bluuebunny/crossref_metadata_2025 huggingface dataset:
Prophylactic Architecture: Formulating the Concept of Pandemic-Resilient Homes
Authors: Elrayies Ghada Mohammad
Published: July 2022

The lockdown instituted during the COVID-19 pandemic has drawn the world’s attention to the importance of homes as integrated structures for practicing all aspects of life. The home has been transformed from a mere place to live into a complete piece of infrastructure accommodating all activities of life, including study, work, shopping, exercise, entertainment, and even telehealth. Although quarantines were necessary to protect against viral infection, we have faced social and psychological challenges due to the failure of the current home design to accommodate the new lockdown lifestyle during the pandemic. Thus, this study aims to set a foundation for the development and design of resilient homes in a post-quarantine world by establishing a comprehensive framework for quarantine-resilient homes. The framework was established on the basis of the relevant literature and proposals from architects and experts. It brings a perspective to the future requirements of homes so as to provide architects, stakeholders, and policymakers with the appropriate knowledge to mitigate the impact of lockdowns on mental health and well-being in residential buildings by focusing on the physical and architectural environment.
Is Robotic Assisted Colorectal Cancer Surgery Equivalent Compared to Laparoscopic Procedures during the Introduction of a Robotic Program? A Propensity-Score Matched Analysis
Authors: Tschann Peter , Weigl Markus P. , Lechner Daniel , Mittelberger Christa , Jäger Tarkan , Gruber Ricarda , Girotti Paolo N. C. , Mittermair Christof , Clemens Patrick , Attenberger Christian , Szeverinski Philipp , Brock Thomas , Frick Jürgen , Emmanuel Klaus , Königsrainer Ingmar , Presl Jaroslav
Published: July 2022

Background: Robotic surgery represents a novel approach for the treatment of colorectal cancers and has been established as an important and effective method over the last years. The aim of this work was to evaluate the effect of a robotic program on oncological findings compared to conventional laparoscopic surgery within the first three years after the introduction. Methods: All colorectal cancer patients from two centers that either received robotic-assisted or conventional laparoscopic surgery were included in a comparative study. A propensity-score-matched analysis was used to reduce confounding differences. Results: A laparoscopic resection (LR Group) was performed in 82 cases, and 93 patients were treated robotic-assisted surgery (RR Group). Patients’ characteristics did not differ between groups. In right-sided resections, an intracorporeal anastomosis was significantly more often performed in the RR Group (LR Group: 5 (26.31%) vs. RR Group: 10 (76.92%), p = 0.008). Operative time was shown to be significantly shorter in the LR Group (LR Group: 200 min (150–243) vs. 204 min (174–278), p = 0.045). Conversions to open surgery did occur more often in the LR Group (LR Group: 16 (19.51%) vs. RR Group: 5 (5.38%), p = 0.004). Postoperative morbidity, the number of harvested lymph nodes, quality of resection and postoperative tumor stage did not differ between groups. Conclusion: In this study, we could clearly demonstrate robotic-assisted colorectal cancer surgery as effective, feasible and safe regarding postoperative morbidity and oncological findings compared to conventional laparoscopy during the introduction of a robotic system.
Novel Approaches in Molecular Characterization of Classical Hodgkin Lymphoma
Authors: van Bladel Diede A. G. , Stevens Wendy B. C. , van den Brand Michiel , Kroeze Leonie I. , Groenen Patricia J. T. A. , van Krieken J. Han J. M. , Hebeda Konnie M. , Scheijen Blanca
Published: July 2022

Classical Hodgkin lymphoma (cHL) represents a B-cell lymphoproliferative disease characterized by clonal immunoglobulin gene rearrangements and recurrent genomic aberrations in the Hodgkin Reed–Sternberg cells in a reactive inflammatory background. Several methods are available for the molecular analysis of cHL on both tissue and cell-free DNA isolated from blood, which can provide detailed information regarding the clonal composition and genetic alterations that drive lymphoma pathogenesis. Clonality testing involving the detection of immunoglobulin and T cell receptor gene rearrangements, together with mutation analysis, represent valuable tools for cHL diagnostics, especially for patients with an atypical histological or clinical presentation reminiscent of a reactive lesion or another lymphoma subtype. In addition, clonality assessment may establish the clonal relationship of composite or subsequent lymphoma presentations within one patient. During the last few decades, more insight has been obtained on the molecular mechanisms that drive cHL development, including recurrently affected signaling pathways (e.g., NF-κB and JAK/STAT) and immune evasion. We provide an overview of the different approaches to characterize the molecular composition of cHL, and the implementation of these next-generation sequencing-based techniques in research and diagnostic settings.
Exploring Cost-Effectiveness of the Comprehensive Geriatric Assessment in Geriatric Oncology: A Narrative Review
Authors: Zuccarino Sara , Monacelli Fiammetta , Antognoli Rachele , Nencioni Alessio , Monzani Fabio , Ferrè Francesca , Seghieri Chiara , Antonelli Incalzi Raffaele
Published: July 2022

