Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncoordinated Spectrum Sharing in Millimeter Wave Networks Using Carrier Sensing

We propose using Carrier Sensing (CS) for distributed interference management in millimeter-wave (mmWave) cellular networks where spectrum is shared by multiple operators that do not coordinate among themselves. In addition, even the base station sites can be shared by the operators. We describe important challenges in using traditional CS in this setting and propose enhanced CS protocols to address these challenges. Using stochastic geometry, we develop a general framework for downlink coverage probability analysis of our shared mmWave network in the presence of CS and derive the downlink coverage probability expressions for several CS protocols. Our work is the first to investigate and analyze (using stochastic geometry) CS for mmWave networks with spectrum and BS sites shared among non-coordinating operators. We evaluate the downlink coverage probability of our shared mmWave network using simulations as well as numerical examples based on our analysis. Our evaluations show that our proposed approach leads to an improvement in coverage probability, compared to the coverage probability with no CS, for higher values of signal-to-interference and noise ratio (SINR). Interestingly, our evaluations also reveal that for lower values of SINR, not using any CS is the best strategy in terms of the downlink coverage probability.
Bblocks Software for Thermoeconomic Analysis of Dual-purpose Power and Desalination Plants

This paper presents the main structure of the Bblocks (Building Blocks) software. Bblocks was a joint research project developed by the Research Centre for Energy Resources and Consumption, CIRCE, directed by A. Valero, and sponsored by The International Centre for Water and Energy Systems, ICWES, directed by Dr. D. Al Gobaisi. Bblocks was conceived for the thermodynamic and thermoeconomic analysis of dual-purpose power and desalination plants. Once a plant configuration was designed by means of its guided graphical interface, its steadystate performance could be easily calculated. Sensitivity analysis and thermoeconomic analysis of the configuration could be further performed, if desired. The end objective of Bblocks is then to search the optimum dual plant configuration in terms of energy efficiency, with the help of a user-friendly software tool. Prof. Y. El-Sayed also actively collaborated in the design phase of Bblocks. His visionary research analysis of 27 feasible configurations to provide power (and water), including its own thermoeconomic optimization procedure, was a good start up to BBlocks. Moreover, some costing and modelling equations (including part load behaviour) developed in this analysis were included in Bblocks. He also visualized the need of a friendly-user interface that could allow a simple layout of any new configuration and its consequent analysis, taking into account the increasing capabilities of present computers.
An affinity propagated clustering aided computerized Inherent Seeded Region Growing and Deep learned Marching Cubes Algorithm (ISRG‐DMCA) based three dimensional image reconstruction approach

In this manuscript, the novel three dimensional (3D) image reconstruction approach based on affinity propagated clustering aided computerized Inherent Seeded Region Growing and Deep learned Marching Cubes Algorithm (ISRG‐DMCA) is proposed. The major purpose of this manuscript is to divide the brain tumor based on Shapelets. Here, the information about the shape/depth that can be obtained in every two dimensional (2D) image on the image stack is handled to acquire a 3D reconstruction, which provides high accurate 3D view of tumor Region of Interest (ROI). Then, the 3D model is rendered with the help of the proposed Deep learned Marching Cubes Algorithm (Deep MCA) at 3D reconstruction technique. The performance of the proposed method is executed in MATLAB. The simulation results show that the proposed ISRG‐DMCA algorithm attains a higher detection rate 14.117%, 5.435%, higher accuracy rate 9.556%, 26.41% and lower execution time 66.667%, 75%, compared with the existing methods, like Improved Marching Cubes Algorithm (IMCA), Improved CNN‐CRF method, respectively. In the proposed ISRG‐DMCA method, the volume of the tumor has a length of 2.56 mm. Finally, the simulation outcomes demonstrate that the proposed ISRG‐DMCA method can be able to find the optimal solutions efficiently and accurately.
Exploring the relationship between board characteristics and environmental disclosure: Empirical evidence for European firms

