bluuebunny/crossref_metadata_2025 huggingface dataset:
Electronic Cigarettes, Heated Tobacco Products, and Oral Health: A Systematic Review and Meta-Analysis
Authors: Camoni Nicole , Conti Giulio , Esteves-Oliveira Marcella , Carvalho Thiago Saad , Roccuzzo Andrea , Cagetti Maria Grazia , Campus Guglielmo
Published: August 2023

Smokers employing electronic nicotine delivery systems (ENDS) and heated tobacco products (HTP) are currently the most common types of smoking patients seen in the dental practice. Both types of smoking are currently viewed as less harmful than cigarette smoking. However, many studies already indicate that they could harm oral health. This systematic review and meta-analysis aimed to collect a comprehensive overview of the actual knowledge regarding ENDS and HTP from a clinical and a laboratory perspective. Publications available through PubMed, Embase, the Web of Science, Scopus, and Google Scholar were used to summarize the effects of ENDS and HTP on oral health. Six surveys on self-perceived gum disease (T2 = 9.47 I2 = 99.32%), three cross-sectional studies reporting the BOP score (T2 = 8.68 I2 = 99.13%), and four in vitro studies on apoptosis after vaping exposure in human oral fibroblasts (T 2 = 8.10 I2 = 91.50%) were separately analyzed. The risk of bias ranged from critical to low. Both ENDS and HTP seem to have detrimental effects on periodontal and peri-implant parameters, and laboratory tests confirmed the presence of carcinogenic and inflammatory biomarkers. flavored e-liquids may also be a caries risk factor. Comprehensive smoking counseling should be carried out with all types of smoking patients, investigating the type of habit in terms of duration, nicotine percentage, and additional flavorings. Additional research is necessary to assess the long-term effects of alternative tobacco products on oral health.
Adsorption of Cadmium and Methylene Blue Using Highly Porous Carbon from Hemp Seeds
Authors: Mphuthi Betty Refilwe , Thabede Patiennce Mapule , Modise Johannes Sekomeng , Xaba Thokozani , Shooto Ntaote David
Published: August 2023

Toxins in water, such as metal ions and dyes, have become a global challenge to humanity by causing several serious illnesses. Removal of these toxins from water is needed for human health and environmental concerns. This work investigated the use of hemp seeds as an environmentally friendly adsorbent for applications in water treatment. Pristine hemp seeds (PHSs) were carbonized at 500 and 700 °C to obtain carbon-based hemp seeds (CHS-500 and CHS-700 for the removal of cadmium and methylene blue. The morphological and functional groups of the carbonized adsorbents and pristine hemp seeds were determined by SEM and FTIR. Isotherm studies showed that the Langmuir model best described the adsorption process based on homogenous surfaces. The maximum adsorption capacities were obtained with CHS-700 with a 36.88 and 52.61 mg/g uptake of cadmium and methylene blue, respectively. The effect of contact time showed that the sorption process rate was rapid initially, followed by a slower increment due to the saturation of active sites. ΔS° values were positive, demonstrating the increased randomness and degree of freedom of cadmium and methylene blue in water. The adsorption trends for cadmium and methylene blue by CHS-500 and CHS-700 increased as the temperature rose; a decrease was observed for adsorption by PHSs. This result suggests that the adsorption was endothermic for CHS-500 and CHS-700 and exothermic for PHSs. The pseudo-second-order model better described the uptake of both pollutants by the adsorbents. This research illustrates the great potential of carbon-based hemp seeds in removing cadmium and methylene blue dye from water.
Convolutional Neural Network and Language Model-Based Sequential CT Image Captioning for Intracerebral Hemorrhage
Authors: Kim Gi-Youn , Oh Byoung-Doo , Kim Chulho , Kim Yu-Seop
Published: August 2023

Intracerebral hemorrhage is a severe problem where more than one-third of patients die within a month. In diagnosing intracranial hemorrhage, neuroimaging examinations are essential. As a result, the interpretation of neuroimaging becomes a crucial process in medical procedures. However, human-based image interpretation has inherent limitations, as it can only handle a restricted range of tasks. To address this, a study on medical image captioning has been conducted, but it primarily focused on single medical images. However, actual medical images often consist of continuous sequences, such as CT scans, making it challenging to directly apply existing studies. Therefore, this paper proposes a CT image captioning model that utilizes a 3D-CNN model and distilGPT-2. In this study, four combinations of 3D-CNN models and language models were compared and analyzed for their performance. Additionally, the impact of applying penalties to the loss function and adjusting penalty values during the training process was examined. The proposed CT image captioning model demonstrated a maximum BLEU score of 0.35 on the in-house dataset, and it was observed that the text generated by the model became more similar to human interpretations in medical image reports with the application of loss function penalties.
Effect of Plant Extracts Addition on the Physico-Chemical and Sensory Properties of Biscuits
Authors: Salihu Salih , Gashi Njomza , Hasani Endrit
Published: August 2023