The Comprehensive Geriatric Assessment (CGA) and the corresponding geriatric interventions are beneficial for community-dwelling older persons in terms of reduced mortality, disability, institutionalisation and healthcare utilisation. However, the value of CGA in the management of older cancer patients both in terms of clinical outcomes and in cost-effectiveness remains to be fully established, and CGA is still far from being routinely implemented in geriatric oncology. This narrative review aims to analyse the available evidence on the cost-effectiveness of CGA adopted in geriatric oncology, identify the relevant parameters used in the literature and provide recommendations for future research. The review was conducted using the PubMed and Cochrane databases, covering published studies without selection by the publication year. The extracted data were categorised according to the study design, participants and measures of cost-effectiveness, and the results are summarised to state the levels of evidence. The review conforms to the SANRA guidelines for quality assessment. Twenty-nine studies out of the thirty-seven assessed for eligibility met the inclusion criteria. Although there is a large heterogeneity, the overall evidence is consistent with the measurable benefits of CGA in terms of reducing the in-hospital length of stay and treatment toxicity, leaning toward a positive cost-effectiveness of the interventions and supporting CGA implementation in geriatric oncology clinical practice. More research employing full economic evaluations is needed to confirm this evidence and should focus on CGA implications both from patient-centred and healthcare system perspectives.
Screening a Targeted Panel of Genes by Next-Generation Sequencing Improves Risk Stratification in Real World Patients with Acute Myeloid Leukemia
Authors: Matos Sónia , Bernardo Paulo , Esteves Susana , Botelho de Sousa Aida , Lemos Marcos , Ribeiro Patrícia , Silva Madalena , Nunes Albertina , Lobato Joana , Frade Maria de Jesus , da Silva Maria Gomes , Chacim Sérgio , Mariz José , Esteves Graça , Raposo João , Espadana Ana , Carda José , Barbosa Pedro , Martins Vânia , Carmo-Fonseca Maria , Desterro Joana
Published: July 2022

Although mutation profiling of defined genes is recommended for classification of acute myeloid leukemia (AML) patients, screening of targeted gene panels using next-generation sequencing (NGS) is not always routinely used as standard of care. The objective of this study was to prospectively assess whether extended molecular monitoring using NGS adds clinical value for risk assessment in real-world AML patients. We analyzed a cohort of 268 newly diagnosed AML patients. We compared the prognostic stratification of our study population according to the European LeukemiaNet recommendations, before and after the incorporation of the extended mutational profile information obtained by NGS. Without access to NGS data, 63 patients (23%) failed to be stratified into risk groups. After NGS data, only 27 patients (10%) failed risk stratification. Another 33 patients were re-classified as adverse-risk patients once the NGS data was incorporated. In total, access to NGS data refined risk assessment for 62 patients (23%). We further compared clinical outcomes with prognostic stratification, and observed unexpected outcomes associated with FLT3 mutations. In conclusion, this study demonstrates the prognostic utility of screening AML patients for multiple gene mutations by NGS and underscores the need for further studies to refine the current risk classification criteria.
Nepenthes mirabilis Fractionated Pitcher Fluid Use for Mixed Agro-Waste Pretreatment: Advocacy for Non-Chemical Use in Biorefineries
Authors: Angadam Justine O. , Njoya Mahomet , Ntwampe Seteno K. O. , Chidi Boredi S. , Lim Jun-Wei , Okudoh Vincent I. , Hewitt Peter L.
Published: July 2022

This study determined whether it is feasible to pretreat mixed agro-waste of different particle sizes using the pitcher fluid of Nepenthes mirabilis (N. mirabilis), which is known to digest leaf litter due to the enzyme cocktail contained in the fluid. This is due to the need for the holocellulolysis (a source of fermentable sugars) of mixed agro-waste to produce fermentable hydrolysates. The pitcher fluid was fractionated (<3 kDa, >3 kDa, <10 kDa, >10 kDa) and slurrified with the mixed agro-waste, i.e., 25% (w/w) for each waste—orange peels, apple peels, maize cobs, grape pomace, and oak plant leaf litter of various particle sizes, i.e., >75 µm x < 106 µm and >106 µm. The process of producing a high concentration of total reducible sugars (TRSs) with the lowest production of total phenolic compounds (TPCs) was determined to be a particle size of >106 µm, pretreatment for 72 h, and an enzyme fraction of <10 kDa, whereby 97 g/L of TRSs were produced with a significantly lower TPCs load (1 g/L). Furthermore, the <10 kDa showed preferable physico-chemical properties, with the highest reduction-oxidation potential including acidity. Several enzymes, i.e., β-1,3-Glucanase, Putative peroxidase 27, Thaumatin-like protein, among others, were identified in the <10 kDa fraction, i.e., enzymes known to perform various functions in plant-based waste. Therefore, there is a need for the renewable energy industry to consider solely using pitcher fluids to pretreat mixed agro-waste for fermentable hydrolysates’ production, which can be used as liquid feedstock for the bioenergy and/or biorefinery industries for environmental pollution reduction.
Universal or Personalized Mesenchymal Stem Cell Therapies: Impact of Age, Sex, and Biological Source
Authors: Carp Diana M. , Liang Yun
Published: July 2022