Research Question: Does the effect of selected board characteristics is contingent on the level of environmental disclosure by European firms. Motivation: Sustainable development is based on a vision where the protection of the environment, social progress and economic efficiency are indispensable. Idea: This research aims to investigate the effect of selected board characteristics on the level of environmental disclosure by European firms. Data: This study used a sample of 220 European companies under the context of a new dataset, namely, DataStream ASSET database. Corporate environmental disclosure index (CEDI) is developed to measure the level of environmental information. Tools: This index is calculated based on the CEDI-related items provided by DataStream ASSET4. Findings: The multiple linear regression analyses were used to verify the effect of the board of directors’ characteristics on the level of environmental disclosure. The results indicate that the board size and board independence have a statistically significant and positive impact on the level of environmental disclosure. Contribution: The findings have important implications for different policymakers; It helps inform regulatory regulators of the importance of good corporate governance to lay the foundation for comprehensive environmental disclosure by establishing valuable relationships with different stakeholders.
Conductive Supramolecular Polymer Nanocomposites with Tunable Properties to Manipulate Cell Growth and Functions

Synthetic bioactive nanocomposites show great promise in biomedicine for use in tissue growth, wound healing and the potential for bioengineered skin substitutes. Hydrogen-bonded supramolecular polymers (3A-PCL) can be combined with graphite crystals to form graphite/3A-PCL composites with tunable physical properties. When used as a bioactive substrate for cell culture, graphite/3A-PCL composites have an extremely low cytotoxic activity on normal cells and a high structural stability in a medium with red blood cells. A series of in vitro studies demonstrated that the resulting composite substrates can efficiently interact with cell surfaces to promote the adhesion, migration, and proliferation of adherent cells, as well as rapid wound healing ability at the damaged cellular surface. Importantly, placing these substrates under an indirect current electric field at only 0.1 V leads to a marked acceleration in cell growth, a significant increase in total cell numbers, and a remarkable alteration in cell morphology. These results reveal a newly created system with great potential to provide an efficient route for the development of multifunctional bioactive substrates with unique electro-responsiveness to manipulate cell growth and functions.
Biogenic Synthesis of Magnetite Nanoparticles Using Leaf Extract of Thymus schimperi and Their Application for Monocomponent Removal of Chromium and Mercury Ions from Aqueous Solution

Currently, plant templated synthesis of magnetite iron oxide nanoparticles (Fe3O4 NPs) was emerged for multifunctional purposes. In this study, the leaf extract of the plant Thymus schimperi was utilized to synthesize Fe3O4 NPs. The synthesized NPs were characterized by using technical tools such as X-ray diffraction (XRD) spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy-energy dispersive X-ray (SEM-EDX) analysis, and ultraviolet-visible (UV-Vis) spectroscopy, and thermal analysis (TGA-DTA). The XRD result corroborated the presence of desired phase formation having pure cubic face centered phase structure with average crystallite particle size ranging from 20 nm to 30 nm. SEM micrographs confirmed microstructural homogeneities and remarkably different morphology of Fe3O4 NPs. Mercury (II) and chromium (VI) removal efficiencies of Fe3O4 NPs were found to be 90% and 86% from aqueous solution at initial concentration of 20 mg/L, respectively. Various factors which affect the metal ion removal efficiency such as metal ion initial concentrations, pH, contact time, and adsorbent dosage were also studied. The optimum pH and contact time for chromium ion adsorption were pH 5 and 60 min and that of mercury were observed to be pH 7 and 90 min, respectively. The Langmuir isotherm was best fitted for sorption of Hg(II) ion, and the Freundlich isotherm was best fitted with sorption of Cr(VI) ion onto the surface of Fe3O4 NPs. The mechanism of adsorption of both Hg(II) and Cr(VI) ions was obeyed pseudo 2nd order kinetics. The recorded percent removal efficiencies revealed that these Fe3O4 NPs synthesized through leaf extract of the plant called Thymus schimperi have demonstrated excellent potentiality in the remediation of heavy metal ions. The synthesized Fe3O4 NPs were regenerated (reused) for adsorptive removal of Hg(II) and Cr(VI) for five consecutive cycles without significant loss of removal efficiency. Fe3O4 NPs were reused with only 4.17% loss of removal efficiency against Hg(II) and only 3% loss of removal efficiency against Cr(VI) metal ions.
Language Assessment Courses: An Investigation of the Course Instructors’ Pedagogical and Assessment Practices

