bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning Model for Outcome Prediction of Patients Suffering from Acute Diverticulitis Arriving at the Emergency Department—A Proof of Concept Study
Authors: Klang Eyal , Freeman Robert , Levin Matthew A. , Soffer Shelly , Barash Yiftach , Lahat Adi
Published: November 2021

Background & Aims: We aimed at identifying specific emergency department (ED) risk factors for developing complicated acute diverticulitis (AD) and evaluate a machine learning model (ML) for predicting complicated AD. Methods: We analyzed data retrieved from unselected consecutive large bowel AD patients from five hospitals from the Mount Sinai health system, NY. The study time frame was from January 2011 through March 2021. Data were used to train and evaluate a gradient-boosting machine learning model to identify patients with complicated diverticulitis, defined as a need for invasive intervention or in-hospital mortality. The model was trained and evaluated on data from four hospitals and externally validated on held-out data from the fifth hospital. Results: The final cohort included 4997 AD visits. Of them, 129 (2.9%) visits had complicated diverticulitis. Patients with complicated diverticulitis were more likely to be men, black, and arrive by ambulance. Regarding laboratory values, patients with complicated diverticulitis had higher levels of absolute neutrophils (AUC 0.73), higher white blood cells (AUC 0.70), platelet count (AUC 0.68) and lactate (AUC 0.61), and lower levels of albumin (AUC 0.69), chloride (AUC 0.64), and sodium (AUC 0.61). In the external validation cohort, the ML model showed AUC 0.85 (95% CI 0.78–0.91) for predicting complicated diverticulitis. For Youden’s index, the model showed a sensitivity of 88% with a false positive rate of 1:3.6. Conclusions: A ML model trained on clinical measures provides a proof of concept performance in predicting complications in patients presenting to the ED with AD. Clinically, it implies that a ML model may classify low-risk patients to be discharged from the ED for further treatment under an ambulatory setting.
Breast Carcinomatous Lymphangitis as an Unusual Presentation of Ovarian Cancer
Authors: Muoio Barbara , Treglia Giorgio , Migliora Paola , Del Grande Maria
Published: November 2021

We describe the case of a 45-year-old woman with an unusual presentation of metastatic ovarian cancer. The patient presented to the oncological clinic with a three-week history of skin rash on the right breast. She underwent a chest and abdomen CT scan, which showed skin thickening of the right breast, right pleural effusion and bilateral cystic ovarian masses. Biopsy of a left ovarian lesion by diagnostic laparoscopy revealed the presence of ovarian serous carcinoma. Biopsy of the breast skin lesion revealed the presence of carcinomatous lymphangitis and immunohistochemistry documented the ovarian origin.
Abnormal Circulating Maternal miRNA Expression Is Associated with a Low (<4%) Cell-Free DNA Fetal Fraction
Authors: Santoro Graziano , Lapucci Cristina , Giannoccaro Marco , Caporilli Simona , Rusin Martina , Seidenari Anna , Ferrari Maurizio , Farina Antonio
Published: November 2021

The present pilot study investigates whether an abnormal miRNA profile in NIPT plasma samples can explain the finding of a low cell-free DNA (cfDNA) fetal fraction (cfDNAff) in euploid fetuses and non-obese women. Twelve women who underwent neoBona® NIPT with a normal fetal karyotype were studied. Six with a cfDNAff < 4% were matched with a control group with normal levels of cfDNAff > 4%. Samples were processed using the nanostring nCounter® platform with a panel of 800 miRNAs. Four of the maternal miRNAs, miR-579, miR-612, miR-3144 and miR-6721, had a significant abnormal expression in patients. A data filtering analysis showed that miR-579, miR-612, miR-3144 and miR-6721 targeted 169, 1, 48 and 136 placenta-specific genes, respectively. miR-579, miR-3144 and miR-6721 shared placenta-specific targeted genes involved in trophoblast invasion and migration pathways (IGF2R, PTCD2, SATB2, PLAC8). Moreover, the miRNA target genes encoded proteins localized in the placenta and involved in the pathogenesis of pre-eclampsia, including chorion-specific transcription factor GCMa, PRG2, Lin-28 Homolog B and IGFBP1. In conclusion, aberrant maternal miRNA expression in circulating plasma could be a source of dysregulating trophoblast invasion and migration and could represent a novel cause of a low cfDNAff in the sera of pregnant women at the time of NIPT analysis.
Ten Fast Transfer Learning Models for Carotid Ultrasound Plaque Tissue Characterization in Augmentation Framework Embedded with Heatmaps for Stroke Risk Stratification
Authors: Sanagala Skandha S. , Nicolaides Andrew , Gupta Suneet K. , Koppula Vijaya K. , Saba Luca , Agarwal Sushant , Johri Amer M. , Kalra Manudeep S. , Suri Jasjit S.
Published: November 2021

