Miracle-dz/UniFAR-FTUs huggingface dataset:
Smart Grid Security and Privacy: From Conventional to Machine Learning Issues (Threats and Countermeasures)

Smart Grid (SG) is the revolutionised power network characterised by a bidirectional flow of energy and information between customers and suppliers. The integration of power networks with information and communication technologies enables pervasive control, automation and connectivity from the energy generation power plants to the consumption level. However, the development of wireless communications, the increased level of autonomy, and the growing sofwarisation and virtualisation trends have expanded the attack susceptibility and threat surface of SGs. Besides, with the real-time information flow, and online energy consumption controlling systems, customers’ privacy and preserving their confidential data in SG is critical to be addressed. In order to prevent potential attacks and vulnerabilities in evolving power networks, the need for additional studying security and privacy mechanisms is reinforced. In addition, recently, there has been an ever-increasing use of machine intelligence and Machine Learning (ML) algorithms in different components of SG. ML models are currently the mainstream for attack detection and threat analysis. However, despite these algorithms’ high accuracy and reliability, ML systems are also vulnerable to a group of malicious activities called adversarial ML (AML) attacks. Throughout this paper, we survey and discuss new findings and developments in existing security issues and privacy breaches associated with the SG and the introduction of novel threats embedded within power systems due to the development of ML-based applications. Our survey builds multiple taxonomies and tables to express the relationships of various variables in the field. Our final section identifies the implications of emerging technologies, future communication systems, and advanced industries on the security and privacy issues of SG.
Criteria to appraise top executives for ambidextrous leadership

PurposeThis paper determines and analyses criteria for top executives to use in appraisal systems to promote ambidextrous leadership, enhancing the organization's ability to identify persons who can lead ambidextrously or determining the development potential of existing top executives.Design/methodology/approachUsing a theoretical-conceptual, triangulated approach, the investigation in this paper examines the requirements for top executives to lead ambidextrously. In a subsequent review and frequency analysis, the specific attributes/behaviours a top executive should possess are examined. Analysis of the application of these appraisal criteria is theoretical.FindingsThe criteria listed in this paper (e.g. ambition, courage, vision) can be used to foster ambidextrous leadership when hiring or evaluating performance. These and/or the criteria already existing in an organization should be classified in one of the two categories presented (1. one-dimensional criteria: differentiation between exploration/exploitation is not necessary; 2. multidimensional criteria: differentiation between exploration and exploitation, opening and closing leadership, and first- and second-order changes is necessary) to differentiate the criteria and thereby illuminate their application in the areas of exploration and exploitation. Thus, a corresponding assessment of applicants and/or job holders for ambidextrous leadership is possible.Originality/valueThis theoretical analysis contributes to the literature on top executives' recruitment, performance management, career and succession planning, focusing on ambidextrous leadership and organizational development by elucidating a differentiated concept for appraisal criteria so that the right person can be appointed to the top executive position or assigned to the necessary personnel development programme. Thus identified, a top executive may be positioned to maintain, improve or install ambidextrous leadership and practice in an organization.
Restricted Hamming-Huffman trees

We study a special case of Hamming-Huffman trees, in which both data compression and data error detection are tackled on the same structure. Given a hypercube Q n of dimension n , we are interested in some aspects of its vertex neighborhoods. For a subset L of vertices of Q n , the neighborhood of L is defined as the union of the neighborhoods of the vertices of L . The minimum neighborhood problem is that of determining the minimum neighborhood cardinality over all those sets L . This is a well-known problem that has already been solved. Our interest lies in determining optimal Hamming-Huffman trees, a problem that remains open and which is related to minimum neighborhoods in Q n . In this work, we consider a restricted version of Hamming-Huffman trees, called [ k ]-HHTs, which admit symbol leaves in at most k different levels. We present an algorithm to build optimal [2]-HHTs. For uniform frequencies, we prove that an optimal HHT is always a [5]-HHT and that there exists an optimal HHT which is a [4]-HHT. Also, considering experimental results, we conjecture that there exists an optimal tree which is a [3]-HHT.
Match-Level Fusion of Finger-Knuckle Print and Iris for Human Identity Validation Using Neuro-Fuzzy Classifier

