scholarly journals Machine learning for perovskite materials design and discovery

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Qiuling Tao ◽  
Pengcheng Xu ◽  
Minjie Li ◽  
Wencong Lu
Keyword(s):  
Machine Learning ◽  
Technological Innovation ◽  
Future Development ◽  
Rational Design ◽  
Driving Forces ◽  
Scientific Progress ◽  
Double Perovskites ◽  
Perovskite Materials ◽  
Development Tendency ◽  
Development Prospects

AbstractThe development of materials is one of the driving forces to accelerate modern scientific progress and technological innovation. Machine learning (ML) technology is rapidly developed in many fields and opening blueprints for the discovery and rational design of materials. In this review, we retrospected the latest applications of ML in assisting perovskites discovery. First, the development tendency of ML in perovskite materials publications in recent years was organized and analyzed. Second, the workflow of ML in perovskites discovery was introduced. Then the applications of ML in various properties of inorganic perovskites, hybrid organic–inorganic perovskites and double perovskites were briefly reviewed. In the end, we put forward suggestions on the future development prospects of ML in the field of perovskite materials.

A Brief Survey of Machine Learning Methods in Identification of Mitochondria Proteins in Malaria Parasite

2020 ◽  
Vol 26 (26) ◽  
pp. 3049-3058
Author(s):  
Ting Liu ◽  
Hua Tang
Keyword(s):  
Machine Learning ◽  
Computational Methods ◽  
Future Development ◽  
Malaria Parasite ◽  
Mitochondrial Proteins ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Effective Drugs ◽  
Construction Strategies ◽  
Day By Day

The number of human deaths caused by malaria is increasing day-by-day. In fact, the mitochondrial proteins of the malaria parasite play vital roles in the organism. For developing effective drugs and vaccines against infection, it is necessary to accurately identify mitochondrial proteins of the malaria parasite. Although precise details for the mitochondrial proteins can be provided by biochemical experiments, they are expensive and time-consuming. In this review, we summarized the machine learning-based methods for mitochondrial proteins identification in the malaria parasite and compared the construction strategies of these computational methods. Finally, we also discussed the future development of mitochondrial proteins recognition with algorithms.

Machine-learning-assisted prediction of magnetic double perovskites

2019 ◽  
Vol 3 (8) ◽  
Author(s):  
Anita Halder ◽  
Aishwaryo Ghosh ◽  
Tanusri Saha Dasgupta
Keyword(s):  
Machine Learning ◽  
Double Perovskites

scholarly journals Binding Ensembles of p53-MDM2 Peptide Inhibitors by Combining Bayesian Inference and Atomistic Simulations

Molecules ◽  
2021 ◽  
Vol 26 (1) ◽  
pp. 198
Author(s):  
Lijun Lang ◽  
Alberto Perez
Keyword(s):  
Bayesian Inference ◽  
Virtual Screening ◽  
Statistical Mechanics ◽  
Small Molecules ◽  
Rational Design ◽  
Driving Forces ◽  
Peptide Inhibitors ◽  
Atomistic Simulations ◽  
Binding Mechanism ◽  
Intrinsically Disordered

Designing peptide inhibitors of the p53-MDM2 interaction against cancer is of wide interest. Computational modeling and virtual screening are a well established step in the rational design of small molecules. But they face challenges for binding flexible peptide molecules that fold upon binding. We look at the ability of five different peptides, three of which are intrinsically disordered, to bind to MDM2 with a new Bayesian inference approach (MELD × MD). The method is able to capture the folding upon binding mechanism and differentiate binding preferences between the five peptides. Processing the ensembles with statistical mechanics tools depicts the most likely bound conformations and hints at differences in the binding mechanism. Finally, the study shows the importance of capturing two driving forces to binding in this system: the ability of peptides to adopt bound conformations (ΔGconformation) and the interaction between interface residues (ΔGinteraction).

scholarly journals Strategies for the Management of Traditional Chestnut Landscapes in Pesio Valley, Italy: A Participatory Approach

