bluuebunny/crossref_metadata_2025 huggingface dataset:
Genotype and Phenotype Influence the Personal Response to Prostaglandin Analogues and Beta-Blockers in Spanish Glaucoma and Ocular Hypertension Patients
Authors: Opazo-Toro Valeria , Fortuna Virginia , Jiménez Wladimiro , Pazos López Marta , Royo María Jesús Muniesa , Ventura-Abreu Néstor , Brunet Mercè , Milla Elena
Published: January 2023

Analysis of the genotype that predicts the phenotypic characteristics of a cohort of glaucoma and ocular hypertension patients, and the correlation with their personal pharmacological response to beta-blockers (BB) and prostaglandin analogues (PGA). Prospective study that included 139 eyes from 72 patients under BB and/or PGA treatment, and in some cases other types of ocular hypotensive treatments. Five single-nucleotide polymorphisms were genotyped by real-time PCR assays: prostaglandin-F2α receptor (rs3766355, rs3753380); cytochrome-P450 2D6 (rs16947, rs769258); and beta-2-adrenergic receptor (rs1042714). Other studied variables were mean deviation (MD) of visual field, previous ocular interventions, medical treatment, baseline (bIOP), and treated intraocular pressure (tIOP). From a total of 139 eyes, 71 (51.1%) were left eyes. The main diagnosis was primary open angle glaucoma (66.2%). A total of 57 (41%) eyes were under three or more medications (PGA + BB + other) and, additionally, 57 eyes (41%) had had some kind of glaucoma surgery. The mean bIOP and tIOP were 26.55 ± 8.19 and 21.01 ± 5.54 mmHg, respectively. Significant differences in tIOP were found between heterozygous (HT) (21.07 ± 0.607 mmHg) and homozygous (HM) (20.98 ± 0.639 mmHg) rs3766355 with respect to wildtype individuals (16 ± 1.08 mmHg) (p = 0.031). The MD values presented significant differences between wildtype rs3766355 (−2 ± 2.2 dB), HT (−3.87 ± 4 dB), and HM carriers (−9.37 ± 9.51 dB) (p = 0.009). Significant differences were also observed between the MD in wildtype rs3753380 (−6.1 ± 8.67 dB), HT (−9.02 ± 8.63 dB), and HM carriers (−9.51 ± 7.44 dB) (p = 0.017). Patients carrying the variant rs3766355 in HM or HT presented clinically-significantly higher tIOP than wildtype patients. Additionally, some differences in MD were found in rs3766355 and rs3753380 carriers, and the more alleles that were affected, the worse the MD value, meaning greater severity of the glaucoma. Poor response to treatment and more visual field damage may be associated with being a carrier of these mutated alleles.
Moringa oleifera: An Updated Comprehensive Review of Its Pharmacological Activities, Ethnomedicinal, Phytopharmaceutical Formulation, Clinical, Phytochemical, and Toxicological Aspects
Authors: Pareek Ashutosh , Pant Malvika , Gupta Madan Mohan , Kashania Pushpa , Ratan Yashumati , Jain Vivek , Pareek Aaushi , Chuturgoon Anil A.
Published: January 2023

Moringa oleifera, also known as the “tree of life” or “miracle tree,” is classified as an important herbal plant due to its immense medicinal and non-medicinal benefits. Traditionally, the plant is used to cure wounds, pain, ulcers, liver disease, heart disease, cancer, and inflammation. This review aims to compile an analysis of worldwide research, pharmacological activities, phytochemical, toxicological, and ethnomedicinal updates of Moringa oleifera and also provide insight into its commercial and phytopharmaceutical applications with a motive to help further research. The scientific information on this plant was obtained from various sites and search engines such as Scopus, Pub Med, Science Direct, BMC, Google Scholar, and other scientific databases. Articles available in the English language have only been referred for review. The pharmacological studies confirm the hepatoprotective, cardioprotective, and anti-inflammatory potential of the extracts from the various plant parts. It was found that bioactive constituents are present in every part of the plant. So far, more than one hundred compounds from different parts of Moringa oleifera have been characterized, including alkaloids, flavonoids, anthraquinones, vitamins, glycosides, and terpenes. In addition, novel isolates such as muramoside A&B and niazimin A&B have been identified in the plant and have potent antioxidant, anticancer, antihypertensive, hepatoprotective, and nutritional effects. The traditional and nontraditional use of Moringa, its pharmacological effects and their phytopharmaceutical formulations, clinical studies, toxicity profile, and various other uses are recognized in the present review. However, several traditional uses have yet to be scientifically explored. Therefore, further studies are proposed to explore the mechanistic approach of the plant to identify and isolate active or synergistic compounds behind its therapeutic potential.
The Role of Organic Cation Transporters in the Pharmacokinetics, Pharmacodynamics and Drug–Drug Interactions of Tyrosine Kinase Inhibitors
Authors: Xiu Fangrui , Rausch Magdalena , Gai Zhibo , Su Shanshan , Wang Shijun , Visentin Michele
Published: January 2023

