bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanical integrity of tubing string in high‐temperature and high‐pressure ultra‐deep gas wells based on uncertainty theory
Authors: Zhang Zhi , Ding Jian , Zheng Yushan , Sang Pengfei , Chen Lili , Fan Yu , Li Yufei 
Published: March 2022

AbstractDuring the manufacturing process of tubing and casing, manufacturing deviations can occur in quality parameters, such as yield strength, outer diameter, and wall thickness, which can lead to uncertainty in the actual strength of the tubing string. Specifically, tubing string failures periodically occur in high‐temperature, high‐pressure, and ultra‐deep gas wells owing to the uncertainty in string strength, attenuation of high‐temperature material properties, and influence of complex load fluctuations. Therefore, in this study, Monte Carlo method is adopted to simulate the local fluctuation of downhole actual load, and the load variation rule of tubing string in high‐temperature and high‐pressure ultra‐deep well is obtained. By considering the effect of manufacturing tolerance and corrosion, variation law of string strength is obtained. Additionally, the influence of load, temperature, manufacturing tolerance, and other uncertainties on the strength and stress of the tubing string is analyzed, and a quantitative evaluation method for the mechanical integrity of the tubing string is established. The calculation results show that the uncertainty of complex loads and influence of high temperature increase the failure probability of the mechanical integrity of tubing string. Furthermore, a failure risk can potentially exist under conditions wherein conventional verification results denote no failure. It is determined via sensitivity analysis that temperature, corrosion rate, and steel grade are the main factors for the failure of the tubing string mechanical integrity. By considering the influence of high temperature, the failure probability of the tubing string is increased by 25.33% when compared to the original basis. However, considering the manufacturing tolerance of tubing string, the actual yield strength of tubing string is higher than the nominal yield strength, which reduces the failure probability of the tubing string. This implies that reduction of the subjective influence in the risk assessment process can lead to precise and quantitative analysis of the failure risk of the tubing string mechanical integrity and optimization of the structure of the tubing string in high‐temperature, high‐pressure, and ultra‐deep gas wells.
Learning‐based deep neural network inference task offloading in multi‐device and multi‐server collaborative edge computing
Authors: Cui Enfang , Yang Dong , Wang Hongchao , Zhang Weiting 
Published: March 2022

AbstractDeep neural network (DNN) inference task offloading is an essential problem of edge intelligence, which faces the challenges of limited computing resources shortage of edge devices and the dynamics of edge networks. In this article, the DNN inference task offloading problem in queue‐based multi‐device and multi‐server collaborative edge computing is investigated. To support efficient collaborative inference, we formulate a multi‐objective optimization problem that minimizes the average delay and maximizes average inference accuracy. Due to time‐varying queue load states and random task arrival, it is challenging to solve this optimization problem. Thus, a deep reinforcement learning based task offloading algorithm, named LSTM‐TD3, is proposed to solve the formulated problem. Specifically, LSTM‐TD3 incorporates the long short‐term memory (LSTM) and twin delayed deep deterministic policy gradient algorithm (TD3), and can leverage long‐term environment information to efficiently explore the optimal task offloading solution. Finally, we compared the performance of LSTM‐TD3 with TD3 (without LSTM) and random offloading algorithms, and simulation results show the LSTM‐TD3 reduce the average inference delay by up to , and the accuracy is better than other algorithms.
Ultrasonic‐assisted extraction of bioactive chlorogenic acid from heilong48 soybean variety: Parametric optimization and evaluation of physicochemical and bioactive properties
Authors: Akpabli‐Tsigbe Nelson Dzidzorgbe Kwaku , Ma Yongkun , Ekumah John‐Nelson , Osabutey Juliet , Hu Jie , Xu Manqing , Johnson Nana Adwoa Nkuma , Mintah Benjamin Kumah 
Published: March 2022