Upon recognizing the significance of assessment literacy as a necessity for modern professional teachers, the quality of assessment courses has been examined from different angles. The present research aimed to examine the nature and functionality of assessment training at Iranian state universities in fostering the development of language assessment literacy (LAL), with a specific focus on the course instructors’ pedagogical practices (in terms of instructional materials/content and pedagogical practices) and assessment practices (including both formative and summative assessment). One hundred three course instructors were surveyed through a set of open-ended questions, and two course instructors’ pedagogical and assessment practices were observed throughout an educational semester. Based on the content and descriptive statistical analysis of the data, a lack of divergence in the instructors’ teaching and assessment practices was observable, with the majority of the instructors adhering to traditional methods, showing no inclination to adopt innovative practices. Lack of a balanced focus on all the core elements of LAL, being theory-laden and disconnected from practice in assessment, and use of dated teaching materials were recognized as factors or inappropriate practices on the part of the course instructors that might hinder the development of LAL in the researched context. Furthermore, a set of key action which might be taken by the course instructors to reduce the obstacles in developing and maintaining LAL has been suggested. Finally, limitations of the study and suggestions for future studies on LAL have been mentioned.
Effects of Tele-Exercise on Body Weight, Body Mass Index, and Fat Mass of Obese Employees

Purpose: Obesity is a growing health problem in Indonesia caused by physical inactivity. Meanwhile, employees are a group that is susceptible to obesity as they often have limited time while working sedentarily in front of a desk or computer, especially during the COVID-19 pandemic. This causes risks of many cardiovascular diseases, obesity and can indirectly cause death. Tele-exercise, a live online video exercise, may be the solution to this problem. Therefore, the purpose of this study is to analyse the effects of tele-exercise on body weight, BMI, and fat mass percentage as indicators of obesity. Methods: The research was conducted from July 2020 to January 2021 according to the policy regarding the pandemic. Also, it used a pre-post quasy experimental design. A total of 39 subjects were given tele-exercise involving 2 strength training and 1 cardio training per week for 3 months. Findings: Subsequently, the results showed that exercise had a significant effect (p<0.05) on BMI and body weight, while fat mass percentage only decreased significantly (p<0.05) from the second to third assessment. Originality: To our knowledge, this is the first study analysing the effects of tele-exercise on obese employee’s body weight, body mass index and fat mass. Conclusion: This proves that tele-Exercise is an effective therapy for obesity that does not require a large space, and has beneficial online aspects, especially during the pandemic. The timing of measurement and hydration status should be considered to assess the body composition.
Occurrence of comorbidity with colorectal cancer and variations by age and stage at diagnosis.

BACKGROUND While age and stage at diagnosis are known to affect treatment choices and survival from colorectal cancer (CRC), few studies have investigated the extent to which these effects are influenced by comorbidity. In this study, we describe the occurrence of comorbidity in CRC cases in South Australia and associations of comorbidity with age, stage and the age-stage relationship. Furthermore, we report on the association of individual comorbidities with age and stage at diagnosis. METHODS The South Australian Cancer Registry (SACR) provided CRC data (C18-C20, ICD-10) for 2004-2013 diagnoses. CRC data were linked with comorbidity data drawn from hospital records and health insurance claims. Logistic regression was used to model associations of comorbidity with age and stage. RESULTS For the 8462 CRC cases in this study, diabetes, peptic ulcer disease, and previous cancers were the most commonly recorded co-existing conditions. Most comorbidities were associated with older age, although some presented more frequently in younger people. Patients at both ends of the age spectrum (<50 and 80 + years) had an increased likelihood of CRC diagnosis at an advanced stage compared with other ages (50-79 years old). Adjusting for comorbidities moderated the association of older age with advanced stage. Conditions associated with advanced stage included dementia (OR = 1.25 (1.01-1.55)), severe liver disease (OR = 1.68 (1.04-2.70)), and a previous cancer (OR = 1.18 (1.08-1.28)). CONCLUSION Comorbidities are prevalent with CRC, especially in older people. These comorbidities differ in their associations with age at diagnosis and stage. Dementia and chronic heart failure were associated with older age whereas inflammatory bowel disease and alcohol access were associated with younger onset of the disease. Severe liver disease and dementia were associated with more advanced stage and rheumatic disease with less advanced stage. Comorbidities also interact with age at diagnosis and appear to vary the likelihood of advanced-stage disease. CRC patient have different association of age with stage depending on their comorbidity status.
High gain Vivaldi antenna from 26 up to 40 GHz for 5G applications