Biscuits are one of the most consumed bakery products that contain a high content of fat, sugar, and different additives that may cause various health problems. This has led to an increased focus on enriching bakery products with plant extracts to improve their nutritional and sensory properties. The objective of the current work was to investigate the effect of replacing wheat flour with plant extracts such as blueberry and cranberry (at concentrations of 3%, 6%, and 9%) and compare with control biscuits regarding the physico-chemical and color parameters. In addition, sensory analysis was conducted to determine the consumer acceptability of the enriched biscuits. The enrichment of biscuits with blueberry powder significantly increased the moisture content and decreased pH values (p < 0.05). Similarly, cranberry-enriched biscuits had a significantly higher moisture content, water activity, and decreased pH values compared to control samples (p < 0.05). On the other hand, enrichment of biscuits with either blueberry or cranberry powder significantly decreased lightness (L*), yellowness (b*), chroma value (C*), and h-value (h) but increased the redness values (a* value) of samples (p < 0.05). Our results showed that with increasing concentrations of plant extract addition in biscuits, the sensory attributes such as odor and taste were significantly improved. The results of the study suggest that the addition of plant extracts to biscuits improved their physico-chemical and sensory properties.
A Combinatory Framework for Link Prediction in Complex Networks
Authors: Dimitriou Paraskevas , Karyotis Vasileios
Published: August 2023

Link prediction is a very important field in network science with various emerging algorithms, the goal of which is to estimate the presence or absence of an edge in the network. Depending on the type of network, different link prediction algorithms can be applied, being less or more effective in the relevant scenarios. In this work, we develop a novel framework that attempts to compose the best features of link prediction algorithms when applied to a network, in order to have even more reliable predictions, especially in topologies emerging in Industrial Internet of Things (IIoT) environments. According to the proposed framework, we first apply appropriate link prediction algorithms that we have chosen for an analyzed network (basic algorithms). Each basic algorithm gives us a numerical estimate for each missing edge in the network. We store the results of each basic algorithm in appropriate structures. Then we provide them as input to a developed genetic algorithm. The genetic algorithm evaluates the results of the basic algorithms for each missing edge of the network. At each missing edge of the network and from generation to generation, it composes the estimates of the basic algorithms regarding each edge and produces a new optimized estimate. This optimization results in a vector of weights where each weight corresponds to the effectiveness of the prediction for each of the basic algorithms we have employed. With these weights, we build a new enhanced predictor tool, which can obtain new optimized estimates for each missing edge in the network. The enhanced predictor tool applies to each missing edge the basic algorithms, normalizes the basic algorithms’ estimates, and, using the weights of the estimates derived from the genetic algorithm, returns a new estimate of whether or not an edge will be added in the future. According to the results of our experiments on several types of networks with five well-known link prediction algorithms, we show that the new enhanced predictor tool yields in every case better predictions than each individual algorithm, therefore providing an accuracy-targeting alternative in the existing state of the art.
Exposure to Noise and Vibration of Vocational Education Training Teachers
Authors: Santos-Romero Lourdes , Redel-Macias Maria Dolores , Gonzalez-Redondo Miguel
Published: August 2023

Teachers in workshops of vocational education training (VET) schools are at risk of exposure to occupational hazards, as are the rest of the teaching staff. However, due to the characteristics of these workshops, these teachers are exposed to a greater extent to other types of risks, such as noise or vibrations. Exposure to these risks for vocational training teachers has been little studied compared to other risks, such as voice disorders. In this study, exposure to noise and vibration was evaluated for teachers in a vocational training center in Cordoba (Spain), working in body shops. The values obtained from the measurements taken for different tasks and machine tools showed that the exposure limit values specified in the corresponding regulations were reached and even exceeded. This implies that these types of risks must be taken into consideration for these types of teachers, and that measures must be taken to mitigate their effects.
Special Issue on Recent Challenges and Innovations in Long-Span Bridges
Authors: Sun Bin , Xiao Rucheng , Song Chaolin
Published: August 2023

Bridges are typical structures that provide connections between destinations and therefore achieve transportation functionality [...]
Research on Thermal and Heat Insulation Properties of Aerogel Heat-Insulating Reflective Coatings
Authors: Liu Yun-Lin , Yang Ding-Guo , Wang Dong-Hua , Liu Xuan
Published: August 2023

This study aims to investigate the heat and thermal insulation mechanisms of aerogel heat-insulating reflective coatings. Two working conditions, the hot box method and the open environment at the hot end, were simulated using a gypsum board as the substrate. We conducted thermal tests on blank panels, composite panels with aerogel heat-insulating reflective coatings, and XPS-insulated composite panels for two operating conditions. And the thermal insulation power calculation was carried out for the reflective and barrier materials. The test results show that the air temperature differences between the hot and cold ends of the blank, aerogel coating, and XPS boards under the hot box method were 28.8 °C, 38.2 °C, and 55.2 °C, respectively, and that the air temperature differences between the cold ends of the coating and XPS panels under the natural environment heating condition were 24.2 °C and 24 °C, respectively. Theoretical calculations show that the aerogel heat-insulating reflective coatings produce a net radiative cooling power of 145.9 W/m² when the surface of the specimen is at the same temperature as the ambient temperature. The heat flux powers of the aerogel coating board and XPS panel were 9.55 W/m² and 1.65 W/m² when the temperature difference between the two surfaces on both sides of the specimen was 10 °C, respectively.
A Sustainability Analysis Based on the LCA–Emergy–Carbon Emission Approach in the Building System
Authors: Zhang Junxue , Asutosh Ashish T.
Published: August 2023

