bluuebunny/crossref_metadata_2025 huggingface dataset:
Lung Cancer Screening in Greece: A Modelling Study to Estimate the Impact on Lung Cancer Life Years
Authors: Souliotis Kyriakos , Golna Christina , Golnas Pavlos , Markakis Ioannis-Anestis , Linardou Helena , Sifaki-Pistolla Dimitra , Hatziandreou Evi
Published: November 2022

(1) Background: Lung cancer causes a substantial epidemiological burden in Greece. Yet, no formal national lung cancer screening program has been introduced to date. This study modeled the impact on lung cancer life years (LCLY) of a hypothetical scenario of comprehensive screening for lung cancer with low-dose computed tomography (LDCT) of the high-risk population in Greece, as defined by the US Preventive Services Taskforce, would be screened and linked to care (SLTC) for lung cancer versus the current scenario of background (opportunistic) screening only; (2) Methods: A stochastic model was built to monitor a hypothetical cohort of 100,000 high-risk men and women as they transitioned between health states (without cancer, with cancer, alive, dead) over 5 years. Transition probabilities were based on clinical expert opinion. Cancer cases, cancer-related deaths, and LCLYs lost were modeled in current and hypothetical scenarios. The difference in outcomes between the two scenarios was calculated. 150 iterations of simulation scenarios were conducted for 100,000 persons; (3) Results: Increasing SLTC to a hypothetical 100% of eligible high-risk people in Greece leads to a statistically significant reduction in deaths and in total years lost due to lung cancer, when compared with the current SLTC paradigm. Over 5 years, the model predicted a difference of 339 deaths and 944 lost years between the hypothetical and current scenario. More specifically, the hypothetical scenario led to fewer deaths (−24.56%, p < 0.001) and fewer life years lost (−31.01%, p < 0.001). It also led to a shift to lower-stage cancers at the time of diagnosis; (4) Conclusions: Our study suggests that applying a 100% screening strategy amongst high-risk adults aged 50–80, would result in additional averted deaths and LCLYs gained over 5 years in Greece.
Classification, Synthetic, and Characterization Approaches to Nanoparticles, and Their Applications in Various Fields of Nanotechnology: A Review
Authors: Khan Yousaf , Sadia Haleema , Ali Shah Syed Zeeshan , Khan Muhammad Naeem , Shah Amjad Ali , Ullah Naimat , Ullah Muhammad Farhat , Bibi Humaira , Bafakeeh Omar T. , Khedher Nidhal Ben , Eldin Sayed M. , Fadhl Bandar M. , Khan Muhammad Ijaz
Published: November 2022

Nanoparticles typically have dimensions of less than 100 nm. Scientists around the world have recently become interested in nanotechnology because of its potential applications in a wide range of fields, including catalysis, gas sensing, renewable energy, electronics, medicine, diagnostics, medication delivery, cosmetics, the construction industry, and the food industry. The sizes and forms of nanoparticles (NPs) are the primary determinants of their properties. Nanoparticles’ unique characteristics may be explored for use in electronics (transistors, LEDs, reusable catalysts), energy (oil recovery), medicine (imaging, tumor detection, drug administration), and more. For the aforementioned applications, the synthesis of nanoparticles with an appropriate size, structure, monodispersity, and morphology is essential. New procedures have been developed in nanotechnology that are safe for the environment and can be used to reliably create nanoparticles and nanomaterials. This research aims to illustrate top-down and bottom-up strategies for nanomaterial production, and numerous characterization methodologies, nanoparticle features, and sector-specific applications of nanotechnology.
Accelerated Decoloration of Organic Dyes from Wastewater Using Ternary Metal/g-C3N4/ZnO Nanocomposites: An Investigation of Impact of g-C3N4 Concentration and Ni and Mn Doping
Authors: Qamar Muhammad Azam , Shahid Sammia , Javed Mohsin , Shariq Mohammad , Fadhali Mohammed M. , Madkhali Osama , Ali Syed Kashif , Syed Imam Saheb , Awaji Majed Yusef , Shakir Khan Mohd. , Hassan Dalin A. , Al Nasir M. Hisham
Published: November 2022

Wastewater from many sectors that contains hazardous organic pollutants exacerbates environmental contamination. Consequently, outstanding photocatalytic substances that can successfully degrade hazardous substances are needed to provide pollution-free water. From this perspective, zinc oxide/g-C3N4-based composites are desirable due to their low cost, strong reactivity, and environmental friendliness. So, in the current investigation, sequences of Mn/g-C3N4/ZnO (Mn/GZ) and Ni/g-C3N4/ZnO (Ni/GZ) nanocomposites (NCs) containing different concentrations (wt.%) of g-C3N4 were made via the co-precipitation process. The chemical makeup and morphological characteristics of the produced composites were ascertained via the techniques of transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), Fourier transform infrared (FTIR), photoluminescence (PL), and UV spectrophotometry. Methyl orange (MO) and Eriochrome Black T (EBT) dyes were used as target pollutants to assess the composite materials’ photocatalytic effectiveness. Compared to g-C3N4/ZnO and g-C3N4, the produced Mn/GZ and Ni/GZ NCs displayed better photocatalytic activity. The improved photocatalytic efficiency of the Ni/GZ and Mn/GZ NCs might be credited to synergistic interactions at the g-C3N4 and ZnO interface that result in a more efficient separation and conduction of photo-induced charges. Furthermore, the Ni/Mn atoms act as the facilitators to improve electron–hole pair separation and conduction in NCs. The nanocomposites were found to be incredibly stable, with consistently high dye decoloration efficiency over five catalytic cycles. Hence, Ni/GZ and Mn/GZ could potentially be very effective and adaptable photocatalysts for the photocatalytic decoloration of wastewater pollutants.
Treatment of Chronic Hepatitis D with Bulevirtide—A Fight against Two Foes—An Update
Authors: Ferenci Peter , Reiberger Thomas , Jachs Mathias
Published: November 2022