Background and Purpose: Only 1–2% of the internal carotid artery asymptomatic plaques are unstable as a result of >80% stenosis. Thus, unnecessary efforts can be saved if these plaques can be characterized and classified into symptomatic and asymptomatic using non-invasive B-mode ultrasound. Earlier plaque tissue characterization (PTC) methods were machine learning (ML)-based, which used hand-crafted features that yielded lower accuracy and unreliability. The proposed study shows the role of transfer learning (TL)-based deep learning models for PTC. Methods: As pertained weights were used in the supercomputer framework, we hypothesize that transfer learning (TL) provides improved performance compared with deep learning. We applied 11 kinds of artificial intelligence (AI) models, 10 of them were augmented and optimized using TL approaches—a class of Atheromatic™ 2.0 TL (AtheroPoint™, Roseville, CA, USA) that consisted of (i–ii) Visual Geometric Group-16, 19 (VGG16, 19); (iii) Inception V3 (IV3); (iv–v) DenseNet121, 169; (vi) XceptionNet; (vii) ResNet50; (viii) MobileNet; (ix) AlexNet; (x) SqueezeNet; and one DL-based (xi) SuriNet-derived from UNet. We benchmark 11 AI models against our earlier deep convolutional neural network (DCNN) model. Results: The best performing TL was MobileNet, with accuracy and area-under-the-curve (AUC) pairs of 96.10 ± 3% and 0.961 (p < 0.0001), respectively. In DL, DCNN was comparable to SuriNet, with an accuracy of 95.66% and 92.7 ± 5.66%, and an AUC of 0.956 (p < 0.0001) and 0.927 (p < 0.0001), respectively. We validated the performance of the AI architectures with established biomarkers such as greyscale median (GSM), fractal dimension (FD), higher-order spectra (HOS), and visual heatmaps. We benchmarked against previously developed Atheromatic™ 1.0 ML and showed an improvement of 12.9%. Conclusions: TL is a powerful AI tool for PTC into symptomatic and asymptomatic plaques.
Evaluation of a Novel Content-Based Image Retrieval System for the Differentiation of Interstitial Lung Diseases in CT Examinations
Authors: Pogarell Tobias , Bayerl Nadine , Wetzl Matthias , Roth Jan-Peter , Speier Christoph , Cavallaro Alexander , Uder Michael , Dankerl Peter
Published: November 2021

To evaluate the reader’s diagnostic performance against the ground truth with and without the help of a novel content-based image retrieval system (CBIR) that retrieves images with similar CT patterns from a database of 79 different interstitial lung diseases. We evaluated three novice readers’ and three resident physicians‘ (with at least three years of experience) diagnostic performance evaluating 50 different CTs featuring 10 different patterns (e.g., honeycombing, tree-in bud, ground glass, bronchiectasis, etc.) and 24 different diseases (sarcoidosis, UIP, NSIP, Aspergillosis, COVID-19 pneumonia etc.). The participants read the cases first without assistance (and without feedback regarding correctness), and with a 2-month interval in a random order with the assistance of the novel CBIR. To invoke the CBIR, a ROI is placed into the pathologic pattern by the reader and the system retrieves diseases with similar patterns. To further narrow the differential diagnosis, the readers can consult an integrated textbook and have the possibility of selecting high-level semantic features representing clinical information (chronic, infectious, smoking status, etc.). We analyzed readers’ accuracy without and with CBIR assistance and further tested the hypothesis that the CBIR would help to improve diagnostic performance utilizing Wilcoxon signed rank test. The novice readers demonstrated an unassisted accuracy of 18/28/44%, and an assisted accuracy of 84/82/90%, respectively. The resident physicians demonstrated an unassisted accuracy of 56/56/70%, and an assisted accuracy of 94/90/96%, respectively. For each reader, as well as overall, Sign test demonstrated statistically significant (p < 0.01) difference between the unassisted and the assisted reads. For students and physicians, Chi²-test and Mann-Whitney-U test demonstrated statistically significant (p < 0.01) difference for unassisted reads and statistically insignificant (p > 0.01) difference for assisted reads. The evaluated CBIR relying on pattern analysis and featuring the option to filter the results of the CBIR by predominant characteristics of the diseases via selecting high-level semantic features helped to drastically improve novices’ and resident physicians’ accuracy in diagnosing interstitial lung diseases in CT.
SARS-CoV-2 Infection Prevalence in the Population of South-Eastern Poland
Authors: Stępień Ewa , Koleśnik Marcin , Mitura Katarzyna , Malm Maria , Drop Bartłomiej , Jędrych Marian , Polz-Dacewicz Małgorzata
Published: November 2021

COVID-19 outbreak began in Wuhan, China, and has spread to other continents, including Europe, placing pressure on healthcare systems. Poland is one of the European countries with the highest number of SARS-CoV-2 infections and COVID-19-related deaths. The aim of this study was to analyze the presence of SARS-CoV-2 in the population of south-eastern Poland. The correlation between viral infection and demographic data (gender, age, place of residence) and cancer was also investigated. A total of 44,801 samples were tested, of which 4862 cases were diagnosed with SARS-CoV-2 infections. A total of 14,970 samples were tested in cancer patients. The RT-PCR method was used to detect viral nucleic acid. In this study, significantly, the highest rate of virus detection was among people living in Lublin and the lowest among people living in a small town (p < 0.0001). Moreover, there was no significant relationship between sex and the frequency of virus detection. The highest number of SARS-CoV-2 infections was observed in the age groups 10–19, 20–29, 30–39, and 90+ (p = 0.0001). In cancer patients, the percentage of positive cases was significantly lower than in the rest (p = 0.0001).
Learning to Classify DWDM Optical Channels from Tiny and Imbalanced Data
Authors: Cichosz Paweł , Kozdrowski Stanisław , Sujecki Sławomir
Published: November 2021

