bluuebunny/crossref_metadata_2025 huggingface dataset:
Interventions to address food insecurity among Aboriginal and Torres Strait Islander people: a rapid review
Authors: McKay Fiona H. , Godrich Stephanie L.
Published: October 2021

Food insecurity disproportionately impacts Aboriginal and Torres Strait Islander Australians. This review sought to investigate research and evaluations of programs and interventions implemented to address food insecurity among Aboriginal and Torres Strait Islander communities. A rapid review was conducted to collate the available research from 6 databases. The search was conducted in May 2020. Search constructs related to food insecurity, Aboriginal and Torres Strait Islander people, and Australia. Twenty-five publications were included in this review, 24 reported on an intervention, while 9 were evaluations of an intervention. Interventions included behaviour change projects, including projects that sought to change purchasing and cooking behaviours, school-based education programs, and gardening programs. In general, the studies included in this sample were small and lacked a systematic consideration of the factors that shape the experience of food insecurity among Aboriginal and Torres Strait Islander people specifically. Based on the findings of this review, authors suggest greater consideration to the systematic determinants of food insecurity among Aboriginal and Torres Strait Islander communities to have lasting and sustainable impact on food insecurity. This review has been registered with the international prospective register of systematic reviews (PROSPERO: CRD42020183709).

Novelty: Food insecurity among Aboriginal and Torres Strait Islander people poses significant risk to health and wellbeing. Small-scale food security interventions may not provide ongoing and sustained impact. Any intervention to promote food security will need to involve Aboriginal and Torres Strait Islander people and be sustained once external parties have left.
Inclusion of sprints during moderate-intensity continuous exercise enhances post-exercise fat oxidation in young males
Authors: Mello-Silva Bruno Nicanor , Protzen Gabriel Völz , Del Vecchio Fabrício Boscolo
Published: October 2021

To assess the physiological demands of including high-intensity efforts during continuous exercise, we designed a randomized crossover study, in which 12 physically active young males executed 3 different exercises in random order: FATmax – continuous exercise at the highest fat oxidation zone; 2min-130% – FATmax interspersed by a 2-minute bout at 130% of the maximal oxygen uptake associated intensity (iV̇O2max); and 20s:10s-170% – FATmax interspersed by four 20-s bouts at 170%iV̇O2max interpolated by 10s of passive recovery. We measured oxygen uptake (V̇O2), blood lactate concentration ([LAC]), respiratory exchange rate (RER), and fat and carbohydrate (CHO) oxidation. For statistical analyses, repeated-measures ANOVA was applied. Although no differences were found for average V̇O2 or carbohydrate oxidation rate, the post-exercise fat oxidation rate was 37.5% and 50% higher during the 2min-130% and 20s:10s-170% protocols, respectively, compared with the FATmax protocol, which also presented lower values of RER during exercise compared with 2min-130% and 20s:10s-170% (p < 0.001 in both), and higher values post-exercise (p = 0.04 and p = 0.002, respectively). [LAC] was higher during exercise when high-intensity bouts were applied (p < 0.001 for both) and was higher at post-exercise during the intermittent bouts compared with FATmax (p = 0.016). The inclusion of high-intensity efforts during moderate-intensity continuous exercise promoted higher physiological demands and post-exercise fat oxidation.

Novelty: The inclusion of 2-minute efforts modifies continuous exercise demands. Maximal efforts can increase post-exercise fat oxidation. 2-minute maximal efforts, continuous or intermittent, presents similar demands.
Quantifying the Generation Process of Multi-Level Tactile Sensations via ERP Component Investigation
Authors: Liu Yuan , Wang Wenjie , Xu Weiguo , Cheng Qian , Ming Dong
Published: October 2021

Humans obtain characteristic information such as texture and weight of external objects, relying on the brain’s integration and classification of tactile information; however, the decoding mechanism of multi-level tactile information is relatively elusive from the temporal sequence. In this paper, nonvariant frequency, along with the variant pulse width of electrotactile stimulus, was performed to generate multi-level pressure sensation. Event-related potentials (ERPs) were measured to investigate the mechanism of whole temporal tactile processing. Five ERP components, containing P100–N140–P200–N200–P300, were observed. By establishing the relationship between stimulation parameters and ERP component amplitudes, we found the following: (1) P200 is the most significant component for distinguishing multi-level tactile sensations; (2) P300 is correlated well with the subjective judgment of tactile sensation. The temporal sequence of brain topographies was implemented to clarify the spatiotemporal characteristics of the tactile process, which conformed to the serial processing model in neurophysiology and cortical network response area described by fMRI. Our results can help further clarify the mechanism of tactile sequential processing, which can be applied to improve the tactile BCI performance, sensory enhancement, and clinical diagnosis for doctors to evaluate the tactile process disorders by examining the temporal ERP components.
Generalized Darboux transformation and higher-order rogue wave solutions to the Manakov system
Authors: Mukam Serge P. , Abbagari Souleymanou , Houwe Alphonse , Kuetche Victor K. , Inc Mustafa , Doka Serge Y. , Bouetou Thomas B. , Akinlar Mehmet Ali
Published: October 2021