HDV infection frequently causes progression to cirrhosis and hepatocellular carcinoma (HCC). In summer 2020, the first potentially effective drug Bulevirtide (BLV) has been approved for the treatment of HDV by the EMA. BLV is a synthetic N-acylated pre-S1 lipopeptide that blocks the binding of HBsAg-enveloped particles to the sodium taurocholate co-transporting polypeptide (NTCP), which is the cell entry receptor for both HBV and HDV. In this review, we discuss the available data from the ongoing clinical trials and from “real world series”. Clinical trials and real-world experiences demonstrated that BLV 2 mg administered for 24 or 48 weeks as monotherapy or combined with pegIFNα reduces HDV viremia and normalizes ALT levels in a large proportion of patients. The combination of BLV and pegIFNα shows a synergistic on-treatment effect compared with either one of the monotherapies.
Lanthanide-Based Langmuir–Blodgett Multilayers: Multi-Emissive, Temperature-Dependent Thin Films
Authors: O’Neil Alex T. , Kitchen Jonathan A.
Published: November 2022

Multi-emissive compounds have attracted significant attention from the research community owing to the wide array of potential application areas. However, to move towards application, such systems should be readily immobilized by solution-based methods to form soft materials such as gels and films. Herein we report the use of Langmuir–Blodgett (LB) deposition to easily immobilize luminescent lanthanide-based amphiphilic solids into multi-emissive ultrathin LB films, by multilayering different luminescent amphiphiles. Utilizing this technique, we have reliably fabricated dual- and triple-emissive films where the overall emission from the film is tuned. Furthermore, we have demonstrated that these multi-emissive films are temperature-dependent, with emission profiles significantly altering from 294 to 340 K, resulting in colour changes and potential application as ultrathin, contactless ratiometric thermometer coatings.
Recent Progress on the Applications of Nanozyme in Surface-Enhanced Raman Scattering
Authors: Li Dan , Xia Ling , Li Gongke
Published: November 2022

Nanozymes are nanomaterial with natural enzyme-like activity and can catalyze specific reactions for analyte identification and detection. Compared to natural enzymes, they have several benefits, including being steady, low-cost, easy to prepare and store. Based on the promising development of nanozymes in surface-enhanced Raman scattering (SERS), this paper reviews the classification of different types of nanozymes in SERS, including metal-based nanozyme, carbon-based nanozyme, metal-organic framework (MOF)/covalent organic framework (COF)-based nanozyme, and semiconductor-based nanozyme, followed by a detailed overview of their SERS applications in disease diagnosis, food safety, and environmental safety. Finally, this paper discusses the practical shortcomings of nanozymes in SERS applications and makes some suggestions for further research.
Measurement of the Filling Degree and Droplet Size of Individual Double Emulsion Droplets Using Raman Technologies
Authors: Hufnagel Thomas , Stoy Richard , Rädle Matthias , Karbstein Heike P.
Published: November 2022

Double emulsions arouse great interest in various industries due to their ability to encapsulate value-adding ingredients. However, they tend to be unstable due to their complex structure. Several measurement techniques have already been developed to study and monitor the stability of double emulsions. Especially for the measurement of the filling degree of double emulsions, so far there is no reliable method available. In this paper, a measurement system is presented that can measure the filling degree of water-in-oil-in-water (W/O/W) double emulsions by both spectrometrical and photometrical means. The method is based on the Raman effect and does not require any sample preparation, and the measurement has no negative influence on the double emulsion. It is shown that both spectrometric and photometric Raman techniques can reliably distinguish between double emulsions with filling degrees that have a 0.5% difference. Additionally, oil droplet sizes can be photometrically measured. Furthermore, the measurement system can be integrated into both inline and online emulsification processes.
A Cellulose Nanofiber Capacitive Humidity Sensor with High Sensitivity and Fast Recovery Characteristics
Authors: Hou Zhaonan , Ma Zhiyan , Guan Xin , Zhao Hongran , Liu Sen , Fei Teng , Zhang Tong
Published: November 2022

