bluuebunny/crossref_metadata_2025 huggingface dataset:
Quality of Life and the Digital Service Landscape: The Moderating Role of Customer Complaining Effort
Authors: Berceanu Denisa Cristina-Alina , Pânișoară Georgeta , Popovici Alexandru-Filip , Ghiță Cristina Marina
Published: May 2023

The last decade, and more specifically the COVID-19 pandemic, has created a favorable environment for digitalization, which has become a necessary condition in the context of how everyday life is conducted. Even if digital communication and services have become a trend and help brand–customer relationships, brands still have more gaps to close. The purpose of this study was to investigate how consumers’ behaviors and digital interactions impact their shopping well-being and quality of life, and how the level of customer complaining effort affects the relationship between digital behavior and quality of life. This research provides practical implications for companies and marketers that offer digital services and technologies, helping them design and deliver more effective and customer-centric digital experiences. Additionally, it contributes to the growing interest in how digital services and technologies can improve consumer experiences and quality of life. This study surveyed 331 respondents in Romania. Results show that digital behavior influences consumers’ shopping well-being and comes with insights that strengthen the importance of reducing consumers’ cognitive and procedural effort in order to increase their quality of life. The paper discusses the implications for brands that must design easy experiences to gain more loyal customers, the study’s implications and novelty for the warranty area.
Mapping the Risk of Occurrence of Defects in Façades with Ceramic Claddings
Authors: Castro Wilamy , Souza Jéssica , Gaspar Pedro , Silva Ana
Published: May 2023

When a building façade does not meet its performance requirements, the integrity and safety of the structure may be compromised, resulting in the reduction of the building’s service life. Ceramic tiles are a commonly applied cladding solution due to their aesthetic value and durability. However, as soon as ceramic claddings are installed, the claddings are subjected to various degradation agents, thus starting a degradation process in which different anomalies occur sequentially and simultaneously over the years. This study intends to find patterns of incidence of anomalies in distinct areas of the façade and to map the risk of occurrence of a given anomaly. For that purpose, 345 ceramic claddings are analysed (46 buildings, corresponding to 81,500 m2) in the region of Brasília, Brazil. Four main defects are identified based on visual inspections and using auxiliary diagnosis techniques, namely (i) detachment of ceramic tiles; (ii) cracking; (iii) grout failure; (iv) efflorescence. The results reveal that the detachment is the most frequent defect. The sensitivity maps proposed allow identifying a certain pattern in the occurrence of defects on ceramic claddings, revealing that continuous walls, transition between floors, and the top of the building are areas critically vulnerable to defects. The results obtained allow mapping the sensitivity of each part of the ceramic claddings to a given defect, aiding the detection and diagnosis of the degradation condition when carrying out inspections on new façades.
Tumor Sink Effect with Prostate-Specific Membrane Antigen-Targeted Theranostics in Patients with Metastatic Castration-Resistant Prostate Cancer: Intra-Individual Evaluations
Authors: Burgard Caroline , Rosar Florian , Marlowe Robert J. , Bartholomä Mark , Dewes Sebastian , Schaefer-Schuler Andrea , Linxweiler Johannes , Khreish Fadi , Ezziddin Samer
Published: May 2023

“Tumor sink effects”, decreased physiological uptake of radiopharmaceuticals due to sequestration by a tumor, may impact radioligand therapy (RLT) toxicity and dosing. We investigated these effects with prostate-specific membrane antigen (PSMA)-targeted radiopharmaceuticals in the healthy organs-at-risk (the parotid glands, kidneys, liver, and spleen) of 33 patients with metastatic castration-resistant prostate cancer (mCRPC). We retrospectively performed three intra-individual comparisons. First, we correlated changes from baseline to post-RLT (after two 177-lutetium (177Lu)-PSMA-617 cycles) in total lesional PSMA (∆TLP) and organ mean standardized uptake values (∆SUVmean). Second, in 25 RLT responders, we compared the organ SUVmean post-RLT versus that at baseline. Lastly, we correlated the baseline TLP and organ SUVmean. Data were acquired via 68-gallium-PSMA-11 positron emission tomography before the first and after the second 177Lu-PSMA-617 cycle. In the parotid glands and spleen, ∆TLP and ∆SUVmean showed a significant inverse correlation (r = −0.40, p = 0.023 and r = −0.36, p = 0.042, respectively). Additionally, in those tissues, the median organ SUVmean rose significantly from baseline after the response to RLT (p ≤ 0.022), and the baseline TLP and SUVmean were significantly negatively correlated (r = −0.44, p = 0.01 and r = −0.42, p = 0.016, respectively). These observations suggest tumor sink effects with PSMA-targeted radiopharmaceuticals in the salivary glands and spleen of patients with mCRPC.
Management of Esophago-Gastric Junction Carcinoma: A Narrative Multidisciplinary Review
Authors: Tondolo Vincenzo , Casà Calogero , Rizzo Gianluca , Leone Mariavittoria , Quero Giuseppe , Alfieri Virginia , Boldrini Luca , Bulajic Milutin , Corsi Domenico , Micciché Francesco
Published: May 2023