Biometrics is the term for measuring human characteristics. If the term is divided into two parts, bio means life, and metric means measurement. The measurement of humans through different computational methods is performed to authorize a person. This measurement can be performed via a single biometric or by using a combination of different biometric traits. The combination of multiple biometrics is termed biometric fusion. It provides a reliable and secure authentication of a person at a higher accuracy. It has been introduced in the UIDIA framework in India (AADHAR: Association for Development and Health Action in Rural) and in different nations to figure out which biometric characteristics are suitable enough to authenticate the human identity. Fusion in biometric frameworks, especially FKP (finger–knuckle print) and iris, demonstrated to be a solid multimodal as a secure framework. The proposed approach demonstrates a proficient and strong multimodal biometric framework that utilizes FKP and iris as biometric modalities for authentication, utilizing scale-invariant feature transform (SIFT) and speeded up robust features (SURF). Log Gabor wavelet is utilized to extricate the iris feature set. From the extracted region, features are computed using principal component analysis (PCA). Both biometric modalities, FKP and iris, are combined at the match score level. The matching is performed using a neuro-fuzzy neural network classifier. The execution and accuracy of the proposed framework are tested on the open database Poly-U, CASIA, and an accuracy of 99.68% is achieved. The accuracy is higher compared to a single biometric. The neuro-fuzzy approach is also tested in comparison to other classifiers, and the accuracy is 98%. Therefore, the fusion mechanism implemented using a neuro-fuzzy classifier provides the best accuracy compared to other classifiers. The framework is implemented in MATLAB 7.10.
RSSGL: Statistical Loss Regularized 3-D ConvLSTM for Hyperspectral Image Classification

Studies on the classification of hyperspectral images (HSIs) based on deep learning are in full swing, especially the spectral–spatial dependent global learning (SSDGL) framework, which is both efficient and robust. However, the global convolutional long short-term memory (GCL) module under this framework fails to take full consideration of the spectral characteristics contained in HSIs, and the hierarchically balanced (H-B) sampling strategy introduced in this framework prevents the training process from converging smoothly. In this article, we develop a novel regularized spectral–spatial global learning (RSSGL) framework. Compared with SSDGL, the proposed framework mainly makes three improvements. Above all, aiming at the problem that the GCL module used in SSDGL cannot fully tap the local spectral dependence, we apply 3-D convolution to the gated units of long short-term memory (LSTM) as an alternative to the GCL module for adjacent and nonadjacent spectral dependencies learning. Furthermore, to extract the most discriminative features, an improved statistical loss regularization term is developed, in which we introduce a simple but effective diversity-promoting condition to make it more reasonable and suitable for deep metric learning in HSI classification. Finally, to effectively address the performance oscillation caused by the H-B sampling strategy, the proposed framework adopts an early stopping strategy to save and restore the optimal model parameters, making it more flexible and stable. Experiments conducted on three representative datasets show that the proposed RSSGL has superior classification performance compared with the existing relatively excellent research methods. The source code is released at https://github.com/swiftest/RSSGL.
Comparing the Safety and Efficacy of L-Glutamine, Voxelotor, and Crizanlizumab for Reducing the Frequency of Vaso-Occlusive Crisis in Sickle Cell Disease: A Systematic Review