Mesenchymal stem/stromal cells (MSCs) hold great promise for the treatment of autoimmune conditions given their immunomodulatory properties. Based on the low immunogenicity of MSCs, it is tempting to consider the expansion of MSCs from a “universal donor” in culture prior to their allogeneic applications for immediate care. This raises the critical question of the criteria we should use to select the best “universal donor”. It is also imperative we compare the “universal” approach with a “personalized” one for clinical value. In addition to the call for MHC-matching, recent studies suggest that factors including age, sex, and biological sources of MSCs can have significant impact on therapy outcome. Here, we will review findings from these studies, which shed light on the variables that can guide the important choice of “universal” or “personalized” MSC therapy for autoimmune diseases.
3D Spheroid Human Dermal Papilla Cell as an Effective Model for the Screening of Hair Growth Promoting Compounds: Examples of Minoxidil and 3,4,5-Tri-O-caffeoylquinic acid (TCQA)
Authors: Bejaoui Meriem , Oliva Aprill Kee , Ke May Sin , Ferdousi Farhana , Isoda Hiroko
Published: July 2022

Dermal papilla cells (DPCs) are an important element of the hair follicle (HF) niche, widely used as an in vitro model to study hair growth-related research. These cells are usually grown in 2D culture, but this system did not show efficient therapeutic effects on HF regeneration and growth, and key differences were observed between cell activity in vitro and in vivo. Recent studies have showed that DPCs grown in 3D hanging spheroids are more morphologically akin to an intact DP microenvironment. In this current study, global gene molecular analysis showed that the 3D model highly affected cell adhesion molecules and hair growth-related pathways. Furthermore, we compared the expression of signalling molecules and metabolism-associated proteins of DPCs treated with minoxidil (an FDA-approved drug for hair loss treatment) and 3,4,5-tri-O-caffeoylquinic acid (TCQA) (recently found to induce hair growth in vitro and in vivo) in 3D spheroid hanging drops and a 2D monolayer using DNA microarray analysis. Further validations by determining the gene and protein expressions of key signature molecules showed the suitability of this 3D system for enhancing the DPC activity of the hair growth-promoting agents minoxidil and TCQA.
Restenosis after Coronary Stent Implantation: Cellular Mechanisms and Potential of Endothelial Progenitor Cells (A Short Guide for the Interventional Cardiologist)
Authors: Gori Tommaso
Published: July 2022

Coronary stents are among the most common therapies worldwide. Despite significant improvements in the biocompatibility of these devices throughout the last decades, they are prone, in as many as 10–20% of cases, to short- or long-term failure. In-stent restenosis is a multifactorial process with a complex and incompletely understood pathophysiology in which inflammatory reactions are of central importance. This review provides a short overview for the clinician on the cellular types responsible for restenosis with a focus on the role of endothelial progenitor cells. The mechanisms of restenosis are described, along with the cell-based attempts made to prevent it. While the focus of this review is principally clinical, experimental evidence provides some insight into the potential implications for prevention and therapy of coronary stent restenosis.
Mechanical Properties of Arc Coatings Sprayed with Cored Wires with Different Charge Compositions
Authors: Student Mykhailo , Hvozdetskyi Volodymyr , Stupnytskyi Taras , Student Oleksandra , Maruschak Pavlo , Prentkovskis Olegas , Skačkauskas Paulius
Published: July 2022

The mechanical properties (hardness, cohesion, and residual stresses) of arc coatings designed for operation under conditions of boundary friction and corrosive-abrasive wear are analyzed. The coatings were formed by arc spraying cored wires (CW) with different charge compositions (the content of carbon, aluminum, and boron in CW charge varied). It is shown that the hardness of the coatings increases with an increase in the carbon content in them up to 1 wt. %, and then decreased due to an increase in the content of residual austenite in their structure. The level of residual stresses of the first kind in such coatings increased by four times with an increase in the carbon content to 2 wt. %. The hardness of the coatings and the level of residual tensile stresses in them also increase with a decrease in the aluminum content in them. In this case, the cohesive strength of the coatings increased due to the implementation of aluminothermic reactions in the droplets of the CW melt during their flight and crystallization on the sprayed surfaces. However, then, with an increase in the aluminum content in the coatings of more than 2 wt. %, their cohesive strength decreased. The level of residual tensile stresses in coatings with a high content of retained austenite decreased after heat treatment (tempering) of the specimens. Sometimes, after tempering, these stresses even transformed into residual compressive stresses (in particular, under using CW C1.4Cr14Ni2). At the same time, the tempering of specimens with a predominance of ferrite in the coating structure increased the level of residual tensile stresses in them, which is due to the precipitation of finely dispersed carbides or borides. It has been shown that the addition of boron-containing components (ferrochromium-boron, chromium-boron) to the composition of the CW charge leads to a significant increase in the hardness of the coatings. Thus, an increase in the boron content in coatings from 0 to 4 wt. % leads to an increase in their hardness from 320 HV to 1060 HV. However, this is accompanied by an increase in tensile residual stresses in the coatings and a decrease in their cohesive strength.
Low Fluorinated Oligoamides for Use as Wood Protective Coating
Authors: Zhang Yuqing , Vespignani Laura , Balzano Maria Grazia , Bellandi Leonardo , Camaiti Mara , Lubin-Germain Nadège , Salvini Antonella
Published: July 2022