Tyrosine kinase inhibitors (TKIs) decisively contributed in revolutionizing the therapeutic approach to cancer, offering non-invasive, tolerable therapies for a better quality of life. Nonetheless, degree and duration of the response to TKI therapy vary depending on cancer molecular features, the ability of developing resistance to the drug, on pharmacokinetic alterations caused by germline variants and unwanted drug–drug interactions at the level of membrane transporters and metabolizing enzymes. A great deal of approved TKIs are inhibitors of the organic cation transporters (OCTs). A handful are also substrates of them. These transporters are polyspecific and highly expressed in normal epithelia, particularly the intestine, liver and kidney, and are, hence, arguably relevant sites of TKI interactions with other OCT substrates. Moreover, OCTs are often repressed in cancer cells and might contribute to the resistance of cancer cells to TKIs. This article reviews the OCT interactions with approved and in-development TKIs reported in vitro and in vivo and critically discusses the potential clinical ramifications thereof.
Acknowledgment to the Reviewers of IJTPP in 2022
Authors:   IJTPP Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Targeted Atrial Fibrillation Therapy and Risk Stratification Using Atrial Alternans
Authors: Muthavarapu Neha , Mohan Anmol , Manga Sharanya , Sharma Palak , Bhanushali Aditi Kishor , Yadav Ashima , Damani Devanshi Narendra , Jais Pierre , Walton Richard D. , Arunachalam Shivaram P. , Kulkarni Kanchan
Published: January 2023

Atrial fibrillation (AF) is the most persistent arrhythmia today, with its prevalence increasing exponentially with the rising age of the population. Particularly at elevated heart rates, a functional abnormality known as cardiac alternans can occur prior to the onset of lethal arrhythmias. Cardiac alternans are a beat-to-beat oscillation of electrical activity and the force of cardiac muscle contraction. Extensive evidence has demonstrated that microvolt T-wave alternans can predict ventricular fibrillation vulnerability and the risk of sudden cardiac death. The majority of our knowledge of the mechanisms of alternans stems from studies of ventricular electrophysiology, although recent studies offer promising evidence of the potential of atrial alternans in predicting the risk of AF. Exciting preclinical and clinical studies have demonstrated a link between atrial alternans and the onset of atrial tachyarrhythmias. Here, we provide a comprehensive review of the clinical utility of atrial alternans in identifying the risk and guiding treatment of AF.
Acknowledgment to the Reviewers of Journal of Imaging in 2022
Authors:   Journal of Imaging Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Questionnaire-Based Analysis of Adverse Events and Compliance with Malaria Chemoprophylaxis in Taiwan
Authors: Lin Ching-Yun , Chang Ko , Chang Chai-Jan
Published: January 2023

Malaria was eradicated in Taiwan in 1952; however, imported malaria cases are reported every year. The subtropical climate in Taiwan permits mosquito propagation and possible outbreaks of mosquito-borne diseases. The aim of this study was to investigate travelers’ compliance and side effects of malaria prophylaxis to prevent a malaria outbreak in Taiwan. In this prospective study, we enrolled travelers who visited our travel clinic before going to malarious areas. A total of 161 questionnaires were collected and analyzed. Associations between the occurrence of side effects and compliance with antimalarial drugs were analyzed. Adjusted odds ratios were calculated after adjusting for potential risk factors in multiple logistic regression analysis. Of the 161 enrolled travelers, 58 (36.0%) reported side effects. Insomnia, somnolence, irritability, nausea, and anorexia were associated with poor compliance. Mefloquine was not associated with more neuropsychological side effects than doxycycline. Multiple logistic regression analysis showed that chemoprophylaxis compliance was affected by a younger age, visiting friends and relatives, visiting the travel clinic more than 1 week before the trip, and preferring to use the same antimalarial regimen on the next trip. Our findings could provide information to travelers besides labeled side effects to improve compliance with malaria prophylaxis and consequently help to prevent malaria outbreaks in Taiwan.
Fractal Organization of Chilean Cities: Observations from a Developing Country
Authors: Martínez Francisco , Sepúlveda Bastian , Manríquez Hermann
Published: January 2023

Urban forms are human-made systems that display a close connection with fractal objects, following organisation patterns that are not as random as believed. In this context, fractal theory can be seriously considered as a powerful tool for characterizing land-use planning. By applying the box-counting method and image-processing methods, the morphology and fractal metrics of urban networks of Chilean cities were measured. This dimension shows a close correlation with area, population and gross domestic product of each entity, revealing significant asymmetries regarding their distribution throughout the country. Such asymmetries have influenced the current shape of cities, issues concerning economic and social inequalities of urban development that still remain in the territory and explained by social segregation process and the historical evolution of cities. Additionally, some interesting allometric scaling laws obtained from these urban forms are also reported. Our results suggest that the use of fractal metrics can be a meaningful and cheap tool for characterizing the complexity of urban networks, providing useful and quick information about the organisation and efficiency of urban planning in developing countries.
Highly Washable and Conductive Cotton E-textiles Based on Electrochemically Exfoliated Graphene
Authors: Evseev Zakhar Ivanovich , Vasileva Fedora Dmitrievna , Smagulova Svetlana Afanasyevna , Dmitriev Petr Stanislavovich
Published: January 2023

