pattern for L2 English at any time of the study. No alterations in the L1 were reported. On the other hand, after the instruction, the experimental group produced higher L2 English VOT values. First language attrition was reported since the L1 BP VOT durations also increased after instruction. In addition to highlighting the effects of explicit instruction on L2 development and L1 attrition, this study confirms that language development is constant, and that even L1 adult grammars are not rigid, with potential to change due to the perception and processing of novel nonnative phonetic-phonological categories.

A Survey on Big IoT Data Indexing: Potential Solutions, Recent Advancements, and Open Issues

The past decade has been characterized by the growing volumes of data due to the widespread use of the Internet of Things (IoT) applications, which introduced many challenges for efficient data storage and management. Thus, the efficient indexing and searching of large data collections is a very topical and urgent issue. Such solutions can provide users with valuable information about IoT data. However, efficient retrieval and management of such information in terms of index size and search time require optimization of indexing schemes which is rather difficult to implement. The purpose of this paper is to examine and review existing indexing techniques for large-scale data. A taxonomy of indexing techniques is proposed to enable researchers to understand and select the techniques that will serve as a basis for designing a new indexing scheme. The real-world applications of the existing indexing techniques in different areas, such as health, business, scientific experiments, and social networks, are presented. Open problems and research challenges, e.g., privacy and large-scale data mining, are also discussed.