Sickle cell disease (SCD) is a group of inherited red blood cell disorders affecting millions worldwide. The median life expectancy of someone with SCD remains significantly low despite improvements in standards of care and the implementation of hydroxyurea therapy. Notably, a 20-year interval existed (after the implementation of hydroxyurea therapy) prior to the approval of other sickle cell medications, namely, l-glutamine, voxelotor, and crizanlizumab. In this systematic review, these new medications' impact on the occurrences of vaso-occlusive crisis (VOC) events were analyzed and the adverse events of each were noted. Further, a secondary analysis was conducted to determine the effect of combination therapies, whether synergistic, antagonistic, or additive. The systematic review was conducted following the PRISMA 2020 guidelines. The effect-based and dose-effect-based approaches were utilized to determine the combined drugs combination index based on the recommended dosage to achieve an efficacy of 50%. L-glutamine and crizanlizumab were effective in reducing the frequency of VOC (p= 0.0216 and p = 0.02). Voxelotor effect on the reduction of VOC occurrences was not significant, however, its effect on increasing hemoglobin levels was significant (p= <0.001). In all three therapies, pain was the most common adverse event reported by participants. The analysis of combination therapies revealed that voxelotor plus l-glutamine was synergistic, voxelotor plus crizanlizumab was antagonistic, and l-glutamine plus crizanlizumab was additive. Thus, voxelotor plus l-glutamine combination therapy may be more beneficial to sickle cell disease patients. As such, robust combination drug studies for approved therapies used in SCD should be initiated with a specific focus on voxelotor plus l-glutamine. Additionally, the development of medications that lessen the pain burden in sickle cell disease patients should also be prioritized.
To What Extent Should Qualitative Inquiry Be Scientific? Notes From and Inspired by an Unscripted Panel Presentation

The components of The Qualitative Report - TQR learning community – including the journal, the conference, and the NSU qualitative research graduate certificate – provide multiple opportunities for scholars to connect and collaborate. This paper is an extension of a moderated panel presentation from TQR 2021 in which we aimed to provide an organic demonstration of how we, as members of the TQR community, aimed to learn from each other through a process of personal construction of understanding, followed by social re-construction of our understanding of the same phenomenon in response to others’ responses. To prepare for the session, five members of the TQR learning community independently developed responses to the question: “To what extent should qualitative inquiry be scientific? ” Prior to the conference session, panel members and an invited moderator held periodic virtual meetings to negotiate aspects of the upcoming presentation. This paper consists of re-presented panelist and moderator reflections, comments, and responses, re-ordered to create an engaging narrative that shares commonalities and contrasts revealed through the process of reflection. We begin the multiple dialogue with excerpts which illustrate participants’ reflections to their invitations to participate, continue with excerpts to show thoughts and transitions at key points of the presentation preparation process, and ending with new questions inspired by involvement in this collaborative process.
Working Capital Financing for MSMEs in the Pandemic Era: Challenges and Opportunities

The COVID-19 pandemic has forced Indian micro, small and medium enterprises (MSMEs) to find survival techniques aided by expanded public policy prerogatives. The shock has left MSMEs in a state of existential crisis, but perhaps the actual issues lie in managing working capital finance (WCF). The article aimed to construct solutions for sustaining the WCF for MSMEs post-pandemic while acknowledging the obstacles. Following the new normal, innovation and technology acceleration have prompted a map of action for resolving WCF requirements in coping with bottlenecks. The current analysis likely helped MSMEs, financiers, governments and others rethink their WCF strategies.
Research on Formation Flight Control of Cooperative UAV

The multi-UAV control characteristics were studied based on the architecture of Agent.The model of relative motion of formation flight was established in the path coordinate frame of the wing UAV.Considering the application of engineer,the formation control of multi-UAV with PID which through adjust relative distance of wing UAV and lead UAV.In The Ground Control Station,the 3D-program was developed by Creator Vega.The ground monitor software for monitoring the flight condition of UAV was developed by MapX. GMS.
A Survey on Novel Services in Smart Home (Optimized for Smart Electricity Grid)

II PREFACE . III ACKNOWLEDGMENT . IV TABLE OF CONTENTS . V LIST OF FIGURES . IX LIST OF TABLES . XI ABBREVIATIONS . XII CHAPTER 1: INTRODUCTION . 1 1.1 ASSIGNMENT . 1 1.2 MOTIVATION . 1 1.3 RESEARCH OBJECTIVES . 1 1.4 METHODOLOGIES . 4 1.5 REPORT OUTLINE . 6 CHAPTER 2: INTERNET OF THINGS (IOT) . 7 2.
Potential of C-Phenylcalix[4]Resorcinarene Epoxide Compound as Drug Delivery Agent in Breast Cancer Cells MCF-7