In this paper, we propose a recursive Darboux transformation in a generalized form of a focusing vector Nonlinear Schrödinger Equation (NLSE) known as the Manakov System. We apply this generalized recursive Darboux transformation to the Lax-pairs of this system in view of generating the Nth-order vector generalization rogue wave solutions with a rule of iteration. We discuss from first- to three-order vector generalizations of rogue wave solutions while illustrating these features with some 3D, 2D graphical depictions. We illustrate a clear connection between higher-order rogue wave solutions and their free parameters for better understanding the physical phenomena described by the Manakov system
Collective model with isovector pair and alpha-particle-type correlations
Authors: Jolos R. V. , Kolganova E. A. , Sazonov D. A.
Published: October 2021

The collective Hamiltonian including isovector pairing and [Formula: see text]-particle-type correlation degrees of freedom is constructed. The Hamiltonian is applied to description of the relative energies of the ground states of even–even nuclei around [Formula: see text]Ni. A satisfactory description of the experimental data is obtained. A significant improvement of the agreement with the experimental data compared to our previous calculations is explained by inclusion in the Hamiltonian of the dynamical variables describing [Formula: see text]-particle-type correlations.
Hamiltonian Cycles Passing Through Prescribed Edges in Locally Twisted Cubes
Authors: Cheng Dongqin
Published: October 2021

Let [Formula: see text] be a set of edges whose induced subgraph consists of vertex-disjoint paths in an [Formula: see text]-dimensional locally twisted cube [Formula: see text]. In this paper, we prove that if [Formula: see text] contains at most [Formula: see text] edges, then [Formula: see text] contains a Hamiltonian cycle passing through every edge of [Formula: see text], where [Formula: see text]. [Formula: see text] has a Hamiltonian cycle passing through at most one prescribed edge.
Cosmological constant, axial anomalies and photon mass dynamos from chiral fermionic torsion
Authors: Garcia de Andrade L. C.
Published: October 2021

Motivated by Palle’s investigation on the handness of chirality of vorticity in Einstein–Cartan cosmology [Entropy 5 (2014)], several aspects of chiral torsional handness in magnetogenesis and cosmology are presented. In the first one, we obtain torsion bounds from massive photons and axial anomalies. In the second, we deal with magnetogenesis from photon mass and in the third, we discuss chiral torsion degrees of freedom to obtain a torsion cosmological constant dependent solution. The torsion solution decays fast and implies a strong suppression of torsion at present universe. Our result contains the Poplawski [Phys. Lett. B (2010)] results in the case axial torsion vector associated to Einstein–Cartan fermionic sector matter and conformal anomalies of quarks. In the third example, a magnetic field bound from chiral torsionic dynamos is obtained as [Formula: see text]. In the non-minimal cosmological models, chiral dynamos are sourced by massive photons, London currents and chiral magnetic effect (CME). Chiral chemical potential is found to be mimic by torsion. Cosmological constant bound [Formula: see text] is found. At the early universe, the cosmological constant [Formula: see text] is obtained. Torsion used in the present universe is [Formula: see text]. In the last and fourth example, chiral anisotropic currents are obtained and magnetic helicity is shown to depend upon torsion when the chiral chemical potential is non-constant.
Characterization of Matrix Classes Transforming Between Almost Sure Convergent Sequences of Complex Uncertain Variables
Authors: Das Birojit , Debnath Piyali , Tripathy Binod Chandra
Published: October 2021

The study of uncertainty theory evolved and developed largely in the last decade. In this paper, we introduce the concept of summability and absolutely summability with respect to almost surely through matrix transformation of complex uncertain sequences and establish the interrelationship between these two concepts. In this context, applications of matrix transformation of complex uncertain sequences are also presented.
Virtual Screening-Based Identification of Potent DENV-3 RdRp Protease Inhibitors via In-House Usnic Acid Derivative Database
Authors: Roney Miah , Huq AKM Moyeenul , Rullah Kamal , Hamid Hazrulrizawati Abd , Imran Syahrul , Islam Md. Alimul , Mohd Aluwi Mohd Fadhlizil Fasihi
Published: October 2021

Dengue virus (DENV) is the causative agent of dengue fever, dengue hemorrhagic disease and dengue shock syndrome (DSS), transmitted predominantly in tropical and subtropical regions by Aedes aegypti. It infects millions of people and causes thousands of deaths each year, but there is no antiviral drug against DENV. Usnic acid lately piqued the interest of researchers for extraordinary biological characteristics, including antiviral activity. Based on high larvicidal activities against Aedes aegypti, this study aims to search usnic acid derivatives as novel anti-DENV agents through a combination of ligand-based and pharmacophore-based virtual screening. One hundred and sixteen (116) usnic acid derivatives were obtained from a database of 428 in-house usnic acid derivatives through pharmacophore filtering steps. Subsequent docking simulation on DENV-3 NS-5 RdRp afforded 41 compounds with a strong binding affinity towards the enzyme. The pharmacokinetics and drug likeness prediction resulted in seven hit compounds, which eventually undergo cytochrome P450 enzyme screening to obtain the lead compound, labelled as 362. In addition, molecular dynamic (MD) simulation of lead compound 362 was performed to verify the stability of the docked complex and the binding posture acquired in docking experiments. Overall, the lead compounds have shown a high fit value of pharmacophore, strong binding affinity towards RdRp enzyme, good pharmacokinetics, and drug likeness properties. The discovery of a new usnic acid derivative as a novel anti-DENV agent targeting RdRp could lead to further drug development and optimization to treat dengue.
New onshore insights into the role of structural inheritance during Mesozoic opening of the Inner Moray Firth Basin, Scotland
Authors: Tamas Alexandra , Holdsworth Robert E. , Underhill John R. , Tamas Dan M. , Dempsey Edward D. , Hardman Kit , Bird Anna , McCarthy Dave , McCaffrey Ken J.W. , Selby David
Published: October 2021