We propose a directive broadband and high gain Vivaldi antenna in the Ka‐band (26–40 GHz) for 5G applications. To increase the gain of this antenna, we use a substrate lens and the quasi‐substrate integrated waveguide structure with the aim of reducing reflected waves and emphasizing the traveling waves. With this method, the gain is increased by 4.5 dBi in average and 7.5 dBi in the peak. The antenna has a good impedance matching in the whole band.
Chapter 5 - A technological infrastructure to sustain Internetworked Enterprises

In the Web 3.0 scenario, where information and services are connected by means of their semantics, organizations can improve their competitive advan- tage by publishing their business and service descriptions. In this scenario, Seman- tic Peer to Peer (P2P) can play a key role in defining dynamic and highly reconfi- gurable infrastructures. Organizations can share knowledge and services, using this infrastructure to move towards value networks, an emerging organizational model characterized by fluid boundaries and complex relationships. This chapter collects and defines the technological requirements and architecture of a modular and multi-Layer Peer to Peer infrastructure for SOA-based applications. This technological infrastructure, based on the combination of Semantic Web and P2P technologies, is intended to sustain Internetworked Enterprise configurations, de- fining a distributed registry and enabling more expressive queries and efficient routing mechanisms. The following sections focus on the overall architecture, while describing the layers that form it.
Microorganisms of Microbial Mats from an Alkaline Hot Spring of Baikal Rift Zone as Bioagents in a Biofuel Cell

Abstract The microbial diversity, transformation potential and ability of microorganisms of the microbial mat consortium of the Kucheger thermal spring (Baikal Rift Zone) to generate electricity were studied. High-throughput sequencing showed the predominance of representatives of the Proteobacteria phylum in the microbial mat community (85.5% of the number of classified bacterial sequences). Among Proteobacteria, filamentous sulfur bacteria of the genus Thiothrix are the most numerous (66.1%). In addition, bacteria of the families Rhodocyclaceae (3%) and Comamonadaceae (7.3%) were present in the mat community. The Bacteroidetes phylum was represented by sequences belonging mainly to the Flavobacteriaceae family (6.8%). The sequences of other phyla accounted for no more than 0.5% of the total number of classified sequences. A wide metabolic activity of microorganisms of mat Kucheger-15 was revealed. The high electrogenic ability of microorganisms of the consortium of microbial mats Kucheger-15 in biofuel cells (BFCs) is shown. Mat-based BFCs generated electricity by adding substrates such as peptone, cellulose, starch. Peptone, glucose, tween-80, starch, sodium acetate, and cellulose were used as substrates. Peptone turned out to be the most effective substrate for the production of electricity in BFCs based on Kucheger microbial mat microorganisms. The addition of a mixture of these substrates to the anolyte (the concentration of each of them is 2.5 g/l) made it possible to achieve some increase in energy release (especially the output current) compared to BFC based on each of these substrates separately. The presence of a wide variety of different microorganisms with broad substrate specificity, the ability to function under extreme conditions (high temperature, high pH values), their well-coordinated work and adaptation to each other and to the resulting metabolites, and stability over time allow us to speak of high prospects for the use of hot spring mats in BFC technologies.
Secure Multi-Party Quantum Summation Based on Quantum Homomorphic Encryption