Cancer therapy through conventional chemotherapy has been widely applied; however, one of the main disadvantages of chemotherapy is the non-selective targeting of cancer cells which causes various adverse side effects. The development of drug delivery agents that are more selective and effective in cancer therapy needs to be performed so that the drugs have a therapeutic effect and minimize side effects. In this study, the compound C-phenylcalyx[4]resorcinarene epoxide (CFKRE) has acted as a drug delivery agent because it can form host complex interactions with ligands. The CFKRE compound was synthesized through two reaction steps: the condensation and alkylation reactions of the epoxide. The structure was analyzed using FTIR, 1H-, and 13C-NMR spectrophotometers and then tested for in vitro cytotoxicity using the MTT assay. The results showed that 70% yield of CFKRE was obtained. Molecular docking analysis of CFKRE compounds against PDGFR and EGFR proteins showed high binding energy compared to conventional chemotherapeutic agents. Molecular dynamic studies showed that CFKRE compounds could form a host-ligand complex with a −350.4 kcal/mol binding energy. Cytotoxic assay of CFKRE compound against MCF-7 breast cancer cells and Vero cells gave IC50 values of 4.04 and 29.59 μg/mL, respectively. These results indicated that CFKRE compounds are not toxic and have the potential to be utilized as new candidates for drug delivery agents.
Instrumental and Social Influences on Adoption of Collaborative Technologies in Global Virtual Teams

Recent advances in Web-based technologies along with investments in international outsourcing and offshore locations have unquestionably increased the importance of global virtual teams. However, because global virtual teams have their members dispersed in different countries and rely extensively on electronic communication to exchange information, complete tasks, and coordinate activities, their implementation is accompanied by challenges beyond those found in traditional teams whose members often meet face-to-face in the same cultural context. One such challenge has to do with cross-cultural collaboration. Although there is a sense that collaborative technologies offer the essential tools for supporting collaboration, it is unknown whether virtual members will actually adopt collaborative technologies in a cross-cultural setting. To gain knowledge about this potential endemic aspect of crosscultural teamwork, one needs to examine the factors that influence the adoption of collaborative technologies in global virtual teams. Drawing on the work of organizations, cognitive theory, and information systems researchers, this study offers a framework that describes the key components underlying collaborative technology adoption in global virtual teams by integrating both social and instrumental aspects of group work.
AKG Attenuates Cerebral Ischemia-Reperfusion Injury through c-Fos/IL-10/Stat3 Signaling Pathway

Inflammation is dominant in the pathogenesis of ischemic stroke (IS). Alpha-ketoglutarate (AKG), according to previous studies, has demonstrated a variety of pharmacological effects such as antioxidation and inhibitive inflammation activities. However, whether AKG ameliorates cerebral ischemic injury, as well as the underlying molecular events, is still unclear. Therefore, the effect and underlying mechanisms of AKG on ischemic brain injury should be identified. The study established a cerebral ischemia-reperfusion (I/R) model in mice as well as an oxygen-glucose deprivation/reperfusion (OGD/R) model in SH-SY5Y cells, respectively. It was observed that AKG markedly suppressed infarction volume and neuronal injuries and improved the neurological score in vivo. Moreover, AKG reduced the inflammatory response and lowered the expression of proinflammatory cytokines. In vitro, AKG treatment strongly inhibited OGD/R-induced neuronal injury and the proinflammatory factors. It was also found that the increased SOD and GSH levels, as well as the lower ROS levels, showed that AKG reduced oxidative stress in OGD/R-treated SY-SY5Y cells. Mechanistically, AKG largely promoted IL-10 expression in ischemic brain injury and OGD/R-induced neuronal injury. Furthermore, IL-10 silencing neutralized the protective effect of AKG on inflammation. Notably, it was discovered that AKG could upregulate IL-10 expression by promoting the translocation of c-Fos from the cytoplasm to the nucleus. The results indicated that AKG demonstrated neuroprotection on cerebral ischemia while inhibiting inflammation through c-Fos/IL-10/stat3 pathway.
A GaN Microwave Power Amplifier Design Based on the Source/Load Pull Impedance Modeling via Virtual Gain Optimization