The Inner Moray Firth Basin (IMFB) forms the western arm of the North Sea trilete rift system that initiated mainly during the Late Jurassic–Early Cretaceous with the widespread development of major NE–SW-trending dip-slip growth faults. The IMFB is superimposed over the southern part of the older Devonian Orcadian Basin. The potential influence of older rift-related faults on the kinematics of later Mesozoic basin opening has received little attention, partly owing to the poor resolution of offshore seismic reflection data at depth. New field observations augmented by drone photography and photogrammetry, coupled with U–Pb geochronology, have been used to explore the kinematic history of faulting in onshore exposures along the southern IMFB margin. Dip-slip north–south- to NNE–SSW-striking Devonian growth faults are recognized that have undergone later dextral reactivation during NNW–SSE extension. The U–Pb calcite dating of a sample from the synkinematic calcite veins associated with this later episode shows that the age of fault reactivation is 130.99  ±  4.60 Ma (Hauterivian). The recognition of dextral-oblique Early Cretaceous reactivation of faults related to the underlying and older Orcadian Basin highlights the importance of structural inheritance in controlling basin- to sub-basin-scale architectures and how this influences the kinematics of IMFB rifting.

Supplementary material:
Analytical protocols and analysed sample details are available at
https://doi.org/10.6084/m9.figshare.c.5635432
3D modelling and capacity estimation of potential targets for CO
2
storage in the Adriatic Sea, Italy
Authors: Proietti Giampaolo , Cvetković Marko , Saftić Bruno , Conti Alessia , Romano Valentina , Bigi Sabina
Published: October 2021

One of the most innovative and effective technologies developed in recent decades for reducing carbon dioxide emissions to the atmosphere is carbon capture and storage (CCS). It consists of capture, transport and injection of CO
2
produced by energy production plants or other industries. The injection takes place in deep geological formations with the suitable geometrical and petrophysical characteristics to trap CO
2
permanently in the subsurface, which is called geological storage. In the development process of a potential geological storage site, correct capacity estimation of the injectable volumes of CO
2
is one of the most important aspects. There are various approaches to estimate CO
2
storage capacities for potential traps, including geometrical equations, dynamic modelling, numerical modelling and 3D modelling. In this work, the generation of 3D petrophysical models and equations for calculation of the storage volumes are used to estimate the effective storage capacity of four potential saline aquifers in the Adriatic Sea offshore. The results show how different saline aquifers, with different lithologies at favourable depths, can host a reasonable amount of CO
2
, which will require further and more detailed feasibility studies for each of these structures. A detailed analysis is carried out for each saline aquifer identified, varying the parameters of each structure identified and adapting them for a realistic estimate of potential geological storage capacity.

Thematic collection:
This article is part of the Geoscience for CO
2
storage collection available at:
https://www.lyellcollection.org/cc/geoscience-for-co2-storage
Whole Inactivated Virus and Protein-Based COVID-19 Vaccines
Authors: Hotez Peter J. , Bottazzi Maria Elena
Published: October 2021

The rapid development and deployment of mRNA and adenovirus-vectored vaccines against coronavirus disease 2019 (COVID-19) continue to astound the global scientific community, but these vaccine platforms and production approaches have still not achieved global COVID-19 vaccine equity. Immunizing the billions of people at risk for COVID-19 in the world's low- and middle-income countries (LMICs) still relies on the availability of vaccines produced and scaled through traditional technology approaches. Vaccines based on whole inactivated virus (WIV) and protein-based platforms, as well as protein particle-based vaccines, are the most produced by LMIC vaccine manufacturing strategies. Three major WIV vaccines are beginning to be distributed widely. Several protein-based and protein particle-based vaccines are advancing with promising results. Overall, these vaccines are exhibiting excellent safety profiles and in some instances have shown their potential to induce high levels of virus neutralizing antibodies and T cell responses (and protection) both in nonhuman primates and in early studies in humans. There is an urgent need to continue accelerating these vaccines for LMICs in time to fully vaccinate these populations by the end of 2022 at the latest. Achieving these goals would also serve as an important reminder that we must continue to maintain expertise in producing multiple vaccine technologies, rather than relying on any individual platform.
Informal (Field-Based) Learning
Authors: Tannenbaum Scott I. , Wolfson Mikhail A.
Published: October 2021

