bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Apical Periodontitis and Endodontic Treatment on Salivary Inflammatory Biomarkers: A Longitudinal Study
Authors: Bakhsh Abdulaziz , Al-Abdulla Noor , Mannocci Francesco , Allihaibi Marwa , Moyes David , Proctor Gordon , Niazi Sadia Ambreen
Published: March 2023

This study aimed to assess the effect of apical periodontitis and its treatment on the profile of salivary inflammatory markers and to investigate its correlation with serum inflammatory markers. Saliva samples were collected from 115 recruited participants. Patients were reviewed after 1 and 2 years following treatment. Saliva samples were analysed using Multiplex microbead immunoassay for identifying the inflammatory biomarkers’ profile. Biomarker levels were compared against healthy controls at baseline. Longitudinal comparison of those markers was further analysed for the review appointments and correlated with the size of the periapical radiolucency, treatment outcome and serum inflammatory biomarker levels. The salivary cytokines, matrix metalloproteinases (MMPs) and vascular adhesion molecules were higher at the review appointments. Pre-operative salivary levels of high-sensitivity C-reactive protein (hs-CRP) were significantly higher in the treatment group than in the control group (p < 0.001). At 1 year, hs-CRP was decreased than baseline. While, in 2 years, fibroblast growth factor (FGF)-23 was significantly lower compared to baseline levels (p = 0.005). Furthermore, the post-operative size of radiolucency was significantly correlated with the levels of several markers. When correlating the salivary levels of biomarkers with the serum levels, a significant correlation was seen in FGF-23 (p = 0.04) at baseline; in intercellular adhesion molecule (ICAM)-1 (p = 0.02) at 1 year post-treatment; and in TNF-α, ICAM-1 and E-Selectin at 2 years post-treatment (p = 0.046; p = 0.033; p = 0.019, respectively). Therefore, his study suggests that higher salivary cytokines, MMPs and vascular adhesion molecules at the post-treatment reviews are related to periapical bone healing and remodelling, whereas salivary FGF-23 and hs-CRP could be prognostic biomarkers. Correlation of some salivary with serum biomarkers suggests that saliva sampling could be a feasible non-invasive option for the measurement of inflammatory marker levels; however, further longitudinal studies are required.
Towards Sustainable Regional Planning: Potential of Commuter Rail in the Madrid Urban Region
Authors: Solís Eloy , Ruiz-Apilánez Borja , Moyano Amparo , Mohíno Inmaculada , Coronado José María
Published: March 2023

In the extensive framework of the historiography on the relationship between railroads and cities that began in the second half of the 19th century, a new phase of thought and action emerged from the 1980s, driven by a transport-oriented development approach and the node–place model within the paradigms of New Urbanism and sustainable urbanism, respectively. This highlights the need to integrate railway planning and urban and territorial planning to take advantage of the development potential of the urban areas surrounding railway stations. In this context, a subject rarely analyzed in Spain is the urban areas around commuter railway stations and the opportunity they represent to rethink growth and development on an urban and metropolitan scale. This study explores and shows the roles that municipalities with commuter stations and their surrounding areas play and could play as a basis for leading an urban and territorial strategy based on a polycentric model in favor of more sustainable mobility and development in the Madrid urban region.
Hybridizing Lithography-Based Ceramic Additive Manufacturing with Two-Photon-Polymerization
Authors: Sänger Johanna Christiane , Schwentenwein Martin , Bermejo Raúl , Günster Jens
Published: March 2023

Stereolithography processes such as lithography-based ceramic manufacturing (LCM) are technologies that can produce centimeter-sized structures in a reasonable time frame. However, for some parts specifications, they lack resolution. Two-photon-polymerization (2PP) ensures the highest geometric accuracy in additive manufacturing so far. Nevertheless, building up parts in sizes as large as a few millimeters or even centimeters is a time-consuming process, which makes the production of 2PP printed parts very costly. Regarding feedstock specification, the requirements for 2PP are different to those for LCM, and generally, feedstocks are designed to meet requirements for only one of these manufacturing technologies. In an attempt to fabricate highly precise ceramic components of a rather large size, it is necessary to develop a feedstock that suits both light-based technologies, taking advantage of LCM’s higher productivity and 2PP’s accuracy. Hybridization should bring the desired precision to the region of interest on reasonably large parts without escalating printing time and costs. In this study, specimens gained from a transparent feedstock with yttria stabilized zirconia (YSZ) particles of 5 nm at 70 wt% were presented. The resin was originally designed to suit 2PP, while being also printable with LCM. This work demonstrates how hybrid parts can be sintered into full YSZ ceramics.
DSC Melting Profile of Cold-Pressed Hemp Seed Oil as an Authenticity Fingerprint Influenced by Scanning Rate
Authors: Islam Mahbuba , Kaczmarek Anna , Rudzińska Magdalena , Tomaszewska-Gras Jolanta
Published: March 2023