Applying machine learning algorithms for assessing the transmission quality in optical networks is associated with substantial challenges. Datasets that could provide training instances tend to be small and heavily imbalanced. This requires applying imbalanced compensation techniques when using binary classification algorithms, but it also makes one-class classification, learning only from instances of the majority class, a noteworthy alternative. This work examines the utility of both these approaches using a real dataset from a Dense Wavelength Division Multiplexing network operator, gathered through the network control plane. The dataset is indeed of a very small size and contains very few examples of “bad” paths that do not deliver the required level of transmission quality. Two binary classification algorithms, random forest and extreme gradient boosting, are used in combination with two imbalance handling methods, instance weighting and synthetic minority class instance generation. Their predictive performance is compared with that of four one-class classification algorithms: One-class SVM, one-class naive Bayes classifier, isolation forest, and maximum entropy modeling. The one-class approach turns out to be clearly superior, particularly with respect to the level of classification precision, making it possible to obtain more practically useful models.
Directly and Simultaneously Expressing Absolute and Relative Treatment Effects in Medical Data Models and Applications
Authors: Teng Haoyang , Zhang Zhengjun
Published: November 2021

Logistic regression is widely used in the analysis of medical data with binary outcomes to study treatment effects through (absolute) treatment effect parameters in the models. However, the indicative parameters of relative treatment effects are not introduced in logistic regression models, which can be a severe problem in efficiently modeling treatment effects and lead to the wrong conclusions with regard to treatment effects. This paper introduces a new enhanced logistic regression model that offers a new way of studying treatment effects by measuring the relative changes in the treatment effects and also incorporates the way in which logistic regression models the treatment effects. The new model, called the Absolute and Relative Treatment Effects (AbRelaTEs) model, is viewed as a generalization of logistic regression and an enhanced model with increased flexibility, interpretability, and applicability in real data applications than the logistic regression. The AbRelaTEs model is capable of modeling significant treatment effects via an absolute or relative or both ways. The new model can be easily implemented using statistical software, with the logistic regression model being treated as a special case. As a result, the classical logistic regression models can be replaced by the AbRelaTEs model to gain greater applicability and have a new benchmark model for more efficiently studying treatment effects in clinical trials, economic developments, and many applied areas. Moreover, the estimators of the coefficients are consistent and asymptotically normal under regularity conditions. In both simulation and real data applications, the model provides both significant and more meaningful results.
Angular Rate Constrained Sliding Mode Control of UAVs for Path Following
Authors: Jang Seok-ho , Yang Youyoung , Leeghim Henzeh
Published: November 2021

In this work, a sliding-mode-based attitude controller constrained with the angular rate for unmanned aerial vehicles (UAVs) is addressed to withstand conditions below the allowable maximum angular velocity of UAVs in order to avoid the possibility of structural failure and to operate UAVs safely. The sliding mode controller suggested in this work defines a new sliding surface, inherently having two equilibrium points. These equilibrium points are carefully inspected, and the stability of the system controlled by means of the proposed approach is also analyzed using Lyapunov stability theory. To highlight the angular-rate constrained attitude control technique, a three-dimensional path is constructed using the Dubins path technique, and three-axis attitude commands for UAV are also generated by augmenting the line-of-sight algorithm. Compared with conventional sliding mode control measures, the excellent performance of the suggested control algorithm has been demonstrated by conducting numerical simulations.
A Noise-Resilient Neuromorphic Digit Classifier Based on NOR Flash Memories with Pulse–Width Modulation Scheme
Authors: Malavena Gerardo , Sottocornola Spinelli Alessandro , Monzio Compagnoni Christian
Published: November 2021

In this work, we investigate the implementation of a neuromorphic digit classifier based on NOR Flash memory arrays as artificial synaptic arrays and exploiting a pulse-width modulation (PWM) scheme. Its performance is compared in presence of various noise sources against what achieved when a classical pulse-amplitude modulation (PAM) scheme is employed. First, by modeling the cell threshold voltage (VT) placement affected by program noise during a program-and-verify scheme based on incremental step pulse programming (ISPP), we show that the classifier truthfulness degradation due to the limited program accuracy achieved in the PWM case is considerably lower than that obtained with the PAM approach. Then, a similar analysis is carried out to investigate the classifier behavior after program in presence of cell VT instabilities due to random telegraph noise (RTN) and to temperature variations, leading again to results in favor of the PWM approach. In light of these results, the present work suggests a viable solution to overcome some of the more serious reliability issues of NOR Flash-based artificial neural networks, paving the way to the implementation of highly-reliable, noise-resilient neuromorphic systems.
Nontargeted vs. Targeted vs. Smart Load Shifting Using Heat Pump Water Heaters
Authors: Obi Manasseh , Metzger Cheryn , Mayhorn Ebony , Ashley Travis , Hunt Walter
Published: November 2021