Ecologically sustainable buildings and their carbon emissions are two popular ideas for building life cycle systems. It is a challenge to comprehensively assess the sustainability of building cases using two different methods. Based on over a decade of research, this paper attempts to explore the possibility of quantitatively integrating both approaches. In this study, we adopted the emergy method and carbon emission approach to assess and analyze a building system. In particular, similarities and differences have been identified through emergy and carbon emissions at each stage of the building’s whole life cycle. The results demonstrate that the building operation phase is the critical contributor (Approximately 79.6% of the total emergy and 97.9% of the entire carbon emission), which occupies the most emergy and carbon emission amounts of the whole building system. In order to improve the ecological sustainability of the building system, renewable energy subsystems are considered and explored. While the overall sustainability of the building system is enhanced, the new systems will aggrandize the carbon emissions. Therefore, the ecological sustainability of building systems and carbon emissions should be considered comprehensively, and the relationship between the two views needs to be balanced.
Handwriting-Based Text Line Segmentation from Malayalam Documents
Authors: P V Pearlsy , Sankar Deepa
Published: August 2023

Optical character recognition systems for Malayalam handwritten documents have become an open research area. A major hindrance in this research is the unavailability of a benchmark database. Therefore, a new database of 402 Malayalam handwritten document images and ground truth images of 7535 text lines is developed for the implementation of the proposed technique. This paper proposes a technique for the extraction of text lines from handwritten documents in the Malayalam language, specifically based on the handwriting of the writer. Text lines are extracted based on horizontal and vertical projection values, the size of the handwritten characters, the height of the text lines and the curved nature of the Malayalam alphabet. The proposed technique is able to overcome incorrect segmentation due to the presence of characters written with spaces above or below other characters and the overlapping of lines because of ascenders and descenders. The performance of the proposed method for text line extraction is quantitatively evaluated using the MatchScore value metric and is found to be 85.507%. The recognition accuracy, detection rate and F-measure of the proposed method are found to be 99.39%, 85.5% and 91.92%, respectively. It is experimentally verified that the proposed method outperforms some of the existing language-independent text line extraction algorithms.
The Behavior of Diurnal Temperature Range (DTR) and Annual Temperature Range (ATR) in the Urban Environment: A Case of Zagreb Grič, Croatia
Authors: Bonacci Ognjen , Ðurin Bojan
Published: August 2023

This paper analyzed the variations of two air temperature indices, diurnal temperature range (DTR) and annual temperature range (ATR), calculated based on observations at the Zagreb Grič Observatory over a period of 133 years (1887–2019). In intense climate changes strongly manifested by the increased air temperature, these two climate indices were determined to significantly impact human health and the environment. This effect is especially evident in urban areas. The Zagreb Grič Observatory is located in the center of Zagreb and has not changed its location during the observed period. It has a long homogeneous series of climatological observations, enabling a detailed study of climate variation in the city, which is strongly influenced by various urbanization processes. In 133 years, both of the analyzed indicators showed a statistically insignificant downward trend. The Rescaled Adjusted Partial Sums (RAPS) method revealed statistically significant differences in DTR’s time series between three sub-periods: 1887–1953, 1954–1989, and 1990–2019. The time series of ATR during 133 years behaved statistically differently in four sub-periods: 1887–1905; 1906–1926; 1927–1964; and 1965–2019. The analysis of monthly values of DTR showed that the DTR values are the highest in the warm part of the year, from May to August, when they are twice as high as those during the cold period from November to December. With an increase in precipitation, the DTR values decrease, while they increase as the mean annual temperature increases.
Downscaling Daily Satellite-Based Precipitation Estimates Using MODIS Cloud Optical and Microphysical Properties in Machine-Learning Models
Authors: Medrano Sergio Callaú , Satgé Frédéric , Molina-Carpio Jorge , Zolá Ramiro Pillco , Bonnet Marie-Paule
Published: August 2023

This study proposes a method for downscaling the spatial resolution of daily satellite-based precipitation estimates (SPEs) from 10 km to 1 km. The method deliberates a set of variables that have close relationships with daily precipitation events in a Random Forest (RF) regression model. The considered variables include cloud optical thickness (COT), cloud effective radius (CER) an cloud water path (CWP), derived from MODIS, along with maximum and minimum temperature (Tx, Tn), derived from CHIRTS. Additionally, topographic features derived from ALOS-DEM are also investigated to improve the downscaling procedure. The approach consists of two main steps: firstly, the RF model training at the native 10 km spatial resolution of the studied SPEs (i.e., IMERG) using rain gauge observations as targets; secondly, the application of the trained RF model at a 1 km spatial resolution to downscale IMERG from 10 km to 1 km over a one-year period. To assess the reliability of the method, the RF model outcomes were compared with the rain gauge records not considered in the RF model training. Before the downscaling process, the CC, MAE and RMSE metrics were 0.32, 1.16 mm and 6.60 mm, respectively, and improved to 0.48, 0.99 mm and 4.68 mm after the downscaling process. This corresponds to improvements of 50%, 15% and 29%, respectively. Therefore, the method not only improves the spatial resolution of IMERG, but also its accuracy.
“Computational Mathematics and Mathematical Physics”—Editorial I (2021–2023)
Authors: Matevossian Hovik A. , dell’Isola Francesco
Published: August 2023