Esophagogastric junction (EGJ) carcinoma represents a specific site of disease, given the opportunities for multimodal clinical care and management and the possibilities of combined treatments. It encompasses various clinical subgroups of disease that are heterogeneous and deserve different treatments; therefore, the guidelines have progressively evolved over time, considering the evidence provided by clinical trials. The aim of this narrative review was to summarize the main evidence, which orientates the current guidelines, and to collect the main ongoing studies to address existing gray areas.
Multidisciplinary Treatment of Patients with Progressive Biliary Tract Cancer after First-Line Gemcitabine and Cisplatin: A Single-Center Experience
Authors: Müller Christian , Omari Jazan , Mohnike Konrad , Bär Caroline , Pech Maciej , Keitel Verena , Venerito Marino
Published: May 2023

Background: Patients with unresectable biliary tract cancer (uBTC) who progress despite first-line gemcitabine plus cisplatin (GC) treatment have limited systemic options with a modest survival benefit. Data are lacking on the clinical effectiveness and safety of personalized treatment based on multidisciplinary discussion for patients with progressing uBTC. Methods: This retrospective single-center study included patients with progressive uBTC who received either best supportive care or personalized treatment based on multidisciplinary discussion, including minimally invasive, image-guided procedures (MIT); FOLFIRI; or both (MIT and FOLFIRI), between 2011 and 2021. Results: Ninety-seven patients with progressive uBTC were identified. Patients received best supportive care (n = 50, 52%), MIT (n = 14, 14%), FOLFIRI (n = 19, 20%), or both (n = 14, 14%). Survival after disease progression was better in patients who received MIT (8.8 months; 95% CI: 2.60–15.08), FOLFIRI (6 months; 95% CI: 3.30–8.72), or both (15.1 months; 95% CI: 3.66–26.50) than in patients receiving BSC (0.36 months; 95% CI: 0.00–1.24, p < 0.001). The most common (>10%) grade 3–5 adverse events were anemia (25%) and thrombocytopenia (11%). Conclusion: Multidisciplinary discussion is critical for identifying patients with progressive uBTC who might benefit the most from MIT, FOLFIRI, or both. The safety profile was consistent with previous reports.
Young-Onset Cancers—Early Steps in the Right Direction
Authors: Barreto Savio George , Ben-Aharon Irit
Published: May 2023

The global incidence of young-onset (YO) cancer is on the rise [...]
Extracellular Vesicles Potentiate Medulloblastoma Metastasis in an EMMPRIN and MMP-2 Dependent Manner
Authors: Jackson Hannah K. , Mitoko Christine , Linke Franziska , Macarthur Donald , Kerr Ian D. , Coyle Beth
Published: May 2023

Extracellular vesicles (EVs) have emerged as pivotal mediators of communication in the tumour microenvironment. More specifically, nanosized extracellular vesicles termed exosomes have been shown to contribute to the establishment of a premetastatic niche. Here, we sought to determine what role exosomes play in medulloblastoma (MB) progression and elucidate the underlying mechanisms. Metastatic MB cells (D458 and CHLA-01R) were found to secrete markedly more exosomes compared to their nonmetastatic, primary counterparts (D425 and CHLA-01). In addition, metastatic cell-derived exosomes significantly enhanced the migration and invasiveness of primary MB cells in transwell migration assays. Protease microarray analysis identified that matrix metalloproteinase-2 (MMP-2) was enriched in metastatic cells, and zymography and flow cytometry assays of metastatic exosomes demonstrated higher levels of functionally active MMP-2 on their external surface. Stable genetic knockdown of MMP-2 or extracellular matrix metalloproteinase inducer (EMMPRIN) in metastatic MB cells resulted in the loss of this promigratory effect. Analysis of serial patient cerebrospinal fluid (CSF) samples showed an increase in MMP-2 activity in three out of four patients as the tumour progressed. This study demonstrates the importance of EMMPRIN and MMP-2-associated exosomes in creating a favourable environment to drive medulloblastoma metastasis via extracellular matrix signalling.
Whole-Body Composition Features by Computed Tomography in Ovarian Cancer: Pilot Data on Survival Correlations
Authors: Raia Giorgio , Del Grande Maria , Colombo Ilaria , Nerone Marta , Manganaro Lucia , Gasparri Maria Luisa , Papadia Andrea , Del Grande Filippo , Rizzo Stefania
Published: May 2023

Background: The primary objective of this study was to assess the associations of computed tomography (CT)-based whole-body composition values with overall survival (OS) and progression-free survival (PFS) in epithelial ovarian cancer (EOC) patients. The secondary objective was the association of body composition with chemotherapy-related toxicity. Methods: Thirty-four patients (median age 64.9 years; interquartile range 55.4–75.4) with EOC and thorax and abdomen CT scans were included. Clinical data recorded: age; weight; height; stage; chemotherapy-related toxicity; and date of last contact, progression and death. Automatic extraction of body composition values was performed by dedicated software. Sarcopenia was defined according to predefined cutoffs. Statistical analysis included univariate tests to investigate associations of sarcopenia and body composition with chemotoxicity. Association of body composition parameters and OS/PFS was evaluated by log-rank test and Cox proportional hazard model. Multivariate models were adjusted for FIGO stage and/or age at diagnosis. Results: We found significant associations of skeletal muscle volume with OS (p = 0.04) and PFS (p = 0.04); intramuscular fat volume with PFS (p = 0.03); and visceral adipose tissue, epicardial and paracardial fat with PFS (p = 0.04, 0.01 and 0.02, respectively). We found no significant associations between body composition parameters and chemotherapy-related toxicity. Conclusions: In this exploratory study, we found significant associations of whole-body composition parameters with OS and PFS. These results open a window to the possibility to perform body composition profiling without approximate estimations.
Catalytic Oxidation of VOC over Cobalt-Loaded Hierarchical MFI Zeolite
Authors: Grahovski Bozhidar , Velinova Ralitsa , Shestakova Pavletta , Naydenov Anton , Kolev Hristo , Yordanova Iliyana , Ivanov Georgi , Tenchev Krasimir , Todorova Silviya
Published: May 2023