Generation of proper source/load pull impedances for a selected GaN device is essential to design a microwave power amplifier for optimum gain and power-added efficiency. As they are obtained, these impedances may not be realizable network functions over the desired frequency band. Therefore, in this paper, first, we introduce a new method to test if the given source and load pull impedances are realizable. Then, a novel numerical procedure is introduced to model the source and load pull impedances as realizable network functions, which in turn results in the optimum power intake and power delivering capacity for the GaN transistor used in the design. In the numerical modelling process, a robust tool called “Virtual Gain Optimization” is presented. Numerically generated realizable source and load impedances are modelled analytically. Eventually, these impedances are synthesized using our automatic Darlington Synthesis Robot software to yield the optimum input and output matching network topologies with component values. Examples are presented to test the realizability of the given source/load pull impedance data. Then, the power intake and delivery capacity of the active device are assessed for a 10W-GaN power transistor, namely “Wolfspeed CGH40010F” over 0.8-3.0 GHz bandwidth. Eventually, the power amplifier is designed and manufactured. It is shown that the computed and the measured performance of the amplifier is very close with 10 Watts output power, 11.4± 0.6 dB gain and 49% to 76 % power added efficiency.
Public Awareness, and Perception towards Chronic Kidney Disease and its Risk Factors in Southern Region, Saudi Arabia

Background: Worldwide, CKDs are the 12th cause of death and the 17th cause of disability, respectively. About 10-13% of the general population had one of the chronic kidney diseases counting more than 500 million persons worldwide. Early diagnosis and treatment of CKD will play an important role in delaying CKD progression [12]. Aim: The current study aims to determine the prevalence and awareness of CKD among the general population and its determinants in Southern region of Saudi Arabia. Methods: A descriptive cross-sectional approach was used targeting all accessible population in Southern Saudi Arabia (including four regions, Aseer region, Albaha region, Najran region, and Jazan region), aged18 years or more and accepting to participate in the study. Data were collected from participants using an online pre-structured questionnaire. The questionnaire covered the following data: participants’ socio-demographic data, participants’ awareness, and participants’ perception towards CKDs, preventive measures and risk. The questionnaire was uploaded online using social media platforms by the researchers and their friends during the period from 20 March 2021 to 20 June 2021. Results: A total of 1317 participants fulfilling the inclusion criteria completed the study questionnaire. Participants’ ages ranged from 18 to 69 years with a mean age of 34.1 12.9 years old. Exactly 255 (19.4%) reported that they had a family member with CKD and 130 (9.9%) of the study respondents had DM, 98 (7.4%) had hypertension, while 20 (1.5%) complained of CKD. Exactly 93% of the study participants had heard about CKDs and 80.8% correctly defined the diseases as a kidney condition that was unable to filter waste, toxins, and fluids from the body. A total of 84.3% reported that chronic kidney disease progresses to kidney failure and 42.9% agreed that chronic kidney disease may not have any symptoms until advanced. The most reported source of knowledge were social media (56%), followed by mass media (22.3%), work (22.1%), books (20.3%), health education campaigns (15.8%), and others (31%). Conclusion: In conclusion, the current study revealed that public awareness in Southern region of Saudi Arabia about CKD and its risk factors is low in contrast to their perception towards the disease and its associated risk. Having information from scientific sources such as books, health education campaigns or study was associated with high awareness level. Key words: Chronic kidney disease, awareness, perception, population, Saudi Arabia, risk factors