Based on the papers published in the Special Issue of the scientific journal Axioms, here we present the Editorial Article “Computational Mathematics and Mathematical Physics”, the main topics of which include both fundamental and applied research in computational mathematics and differential equations of mathematical physics [...]
Statistical Modeling Procedures for Rapid Battery Pack Characterization
Authors: Beslow Lucas , Landore Shantanu , Park Jae Wan
Published: August 2023

As lithium-ion battery (LIB) cells degrade over time and usage, it is crucial to understand their remaining capacity, also known as State of Health (SoH), and inconsistencies between cells in a pack, also known as cell-to-cell variation (CtCV), to appropriately operate and maintain LIB packs. This study outlines efforts to model pack SoH and SoH CtCV of nickel-cobalt-aluminum (NCA) and lithium-iron-phosphate (LFP) battery packs consisting of four cells in series using pack-level voltage data. Using small training data sets and rapid testing procedures, partial least squares regression (PLS) models were built and achieved a mean absolute error of 0.38% and 1.43% pack SoH for the NCA and LFP packs, respectively. PLS models were also built that correctly categorized the packs as having low, medium, and high-ranked SoH CtCV 72.5% and 65% of the time for the NCA and LFP packs, respectively. This study further investigates the relationships between pack SoH, SoH CtCV, and the voltage response of the NCA and LFP packs. The slope of the discharge voltage response of the NCA packs was shown to have a strong correlation with pack dynamics and pack SoH, and the lowest SoH cell within the NCA packs was shown to dominate the dynamic response of the entire pack.
3D-Vision-Transformer Stacking Ensemble for Assessing Prostate Cancer Aggressiveness from T2w Images
Authors: Pachetti Eva , Colantonio Sara
Published: August 2023

Vision transformers represent the cutting-edge topic in computer vision and are usually employed on two-dimensional data following a transfer learning approach. In this work, we propose a trained-from-scratch stacking ensemble of 3D-vision transformers to assess prostate cancer aggressiveness from T2-weighted images to help radiologists diagnose this disease without performing a biopsy. We trained 18 3D-vision transformers on T2-weighted axial acquisitions and combined them into two- and three-model stacking ensembles. We defined two metrics for measuring model prediction confidence, and we trained all the ensemble combinations according to a five-fold cross-validation, evaluating their accuracy, confidence in predictions, and calibration. In addition, we optimized the 18 base ViTs and compared the best-performing base and ensemble models by re-training them on a 100-sample bootstrapped training set and evaluating each model on the hold-out test set. We compared the two distributions by calculating the median and the 95% confidence interval and performing a Wilcoxon signed-rank test. The best-performing 3D-vision-transformer stacking ensemble provided state-of-the-art results in terms of area under the receiving operating curve (0.89 [0.61–1]) and exceeded the area under the precision–recall curve of the base model of 22% (p < 0.001). However, it resulted to be less confident in classifying the positive class.
Pro-Inflammatory Biomarkers Combined with Body Composition Display a Strong Association with Knee Osteoarthritis in a Community-Based Study
Authors: Tarabeih Nader , Kalinkovich Alexander , Shalata Adel , Higla Orabi , Livshits Gregory
Published: August 2023

Knee osteoarthritis (KOA) is one of the most common progressive, age-dependent chronic degenerative joint diseases. KOA often develops as a result of a gradual articular cartilage loss caused by its wear and tear. Numerous studies suggest that the degradation of the knee joint involves inflammatory components. This process is also associated with body composition, particularly being overweight and muscle mass loss. The present study aimed to search for novel circulating KOA inflammatory biomarkers, taking into account body composition characteristics. To this aim, we recruited 98 patients diagnosed and radiologically confirmed with KOA and 519 healthy controls from the Arab community in Israel. A panel of soluble molecules, related to inflammatory, metabolic, and musculoskeletal disorders, was measured by ELISA in plasma samples, while several body composition parameters were assessed with bioimpedance analysis. Statistical analysis, including multivariable logistic regression, revealed a number of the factors significantly associated with KOA, independently of age and sex. The most significant independent associations [OR (95% CI)] were fat body mass/body weight index—1.56 (1.20–2.02), systemic immune-inflammation index—4.03 (2.23–7.27), circulating vaspin levels—1.39 (1.15–1.68), follistatin/FSTL1 ratio—1.32 (1.02–1.70), and activin A/FSTL1 ratio—1.33 (1.01–1.75). Further clinical studies are warranted to confirm the relevance of these KOA-associated biological factors. Hereafter, they could serve as reliable biomarkers for KOA in the general human population.
Potentially Inappropriate Use of Opioids in the Management of Migraine in Colombia
Authors: Machado-Duque Manuel E. , Echeverry-Gutiérrez Maria Fernanda , Gaviria-Mendoza Andrés , Valladales-Restrepo Luis F. , Machado-Alba Jorge E.
Published: August 2023