The zeolites ZSM-5 with different Si/Al ratios were modified with a buffer solution of HF and NH4F. This acidic treatment led to the obtaining of a material with secondary mesoporosity. The deposition of cobalt from an aqueous solution of cobalt acetate on the surface of treated samples generates the formation of different cobalt oxide species: bulk-like Co3O4 phases strongly interacting with the support, Co2+ in ion exchange positions (γ and β sites) and silicate-like phases. The mechanism of cobalt silicate phase formation is proposed here and includes a replacement of silanol groups and the bridging hydrogens by Co and the inclusion of the Co atoms in tetrahedral framework positions. The catalysts, obtained through use of the treated ZSM-5, exhibit higher activity in the reactions of propane, and n-hexane completes oxidation compared with the catalyst samples containing un-treated zeolite. Both the finer dispersion of metal oxide particles on the hierarchical sample and the presence of secondary mesoporosity improve the effectiveness of the active phase utilization via access to larger number of active sites.
Clorfl86/RHEX Is a Negative Regulator of SCF/KIT Signaling in Human Skin Mast Cells
Authors: Franke Kristin , Bal Gürkan , Li Zhuoran , Zuberbier Torsten , Babina Magda
Published: May 2023

Mast cells (MCs) are key effector cells in allergic and inflammatory diseases, and the SCF/KIT axis regulates most aspects of the cells’ biology. Using terminally differentiated skin MCs, we recently reported on proteome-wide phosphorylation changes initiated by KIT dimerization. C1orf186/RHEX was revealed as one of the proteins to become heavily phosphorylated. Its function in MCs is undefined and only some information is available for erythroblasts. Using public databases and our own data, we now report that RHEX exhibits highly restricted expression with a clear dominance in MCs. While expression is most pronounced in mature MCs, RHEX is also abundant in immature/transformed MC cell lines (HMC-1, LAD2), suggesting early expression with further increase during differentiation. Using RHEX-selective RNA interference, we reveal that RHEX unexpectedly acts as a negative regulator of SCF-supported skin MC survival. This finding is substantiated by RHEX’s interference with KIT signal transduction, whereby ERK1/2 and p38 both were more strongly activated when RHEX was attenuated. Comparing RHEX and capicua (a recently identified repressor) revealed that each protein preferentially suppresses other signaling modules elicited by KIT. Induction of immediate-early genes strictly requires ERK1/2 in SCF-triggered MCs; we now demonstrate that RHEX diminution translates to this downstream event, and thereby enhances NR4A2, JUNB, and EGR1 induction. Collectively, our study reveals RHEX as a repressor of KIT signaling and function in MCs. As an abundant and selective lineage marker, RHEX may have various roles in the lineage, and the provided framework will enable future work on its involvement in other crucial processes.
Effects of Rho-Associated Kinase (Rock) Inhibitors (Alternative to Y-27632) on Primary Human Corneal Endothelial Cells
Authors: Peh Gary S. L. , Bandeira Francisco , Neo Dawn , Adnan Khadijah , Hartono Yossa , Ong Hon Shing , Naso Sacha , Venkatraman Anandalakshmi , Gomes José A. P. , Kocaba Viridiana , Mehta Jodhbir S.
Published: May 2023

(1) Rho-associated coiled-coil protein kinase (ROCK) signaling cascade impacts a wide array of cellular events. For cellular therapeutics, scalable expansion of primary human corneal endothelial cells (CECs) is crucial, and the inhibition of ROCK signaling using a well characterized ROCK inhibitor (ROCKi) Y-27632 had been shown to enhance overall endothelial cell yield. (2) In this study, we compared several classes of ROCK inhibitors to both ROCK-I and ROCK-II, using in silico binding simulation. We then evaluated nine ROCK inhibitors for their effects on primary CECs, before narrowing it down to the two most efficacious compounds—AR-13324 (Netarsudil) and its active metabolite, AR-13503—and assessed their impact on cellular proliferation in vitro. Finally, we evaluated the use of AR-13324 on the regenerative capacity of donor cornea with an ex vivo corneal wound closure model. Donor-matched control groups supplemented with Y-27632 were used for comparative analyses. (3) Our in silico simulation revealed that most of the compounds had stronger binding strength than Y-27632. Most of the nine ROCK inhibitors assessed worked within the concentrations of between 100 nM to 30 µM, with comparable adherence to that of Y-27632. Of note, both AR-13324 and AR-13503 showed better cellular adherence when compared to Y-27632. Similarly, the proliferation rates of CECs exposed to AR-13324 were comparable to those of Y-27632. Interestingly, CECs expanded in a medium supplemented with AR-13503 were significantly more proliferative in (i) untreated vs. AR-13503 (1 μM; * p < 0.05); (ii) untreated vs. AR-13503 (10 μM; *** p < 0.001); (iii) Y-27632 vs. AR-13503 (10 μM; ** p < 0.005); (iv) AR-13324 (1 μM) vs. AR-13503 (10 μM; ** p < 0.005); and (v) AR-13324 (0.1 μM) vs. AR-13503 (10 μM; * p < 0.05). Lastly, an ex vivo corneal wound healing study showed a comparable wound healing rate for the final healed area in corneas exposed to Y-27632 or AR-13324. (4) In conclusion, we were able to demonstrate that various classes of ROCKi compounds other than Y-27632 were able to exert positive effects on primary CECs, and systematic donor-match controlled comparisons revealed that the FDA-approved ROCK inhibitor, AR-13324, is a potential candidate for cellular therapeutics or as an adjunct drug in regenerative treatment for corneal endothelial diseases in humans.
GFAP as a Potential Biomarker for Alzheimer’s Disease: A Systematic Review and Meta-Analysis
Authors: Kim Ka Young , Shin Ki Young , Chang Keun-A
Published: May 2023