Among the variety of edible cold-pressed oils on the market, hemp seed oil is becoming increasingly popular among scientists and consumers due to its plethora of nutritional compounds. In this study, the goal was to examine the thermal characteristics of cold-pressed hemp seed oil pressed from seeds of the Henola cultivar procured by five different suppliers in two different seasons. This aim of this research was to establish how various scanning rates can affect the unique thermal profile of cold-pressed hemp seed oil in terms of an authenticity assessment. The melting transition was manifested by curves with four peaks for all hemp seed oils; however, they differed for each scanning rate in terms of the shape and peak intensity. Comparing the curves obtained at heating rates of 1 and 2 °C/min, noticeable differences were observed in the melting transition parameters between hemp seed oils, showing that small differences in fatty acid composition can cause changes in DSC profiles. In contrast, at a scanning rate 5 °C/min, the melting curves were similar for all hemp seed oils. It was also observed that for all the scanning rates, there was a strong negative correlation between the total content of polyunsaturated fatty acids (ƩPUFAs) and the peak temperature of the three peaks (Tm2, Tm3, and Tm4). The most abundant fatty acids were PUFAs, i.e., linoleic acid (C18:2), with contents ranging from 47 to 55%; and α-linolenic acid (C 18:3 n–3), with contents ranging from 17 to 25%. The application of linear discriminant analysis (LDA) enabled a discriminant model to be built based on the DSC data obtained for differentiation of oils pressed from fresh and stored seeds.
Collagen Peptides-Minerals Complexes from the Bovine Bone by-Product to Prevent Lipids Peroxidation in Meat and Butter and to Quench Free Radicals—Influence of Proteases and of Steam Sterilisation
Authors: Aubry Laurent , Sy Khady , Sayd Thierry , Ferraro Vincenza
Published: March 2023

Food-grade animal by-products are a source of bioactive peptides that could be used as natural antioxidant compounds. Until now, only few studies have put attention to the research of the most effective enzyme(s), to the antioxidant power of collagen peptides in food matrix and to the consideration of a mineralized collagen tissue such as bone, in particular the bovine one. Hence, this study aimed to investigate the effect of enzymes of different origins (animal, plant and microbial) and the effect of processing parameters such as the enzyme-collagen ratio, the steam sterilisation, the concentration of peptides and the mixing of peptides obtained by different enzymes on their antioxidant activity. Low molecular weight peptides (<3000 Da) were produced by the hydrolysis of bovine bone collagen by bromelain, cathepsin B and collagenase B. The antioxidant activity towards lipids peroxidation in meat and butter and the quenching capacity toward free radical were assessed. The bone minerals calcium, magnesium and phosphorous were also present in solution. Peptides-minerals complexes showed a significant antioxidant activity, which depended on the enzyme and on the test used to measure the antioxidant power; collagenase B showed the highest antioxidant capacity, which was further improved by peptides mixing and concentration; sterilization had no adverse effect on the antioxidant capacity. The results of this study can corroborate that food-grade animal by-products, such as the bovine bone, could be valorised for high-value food and health application, which can contribute to a circular use of the agro-food resources.
PDF Malware Detection Based on Fuzzy Unordered Rule Induction Algorithm (FURIA)
Authors: Mejjaouli Sobhi , Guizani Sghaier
Published: March 2023

The number of cyber-attacks is increasing daily, and attackers are coming up with new ways to harm their target by disseminating viruses and other malware. With new inventions and technologies appearing daily, there is a chance that a system might be attacked and its weaknesses taken advantage of. Malware is distributed through Portable Document Format (PDF) files, among other methods. These files’ adaptability makes them a prime target for attackers who can quickly insert malware into PDF files. This study proposes a model based on the Fuzzy Unordered Rule Induction Algorithm (FURIA) to detect PDF malware. The proposed model outperforms currently used methods in terms of reducing error rates and increasing accuracy. Other models, such as Naïve Bayes (NB), Decision Tree (J48), Hoeffding Tree (HT), and Quadratic Discriminant Analysis (QDA), were compared to the proposed model. The accuracy achieved by the proposed model is 99.81%, with an error rate of 0.0022.
A Cognitive Environment Modeling Approach for Autonomous Vehicles: A Chinese Experience
Authors: Chen Ruinan , Hu Jie , Zhong Xinkai , Zhang Minchao , Zhu Linglei
Published: March 2023

Existing environment modeling approaches and trajectory planning approaches for intelligent vehicles are difficult to adapt to multiple scenarios, as scenarios are diverse and changeable, which may lead to potential risks. This work proposes a cognitive spatial–time environment modeling approach for autonomous vehicles, which models a multi-scenario-adapted spatial–time environment model from a cognitive perspective and transforms the scenario-based trajectory planning problem into a unified spatial–time planning problem. The commonality of multiple typical Chinese road scenarios is analyzed, and a unified spatial–time environment model for multi-scenario adaptation is defined and established. The adaptability and trajectory planning potential of the spatial–time environment model are analyzed, and the planning results are obtained through a hybrid A* algorithm. The simulation results show that the proposal is effective in blurring the boundary between scenarios, allowing a single planning approach to adapt to multiple scenarios and plan optimal trajectories (optimal in both path and speed domains) and introducing more flexibility to the planning.
Real-Time Target Detection System for Animals Based on Self-Attention Improvement and Feature Extraction Optimization
Authors: Zhang Mingyu , Gao Fei , Yang Wuping , Zhang Haoran
Published: March 2023