Land ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 536
Author(s):  
Paola Gullino ◽  
Maria Mellano ◽  
Gabriele Beccaro ◽  
Marco Devecchi ◽  
Federica Larcher
Keyword(s):  
Focus Group ◽  
Future Development ◽  
Driving Forces ◽  
Landscape Planning ◽  
Landscape Management ◽  
Development Program ◽  
Participatory Approach ◽  
Planning Approach ◽  
Development Policies ◽  
Forestry Policies

Through an exploratory case study conducted in the Pesio Valley, northwest Italy, this paper proposes a framework for maintaining traditional chestnut production landscapes and addressing future development policies. The main goal was to understand how to promote a bottom-up planning approach, including stakeholder perceptions in traditional chestnut landscape management. To ensure the sustainability of the landscape, current driving forces and their landscape effects were identified by local stakeholders using a focus group technique. Population ageing, local forestry policies directed towards supporting chestnut growers’ income, social and economic needs, and land fragmentation are the main driving forces that will influence future chestnut landscapes. The focus group participants built two scenarios of possible future development of the chestnut landscape, one characterized by the disappearance and transformation of chestnut stands, the other by their permanence and maintenance. The most recommended strategies for maintaining traditional chestnut cultivation were chestnut processing, fruit designation of origin, and the cultivation of traditional varieties. This study shows that, to preserve the traditional chestnut landscape, the participation of multiple stakeholders is a useful approach in landscape planning. This methodology could guide decision-makers and planners who desire to implement a participatory approach to a sustainable development program for traditional chestnut landscapes.

scholarly journals Lead-Free Halide Double Perovskites: A Review of the Structural, Optical, and Stability Properties as Well as Their Viability to Replace Lead Halide Perovskites

Metals ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 667 ◽  
Author(s):  
Edson Meyer ◽  
Dorcas Mutukwa ◽  
Nyengerai Zingwe ◽  
Raymond Taziwa
Keyword(s):  
Solar Cells ◽  
Perovskite Solar Cells ◽  
Lead Free ◽  
Double Perovskites ◽  
Stability Properties ◽  
Perovskite Materials ◽  
Halide Perovskites ◽  
Halide Perovskite ◽  
Light Absorbers ◽  
Lead Halide

Perovskite solar cells employ lead halide perovskite materials as light absorbers. These perovskite materials have shown exceptional optoelectronic properties, making perovskite solar cells a fast-growing solar technology. Perovskite solar cells have achieved a record efficiency of over 20%, which has superseded the efficiency of Gräztel dye-sensitized solar cell (DSSC) technology. Even with their exceptional optical and electric properties, lead halide perovskites suffer from poor stability. They degrade when exposed to moisture, heat, and UV radiation, which has hindered their commercialization. Moreover, halide perovskite materials consist of lead, which is toxic. Thus, exposure to these materials leads to detrimental effects on human health. Halide double perovskites with A2B′B″X6 (A = Cs, MA; B′ = Bi, Sb; B″ = Cu, Ag, and X = Cl, Br, I) have been investigated as potential replacements of lead halide perovskites. This work focuses on providing a detailed review of the structural, optical, and stability properties of these proposed perovskites as well as their viability to replace lead halide perovskites. The triumphs and challenges of the proposed lead-free A2B′B″X6 double perovskites are discussed here in detail.

scholarly journals Research on the Development Process and Optimization Path of Crowdsourcing in China

2021 ◽  
Vol 235 ◽  
pp. 02076
Author(s):  
Yanrong Huang ◽  
Bin Huang ◽  
Min Chen
Keyword(s):  
Technological Innovation ◽  
Future Development ◽  
Value Creation ◽  
Open Innovation ◽  
Development Process ◽  
The Public ◽  
Operation Process ◽  
Development Direction ◽  
The Future ◽  
Important Form