Blood biomarkers have been considered tools for the diagnosis, prognosis, and monitoring of Alzheimer’s disease (AD). Although amyloid-β peptide (Aβ) and tau are primarily blood biomarkers, recent studies have identified other reliable candidates that can serve as measurable indicators of pathological conditions. One such candidate is the glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal protein that can be detected in blood samples. Increasing evidence suggests that blood GFAP levels can be used to detect early-stage AD. In this systematic review and meta-analysis, we aimed to evaluate GFAP in peripheral blood as a biomarker for AD and provide an overview of the evidence regarding its utility. Our analysis revealed that the GFAP level in the blood was higher in the Aβ-positive group than in the negative groups, and in individuals with AD or mild cognitive impairment (MCI) compared to the healthy controls. Therefore, we believe that the clinical use of blood GFAP measurements has the potential to accelerate the diagnosis and improve the prognosis of AD.
Ziziphus spina-christi Leaf-Derived Carbon Dots as a Fluorescence Nanosensor to Evaluate Rifaximin Antibacterial via Inner Filter Effect: Greenness and Whiteness Studies
Authors: Hamd Mohamed , Albalawi Marzough , Gomaa Hassanien , Mohammad Bassam , Abdul-Kareem Rady , Obaydo Reem , Alsaggaf Wejdan , Saleh Safaa , Alossaimi Manal , Abdel-Lateef Mohamed
Published: May 2023

Rifaximin (RFX) is a non-absorbable antibiotic with broad-spectrum efficacy. It treats travelers’ diarrhea, irritable bowel syndrome, non-systematic bacterial diarrhea, bowel infections, overgrowth syndrome, and enteric infections. In this work, carbon dots prepared from Ziziphus spina-christi leaves’ powders are utilized as a green fluorometric biosensor for the assessment of RFX. The morphological lineaments of the prepared carbon dots were recognized by using TEM and SEM techniques. The prepared carbon dots manifest a fluorescence emission peak at 432 nm after an excitation fluorescence peak at 366 nm. The absorbance band of RFX (absorbance peaks at 370 nm and 443 nm) could be thoroughly overlapped with fluorescence excitation/emission bands of the produced carbon dots. A fluorometric tool has been designed and validated for the evaluation of RFX reliant on the inner filter effect methodology, in which the produced carbon dots act as an inner filter effect fluorophore and RFX as an inner filter effect absorber. The quenching degree in the fluorescence activity of the prepared carbon dots depended on the concentration of RFX. The analytical parameters were checked and directed for successfully applied assessment of RFX concentration in different pharmaceutical formulations. The proposed tool’s greenness and eco-friendliness profile was evaluated using the most recent greenness assessment tool, which is the complementary green analytical procedure index (Complex-GAPI) and the Analytical GREEnness metric (AGREE). Additionally, using the recently released White Analytical Chemistry (WAC) tool, the whiteness characteristic—which indicated the method’s sustainability—was investigated.
Preparation of Reduced Graphene Oxide Sheets with Large Surface Area and Porous Structure for High-Sensitivity Humidity Sensor
Authors: Kim Seo Jin , Park Hong Jun , Yoon Eun Seop , Choi Bong Gill
Published: May 2023

Humidity sensors provide environmental conditions suitable for several applications. However, they suffer from a limited reliable range originating from the low electrical conductivity and low water-sensitive sites of humidity-sensing materials. In this study, we developed high-sensitivity humidity sensors based on holey-reduced graphene oxide (HRGO) with a large surface area (274.5 m2/g) and an abundant pore structure. HRGO was prepared via the H2O2-etching-reaction-assisted hydrothermal processing of graphene oxide sheets. The resulting humidity sensor exhibited high sensitivity (−0.04317 log Z/%RH, R2 = 0.9717), a fast response time (<3 s), and long-term stability over 28 days. The impedance responses of the humidity sensor were almost similar between the mechanically standard and bent states. Furthermore, electrochemical impedance spectroscopy was performed to understand the humidity-sensing mechanism of the HRGO materials.
Specific Features of Focal Cortical Dysplasia in Tuberous Sclerosis Complex
Authors: Bychkova Ekaterina , Dorofeeva Marina , Levov Aleksandr , Kislyakov Alexey , Karandasheva Kristina , Strelnikov Vladimir , Anoshkin Kirill
Published: May 2023