Most learning in the workplace occurs outside of formal learning environments—it happens informally, “in the field.” In this review, we share what is known about how such informal field-based learning (IFBL) works, offer guidance on how to promote healthy IFBL, and identify future research needs. We first situate IFBL within the broader stream of the learning literature. On the basis of the literature and organizational needs, we propose a CAM-OS framework that emphasizes five personal and situational readiness factors for enabling constructive IFBL: Capability, Awareness, Motivation, Opportunity, and Support. We use the framework to offer practical, evidence-based advice for each of three stakeholder groups—senior leaders, managers, and employees—and conclude with suggested avenues for future research. The review is grounded in the research literature with an emphasis on implications for practice.
Physiological Functions of CRAC Channels
Authors: Emrich Scott M. , Yoast Ryan E. , Trebak Mohamed
Published: October 2021

Store-operated Ca2+entry (SOCE) is a ubiquitous Ca2+signaling pathway that is evolutionarily conserved across eukaryotes. SOCE is triggered physiologically when the endoplasmic reticulum (ER) Ca2+stores are emptied through activation of inositol 1,4,5-trisphosphate receptors. SOCE is mediated by the Ca2+release-activated Ca2+(CRAC) channels, which are highly Ca2+selective. Upon store depletion, the ER Ca2+-sensing STIM proteins aggregate and gain extended conformations spanning the ER–plasma membrane junctional space to bind and activate Orai, the pore-forming proteins of hexameric CRAC channels. In recent years, studies on STIM and Orai tissue-specific knockout mice and gain- and loss-of-function mutations in humans have shed light on the physiological functions of SOCE in various tissues. Here, we describe recent findings on the composition of native CRAC channels and their physiological functions in immune, muscle, secretory, and neuronal systems to draw lessons from transgenic mice and human diseases caused by altered CRAC channel activity.
Displacement Measurements and Numerical Analysis of Long‐Term Rock Slope Deformation at Higashi‐Shikagoe Limestone Quarry, Japan
Authors: Amagu Clement A. , Zhang Cheng , Kodama Jun-ichi , Shioya Kazuyuki , Yamaguchi Tomoyuki , Sainoki Atsushi , Fukuda Daisuke , Fujii Yoshiaki , Sharifzadeh Mostafa
Published: October 2021

The Higashi‐Shikagoe limestone quarry is an open‐pit mine situated in Hokkaido Prefecture, Japan, that has experienced four slope failure incidents since 1996. The rock slope behaviour has been monitored since the first failure event by measuring the rock slope surface displacement using an automated polar system. Recent measurements have revealed a gradual decrease of the distance between the beam generator and mirrors over time; however, the displacements and decrease rate differs between the centre and left‐ and right‐hand sides of the quarry. This implies that the deformation characteristics of the rock slope and factors influencing the slope deformation differ at the centre and left‐ and right‐hand sides of the quarry. In this study, the two‐dimensional finite element method was used to identify the causes of slope deformation by investigating the effects of limestone excavation at the foot of the rock slope, the deterioration of a ∼70 m‐thick clay layer at the rock slope foot wall, and shear failure owing to rainfall infiltration. The numerical results show that slope deformation on the left‐hand side and centre of the quarry are induced by clay deterioration, whereas the right‐hand side of the quarry is deformed owing to floor excavation and/or shear sliding. The rock slope is presently stable because the magnitude of the rate of displacement decrease is small and no acceleration is observed.
A New Method of Central Axis Extracting for Pore Network Modeling in Rock Engineering
Authors: Guo Xiao , Yang Kairui , Jia Haowei , Tao Zhengwu , Xu Mo , Dong Baozhu , Liu Lei
Published: October 2021

Characterizing internal microscopic structures of porous media is of vital importance to simulate fluid and electric current flow. Compared to traditional rock mechanics and geophysical experiments, digital core and pore network modeling is attracting more interests as it can provide more details on rock microstructure with much less time needed. The axis extraction algorithm, which has been widely applied for pore network modeling, mainly consists of a reduction and burning algorithm. However, the commonly used methods in an axis extraction algorithm have the disadvantages of complex judgment conditions and relatively low operating efficiency, thus losing the practicality in application to large-scale pore structure simulation. In this paper, the updated algorithm proposed by Palágyi and Kuba was used to perform digital core and pore network modeling. Firstly, digital core was reconstructed by using the Markov Chain Monte Carlo (MCMC) method based on the binary images of a rock cutting plane taken from heavy oil reservoir sandstone. The digital core accuracy was verified by comparing porosity and autocorrelation function. Then, we extracted the central axis of the digital pore space and characterize structural parameters through geometric transformation technology and maximal sphere method. The obtained geometric parameters were further assigned to the corresponding nodes of pore and throat on the central axis of the constructed model. Moreover, the accuracy of the new developed pore network model was measured by comparing pore/throat parameters, curves of mercury injection, and oil-water relative permeability. The modeling results showed that the new developed method is generally effective for digital core and pore network simulation. Meanwhile, the more homogeneity of the rock, which means the stronger “representative” of binary map the rock cutting plane, the more accurate simulated results can be obtained.
Emotion Recognition Based on EEG Using Generative Adversarial Nets and Convolutional Neural Network
Authors: Pan Bo , Zheng Wei
Published: October 2021