Crowdsourcing is an important form for enterprises to realize open innovation, which can gather the wisdom of the public and gather talents from various fields to participate in technological innovation and value creation. This paper systematically reviews the emergence and development of crowdsourcing in China, analyzes the causes and characteristics of the four stages of crowdsourcing development with the clue of major events in the development process of crowdsourcing; takes the operation process of crowdsourcing as the breakthrough point, discusses the bidirectional driving optimization path for the benign rolling development of crowdsourcing mode under the background of “mass entrepreneurship and innovation”; and prospects. Finally, the future development direction of crowdsourcing mode is pointed out.

scholarly journals Are we there yet? A machine learning architecture to predict organotropic metastases

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Michael Skaro ◽  
Marcus Hill ◽  
Yi Zhou ◽  
Shannon Quinn ◽  
Melissa B. Davis ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cancer Metastasis ◽  
Driving Forces ◽  
The Cancer Genome Atlas ◽  
Tumor Type ◽  
Metastatic Progression ◽  
Statistical Machine Learning ◽  
Primary Tumors ◽  
Site Specific ◽  
Tissue Specific

Abstract Background & Aims Cancer metastasis into distant organs is an evolutionarily selective process. A better understanding of the driving forces endowing proliferative plasticity of tumor seeds in distant soils is required to develop and adapt better treatment systems for this lethal stage of the disease. To this end, we aimed to utilize transcript expression profiling features to predict the site-specific metastases of primary tumors and second, to identify the determinants of tissue specific progression. Methods We used statistical machine learning for transcript feature selection to optimize classification and built tree-based classifiers to predict tissue specific sites of metastatic progression. Results We developed a novel machine learning architecture that analyzes 33 types of RNA transcriptome profiles from The Cancer Genome Atlas (TCGA) database. Our classifier identifies the tumor type, derives synthetic instances of primary tumors metastasizing to distant organs and classifies the site-specific metastases in 16 types of cancers metastasizing to 12 locations. Conclusions We have demonstrated that site specific metastatic progression is predictable using transcriptomic profiling data from primary tumors and that the overrepresented biological processes in tumors metastasizing to congruent distant loci are highly overlapping. These results indicate site-specific progression was organotropic and core features of biological signaling pathways are identifiable that may describe proliferative plasticity in distant soils.

scholarly journals The Relationship between High-Rise Building and Urban Environment

2015 ◽  
Vol 4 (3) ◽  
pp. 18
Author(s):  
Shujun Shi
Keyword(s):  
Sustainable Development ◽  
Urban Environment ◽  
Future Development ◽  
Comprehensive Analysis ◽  
High Rise ◽  
High Rise Building ◽  
Development Direction ◽  
Negative Impacts ◽  
The Relationship ◽  
Development Prospects

<p>High-rise buildings have become an inevitable trend in future building development. Since today’s building theories and technologies have not fully matured, we should perform a comprehensive analysis by combining urban environmental conditions in order to promote sustainable development of high-rise buildings. This study will discuss development prospects and problems of high-rise buildings via the relationship between urban environment and high-rise buildings, in order to form a more comprehensive and mature understanding of future development direction and the focus of high-rise building, and to propose appropriate countermeasures to the negative impacts of high-rise buildings on the development of urban environment.</p>

“Smash Temples, Build Schools”: Comparing Secularism in India and China

2013 ◽  
Author(s):  
Peter van der Veer
Keyword(s):  
Rational Choice ◽  
Technological Innovation ◽  
Scientific Knowledge ◽  
Scientific Discovery ◽  
Scientific Progress ◽  
Western Society ◽  
Religious Authority ◽  
Societal Development ◽  
Political Project ◽  
India And China

This chapter discusses secularism as a political project with its own utopian elements. Secularism refers to the growing importance of scientific knowledge that is not constrained by religious authority. Religion is sometimes taken to be an obstacle for scientific progress and secularism demands its removal for the benefit of societal development that is guided by scientific discovery and technological innovation. Secularization was seen by sociologists as an intrinsic and inescapable part of the modernization of Western society, with the assumption that this was something all societies had to go through. An alternative to post-Weberian arguments in sociology about religion and secularity is offered by theories that emphasize individual, rational choice in religious markets.

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