In this study, cotton e-textiles were obtained using two types of graphene oxide. The first type of graphene oxide was synthesized using the Hummers’ method. The second type was obtained by the electrochemical exfoliation of graphite in an ammonium salt solution. It was shown that e-textiles based on electrochemically exfoliated graphene have a higher electrical conductivity (2 kΩ/sq) than e-textiles based on graphene oxide obtained by the Hummers’ method (585 kΩ/sq). In addition, textiles based on electrochemically exfoliated graphene exhibit better washing and mechanical stress stability. The electrical resistance of the e-textiles increased only 1.86 times after 10 cycles of washing, compared with 48 times for the Hummers’ method graphene oxide textiles. The X-ray photoelectron spectra of the two types of graphene oxides showed similarity in their functional compositions after reduction. Studies of individual graphene flakes by atomic force microscopy showed that graphene oxide of the second type had a smaller lateral size. Raman spectroscopy showed a higher degree of sp2 structure regeneration after reduction for the second type of graphene. These properties and the tendency to form agglomerated particles determine the mechanochemical stability and high electrical conductivity of e-textiles based on electrochemically exfoliated graphene.
Fixed-Time Sliding Mode-Based Active Disturbance Rejection Tracking Control Method for Robot Manipulators
Authors: Vo Anh Tuan , Truong Thanh Nguyen , Le Quang Dan , Kang Hee-Jun
Published: January 2023

This work investigates the issue of a hybrid trajectory tracking control algorithm (HTCA) for robot manipulators (RMs) with uncertain dynamics and the effect of external disturbances. Following are some proposals for achieving the control target. Firstly, to achieve the active disturbance rejection, we propose a uniform second-order sliding mode disturbance observer (USOSMDO) to obtain directly the lumped uncertainties without their prior upper-bound information. Secondly, a fixed-time singularity-free terminal sliding surface (FxSTSS) is proposed to obtain a fixed-time convergence of the tracking control error (TCE) without the singularity in the control input. Then, using information on the proposed USOSMDO, our HTCA is formed based on the FxSTSS and the fixed-time power rate reaching law (FxPRRL). The control proposal not only stabilizes with the global fixed-time convergence but also attains high tracking accuracy. In addition, the chattering problem also is handled almost completely. Finally, numerical simulations verify the effectiveness and advantages of applying the proposed HTCA to a FARA robot.
Effects of Matching between the Inducer and the Impeller of a Centrifugal Pump on Its Cavitation Performance
Authors: Wang Daocheng , Gao Bingwen , Chen Yunzhang , Pan Yufan , Luo Jinping , Liu Lei , Wei Qingxi , Liu Lijun
Published: January 2023

The inducer is often used to prevent cavitation in a centrifugal pump. However, it may lead to deterioration of the cavitation performance of the pump when poorly matched with the impeller. Numerical simulations are employed to study the effects of the matching, specifically, the axial space and the circumferential deflection between the inducer and the impeller, on the cavitation performance. The results show that the inducer destroys the rotational symmetry of the velocity distribution at the inlet of the impeller, resulting in the influence of cavitation on the part of the channels in advance, which explains why the inducer cannot improve the cavitation performance even though it improves the inlet energy of the impeller. On the basis of not changing the geometric shape of the inducer and the impeller, the suction-specific speed is increased by nearly 300 by only adjusting the axial space and by nearly 100 by only adjusting the circumferential deflection. The cavitation performance is better with a larger axial space. There is an optimal value of the circumferential deflection at which the pump works at the best cavitation performance. The effect of the axial space on the overall cavitation performance is more significant than that of the circumferential deflection. The results provide a useful reference for the design and installation of a centrifugal pump inducer.
Predictive Extended State Observer-Based Active Disturbance Rejection Control for Systems with Time Delay
Authors: Nahri Syeda Nadiah Fatima , Du Shengzhi , van Wyk Barend J.
Published: January 2023

The latest research on disturbance rejection mechanisms has shown active disturbance rejection control (ADRC) to be an effective controller for uncertainties and nonlinear dynamics embedded in systems to be controlled. The significance of the ADRC controller is its model-free nature, as it requires minimal knowledge of the system model. In addition, it can actively estimate and compensate for the impact of internal and external disturbances present, with the aid of its crucial subsystem called the extended state observer (ESO). However, ADRC controller design becomes more challenging owing to different system disturbances, such as output disturbances, measurement noise, and varying time-delays persistent in the system’s communication channels. Most disturbance rejection techniques aim to reduce internal perturbations and external disturbances (input and output disturbance). However, output disturbance rejection with measurement noise under time-delay control is still a challenging problem. This paper presents a novel predictive ESO-based ADRC controller for time-delay systems by employing predictive methods to compensate for the disturbances originating from time delay. The prediction mechanism of the novel (proposed) controller design is greatly attributed to the extended state predictor observer (ESPO) integrated with the delay-based ADRC inside the proposed controller method. Thus, the proposed controller can predict the unknown system dynamics generated during the delay and compensate for these dynamics via disturbance rejection under time-delay control. This approach uses the optimization mechanism to determine controller parameters, where the genetic algorithm (GA) is employed with the integral of time-weighted absolute error (ITAE) as the fitness function. The proposed controller is validated by controlling second-order systems with time delay. Type 0, Type 1, and Type 2 systems are considered as the controlled plants, with disturbances (unknown dynamics due to delay and external disturbance), along with measurement noise present. The proposed controller method is compared with state-of-the-art methods, such as the modified time-delay-based ADRC method and the ESPO-based controller method. The findings indicate that the method proposed in this paper outperforms its existing competitors by compensating for the dynamics during the time delay and shows robust behaviour, improved disturbance rejection, and a fair extent of resilience to noise.
Petroleum Price Prediction with CNN-LSTM and CNN-GRU Using Skip-Connection
Authors: Kim Gun Il , Jang Beakcheol
Published: January 2023