AbstractChlorogenic acid (CA), especially that found in soybeans, is a rich bioactive compound but has received very little attention in research settings in past decades. Ultrasonic‐assisted extraction (UAE) could be an efficient method to increase CA release from soybeans. Hence, this study aimed to optimize UAE parameters for CA extraction from heilong48 soybean (HS) variety and evaluate the physicochemical and bioactive properties of the soybean. Optimization of ultrasound parameters with a Box–Behnken design found a frequency of 20.0 kHz, a power density of 30.0 W/L), a temperature of 37.9°C, and a time of 28.0 min to be the best conditions, which gave a CA yield of 5.007 ± 0.033 mg/g and 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) radical scavenging activity of 93.197 ± 0.213 μmol of AA eq/g dry sample; these were higher than those of a non–ultrasound‐treated (raw) HS sample (CA yield of 1.627 ± 0.528 mg/g and DPPH radical scavenging activity of 10.760 ± 0.207 μmol of AA eq/g dry sample). A satisfactory model was obtained. Scanning electron microscopy results confirmed the structural changes of the HS variety caused by the optimized UAE parameters. High total polyphenol contents (TPCs; 4.726 ± 0.002 mg GAE/g) and total phenolic acids (1.883 ± 0.005 mg GAE/g) and low total flavonoid contents (0.040 ± 0.008 mg RE/g) were obtained. A positive linear correlation between antioxidant activity and TPC was established. A protein–phenolic interaction in the HS variety was observed. The results established that polyphenols should be considered a significant component of the HS variety. Likewise, the HS variety could be used for CA extraction.
Effects of packinghouse operations on the flavor of ‘Orri’ mandarins
Authors: Otieno James , Owoyemi Abiola , Goldenberg Livnat , Yaniv Yossi , Carmi Nir , Porat Ron 
Published: March 2022

AbstractMandarins have a delicate flavor and are easy to peel and easy to consume. However, they are relatively perishable and suffer from flavor deterioration after harvest. The goal of the current study was to examine the effects of commercial packinghouse operations on the flavor of ‘Orri’ mandarins. For that purpose, we collected fruit from four different points along a commercial citrus packing line: (1) directly from the harvest bin, (2) after application of a hot (53°C) fungicide treatment for 30 s, (3) after waxing, and (4) after waxing and after the fruit had passed through a hot‐air drying tunnel (37°C) for 2 min. The collected fruit were stored for 3 or 6 weeks at 5°C and then kept for five more days under shelf‐life conditions at 22°C. The observed results indicate that the hot fungicide treatment had no effect on flavor quality. However, the waxing and waxing +drying treatments resulted in significant increases in ethanol accumulation, lower flavor‐acceptability scores, and increased off‐flavors. Gas‐chromatography mass‐spectrometry (GC–MS) analysis revealed that the waxing and waxing +drying treatments resulted in particular increases in the levels of alcohol and ethyl ester volatiles; whereas levels of other aroma volatiles (i.e., esters, aldehydes, monoterpenes, and sesquiterpenes) decreased after storage in all fruit samples. Overall, the waxing process in commercial citrus packinghouses increased ethanol and ethyl ester volatile levels and harmed flavor acceptability. These findings demonstrate the need to identify new wax formulations that do not hamper fruit‐flavor quality.
High‐performing mortar‐based materials from the late imperial baths of Aquileia: An outstanding example of Roman building tradition in Northern Italy
Authors: Dilaria Simone , Secco Michele , Rubinich Marina , Bonetto Jacopo , Miriello Domenico , Barca Donatella , Artioli Gilberto 
Published: March 2022