Deployment of CTA-2045–enabled devices is increasing in the U.S. market. These devices allow utilities or third-party aggregators to control appliance energy use in homes, and could also be applied to end uses in small commercial buildings. This study focuses on a field study using CTA-2045–enabled water heaters to shift electric load off the peak and toward periods when renewable resources are more prevalent (e.g., near noon for solar resources and near midnight for wind resources). The following load shifting strategies were compared to understand effects on the aggregate load-shifting capabilities of Heat Pump Water Heaters (HPWHs) and on consumer hot water supply: non-targeted (traditional), targeted (grouped, with different shifting schedules) and “smart” (adaptive control commands). The results of this study show that targeted and smart control strategies yield significantly more load-shifting potential from a population of water heaters than the non-targeted approach without sacrificing hot water supply to occupants. However, as control commands become more aggressive, aggregators may face challenges in meeting consumer hot water demand. The findings and lessons learned can benefit electric utilities and inform updates to manufacturer controls and communications standards. The data collected may also be useful for developing and validating HPWH models.
Resilience Assessment: A Performance-Based Importance Measure
Authors: Nouri Qarahasanlou Ali , Zamani Ali , Barabadi Abbas , Mokhberdoran Mahdi
Published: November 2021

The resilience of a system can be considered as a function of its reliability and recoverability. Hence, for effective resilience management, the reliability and recoverability of all components which build up the system need to be identified. After that, their importance should be identified using an appropriate model for future resource allocation. The critical infrastructures are under dynamic stress due to operational conditions. Such stress can significantly affect the recoverability and reliability of a system’s components, the system configuration, and consequently, the importance of components. Hence, their effect on the developed importance measure needs to be identified and then quantified appropriately. The dynamic operational condition can be modeled using the risk factors. However, in most of the available importance measures, the effect of risk factors has not been addressed properly. In this paper, a reliability importance measure has been used to determine the critical components considering the effect of risk factors. The application of the model has been shown through a case study.
The Challenge for Energy Saving in Smart Homes: Exploring the Interest for IoT Devices Acquisition in Romania
Authors: Micu Adrian , Micu Angela-Eliza , Geru Marius , Capatina Alexandru , Muntean Mihaela-Carmen
Published: November 2021

The Internet of Things (IoT) is a shift towards a digitally enriched environment that connects smart objects and users, aiming to provide merchants with innovative ways to communicate with customers. Therefore, the aim of this research was to identify the Romanian consumer′s openness to technological autonomy and the degree of acceptance of IoT services and technologies to address the green deal principle of low energy consumption. This article investigated the factors that influence the decision to buy smart IoT devices and customers′ perception regarding the security of the data generated in this process. Based on the Technology Acceptance Model (TAM), this research proposed an alternative model consisting of 18 items measured on a Likert scale in order to identify the factors that contribute to the perceived value of the consumer and the behavioral precursors impacting the decision to purchase IoT products. More and more products have built-in sensors and through the Internet connection generate valuable data from a managerial point of view in relation to the customer. Although these data are expected to be of great value to companies, the way they are used is not always transparent and can affect the purchasing decisions and the behavior of IoT products′ customers. The findings of this paper aimed to better promote Smart Home IoT technologies and devices among Romanian people, making possible the control of consumption and the generation of energy savings.
A Modification of Newton–Raphson Power Flow for Using in LV Distribution System
Authors: Chanhome Anuwat , Chaitusaney Surachai
Published: November 2021

The Newton–Raphson (NR) method is still frequently applied for computing load flow (LF) due to its precision and quadratic convergence properties. To compute LF in a low voltage distribution system (LVDS) with unbalanced topologies, each branch model in the LVDS can be simplified by defining the neutral and ground voltages as zero and then using Kron’s reduction to transform into a 3 × 3 branch matrix, but this decreases accuracy. Therefore, this paper proposes a modified branch model that is also reduced into a 3 × 3 matrix but is derived from the impedances of the phase-A, -B, -C, neutral, and ground conductors together with the grounding resistances, thereby increasing the accuracy. Moreover, this paper proposes improved LF equations for unbalanced LVDS with both PQ and PV nodes. The improved LF equations are based on the polar-form power injection approach. The simulation results show the effectiveness of the modified branch model and the improved LF equations.
Conceptual Design and Hydrodynamic Performance of a Modular Hybrid Floating Foundation
Authors: Qu Xiaobin , Yao Yingxue , Du Jianjun
Published: November 2021

The comprehensive utilization of offshore renewable energies is an effective way to solve the intermittency and variability of power supply. This paper aims to present a hybrid floating system (HFS) based on a modular buoyancy-distributed floating foundation (BDFF) that can be equipped with a horizontal-axis wind turbine, solar panels, and wave energy converters (WEC). A simplified test model with a Froude scale ratio of 1/10 is employed to perform the experiments in a deep-water basin to validate the numerical results computed from the code program ANSYS AQWA based on the potential flow theory. The Response Amplitude Operators (RAOs) under regular waves are compared to evaluate the hydrodynamic performance. There is a good agreement in the surge, pitch, and heave RAOs for experiments and the numerical simulation, with a maximum of 6.45 degrees per meter for the pitch motion. Furthermore, the mooring tensions in the time domain are analyzed under different wave conditions.The tension RAOs from simulations are slightly higher than those from measurements with a maximum value at the period of 3.416 s. The mooring line on the windward side has a more considerable mooring tension that is far less than the allowable tensile strength, especially under the wave height of 2 m and the wave period of 2.873 s. The influence of loaded weight representing solar panels is weak, and the impact of winds is acceptable, as the platform deviates 1.3 degrees from the equilibrium state under the test wind speed. Eventually, the effect of irregular waves on the HFS is presented with the critical parameters of mooring tension and pitch motion. The results show that the HFS has a good motion performance.
Potential and Mechanisms for Stable C Storage in the Post-Mining Soils under Long-Term Study in Mitigation of Climate Change
Authors: Kowalska Aneta , Kucbel Marek , Grobelak Anna
Published: November 2021

