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Unfortunately, silicon, Ge, and related alloys, which provide the leading materials platform of electronics, are inefficient light emitters because of the indirect nature of their fundamental energy band-gap.
The luminescence is expected to be larger as the tensile strain is increased and a direct band-gap material has been predicted for a tensile strain around 2% [6].
(B) Band-to-band luminescence spectra from thin strained samples compared with that from bulk material.
Abrosimov, Room temperature luminescence from germanium, Journal of Physics: Conference Series 281 (2011) 012021 [16] Y.
Simoen, Extended defects in germanium: Fundamental and technological aspects , Springer Series in Materials Science 118, Wiesbaden (2009) [35] S.

Evaluation of the Gross and Net Calorific Value of the Selected Wood Species Emília Orémusová1,a , Ľudmila Tereňová1,b , Roman Réh1,c 1Technical University in Zvolen, Faculty of Wood Science Technology, T.G.
Materials and method For particular wood species individual samples of wood, bark, leaves and needles tested.
European Journal of Environmental and Safety Sciencis.
Wood as an engineering material.
Fire technical properties of wood and wood-based materials.

L'vov: in Advances in Shape Memory Materials, edited by V.A.
Boston, MA: Materials Research Society, pp. 415-420. 13.
Celotto: International Materials Reviews Vol. 48 (2003), pp.225-245. 16.
L.Remy, Metallurgical Transactions a-Physical Metallurgy and Materials Science Vol. 12 (1981), pp. 387-408. 22.
Shape Memory Materials (Cambridge University Press, Cambridge,1998). 48.

Materials and methods Bacterium Species and Gene Sequences.The major facilitator superfamily mfs_1 gene from Riemerella anatipestifer(RA) was identified in our laboratory[34].
Acknowledgments The research was supported by Special Fund for Agro-scientific Research in the Public Interest (No.201003012), National science and technology support program for agriculture (2011BAD34B03), China Agricultural Research System (CARS-43-8) and Changjiang Scholars and Innovative Research Team in University (PCSIRT0848).
Vol. 341–350(1982), p. 11 [31] Cheng AC, Wang MS and Chen XY:Chinese Journal of Veterinary Science.
Vol.278–283(2011), p. 150 [34] Xiaojia Wang, DeKang Zhu, MingShu Wang, AnChun Cheng, RenYong Jia, Yi Zhou, Zhengli Chen, QiHui Luo, Fei Liu, Yi Wang and XiaoYue Chen: Journal of Bacteriology.

Building envelopes consist of wall constructions including wall layers and materials.
Layers consist of materials with their respective thickness.
Each material is assigned values for heat conductivity, density and specific heat.
In order to integrate the constructions into the automation process, the materials are first written to the source code of the main file and the wall definitions are created afterwards.
Michalatos, Autozoner: an algorithm for automatic thermal zoning of buildings with unknown interior space definitions, Journal of Building Performance Simulation 9 (2) (2016) 176-189

Outbreak Prediction of COVID-19 in India Using ARIMA and Prophet Model with Lockdown and Unlock Avinash Sharma1, Dharminder Yadav2, Umesh Chandra3, Himani Maheswari4 1Assistant Professor, Department of Computer Science and Engg, Maharishi Markandeshwar Deemed to be University, Ambala, Haryana, India 2Research Scholar, Department of Computer Science and Technology, Glocal University, Saharanpur, UP, India 3Assistant Professor, Department of Computer Science, Banda University of Agriculture and Technology, Banda, UP, India 4Assistant Professor, Department of Computer Science, Uttaranchal University, Dehradun, UK, India 1asharma@mmumullana.org, 2ydharminder@yahoo.com, 3uck.iitr@gmail.com, 4himani_bahmah@yahoo.com Keywords: coronavirus, COVID-19, Prophet, ARIMA, Linear Regression.
Material and Methods Linear Regression: This is a supervised machine learning algorithm that has established a relationship between a dependent and an independent variable.
COVID-19 Epidemic Forecast in Different States of India using SIR Model. medRXiv The Preprint server for health sciences. (2020) 1-19 [11] Khashei, M.; Bijari, M.; Ardali, G.A.R., Improvement of auto-regressive integrated moving average models using fuzzy logic and artificial neural networks (ANNs).
Advances in Mathematics: Scientific Journal, 9(6) (2020) 3417–3430 [15] Meyler, A.; Kenny, G.; Quinn, T., Forecasting Irish Inflation Using ARIMA Models.
Science of the Total Environment, 728(2020) 13876 [20] Tran, T.T.; Pham, L.T.; Ngo, Q.X., Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran).

Chen1 1School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney 2052, Australia 2Australian Nuclear Science and Technology Organisation (ANSTO), PMB 1, Menai, NSW 2234, Australia 3Department of Civil and Architectural Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong, PRC abckkyuen@cityu.edu.hk AbstractThe Wall Adpating Local Eddy Viscosity (WALE) subgrid-scale turbulence model was adopted for an in-house large eddy simulation (LES)fire code in which the turbulence is fully coupled combustion and radiation models.
However, this assumption might not be applicable to the wall materials used in the experiments.
A fully-coupled simulation of vortical structures in a large-scale buoyant pool fire,International Journal of Thermal Sciences, Vol. 48, pp. 2187-2202
Predicting Radiative Transfer in Rectangular Enclosures Using the Discrete Ordinates Method, Combustion Science and Technology,Vol. 59,pp. 321-340

MATERIAL AND METHODS Three datasets were involved in the current temporal characterization of the forest fragmentation over the 36 forest ecoregions.
In which, the 1995 land use data, with a 250-m spatial resolution, were prepared by the Institute of Geographic Sciences and Natural Resources, CAS (Chinese Academy of Sciences), providing 30 land use classes.
Conservation Science Program of WWF-US: Washington, DC, 2000
Peng, "Assessment of forest geospatial patterns over the three giant forest areas of China," Journal of Forestry Research, vol. 19(1), pp. 25-31, 2008
Santiago, “Forest fragmentation estimated from remotely sensed data: is comparison across scales possible,” Forest Science, vol. 51 (1), pp. 51-63, 2005

Measuring blur in computer science.
A keen research area in computer science is that of ‘image deblurring’.
Smart materials and structures. 12 (2003) 785–794
Journal of Sound and Vibration. 145(2) (1991) 321–332
[8] Maas, H. & Hampel, U., Photogrammetric Techniques in Civil Engineering Material Testing and Structure Monitoring.

Gas-air and fuel-air mixture explosions have been particularly dangerous, often resulting in fatalities, injuries, and substantial material losses [1].
Journal of Sensors. 2017 (2017). https://www.hindawi.com/journals/js/2017/9851406/
In IOP Conference Series: Earth and Environmental Science. 1348 1 (2024) 012014.
Materials Science Forum. 1141 (2024) 35–42.