AbstractThis study provides the first detailed insight into the composition and properties of structural mortars used in a 4th‐century AD bath complex in Aquileia, the emblematic center of Roman culture in Northern Italy. Eighteen mortars, taken from different structures of the site, and three stone samples from the vaulting opus caementicium have been analyzed adopting a multianalytical approach integrating optical microscopy, X‐ray powder diffraction, X‐ray fluorescence, and scanning electron microscopy coupled with energy‐dispersive spectroscopy. The properties of the compounds are outstanding, as revealed by the formation of hydraulic phases (i.e., Al‐tobermorite and AFm) in most of the samples: the waterproofing capabilities of cocciopesto mortars are remarkable, as revealed by the formation of anthropogenic Al‐tobermorite (5.5 wt%) in pool coating samples; the lightweight of the vaults was guaranteed by the use of porous caementa and pozzolanic volcanic aggregates imported from the Gulf of Naples, as demonstrated by petro‐mineralogical features and chemical analysis of major and trace elements. This is the first proven case of trade in these building materials to the north of the Italian peninsula. These outcomes shed new light on the robust technical expertise of local artisans in Aquileia and indicate that the Cisalpina province was by no means a peripheral reality in the Roman Empire, as far as mortar‐based materials are concerned.
Statelets: Capturing recurrent transient variations in dynamic functional network connectivity
Authors: Rahaman Md Abdur , Damaraju Eswar , Saha Debbrata K. , Plis Sergey M. , Calhoun Vince D. 
Published: March 2022

AbstractDynamic functional network connectivity (dFNC) analysis is a widely used approach for capturing brain activation patterns, connectivity states, and network organization. However, a typical sliding window plus clustering (SWC) approach for analyzing dFNC models the system through a fixed sequence of connectivity states. SWC assumes connectivity patterns span throughout the brain, but they are relatively spatially constrained and temporally short‐lived in practice. Thus, SWC is neither designed to capture transient dynamic changes nor heterogeneity across subjects/time. We propose a state‐space time series summarization framework called “statelets” to address these shortcomings. It models functional connectivity dynamics at fine‐grained timescales, adapting time series motifs to changes in connectivity strength, and constructs a concise yet informative representation of the original data that conveys easily comprehensible information about the phenotypes. We leverage the earth mover distance in a nonstandard way to handle scale differences and utilize kernel density estimation to build a probability density profile for local motifs. We apply the framework to study dFNC of patients with schizophrenia (SZ) and healthy control (HC). Results demonstrate SZ subjects exhibit reduced modularity in their brain network organization relative to HC. Statelets in the HC group show an increased recurrence across the dFNC time‐course compared to the SZ. Analyzing the consistency of the connections across time reveals significant differences within visual, sensorimotor, and default mode regions where HC subjects show higher consistency than SZ. The introduced approach also enables handling dynamic information in cross‐modal and multimodal applications to study healthy and disordered brains.
Decoding motor expertise from fine‐tuned oscillatory network organization
Authors: Amoruso Lucia , Pusil Sandra , García Adolfo Martín , Ibañez Agustín 
Published: March 2022

AbstractCan motor expertise be robustly predicted by the organization of frequency‐specific oscillatory brain networks? To answer this question, we recorded high‐density electroencephalography (EEG) in expert Tango dancers and naïves while viewing and judging the correctness of Tango‐specific movements and during resting. We calculated task‐related and resting‐state connectivity at different frequency‐bands capturing task performance (delta [δ], 1.5–4 Hz), error monitoring (theta [θ], 4–8 Hz), and sensorimotor experience (mu [μ], 8–13 Hz), and derived topographical features using graph analysis. These features, together with canonical expertise measures (i.e., performance in action discrimination, time spent dancing Tango), were fed into a data‐driven computational learning analysis to test whether behavioral and brain signatures robustly classified individuals depending on their expertise level. Unsurprisingly, behavioral measures showed optimal classification (100%) between dancers and naïves. When considering brain models, the task‐based classification performed well (~73%), with maximal discrimination afforded by theta‐band connectivity, a hallmark signature of error processing. Interestingly, mu connectivity during rest outperformed (100%) the task‐based approach, matching the optimal classification of behavioral measures and thus emerging as a potential trait‐like marker of sensorimotor network tuning by intense training. Overall, our findings underscore the power of fine‐tuned oscillatory network signatures for capturing expertise‐related differences and their potential value in the neuroprognosis of learning outcomes.
Application of a sustainability framework to enhance Australian food literacy programs in remote Western Australian communities
Authors: Aberle Leisha M. , Platts Julia R. , Kioutis Marie A. , Haustead Louise M. , Godrich Stephanie L. 
Published: March 2022