Carbon storage in soil increases along with remediation of post-mining soils. Despite many studies on the issue of carbon sequestration in soils, there is a knowledge gap in the potential and mechanisms of C sequestration in post-mining areas. This research, including nuclear magnetic resonance analysis, determines the soil organic carbon formation progress in a long-term study of limestone (S1), and lignite (S2) post-mining soil under different remediation stages. The main remediation target is reforesting; however, S2 was previously amended with sewage sludge. The study showed that for S1, the O-alkyl groups were the dominant fraction in sequestered soil. However, for S2, increased fractions of acetyl-C and aromatic C groups within remediation progress were observed. The remediation of S1 resulted in improved hydrophobicity and humification; however, the decrease in aromatic groups’ formation and C/N ratio was noted. For S2, we noticed an increase for all indicators for sequestered C stability, which has been assigned to the used sewage sludge in remediation techniques. While both post-mining soils showed huge potential for C sequestration, S2 showed much higher properties of sequestered C indicating its higher stabilization which can suggest that soils non-amended with sewage sludge (S1) require more time for stable storage of C.
Efficient n-i-p Monolithic Perovskite/Silicon Tandem Solar Cells with Tin Oxide via a Chemical Bath Deposition Method
Authors: Hyun Jiyeon , Yeom Kyung Mun , Lee Ha Eun , Kim Donghwan , Lee Hae-Seok , Noh Jun Hong , Kang Yoonmook
Published: November 2021

Tandem solar cells, based on perovskite and crystalline silicon absorbers, are promising candidates for commercial applications. Tin oxide (SnO2), applied via the spin-coating method, has been among the most used electron transfer layers in normal (n-i-p) perovskite/silicon tandem cells. SnO2 synthesized by chemical bath deposition (CBD) has not yet been applied in tandem devices. This method shows improved efficiency in perovskite single cells and allows for deposition over a larger area. Our study is the first to apply low-temperature processed SnO2 via CBD to a homojunction silicon solar cell without additional deposition of a recombination layer. By controlling the reaction time, a tandem efficiency of 16.9% was achieved. This study shows that tandem implementation is possible through the CBD method, and demonstrates the potential of this method in commercial application to textured silicon surfaces with large areas.
Influence of the Hydrophilic Surface of Nanofiber Support on the Performance of Hybrid Supercapacitors
Authors: Kim Hyo-Young , Lee Seon-Yeong , Jeon In-Yup , Shin Jeeyoung , Ju Young-Wan
Published: November 2021

Concerns associated with global warming and the depleting reserves of fossil fuels have highlighted the importance of high−performance energy storage systems (ESSs) for efficient energy usage. ESSs such as supercapacitors can contribute to improved power quality of an energy generation system, which is characterized by a slow load response. Composite materials are primarily used as supercapacitor electrodes because they can compensate for the disadvantages of carbon or metal oxide electrode materials. In this study, a composite of oxide nanoparticles loaded on a carbon nanofiber support was used as an electrode material for a hybrid supercapacitor. The addition of a small amount of hydrophilic FeN@GnP (Fe− and N−doped graphene nanoplates) modified the surface properties of carbon nanofibers prepared by electrospinning. Accordingly, the effects of the hydrophobic/hydrophilic surface properties of the nanofiber support on the morphology of Co3O4 nanoparticles loaded on the nanofiber, as well as the performance of the supercapacitor, were systematically investigated.
Influence of Upstream Disturbances on the Vortex Structure of Francis Turbine Based on the Criteria of Identification of Various Vortexes
Authors: Guo Tao , Xu Lihui , Wang Wenquan
Published: November 2021

The inter-blade passage vortex, the vortex rope of the draft tube, and the vortex in the guide apparatus are the characteristics of flow instability of the Francis turbine, which may lead to fatigue failure in serious cases. In the current study, in order to accurately capture the transient turbulent characteristics of flow under different conditions and fully understand the flow field and vortex structure, we conduct a simulation that adopts sliding grid technology and the large-eddy simulation (LES) method based on the wall-adapting local eddy viscosity (WALE) model. Using the pressure iso-surface method, the Q criterion, and the latest third-generation Liutex vortex identification method, this study analyzes and compares the inter-blade passage vortex, the vortex rope of the draft tube, and the outflow and vortex in the guide apparatus, focusing on the capture ability of flow field information by various vortex identification methods and the unique vortex structure under the condition of a small opening. The results indicate that the dependence of Liutex on the threshold is small, and the scale range of the flow direction vortex captured by Liutex is wider, but the ability of the spanwise vortex is relatively weak. The smaller the opening, the more disorderly the vortexes generated in each component and the more unstable the flow field. In the draft tube, the original shape of the vortex rope is destroyed due to the interaction between vortexes. Under the condition of a small opening, an inter-blade passage vortex is generated, affecting the efficient and stable operation of the turbine.
Impact of Tumbling Process on the Toughness and Structure of Raw Beef Meat Pieces
Authors: N’Gatta Konan Charles Aimeric , Kondjoyan Alain , Favier Raphael , Rouel Jacques , Vénien Annie , Astruc Thierry , Gruffat Dominique , Mirade Pierre-Sylvain
Published: November 2021