Crude oil plays an important role in the global economy, as it contributes one-third of the energy consumption worldwide. However, despite its importance in policymaking and economic development, forecasting its price is still challenging due to its complexity and irregular price trends. Although a significant amount of research has been conducted to improve forecasting using external factors as well as machine-learning and deep-learning models, only a few studies have used hybrid models to improve prediction accuracy. In this study, we propose a novel hybrid model that captures the finer details and interconnections between multivariate factors to improve the accuracy of petroleum oil price prediction. Our proposed hybrid model integrates a convolutional neural network and a recurrent neural network with skip connections and is trained using petroleum oil prices and external data directly accessible from the official website of South Korea’s national oil corporation and the official Yahoo Finance site. We compare the performance of our univariate and multivariate models in terms of the Pearson correlation, mean absolute error, mean squared error, root mean squared error, and R squared (R2) evaluation metrics. Our proposed models exhibited significantly better performance than the existing models based on long short-term memory and gated recurrent units, showing correlations of 0.985 and 0.988, respectively, for 10-day price predictions and obtaining better results for longer prediction periods when compared with other deep-learning models. We validated that our proposed model with skip connections outperforms the benchmark models and showed that the convolutional neural network using gated recurrent units with skip connections is superior to the compared models. The findings suggest that, to some extent, relying on a single source of data is ineffective in predicting long-term changes in oil prices, and thus, to develop a better prediction model based on time-series based data, it is necessary to take a multivariate approach and develop an efficient computational model with skip connections.
A Semantics-Based Clustering Approach for Online Laboratories Using K-Means and HAC Algorithms
Authors: Haji Saad Hikmat , Jacksi Karwan , Salah Razwan Mohmed
Published: January 2023

Due to the availability of a vast amount of unstructured data in various forms (e.g., the web, social networks, etc.), the clustering of text documents has become increasingly important. Traditional clustering algorithms have not been able to solve this problem because the semantic relationships between words could not accurately represent the meaning of the documents. Thus, semantic document clustering has been extensively utilized to enhance the quality of text clustering. This method is called unsupervised learning and it involves grouping documents based on their meaning, not on common keywords. This paper introduces a new method that groups documents from online laboratory repositories based on the semantic similarity approach. In this work, the dataset is collected first by crawling the short real-time descriptions of the online laboratories’ repositories from the Web. A vector space is created using frequency-inverse document frequency (TF-IDF) and clustering is done using the K-Means and Hierarchical Agglomerative Clustering (HAC) algorithms with different linkages. Three scenarios are considered: without preprocessing (WoPP); preprocessing with steaming (PPwS); and preprocessing without steaming (PPWoS). Several metrics have been used for evaluating experiments: Silhouette average, purity, V-measure, F1-measure, accuracy score, homogeneity score, completeness and NMI score (consisting of five datasets: online labs, 20 NewsGroups, Txt_sentoken, NLTK_Brown and NLTK_Reuters). Finally, by creating an interactive webpage, the results of the proposed work are contrasted and visualized.
A Flexible Method for Diagnostic Accuracy with Biomarker Measurement Error
Authors: Wang Ching-Yun , Feng Ziding
Published: January 2023

Diagnostic biomarkers are often measured with errors due to imperfect lab conditions or analytic variability of the assay. The ability of a diagnostic biomarker to discriminate between cases and controls is often measured by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, among others. Ignoring measurement error can cause biased estimation of a diagnostic accuracy measure, which results in misleading interpretation of the efficacy of a diagnostic biomarker. Existing assays available are either research grade or clinical grade. Research assays are cost effective, often multiplex, but they may be associated with moderate measurement errors leading to poorer diagnostic performance. In comparison, clinical assays may provide better diagnostic ability, but with higher cost since they are usually developed by industry. Correction for attenuation methods are often valid when biomarkers are from a normal distribution, but may be biased with skewed biomarkers. In this paper, we develop a flexible method based on skew–normal biomarker distributions to correct for bias in estimating diagnostic performance measures including AUC, sensitivity, and specificity. Finite sample performance of the proposed method is examined via extensive simulation studies. The methods are applied to a pancreatic cancer biomarker study.
Some Certain Fuzzy Aumann Integral Inequalities for Generalized Convexity via Fuzzy Number Valued Mappings
Authors: Khan Muhammad Bilal , Othman Hakeem A. , Voskoglou Michael Gr. , Abdullah Lazim , Alzubaidi Alia M.
Published: January 2023

The topic of convex and nonconvex mapping has many applications in engineering and applied mathematics. The Aumann and fuzzy Aumann integrals are the most significant interval and fuzzy operators that allow the classical theory of integrals to be generalized. This paper considers the well-known fuzzy Hermite–Hadamard (HH) type and associated inequalities. With the help of fuzzy Aumann integrals and the newly introduced fuzzy number valued up and down convexity (UD-convexity), we increase this mileage even further. Additionally, with the help of definitions of lower UD-concave (lower UD-concave) and upper UD-convex (concave) fuzzy number valued mappings (FNVMs), we have gathered a sizable collection of both well-known and new extraordinary cases that act as applications of the main conclusions. We also offer a few examples of fuzzy number valued UD-convexity to further demonstrate the validity of the fuzzy inclusion relations presented in this study.
Lung Ultrasound Is Useful for Evaluating Lung Damage in COVID-19 Patients Treated with Bamlanivimab and Etesevimab: A Single-Center Pilot Study
Authors: Cicco Sebastiano , Marozzi Marialuisa Sveva , Palumbo Carmen Alessandra , Sturdà Elisabetta , Fusillo Antonio , Scarilli Flavio , Albanese Federica , Morelli Claudia , Bavaro Davide Fiore , Diella Lucia , Saracino Annalisa , Pappagallo Fabrizio , Solimando Antonio Giovanni , Lauletta Gianfranco , Ria Roberto , Vacca Angelo
Published: January 2023