In this paper, we propose a wildlife detection algorithm based on improved YOLOv5s by combining six real wildlife images of different sizes and forms as datasets. Firstly, we use the RepVGG model to simplify the network structure that integrates the ideas of VGG and ResNet. This RepVGG introduces a structural reparameterization approach to ensure model flexibility while reducing the computational effort. This not only enhances the ability of model feature extraction but also speeds up the model computation, further improving the model’s real-time performance. Secondly, we use the sliding window method of the Swin Transformer module to divide the feature map to speed up the convergence of the model and improve the real-time performance of the model. Then, it introduces the C3TR module to segment the feature map, expand the perceptual field of the feature map, solve the problem of backpropagation gradient disappearance and gradient explosion, and enhance the feature extraction and feature fusion ability of the model. Finally, the model is improved by using SimOTA, a positive and negative sample matching strategy, by introducing the cost matrix to obtain the highest accuracy with the minimum cost. The experimental results show that the improved YOLOv5s algorithm proposed in this paper improves mAP by 3.2% and FPS by 11.9 compared with the original YOLOv5s algorithm. In addition, the detection accuracy and detection speed of the improved YOLOv5s model in this paper have obvious advantages in terms of the detection effects of other common target detection algorithms on the animal dataset in this paper, which proves that the improved effectiveness and superiority of the improved YOLOv5s target detection algorithm in animal target detection.
Machine Learning Diffuse Optical Tomography Using Extreme Gradient Boosting and Genetic Programming
Authors: Hauptman Ami , Balasubramaniam Ganesh M. , Arnon Shlomi
Published: March 2023

Diffuse optical tomography (DOT) is a non-invasive method for detecting breast cancer; however, it struggles to produce high-quality images due to the complexity of scattered light and the limitations of traditional image reconstruction algorithms. These algorithms can be affected by boundary conditions and have a low imaging accuracy, a shallow imaging depth, a long computation time, and a high signal-to-noise ratio. However, machine learning can potentially improve the performance of DOT by being better equipped to solve inverse problems, perform regression, classify medical images, and reconstruct biomedical images. In this study, we utilized a machine learning model called “XGBoost” to detect tumors in inhomogeneous breasts and applied a post-processing technique based on genetic programming to improve accuracy. The proposed algorithm was tested using simulated DOT measurements from complex inhomogeneous breasts and evaluated using the cosine similarity metrics and root mean square error loss. The results showed that the use of XGBoost and genetic programming in DOT could lead to more accurate and non-invasive detection of tumors in inhomogeneous breasts compared to traditional methods, with the reconstructed breasts having an average cosine similarity of more than 0.97 ± 0.07 and average root mean square error of around 0.1270 ± 0.0031 compared to the ground truth.
HOXA10 DNA Methylation Level in the Endometrium Women with Endometriosis: A Systematic Review
Authors: Elias Marjanu Hikmah , Lazim Nurunnajah , Sutaji Zulazmi , Abu Mohammad Azrai , Abdul Karim Abdul Kadir , Ugusman Azizah , Syafruddin Saiful Effendi , Mokhtar Mohd Helmy , Ahmad Mohd Faizal
Published: March 2023

Endometriosis is an inflammatory chronic systemic disease resulting in pelvic pain and infertility. However, despite a high prevalence of endometriosis, disease identification is still insufficient, and a high percentage of misdiagnosing was observed. Hence, a comprehensive study needs to be done to improve our understanding of the pathogenesis of endometriosis. Aberrant hypermethylation of HOXA10 has been reported to play a role in endometriosis. Thus, a comprehensive literature search was conducted to identify the DNA methylation level of HOXA10 among endometriosis patients across populations. The literature search was done using PubMed, Scopus, EBSCOhost, and Science Direct applying (HOXA10 OR “homeobox A10” OR “HOXA-10” OR HOX1) AND (“DNA methylation” OR methylation) AND (endometriosis OR endometrioma) as keywords. From 491 retrieved studies, five original articles investigating the DNA methylation level of HOXA10 from endometrium tissues among endometriosis women were included. All five included studies were classified as high-quality studies. High HOXA10 DNA methylation level was observed in the endometrium tissue of women with endometriosis in all the included studies. The secretory phase was identified as the best sampling time for HOXA10 DNA methylation study in endometriosis, and the most studied DNA methylation site is the promoter region of the HOXA10. However, more studies are needed to expose the HOXA10 mechanism in the pathogenesis of endometriosis.
Urinary ACE Phenotyping as a Research and Diagnostic Tool: Identification of Sex-Dependent ACE Immunoreactivity
Authors: Kozuch Alexander J. , Petukhov Pavel A. , Fagyas Miklos , Popova Isolda A. , Lindeblad Matthew O. , Bobkov Alexander P. , Kamalov Armais A. , Toth Attila , Dudek Steven M. , Danilov Sergei M.
Published: March 2023