Patients with tuberous sclerosis complex present with cognitive, behavioral, and psychiatric impairments, such as intellectual disabilities, autism spectrum disorders, and drug-resistant epilepsy. It has been shown that these disorders are associated with the presence of cortical tubers. Tuberous sclerosis complex results from inactivating mutations in the TSC1 or TSC2 genes, resulting in hyperactivation of the mTOR signaling pathway, which regulates cell growth, proliferation, survival, and autophagy. TSC1 and TSC2 are classified as tumor suppressor genes and function according to Knudson’s two-hit hypothesis, which requires both alleles to be damaged for tumor formation. However, a second-hit mutation is a rare event in cortical tubers. This suggests that the molecular mechanism of cortical tuber formation may be more complicated and requires further research. This review highlights the issues of molecular genetics and genotype–phenotype correlations, considers histopathological characteristics and the mechanism of morphogenesis of cortical tubers, and also presents data on the relationship between these formations and the development of neurological manifestations, as well as treatment options.
Theoretical and Numerical Constant Mean Curvature Surface and Liquid Entry Pressure Calculations for a Combined Pillar–Pore Structure
Authors: Jäger Tobias , Keup Jemp , Prasianakis Nikolaos I. , Leyer Stephan
Published: May 2023

Modern microfabrication techniques have led to a growing interest in micropillars and pillar–pore structures. Therefore, in this paper a study of the liquid entry pressure of a hydrophobic pillar–pore structure and the corresponding liquid–gas interface shape for the pressurized liquid is presented. We theoretically analysed the constant mean curvature problem for the rotationally symmetric case and determined an analytical expression for the liquid entry pressure of a hydrophobic pillar–pore structure. Furthermore, the shape of the liquid–gas interface as well as a formula for the location of the minimum were derived. The results are useful for designing geometries with specific properties, such as preventing or facilitating liquid intrusion into rough structures. We compared these results to multiphase lattice Boltzmann simulations where equilibrium contact angles in the range of 157∘ to 102∘ were tested. In our further analysis, we compared theoretical findings from previous works to our lattice Boltzmann simulations. The presented cases can serve as a benchmark for the development and validation of numerical multiphase models.
Effects of Preparation Parameters on the Structural and Morphologic Properties of SnO2-Sb Coatings
Authors: He Zhen , Yu Chen , Liu Jiaming , Miao Zengcheng , Wang Yuxin
Published: May 2023

Sb-doped SnO2 (SnO2-Sb) coatings show superiority in degrading toxic and refractory organic pollutants. SnO2-Sb coatings can be prepared by oxidizing electrodeposited Sn-Sb coatings through an annealing process. The properties and structure of SnO2-Sb coatings can be tailored by adjusting the preparation parameters. This study examines the effects of crucial preparation parameters on the performance of SnO2-Sb coatings, with the aim of enhancing their properties.Determining the coatings’ cross-sectional and surface characteristics was accomplished using various characterization techniques. A thorough investigation of the prepared samples’ phase and element components was also carried out. Based on the findings, the surface roughness of the prepared Sn-Sb precoating changed with increasing current density, yet the primary surface features of the SnO2-Sb coatings were hardly altered by the annealing process. Without lowering the coating thickness, the appropriate current density of 30 mA/cm2 produced a rough and active coating surface. Our study’s proper annealing temperature of 600 °C transformed Sn-Sb precoating into SnO2-Sb coating and achieved excellent coating quality.While changes in the Sb content affected the morphology of the prepared SnO2-Sb coatings, the mixed oxide coatings’ cassiterite SnO2 phase was unaffected. These results may provide insights into the optimized use of SnO2-Sb coatings in various applications.
The Applicability of Automated Testing Frameworks for Mobile Application Testing: A Systematic Literature Review
Authors: Berihun Natnael Gonfa , Dongmo Cyrille , Van der Poll John Andrew
Published: May 2023

Mobile applications are developed and released to the market every day. Due to the intense usage of mobile applications, their quality matters. End users’ rejection of mobile apps increases from time to time due to their low quality and lack of proper mobile testing. This indicates that the role of mobile application testing is crucial in the acceptance of a given software product. Test engineers use automation frameworks for testing their mobile applications. Automated testing brings several advantages to the development team. For example, automated checks are used for regression testing, fast execution of test scripts, and providing quick feedback for the development team. A systematic literature review has been used to identify and collect evidence on automated testing frameworks for mobile application testing. A total of 56 relevant research papers were identified that were published in prominent journals and conferences until February 2023. The results were summarized and tabulated to provide insights into the suitability of the existing automation testing framework for mobile application testing. We identified the major test concerns and test challenges in performing mobile automation testing. The results showed that the keyword-driven testing framework is the widely used approach, but recently, hybrid approaches have been adopted for mobile test automation. On the other hand, this review indicated that the existing frameworks need to be customized using reusable and domain-specific keywords to make them suitable for mobile application testing. Considering this, this study proposes an architecture, the mobile-based automation testing framework (MATF). In the future, to address the mobile application testing challenges, the authors will work on implementing the proposed framework (MATF).
Adverse Effects of Immune-Checkpoint Inhibitors: A Comprehensive Imaging-Oriented Review
Authors: Mallio Carlo Augusto , Bernetti Caterina , Cea Laura , Buoso Andrea , Stiffi Massimo , Vertulli Daniele , Greco Federico , Zobel Bruno Beomonte
Published: May 2023

