Lead-Free Inorganic Cesium Tin-Germanium Triiodide Perovskites for Photovoltaic Application

The toxicity of lead associated with the lifecycle of perovskite solar cells (PSCs( is a serious concern which may prove to be a major hurdle in the path toward their commercialization. The current proposed lead-free PSCs including Ag(I), Bi(III), Sb(III), Ti(IV), Ge(II), and Sn(II) low-toxicity cations are still plagued with the critical issues of poor stability and low efficiency. This is mainly because of their chemical stability. In the present research, utilization of all inorganic CsSnGeI3 based materials offers the advantages to enhance resistance of device to degradation, reduce the cost of cells, and minimize the carrier recombination. The presence of inorganic halide perovskite improves the photovoltaic parameters of PCSs via improved surface coverage and stability. The inverted structure of simulated devices using a 1D simulator like solar cell capacitance simulator (SCAPS) version 3308 involves TCOHTL/Perovskite/ETL/Au contact layer. PEDOT:PSS, PCBM, and CsSnGeI3 used as hole transporting layer (HTL), electron transporting layer (ETL), and perovskite absorber layer in the inverted structure for the first time. The holes are injected from highly stable and air tolerant Sn0.5Ge0.5I3 perovskite composition to HTM and electrons from the perovskite to ETL. Simulation results revealed a great dependence of power conversion efficiency (PCE) on the thickness and defect density of perovskite layer. Here the effect of an increase in operating temperature from 300 K to 400 K on the performance of CsSnGeI3 based perovskite devices is investigated. Comparison between simulated CsSnGeI3 based PCSs and similar real testified devices with spiro-OMeTAD as HTL showed that the extraction of carriers at the interfaces of perovskite absorber depends on the energy level mismatches between perovskite and HTL/ETL. We believe that optimization results reported here represent a critical avenue for fabricating the stable, low-cost, efficient, and eco-friendly all-inorganic Cs-Sn-Ge based lead-free perovskite devices.

Operational Challenges of Marine Fiber Reinforced Polymer Composite Structures Coupled with Piezoelectric Transducers

Composite structures become intriguing for the design of aerospace, automotive and marine applications due to weight reduction, corrosion resistance and radar signature reduction demands and requirements. Studies on piezoelectric ceramic transducers (PZT) for diagnostics and health monitoring have gained attention for their sensing capabilities, however PZT structures are prone to fail in case of heavy operational loads. In this paper, we develop a piezo-based Glass Fiber Reinforced Polymer (GFRP) composite finite element (FE) model, validate with experimental setup, and identify the applicability and limitations of PZTs for a marine application. A case study is conducted to assess the piezo-based sensing capabilities in a representative marine composite structure. A FE model of the composite structure combined with PZT patches is developed, afterwards the response and functionality are investigated according to the sea conditions. Results of this study clearly indicate the blockers and critical aspects towards industrialization and wide-range use of PZTs for marine composite applications.

Implementation of Cloud Customer Relationship Management in Banking Sector: Strategies, Benefits and Challenges

The cloud customer relationship management (CRM) has emerged as an innovative tool to augment the customer satisfaction and performance of banking systems. Cloud CRM allows to collect, analyze and utilize customer-associated information and update the systems, thereby offer superior customer service. Cloud technologies have invaluable potential to ensure innovative customer experiences, successful collaboration, enhanced speed to marketplace and IT effectiveness. As such, many leading banks have been attracted towards adoption of such innovative and customer-driver solutions to revolutionize their existing business models. Chief Information Officers (CIOs) are already implemented or in the process of implementation of cloud CRM. However, many organizations are still reluctant to take such initiative due to the lack of information on the factors influencing its implementation. This paper, therefore, aims to delve into the strategies, benefits and challenges intertwined in the implementation of cloud CRM in banking sector and provide reliable solutions.