Background and Objectives: COVID-19 induces massive systemic inflammation. Researchers have spent much time and effort finding an excellent and rapid image tool to evaluate COVID-19 patients. Since the pandemic’s beginning, lung ultrasound (LUS) has been identified for this purpose. Monoclonal antibodies (mAb) were used to treat mild patients and prevent respiratory disease worsening. Materials and Methods: We evaluated 15 Caucasian patients with mild COVID-19 who did not require home oxygen, treated with Bamlanivimab and Etesevimab (Group 1). A molecular nose–throat swab test confirmed the diagnosis. All were office patients, and nobody was affected by respiratory failure. They were admitted to receive the single-day infusion of mAb treatment in agreement with the Italian Drug Agency (AIFA) rules for approval. LUS was performed before the drug administration (T0) and after three months (T1). We compared LUS at T1 in other outpatients who came for follow-up and were overlapping at the time of diagnosis for admittance criteria to receive mAb (Group 2). Results: Our COVID-19 outpatients reported no hospitalization in a follow-up visit after recovery. All patients became SARS-CoV-2 negative within one month since T0. LUS score at T0 was 8.23 ± 6.46. At T1 we found a significant decrease in Group 1 LUS score (5.18 ± 4.74; p < 0.05). We also found a significant decrease in the LUS score of Group 1 T1 compared to Group2 T1 (5.18 ± 4.74 vs 7.82 ± 5.21; p < 0.05). Conclusion: Early treatment of the SARS-CoV-2 virus effectively achieves a better recovery from disease and reduces lung involvement after three months as evaluated with LUS. Despite extrapolation to the general population may be done with caution, based on our data this ultrasound method is also effective for evaluating and following lung involvement in COVID-19 patients.
Alterations in Inflammatory Markers and Cognitive Ability after Treatment of Pediatric Obstructive Sleep Apnea
Authors: Eldin Mohamed Shams , Alahmer Mohamed , Alkashlan Ebrahim , Zahran Mahmoud , Eltonsy Mohamed , Zewail Amr , Kasem Abdelfattah , Abdelaal Khaled , Seddeek Mahrous , Ahmed Zakaria
Published: January 2023

Background and Objectives: Determination of the impact of obstructive sleep apnea (OSA) on the cognitive function (CF), and serum tumor necrosis factor-α (TNF-α), interleukin (IL)-6 and 1β levels and the effect of OSA management on these variables in children. Materials and Methods: A total of 224 patients were evaluated using the Pediatric Sleep Questionnaire, the NEPSY score for CF, and polysomnography (PSG) to grade OSA severity according to the apnea/hypopnea index (AHI). Adentonsillectomy (AT) was performed for patients with adenotonsillar hypertrophy grade > 2. Patients with overweight or obesity with mild or moderate OSAS underwent a 6-month protocol of lifestyle intervention (LSI). Blood samples were obtained for an enzyme-linked immunosorbent assay (ELISA) estimation of cytokine levels. All variables were re-evaluated at the end of the 6-month follow-up period. Results: A total of 181 patients had surgical interference and 43 patients underwent a LSI trial; 15 patients failed to respond and underwent surgery. At the end of the follow-up, 33 patients had residual OSAS with a significantly higher incidence among patients with severe OSAS, the mean score of the pediatric sleep questionnaire was significantly decreased in all patients, 181 patients showed an improved NESPY score, and cytokine levels were decreased. The baseline NESPY score, AHI index and sleep questionnaire score were negatively correlated. The percentage of change in the NESPY score and serum cytokine levels showed a positive correlation. Conclusions: OSAS is associated with cognitive dysfunction that significantly improves after adenotonsillectomy. LSI as a therapeutic line is satisfactory for children with mild OSAS and minimal cognitive dysfunction and is of value preoperatively to improve the surgical outcomes of AT.
Circulating CD4+ Treg, CD8+ Treg, and CD3+ γδ T Cell Subpopulations in Ovarian Cancer
Authors: Li Rong , Xu Juan , Wu Ming , Liu Shuna , Fu Xin , Shang Wenwen , Wang Ting , Jia Xuemei , Wang Fang
Published: January 2023