Secure multi-party computation has been playing a fundamental role in terms of classical cryptography. Quantum homomorphic encryption (QHE) could compute the encrypted data without decryption. At present, most protocols use a semi-honest third party (TP) to protect participants’ secrets. We use a quantum homomorphic encryption scheme instead of TP to protect the privacy of parties. Based on quantum homomorphic encryption, a secure multi-party quantum summation scheme is proposed in which N participants can delegate a server with strong quantum computing power to assist computation. By delegating the computation and key update processes to a server and a semi-honest key center, participants encrypt their private information data using Pauli operators to get the sum. Besides, the server can design and optimize the summation lines itself, and the correct results can be obtained even if the secret information is negative. The correctness analysis showed that the participants could correctly obtain the results of the calculation. The security analysis proves the scheme is resistant to both outside attack and participant’s attack, and is secure against collusive attack by up to N-2 participants. From the theoretical point of view, our protocol can extend to other secure multi-party computing problems.
Comparison of Anxiety and Depression Among HIV-Positive and HIV-Negative Pregnant Women During COVID-19 Pandemic in Ekiti State, Southwest Nigeria

Purpose Coronavirus disease 2019 (COVID-19) pandemic is the significant public health crisis of the 21st century that has disrupted personal, local, and international territorial relationships. Earlier studies have shown that people with HIV were at least twice at risk of dying from COVID-19 than the general population. There are also deep concerns about the indirect impact of COVID-19 on women within the reproductive age group in Sub-Saharan Africa who were already struggling to access reproductive healthcare services. In addition, pregnant HIV-positive women have an increased rate of anxiety and depression. This study, therefore, examined depression and anxiety disorders in pregnant HIV-positive women in response to the COVID-19 pandemic. Patients and Methods This cross-sectional study used a structured questionnaire containing sociodemographic information, Patient Health Questionnaire-9 (PHQ-9), and General Anxiety Disorder-7 (GAD-7) assessment tools. Data obtained were analyzed using Statistical Package for Social Science version 26. Results Ninety-nine (99) representing 78% of 127 pregnant HIV-positive women enrolled in the PMTCT program were eligible for this study. This number matched 99 randomly selected pregnant HIV-negative in the study areas as controls. Major depressive disorder (MDD) and severe anxiety disorder were significantly higher among the HIV-positive group than in the HIV-negative group (PHQ-9 Mean ± SD 8.0 ± 5.4 vs 2.3 ± 2.9; p = 0.000) and (GAD-7 Mean ± SD 5.9 ± 4.6 vs 1.2 ± 2.2; p = 0.000). Conclusion Given the high prevalence of major depressive disorder and severe anxiety disorder among pregnant HIV-positive women, mental health care should be incorporated into the prevention with positive interventions and strategies to reduce the indirect consequences of the COVID-19 pandemic.
Robot grasp detection using multimodal deep convolutional neural networks

Autonomous manipulation has enabled a wide range of exciting robot tasks. However, perceiving outside environment is still a challenging problem in the field of intelligent robotic research due to the lack of object models, unstructured environments, and time-consuming computation. In this article, we present a novel robot grasp detection system that maps a pair of RGB-D images of novel objects to best grasping pose of a robotic gripper. First, we segment the graspable objects from the unstructured scene using the geometrical features of both the object and the robotic gripper. Then, a deep convolutional neural network is applied on these graspable objects, which aims to find the best graspable area for each object. In order to improve the efficiency in the detection system, we introduce a structured penalty term to optimize the connections between multimodality, which significantly mitigates complexity of the network and outperforms fully connected multimodal processing. We also present a two-stage closed-loop grasping candidate estimator to accelerate the searching efficiency of grasping-candidate generation. Moreover, the combination of a two-stage estimator with the grasping detection network naturally improves detection accuracy. Experiments have been conducted to validate the proposed methods. The results show that our method outperforms the state of the art and runs at real-time speed.