Generative Adversarial Network Based Fingerprint Anti-Spoofing Limitations

Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Impact of Climate Change on Sea Level Rise along the Coastline of Mumbai City, India

Sea-level rise being one of the most important impacts of anthropogenic induced climate change resulting from global warming and melting of icebergs at Arctic and Antarctic, the investigations done by various researchers both on Indian Coast and elsewhere during the last decade has been reviewed in this paper. The paper aims to ascertain the propensity of consistency of different suggested methods to predict the near-accurate future sea level rise along the coast of Mumbai. Case studies at East Coast, Southern Tip and West and South West coast of India have been reviewed. Coastal Vulnerability Index of several important international places has been compared, which matched with Intergovernmental Panel on Climate Change forecasts. The application of Geographic Information System mapping, use of remote sensing technology, both Multi Spectral Scanner and Thematic Mapping data from Landsat classified through Iterative Self-Organizing Data Analysis Technique for arriving at high, moderate and low Coastal Vulnerability Index at various important coastal cities have been observed. Instead of data driven, hindcast based forecast for Significant Wave Height, additional impact of sea level rise has been suggested. Efficacy and limitations of numerical methods vis-à-vis Artificial Neural Network has been assessed, importance of Root Mean Square error on numerical results is mentioned. Comparing between various computerized methods on forecast results obtained from MIKE 21 has been opined to be more reliable than Delft 3D model.

Transformation of Industrial Policy towards Industry 4.0 and Its Impact on Firms' Competition

Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

The SOCI Strategy as a Method to Meet the Innovation Challenges of COVID-19

The COVID-19 causes a worldwide crisis and has an impact in every dimension of the economy. Organizations with the ability to adapt to new developments and which innovate solutions for the disrupted world during and after the Corona crises have the opportunity to not only survive the crisis but rather to use new trends to implement new business models and gain advantage. In this context, startups seem to have better opportunities to manage the Corona crisis through their innovation-based nature. The main result of this paper is the understanding that by applying a startup orientated innovation (SOCI) strategy, established companies can be motivated to meet the challenge of COVID-19 in a similar way like startups. This result can be achieved by describing the role of innovation and a SOCI strategy as helpful methods for organizations to meet the coming challenges during and after the COVID-19 epidemics. In addition to this, this paper presents a practical application of SOCI through the PANDA approach of the Fresenius University of Applied Sciences in Germany and discuss it in the context of COVID-19 as an exemplary successful real-world implementation of SOCI strategy.

Investigation of the Effects of Biodiesel Blend on Particulate-Phase Exhaust Emissions from a Light Duty Diesel Vehicle

This study presents an investigation of diesel vehicle particulate-phase emissions with neat ultralow sulphur diesel (B0, ULSD) and 5% waste cooking oil-based biodiesel blend (B5) in Hong Kong. A Euro VI light duty diesel vehicle was tested under transient (New European Driving Cycle (NEDC)), steady-state and idling on a chassis dynamometer. Chemical analyses including organic carbon (OC), elemental carbon (EC), as well as 30 polycyclic aromatic hydrocarbons (PAHs) and 10 oxygenated PAHs (oxy-PAHs) were conducted. The OC fuel-based emission factors (EFs) for B0 ranged from 2.86 ± 0.33 to 7.19 ± 1.51 mg/kg, and those for B5 ranged from 4.31 ± 0.64 to 15.36 ± 3.77 mg/kg, respectively. The EFs of EC were low for both fuel blends (0.25 mg/kg or below). With B5, the EFs of total PAHs were decreased as compared to B0. Specifically, B5 reduced total PAH emissions by 50.2%, 30.7%, and 15.2% over NEDC, steady-state and idling, respectively. It was found that when B5 was used, PAHs and oxy-PAHs with lower molecular weight (2 to 3 rings) were reduced whereas PAHs/oxy-PAHs with medium or high molecular weight (4 to 7 rings) were increased. Our study suggests the necessity of taking atmospheric and health factors into account for biodiesel application as an alternative motor fuel.

Modelling of Multi-Agent Systems for the Scheduling of Multi-EV Charging from Power Limited Sources

This paper presents the research and application of model predictive scheduled charging of electric vehicles (EV) subject to limited available power resource. To focus on algorithm and operational characteristics, the EV interface to the source is modelled as a battery state equation during the charging operation. The researched methods allow for the priority scheduling of EV charging in a multi-vehicle regime and when subject to limited source power availability. Priority attribution for each connected EV is described. The validity of the developed methodology is shown through the simulation of different scenarios of charging operation of multiple connected EVs including non-scheduled and scheduled operation with various numbers of vehicles. Performance of the developed algorithms is also reported with the recommendation of the choice of suitable parameters.

Identifying Network Subgraph-Associated Essential Genes in Molecular Networks

Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.