Emotion recognition plays an important role in the field of human-computer interaction (HCI). Automatic emotion recognition based on EEG is an important topic in brain-computer interface (BCI) applications. Currently, deep learning has been widely used in the field of EEG emotion recognition and has achieved remarkable results. However, due to the cost of data collection, most EEG datasets have only a small amount of EEG data, and the sample categories are unbalanced in these datasets. These problems will make it difficult for the deep learning model to predict the emotional state. In this paper, we propose a new sample generation method using generative adversarial networks to solve the problem of EEG sample shortage and sample category imbalance. In experiments, we explore the performance of emotion recognition with the frequency band correlation and frequency band separation computational models before and after data augmentation on standard EEG-based emotion datasets. Our experimental results show that the method of generative adversarial networks for data augmentation can effectively improve the performance of emotion recognition based on the deep learning model. And we find that the frequency band correlation deep learning model is more conducive to emotion recognition.
Deformation Analysis of the Multiplanar Conformal Off-Axis Four-Mirror in an Aerospace Environment
Authors: Huo Haodong , Ji Shijun , Zhao Ji , Sun Rengquan , Dai Handa
Published: October 2021

The effect of maneuver overload on a new type of the multiplanar conformal off-axis four-mirror is studied under the noninertial environment of aerospace. Two kinds of maneuvering flight, horizontal maneuvering and vertical maneuvering, are taken as examples, and the force analysis of the aircraft in the noninertial environment is considered. And the force analysis of the aircraft and the multiplanar conformal off-axis four-mirror is connected by the overload coefficient. Finally, the finite element simulation analysis of the multiplanar conformal off-axis four-mirror is carried out. The results show that the influence of maneuver overload on the multiplanar conformal off-axis four-mirror cannot be ignored. Large overload will result in large deformation of the multiplanar conformal off-axis four-mirror. The deformation is closely related to the structure of the multiplanar conformal off-axis four-mirror. Under the action of lateral force, nonuniform deformation is more likely to occur on the surface of the multiplanar conformal off-axis four-mirror.
Research on Search Method of Potential Sliding Surface of Rock Slope with Embedded Structural Plane
Authors: Yao Aijun , Lu Jian , Tian Zhizhou , Li Yanyan
Published: October 2021

Slope stability has been a key issue in the field of geotechnical engineering. Determining the potential sliding surface of a slope is an important link in evaluating the stability of the slope. For rock slope with embedded structural plane, the potential sliding surface is greatly affected by the embedded structural plane. When determining the potential sliding surface, the influence of the position of the embedded structural plane should be considered. According to the distribution characteristics of the embedded structural plane of the rock slope, the structural plane in rock slope is divided into two types: (1) front embedded and (2) rear embedded structural plane. Considering the influence of two types of structural planes, a search method for potential sliding surfaces of rock slope is proposed combined with the finite random tracking method. The location of the sliding surface is controlled through the cut‐in point, cut‐out point, and arc height so that the range of search variables does not need empirical assumption. An engineering example is used to verify the search method. The results show that the method could accurately obtain the potential sliding surface of the rock slope with embedded structural plane, which proves the effectiveness of the search method.
Prediction of Geological Parameters during Tunneling by Time Series Analysis on In Situ Data
Authors: Liu Shanglin , Yang Kaihong , Cai Jie , Zhou Siyang , Zhang Qian
Published: October 2021

A tunnel boring machine (TBM) is a type of heavy load equipment that is widely used in underground tunnel construction. The geological conditions in the tunneling process are decisive factors that directly affect the control of construction equipment. Because TBM tunneling always takes place underground, the acquisition of geological information has become a key issue in this field. This study focused on the internal relationships between the sequential nature of tunnel in situ data and the continuous interaction between equipment and geology and introduced the long short‐term memory (LSTM) time series neural network method for processing in situ data. A method for predicting the geological parameters in advance based on TBM real‐time state monitoring data is proposed. The proposed method was applied to a tunnel project in China, and the R2 of the prediction results for five geological parameters are all higher than 0.98. The performance of the LSTM was compared with that of an artificial neural network (ANN). The prediction accuracy of the LSTM was significantly higher compared with that of the ANN, and the generalization and robustness of LSTM are also better than those of ANN, which indicates that the proposed LSTM method could extract the sequence properties of the in situ data. The rule of equipment‐geology interaction was reflected by increasing the memory structure of the model through the introduction of the “gate” concept, and the accurate prediction of geological parameters during tunneling was realized. Additionally, the influence of time window and distance of prediction on the model is discussed. The proposed method provides a new approach toward obtaining geological information during TBM construction and also provides a certain reference for the effective analysis of the in situ data with sequence properties.
Therapeutic Effects of 25-Hydroxyvitamin D on the Pathological Process of Benign Prostatic Hyperplasia: An In Vitro Evidence
Authors: Chen Yanbo , Xu Hui , Liu Chong , Gu Meng , Chen Qi , Zhan Ming , Wang Zhong
Published: October 2021