Humidity sensors with high sensitivity and fast response characteristics are of great interest for researchers. In this work, capacitive humidity sensors were fabricated using ionic liquid/cellulose nanofibers (CNFs) as the composited sensing film. The porous CNFs are beneficial for preparing sensing films via a solution process, and the ionic liquid could be uniformly dispersed in the films. The humidity-sensing performance of the as-prepared sensors was investigated. The optimized sensor showed a high response (27.95 pF/% RH) in a wide humidity range (11–95% RH) and a fast response speed in the adsorption process (the recovery time was only ~1 s). The high response of the sensors was attributed to the polarization at the interface between the electrolyte and the metal electrode, while the fast recovery was due to the rapid desorption of water molecules on the sensing films. Finally, the application of the obtained sensors in human breath monitoring was explored.
Children’s Self-Esteem and Attitudes toward Disability, Perceived Competence and Morality: The Indirect Effect of Cognitive Empathy
Authors: Maftei Alexandra
Published: November 2022

The present study explored children’s attitudes toward disability and the links with demographic factors (i.e., gender) and personal factors (i.e., empathy, sympathy, self-esteem). Our sample comprised 405 children aged 9 to 11 (M = 9.88, SD = 0.65, 47.4% males). First, we explored the links between self-esteem, empathy (cognitive and affective), and attitudes toward disability. Then, by using three scenarios involving a child in a wheelchair (Group 1), a child with an intellectual disability (Group 2), and a child with visual impairment (Group 3), we investigated the perceived competence and morality of these characters. The results suggested that cognitive empathy mediated the link between self-esteem and attitudes toward disability. Moreover, our data suggested that the character in a wheelchair (Group 1) received the highest scores regarding morality and competence, whereas the character with an intellectual disability (Group 2) received the lowest scores. We discuss the present findings regarding their practical implications for inclusive education strategies.
An Adaptive Downsampling FPGA-Based TDC Implementation for Time Measurement Improvement
Authors: Dikopoulos Evangelos , Birbas Michael , Birbas Alexios
Published: November 2022

In this work, we present a compact “adaptive downsampling” method that mitigates the nonlinearity problems associated with FPGA-based TDCs that utilize delay lines. Additionally, this generic method allows for trade-offs between resolution, linearity, and resource utilization. Since nonlinearity is one of the predominant issues regarding delay lines in FPGA-based TDCs, combined with the fact that delay lines are utilized for a wide range of TDC architectures (not limited to the delay-line TDC), other implementations (e.g., Vernier or wave union TDCs), also in different FPGA devices, can directly benefit from the proposed adaptive method, with no need for either custom routing or complex tuning of the converter. Furthermore, implementation-related challenges regarding clock skew, measurement uncertainty, and the placement of the TDC are discussed and we also propose an experimental setup that utilizes only FPGA resources in order to characterize the converter. Although the TDC in this work was implemented in a Xilinx Virtex-6 device and was characterized under different operational modes, we successfully optimized the converter’s nonlinearity and resource utilization while retaining single-shot precision. The best performing (in terms of linearity) implementation reached DNLrms and INLrms values of 0.30 LSB and 0.45 LSB, respectively, and the single-shot precision (σ) was 9.0 ps.
Novel Organotin(IV) Complexes of 2-[4-Hydroxy-3-((2-hydroxyethylimino)methyl)phenylazo]benzoic Acid: Synthesis, Structure, Noncovalent Interactions and In Vitro Antibacterial Activity
Authors: Debnath Pratima , Debnath Paresh , Roy Manojit , Sieroń Lesław , Maniukiewicz Waldemar , Aktar Tamanna , Maiti Debasish , Novikov Alexander S. , Misra Tarun Kumar
Published: November 2022

Three new organotin(IV) complexes, [Me3Sn(H2L)]2 (1), Bu3Sn(H2L) (2), and [(Bu2Sn(H2L))2O]2 (3) were synthesized by the reaction of 2-[4-hydroxy-3-((2-hydroxyethylimino)methyl)phenylazo]benzoic acid (H3L) with appropriate alkyltin(IV) precursors. The complexes were characterized by elemental analysis, IR, and multinuclear (1H, 13C and 119Sn) NMR spectroscopy. Further, the complex 1 was analyzed by single-crystal X-ray analysis. It displays a 24-membered cyclic dimeric Me3SnIV(H2L) unit where the ligand act as a bridging framework using its carboxylate-O and phenoxy-O atoms. The Sn(IV) adopts distorted trigonal-bipyramidal geometry. In the solution state, the structures were determined by 119Sn-NMR spectroscopy, and the complexes 1 and 2 have distorted tetrahedral geometry, whereas complex 3 shows distorted trigonal-bipyramidal geometry around the tin centres. The Hirshfeld surface analysis and DFT calculations, together with a topological analysis of the electron density distribution in the crystal structure of complex 1, indicate that its molecular packing determined by various noncovalent interactions, including stacking and hydrogen bonding. The antibacterial studies of the ligand and the complexes (1–3) against gram-negative bacteria viz. Klebsiella pneumoniae (A),Vibrio cholerae (M) and Shigella boydii (Q) and gram-positive bacteria viz.Staphylococcus aureus (J), Streptococcus pneumonia (K) are promising and the compounds can be treated as potential common antibacterial materials.
Dataset on Force Myography for Human–Robot Interactions
Authors: Zakia Umme , Menon Carlo
Published: November 2022