Tenderness is a major factor in consumer perception and acceptability of beef meat. Here we used a laboratory tumbling simulator to investigate the effectiveness of the tumbling process in reducing the toughness of raw beef cuts. Twelve Semitendinosus beef muscles from cows were tumbled according to four programs: T1 (2500 consecutive compression cycles (CC), for about 3 h), T2 (6000 CC, about 7.5 h), T3 (9500 CC, about 12 h), and T4 (13,000 CC, about 16 h). The effect of tumbling on the toughness of raw meat was assessed using compression tests (stresses measured at 20% and 80% of deformation ratios) and microscopic observations made at the periphery and centre of meat samples, and compared against non-tumbled controls. Longer tumbling times significantly reduced the stresses measured at 20% and 80% compression rates, which reflected the toughness of muscle fibres and connective tissue, respectively. At the microscopic level, longer tumbling times led to reduced extracellular spaces, increased degradation of muscle structure, and the emergence of amorphous zones. A 12-h tumbling protocol ultimately makes the best compromise between the process time demand and toughness reduction in beef Semitendinosus meat pieces.
The Mutational Landscape of PTK7 in Congenital Scoliosis and Adolescent Idiopathic Scoliosis
Authors: Su Zhe , Yang Yang , Wang Shengru , Zhao Sen , Zhao Hengqiang , Li Xiaoxin , Niu Yuchen ,   Deciphering Disorders Involving Scoliosis and COmorbidities (DISCO) Study Group, Qiu Guixing , Wu Zhihong , Wu Nan , Zhang Terry Jianguo
Published: November 2021

Depletion of ptk7 is associated with both congenital scoliosis (CS) and adolescent idiopathic scoliosis (AIS) in zebrafish models. However, only one human variant of PTK7 has been reported previously in a patient with AIS. In this study, we systemically investigated the variant landscape of PTK7 in 583 patients with CS and 302 patients with AIS from the Deciphering Disorders Involving Scoliosis and COmorbidities (DISCO) study. We identified a total of four rare variants in CS and four variants in AIS, including one protein truncating variant (c.464_465delAC) in a patient with CS. We then explored the effects of these variants on protein expression and sub-cellular location. We confirmed that the c.464_465delAC variant causes loss-of-function (LoF) of PTK7. In addition, the c.353C>T and c.2290G>A variants identified in two patients with AIS led to reduced protein expression of PTK7 as compared to that of the wild type. In conclusion, LoF and hypomorphic variants are associated with CS and AIS, respectively.
On the Origin and Evolution of Drosophila New Genes during Spermatogenesis
Authors: Su Qianwei , He Huangyi , Zhou Qi
Published: November 2021

The origin of functional new genes is a basic biological process that has significant contribution to organismal diversity. Previous studies in both Drosophila and mammals showed that new genes tend to be expressed in testes and avoid the X chromosome, presumably because of meiotic sex chromosome inactivation (MSCI). Here, we analyze the published single-cell transcriptome data of Drosophila adult testis and find an enrichment of male germline mitotic genes, but an underrepresentation of meiotic genes on the X chromosome. This can be attributed to an excess of autosomal meiotic genes that were derived from their X-linked mitotic progenitors, which provides direct cell-level evidence for MSCI in Drosophila. We reveal that new genes, particularly those produced by retrotransposition, tend to exhibit an expression shift toward late spermatogenesis compared with their parental copies, probably due to the more intensive sperm competition or sexual conflict. Our results dissect the complex factors including age, the origination mechanisms and the chromosomal locations that influence the new gene origination and evolution in testes, and identify new gene cases that show divergent cell-level expression patterns from their progenitors for future functional studies.
Longitudinal Rise in Seroprevalence of SARS-CoV-2 Infections in Children in Western Germany—A Blind Spot in Epidemiology?
Authors: Brinkmann Folke , Diebner Hans H. , Matenar Chantal , Schlegtendal Anne , Spiecker Jan , Eitner Lynn , Timmesfeld Nina , Maier Christoph , Lücke Thomas
Published: November 2021