Immune-checkpoint inhibitors (ICIs) are immunomodulatory monoclonal antibodies, which increase antitumor immunity of the host and facilitate T-cell-mediated actions against tumors. These medications have been used in recent years as a weapon against advanced stage malignancies, such as melanoma, renal cell carcinoma, lymphoma, small or non-small cell lung cancer, and colorectal cancer. Unfortunately, they are not free from possible adverse effects (immune-related adverse events—irAEs) that mainly affect skin, gastrointestinal, hepatic, and endocrine systems. Early diagnosis of irAEs is essential to correctly and rapidly manage patients, with ICIs suspension and therapies administration. Deep knowledge of the imaging and clinical patterns of irAEs is the key to promptly rule out other diagnoses. Here, we performed a review of the radiological signs and differential diagnosis, based on the organ involved. The aim of this review is to provide guidance to recognize the most significant radiological findings of the main irAEs, based on incidence, severity, and the role of imaging.
Chest CT Findings after Mild COVID-19 Do Not Explain Persisting Respiratory Symptoms: An Explanatory Study
Authors: Malesevic Stefan , Sievi Noriane A. , Herth Jonas , Schmidt Felix , Schmidt Dörthe , Vallelian Florence , Jelcic Ilijas , Jungblut Lisa , Frauenfelder Thomas , Kohler Malcolm , Martini Katharina , Clarenbach Christian F.
Published: May 2023

(1) Background: Lung tissue involvement is frequently observed in acute COVID-19. However, it is unclear whether CT findings at follow-up are associated with persisting respiratory symptoms after initial mild or moderate infection. (2) Methods: Chest CTs of patients with persisting respiratory symptoms referred to the post-COVID-19 outpatient clinic were reassessed for parenchymal changes, and their potential association was evaluated. (3) Results: A total of 53 patients (31 female) with a mean (SD) age of 46 (13) years were included, of whom 89% had mild COVID-19. Median (quartiles) time from infection to CT was 139 (86, 189) days. Respiratory symptoms were dyspnea (79%), cough (42%), and thoracic pain (64%). Furthermore, 30 of 53 CTs showed very discrete and two CTs showed medium parenchymal abnormalities. No severe findings were observed. Mosaic attenuation (40%), ground glass opacity (2%), and fibrotic-like changes (25%) were recorded. No evidence for an association between persisting respiratory symptoms and chest CT findings was found. (4) Conclusions: More than half of the patients with initially mild or moderate infection showed findings on chest CT at follow-up. Respiratory symptoms, however, were not related to any chest CT finding. We, therefore, do not suggest routine chest CT follow-up in this patient group if no other indications are given.
BRMI-Net: Deep Learning Features and Flower Pollination-Controlled Regula Falsi-Based Feature Selection Framework for Breast Cancer Recognition in Mammography Images
Authors: Rehman Shams ur , Khan Muhamamd Attique , Masood Anum , Almujally Nouf Abdullah , Baili Jamel , Alhaisoni Majed , Tariq Usman , Zhang Yu-Dong
Published: May 2023

The early detection of breast cancer using mammogram images is critical for lowering women’s mortality rates and allowing for proper treatment. Deep learning techniques are commonly used for feature extraction and have demonstrated significant performance in the literature. However, these features do not perform well in several cases due to redundant and irrelevant information. We created a new framework for diagnosing breast cancer using entropy-controlled deep learning and flower pollination optimization from the mammogram images. In the proposed framework, a filter fusion-based method for contrast enhancement is developed. The pre-trained ResNet-50 model is then improved and trained using transfer learning on both the original and enhanced datasets. Deep features are extracted and combined into a single vector in the following phase using a serial technique known as serial mid-value features. The top features are then classified using neural networks and machine learning classifiers in the following stage. To accomplish this, a technique for flower pollination optimization with entropy control has been developed. The exercise used three publicly available datasets: CBIS-DDSM, INbreast, and MIAS. On these selected datasets, the proposed framework achieved 93.8, 99.5, and 99.8% accuracy, respectively. Compared to the current methods, the increase in accuracy and decrease in computational time are explained.
Comprehensive Genomic Profiling and Therapeutic Implications for Patients with Advanced Cancers: The Experience of an Academic Hospital
Authors: Teuwen Laure-Anne , Roets Evelyne , D’Hoore Pieter , Pauwels Patrick , Prenen Hans
Published: May 2023