Research objective: To identify the frequency of opioid use in a group of patients diagnosed with migraine in Colombia. Methods: Study of a retrospective cohort of patients with a diagnosis of migraine and a first prescription of antimigraine drugs from emergency services and a priority outpatient clinic. Sociodemographic, clinical, and pharmacological variables were identified; a 12-month follow-up was carried out to identify the use of a new opioid. Results: A total of 6309 patients with a diagnosis of migraine were identified, with a mean age of 35.5 ± 12.3 years, of which 81.3% were women. Nonsteroidal anti-inflammatory drugs (51.1%) were the most frequently prescribed medications, followed by ergotamine + caffeine (31.3%), acetaminophen (15.05%), and acetaminophen + codeine (14.4%). At the time of the index, 1300 (20.6%) patients received some opioid. During the follow-up, a total of 1437 (22.8%) patients received a new opioid, of which 31.8% belonged to the group that received an initial opioid and 20.4% to the group that did not receive one, which was statistically significant (OR:1.81; 95%CI:1.58–2.07; p < 0.001). Conclusions: The frequent use of opioids in the management of migraines is potentially inappropriate and can lead to problems of tolerance, abuse and dependence. This combined with the low prescription of triptans, offers an opportunity for improvements in medical practice.
A New Cu/Fe Layer Double Hydroxide Nanocomposite Exerts Anticancer Effects against PC-3 Cells by Inducing Cell Cycle Arrest and Apoptosis
Authors: Zaky Mohamed Y. , Mahmoud Rehab , Farghali Ahmed A. , Abd El-Raheem Hany , Hassaballa Ahmed , Mohany Mohamed , Alkhalifah Dalal Hussien M. , Hozzein Wael N. , Mohamed Abdelrahman
Published: August 2023

Prostate cancer treatment poses significant challenges due to its varying aggressiveness, potential for metastasis, and the complexity of treatment options. Balancing the effectiveness of therapies, minimizing side effects, and personalizing treatment strategies are ongoing challenges in managing this disease. Significant advances in the use of nanotechnology for the treatment of prostate cancer with high specificity, sensitivity, and efficacy have recently been made. This study aimed to synthesize and characterize a novel Cu/Fe layer double hydroxide (LDH) nanocomposite for use as an anticancer agent to treat prostate cancer. Cu/Fe LDH nanocomposites with a molar ratio of 5:1 were developed using a simple co-precipitation approach. FT-IR, XRD, SEM, TEM, TGA, and zeta potential analyses confirmed the nanocomposite. Moreover, the MTT cell viability assay, scratch assay, and flow cytometry were utilized to examine the prospective anticancer potential of Cu/Fe LDH on a prostate cancer (PC-3) cell line. We found that Cu/Fe LDH reduced cell viability, inhibited cell migration, induced G1/S phase cell cycle arrest, and triggered apoptotic effect in prostate cancer cells. The findings also indicated that generating reactive oxygen species (ROS) formation could improve the biological activity of Cu/Fe LDH. Additionally, Cu/Fe LDH showed a good safety impact on the normal lung fibroblast cell line (WI-38). Collectively, these findings demonstrate that the Cu/Fe LDH nanocomposite exhibited significant anticancer activities against PC-3 cells and, hence, could be used as a promising strategy in prostate cancer treatment.
HSP47: A Therapeutic Target in Pulmonary Fibrosis
Authors: Sakamoto Noriho , Okuno Daisuke , Tokito Takatomo , Yura Hirokazu , Kido Takashi , Ishimoto Hiroshi , Tanaka Yoshimasa , Mukae Hiroshi
Published: August 2023

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by a progressive decline in lung function and poor prognosis. The deposition of the extracellular matrix (ECM) by myofibroblasts contributes to the stiffening of lung tissue and impaired oxygen exchange in IPF. Type I collagen is the major ECM component and predominant collagen protein deposited in chronic fibrosis, suggesting that type I collagen could be a target of drugs for fibrosis treatment. Heat shock protein 47 (HSP47), encoded by the serpin peptidase inhibitor clade H, member 1 gene, is a stress-inducible collagen-binding protein. It is an endoplasmic reticulum-resident molecular chaperone essential for the correct folding of procollagen. HSP47 expression is increased in cellular and animal models of pulmonary fibrosis and correlates with pathological manifestations in human interstitial lung diseases. Various factors affect HSP47 expression directly or indirectly in pulmonary fibrosis models. Overall, understanding the relationship between HSP47 expression and pulmonary fibrosis may contribute to the development of novel therapeutic strategies.
Acquired Hemophilia A after SARS-CoV-2 Infection: A Case Report and an Updated Systematic Review
Authors: Németh Márton , Mühl Diána , Csontos Csaba , Nagy Ágnes , Alizadeh Hussain , Szakács Zsolt
Published: August 2023