SARS-CoV-2 infection rates in children and adolescents are often underestimated due to asymptomatic or oligosymptomatic infections. Seroprevalence studies can reveal the magnitude of “silent” infections in this age group and help to assess the risk of infection for children but also their role in spreading the disease. In total, 2045 children and their parents from the Ruhr region were finally included after the exclusion of drop-outs. Seroconversion rates among children of all age groups increased from 0.5% to 8% during the study period and were about three to fourfold higher than the officially registered PCR-based infection rates. Only 41% recalled symptoms of infection; 59% were asymptomatic. In 51% of the infected children, at least one parent also developed SARS-CoV-2 antibodies. Depending on local incidences, the rates of seroconversion rose to different levels during the study period. Although the dynamics of infection within the study cohort mirrors local incidence, the figure of SARS-CoV-2 infections in children and adolescents appears to be high. Reported contact with SARS-CoV-2-infected individuals in the same household carries a high risk of infection.
Predictors of Major Depressive Disorder in Older People
Authors: Sousa Susana , Paúl Constança , Teixeira Laetitia
Published: November 2021

Major depressive disorder (MDD) is one of the most common mental disorders in older people. There are several biological, psychological, and social factors associated with this disorder. This study aimed to describe the depressive state to identify the associated factors and potential predictors of MDD in a population of community-dwelling older people with probable MDD. The sample consisted of 378 participants with probable dementia, with 47.3% of them presenting MDD. The factors that were found to be associated with MDD were sex, living status, mobility, and nutritional status. Knowing the factors that can predict a condition such as MDD is extremely important, both for prevention and for the customization of interventions.
Reduction in Blood Lead Concentration in Children across the Republic of Georgia following Interventions to Address Widespread Exceedance of Reference Value in 2019
Authors: Ruadze Ekaterine , Leonardi Giovanni S. , Saei Ayoub , Khonelidze Irma , Sturua Lela , Getia Vladimer , Crabbe Helen , Marczylo Tim , Lauriola Paolo , Gamkrelidze Amiran
Published: November 2021

In recent years, reports of lead contamination have dramatically increased in Georgia. Given concerns about the exposure of children to lead (Pb), the National Multiple Indicator Cluster Survey (MICS-2018) included a blood sampling component. The results showed that 41% of the children that participated had blood Pb levels (BLL) ≥ 5 µg/dL and that BLL in children living in Western Georgia were higher than those in Eastern regions. In response to these findings, NCDC implemented written and verbal advice to the families of children who participated in the MICS-2018 on how to reduce Pb exposure. From August 2019 onwards, the state program of clinical follow-up was implemented. The design of this study was a longitudinal study. The intervention of interest was the public health advice and medical follow-up, and the outcome was defined as the difference in BLL between the MICS-2018 survey and the state program follow-up. We observed a significant overall reduction in median BLL between MICS-2018 and state program follow-up in both August 2019 and the latest results (until December 2019). However, we did not observe any significant further reduction between August and the most recent BLL results. In the Georgian setting, written and verbal communication targeting individual households, alongside home visits to the most exposed, effectively reduced BLL in children.
Tell Me about Loneliness: Interviews with Young People about What Loneliness Is and How to Cope with It
Authors: Verity Lily , Schellekens Tine , Adam Tine , Sillis Floor , Majorano Marinella , Wigelsworth Michael , Qualter Pamela , Peters Beth , Stajniak Stephanie , Maes Marlies
Published: November 2021

Background: loneliness is a common experience for adolescents, yet the voices of adolescents are missing from current conceptualisations of loneliness. That means, measures that have been created based on current conceptualisations may miss important contexts of adolescence, such as the roles of friendships, that determine the way loneliness is experienced. The current study aims to centre adolescent voices to identify how they conceptualise loneliness and what strategies they consider to be useful for adolescents to cope with loneliness. Method: thematic framework analysis (TFA) was conducted on qualitative interviews with young people aged 8–14 years in Belgium and Italy to identify salient themes in their conceptualisations of loneliness. Results: Loneliness was conceptualised as a negative emotional state involving negative thinking patterns that occurs when an individual perceives they are missing out on a desired aspect in their social relationships. Coping strategies related to alleviating negative affect, and aiding social reconnection. Conclusions: friendships with peers were understood to be central to adolescent loneliness experiences. In line with that, loneliness was seen to be experienced at school. Age-related differences in friendship expectations were identified, highlighting how developmental needs relate to the loneliness experience.
Effects of High-Intensity Interval Training and Moderate-Intensity Continuous Training on Cardiometabolic Risk Factors in Overweight and Obesity Children and Adolescents: A Meta-Analysis of Randomized Controlled Trials
Authors: Cao Meng , Tang Yucheng , Li Shu , Zou Yu
Published: November 2021