New highly hydrophobic fluorinated oligoamides were synthesized and studied as materials for the protection of non-varnishable wooden artifacts. The new oligoamides were designed to achieve the best performance (including high chemical affinity to the wood material) and the lowest environmental impact. In order to minimize the risk of bioaccumulation, short perfluoroalkyl side chains were reacted with oligoethylene L-tartaramide (ET), oligoethylene adipamide-L-tartaramide (ETA), oligoethylene succinamide-L-tartaramide (EST), oligoethylene succinamide (ES), and oligodiethylenetriamino-L-tartaramide (DT). Favorable reaction conditions were also adopted to obtain low molecular weight compounds characterized by non-film-forming properties and solubility or dispersibility in environmentally friendly organic solvents. Their behavior in terms of modification of the wood surface characteristics, such as wettability, moisture absorption, and color, was analyzed using a specific diagnostic protocol to rapidly obtain preliminary, but reliable, results for optimizing a future synthesis of new and tailored protectives. The influence of different monomer units on the reactivity, solubility, and hydrophobic properties of different oligoamides was compared showing ESF (contact angle 138.2°) and DF (132.2°) as the most effective products. The study of stability to photochemical degradation confirms ESF as promising protective agents for artefacts of historical and artistic interest in place of long-chain perfluoroalkyl substances (PFAS), products currently subject to restrictions on use.
The Characterization of Running-In Coatings on the Surface of Tin Bronze by Electro-Spark Deposition
Authors: Zhang Zhengchuan , Konoplianchenko Ievgen , Tarelnyk Viacheslav , Liu Guanjun , Du Xin , Yu Hua
Published: July 2022

Antifriction materials, such as silver, copper, Babbitt B83, and graphene oxide (GO), were used to prepare running-in coatings on the surface of bronze QSn10-1 by electro-spark deposition (ESD). The analyses of mass transfer, roughness, thickness, morphology, composition, nanoindentation, and tribological properties of the coatings were investigated. The results showed that the running-in coatings were dense with refined grains that were uniformly distributed and in a metallurgical bond state with the tin bronze substrate. At optimum process parameters, the mass transfer was 244.2 mg, the surface roughness was 15.9 μm, and the thickness of the layers was 160 μm. The diffraction peaks clearly indicated the phases corresponding to α-Sn, SbSn, Cu6Sn5, and Cu, and a phase of Ag3Sn appeared. The modulus and the hardness of the running-in coatings were 24.9% and 14.2% of the substrate, and the deformation ratio of the coatings was 10.2% higher than that of the substrate. The friction coefficient of the running-in coatings was about 0.210 after the running-in stage, which was 64.8% of that of the substrate (0.324). The main wear mechanism of the running-in coatings under optimal process parameters is plastic deformation, scratching, and slight polishing. The running-in coating deformation under the action of high specific loads provides the automatic adjustment of parts and compensation for manufacturing errors.
DMLAR: Distributed Machine Learning-Based Anti-Collision Algorithm for RFID Readers in the Internet of Things
Authors: Mafamane Rachid , Ouadou Mourad , Sahbani Hajar , Ibadah Nisrine , Minaoui Khalid
Published: July 2022

Radio Frequency Identification (RFID) is considered as one of the most widely used wireless identification technologies in the Internet of Things. Many application areas require a dense RFID network for efficient deployment and coverage, which causes interference between RFID tags and readers, and reduces the performance of the RFID system. Therefore, communication resource management is required to avoid such problems. In this paper, we propose an anti-collision protocol based on feed-forward Artificial Neural Network methodology for distributed learning between RFID readers to predict collisions and ensure efficient resource allocation (DMLAR) by considering the mobility of tags and readers. The evaluation of our anti-collision protocol is performed for different mobility scenarios in healthcare where the collected data are critical and must respect the terms of throughput, delay, overload, integrity and energy. The dataset created and distributed by the readers allows an efficient learning process and, therefore, a high collision detection to increase throughput and minimize data loss. In the application phase, the readers do not need to exchange control packets with each other to control the resource allocation, which avoids network overload and communication delay. Simulation results show the robustness and effectiveness of the anti-collision protocol by the number of readers and resources used. The model used allows a large number of readers to use the most suitable frequency and time resources for simultaneous and successful tag interrogation.
Enhancement of Light Extraction Efficiency of UVC-LED by SiO2 Antireflective Film
Authors: Wang Yu , Lv Zhenxing , Qi Shengli , Liu Yazhu , Long Hao
Published: July 2022