Background: Angiotensin-converting enzyme (ACE) is highly expressed in renal proximal tubules, but ACE activity/levels in the urine are at least 100-fold lower than in the blood. Decreased proximal tubular ACE has been associated with renal tubular damage in both animal models and clinical studies. Because ACE is shed into urine primarily from proximal tubule epithelial cells, its urinary ACE measurement may be useful as an index of tubular damage. Objective and Methodology: We applied our novel approach—ACE phenotyping—to characterize urinary ACE in volunteer subjects. ACE phenotyping includes (1) determination of ACE activity using two substrates (ZPHL and HHL); (2) calculation of the ratio of hydrolysis of the two substrates (ZPHL/HHL ratio); (3) quantification of ACE immunoreactive protein levels; and (4) fine mapping of local ACE conformation with mAbs to ACE. Principal findings: In normal volunteers, urinary ACE activity was 140-fold less than in corresponding plasma/serum samples and did not differ between males and females. However, urinary ACE immunoreactivity (normalized binding of 25 mAbs to different epitopes) was strongly sex-dependent for the several mAbs tested, an observation likely explained by differences in tissue ACE glycosylation/sialylation between males and females. Urinary ACE phenotyping also allowed the identification of ACE outliers. In addition, daily variability of urinary ACE has potential utility as a feedback marker for dieting individuals pursuing weight loss. Conclusions/Significance: Urinary ACE phenotyping is a promising new approach with potential clinical significance to advance precision medicine screening techniques.
Calculated Whole Blood Viscosity and Albumin/Fibrinogen Ratio in Patients with a New Diagnosis of Multiple Myeloma: Relationships with Some Prognostic Predictors
Authors: Carlisi Melania , Lo Presti Rosalia , Mancuso Salvatrice , Siragusa Sergio , Caimi Gregorio
Published: March 2023

Background: In this single center study, we retrospectively evaluated the calculated hemorheological profile in patients with a new diagnosis of multiple myeloma, with the aim to evaluate possible relationships with some prognostic predictors, such as ISS, albumin levels, beta2-microglobulin, red cell distribution width, and bone marrow plasma cell infiltration. Methods: In a cohort of 190 patients, we examined the calculated blood viscosity using the de Simone formula, and the albumin/fibrinogen ratio as a surrogate of erythrocyte aggregation, and then we related these parameters to prognostic factors, using the Kruskal–Wallis and the Mann–Whitney tests, respectively. Results: From our analysis, it emerged that the evaluated hemorheological pattern differed in the three isotypes of multiple myeloma, and the whole blood viscosity was higher in IgA and IgG isotypes with respect to the light chain multiple myeloma (p < 0.001). Moreover, we observed that, as the ISS stage progressed, the albumin/fibrinogen ratio was reduced, and the same hemorheological trend was traced in subgroups with lower albumin levels, higher beta2-microglobulin and red cell distribution width RDW values, and in the presence of a greater bone marrow plasma cell infiltrate. Conclusions: Through the changes in blood viscosity in relation to different prognostic factors, this analysis might underline the role of the hemorheological pattern in multiple myeloma.
Skin Microbiota: Setting up a Protocol to Evaluate a Correlation between the Microbial Flora and Skin Parameters
Authors: Perugini Paola , Grignani Camilla , Condrò Giorgia , van der Hoeven Harald , Ratti Annamaria , Mondelli Antonella , Colpani Antonio , Bleve Mariella
Published: March 2023

The concept of skin microbiota is not really clear and more accurate approaches are necessary to explain how microbial flora can influence skin biophysical parameters in healthy individuals and in pathology patients with non-infectious skin disease. The aim of this work is to provide a suitable, fast and reproducible protocol to correlate skin parameters with the composition of skin microbiota. For this purpose, the work was split into two main phases. The first phase was focused on the selection of volunteers by the administration of a specific questionnaire. The skin microbiota was then collected from the forehead of selected volunteers as a test area and from the shoulder as control area. On the same skin area, the biophysical parameters, such as trans-epidermal water loss (TEWL), sebum level (SL), porphyrin intensity, keratin content and stratum corneum water content were taken. All parameters were taken at t0 and after 15 days without changes in the volunteers’ lifestyle. A strong correlation was found between forehead and shoulder area for porphyrin intensity, pH and TEWL parameters, and between Cutibacterium acnes and some biophysical parameters both in the forehead and the shoulder area. The procedural setup in this work represents the starting point for evaluating problematic skins and the efficacy of cosmetic products or treatment against skin dysbiosis.
Performances of Heat-Insulating Concrete Doped with Straw Fibers for Use in Tunnels
Authors: Zhang Xiao , Liu Weitao , Cao Mengting , Zhang Shuo , Hou Jiaoyun
Published: March 2023

Current research efforts aim to develop insulating building materials to cope with hot tunnels by using crop straw fibers. The amount of straw fiber incorporated included different percentages of the gelling material mass: 0% (reference specimen), 2.5%, 5%, 7.5%, and 10%. The study focused on the concrete’s compressive strength, permeability, and thermal coefficient. The thermal coefficient of dry concrete decreased with increasing fiber content. However, the porosity of concrete mixed with more straw fibers increased, thus decreasing compressive strength. Concrete with a fiber content of 7.5% had the best overall performance, and it had a low thermal conductivity (0.158 W/(m·k)). According to COMSOL simulation results, the tunnel wind flow temperature of concrete with 7.5% fiber content was lower than the tunnel wind flow temperature of plain concrete. Thus, the obtained straw fiber heat-insulating concrete is a promising candidate material for tunnel insulation.
Rational Design of a Biocatalyst Based on Immobilized CALB onto Nanostructured SiO2
Authors: Llerena Suster Carlos R. , Toledo María V. , Matkovic Silvana R. , Morcelle Susana R. , Briand Laura E.
Published: March 2023