Force myography (FMG) is a contemporary, non-invasive, wearable technology that can read the underlying muscle volumetric changes during muscle contractions and expansions. The FMG technique can be used in recognizing human applied hand forces during physical human robot interactions (pHRI) via data-driven models. Several FMG-based pHRI studies were conducted in 1D, 2D and 3D during dynamic interactions between a human participant and a robot to realize human applied forces in intended directions during certain tasks. Raw FMG signals were collected via 16-channel (forearm) and 32-channel (forearm and upper arm) FMG bands while interacting with a biaxial stage (linear robot) and a serial manipulator (Kuka robot). In this paper, we present the datasets and their structures, the pHRI environments, and the collaborative tasks performed during the studies. We believe these datasets can be useful in future studies on FMG biosignal-based pHRI control design.
[18F]FDG PET/CT in Large Vessel Vasculitis: The Impact of Expertise and Confounders on Image Analysis
Authors: Antunovic Lidija , Artesani Alessia , Coniglio Michael , Oyen Wim J. G. , Ciccarelli Michele , Selmi Carlo , Chiti Arturo , Sollini Martina
Published: November 2022

Background: Diagnosis of vasculitis is challenging. To avoid invasive approaches, clinical guidelines recommend the use of diagnostic imaging. This study aimed at evaluating the diagnostic accuracy of [18F]-fluorodeoxyglucose ([18F]FDG) position emission tomography/computed tomography (PET/CT) in large vessel vasculitis (LVV) and how this is affected by inter-operator variability. Methods: A total of 279 patients who performed [18F]-FDG PET/CT for suspicion of LVV were retrospectively analyzed. We tested the qualitative and semi-quantitative analysis and parameters influencing image quality and interpretation. Exams were evaluated by two readers with different experience and their performance was compared. Results: LVV diagnosis was confirmed in 81 patients. [18F]-FDG PET/CT accuracy was 73% and 67% for the expert reader and less experienced reader, respectively. The expert reader overall performed better than the less experienced one, with higher accuracy in patients with normal BMI (77.3 vs. 63.8%), normal level of glycemia (73.3 vs. 65%), younger age (76.6 vs. 68.2%), and when no therapy was in course at time of imaging (76.7 vs. 66.7%). The diagnostic performance of both readers did not improve using semi-quantitative parameters. Conclusions: We confirmed the appropriateness of the recommended criteria for image acquisition and interpretation, underlining the importance of experience in image interpretation for the optimal diagnostic performance of [18F]FDG PET/CT in vasculitis.
Kinesthesia and Temporal Experience: On the ‘Knitting and Unknitting’ Process of Bodily Subjectivity in Schizophrenia
Authors: Sánchez Camilo , Moskalewicz Marcin
Published: November 2022

This paper proposes a phenomenological hypothesis that psychosis entails a disturbance of the two-fold process of the indication function of kinesthesia and the presentification function of touch that affects the constitution of bodily subjectivity. Recent functional connectivity studies showed that the increased synchrony between the right anterior insula and the default mode network are associated with psychosis. This association is proposed to be correlated with the disrupted dynamics between the pre-reflective and reflective temporal experience in psychotic patients. The paper first examines the dynamic nature of kinesthesia and the influence touch and vision exert on it, and then the reciprocal influence with temporal experience focusing on the body’s cyclic sense of temporality and its impact on physiology and phenomenology. Affectivity and self-affection are considered in their basic bodily expressions mainly through the concepts of responsivity and receptivity. The overall constitutive processes referred to throughout the article are proposed as a roadmap to develop body-based therapeutic work.
The Sub-Molecular and Atomic Theory of Cancer Beginning: The Role of Mitochondria
Authors: Balzanelli Mario , Distratis Pietro , Lazzaro Rita , Pham Van , Tran Toai , Dipalma Gianna , Inchingolo Francesco , Tomassone Diego , Aityan Sergey , Vergara Sossio , Nguyen Kieu , Isacco Ciro
Published: November 2022

Life as we know it is made of strict interaction of atom, metabolism, and genetics, made around the chemistry of the most common elements of the universe: hydrogen, oxygen, nitrogen, sulfur, phosphorus, and carbon. The interaction of atomic, metabolic, and genetic cycles results in the organization and de-organization of chemical information of what we consider living entities, including cancer cells. In order to approach the problem of the origin of cancer, it is therefore reasonable to start from the assumption that the atomic structure, metabolism, and genetics of cancer cells share a common frame with prokaryotic mitochondria, embedded in conditions favorable for the onset of both. Despite years of research, cancer in its general acceptation remains enigmatic. Despite the increasing efforts to investigate the complexity of tumorigenesis, complementing the research on genetic and biochemical changes, researchers face insurmountable limitations due to the huge presence of variabilities in cancer and metastatic behavior. The atomic level of all biological activities it seems confirmed the electron behavior, especially within the mitochondria. The electron spin may be considered a key factor in basic biological processes defining the structure, reactivity, spectroscopic, and magnetic properties of a molecule. The use of magnetic fields (MF) has allowed a better understanding of the grade of influence on different biological systems, clarifying the multiple effects on electron behavior and consequently on cellular changes. Scientific advances focused on the mechanics of the cytoskeleton and the cellular microenvironment through mechanical properties of the cell nucleus and its connection to the cytoskeleton play a major role in cancer metastasis and progression. Here, we present a hypothesis regarding the changes that take place at the atomic and metabolic levels within the human mitochondria and the modifications that probably drive it in becoming cancer cell. We propose how atomic and metabolic changes in structure and composition could be considered the unintelligible reason of many cancers’ invulnerability, as it can modulate nuclear mechanics and promote metastatic processes. Improved insights into this interplay between this sub-molecular organized dynamic structure, nuclear mechanics, and metastatic progression may have powerful implications in cancer diagnostics and therapy disclosing innovation in targets of cancer cell invasion.
Precision Medicine in Breast Cancer: Do MRI Biomarkers Identify Patients Who Truly Benefit from the Oncotype DX Recurrence Score® Test?
Authors: Galati Francesca , Magri Valentina , Moffa Giuliana , Rizzo Veronica , Botticelli Andrea , Cortesi Enrico , Pediconi Federica
Published: November 2022