Background and Objectives: Regulatory T cells (Tregs) are usually enriched in ovarian cancer (OC), and their immunosuppressive function plays a key role in tumorigenesis and progression. We mainly explored the phenotypical characterization of Treg-related markers on αβ and γδ T cell subsets in patients with OC. Materials and Methods: Thirty-six untreated patients with OC at the Women’s Hospital of Nanjing Medical University from September 2019 to August 2021 were enrolled. Phenotypical characterization of Tregs-related markers were detected by flow cytometry (FCM). Enzyme-linked immunosorbent assay was used to detect the levels of carbohydrate antigen (CA125) and transforming growth factor β (TGF-β). The level of human epididymis protein 4 (HE4) was detected by electrochemiluminescence immunoassay. Results: Circulating CD4+ Tregs, CD8+ Tregs, and CD3+γδ T cell subpopulations from OC patients have elevated Foxp3, CD25, CD122, Vδ1, and reduced CD28 expression compared to benign ovarian tumor (BOT) patients and healthy controls (HC). The upregulation of Foxp3 and Vδ1 and the downregulation of CD28 were highly specific for maintaining the immunosuppression function of CD4+ Tregs, CD3+γδ T cells, and CD8+ Tregs in OC patients. These Treg subpopulations were able to discriminate OC from BOT and HC. The levels of CA125, HE4, and TGF-β were increased in OC patients. A significant positive correlation between Treg subpopulations and CA125, HE4, and TGF-β was revealed. Conclusions: Proportions of CD4+ Tregs, CD8+ Tregs, and CD3+γδ T cell subsets were significantly increased in OC patients and were positively correlated with FIGO stage/metastasis status, CA125, HE4, and TGF-β. These indicators have the potential to be used as immunosurveillance biomarkers for OC.
Comparative Genomic Analysis of Sphingomonas morindae sp. NBD5 and Sphingopyxis sp. USTB-05 for Producing Macular Pigment
Authors: Liu Chao , Zhao Zhenzhen , Xu Qianqian , Zhang Haiyang , Liu Xiaolu , Yin Chunhua , Yan Hai , Liu Yang
Published: January 2023

Sphingomonas morindae sp. NBD5, which we previously identified and tested, is a new bacterial strain for producing lutein. Here, based on the next-generation sequencing technology, we analyzed high throughput genomic sequences and compared related functional genes of Sphingomonas morindae sp. NBD5 and Sphingopyxis sp. USTB-05. The genome of Sphingomonas morindae sp. NBD5 has two sets of chromosomes, which is 4,239,716 bp and harbors 3882 protein coding genes. There are 59 protein-coding genes related to the macular pigment (MP) biosynthesis, of which four genes (ackA, pgm, gpmI and pckA) are unique. These genes, pckG, porB, meh, and fldA, are unique in Sphingopyxis sp. USTB-05. The analysis of Sphingomonas morindae sp. NBD5 and Sphingopyxis sp. USTB-05 genomes gives an insight into the new pathway for MP production. These genes for the transformation of glucose to MP were also found in Sphingomonas morindae sp. NBD5 and Sphingopyxis sp. USTB-05. This study expands the understanding of the pathway for complete biosynthesis of MP by Sphingomonas morindae sp. NBD5 and Sphingopyxis sp. USTB-05.
Emerging Technologies and New Media for Children: Introduction
Authors: Brulé Émeline , Sobel Kiley
Published: January 2023

In his 1749 essay, Letter on the Blind for the Use of Those Who Can See, Diderot explores the impact of vision, or lack thereof, on the development of knowledge [...]
Acknowledgment to the Reviewers of Pharmacy in 2022
Authors:   Pharmacy Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Acknowledgment to the Reviewers of Poultry in 2022
Authors:   Poultry Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Research on 3D Path Planning of Quadrotor Based on Improved A* Algorithm
Authors: Zheng Wei , Huang Kaipeng , Wang Chenyang , Liu Yang , Ke Zhiwu , Shen Qianyu , Qiu Zhiqiang
Published: January 2023

Considering the complexity of the three-dimensional environment and the flexibility of the quadrotor aircraft, using the traditional A* algorithm for global path planning has the disadvantages of less search direction, more expanded nodes, and a longer planning path. Therefore, an improved A* algorithm is proposed, which is improved from two aspects. Firstly, a two-layer extended neighborhood strategy is proposed, which can increase the search direction and make better use of the flexibility of the aircraft. Secondly, the heuristic function is improved to make the heuristic function value closer to the actual planning path distance, which can reduce the expansion nodes and optimize the planning path. Finally, the path planning simulation of the improved A* algorithm is carried out and the results show that the path planned by the improved algorithm is shorter and the expanded nodes are fewer, which can guide the quadrotor to reach the destination better.
Enhancing Biobased Volatile Fatty Acids Production from Olive Mill Solid Waste by Optimization of pH and Substrate to Inoculum Ratio
Authors: da Fonseca Yasmim A. , de Camargos Adonai B. , Gomes Gustavo S. M. , Fregulia P. , Silva Silvana Q. , Gurgel Leandro V. A. , Baêta Bruno E. L.
Published: January 2023

The pH and substrate-to-inoculum ratio (S/I) are important parameters in the anaerobic fermentation of agroindustrial residues, and therefore the optimization of these two parameters is needed for a stable, efficient, and sustainable reactor operation. In this work, the parameters pH (5–9) and S/I (0.5–3 gVS gVS−1) were optimized to produce biobased volatile fatty acids (VFAs) from hydrothermally pretreated olive mill solid waste (HPOMSW). The response variables evaluated in the Doehlert design were total VFAs concentration (tVFAs) (mg L−1) and amounts (%) of isobutyric, butyric, isovaleric, and valeric acids on the VFAs profile. The pH was the variable that most influenced the mixed culture fermentation of HPOMSW, proving to be a key parameter in the process. Microbial community analyses of conditions 1 (S/I = 3 gVS gVS−1 and pH = 7) and 4 (S/I = 1.13 gVS gVS−1 and pH = 5) showed that Proteobacteria and Firmicutes accounted for more than 87% of the total microorganisms identified for both conditions. In addition, the second-order model best fitted the experimental data for the VFAs production at the desirable condition (S/I = 3 gVS gVS−1 and pH = 8).
Generating High-Resolution 3D Faces and Bodies Using VQ-VAE-2 with PixelSNAIL Networks on 2D Representations
Authors: Gallucci Alessio , Znamenskiy Dmitry , Long Yuxuan , Pezzotti Nicola , Petkovic Milan
Published: January 2023

