Thermoelectric La-doped SrTiO3 epitaxial layers with single-crystal quality: from nano to micrometers

Abstract

High-quality thermoelectric La_0.2Sr_0.8TiO₃ (LSTO) films, with thicknesses ranging from 20 nm to 0.7 μm, have been epitaxially grown on SrTiO₃(001) substrates by enhanced solid-source oxide molecular-beam epitaxy. All films are atomically flat (with rms roughness < 0.2 nm), with low mosaicity (<0.1°), and present very low electrical resistivity (<5 × 10^?4 Ω cm at room temperature), one order of magnitude lower than standard commercial Nb-doped SrTiO₃ single-crystalline substrate. The conservation of transport properties within this thickness range has been confirmed by thermoelectric measurements where Seebeck coefficients of approximately –60 μV/K have been recorded for all films. These LSTO films can be integrated on Si for non-volatile memory structures or opto-microelectronic devices, functioning as transparent conductors or thermoelectric elements.     

Green Measurements for Software Product Based on Sustainability Dimensions

Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits will not be attained. Currently, there are not enough works to address this problem, and the green status of software products is uncertain and unsure. This paper aims to identify the green measurements based on sustainable dimensions in a software product. The second objective is to reveal the relationships between the elements and measurements through empirical study. The study is conducted in two phases. The first phase is the theoretical phase, where the main components, measurements and practices that influence the sustainability of a software product are identified. The second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achieving green software products. This study has revealed seven green measurements of software product: Productivity, Usability, Cost Reduction, Employee Support, Energy Efficiency, Resource Efficiency and Tool Support. The relationships are statistically significant, with a significance level of less than 0.01 (p = 0.000). Thus, the hypothesised relationships were all accepted. The contributions of this study revolve around the research perspectives of the measurements to attain a green software product.     

Unsteady 3D mixed convection flow of a chemically reactive Oldroyd-B nanofluid configured by a periodically accelerated surface

Fundamental developments in nanotechnology have attracted the attention of scientists towards the interaction of nanoparticles due to their fascinating applications in thermal engineering and solar energy systems. Convinced by such motivating applications, the current research project addresses the utilization of nanoparticles in the unsteady three-dimensional chemically reactive flow of an Oldroyd-B fluid induced by a bidirectional oscillatory stretching surface. The effects of mixed convection are also considered here. The prime features of the nanofluid namely thermophoresis and Brownian motion characteristics are explored by introducing the famous Buongiorno's nanofluid model. The relevant equations for the formulated theoretical model have been reduced by the appropriate transformations for which the analytic solution is deliberated via the homotopic technique. Later on, a complete graphical analysis for distinct flow parameters is deliberated for dimensionless velocities, concentration, and temperature distributions with the relevant physical implications. Moreover, stimulating physical quantities like local Nusselt and Sherwood numbers are numerically calculated and discussed. The study emphasizes that decreasing variation in both components of velocities has been reported with an increment of relaxation time, while the impact of the retardation time constant is quite opposite. It is further claimed that the velocity distribution has an increasing tendency in the horizontal direction for a higher buoyancy ratio and mixed convection parameters. Moreover, an increment in thermophoresis parameter enhances both temperature and concentration distributions.     

Deep Transfer Learning-Enabled Activity Identification and Fall Detection for Disabled People

The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection. This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes. These sensors produce a huge volume of physical activity data that necessitates real-time recognition, especially during emergencies. Falling is one of the most important problems confronted by older people and people with movement disabilities. Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people. But, the costs incurred upon installation and operation are high, whereas the technology is relevant only for indoor environments. Currently, commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s movements. Against this background, the current study develops an Improved Whale Optimization with Deep Learning-Enabled Fall Detection for Disabled People (IWODL-FDDP) model. The presented IWODL-FDDP model aims to identify the fall events to assist disabled people. The presented IWODL-FDDP model applies an image filtering approach to pre-process the image. Besides, the EfficientNet-B0 model is utilized to generate valuable feature vector sets. Next, the Bidirectional Long Short Term Memory (BiLSTM) model is used for the recognition and classification of fall events. Finally, the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method, which shows the novelty of the work. The experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.     