The aim of this study was to combine breast MRI-derived biomarkers with clinical-pathological parameters to identify patients who truly need an Oncotype DX Breast Recurrence Score® (ODXRS) genomic assay, currently used to predict the benefit of adjuvant chemotherapy in ER-positive/HER2-negative early breast cancer, with the ultimate goal of customizing therapeutic decisions while reducing healthcare costs. Patients who underwent a preoperative multiparametric MRI of the breast and ODXRS tumor profiling were retrospectively included in this study. Imaging sets were evaluated independently by two breast radiologists and classified according to the 2013 American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) lexicon. In a second step of the study, a combined oncologic and radiologic assessment based on clinical-pathological and radiological data was performed, in order to identify patients who may need adjuvant chemotherapy. Results were correlated with risk levels expressed by ODXRS, using the decision made on the basis of the ODXRS test as a gold standard. The χ2 test was used to evaluate associations between categorical variables, and significant ones were further investigated using logistic regression analyses. A total of 58 luminal-like, early-stage breast cancers were included. A positive correlation was found between ODXRS and tumor size (p = 0.003), staging (p = 0.001) and grading (p = 0.005), and between BI-RADS categories and ODXRS (p < 0.05 for both readers), the latter being confirmed at multivariate regression analysis. Moreover, BI-RADS categories proved to be positive predictors of the therapeutic decision taken after performing an ODXRS assay. A statistically significant association was also found between the therapeutic decision based on the ODXRS and the results of combined onco-radiologic assessment (p < 0.001). Our study suggests that there is a correlation between BI-RADS categories at MRI and ODXRS and that a combined onco-radiological assessment may predict the decision made on the basis of the results of ODXRS genomic test.
Communication Efficient Algorithms for Bounding and Approximating the Empirical Entropy in Distributed Systems
Authors: Shahar Amit , Alfassi Yuval , Keren Daniel
Published: November 2022

The empirical entropy is a key statistical measure of data frequency vectors, enabling one to estimate how diverse the data are. From the computational point of view, it is important to quickly compute, approximate, or bound the entropy. In a distributed system, the representative (“global”) frequency vector is the average of the “local” frequency vectors, each residing in a distinct node. Typically, the trivial solution of aggregating the local vectors and computing their average incurs a huge communication overhead. Hence, the challenge is to approximate, or bound, the entropy of the global vector, while reducing communication overhead. In this paper, we develop algorithms which achieve this goal.
Does Economic Inequality Account for Cross-Country Discrepancies in Relative Social Mobility: An Empirical Investigation
Authors: Muteba Mwamba John Weirstrass , Shiwamya Paul Mumba , Mudiangombe Benjamin Mudiangombe
Published: November 2022

This paper makes use of the Markov Switching model and the K-Means Cluster analysis to estimate the transition probabilities of social mobility and to analyze the impact of social inequalities on intergenerational social mobility. The dataset is a sample of 44 countries and comprises the 2018 social mobility indices, and the 2018 or latest income inequality measures. The data are collected from the OECD Income and Wealth Distribution Databases, and from the world economic forum. It was found that the likelihood of moving upward or downward the social ladder is minimal in both developed and emerging countries. In addition, the paper found that the hypothesis according to which high-income countries have a higher relative social mobility is not necessarily true. The United States, a high-income country, was found to have a lower social mobility, similar to that of Turkey and South Africa. Furthermore, it was found that when poverty decreases, intergenerational social mobility increases in both lower and higher mobility countries. Policies that promote equality of opportunities at all stages of life are therefore recommended to improve intergenerational social mobility.
Management Skills and Styles of School Principals during the COVID-19 Pandemic
Authors: Taun Khazni , Zagalaz-Sánchez Mª Luisa , Chacón-Cuberos Ramón
Published: November 2022