AbstractIssue addressedFood literacy programs aim to build individuals’ knowledge, skills and self‐efficacy to adopt healthy food choices conducive to reducing the risk of chronic diseases, such as obesity. Foodbank WA’s (FBWA) Healthy Food for All® nutrition programs have supported the improvement of food literacy knowledge and skills among vulnerable people living in the Pilbara.MethodsA Sustainability Framework containing ten sustainability factors was overlaid with social ecological model (SEM) levels of influence to form a matrix. The use of this matrix facilitated sustainability strategy appraisal within three food literacy programs delivered in remote WA.ResultsPrograms included multiple sustainability strategies across levels of influence; all programs addressed all ten sustainability factors at community and organisational SEM levels of influence. Few sustainability strategies were employed at the public policy level of influence. No program employed formal governance structures to guide program direction, such as steering groups; however, school and parent program staff developed Memoranda of Understanding to ensure the continuation of program delivery between the FBWA teams’ regional visits.ConclusionsThis study has showcased the comprehensive assessment of food literacy program sustainability across levels of influence and identified gaps for improvement by FBWA teams.So What?The sustainability of food literacy programs aiming to increase knowledge and skills could be enhanced by conducting a similar analysis, during program planning or at program review. Using the matrix provides the opportunity to focus resources to address sustainability; supporting health promotion practitioners to transform the impacts of short‐term food literacy interventions into long‐term sustained outcomes.
Lu Tong Ke Li protects neurons from injury by regulating inflammation in rats with brain trauma
Authors: Chen Jie , Li Ting‐Ting , Chen Ting‐Bao , Niu Rui‐Ze , Chen Ji‐Lin , Chen Yong , Huang Jin 
Published: March 2022

AbstractCurrently, there is no effective therapy for traumatic brain injury (TBI). Therefore, this study was conducted to determine the protective effect of Lu Tong Ke Li (LTKL), a Chinese medicine, for TBI in experimental animals. The TBI rat model was induced using the modified Feeney's protocol. The rats were divided into four groups: Sham group, Control group, LTKL lower‐dose group (LTL, 2 g/kg/day, p.o.), and LTKL higher‐dose group (LTH, 4 g/kg/day, p.o.). The Neurological Severity Score (NSS) was used to examine neurological function. Magnetic resonance imaging was performed to check the brain tissue lesions in rats. Cell apoptosis in the damaged area was evaluated using the Terminal deoxynucleotidyl transferase deoxy‐UTP‐nick end labeling assay. Reverse‐transcription polymerase chain reaction was used to investigate the expression of inflammatory cytokines, including tumor necrosis factor‐α (TNF‐α), interleukin 1β (IL‐1β), and interleukin 10 (IL‐10). The TBI rat model was successfully constructed. Neurological function was enhanced at 14, 21, and 28 days post TBI in the LTH groups, indicated by gradually decreased NSS scores. Administration of LTH led to fewer brain defects in the damaged area, and the number of apoptosis cells in the brain injury area markedly decreased. LTKL treatment led to upregulation of IL‐10 expression and downregulation of TNF‐α and IL‐1β expressions at the molecular level. LTKL can improve the neurobehavior of TBI. The neuroprotective effect was probably related to regulation of inflammation cytokines. Our results provide crucial evidence of the potentially useful application of LTKL in the therapy of TBI in clinic practice in the future.
hsa_circ_0058122 knockdown prevents steroid‐induced osteonecrosis of the femoral head by inhibiting human umbilical vein endothelial cells apoptosis via the miR‐7974/IGFBP5 axis
Authors: Yao Tao , Wang Lei , Ding Zhen‐Fei , Yin Zong‐Sheng 
Published: March 2022