In order to achieve high quantum efficiency of AlGaN-based deep ultraviolet light-emitting diodes (UVC-LED), it is important to improve the light extraction efficiency (LEE). In this paper, theoretical simulation and experiment of SiO2 anti-reflective film deposited on UVC-LED were investigated. The effect of different SiO2 thickness on the light extraction efficiency of 275 nm UVC-LED was studied, showing that 140 nm SiO2 anti-reflective film can effectively improve the light output power of UVC-LED by more than 5.5%, which were also confirmed by the TFCALC simulation. The enhancement of UVC-LED light extraction efficiency by this antireflective film is mainly due to the 3λ2 light coherent effect at the SiO2/Al2O3 interface. Our work proved the promising application of antireflective coating on UVC-LED.
Numerical Modeling and Simulations of Twinning-Induced Plasticity Using Crystal Plasticity Finite Element Method
Authors: Khan Rashid , Pervez Tasneem , Alfozan Adel , Qamar Sayyad Zahid , Mohsin Sumiya
Published: July 2022

In the current work, a fully implicit numerical integration scheme is developed for modeling twinning-induced plasticity using a crystal plasticity framework. Firstly, the constitutive formulation of a twin-based micromechanical model is presented to estimate the deformation behavior of steels with low stacking fault energy. Secondly, a numerical integration scheme is developed for discretizing constitutive equations through a fully implicit time integration scheme using the backward Euler method. A time sub-stepping algorithm and the two-norm convergence criterion are used to regulate time step size and stopping criterion. Afterward, a numerical scheme is implemented in finite element software ABAQUS as a user-defined material subroutine. Finally, finite element simulations are executed for observing the validity, performance, and limitations of the numerical scheme. It is observed that the simulation results are in good agreement with the experimental observations with a maximum error of 16% in the case of equivalent stress and strain. It is also found that the developed model is able to estimate well the deformation behavior, magnitude of slip and twin shear strains, and twin volume fraction of three different TWIP steels where the material point is subjected to tension and compression.
Gynecologic Cancer Risk and Genetics: Informing an Ideal Model of Gynecologic Cancer Prevention
Authors: Tindale Lauren C. , Zhantuyakova Almira , Lam Stephanie , Woo Michelle , Kwon Janice S. , Hanley Gillian E. , Knoppers Bartha , Schrader Kasmintan A. , Peacock Stuart J. , Talhouk Aline , Dummer Trevor , Metcalfe Kelly , Pashayan Nora , Foulkes William D. , Manchanda Ranjit , Huntsman David , Stuart Gavin , Simard Jacques , Dawson Lesa
Published: July 2022

Individuals with proven hereditary cancer syndrome (HCS) such as BRCA1 and BRCA2 have elevated rates of ovarian, breast, and other cancers. If these high-risk people can be identified before a cancer is diagnosed, risk-reducing interventions are highly effective and can be lifesaving. Despite this evidence, the vast majority of Canadians with HCS are unaware of their risk. In response to this unmet opportunity for prevention, the British Columbia Gynecologic Cancer Initiative convened a research summit “Gynecologic Cancer Prevention: Thinking Big, Thinking Differently” in Vancouver, Canada on 26 November 2021. The aim of the conference was to explore how hereditary cancer prevention via population-based genetic testing could decrease morbidity and mortality from gynecologic cancer. The summit invited local, national, and international experts to (1) discuss how genetic testing could be more broadly implemented in a Canadian system, (2) identify key research priorities in this topic and (3) outline the core essential elements required for such a program to be successful. This report summarizes the findings from this research summit, describes the current state of hereditary genetic programs in Canada, and outlines incremental steps that can be taken to improve prevention for high-risk Canadians now while developing an organized population-based hereditary cancer strategy.
The Effectiveness of Spinal, Diaphragmatic, and Specific Stabilization Exercise Manual Therapy and Respiratory-Related Interventions in Patients with Chronic Nonspecific Neck Pain: Systematic Review and Meta-Analysis
Authors: Tatsios Petros I. , Grammatopoulou Eirini , Dimitriadis Zacharias , Papandreou Maria , Paraskevopoulos Eleftherios , Spanos Savvas , Karakasidou Palina , Koumantakis George A.
Published: July 2022

Patients with nonspecific chronic neck pain (NSCNP) exhibit respiratory dysfunction. This systematic review aimed to analyze randomized controlled trials (RCTs) investigating the effect of spinal and/or diaphragmatic and/or specific stabilization exercise manual therapy and/or respiratory exercises on musculoskeletal and respiratory diagnostic outcomes in patients with NSCNP. A systematic search and selection of RCTs was performed in three scientific databases (Pubmed, Scopus, and Physiotherapy Evidence Database (PEDro)) and one search engine (Google Scholar) from inception to April 2022. Relevant studies published in the English language were extracted, evaluated, and independently rated for methodological quality (PEDro scale). The quality of the evidence was assessed with the GRADE approach. Out of 1089 studies collected in total, 1073 were excluded (i.e., did not meet the inclusion criteria or were duplicates). Sixteen RCTs were finally included, rated on 5.62/10 (PEDro score) on average for methodological quality. Overall, there was sparse evidence that spinal and/or diaphragmatic manual therapy and/or trunk stabilization exercises and/or respiratory exercises significantly improved pain, disability, and respiratory outcomes in patients with NSCNP immediately post-treatment. However, the clinical heterogeneity between studies was significant, and the level of certainty of the evidence was low to very low. More, high-quality RCTs are required, contributing to the holistic diagnostic monitoring and management of patients with NSCNP.
Is Initial Performance in a Course Informative? Machine Learning Algorithms as Aids for the Early Detection of At-Risk Students
Authors: Pilotti Maura A. E. , Nazeeruddin Emaan , Nazeeruddin Mohammad , Daqqa Ibtisam , Abdelsalam Hanadi , Abdullah Maryam
Published: July 2022