The present study investigated a significant issue among a population with unique characteristics. This research and discussion centered on the challenges of running a school during the COVID-19 pandemic. The central question in this study was, how do school principals perceive their abilities and the skills required to run schools during the pandemic? In addition, this study aimed to assess the awareness of the teachers that were subordinate to these same school principals and the impact of their leadership style. The current study involved 151 teachers and 18 school principals from 18 governmental Bedouin schools in Israel. Structured questionnaires were used to collect data and measure the research variables. To analyze the data, indices and statistical tests were applied using SPSS software. The main research findings indicated that the teachers perceived the leadership styles of their school principals as a formative and rewarding part of their personality and not as an evasive style. The principals reported a high level of availability and accessibility and appropriate communication levels with all of the relevant parties. Moreover, the principals reported their level of decision-making ability as high, their judgment calls as sound, and their organizational planning skills and knowledge-development abilities as excellent. Additionally, cultivating the organizational structure was a priority for the principals; they believed that they could develop a comfortable and supportive organizational atmosphere and that this was the core of their work. The school principals perceived themselves as having the requisite skills, including a high level of ability and efficient team management. Self-confidence and a high level of competence helped the school principals cope with the challenges of the COVID-19 pandemic and traverse them safely.
A Cost-Effective and Compact All-Digital Dual-Loop Jitter Attenuator for Built-Off-Test Applications
Authors: Kim Seungjun , Jin Junghoon , Kim Jongsun
Published: November 2022

A compact and low-power all-digital CMOS dual-loop jitter attenuator (DJA) for low-cost built-off-test (BOT) applications such as parallel multi-DUT testing is presented. The proposed DJA adopts a new digital phase interpolator (PI)-based clock recovery (CR) loop with an adaptive decimation filter (ADF) function to remove the jitter and phase noise of the input clock, and generate a phase-aligned clean output clock. In addition, by adopting an all-digital multi-phase multiplying delay-locked loop (MDLL), eight low-jitter evenly spaced reference clocks that are required for the PI are generated. In the proposed DJA, both the MDLL and PI-based CR are first-order systems, and so this DJA has the advantage of high system stability. In addition, the proposed DJA has the benefit of a wide operating frequency range, unlike general PLL-based jitter attenuators that have a narrow frequency range and a jitter peaking problem. Implemented in a 40 nm 0.9 V CMOS process, the proposed DJA generates cleaned programmable output clock frequencies from 2.4 to 4.7 GHz. Furthermore, it achieves a peak-to-peak and RMS jitter attenuation of –25.6 dB and –32.6 dB, respectively, at 2.4 GHz. In addition, it occupies an active area of only 0.0257 mm2 and consumes a power of 7.41 mW at 2.4 GHz.
Anomalous Behavior Detection Based on the Isolation Forest Model with Multiple Perspective Business Processes
Authors: Fang Na , Fang Xianwen , Lu Ke
Published: November 2022

Anomalous behavior detection in business processes inspects abnormal situations, such as errors and missing values in system execution records, to facilitate safe system operation. Since anomaly information hinders the insightful investigation of event logs, many approaches have contributed to anomaly detection in either the business process domain or the data mining domain. However, most of them ignore the impact brought by the interaction between activities and their related attributes. Based on this, a method is constructed to integrate the consistency degree of multi-perspective log features and use it in an isolation forest model for anomaly detection. First, a reference model is captured from the event logs using process discovery. After that, the similarity between behaviors is analyzed based on the neighborhood distance between the logs and the reference model, and the data flow similarity is measured based on the matching relationship of the process activity attributes. Then, the integration consistency measure is constructed. Based on this, the composite log feature vectors are produced by combining the activity sequences and attribute sequences in the event logs and are fed to the isolation forest model for training. Subsequently, anomaly scores are calculated and anomalous behavior is determined based on different threshold-setting strategies. Finally, the proposed algorithm is implemented using the Scikit-learn framework and evaluated in real logs regarding anomalous behavior recognition rate and model quality improvement. The experimental results show that the algorithm can detect abnormal behaviors in event logs and improve the model quality.
Assessing Service Quality and Customer Satisfaction of Electric Utility Provider’s Online Payment System during the COVID-19 Pandemic: A Structural Modeling Approach
Authors: Jou Yung-Tsan , Saflor Charmine Sheena , Mariñas Klint Allen , Young Michael Nayat , Prasetyo Yogi Tri , Persada Satria Fadil
Published: November 2022

The COVID-19 pandemic has rapidly changed people’s lives, especially technological advancements. Most service industries have opted to adopt online payments since the pandemic happened. Electric utility companies are one of the major industries that utilize online payments as an alternative mode of payment to traditional cash payments to minimize person-to-person contact. The current study aimed to assess electric utility companies’ service quality and customer satisfaction to improve the payment system. The study was conducted in Occidental Mindoro Electric Cooperative, Inc. (OMECO), which utilized an online payment system due to COVID-19-protocol. The research model comprises 60 questionnaires with ten sections developed from the literature and distributed to 400 participants. The data were analyzed using the structural equation modeling and path analysis technique. The results showed that Online Payment Security had the most positive effect on service quality, thus affecting customer satisfaction. Moreover, tangibility, reliability, online payment method, and COVID-19-protocol positively affected service quality. While reliability, assurance, and empathy had a negative effect on the service quality of OMECO. Aligning with the result, OMECO was poorly evaluated by the participants in terms of empathy, assurance, responsiveness, and reliability. Moreover, the result of the study can be used by major electric companies to improve their service in terms of online payment. Finally, the current research is one of the first studies that integrate service quality and customer satisfaction while utilizing the structural modeling approach.
Application of Simulated Annealing Algorithm in Core Flow Distribution Optimization
Authors: Wang Zixuan , Wang Yan , Xu Haipeng , Xie Heng
Published: November 2022