Modeling and representing 3D shapes of the human body and face is a prominent field due to its applications in the healthcare, clothes, and movie industry. In our work, we tackled the problem of 3D face and body synthesis by reducing 3D meshes to 2D image representations. We show that the face can naturally be modeled on a 2D grid. At the same time, for more challenging 3D body geometries, we proposed a novel non-bijective 3D–2D conversion method representing the 3D body mesh as a plurality of rendered projections on the 2D grid. Then, we trained a state-of-the-art vector-quantized variational autoencoder (VQ-VAE-2) to learn a latent representation of 2D images and fit a PixelSNAIL autoregressive model to sample novel synthetic meshes. We evaluated our method versus a classical one based on principal component analysis (PCA) by sampling from the empirical cumulative distribution of the PCA scores. We used the empirical distributions of two commonly used metrics, specificity and diversity, to quantitatively demonstrate that the synthetic faces generated with our method are statistically closer to real faces when compared with the PCA ones. Our experiment on the 3D body geometry requires further research to match the test set statistics but shows promising results.
Light Penetrating the Seawater Column as the Indicator of Oil Suspension—Monte Carlo Modelling for the Case of the Southern Baltic Sea
Authors: Lednicka Barbara , Otremba Zbigniew , Piskozub Jacek
Published: January 2023

The strong need to control investments related to oil extraction and the growing demand for offshore deep-water exploration are the reasons for looking for tools to make up a global underwater monitoring system. Therefore, the current study analyses the possibility of revealing the existence of oil-in-water emulsions in the water column, based on the modelling of the downwelling radiance detected by a virtual underwater sensor. Based on the Monte Carlo simulation for the large numbers of solar photons in the water, the analyses were carried out for eight wavelengths ranging from 412 to 676 nm using dispersed oil with a concentration of 10 ppm. The optical properties of the seawater were defined as typical for the southern Baltic Sea, while the oil emulsion model was based on the optical properties of crude oil extracted in this area. Based on the above-mentioned assumptions and modelling, a spectral index was obtained, with the most favourable combination of 555/412 nm, whose value is indicative of the presence of an oil emulsion in the water.
Point Cloud Classification by Domain Adaptation Using Recycling Max Pooling and Cutting Plane Identification
Authors: Yoo Hojin , Jun Kyungkoo
Published: January 2023

Deep models have been studied in point cloud classification for the applications of autonomous driving and robotics. One challenging issue is that the point cloud of the same object could be discrepantly captured depending on sensors. Such a difference is the main cause of the domain gap. The deep models trained with one domain of point clouds may not work well with other domains because of such a domain gap. A technique to reduce domain inconsistency is domain adaptation. In this paper, we propose an unsupervised domain adaptation with two novel schemes. First, to improve unreliable pseudo-label assignment, we introduce a voting-based procedure based on the recycling max pooling module, which involves self-paced learning. It helps to increase the training stability of the models. Second, to learn the geometrical characteristics of point clouds in unfamiliar settings, we propose a training method of cutting plane identification, which works in an unsupervised way. Testing with the popular point cloud dataset of PointDA-10 and Sim-to-Real, experiments show that our method increase classification accuracy by 6.5%-points on average, ModelNet and ShapeNet as the source domain and ScanNet, and ScanObjectNN as the target domain. From an ablation study, it was observed that each method contributes to improving the robustness of domain adaptation.
Electrical Impedance Tomography: From the Traditional Design to the Novel Frontier of Wearables
Authors: Pennati Francesca , Angelucci Alessandra , Morelli Letizia , Bardini Susanna , Barzanti Elena , Cavallini Federico , Conelli Antonello , Di Federico Gaia , Paganelli Chiara , Aliverti Andrea
Published: January 2023

Electrical impedance tomography (EIT) is a medical imaging technique based on the injection of a current or voltage pattern through electrodes on the skin of the patient, and on the reconstruction of the internal conductivity distribution from the voltages collected by the electrodes. Compared to other imaging techniques, EIT shows significant advantages: it does not use ionizing radiation, is non-invasive and is characterized by high temporal resolution. Moreover, its low cost and high portability make it suitable for real-time, bedside monitoring. However, EIT is also characterized by some technical limitations that cause poor spatial resolution. The possibility to design wearable devices based on EIT has recently given a boost to this technology. In this paper we reviewed EIT physical principles, hardware design and major clinical applications, from the classical to a wearable setup. A wireless and wearable EIT system seems a promising frontier of this technology, as it can both facilitate making clinical measurements and open novel scenarios to EIT systems, such as home monitoring.
Long-Term Coronary Artery Disease Risk Prediction with Machine Learning Models
Authors: Trigka Maria , Dritsas Elias
Published: January 2023