Background: The purpose of this review was to compare the effectiveness of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on cardiometabolic risk factors of obese children and adolescents. Methods: Relevant studies published in PubMed, MEDLINE and Web of Science databases were searched. Only randomized controlled trials (RCTs) that examined the effect of HIIT and MICT on children and adolescents with obesity were included. Meta-analyses were conducted to determine the effect of HIIT on cardiometabolic risk factors using STATA software and potential moderators were explored (i.e., study duration, training modalities, work/rest ratio and work duration time). Results: Twelve RCTs involving 325 participants were included in the meta-analysis. HIIT showed more positive effects on maximal oxygen uptake (VO2max; SMD = 0.87, 95% CI: 0.39 to 1.35, p = 0.000) and systolic blood pressure (SBP; SMD = −0.64, 95% CI: −1.05 to −0.22, p = 0.003) than MICT. However, when compared with MICT, HIIT caused no significant differences in body weight, body mass index, body fat percentage, diastolic blood pressure and glycolipid metabolism markers. Furthermore, subgroup analysis showed that the effects of HIIT on VO2max and SBP were significantly different regarding protocol factors, such as modality, duration, training time, training settings, work/rest ratio and work duration. Conclusions: HIIT has a positive role in promoting cardiometabolic risk factors in obese children and adolescents. Moreover, when compared with MICT, HIIT had a more significant effect on improving cardiorespiratory fitness and systolic blood pressure. The factors of HIIT protocol had an important influence on the intervention effects of childhood obesity.
The Impact of COVID-19 on Preschool-Aged Children’s Movement Behaviors in Hong Kong: A Longitudinal Analysis of Accelerometer-Measured Data
Authors: Ng Johan Y. Y. , He Qing , Chong Kar Hau , Okely Anthony D. , Chan Cecilia H. S. , Ha Amy S.
Published: November 2021

During the COVID-19 pandemic, many preschool-aged children were forced to remain indoors due to social distancing measures and school closures. In this study, we examined how children’s movement behaviors (sedentary behaviors, physical activity, and sleep) were affected by the pandemic. Children’s (N = 25, age = 4.4 years, SD = 0.3) movement behaviors were measured before and after the COVID outbreak, respectively. Data collected using accelerometers were analyzed using compositional data analyses. A significant change in the overall time-use composition (F = 5.89, p = 0.002) was found. Results suggested that children spent more time sleeping (8% increase) and in moderate-to-vigorous physical activity (16% increase), with less time spent in sedentary behaviors (9% decrease). However, parent reports suggested that children were less active and had more screen time. In conclusion, the current evidence suggests that children’s physical activity is not negatively impacted by the pandemic. However, the continuous surveillance of movement behaviors of young children during the pandemic is needed.
Key Parameters Affecting Kick Start Performance in Competitive Swimming
Authors: Matúš Ivan , Ružbarský Pavel , Vadašová Bibiana
Published: November 2021

The study aims to determine the contribution of kinematic parameters to time to 5 m without underwater undulating and kicking. Eighteen male competitive swimmers started from three weighted positions and set the kick plate to positions 1–5. We used SwimPro cameras and the Dartfish© software. In the on-block phase, we found significant correlations (p < 0.01) between the front ankle angle and block time. The correlations between start phases were statistically significant (p < 0.01) between block time and rear ankle angle, respectively, to time to 2 m; rear knee angle and glide time; block time and time to 5 m; time to 2 m and time to 5 m; and flight distance and glide distance. The multiple regression analysis showed that the on-block phase and flight phase parameters, respectively, contributed 64% and 65% to the time to 5 m. The key block phase parameters included block time and rear knee angle. The key flight phase parameters determining time to 5 m included take-off angle and time to 2 m. The key parameters determining the performance to 5 m during the above-water phase include rear knee angle, block time, takeoff angle, and time to 2 m.
Spatial Variations and Influencing Factors of River Networks in River Basins of China
Authors: Zheng Yuanhuan , Yu Chunxue , Zhou Huabin , Xiao Jiannan
Published: November 2021

Analysis of the spatial variations in river networks and the related influencing factors is crucial for the management and protection of basins. To gain insight into the spatial variations and influencing factors of river networks between large basins, in this study, three river basins from north to south in China (Songhua River Basin, Yellow River Basin and Pearl River Basin) were selected for investigation. First, based on a digital elevation model, different river networks with six drainage accumulation thresholds of three basins were extracted using ArcGIS. The optimal networks were determined through fitting the relationship between the accumulation threshold and related drainage density. Then, we used two indicators, drainage density and water surface ratio, to characterize the spatial variations of three basins. Finally, Pearson’s correlation coefficients were calculated between those two indicators and natural/human influencing factors. The results showed that drainage density and water surface ratio decreased from north to south in China and were negatively correlated with natural/human influencing factors. Drainage density was more influenced by natural factors than by human factors, while the opposite was true for water surface ratio. These findings may provide some basis for the management and protection of the river network.
Parents’ and Early Childhood Educators’ Perceptions on Movement and Learning Program Implementation
Authors: Mavilidi Myrto F. , Bennett Sue , Paas Fred , Okely Anthony D. , Vazou Spyridoula
Published: November 2021

There is currently limited evidence on parents’ and early childhood educators’ perspectives on implementing programs that combine cognitive and motor tasks in early childhood. An online survey was distributed across Australia through social network platforms and emails at preschool centres, asking 65 parents of preschool children and early childhood educators about their preferences on program delivery, duration, and mode. Responses from the survey were evaluated in order to develop and pilot a 4 week home-based (n = 5 parents) and a 6 week school-based program (n = 5 educators) including cognitively engaging physical activity, requesting parents’ and educators’ perspectives, respectively, about the program components. Results from the online survey showed a preference for programs with online (e.g., video-based) compared to traditional delivery (e.g., books), emphasising the potential benefits on children’s physical activity levels, sleep, and cognitive function. However, after piloting the program, educators preferred to use the book version instead of the video. This program has the potential to become part of daily regular practice. Barriers reported include logistics issues (i.e., book size), connectivity issues with internet, and the need for varying activities.