Core flow distribution is closely related to the thermal–hydraulic performance and safety of reactors. For natural circulation reactors with a limited driving force, flow distribution optimization is of particular significance, which can be contrived by suitably assigning the inlet resistance of a core assembly channel in reactor design. In the present work, core flow distribution optimization during the fuel life cycle is regarded as a global optimization problem. The optimization objective is to minimize the maximal outlet temperature difference of assembly channels during the fuel life cycle, while the input variable is the inlet resistance coefficient of each assembly channel. The simulated annealing algorithm is applied to the optimization code. The results show that the maximal outlet temperature difference is significantly reduced after optimization, and the resultant core outlet temperature distribution becomes more uniformed. Further evaluation indicates that the optimal solution has good applicability and stability under different reactor conditions. A comparison of the optimization objective function using different temperature difference definitions is also studied in the current study.
Stress and Displacement of Cylindrical Lithium-Ion Power Battery during Charging and Discharging
Authors: Chen Jingyi , Wang Genwei , Song Hui , Wang Bin , Wu Guiying , Lei Jianyin
Published: November 2022

During the charging and discharging process of a lithium-ion power battery, the intercalation and deintercalation of lithium-ion can cause volume change in the jellyroll and internal stress change in batteries as well, which may lead to battery failures and safety issues. A mathematical model based on a plane strain hypothesis was established to predict stresses in both the radial and hoop directions, with the hoop stress of each winding layer of the jellyroll obtained. Displacements of the steel case, the jellyroll, and the core of the battery during the charging and discharging processes were also analyzed, with the effect of lithium-ion concentration and the battery size discussed. The research results can explain well the wrinkling and fracture of the jellyroll.
Enviro-Economic Assessment of HHO–CNG Mixture Utilization in Spark Ignition Engine for Performance and Environmental Sustainability
Authors: Usman Muhammad , Malik Muhammad Ali Ijaz , Bashir Rehmat , Riaz Fahid , Raza Muhammad Juniad , Suleman Khubaib , Rehman Abd-ul , Ashraf Waqar Muhammad , Krzywanski Jaroslaw
Published: November 2022

Road transportation has received the attention of researchers due to its higher carbon footprint. Alternative fuels present major advantages in terms of environmental sustainability. For this reason, an enviro-economic analysis of alternative fuels carries great significance. However, scarce attempts have been rendered in order to ascertain the impact of a hydroxy gas (HHO) and compressed natural gas (CNG) mixture on sustainable environmental development. The current study addresses this issue by employing an HHO–CNG mixture and gasoline in spark ignition (SI) engines for the purposes of performance and environmental pollutants measurement. Then, engine emission data were substituted for Weibull distribution in order to establish suitability for 50 and 95% confidence intervals (CIs). The mixture outperformed gasoline in terms of brake-specific fuel consumption (BSFC) and emission contents. On average, hydroxy gas with CNG produced 10.59% lower oxides of nitrogen (NOX) comparative to gasoline. Finally, the enviro-economic analysis also turned out to be in favor of the hydroxy gas mixture owing to a saving of 36.14% in USD/year due to 27.87% lower production of carbon dioxide (CO2) emission.
An Application of the Hamilton–Ostrogradsky Principle to the Modeling of an Asymmetrically Loaded Three-Phase Power Line
Authors: Chaban Andriy , Lis Marek , Szafraniec Andrzej , Levoniuk Vitaliy
Published: November 2022

This paper presents a mathematical model of an electric power system which consists of a three-phase power line with distributed parameters and an equivalent, unbalanced RLC load cooperating with the line. The above model was developed on the basis of the modified Hamilton–Ostrogradsky principle, which extends the classical Lagrangian by adding two more components: the energy of dissipative forces in the system and the work of external non-conservative forces. In the developed model, there are four types of energy and four types of linear energy density. On the basis of Hamilton’s principle, the extended action functional was formulated and then minimized. As a result, the extremal of the action functional was derived, which can be treated as a solution of the Euler–Lagrange equation for the subsystem with lumped parameters and the Euler–Poisson equation for the subsystem with distributed parameters. The derived system of differential equations describes the entire physical system and consists of ordinary differential equations and partial differential equations. Such a system can be regarded as a full mathematical model of a dynamic object based on interdisciplinary approaches. The partial derivatives in the derived differential state–space equations of the analyzed object are approximated by means of finite differences, and then these equations are integrated in the time coordinate using the Runge–Kutta method of the fourth order. The results of computer simulation of transient processes in the dynamic system are presented as graphs and then discussed.
Morphological, Dielectric, and Impedance Study of Ag-Coated Lead Oxide–Lignocellulose Composite Sheets for Energy Storage and Tunable Electric Permittivity Applications
Authors: Raza Ali , Sultana Ishrat , Bashir Aneeqa , Hussain Shahzada Qamar , Ullah Zahid , Jafri S. Hassan M. , Haq Naveed-UL , Atiq Shahid , Kim Youngkuk , Cho Eun-Chel , Yi Junsin , Razaq Aamir
Published: November 2022