The extent to which grades in the first few weeks of a course can predict overall performance can be quite valuable in identifying at-risk students, informing interventions for such students, and offering valuable feedback to educators on the impact of instruction on learning. Yet, research on the validity of such predictions that are made by machine learning algorithms is scarce at best. The present research examined two interrelated questions: To what extent can educators rely on early performance to predict students’ poor course grades at the end of the semester? Are predictions sensitive to the mode of instruction adopted (online versus face-to-face) and the course taught by the educator? In our research, we selected a sample of courses that were representative of the general education curriculum to ensure the inclusion of students from a variety of academic majors. The grades on the first test and assignment (early formative assessment measures) were used to identify students whose course performance at the end of the semester would be considered poor. Overall, the predictive validity of the early assessment measures was found to be meager, particularly so for online courses. However, exceptions were uncovered, each reflecting a particular combination of instructional mode and course. These findings suggest that changes to some of the currently used formative assessment measures are warranted to enhance their sensitivity to course demands and thus their usefulness to both students and instructors as feedback tools. The feasibility of a grade prediction application in general education courses, which critically depends on the accuracy of such tools, is discussed, including the challenges and potential benefits.
A Link Prediction Algorithm Based on GAN
Authors: Jin Haiyan , Xu Guodong , Cheng Kangda , Liu Jinlong , Wu Zhilu
Published: July 2022

Link prediction, as an important research direction in complicated network analysis, has broad application prospects. However, traditional link prediction algorithms are generally designed by the sparse expression of the adjacency matrix, which is computationally expensive and inefficient, being also unable to run on large-scale networks and to preserve their higher order structural features. To fill this gap, we propose a GAN (generative adversarial network)-based link prediction algorithm. The algorithm layers the network graph, preserving the local features and higher-level structural features of the original network graph, and uses a generative adversarial model to recursively and backwardly obtain the low-dimensional vector form of the vertices in each layer of the network graph as the initialization of the network graph in the previous layer. It then obtains the low-dimensional vector form of all the vertices in the original network graph for link prediction, and the problem of local minima that can be generated by random initialization is solved. The experimental results show that our method is superior to many state-of-the-art algorithms.
A Proposed Priority Pushing and Grasping Strategy Based on an Improved Actor-Critic Algorithm
Authors: You Tianya , Wu Hao , Xu Xiangrong , Petrovic Petar B. , Rodić Aleksandar
Published: July 2022

The most basic and primary skills of a robot are pushing and grasping. In cluttered scenes, push to make room for arms and fingers to grasp objects. We propose a modified Actor-Critic (A-C) framework for deep reinforcement learning, Cross-entropy Softmax A-C (CSAC), and use the Prioritized Experience Replay (PER) based on the theoretical foundation and main methods of deep reinforcement learning, combining the advantages of algorithms based on value functions and policy gradients. The grasping model is trained using self-supervised learning to achieve end-to-end mapping from image to propulsion and grasping action. A vision module and an action module have been created out of the entire algorithm framework. The prioritized experience replay is improved to further improve the CSAC-PER algorithm for model sample diversity and robot exploration performance during robot grasping training. The experience replay buffer is dynamically sampled using the prior beta distribution and the dynamic sampling algorithm based on the beta distribution (CSAC-β) is proposed based on the CSAC algorithm. Despite its low initial efficiency, the experimental simulation results show that the CSAC-β algorithm eventually achieves good results and has a higher grasping success rate (90%).
Scientometric Analysis and Classification of Research Using Convolutional Neural Networks: A Case Study in Data Science and Analytics
Authors: Daradkeh Mohammad , Abualigah Laith , Atalla Shadi , Mansoor Wathiq
Published: July 2022

With the increasing development of published literature, classification methods based on bibliometric information and traditional machine learning approaches encounter performance challenges related to overly coarse classifications and low accuracy. This study presents a deep learning approach for scientometric analysis and classification of scientific literature based on convolutional neural networks (CNN). Three dimensions, namely publication features, author features, and content features, were divided into explicit and implicit features to form a set of scientometric terms through explicit feature extraction and implicit feature mapping. The weighted scientometric term vectors are fitted into a CNN model to achieve dual-label classification of literature based on research content and methods. The effectiveness of the proposed model is demonstrated using an application example from the data science and analytics literature. The empirical results show that the scientometric classification model proposed in this study performs better than comparable machine learning classification methods in terms of precision, recognition, and F1-score. It also exhibits higher accuracy than deep learning classification based solely on explicit and dominant features. This study provides a methodological guide for fine-grained classification of scientific literature and a thorough investigation of its practice.
On the Need for Collaborative Intelligence in Cybersecurity
Authors: Martin Trevor
Published: July 2022