The role of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been implicated in the pathogenesis of acquired hemophilia A (AHA). The aim of this study is to report our case and to summarize clinical studies on de novo AHA after SARS-CoV-2 infection. We performed a systematic search on the association of SARS-CoV-2 with AHA in four medical databases up to 28 May 2023. Eligible studies should include de novo AHA patients who had SARS-CoV-2 infection before or concomitant with the diagnosis of AHA. Findings were synthesized narratively. In addition, we report the case of a 62-year-old female patient, who presented to our clinic with left flank pain 2 weeks after SARS-CoV-2 infection. Clinical investigations confirmed AHA and imaging studies revealed retroperitoneal bleeding. Her hemostasis was successfully secured with bypassing agents; however, despite immunosuppressive therapy, high inhibitor titer persisted. In the systematic review, we identified only 12 relevant cases with a questionable cause–effect relationship between SARS-CoV-2 infection and AHA. Based on the qualitative analysis of the relevant publications, current clinical evidence is insufficient to support a cause–effect relationship. The analysis of data from ongoing AHA registries can serve further evidence.
Is the Development of Ascites in Alcoholic Liver Patients Influenced by Specific KIR/HLA Gene Profiles?
Authors: Legaz Isabel , Morales Raquel , Bolarín José Miguel , Collados-Ros Aurelia , Pons José Antonio , Muro Manuel
Published: August 2023

Decompensated cirrhosis is the most common cause of ascites due to hemodynamic and renal alteration by continuous fluid leakage from the hepatic sinusoids and splanchnic capillaries into the interstitial space. Then, fluid leakage exceeds lymphatic return, leading to progressive fluid accumulation directly into the peritoneal cavity. Alcohol consumption is one of the main risks of developing alcoholic cirrhosis (AC), but not all AC patients develop ascites. Avoiding the development of ascites is crucial, given that it deteriorates prognosis and increases the patient mortality patient. The innate immune system plays a crucial role in cirrhosis through natural killer cells, which are abundant in the liver. The aim of this study was to analyze the KIR/HLA-C genetic profile in AC patients with and without ascites to understand this pathology and find predictive clinical susceptibility biomarkers that can help to establish risks and prevent the development of ascites in AC patients. A total of 281 AC patients with and without ascites were analyzed and compared with 319 healthy controls. Genomic DNA was extracted from peripheral blood in all groups. A PCR-SSO assay was performed for KIR/HLA genotyping analysis. A total of 16 activating and inhibitor KIR genes and their corresponding known ligands, epitopes of HLA-C, and their genotypes were analyzed. According to our analysis, C1 epitopes were statistically significantly decreased in AC patients with and without ascites. When comparing AC patients with ascites and healthy controls, a significant decrease in C1 epitope frequency was also observed. A statistically significant decrease was also found when comparing the C1C2 genotype in AC patients without ascites with controls. In conclusion, the absence of KIR2DL2 and KIR3DL1 genes may be a predisposing factor for the development of ascites in AC patients. The KIR2DS2/KIR2DL2 may could be involved in grade I ascites development, and the presence of the C1+ epitope and the homozygous C2C2 genotype may be protective genetic factors against ascites development in AC patients.
Effect of Fly Ash on Mechanical Properties of Polymer Resin Grout
Authors: Fadiel Ashraf A. M. , Mohammed Nuria S. , Rahman Ahmad Baharuddin Abdul , Ali Esam Abu Baker , Abu-Lebdeh Taher , Petrescu Florian Ion Tiberiu
Published: August 2023

High-strength grout is specified to increase the bond between grout and bar in grouted connections and to ensure that the forces in the bars can be transferred to the surrounding material accordingly. Although polymer grout is fast setting and rapid in strength development, the use of polymer mortar in grouted connections is still limited because of the lack of information and familiarity practitioners have regarding the product. The goal of this work is to investigate the mechanical characteristics and performance of polyester grout containing fly ash that can be used as an infill material for grouted connections. This study focused on the composition of polymer grout, which typically consists of a binder, hardener, and filler. In this particular case, the binder was made of unsaturated polyester resin and hardener, while the filler was fine sand. The aim of the research was to investigate the potential benefits of incorporating fly ash as an additional filler in polymer resin grout and examine the mechanical properties of polymer resin grout. To this end, varying amounts of fly ash were added to the mix, ranging from 0% to 32% of the total filler by volume, with a fixed polymer content of 40%. The performance of the resulting grout was evaluated through flowability, compression, and splitting tensile tests. The results of the experiments showed that, at a fly ash volume of 28%, the combination of fine sand and fly ash led to an improvement in grout strength; specifically, at this volume of fly ash, the compressive and tensile strengths increased by 24.7% and 124%, respectively, compared to the control mix. However, beyond a fly ash volume of 28%, the mechanical properties of the grout started to deteriorate. Due its superior properties in terms of compressive and flexural strengths over all examined mixes, the PRG-40-28 mix is ideal for use in the infill material for mechanical connections.
(R)evolution of the Standard Addition Procedure for Immunoassays
Authors: Conrad Monika , Fechner Peter , Proll Günther , Gauglitz Günter
Published: August 2023