The heart is the most vital organ of the human body; thus, its improper functioning has a significant impact on human life. Coronary artery disease (CAD) is a disease of the coronary arteries through which the heart is nourished and oxygenated. It is due to the formation of atherosclerotic plaques on the wall of the epicardial coronary arteries, resulting in the narrowing of their lumen and the obstruction of blood flow through them. Coronary artery disease can be delayed or even prevented with lifestyle changes and medical intervention. Long-term risk prediction of coronary artery disease will be the area of interest in this work. In this specific research paper, we experimented with various machine learning (ML) models after the use or non-use of the synthetic minority oversampling technique (SMOTE), evaluating and comparing them in terms of accuracy, precision, recall and an area under the curve (AUC). The results showed that the stacking ensemble model after the SMOTE with 10-fold cross-validation prevailed over the other models, achieving an accuracy of 90.9 %, a precision of 96.7%, a recall of 87.6% and an AUC equal to 96.1%.
Rain Discrimination with Machine Learning Classifiers for Opportunistic Rain Detection System Using Satellite Micro-Wave Links
Authors: Gianoglio Christian , Alyosef Ayham , Colli Matteo , Zani Sara , Caviglia Daniele D.
Published: January 2023

In the climate change scenario the world is facing, extreme weather events can lead to increasingly serious disasters. To improve managing the consequent risks, there is a pressing need to have real-time systems that provide accurate monitoring and possibly forecasting which could help to warn people in the affected areas ahead of time and save them from hazards. The oblique earth-space links (OELs) have been used recently as a method for real-time rainfall detection. This technique poses two main issues related to its indirect nature. The first one is the classification of rainy and non-rainy periods. The second one is the determination of the attenuation baseline, which is an essential reference for estimating rainfall intensity along the link. This work focuses mainly on the first issue. Data referring to eighteen rain events were used and have been collected by analyzing a satellite-to-earth link quality and employing a tipping bucket rain gauge (TBRG) properly positioned, used as reference. It reports a comparison among the results obtained by applying four different machine learning (ML) classifiers, namely the support vector machine (SVM), neural network (NN), random forest (RF), and decision tree (DT). Various data arrangements were explored, using a preprocessed version of the TBRG data, and extracting two different sets of characteristics from the microwave link data, containing 6 or 12 different features, respectively. The achieved results demonstrate that the NN classifier has outperformed the other classifiers.
Design and Evaluation for Immersive Virtual Reality Learning Environment: A Systematic Literature Review
Authors: Cao Ying , Ng Giap-Weng , Ye Sha-Sha
Published: January 2023

This systematic review broadly attempted to synthesize all relevant evidence residing in the Scopus, IEEE Xplore and MDPI databases, in order to inform the related Research Questions of this work. More precisely, the review protocol includes a broad and comprehensive search for eligible data sets from the Scopus, IEEE Xplore and MDPI databases, published from January 2017 to December 2022 by using inclusion/exclusion search criteria. Medical Education Research Study Quality Instrument (MERSQI) was commissioned to assess and analyze the quality of 69 quantitative studies. The findings generally received positive feedback and there was a discussion about the results. This work was an original contribution guided by pedagogical theory and the validity of the evaluation constitutes a proposal for future improvement.
Capitalization of Tourist Resources in the Post-COVID-19 Period—Developing the Chorematic Method for Oltenia Tourist Destination, Romania
Authors: Drăguleasa Ionuț-Adrian , Niță Amalia , Mazilu Mirela
Published: January 2023

The paper aims at adapting the knowledge regarding the capitalization of tourist resources to the method of tourist choremas in the Oltenia region, Romania, thus creating a tool for planning and organizing the geographical space for sustainable development. The tourism choremas method uses the graphic and cartographic modelling of the territory of the South-West Oltenia region, and in a post-COVID-19 period it is important that the research can help in increasing the productivity in tourism, which can lead to higher incomes for managers in the tourism sector and for the locals from different rural/disadvantaged area of the region. GIS (Geographical Information Systems) represents a key element for the future development of tourism in the virtual environment, given the fact that many travellers use virtual electronic systems to see the tourist destination, surroundings, protected areas, accommodation, tourist routes, recreation and entertainment areas (zoos, hunting areas), etc. Choremes of the Oltenia region were created using ArcGIS 10.1 software, showing different entities and a series of attributes (descriptive elements) marked on the created maps as follows: elements of the natural environment (landforms altimetry, hydrographic network, lakes, national parks and reserves, waterfalls); man-made environment (roads, landmarks—churches, monasteries, museums); or conventional delimitations (county boundary, the boundaries of the two areas—Northern and Southern Oltenia). Four successive stages were conducted in order to create the choremes using the GIS software: (1) creating the database for the analysis of the studied destination; (2) processing the statistical data for Northern and Southern Oltenia; (3) the interpretation of the data obtained in correlation with the specialized literature on the capitalization of tourism resources and forms of tourism existing in the region; and (4) cartographic representation. The chorematic maps are represented at the scale of the geographical territory where the study analysis is carried out. The representation of physico-geographical elements, but also of touristic elements, was represented by lines, points and polygons, using the vector and raster spatial data model. The chorematic method proves to be innovative and up-to-date especially for the organization of the tourist space, for the sustainable development of the region and for the tourism research activity in the area.