Functional materials, in the combination of lignocelluloses, known as natural fibers, with oxide materials, can result in cultivating functional properties such as flexibility, relativity good electrical conduction, good electrical charge storage capacity, and tunable electric permittivity. This study presents the morphological, dielectric, and impedance properties of lignocellulose–lead oxide (LC/PbO2) composite sheets electrodeposited with silver metallic nanoparticles for various time spans. The uncoated samples show a rather simple behavior where the impedance data fit well to the two-system model with different relaxation times. On the other side, the impedance spectra of the electrodeposited sample have varying features, which mainly depend upon the deposition thickness of the Ag particles. The common feature is the drift of conductive species, as seen from the straight-line behavior in the Nyquist plots, which were fitted using a Warburg element in the equivalent circuit model.
Three Phase Induction Motor Drive: A Systematic Review on Dynamic Modeling, Parameter Estimation, and Control Schemes
Authors: Sengamalai Usha , Anbazhagan Geetha , Thamizh Thentral T. M. , Vishnuram Pradeep , Khurshaid Tahir , Kamel Salah
Published: November 2022

An induction motor is generally used in industrial applications because it is reliable, robust, and low cost. Reliability is one of the essential parameters based on which the motor is selected, and the induction motor primarily comes into force. The well-founded induction motor gives good results under various operating states. To achieve this, the values of the motor are kept in mind. Dynamic simulation plays a significant part in evaluating the model’s design process to eliminate design errors in typical construction types and when testing the motor drive system. The induction motor is modeled in a synchronously revolving rotor flux-oriented frame, which is used as a reference. For sensorless vector control and induction motor control methods, accurate knowledge of a few induction motor parameters is necessary. The presentation of the drive will degrade if the original data in the motor do not match the values utilized in the controller. Various mechanisms have been developed to calculate the online and offline parameters of the induction machine for its application in high-performance drives. The foremost grail of this review paper is to present dynamic modeling and other considerable approaches used for estimating the induction motor parameter. This paper also constitutes some simulation examples related to dynamic modeling and parameter estimation techniques, which may be useful for specialists in the field of electric drive control systems.
Numerical Comparative Study of Fuel Cavitation in Microchannels under Different Turbulence Models
Authors: Li Ziming , Liu Zhenming , Chen Ping , Liu Jingbin , Wu Jiechang
Published: November 2022

The fuel injector is a critical component of the internal combustion engine. The diameters of the injector nozzle and the control chamber’s oil inlet and outlet are generally between 0.2 and 0.5 mm, which are typical microchannel structures. During high-pressure injection, the cavitation phenomenon in the channel seriously affects the reliability of the internal combustion engine. The choice of turbulence and cavitation models is the key to investigate the cavitation in the microchannel by using numerical methods. Based on the Winklhofer microchannel fuel experiment, five representative turbulence models were used to construct a microchannel model, and the results were compared and analyzed with the experiment. The results show that the pressure gradient values obtained from the combination of RNG k-ε and ZGB models were similar to the experimental data, with an error of less than 6%. The cavitation distribution calculated from the combination of LES and ZGB models was most consistent with the experimental observation data. The outlet mass flow rate obtained from the LES and ZGB models matched the trend of the experimental data in the pressure difference range of 19 bar to 85 bar, with an error of less than 2%. For the cross-sectional flow rate calculation, the RNG k-ε and ZGB models had the smallest calculation errors, with errors below 11%.
Applying Reservoir Simulation and Artificial Intelligence Algorithms to Optimize Fracture Characterization and CO2 Enhanced Oil Recovery in Unconventional Reservoirs: A Case Study in the Wolfcamp Formation
Authors: Wan Xincheng , Jin Lu , Azzolina Nicholas A. , Butler Shane K. , Yu Xue , Zhao Jin
Published: November 2022

Reservoir simulation for unconventional reservoirs requires proper history matching (HM) to quantify the uncertainties of fracture properties and proper modeling methods to address complex fracture geometry. An integrated method, namely embedded discrete fracture model–artificial intelligence–automatic HM (EDFM–AI–AHM), was used to automatically generate HM solutions for a multistage hydraulic fracturing well in the Wolfcamp Formation. Thirteen scenarios with different combinations of matrix and fracture parameters as variables or fixed inputs were designed to generate 1300 reservoir simulations via EDFM–AI–AHM, from which 358 HM solutions were retained to reproduce production history and quantify the uncertainties of matrix and hydraulic fracture properties. The best HM solution was used for production forecasting and carbon dioxide (CO2)-enhanced oil recovery (EOR) strategy optimization. The results of the production forecast for primary recovery indicated that the drainage area for oil production was difficult to extend further into the low-permeability reservoir matrix. However, CO2 EOR simulations showed that increasing the gas injection rate during the injection cycle promoted incremental oil production from the reservoir matrix, regardless of minimum miscibility pressure. A gas injection rate of 25 million standard cubic feet per day (MMscfd) resulted in a 14% incremental oil production improvement compared to the baseline scenario with no EOR. This paper demonstrates the utility of coupling reservoir simulation with artificial intelligence algorithms to generate ensembles of simulation cases that provide insights into the relationships between fracture network properties and production.