Growth of Non-Polar a-Plane AlGaN Epilayer with High Crystalline Quality and Smooth Surface Morphology

Non-polar a-plane AlGaN epilayers of high structural quality have been grown on r-sapphire substrate by using metalorganic chemical vapor deposition (MOCVD). A graded non-polar AlGaN buffer layer with variable aluminium concentration was used to improve the structural quality of the non-polar a-plane AlGaN epilayer. The characterisations were carried out by high-resolution X-ray diffraction (HR-XRD), atomic force microscopy (AFM) and Hall effect measurement. The XRD and AFM results demonstrate that the Al-composition-graded non-polar AlGaN buffer layer significantly improved the crystalline quality and the surface morphology of the top layer. A low root mean square roughness 1.52 nm is obtained from AFM, and relatively low background carrier concentration down to 3.9×  cm-3 is obtained from Hall effect measurement.

Influences on Occupational Identity through Trans and Gender Diverse Identity: A Qualitative Study about Work Experiences of Trans and Gender Diverse Individuals

Work experiences and satisfaction as well as the feeling of belonging has been narrowly explored from the perspective of trans and gender diverse individuals. Hence, the study investigates the relationship of values, attitudes, and norms of occupational environments and the working identity of trans and gender diverse people of the Australian workforce. Based on 22 semi-structured interviews with trans and gender diverse individuals regarding their work and career experiences, a first insight about their feeling of belonging through commonality in the workplace could be established. Communality between the values, attitudes and norms of a trans and gender diverse individuals working identities and profession, organization and working environment could increase the feeling of belonging. Further reflection and evaluation of trans and gender diverse identities in the workplace need to be considered to create an equitable and inclusive workplace of the future. Consequently, an essential development step for the future of work and its fundamental values of diversity, inclusion, and belonging will consist of the acknowledgement and inclusion of trans and gender diverse people as part of a broader social identity of the workplace.

Self-Organization-Based Approach for Embedded Real-Time System Design

This paper proposes a self-organization-based approach for real-time systems design. The addressed issue is the mapping of an application onto an architecture of heterogeneous processors while optimizing both makespan and reliability. Since this problem is NP-hard, a heuristic algorithm is used to obtain efficiently approximate solutions. The proposed approach takes into consideration the quality as well as the diversity of solutions. Indeed, an alternate treatment of the two objectives allows to produce solutions of good quality while a self-organization approach based on the neighborhood structure is used to reorganize solutions and consequently to enhance their diversity. Produced solutions make different compromises between the makespan and the reliability giving the user the possibility to select the solution suited to his (her) needs.

Low Temperature Biological Treatment of Chemical Oxygen Demand for Agricultural Water Reuse Application Using Robust Biocatalysts

The agriculture industry is especially vulnerable to forecasted water shortages. In the fresh and fresh-cut produce sector, conventional flume-based washing with recirculation exhibits high water demand. This leads to a large water footprint and possible cross-contamination of pathogens. These can be alleviated through advanced water reuse processes, such as membrane technologies including reverse osmosis (RO). Water reuse technologies effectively remove dissolved constituents but can easily foul without pre-treatment. Biological treatment is effective for the removal of organic compounds responsible for fouling, but not at the low temperatures encountered at most produce processing facilities. This study showed that the Microvi MicroNiche Engineering (MNE) technology effectively removes organic compounds (> 80%) at low temperatures (6-8 °C) from wash water. The MNE technology uses synthetic microorganism-material composites with negligible solids production, making it advantageously situated as an effective bio-pretreatment for RO. A preliminary technoeconomic analysis showed 60-80% savings in operation and maintenance costs (OPEX) when using the Microvi MNE technology for organics removal. This study and the accompanying economic analysis indicated that the proposed technology process will substantially reduce the cost barrier for adopting water reuse practices, thereby contributing to increased food safety and furthering sustainable water reuse processes across the agricultural industry.

The Influence of Job Recognition and Job Motivation on Organizational Commitment in Public Sector: The Mediation Role of Employee Engagement

It is an established fact that organizations across the globe consider employees as their assets and try to advance their well-being. However, the local firms of developing countries are mostly profit oriented and do not have much concern about their employees’ engagement or commitment. Like other developing countries, the local organizations of Pakistan are also less concerned about the well-being of their employees. Especially public sector organizations lack concern regarding engagement, satisfaction or commitment of the employees. Therefore, this study aimed at investigating the impact of job recognition and job motivation on organizational commitment in the mediation role of employee engagement. The data were collected from land record officers of board of revenue, Punjab, Pakistan. Structured questionnaire was used to collect data through physically visiting land record officers and also through the internet. A total of 318 land record officers’ responses were finalized to perform data analysis. The data were analyzed through confirmatory factor analysis and structural equation modeling technique. The findings revealed that job recognition and job motivation have direct as well as indirect positive and significant impact on organizational commitment. The limitations, practical implications and future research indications are also explained.