Next-generation sequencing (NGS) can be used to detect tumor-specific genomic alterations. This retrospective single-center study aims to assess the application of an extensive NGS panel to identify actionable alterations and initiate matched targeted treatment for patients with advanced cancer. We analyzed genomic alterations in solid tumor biopsies from 464 patients with advanced cancer with the Foundation Medicine assay (FoundationOne®CDx). Therapeutic implications were determined using the Memorial Sloan Kettering Precision Oncology Knowledge Base (OncoKB) classification. The FoundationOne®CDx was successfully applied in 464/521 patients (89%). The most common altered genes were TP53 (61%), KRAS (20%), CDKN2A (20%), TERT (16%), and APC (16%). Among the 419 patients with successfully analyzed tumor mutational burden (TMB), 43 patients presented with a high TMB (≥10 mutations/megabase). Out of the 126 patients with an actionable target, 40 patients received matched treatment (32%) of which 17 were within a clinical trial. This study shows that the application of NGS is feasible in an academic center and increases the detection of actionable alterations and identification of patients eligible for targeted treatment or immunotherapy regardless of tumor histology. Strategies such as early referral for NGS, inclusion in clinical (basket) trials, and the development of new targeted drugs are necessary to improve the matched treatment rate.
A Novel Hybrid Runge Kutta Optimizer with Support Vector Machine on Gene Expression Data for Cancer Classification
Authors: Houssein Essam , Hassan Hager , Samee Nagwan , Jamjoom Mona
Published: May 2023

It is crucial to accurately categorize cancers using microarray data. Researchers have employed a variety of computational intelligence approaches to analyze gene expression data. It is believed that the most difficult part of the problem of cancer diagnosis is determining which genes are informative. Therefore, selecting genes to study as a starting point for cancer classification is common practice. We offer a novel approach that combines the Runge Kutta optimizer (RUN) with a support vector machine (SVM) as the classifier to select the significant genes in the detection of cancer tissues. As a means of dealing with the high dimensionality that characterizes microarray datasets, the preprocessing stage of the ReliefF method is implemented. The proposed RUN–SVM approach is tested on binary-class microarray datasets (Breast2 and Prostate) and multi-class microarray datasets in order to assess its efficacy (i.e., Brain Tumor1, Brain Tumor2, Breast3, and Lung Cancer). Based on the experimental results obtained from analyzing six different cancer gene expression datasets, the proposed RUN–SVM approach was found to statistically beat the other competing algorithms due to its innovative search technique.
On the Determinants of Sanctions Effectiveness: An Empirical Analysis by Using Duration Models
Authors: Caetano José , Galego Aurora , Caleiro António
Published: May 2023

Sanctions are a recurrent issue on the international scene that has gained relevance in recent decades. This article intends to approach this matter in an innovative way by analyzing the relative importance of sanctions’ types and objectives, besides target countries’ characteristics, on sanctions outcomes. Unlike most previous studies, we use more comprehensive data and a competing risk discrete-time hazard model to analyze the differences between sanctions termination by target compliance and sender capitulation. Our results show that the determinants for the two outcomes differ and that there are differences in the efficacy of sanctions according to their type and objective. We conclude that while higher levels of political volatility, democracy, and equality in target countries increase the probability of compliance, higher levels of democracy and globalization increase the probability of sender capitulation. Smart sanctions seem to be more effective at targeting compliance, as the likelihood of compliance is higher for financial and military sanctions than for trade. The likelihood of compliance also increases if the objective is to promote democracy and decreases if the objectives are policy, regime change, or terrorism. Instead, the probability of sender capitulation is higher for travel and trade sanctions and if the objective is to promote human rights.
A Systematic Review of Critical Success Factors in Blended Learning
Authors: Min Wenhe , Yu Zhonggen
Published: May 2023

Against the backdrop of the post-pandemic period, there is an increasing need for blended learning in modern higher education systems. Critical success factors for blended learning should be considered as key indicators of learning outcomes. Therefore, the aim is to systematically review studies that examine the critical success factors for blended learning from the perspectives of the learner, instructor, course, design, technology, and environment. Eighty-two articles were analysed according to PRISMA (Preferred Reporting Items for Systematic Review and Meta-analysis) principles. The results show that critical success factors in these six dimensions have a positive impact on blended learning outcomes. These critical success factors are mainly learner characteristics, teacher characteristics, course materials and objectives, learning characteristics according to institutional objectives, ICT system, and learning environment. Future research could explore the impact of positive emotions on student and teacher learning outcomes in blended learning.
Impact of Gamified Teaching on University Student Learning
Authors: Montenegro-Rueda Marta , Fernández-Cerero José , Mena-Guacas Andrés F. , Reyes-Rebollo Miguel María
Published: May 2023

Gamification is presented as an innovative strategy to traditional teaching in higher education. In this sense, the aim of this study is to review the scientific literature in order to analyse the implementation of gamification in higher education. The impact of gamified teaching on the learning of university students was identified through the analysis of eighteen articles published in four databases (Web of Science, Scopus, Google Scholar, and Dialnet). It is evident that gamification is a novel topic in higher education, providing numerous benefits in the learning of university students, but it is still a little-explored area, being scarce in its application in some branches of knowledge. It is recommended to continue researching and generating experiences on its application in higher education in order to know its real effects on the teaching–learning process of university students.
Investigating the Characteristics of Knowledge-Related Learning Assignments in Upper Secondary School
Authors: Ilomäki Liisa , Lakkala Minna , Muukkonen Hanni , Paavola Sami , Toom Auli
Published: May 2023