The pathogenesis of benign prostatic hyperplasia (BPH) is extremely complicated which involving the multiple signaling pathways. The deficiency of vitamin D is an important risk factor for BPH, and exogenous vitamin D is effective for the treatment of BPH. In this study, we provided in vitro mechanical evidence of vitamin D as a treatment for BPH using BPH-1, WPMY-1, and PBMC cells. We found that 25-hydroxyvitamin D (25-OH D) level is decreased in BPH and closely correlated with age, prostate volume, maximum flow, international prostate symptom score, and prostate-specific antigen of the BPH patients. We further revealed that 25-OH D ameliorated TGF-β1 induces epithelial-mesenchymal transition (EMT) of BPH-1 cells and proliferation of WPMY-1 cells via blocking TGF-β signaling. Moreover, 25-OH D was able to block NF-κB signaling in PBMCs of BPH patients and STAT3 signaling in BPH cells to relieve inflammation. 25-OH D also protects BPH cells from inflammatory cytokines selected by PBMCs. Finally, we uncovered that 25-OH D alleviated prostate cell oxidative stress by triggering Nrf2 signaling. In conclusion, our data verified that 25-OH D regulated multiple singling pathways to restrain prostate cell EMT, proliferation, inflammation, and oxidative stress. Our study provides in vitro mechanical evidence to support clinical use of vitamin D as a treatment for BPH.
Effect of Nitrogen Ion Implantation Energy on the Mechanical and Chemical Properties of AISI M50 Steel
Authors: Xie Xiangyu , Chen Chao , Luo Jun , Xu Jin
Published: October 2021

Nitrogen ion implantation has shown its role in enhancing steel surface properties. In this work, AISI M50 steel was implanted with nitrogen ions by using the metal vapor vacuum arc technique with a dose of 2 × 1017 cm−2, and corresponding implanted energies were at 60 keV, 80 keV, and 100 keV, respectively. The distribution of implanted nitrogen ions was calculated, and the samples were tribologically tested and examined. As shown by the results, the microhardness in implanted samples was 1.17 times greater relative to that of the unimplanted sample. The implantation of the nitrogen ion leads to a change in the friction coefficient of the AISI M50 steel. Adhesive wear mechanism occurs in the unimplanted sample, and adhesion resistance tends to increase when nitrogen-implanted energy increases. The formation of oxides α-Fe2O3 and Fe3O4 further enhanced the tribological properties for implanted samples.
The Effect of Oral Vitamin E on Semen Parameters and IVF Outcome: A Double‐Blinded Randomized Placebo‐Controlled Clinical Trial
Authors: Sabetian Soudabeh , Jahromi Bahia Namavar , Vakili Sina , Forouhari Sedighe , Alipour Shohreh
Published: October 2021

Background. Male infertility is a main clinical problem that affects about 7% of all men worldwide. Many patients with male infertility are caused by a reduced antioxidant capacity of semen. Several antioxidant supplements, especially vitamin E, are proposed to help male infertility treatment. This project was goaled to study the effects of oral synthetic vitamin E (400 IU/day) for eight weeks on betterment of semen parameters and pregnancy rate. Methods. After dropping the cases, 124 infertile couples with a male factor who were admitted to the IVF program were included. The male patients with idiopathic abnormal motility and/or morphology were randomized into two groups: 61 receiving vitamin E and 63 as the control group receiving placebo for eight weeks. The pretreatment semen parameters of both groups were compared with those of posttreatment. The pregnancy outcomes were considered between the two groups. Results. There were no significant differences statistically between before and after treatment in the term of sperm volume, count, motility, and morphology. Furthermore, the IVF outcomes of the two groups were not different significantly, either. Interestingly, the percent of normal sperm in the placebo group was significantly decreased after eight weeks. Conclusion. Vitamin E supplementation might neutralize free radical activity to keep sperm from more oxidative damages. Further studies regarding the influence of higher acceptable doses of vitamin E on semen characteristics and fertility rates are needed. This study was registered as a two‐arm, blinded, randomized, placebo‐controlled clinical trial (IRCTID: IRCT2014020616506N1, 2014‐03‐18).
Ocean Observation Data Prediction for Argo Data Quality Control Using Deep Bidirectional LSTM Network
Authors: Jiang Fan , Ma Jitong , Wang Baosen , Shen Feifei , Yuan Lingling
Published: October 2021

With the rapid development of maritime technologies, a huge amount of ocean data has been acquired through the state-of-the-art ocean equipment to get better understanding and development of ocean. The prediction and correction of oceanic observation data play a fundamental and important role in the oceanic relevant applications, including both civilian and military fields. On the basis of Argo data, aiming at predicting and correcting the oceanic observation data, we propose an ocean temperature and salinity prediction approach in this paper. In our approach, firstly, bounded nonlinear function is utilized for dataset quality control, which can effectively eliminate the influence of spikes or outliers in Argo data. Then, RBF neural network is used for high-resolution Argo dataset construction. Finally, a bidirectional LSTM framework is proposed to predict and analyze the ocean temperature and salinity on the basis of BOA Argo data. Experimental results demonstrate that the proposed bidirectional LSTM framework can accurately predict the ocean temperature and salinity and enable outstanding performance in oceanic observation data prediction and correction. The proposed approach is also important for the realization of Argo dataset automatic quality control.
Bayesian and Classical Inference for the Generalized Log‐Logistic Distribution with Applications to Survival Data
Authors: Muse Abdisalam Hassan , Mwalili Samuel , Ngesa Oscar , Almalki Saad J. , Abd-Elmougod Gamal A.
Published: October 2021