The success of artificial intelligence (and particularly data-driven machine learning) in classifying and making predictions from large bodies of data has led to an expectation that autonomous AI systems can be deployed in cybersecurity applications. In this position paper we outline some of the problems facing machine learning in cybersecurity and argue for a collaborative approach where humans contribute insight and understanding, whilst machines are used to gather, filter and process data into a convenient and understandable form. In turn this requires a convenient representation for exchanging information between machine and human, and we argue that graded concepts are suitable, allowing summarisation at multiple levels of discernibility (granularity). We conclude with some suggestions for developing a hierarchical and graded representation.
ZnO Nanorods as Antireflection Layers in Metal-Insulator-Semiconductor Solar Cells
Authors: Chang Chung-Cheng , Huang Chia-Hong
Published: July 2022

One of the most promising techniques for manufacturing low-cost solar cells is a solution processing method. In this study, it is proposed that solution-grown ZnO nanorods (NRs) are used as antireflection coatings on metal-insulator-semiconductor (MIS) solar cells with sol-gel SiO2. Except Al electrodes prepared by thermal evaporation, no other vacuum process was utilized during fabrication. The ZnO NRs were produced with a hydrothermal method and suppressed Fresnel reflection. With the solution-grown ZnO NRs, it was observed the average reflectance of the MIS solar cell decreased from 38.7% to 15.8%, and the short circuit density (JSC) increased from 5.22 mA/cm2 to 6.71 mA/cm2 (28.4% enhancement). Meanwhile, the open circuit voltage (VOC) was improved from 0.39 V to 0.47 V owing to a passivation effect. The MIS solar cell with the ZnO NRs exhibited a 35.5% efficiency enhancement compared to that without ZnO NRs. The performance improvement in MIS solar cells with ZnO NRs could be due to multiple reflections of an incident light between the vertically arranged NRs, and then light coupling into the cell. The results show a potential application of ZnO NRs for the performance enhancement of MIS solar cells.
A Preliminary Study of the Characteristics of Radon Data from Indoor Environments and Building Materials in the Campania Region Using PCA and K-Means Statistical Analyses
Authors: Sabbarese Carlo , Feola Maria Luisa , Ambrosino Fabrizio , Roca Vincenzo , D’Onofrio Antonio , La Verde Giuseppe , D’Avino Vittoria , Pugliese Mariagabriella , Festa Vittorio
Published: July 2022

For a healthy indoor environment, it is important to understand which materials and factors favor the generation of high levels of indoor radon. A preliminary multivariate statistical analysis was carried out on two datasets concerning indoor radon and building materials in the Campania Region using Principal Component Analysis (PCA) and the k-means partitional analysis technique. A total of 13 parameters related to building materials were used. The results show the greater contribution of building materials of volcanic origin to the concentration of indoor radon and thoron activity and the different influence of the parameters of the 31 materials analyzed. The same analyses applied to the indoor radon values of 694 rooms in the Campania Region were equally effective in assessing the structural characteristics of indoor environments that most influence indoor radon levels. The study provided an effective assessment of the influence on radon activity of several environmental parameters, which are often not adequately considered.
Influence of Ultrasound Application in Fermented Pineapple Peel on Total Phenolic Content and Antioxidant Activity
Authors: Polanía Anna María , Londoño Liliana , Ramírez Cristina , Bolívar German
Published: July 2022

Antioxidant phenolic compounds were extracted from fermented samples of Golden pineapple peels via an ultrasound method. The fermentation conditions to maximize the production of phenolic content and antioxidant activity were previously determined (pH: 5.5, T: 37.3 °C and 85% moisture content). A central composite design with 20 treatments was applied to evaluate the effect of the ethanol concentration, time, and temperature on the production of phenolic compounds and antioxidant activity of the extracts. The statistical analysis showed that the optimal conditions to produce extracts with high phenolic content and antioxidant activity were: 62 °C, 30 min and 58% ethanol. We obtained 866.26 mg gallic acid equivalents (GAE)/g d.m in total phenolic content and for antioxidant activity expressed as percentage inhibition, 80.06 ± 1.02% for ABTS and 63.53 ± 2.02% for DPPH, respectively. The bioactive compound profile in the extracts was identified and quantified using ultra-high performance liquid chromatography (UHPLC), this method showed the presence of rosmarinic acid, caffeic acid, vanillic acid, p-coumaric acid, ferulic acid, quercetin-3 glucoside, rutine, quercetin, kaempherol-3 glucoside and gallic acid, demonstrating the great potential of these by-products to obtain components that can benefit the consumer’s health.
Misuse Patterns from the Threat of Modification of Non-Control Data in Network Function Virtualization
Authors: Alnaim Abdulrahman
Published: July 2022