A new method to transfer the standard addition procedure for concentration determination to immunoassays with non-linear calibration curves was developed. The new method was successfully applied to simulated data and benchmarked against a state-of-the-art algorithm, showing a significantly improved performance with improvement factors between 2 and 192. The logit function was used to transform the immunoassay signal response of test samples spiked with known analyte concentrations. The relationship between logit(signal) and log-transformed estimated total analyte concentration is linear if the estimated total analyte concentration is correct. Finally, the new method was validated experimentally using different assays in varying, relevant complex matrices, such as serum, saliva, and milk. Different concentrations of testosterone and amitriptyline between 0.05 and 3.0 µg L−1 were quantified using a binding inhibition assay in combination with reflectometric interference spectroscopy (RIfS) as the transduction principle. The sample concentration was calculated using a numerical method. Samples could be quantified with recoveries between 70 and 118%. The standard addition method accounts for individual matrix interference on the immunoassay by spiking the test sample itself. Although the experiments were carried out using RIfS, the method can be applied to any immunoassay that meets the analytical requirements.
Post-Vaccination Detection of SARS-CoV-2 Antibody Response with Magnetic Nanoparticle-Based Electrochemical Biosensor System
Authors: Harmanci Duygu , Balaban Hanoglu Simge , Akkus Kayali Gozde , Durgunlu Evrim , Ucar Nursima , Cicek Candan , Timur Suna
Published: August 2023

Here, we report magnetic nanoparticle-based biosensor platforms for the rapid detection of SARS-CoV-2 antibody responses in human serum. The use of the proposed system enabled the detection of anti-SARS-CoV-2 spike (S) and nucleocapsid (N) proteins at a concentration of ng/mL in both buffer and real serum samples. In particular, the protocol, which is considered an indicator of innate immunity after vaccination or post-infection, could be useful for the evaluation of antibody response. We included a total of 48 volunteers who either had COVID-19 but were not vaccinated or who had COVID-19 and were vaccinated with CoronoVac or Biontech. Briefly, in this study, which was planned as a cohort, serum samples were examined 3, 6, and 12 months from the time the volunteers’ showed symptoms of COVID-19 with respect to antibody response in the proposed system. Anti-S Ab and anti-N Ab were detected with a limit of detection of 0.98 and 0.89 ng/mL, respectively. These data were confirmed with the corresponding commercial an electrochemiluminescence immunoassay (ECLIA) assays. Compared with ECLIA, more stable data were obtained, especially for samples collected over 6 months. After this period, a drop in the antibody responses was observed. Our findings showed that it could be a useful platform for exploring the dynamics of the immune response, and the proposed system has translational use potential for the clinic. In conclusion, the MNP-based biosensor platform proposed in this study, together with its counterparts in previous studies, is a candidate for determining natural immunity and post-vaccination antibody response, as well as reducing the workload of medical personnel and paving the way for screening studies on vaccine efficacy.
Daring and Distress: Insights on Adolescent Risk Taking and Difficulties in Emotion Regulation from a Network Analysis Perspective
Authors: Cerniglia Luca , Cimino Silvia , Tambelli Renata , Lauriola Marco
Published: August 2023

We explored the interrelationships between risk-taking and self-harm in typically developing adolescents by examining various contributing factors, such as personality traits, difficulties in emotion regulation, attachment styles, and maladaptive psychological functioning. A sample of 234 Italian adolescents completed the Risk-Taking and Self-Harm Inventory for Adolescents (RTSHIA), the Risk-Taking Questionnaire (RT-18), the Difficulties in Emotion Regulation Strategies (DERS), the State Adult Attachment Measure (SAAM), and the Youth Self-Report (YSR). Network analysis was used to visualize and describe the interdependencies among the variables. Risk-taking behaviors were strongly linked to rule-breaking, aggression, and risk propensity, while self-harm behaviors were connected to limited access to emotion regulation strategies and thought problems. Centrality indices indicated that variables such as anxiety/depression, limited access to emotion regulation strategies, and rule-breaking had a high influence within the network. This study provided a comprehensive understanding of the nomological network of risk-taking and self-harm behaviors among adolescents. It highlighted the relative importance of factors such as emotion regulation difficulties and maladaptive psychological functioning in influencing these behaviors. The findings could inform psychological interventions and prevention strategies targeting adolescents at risk for engaging in risk-taking or self-harm behaviors.
Memory in Social Interactions: The Effects of Introspection on Destination Memory in Traumatic Brain Injury
Authors: El Haj Mohamad , Moustafa Ahmed A. , Allain Philippe
Published: August 2023

Destination memory, which is the ability to remember to whom one has sent information, is intimately associated with social cognition. We assessed whether processing attributes of destinations would improve destination memory in patients with traumatic brain injury (TBI). In this cross-sectional study, we tested the destination memory of 24 patients with TBI and 25 control participants in two conditions. On the first one (control condition), we invited participants to tell proverbs to celebrities’ faces in order to decide, on a subsequent recognition test, whether they previously told that proverb to that celebrity or not. On the second condition (experimental introspection condition), the same procedures were repeated. However, after telling the proverbs, we invited participants to introspect about what the destination might believe about the proverbs (e.g., “What do you think that the celebrities would think about the proverbs?”). Group comparisons demonstrated better destination memory after the introspection than when no introspection was implemented in control participants, but there were no significant differences between the two conditions in patients with TBI. However, analyses of individual profiles demonstrated that more than half (n = 13) of the patients with TBI demonstrated better destination memory after introspection. While these results demonstrate a beneficial effect of introspection on destination memory for some cases of patients with TBI, more research is needed to reveal how introspection may influence patients’ memory in social interactions.
Profiling Somatosensory Impairment after Stroke: Characterizing Common “Fingerprints” of Impairment Using Unsupervised Machine Learning-Based Cluster Analysis of Quantitative Measures of the Upper Limb
Authors: Senadheera Isuru , Larssen Beverley C. , Mak-Yuen Yvonne Y. K. , Steinfort Sarah , Carey Leeanne M. , Alahakoon Damminda
Published: August 2023

