CellRank for directed single-cell fate mapping

Computational trajectory inference enables the reconstruction of cell state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank (https://cellrank.org) for single-cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, taking into account the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in velocity vectors. On pancreas development data, CellRank automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage-traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes. CellRank also predicts a new dedifferentiation trajectory during postinjury lung regeneration, including previously unknown intermediate cell states, which we confirm experimentally.

Small mammals of background areas in the vicinity of the Karabash copper smelter (Southern Urals, Russia)

The dataset contains records of small mammals (Eulipotyphla and Rodentia) collected in the background (unpolluted) areas in the vicinity of Karabash copper smelter (Southern Urals, Russia) and the territory of the Sultanovskoye deposit of copper-pyrite ores before the start of its development. Data were collected during the snowless periods in 2007 (18 sampling plots), 2008–2010 (13 plots annually), 2011 (30 plots) and 2012–2014 (19 plots annually). The capture of animals was carried out in different types of forests (pine, birch, mixed and floodplain), sparse birch stands, reed swamps, marshy and dry meadows, border areas, a household waste dump, areas of ruderal vegetation and a temporary camp. Our study of small mammals was conducted using trap lines (snap and live traps). During the study period, 709 specimens of small mammals were caught, which belonged to five species of shrews and 13 species of rodents. The dataset may be highly useful for studying regional fauna and the distribution of species in different habitats and could also be used as reference values for environmental monitoring and conservation activities. Our dataset contains new information on occurrences of small mammals. It includes the peculiarities of their habitat distribution in the background areas in the vicinity of the large copper smelter and the deposit of copper-pyrite ores before the start of its development (Chelyabinsk Oblast, Russia). All occurrence records of 18 mammal species with georeferencing have been published in GBIF.

Communication Strategies of Entrepreneurial Organizations in Mobile Apps Industry

This research advances scholarly understanding of the strategic decisions regarding external communication during the critical period of product launch. Drawing on research about dynamic capabilities and external organizational communication, this study examines ways in which entrepreneurial organizations use silence as an effective communication strategy to reduce external uncertainty and to nurture growth during critical periods of development. Data were collected tracking the external communication of 54 entrepreneurial organizations that focus on mobile news application development. Results show a significant relationship between the attention organizations attract after product launch and an organization’s performance. The greater the magnitude of change from pre-launch to post-launch, from less frequent external communication to more frequent external communication, the more likely there is to be an increase in the product performance. The findings emphasize a more nuanced understanding of external communication as a strategic tool in entrepreneurial organizations.

Regional Leading Industry Selection based on an Extended Fuzzy VIKOR Approach

To improve the deployment and optimization of the industrial structure, researchers and practitioners have performed a variety of researches in terms of regional leading industry selection based on AO Hirschman, Rostow and Miyohei’s principles. The criteria and methods employed in previous studies are mainly based on the mass industrial development data, leading to the limitation of study on the application in new high-tech district and underdeveloped regions. Due to lack of industrial data and detail industry information, it is difficult to employ the deterministic regional industry selection model. Therefore, an extended fuzzy-VIKOR approach that the expert-based and trapezoidal fuzzy number decision-making techniques, embedded into the VIKOR steps is proposed. It is developed to solve the regional leading industry selection problems concerning industrial, economic, social and environmental dimensions. Finally, a case study for the industrial planning of a high-tech zone is applied to verify the proposed decision-making approach.

A Unified Model of Shariah Indices for Human Development and Prosperity

In recent years, several attempts have been made to measure human prosperity using shariah objectives. These, however, have failed to propose a unified model that incorporates the ‘means to achieve these objectives’. This paper attempts to fill this gap by arguing that a large proportion of shariah-led prosperity measures are in line with the United Nations’ Millennium and Sustainable Development (MSD) goals to achieve global development targets and reduce poverty. This paper proposes a global unified model for a human development index that identifies existing development data that can be utilised in accordance with the objectives of shariah. The proposed model attempts to build a bridge between shariah-based Islamic development indices and MSD goals to achieve prosperity via religiosity.