Network Function Virtualization (NFV) is a virtual network model, the goal of which is a cost-efficient transition of the hardware infrastructure into a flexible and reliable software platform. However, this transition comes at the cost of more security threats. A key part of this virtualization environment is the hypervisor, which emulates the hardware resources to provide a runtime environment for virtual machines (VMs). The hypervisor is considered a major attack vector and must be secured to ensure network service continuity. The virtualization environment contains critical non-control data where compromise could lead to several misuses, including information leakage and privilege and resource modification. In this paper, we present a misuse pattern for an attack that exploits the security vulnerabilities of the hypervisor to compromise the integrity of non-control data in the NFV environment. Misuse patterns are used to describe how attacks are carried out from the attackers’ perspective. The threat of modification of non-control data can lead to several misuses, and in this paper, we discuss three of them. The defenses to this attack can be incorporated into the Security Reference Architecture (SRA) of the NFV system to prevent these misuses.
Aesthetic Trends and Semantic Web Adoption of Media Outlets Identified through Automated Archival Data Extraction
Authors: Lamprogeorgos Aristeidis , Pergantis Minas , Panagopoulos Michail , Giannakoulopoulos Andreas
Published: July 2022

The last decade has been a time of great progress in the World Wide Web and this progress has manifested in multiple ways, including both the diffusion and expansion of Semantic Web technologies and the advancement of the aesthetics and usability of Web user interfaces. Online media outlets have often been popular Web destinations and so they are expected to be at the forefront of innovation, both in terms of the integration of new technologies and in terms of the evolution of their interfaces. In this study, various Web data extraction techniques were employed to collect current and archival data from news websites that are popular in Greece, in order to monitor and record their progress through time. This collected information, which took the form of a website’s source code and an impression of their homepage in different time instances of the last decade, has been used to identify trends concerning Semantic Web integration, DOM structure complexity, number of graphics, color usage, and more. The identified trends were analyzed and discussed with the purpose of gaining a better understanding of the ever-changing presence of the media industry on the Web. The study concluded that the introduction of Semantic Web technologies in online media outlets was rapid and extensive and that website structural and visual complexity presented a steady and significant positive trend, accompanied by increased adherence to color harmony.
Synthesis and Characterization of Chitosan-Decorated Nanoemulsion Gel of 5-Fluorouracil for Topical Delivery
Authors: Nawaz Asif , Latif Muhammad Shahid , Alnuwaiser Maha Abdallah , Ullah Shafi , Iqbal Muhammad , Alfatama Mulham , Lim Vuanghao
Published: July 2022

(1) Background: The present study aimed to prepare chitosan-coated nanoemulsion gel containing 5-fluorouracil for enhanced topical delivery. (2) Methods: To formulate the nanoemulsion gel, oleic acid was used as the oil phase and Carbopol 940 as a gelling agent. Chitosan was used as a coating agent to control the release of 5-FU. Drug–excipient compatibility was evaluated using ATR-FTIR. The prepared nanoemulsion formulations were characterized based on particle size distribution, zeta potential, % encapsulation efficiency and drug content. In vitro drug release, skin drug retention and ex vivo permeation profiles were performed across rat skin using a Franz diffusion cell. Skin irritation experiments were also conducted on rats to examine the irritation potential of the formulations. (3) Results: It was found that the drug and excipients were compatible and chitosan successfully coated 5-FU, as demonstrated by ATR-FTIR results. The introduction of chitosan increased the size and zeta potential of the nanoemulsion. The 5-FU release in vitro was significantly lowered in the case of chitosan-decorated nanoemulsion (5-FU-C-NE), whereas the permeation and skin drug retention were higher in the case of 5-FU-C-NE. The formulations were proven non-irritant to the skin of the rats. The optimized formulation of the nanoemulsion was introduced into 1% Carbopol 940 gel. Incorporating the nanoemulsion into the gel further reduced the drug release in vitro and ex vivo permeation, whereas the retention of the drug in the skin was significantly increased (ANOVA; p < 0.05). The increase in skin retention was due to the presence of chitosan and Carbopol 940. The in vitro and ex vivo results were also confirmed with in vivo studies. Incorporating nanoemulsion into gel has resulted in higher Tmax, longer half-life and greater skin drug retention. (4) Conclusion: The results suggest that chitosan-decorated nanoemulsion gel is safe and can potentially be used to promote 5-FU skin retention, which is ideal for skin diseases such as melanoma.
Overview of Transcriptomic Research on Type 2 Diabetes: Challenges and Perspectives
Authors: Tonyan Ziravard N. , Nasykhova Yulia A. , Danilova Maria M. , Barbitoff Yury A. , Changalidi Anton I. , Mikhailova Anastasiia A. , Glotov Andrey S.
Published: July 2022

Type 2 diabetes (T2D) is a common chronic disease whose etiology is known to have a strong genetic component. Standard genetic approaches, although allowing for the detection of a number of gene variants associated with the disease as well as differentially expressed genes, cannot fully explain the hereditary factor in T2D. The explosive growth in the genomic sequencing technologies over the last decades provided an exceptional impetus for transcriptomic studies and new approaches to gene expression measurement, such as RNA-sequencing (RNA-seq) and single-cell technologies. The transcriptomic analysis has the potential to find new biomarkers to identify risk groups for developing T2D and its microvascular and macrovascular complications, which will significantly affect the strategies for early diagnosis, treatment, and preventing the development of complications. In this article, we focused on transcriptomic studies conducted using expression arrays, RNA-seq, and single-cell sequencing to highlight recent findings related to T2D and challenges associated with transcriptome experiments.