Altered somatosensory function is common among stroke survivors, yet is often poorly characterized. Methods of profiling somatosensation that illustrate the variability in impairment within and across different modalities remain limited. We aimed to characterize post-stroke somatosensation profiles (“fingerprints”) of the upper limb using an unsupervised machine learning cluster analysis to capture hidden relationships between measures of touch, proprioception, and haptic object recognition. Raw data were pooled from six studies where multiple quantitative measures of upper limb somatosensation were collected from stroke survivors (n = 207) using the Tactile Discrimination Test (TDT), Wrist Position Sense Test (WPST) and functional Tactile Object Recognition Test (fTORT) on the contralesional and ipsilesional upper limbs. The Growing Self Organizing Map (GSOM) unsupervised machine learning algorithm was used to generate a topology-preserving two-dimensional mapping of the pooled data and then separate it into clusters. Signature profiles of somatosensory impairment across two modalities (TDT and WPST; n = 203) and three modalities (TDT, WPST, and fTORT; n = 141) were characterized for both hands. Distinct impairment subgroups were identified. The influence of background and clinical variables was also modelled. The study provided evidence of the utility of unsupervised cluster analysis that can profile stroke survivor signatures of somatosensory impairment, which may inform improved diagnosis and characterization of impairment patterns.
The Roles of Personal and Environmental Resources in Predicting Work–Family Facilitation and Mental Health among Employed Parents of Children with Disabilities in Croatia
Authors: Šimunić Ana , Slišković Ana , Tokić Andrea , Ombla Jelena , Stewart Lisa
Published: August 2023

Quantitative research on the positive aspects of work–life integration and the well-being of families with children with disabilities is scarce, especially in the national context. The family can provide gains that enhance work domain functioning (family-to-work facilitation; FWF), and work can provide gains that enhance family domain functioning (work-to-family facilitation; WFF). The aim of this study is to examine the contributions of some personal and environmental resources in explaining WFF and FWF and the mental health of parents of children with disabilities residing in Croatia. The mediational role of WFF and FWF in the relationship between resources and mental health was tested, while controlling for some general socio-demographic variables. A total of 571 employed parents of a child/children with disabilities completed an online self-assessment questionnaire. The results show that higher WFF (19%) was predicted by higher levels of social support at work, a higher level of education, posttraumatic growth (PTG) of personal strength, and recovery management. Higher FWF (46%) was predicted by higher levels of social support in the family, PTG of personal strength, the emotional regulation strategy of reorienting to planning, optimism, a younger age, the male gender, a greater number of children, and a higher level of education. A higher level of mental health (47%) was predicted directly by higher levels of optimism, recovery management, FWF, emotional regulation strategies of positive refocusing and planning, and a greater number of children, and was indirectly predicted by all the predictors of FWF through a higher level of FWF (but not WFF).
Infra-Low-Frequency Neurofeedback Treatment in Dysthymia: A Case Study
Authors: Tschiesner Reinhard
Published: August 2023

Depression is one of the most common mental disorders worldwide. Dysthymia, a long-lasting form of depressive disorder that is also known as persistent depressive disorder (PDD) with pure dysthymic syndrome according to the Diagnostical and Statical Manual of Mental Disorders (DSM-5), is characterised by being difficult to treat. The most prominent therapeutic approaches in treating dysthymia are pharmacotherapy and psychotherapy, but recent studies also demonstrate the success of neurofeedback in treating individuals with depressive disorders. However, infra-low-frequency (ILF) neurofeedback, the main new neurofeedback protocol, lacks empirical evidence, and there is no evidence that it can treat dysthymia. This case report investigates the ILF neurofeedback method in a male patient with dysthymia. After 45 sessions of ILF neurofeedback combined with ILF synchrony, a decrease in symptom severity was found on assessment after treatment, and these results remained consistent at a low level at a 6-month follow-up. Additionally, the patient reported benefits on interpersonal and cognitive levels and in daily life situations. This study should incentivise further investigations into using ILF neurofeedback to treat dysthymia and all variations of depressive disorders.
How Do University Students Perceive Inequality, Relationships and Power in University Life in the COVID-19 Era?
Authors: Shim Taeeun , Lee Songyi , Jun Mikyung
Published: August 2023

This study examined university students’ perceptions of inequality, relationships and power following the COVID-19 outbreak. We used a qualitative research method, inductive content analysis (ICA), to analyse their perceptions of inequality in their personal life, insiders and outsiders that show superiority in relationships and people with strong and weak characteristics of power structures. We extracted superordinate concepts, such as those in the individual, interaction and social/environmental dimensions, as the perceptions of inequality, insiders and outsiders and people with strong and weak characteristics. First, we found that university students experience inequalities when they perceive that individuals must cope independently with changes brought about by COVID-19. Second, the results showed that individuals can become insiders or outsiders depending on how they act during the COVID-19 pandemic. Finally, we demonstrated that strong individuals are less affected by COVID-19-related changes than weak individuals. Therefore, improving university students’ quality of life requires plans based on the students’ perceptions of inequality.