This study reports on whether students have the opportunity to acquire generic competencies when they work with knowledge-related assignments at upper secondary school. We investigated 30 assignments. The data included lesson observations and interviews with teachers. The main categories of teaching practices were theory-based, and the subcategories and the levels of intensity were based on qualitative analysis of the data. The most common categories were Object-orientedness, Epistemic challenge, Process-like emphasis, Intensity of collaboration, Cross-fertilisation, and Information practices. The least common categories were Cross-fertilisation, Process-like emphasis, and Object-orientedness. Cluster analysis produced three groups: Open and challenging assignments with guidance and support (eight cases), Demanding assignments without support (seven cases), and Well-defined, teacher-directed assignments (15 cases). Assignments of the first type support students’ knowledge-related competencies the best. The second type of assignment is demanding because students work independently with limited support for challenging assignments. Assignments of the third type were well-structured and teacher-centered assignments.
Say Yes to Education—Buffalo: A Human Capabilities Approach to College Access and Local Economic Development
Authors: Daun-Barnett Nathan J.
Published: May 2023

In December 2012, researchers from the University at Buffalo partnered with Buffalo Public Schools and Say Yes to Education—Buffalo to assist students and families with the Free Application for Federal Student Aid (FAFSA). The community had just announced a last-dollar tuition guarantee for all public and charter high school graduates. Students had to apply for federal and state financial aid to be eligible. We use the human capabilities framework described by St. John to examine the contributions of this specific intervention and the broader collective impact strategy. In this study, we employ difference-in-difference regression analysis to examine the effects of a FAFSA completion intervention and find that providing support to students and families to complete the financial aid process increased FAFSA completion rates by more than 60%, year over year. In addition to considering the outcomes of this intervention, we report lessons learned in the process of establishing a university-community collaboration to improve postsecondary opportunity and economic development. We find that effective collaboration takes time and a shared commitment to understanding and addressing problems of practice in schools.
E-BiT: Extended Bio-Inspired Texture Descriptor for 2D Texture Analysis and Characterization
Authors: Ataky Steve Tsham Mpinda , Lameiras Koerich Alessandro
Published: May 2023

This paper presents an extended bio-inspired texture (E-BiT) descriptor for image texture characterization. The E-BiT descriptor combines global ecological concepts of species diversity, evenness, richness, and taxonomic indexes to effectively capture texture patterns at local and global levels while maintaining invariance to scale, translation, and permutation. First, we pre-processed the images by normalizing and applying geometric transformations to assess the invariance properties of the proposed descriptor. Next, we assessed the performance of the proposed E-BiT descriptor on four datasets, including histopathological images and natural texture images. Finally, we compared it with the original BiT descriptor and other texture descriptors, such as Haralick, GLCM, and LBP. The E-BiT descriptor achieved state-of-the-art texture classification performance, with accuracy improvements ranging from 0.12% to 20% over other descriptors. In addition, the E-BiT descriptor demonstrated its generic nature by performing well in both natural and histopathologic images. Future work could examine the E-BiT descriptor’s behavior at different spatial scales and resolutions to optimize texture property extraction and improve performance.
LiDAR Point Cloud Object Recognition Method via Intensity Image Compensation
Authors: Shi Chunhao , Wang Chunyang , Sun Shaoyu , Liu Xuelian , Xi Guan , Ding Yueyang
Published: May 2023

LiDAR point cloud object recognition plays an important role in robotics, remote sensing, and automatic driving. However, it is difficult to fully represent the object feature information only by using the point cloud information. To address this challenge, we proposed a point cloud object recognition method that uses intensity image compensation, which is highly descriptive and computationally efficient. First, we constructed the local reference frame for the point cloud. Second, we proposed a method to calculate the deviation angle between the normal vector and local reference frame in the local neighborhood of the point cloud. Third, we extracted the contour information of the object from the intensity image corresponding to the point cloud, carried out Discrete Fourier Transform on the distance sequence between the barycenter of the contour and each point of the contour, and took the obtained result as Discrete Fourier Transform contour feature of the object. Finally, we repeated the above steps for the existing prior data and marked the obtained results as the feature information of the corresponding object to build a model library. We can recognize an unknown object by calculating the feature information of the object to be recognized and matching the feature information with the model library. We rigorously tested the proposed method with avalanche photon diode array LiDAR data and compared the results with those of four other methods. The experimental results show that the proposed method is superior to the comparison method in terms of description and computational efficiency and that it can meet the needs of practical applications.
InSEption: A Robust Mechanism for Predicting FoG Episodes in PD Patients
Authors: Dimoudis Dimitris , Tsolakis Nikos , Magga-Nteve Christoniki , Meditskos Georgios , Vrochidis Stefanos , Kompatsiaris Ioannis
Published: May 2023

The integration of IoT and deep learning provides the opportunity for continuous monitoring and evaluation of patients’ health status, leading to more personalized treatment and improved quality of life. This study explores the potential of deep learning to predict episodes of freezing of gait (FoG) in Parkinson’s disease (PD) patients. Initially, a literature review was conducted to determine the state of the art; then, two inception-based models, namely LN-Inception and InSEption, were introduced and tested using the Daphnet dataset and an additional novel medium-sized dataset collected from an IMU (inertial measuring unit) sensor. The results show that both models performed very well, outperforming or achieving performance comparable to the state-of-the-art. In particular, the InSEption network showed exceptional performance, achieving a 6% increase in macro F1 score compared to the inception-only-based counterpart on the Daphnet dataset. In a newly introduced IMU dataset, InSEption scored 97.2% and 98.6% in terms of F1 and AUC, respectively. This can be attributed to the added squeeze and excitation blocks and the domain-specific oversampling methods used for training. The benefits of using the Inception mechanism for signal data and its potential for integration into wearable IoT are validated.