The adsorption of the lipase B from Candida antarctica (CALB) over nanostructured SiO2 (Ns SiO2 from now on) with and without the addition of polyols (sorbitol and glycerol) was investigated. The isotherms of adsorption made it possible to establish that the maximum dispersion limit was 0.029 µmol of protein per surface area unit of Ns SiO2 (29.4 mg per 100 mg of support), which was reached in 30 min of exposure. The studies through SDS-PAGE of the immobilization solutions and infrared spectroscopy of the prepared solids determined that CALB (from a commercial extract) is selectively adsorbed, and its secondary structure distribution is thus modified. Its biocatalytic activity was corroborated through the kinetic resolution of rac-ibuprofen. Conversions of up to 70% and 52% enantiomeric excess toward S-ibuprofen in 24 h of reaction at 45 °C were achieved. The biocatalytic performance increased with the increase in protein loading until it leveled off at 0.021 µmol.m−2, reaching 0.6 µmol.min−1. The biocatalyst containing the lipase at the maximum dispersion limit and co-adsorbed polyols presented the best catalytic performance in the kinetic resolution of rac-ibuprofen, an improved thermal resistance (up to 70 °C), and stability under long-term storage (more than 2 years).
Microbial Biocatalysis
Authors: Pan Tao , Wang Zhilong
Published: March 2023

Biocatalysis, which can be performed by whole cells and isolated enzymes, has become a topic of public interest for its potential use in the chemical industry in manufacturing, monitoring, and waste management [...]
Impact of Translocator Protein 18 kDa (TSPO) Deficiency on Mitochondrial Function and the Inflammatory State of Human C20 Microglia Cells
Authors: Bader Stefanie , Würfel Thea , Jahner Tatjana , Nothdurfter Caroline , Rupprecht Rainer , Milenkovic Vladimir M. , Wetzel Christian H.
Published: March 2023

Microglia are the resident immune cells of the central nervous system. Upon stimulus presentation, microglia polarize from a resting to an activated state. Microglial translocator protein 18 kDa (TSPO) is considered a marker of inflammation. Here, we characterized the role of TSPO by investigating the impact of TSPO deficiency on human microglia. We used TSPO knockout (TSPO−/−) variants of the human C20 microglia cell line. We found a significant reduction in the TSPO-associated protein VDAC1 in TSPO−/− cells compared to control cells. Moreover, we assessed the impact of TSPO deficiency on calcium levels and the mitochondrial membrane potential. Cytosolic and mitochondrial calcium concentrations were increased in TSPO−/− cell lines, whereas the mitochondrial membrane potential tended to be lower. Assessment of the mitochondrial DNA copy number via RT-PCR revealed a decreased amount of mtDNA in the TSPO−/− cells when compared to controls. Moreover, the metabolic profiles of C20 cells were strongly dependent on the glycolytic pathway. However, TSPO depletion did not affect the cellular metabolic profile. Measurement of the mRNA expression levels of the pro-inflammatory mediators revealed an attenuated response to pro-inflammatory stimuli in TSPO-depleted cells, implying a role for the TSPO protein in the process of microglial polarization.
Cesium Heteropolyacid Salts: Synthesis, Characterization and Activity of the Solid and Versatile Heterogeneous Catalysts
Authors: da Silva Marcio Jose , Rodrigues Alana Alves , Lopes Neide Paloma Gonçalves
Published: March 2023

Keggin-type heteropolyacid cesium salts have been regarded as potential candidates for heterogeneous catalytic reactions. This review describes the success of Keggin-type heteropolyacids cesium salts (Cs-HPA salts) as efficient catalysts in various synthesis processes. The Cs-HPA catalysts can be synthesized as solid salts through the metathesis of a solution containing precursor HPA and another solution containing soluble Cs salt, which will give Cs-HPA salt as a solid precipitate. Alternatively, they can be also obtained from the commercial precursor HPA. In this review, all the routes to prepare the different cesium salts (i.e., saturated, lacunar, metal-doped) were described. These salts can be used in acid-catalyzed reactions (i.e., esterification, etherification, acetalization, dehydration) or oxidative transformations (oxidative esterification, oxidation, epoxidation). All of these reactions were addressed herein. Aspects related to the synthesis and characterization of these catalyst salts were discussed. This review aims to discuss the most pertinent heterogeneous catalytic systems based on Keggin HPA Cs salts. The focus was to correlate the physicochemical properties of these salts with their catalytic activity. Ultimately, the most recent advances achieved in the applications of these Cs-HPA salts as catalysts in the synthesis of industrial interest compounds were discussed. Cesium heteropoly salts are an alternative to the traditional soluble mineral acids as well as to solid-supported catalysts.
Facile Electrochemical Approach Based on Hydrogen-Bonded MOFs-Derived Tungsten Ethoxide/Polypyrrole-Reduced GO Nanocrystal for ppb Level Ammonium Ions Detection
Authors: Mohd Hizam Sara Maira , Mohamed Saheed Mohamed Shuaib
Published: March 2023