The generalized log‐logistic distribution is especially useful for modelling survival data with variable hazard rate shapes because it extends the log‐logistic distribution by adding an extra parameter to the classical distribution, resulting in greater flexibility in analyzing and modelling various data types. We derive the fundamental mathematical and statistical properties of the proposed distribution in this paper. Many well‐known lifetime special submodels are included in the proposed distribution, including the Weibull, log‐logistic, exponential, and Burr XII distributions. The maximum likelihood method was used to estimate the unknown parameters of the proposed distribution, and a Monte Carlo simulation study was run to assess the estimators’ performance. This distribution is significant because it can model both monotone and nonmonotone hazard rate functions, which are quite common in survival and reliability data analysis. Furthermore, the proposed distribution’s flexibility and usefulness are demonstrated in a real‐world data set and compared to its submodels, the Weibull, log‐logistic, and Burr XII distributions, as well as other three‐parameter parametric survival distributions, such as the exponentiated Weibull distribution, the three‐parameter log‐normal distribution, the three‐parameter (or the shifted) log‐logistic distribution, the three‐parameter gamma distribution, and an exponentiated Weibull distribution. The proposed distribution is plausible, according to the goodness‐of‐fit, log‐likelihood, and information criterion values. Finally, for the data set, Bayesian inference and Gibb’s sampling performance are used to compute the approximate Bayes estimates as well as the highest posterior density credible intervals, and the convergence diagnostic techniques based on Markov chain Monte Carlo techniques were used.
Nutrient Composition and Physical Properties of Two Orange Seed Varieties
Authors: Adubofuor Joseph , Akyereko Yaw Gyau , Batsa Vida , Apeku Osborn-Jnr Doetser , Amoah Isaac , Diako Charles
Published: October 2021

Orange is mainly consumed as fresh fruit, concentrated juice, or thin dried slices, while the seeds are usually discarded by consumers and orange juice processing companies. This study was carried out to determine the physical, frictional, nutritional, and antinutritional properties of the Late Valencia and Red Blood orange seeds. The proximate composition, mineral profile, antinutrient content, and physical and frictional properties of two orange seed varieties were determined using standard methods. The mean length, width, thickness, geometric, and arithmetic mean diameter of the Late Valencia and Red Blood seeds were 14.66, 8.45, 5.05, 8.47, and 9.39 and 13.74, 7.51, 4.99, 7.97, and 8.75 mm, respectively. An angle of repose 39.62° and 38.62°, coefficient of friction of 0.63 and 0.61 on wood, 0.33 each on mild steel, and 0.41 and 0.43 on Teflon were recorded, respectively, for the Late Valencia and Red Blood orange seed varieties. Seeds from Late Valencia and Red Blood orange variety contained 547.39 mg/100 g and 693.87 mg/100 g of oxalate, respectively. Proximate and vitamin C of the orange seeds analyzed indicated that the protein (4.18%), fat (57.45%), fiber (6.06%), energy (640.66 kcal/100 g), and vitamin C (63 mg/100 g) content in the Late Valencia were significantly higher (

p
<
0.05

) than the Red Blood orange (3.61%, 55.77%, 5.49%, 85 kcal/100 g, and 54 mg/100 g) correspondingly. The high fat content of the orange seeds makes them potential source of oil for both food and nonfood product applications. Ca, P, and K were predominantly found in the two orange seed varieties. Physical and frictional properties obtained from this work could aid in the design of equipment for harvesting, processing, transporting, separating, packaging, and storage of orange seeds from Late Valencia and Red Blood orange varieties. Further research is required to determine the suitability of orange seed flours for value-added products.
New Network Selection Algorithm Based on Cosine Similarity Distance and PSO in Heterogeneous Wireless Networks
Authors: Radouche Said , Leghris Cherkaoui
Published: October 2021

Future wireless communication networks will be composed of different technologies with complementary characteristics. Thus, vertical handover (VHO) must support seamless mobility in such heterogeneous environments. The network selection is an important phase in the VHO process and it can be formulated as a multiattribute decision-making problem. So, the mobile terminal equipped with multiple interfaces will be able to choose the most suitable network. This work proposes an access network selection algorithm, based on cosine similarity distance, subjective weights using Fuzzy ANP, and objective weights using particle swarm optimization. The comprehensive weights are based on the cosine similarity distance between the networks and the ideal network. Finally, the candidate network with the minimum cosine distance to the ideal network will be selected in the VHO network selection stage. The performance analysis shows that our proposed method, based on cosine similarity distance and combination weights, reduces the ranking abnormality and number of handoffs in comparison with other MADM methods in the literature.
[Retracted] Automatic Film Label Acquisition Method Based on Improved Neural Networks Optimized by Mutation Ant Colony Algorithm
Authors: Liu Junjie
Published: October 2021