An Investigation to Study the Moisture Dependency of Ground Enhancement Compound

Lightning protection consists of three main parts; mainly air termination system, down conductor, and earth termination system. Earth termination system is the most important part as earth is the sink and source of charges. Therefore, even when the charges are captured and delivered to the ground, and an easy path is not provided to the charges, earth termination system would lead to problems. Soil has significantly different resistivities ranging from 10 Ωm for wet organic soil to 10000 Ωm for bedrock. Different methods have been discussed and used conventionally such as deep-ground-well method and altering the length of the rod. Those methods are not considered economical. Therefore, it was a general practice to use charcoal along with salt to reduce the soil resistivity. Bentonite is worldwide acceptable material, that had led our interest towards study of bentonite at first. It was concluded that bentonite is a clay which is non-corrosive, environment friendly. Whereas bentonite is suitable only when there is moisture present in the soil, as in the absence of moisture, cracks will appear on the surface which will provide an open passage to the air, resulting into increase in the resistivity. Furthermore, bentonite without moisture does not have enough bonding property, moisture retention, conductivity, and non-leachability. Therefore, bentonite was used along with the other backfill material to overcome the dependency of bentonite on moisture. Different experiments were performed to get the best ratio of bentonite and carbon backfill. It was concluded that properties will highly depend on the quantity of bentonite and carbon-based backfill material.

Building Blocks for the Next eGovernment Era: Exploratory Study Based on Dubai and UAE’s Ministry of Happiness Communication in 2020

Dubai and the UAE governments have been investing in technology and digital communication for a long time. These governments are pioneers in introducing innovative strategies, policies and projects. They are also recognized worldwide for defining and implementing long term public programs. In terms of eGovernment Dubai and the UAE rank among the world’s most advanced. Both governments have surprised the world a few years ago by creating a Happiness Ministry. This paper focuses on UAE’s government digital strategies and its approach to the next era. The main goal of this exploratory study is to understand the new era of eGovernment and transfer of the happiness and wellness programs. Data were collected from the corpus latente and analysis was anchored in qualitative methodology using content analysis and observation as analysis techniques. The study allowed to highlight that the 2020 government reshuffle has a strong focus on digital reorganisation and digital sustainability, one of the newest trends in sustainability. Regarding happiness and wellbeing portfolio, we were able to observe that there has been a major change within the government organisation: The Ministry of Happiness was extinct and the Ministry of Community Development will manage the so-called ‘Happiness Portfolio’. Additionally, our observation allowed to note the government dual approach to governance: one through digital transformation, thus enhancing the digital sustainability process and, the second one trough government development.

A Comparative Study of Medical Image Segmentation Methods for Tumor Detection

Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

A Study of Soil Heavy Metal Pollution in the Manganese Mining in Drama, Greece

The release of heavy metals into the environment has increased over the last years. In this study, 25 soil samples (0-15 cm) from the fields near the mining area in Drama region were selected. The samples were analyzed in the laboratory for their physicochemical properties and for seven “pseudo-total’’ heavy metals content, namely Pb, Zn, Cd, Cr, Cu, Ni, and Mn. The total metal concentrations (Pb, Zn, Cd, Cr, Cu, Ni and Mn) in digests were determined by using the atomic absorption spectrophotometer. According to the results, the mean concentration of the listed heavy metals in 25 soil samples are Cd 1.1 mg/kg, Cr 15 mg/kg, Cu 21.7 mg/kg, Ni 30.1 mg/kg, Pd 50.8 mg/kg, Zn 99.5 mg/kg and Mn 815.3 mg/kg. The results show that the heavy metals remain in the soil even if the mining closed many years ago.

The Study of Digital Transformation Skills and Competencies Framework at Umm Alqura University

The lack of digital transformation professionals could prevent Saudi Arabia’s universities from providing digital services. The task of understanding what digital skills are needed within an organization, measuring the existing skills, and developing or attracting talents is a complex task. This paper provides a comprehensive analysis of the digital transformation skills needed in the organizations who seek digital transformation and identifies the skills and competencies framework DigSC built on Skills Framework for the Informational Age (SFIA) framework that is adopted by the Ministry of Communications and Information Technology (MCIT) in Saudi Arabia. The framework adopted identifies the main digital transformation skills clusters, categories and levels of responsibilities for each job description to fill the gap between this requirement and the digital skills supplied by the Umm Alqura University (UQU).