Ammonium (NH4+) ions are a primary contaminant in the river and along the waterside near an agricultural area, therefore, necessitating sensitive detection of pollutants before irreversibly damaging environment. Herein, a new approach of metal-organic framework-derived tungsten ethoxide/polypyrrole-reduced graphene oxide (MOFs-W(OCH2CH3)6/Ppy-rGO) electrochemical sensors are introduced. Through a simple hydrothermal process, Ppy-rGO is linked to tungsten ethoxide as an organic linker. This creates the MOFs-W(OCH2CH3)6/Ppy-rGO nanocrystal through hydrogen bonding. The synergistic combination of tungsten ethoxide and Ppy-rGO provides three-fold advantages: stabilization of Ppy-rGO for extended usage, enabling detection of analytes at ambient temperature, and availability of multiple pathways for effective detection of analytes. This is demonstrated through excellent detection of NH4+ ions over a dynamic concentration range of 0.85 to 3.35 µM with a ppb level detection limit of 0.278 µM (9.74 ppb) and a quantitation limit of 0.843 µM (29.54 ppb). The increment in the concentration of NH4+ ions contributes to the increment in proton (H+) concentration. The increment in proton concentration in the solution will increase the bonding activity and thus increase the conductivity. The cyclic voltammetry curves of all concentrations of NH4+ analytes at the operating potential window between −1.5 and 1.5 V exhibit a quasi-rectangular shape, indicating consistent electronic and ionic transport. The distinctive resistance changes of the MOFs-W(OCH2CH3)6/Ppy-rGO to various NH4+ ion concentrations and ultrasensitive detection provide an extraordinary platform for its application in the agriculture industry.
Multiple Sulfatase Deficiency from an Ophthalmologist’s Perspective—Case Report and Literature Review
Authors: Schittkowski Michael P. , Naxer Sabine , Elabbasy Mohamed , Herholz Leonie , Breitling Vivian , Finglas Alan , Gärtner Jutta , Schlotawa Lars
Published: March 2023

Multiple sulfatase deficiency (MSD) is an extremely rare autosomal recessively inherited disease with a prevalence of 1:500.000 caused by mutations on the sulfatase-modifying-Factor 1 gene (SUMF1). MSD is most specifically characterised by a combination of developmentally retarded psychomotoric functions, neurodegeneration that entails the loss of many already acquired abilities, and by ichthyosis. Other symptoms include those associated with mucopolysaccharidosis, i.e., facial dysmorphy, dwarfism, and hepatosplenomegaly. In 50–75% of all MSD-affected patients, functional or structural ocular damage is likely. MSD seldom affects the anterior segment of the eye. The main pathology these patients present is a highly conspicuous tapetoretinal degeneration, similar to severe Retinitis pigmentosa, that leads to blindness at an early age. An initially five-year-old boy with MSD, genetically verified at his first examination in our opthalmology department (SUMF1 mutations c.776A>T, p.Asn259Ile; c.797A>T, p.Pro266Leu; c.836A>T, p.Ala279Val), and a 4, 5 year regular follow-up are described. The patient had some visual potential (“tunnel view”), which deteriorated dramatically after his fifth birthday. We observed no evidence of worsening retinal involvement in this patient in spite of his progressively worsening clinical symptoms, extending to total blindness/no light perception. OCT revealed that the outer retinal layers containing photoreceptors were diseased; the ellipsoid zone was only partially discernible and the outer nuclear layer appeared to be thinned out. The inner nuclear layer, ganglion cell layer, and retinal nerve fibre layer were indistinguishable. These anomalies are indicative of a severe pathology within the retina’s inner layers. Characteristic anomalies in the fundus should stimulate clinicians to suspect a case of MSD in their differential diagnosis, and thus to order thorough genetic and paediatric diagnostics.
Does Problematic Use of Social Network Mediate the Association between Bullying Victimization and Loneliness among Lebanese Adolescents?
Authors: Eid Elia , Fekih-Romdhane Feten , Sarray El Dine Abir , Malaeb Diana , Hallit Souheil , Obeid Sahar
Published: March 2023

(1) Background: Bullying victimization has been associated with several behavioral outcomes, particularly loneliness. Similarly, an increase in social network use has been identified in recent years, particularly during the COVID-19 pandemic, and has been shown to be associated with bullying and loneliness. Investigating the mediating factors of loneliness among bullied adolescents is useful for taking preventive measures in the Lebanese population. This study aims to examine the association between bullying victimization and loneliness among Lebanese adolescents while considering the indirect effect of problematic social network use. (2) Methods: We carried out a cross-sectional study, between January and April 2022, that enrolled 379 adolescent Lebanese students (64.9% females, mean age 16.07 ± 1.19 years) who were current residents of Lebanon (15 to 18 years), and were from the five governorates of Lebanon (Beirut, Mount Lebanon, North, South and Bekaa). The snowball method was applied to select our sample; an electronic copy of the questionnaire was created using the Google Forms software and an online strategy was designed to collect the data. (3) Results: Negative social comparison and addictive consequences of problematic use of social network mediated the association between bullying victimization and loneliness. Higher bullying victimization was significantly associated with higher negative social comparison and addictive consequences of problematic use of social network, which in turn were significantly associated with more loneliness. Finally, higher bullying victimization was directly significantly associated with more loneliness. (4) Conclusions: Studying the mediating factors of loneliness in bullied adolescents can improve our understanding of this topic, allowing us to propose new interventions to prevent psychological problems in adolescents. Future studies are needed to further clarify the physiological processes that underlie the associations between social triggers and loneliness during adolescence.
The Effect of a Diet Enriched with Jerusalem artichoke, Inulin, and Fluoxetine on Cognitive Functions, Neurogenesis, and the Composition of the Intestinal Microbiota in Mice
Authors: Szewczyk Aleksandra , Andres-Mach Marta , Zagaja Mirosław , Kaczmarczyk-Ziemba Agnieszka , Maj Maciej , Szala-Rycaj Joanna
Published: March 2023