Process design,simulation, and techno-economic analysis of integrated production of furfural and glucose derived from palm oil empty fruit bunches

Clean Technologies and Environmental Policy - This study aims to propose a new process design, simulation, and techno-economic analysis of an integrated process plant that produces glucose and...     

KP-Rank: a semantic-based unsupervised approach for keyphrase extraction from text data

Automatic key concept identification from text is the main challenging task in information extraction, information retrieval, digital libraries, ontology learning, and text analysis. The main difficulty lies in the issues with the text data itself, such as noise in text, diversity, scale of data, context dependency and word sense ambiguity. To cope with this challenge, numerous supervised and unsupervised approaches have been devised. The existing topical clustering-based approaches for keyphrase extraction are domain dependent and overlooks semantic similarity between candidate features while extracting the topical phrases. In this paper, a semantic based unsupervised approach (KP-Rank) is proposed for keyphrase extraction. In the proposed approach, we exploited Latent Semantic Analysis (LSA) and clustering techniques and a novel frequency-based algorithm for candidate ranking is introduced which considers locality-based sentence, paragraph and section frequencies. To evaluate the performance of the proposed method, three benchmark datasets (i.e. Inspec, 500N-KPCrowed and SemEval-2010) from different domains are used. The experimental results show that overall, the KP-Rank achieved significant improvements over the existing approaches on the selected performance measures.

     

Retardation of Dredged Material Leachate in Foundation Soils

Contaminated dredged material is often placed in confined disposal facilities (CDFs) designed and managed to control environmental impacts of the disposed sediment. This note presents equations for use in a screening procedure to evaluate the impact of a CDF on groundwater. The hydrologic evaluation of leachate production and quality model was used to simulate leachate production and transport through the foundation considering a range of foundation soil characteristics and contaminant properties. The model results were used to develop predictive equations of contaminant attenuation and travel time in the foundation soils. When used with equations to predict dispersion in the aquifer, contaminant exposures at receptor locations can be predicted, which is essential in leachate screening applications. The approach does not consider degradation or permanent sequestration of contaminants. Therefore, the procedure is conservative in that it may overestimate actual leachate concentrations and underestimate actual travel times.     

Lateral polysilicon pn diodes: current-voltage characteristicssimulation between 200 K and 400 K using a numerical approach

The current-voltage characteristics of lateral pn diodes fabricated in polysilicon layer grown by LPCVD on oxidized silicon substrates are analyzed versus temperature. The simulation proposed by Greve (1985) using the analytical current modeling is applied to forward and reverse junction currents for various temperatures; this modeling shows its limitations. Then to fit the experimental characteristics at low and high temperatures as well as at low and high current levels, a numerical modeling is developed taking into account the local electrical field effect on recombination and generation mechanisms at grain boundaries in the whole of the structure, i.e., quasi-neutral and depleted regions. This modeling allows one to fit the complete I-V experimental curves in the whole of the considered temperature range (200 K-400 K) with physical acceptable parameters     

On Supporting Secure Information Distribution in Heterogeneous Systems Using Standard Technologies

This paper presents an integrated security architecture for heterogeneous distributed systems. Based on the MPEG-21 standard data structures and the MPEG-M standard services, the proposed architecture provides a unified, fine-grained solution for protecting each information unit circulated in the system. In this context, a novel scheme for translating the access control rules, initially expressed by means of the standard MPEG-21 Rights Expression Language, into Ciphertext-Policy Attribute-Based Encryption access trees is introduced, thereby enabling offline authorization based on the users’ attributes, also encapsulated and certified using MPEG-21 licenses. The proposed framework provides a detailed approach in all the steps of the information protection process, from attribute acquisition to data encryption and decryption.