SUSTAINABLE DEVELOPMENT AND DISASTER RISK REDUCTION MAINSTREAMING: NEXUS BETWEEN POLICY PROCLAMATION AND IMPLEMENTATION

Land-use planning, disasters and development are clearly related. Risk-sensitive development practices and responsible land use planning can contribute to resilience building. At the same time, poorly planned development can intensify social, economic, physical and environmental vulnerabilities of the population and can trigger devastating extreme events. Therefore, the process of disaster risk reduction has to be weaved into the developmental framework and India has given its commitment at national and international forums to ensure the same. However, since there is no specific policy on integrating DRR into development planning in India, this paper discusses the extent to which such integration is seen through one of the major projects- the Navi Mumbai International Airport (NMIA) in the planning and approval process, especially in the contexts of environmental vulnerabilities. The study suggests that there are serious gaps between the policy proclamations that seek to ensure sustainable development through DRR integration into development projects and its implementation. Thus, much more work is needed to enforce the idea of mainstreaming DRR in to foster risk aware or risk sensitive development. Data for this qualitative study was obtained from both primary as well as secondary sources.

Automatic Phonemes Segmentation for Quran Verses Using Kaldi Toolkit

In this paper, automatic segmentation system was built using the Kaldi toolkit at phoneme level for Quran verses data set with a total speech corpus of (80 hours) and its corresponding text corpus respectively, with a size of 1100 recorded Quran verses of 100 non-Arab reciters. Initiated with the extraction of Mel Frequency Cepstral Coefficients MFCCs, the proceedings of the building of Language Model LM and Acoustic Model AM training phase continued until the Deep Neural Network DNN level by selecting 770 waves (70 reciters). The testing of the system was done using 220 waves (20 reciters), and concluded with the selection of the development data set which was 280 waves (10 reciters). Comparison was implemented between automatic and manual segmentation, and the results obtained for the test set was 99% and for the Development set was 99% with Time Delay Neural Networks TDNN based acoustic modelling.

THE FUTSAL DEFENSE SYSTEM MODEL FOR 14-16 YEARS OLD

The purpose of this research is to produce a futsal defense system model for 14-16 years olds and to test the effectiveness of the futsal defense model for 14-16 years olds. The method used in this research is research and development. Data collection techniques used, interviews, tests, and field observations. The results of the product effectiveness test by comparing the two groups. the treatment group using the product development, and the control group using the pretest and posttest designs. The mean score of each group based on the test is that the effectiveness of the experimental group is higher than that of the control group. The improvement of the futsal defense system for ages 14-16 years at the time of the pre-test showed t-count = 22, 219,> t-table = 1.70329, df = 27 and p-value = 0.00 <0.005. Based on the comparison of the test results. the increase in test results for the experimental group increased significantly than that of the control group. The subjects in this study were MC Utama athletes aged 14-16 years. It is hoped that this research can provide benefits for sports practitioners, especially in the sport of futsal. Key words : Futsal, a futsal defense system model

Influence of seed sowing rates on height, development and yield of the Russian varieties of oil-type sunflower in the Tashkent region of the Uzbekistan Republic

To obtain high yields of good quality of sunflower seeds, it is necessary to strictly observe scientifically justified cultivation technology, which combines techniques accounting both the biological features of the crop and the natural and climatic conditions of the region. But the role of varietal agricultural technology is also great, which takes into account the properties of a new variety and ensures the fullest realization of its productivity potential under these conditions. Research and development data are very important when introducing crops or varieties into new regions. In this regard, it became necessary to study and scientifically substantiate the optimal seed sowing rates of Russian sunflower varieties in irrigated conditions of the Uzbekistan Republic. The effect of seed sowing rates on the growth, development and yield of Russian oil sunflower varieties was studied in 2020– 2021 at the experimental station of the Tashkent State Agrarian University of Uzbekistan. The objects of the research were promising varieties Irtysh, Skormas (Russia) and the local variety Dilbar (Uzbekistan), which were cultivated at different seed sowing rates, providing a plant population of 40, 50, 60 and 70 thousand plants per ha. As a result of the studies, we found out, according to the complex of economically valuable traits, the best varieties of oil sunflower in the conditions of the Tashkent region are the middle maturing variety Dilbar of the local selection and the ultra-early maturing variety Skormas of the Russian selection, they formed the highest yield in the main crops on irrigation with a seed sowing rate of 50 thousand plant per ha – 4.35 and 4.09 t per ha, respectively. The Russian variety Irtysh is ultra-early maturing, the growing season is 86–88 days, it is less productive and can be considered as promising for repeated crops.