The aim of the study was to assess the effect of long-term administration of natural prebiotics: Jerusalem artichoke (topinambur, TPB) and inulin (INU) as well as one of the most popular antidepressants, fluoxetine (FLU), on the proliferation of neural stem cells, learning and memory functions, and the composition of the intestinal microbiota in mice. Cognitive functions were assessed using the Morris Water Maze (MWM)Test. Cells were counted using a confocal microscope and ImageJ software. We performed 16S rRNA sequencing to assess changes in the gut microbiome of the mice. The obtained results showed that the 10-week supplementation with TPB (250 mg/kg) and INU (66 mg/kg) stimulates the growth of probiotic bacteria, does not affect the learning and memory process, and does not disturb the proliferation of neural stem cells in the tested animals. Based on this data, we can assume that both TPB and INU seem to be safe for the proper course of neurogenesis. However, 2-week administration of FLU confirmed an inhibitory impact on Lactobacillus growth and negatively affected behavioral function and neurogenesis in healthy animals. The above studies suggest that the natural prebiotics TPB and INU, as natural supplements, may have the potential to enrich the diversity of intestinal microbiota, which may be beneficial for the BGM axis, cognitive functions, and neurogenesis.
Simulation and Experimental Analysis of Microalgae and Membrane Surface Interaction
Authors: Khosravizadeh Negar , Lu Duowei , Liao Yichen , Liao Baoqiang , Fatehi Pedram
Published: March 2023

The microalgae-induced membrane system applied in wastewater treatment has attracted attention due to microalgae’s outstanding nutrient fixation capacity and biomass harvesting. However, the fundamental understanding of the interaction of microalgae and membrane surfaces is still limited. This study presents experimental and numerical methods to analyze the attachment of microalgae to the membrane. An atomic force microscope (AFM) analysis confirmed that a polydimethylsiloxane (PDMS) sensor, as a simulated membrane surface, exhibited a rougher surface morphology than a polyurethane (PU) sensor did. The contact angle and adsorption analysis using a quartz crystal microbalance confirmed that the PDMS surface, representing the membrane surface, provided a better attachment affinity than the PU surface for microalgae because of the lower surface tension and stronger hydrophobicity of PDMS. The simulation studies of this work involved the construction of roughly circular-shaped particles to represent microalgae, rough flat surfaces to represent membrane surfaces, and the interaction energy between particles and surfaces based on XDLVO theory. The modeling results of the microalgae adsorption trend are consistent and verified with the experimental results. It was observed that the interfacial energy increased with increasing the size of particles and asperity width of the membrane surface. Contrarily, the predicted interaction energy dropped with elevating the number of asperities and asperity height of the microalgae and membrane. The most influential parameter for controlling interfacial interaction between the simulated microalgae and membrane surface was the asperity height of the membrane; changing the height from 50 nm to 250 nm led to alteration in the primary minimum from −18 kT to −3 kT. Overall, this study predicted that the microalgae attachment depends on the size of the asperities to a great extent and on the number of asperities to a lesser extent. These results provide an insight into the interaction of microalgae and membrane surface, which would provide information on how the performance of microalgae-based membrane systems can be improved.
An Energy-Saving Road-Lighting Control System Based on Improved YOLOv5s
Authors: Tang Ren , Zhang Chaoyang , Tang Kai , He Xiaoyang , He Qipeng
Published: March 2023

Road lighting is one of the largest consumers of electric energy in cities. Research into energy-saving street lighting is of great significance to city sustainable development and economies, especially given that many countries are now in a period of energy shortage. The control system is critical for energy-saving street lighting, due to its capability to directly change output power. Here, we propose a control system with high intelligence and efficiency, by incorporating improved YOLOv5s with terminal embedded devices and designing a new dimming method. The improved YOLOv5s has more balanced performance in both detection accuracy and detection speed compared to other state-of-the-art detection models, and achieved the highest cognition recall of 67.94%, precision of 81.28%, 74.53%AP50, and frames per second (FPS) of 59 in the DAIR-V2X dataset. The proposed method achieves highly complete and intelligent dimming control based on the prediction labels of the improved YOLOv5s, and a high energy-saving efficiency was achieved during a two week-long lighting experiment. Furthermore, this system can also contribute to the construction of the Internet of Things, smart cities, and urban security. The proposed control system here offered a novel, high-performance, adaptable, and economical solution to road lighting.
A Temporal Transformer-Based Fusion Framework for Morphological Arrhythmia Classification
Authors: Anjum Nafisa , Sathi Khaleda Akhter , Hossain Md. Azad , Dewan M. Ali Akber
Published: March 2023