Nowadays, with the constant change of public aesthetic standards, a large number of new types and themes of film programs have emerged. For this reason, this paper proposes an improved neural network optimized by mutation ant colony algorithm for automatic acquisition of film labels, which not only overcomes the disadvantages of traditional neural network, such as difficulty in determining weights, slow convergence speed, and easiness to fall into local minimum, but also makes up for the shortcomings faced by using ant colony algorithm alone through the gradient information of quantum genetic algorithm neural network. The results show that the user similarity judgment is added in the process of calculating the user rating deviation between movies, and the neighbor chooses to add the movie tag weight and rating similarity as the basis for the neighbor selection of the target movie in the process of predicting the target movie rating. Experiments show the effectiveness of the algorithm.
[Retracted] Innovation and Development of University Education Management Informationization in the Environment of Wireless Communication and Big Data
Authors: Li Weizhe
Published: October 2021

The development of information technology has spawned a new type of demand and management analysis model of big data. The value of data is vividly reflected in the contemporary era, and all walks of life have devoted great energy to the construction and use of informatization. The object of college education and management is the group of college students who are most closely connected with contemporary trends. Their thoughts are active, their state is changeable, and they are very sensitive to external stimuli. Such an educational situation has greatly increased the difficulty of educational management in colleges and universities. This article takes the big data research as the breakthrough point, focuses on the promotion and innovation of contemporary college education management informatization, and strives to improve the college education management informatization system by solving existing problems. The innovation of this research is to use big data technology as the starting point for improving the current stage of the education informatization work of colleges and universities, through the combination of data analysis and the latter, to realize the comprehensive informatization innovation of education management. The study used questionnaire surveys to investigate and interview some students and related managers in 5 universities in the province and conducted an objective assessment of the construction of educational management informatization in these universities and found that these five universities have common problems in this field. Research experiments have found that among the five representative universities in the province, the service awareness of education administrators is not above the fifth level. This shows that in the big data environment, the quality of education administrators cannot be ignored.
A User-Priority-Driven Multi-UAV Cooperative Reconnaissance Strategy
Authors: Liu Zeyuan , Liu Cuntao , Zhao Wendong , Li Aijing
Published: October 2021

This paper considers a reconnaissance scenario where multiple unmanned aerial vehicles (UAVs) provide services cooperatively for multiple users with different priorities. Although users all expect to acquire their needed information in a short time, the degree of urgency to meet their demands is different when taking their diverse priorities into account. A priority-driven multiuser satisfaction model is designed, where users’ satisfaction is quantified based on their different priorities, information acquisition demands, and the time they obtain their desired information. To ensure high priority users’ fast information acquisition while avoiding excessive delay in low priority users’ information acquisition, a batchwise information backhaul strategy is adopted. In each batch, a UAV is selected as the data ferry through a consultative mechanism to carry information back to users. This reconnaissance process is formulated as a cooperative path planning problem, where the optimization objective is maximizing users’ total satisfaction, while an intelligent algorithm is proposed to solve this problem effectively. The simulation results show that compared with traditional path planning algorithms without considering user satisfaction, our proposed algorithm can guarantee faster information acquisition for users with higher priorities, which leads to higher satisfaction. In addition, the applicability of our proposed reconnaissance strategy and path planning algorithm in different situations is also analyzed.
[Retracted] Effects of High‐Flux Dialysis Combined with Hemoperfusion on Serum GRP78 and miR‐495‐3p in Renal Failure Patients
Authors: Fan Wei , Li Xudong , Xu Xiangjun , Chu Hong
Published: October 2021

Objective. This study was designed to probe into the changes and clinical significance of GRP78 and miR‐495‐3p in renal failure (RF) patients during high‐flux dialysis (HFD) combined with hemoperfusion (HP). Methods. Sixty‐five RF patients and 74 health check‐ups who were admitted in our hospital from March 2015 to February 2017 were prospectively selected, and the related characteristics were retrospectively collected for analysis. GRP78 and miR‐495‐3p were detected in RF patients at admission (before treatment), 12 weeks after treatment (during treatment), 24 weeks after treatment (after treatment), and the control group at admission, and the relationship between the two and the occurrence, efficacy, and recurrence of RF was analyzed. Results. Before treatment, the GRP78 mRNA level in RF patients was higher than that in health check‐ups, while the miR‐495‐3p level was lower (P < 0.05). GRP78 mRNA in RF patients was lower than that before treatment and was the lowest after treatment. On the contrary, miR‐495‐3p was higher than that before treatment and was the highest after treatment (P < 0.05). The two had a significant effect on predicting RF before treatment, efficacy of patients, and their recurrence after treatment (all P < 0.001). Conclusion. GRP78 decreased during the treatment of high‐flux hemodialysis (HF‐HD) combined with systemic HP in RF patients, while miR‐495‐3p increased. Both of them have a good reference value for RF occurrence, treatment results, and recurrence.