By using computer-aided arrhythmia diagnosis tools, electrocardiogram (ECG) signal plays a vital role in lowering the fatality rate associated with cardiovascular diseases (CVDs) and providing information about the patient’s cardiac health to the specialist. Current advancements in deep-learning-based multivariate time series data analysis, such as ECG data classification include LSTM, Bi-LSTM, CNN, with Bi-LSTM, and other sequential networks. However, these networks often struggle to accurately determine the long-range dependencies among data instances, which can result in problems such as vanishing or exploding gradients for longer data sequences. To address these shortcomings of sequential models, a hybrid arrhythmia classification system using recurrence along with a self-attention mechanism is developed. This system utilizes convolutional layers as a part of representation learning, designed to capture the salient features of raw ECG data. Then, the latent embedded layer is fed to a self-attention-assisted transformer encoder model. Because the ECG data are highly influenced by absolute order, position, and proximity of time steps due to interdependent relationships among immediate neighbors, a component of recurrence using Bi-LSTM is added to the encoder model to address this characteristic of the data. The model performance indices such as classification accuracy and F1-score were found to be 99.2%. This indicates that the combination of recurrence along with self-attention-assisted architecture produces improved classification of arrhythmia from raw ECG signal when compared with the state-of-the-art models.
Use of Formalin-Preserved Collections to Infer Trophic Indicators of Marine Zooplankton from Stable Isotopes
Authors: Bode Antonio , Otero Jaime , Lamas Ángel F. , Mompeán Carmen
Published: March 2023

Formalin preservation affects the stable isotope composition of zooplankton samples, thus limiting the analysis of valuable collections covering large time intervals. Here, we compare different procedures for correcting the bias caused by formalin in δ13C and δ15N of zooplankton community samples. Zooplankton samples representative of seasonal variations in the period 2000–2009 were collected off A Coruña (NW Spain). Part of the sample was immediately dried and analysed for δ13C, δ15N, and elemental composition within 3 years of collection. These values were used as the unpreserved reference. The remaining sample was preserved in 4% formaldehyde and aliquots obtained after a period ranging from 3 years to more than 10 years of storage were analysed as the originally dried samples. Additionally, the copepod fraction of total biomass was determined in the preserved samples. Corrections of formalin effects based on ordinary least squares regression had large uncertainties, while mass balance corrections based on the change in C:N ratio (only possible for δ13C) overestimated reference values. However, either simple corrections based on the mean difference between values in dry and preserved samples or more complex generalised additive models considering seasonality, copepod biomass, and time of sample storage, produced estimations with relatively low uncertainty. Our results highlight the importance of determining specific correction solutions for each preserved collection before reconstructing stable isotope time series. Furthermore, the uncertainties associated with the estimates can be used in sensitivity analysis to assess their potential impact on the interpretation of the series.
The Investigation of Health-Related Topics on TikTok: A Descriptive Study Protocol
Authors: Mandzufas Joelie , Ayalde Jeremiah , Ta Daniel , Munro Emily , Paciente Rigel , Pranoto Emmanuel Philip , King Kaelyn , How Kelly , Sincovich Alanna , Brushe Mary , Wickens Nicole , Wells Gabriella , Woolard Alix , Edmunds Melinda , Thomas Hannah , Trapp Gina S. A. , Lombardi Karen
Published: March 2023

The social media application TikTok allows users to view and upload short-form videos. Recent evidence suggests it has significant potential for both industry and health promoters to influence public health behaviours. This protocol describes a standardised, replicable process for investigations that can be tailored to various areas of research interest, allowing comparison of content and features across public health topics. The first 50 appearing videos in each of five relevant hashtags are sampled for analysis. Utilising a codebook with detailed definitions, engagement metadata and content variables applicable to any content area is captured, including an assessment of the video’s overall sentiment (positive, negative, neutral). Additional specific coding variables can be developed to provide targeted information about videos posted within selected hashtags. A descriptive, cross-sectional content analysis is applied to the generic and specific data collected for a research topic area. This flexible protocol can be replicated for any health-related topic and may have a wider application on other platforms or to assess changes in content and sentiment over time. This protocol was developed by a collaborative team of child health and development researchers for application to a series of topics. Findings will be used to inform health promotion messaging and counter-advertising.
Homogeneity Test of the First-Order Agreement Coefficient in a Stratified Design
Authors: Xu Mingrui , Li Zhiming , Mou Keyi , Shuaib Kalakani Mohammad
Published: March 2023

Gwet’s first-order agreement coefficient (AC1) is widely used to assess the agreement between raters. This paper proposes several asymptotic statistics for a homogeneity test of stratified AC1 in large sample sizes. These statistics may have unsatisfactory performance, especially for small samples and a high value of AC1. Furthermore, we propose three exact methods for small pieces. A likelihood ratio statistic is recommended in large sample sizes based on the numerical results. The exact E approaches under likelihood ratio and score statistics are more robust in the case of small sample scenarios. Moreover, the exact E method is effective to a high value of AC1. We apply two real examples to illustrate the proposed methods.
Quantum Computing Approaches for Vector Quantization—Current Perspectives and Developments
Authors: Engelsberger Alexander , Villmann Thomas
Published: March 2023

In the field of machine learning, vector quantization is a category of low-complexity approaches that are nonetheless powerful for data representation and clustering or classification tasks. Vector quantization is based on the idea of representing a data or a class distribution using a small set of prototypes, and hence, it belongs to interpretable models in machine learning. Further, the low complexity of vector quantizers makes them interesting for the application of quantum concepts for their implementation. This is especially true for current and upcoming generations of quantum devices, which only allow the execution of simple and restricted algorithms. Motivated by different adaptation and optimization paradigms for vector quantizers, we provide an overview of respective existing quantum algorithms and routines to realize vector quantization concepts, maybe only partially, on quantum devices. Thus, the reader can infer the current state-of-the-art when considering quantum computing approaches for vector quantization.