AbstractBackgroundSteroid‐induced osteonecrosis of femoral head (SONFH) is a serious complication of glucocorticoid overused. Recent evidence has demonstrated that circRNAs exert key pathophysiological roles in a variety of disease processes. However, the role of circRNA in SONFH remains largely unknown. The current study sought to evaluate how hsa_circ_0058122 affects SONFH in dexamethasone (DEX) treated human umbilical vein endothelial cells (HUVECs) model.MethodsRT‐PCR was used to demonstrate the hsa_circ_0058122 expression level in Dex‐treated HUVECs cells. The effects of hsa_circ_0058122 on HUVECs apoptosis were evaluated via overexpression plasmid and siRNA. Using dual‐luciferase and fluorescence in situ hybridization assays, we demonstrated that hsa_circ_0058122 binds to miR‐7974 thereby facilitating HUVECs apoptosis. Bioinformatics analysis and western blot were performed to confirm target genes of hsa‐miR‐7974.ResultsIn our previous work, we revealed the top 20 elevated circRNAs in SONFH patients were hsa_circ_0010027, hsa_circ_0058115, hsa_circ_0010026, hsa_circ_0058839, hsa_circ_0056886, hsa_circ_0056885, hsa_circ_0058146, hsa_circ_0058105, hsa_circ_0058112, hsa_circ_0058143, hsa_circ_0058102, hsa_circ_0058090, hsa_circ_0075353, hsa_circ_0058126, hsa_circ_0058130, hsa_circ_0058140, hsa_circ_0058122, hsa_circ_0058123, hsa_circ_0058103, and hsa_circ_0058121. Among these, hsa_circ_0058122 was finally selected for further investigation. We found hsa_circ_0058122 expression was markedly elevated in Dex‐treated HUVECs cells, and the Dex‐mediated HUVEC apoptosis was impaired in hsa_circ_0058122‐silenced cells and increased in hsa_circ_0058122‐overexpressing cells. hsa_circ_0058122 competitively binds to hsa‐miR‐7974, which in turn interacts with insulin‐like growth factor binding protein 5 (IGFBP5).Conclusionshsa_circ_0058122/miR‐7974/IGFBP5 was proposed to be a key regulatory pathway for SONFH. DEX treatment upregulated hsa_circ_0058122 expression in HUVECs, which sponged miR‐7974, thereby increasing IGFBP5 expression, the hsa_circ_0058122/miR‐7974/IGFBP5 axis contributed to the Dex‐mediated apoptosis. These findings may identify novel targets for SONFH molecular therapy.
Aberrant expression of long non‐coding RNA PVT1 in allergic rhinitis children: Correlation with disease risk, symptoms, and Th1/Th2 imbalance
Authors: Sun Yujun , Han Jingjing , Ma Haifeng , Ma Jingbin , Ren Zengzhi 
Published: March 2022

AbstractBackgroundLong non‐coding RNA plasmacytoma variant translocation 1 (lnc‐PVT1) exacerbates inflammation and induces T helper (Th) 1/Th2 imbalance in allergic diseases, but its clinical role in allergic rhinitis (AR) remains unclear. Hence, we conducted this study to compare lnc‐PVT1 expression among AR children, disease controls (DCs), and health controls (HCs), aiming to investigate its clinical application in AR children.MethodsSixty AR children, 30 DCs, and 30 HCs were enrolled in the study, and then, their lnc‐PVT1 expression in peripheral blood mononuclear cell was detected. Serum interferon‐gamma (IFN‐γ), interleukin 10 (IL‐10), Th1, and Th2 cells in AR children were also analyzed. Besides, lnc‐PVT1 was also detected at Week (W)4 after treatment in AR patients.ResultsLnc‐PVT1 was upregulated in AR children compared with DCs and HCs (both p < 0.001). Lnc‐PVT1 was positively related to nasal rhinorrhea score, itching score, congestion score, and total nasal symptom score (TNSS) in AR children (all p < 0.050), instead of sneezing score (p = 0.115). Lnc‐PVT1 negatively associated with Th1 cells in AR children (p = 0.028) also exhibited a negative correlation trend with IFN‐γ (but without statistical significance) (p = 0.065). Differently, lnc‐PVT1 was positively related to Th2 cells (p = 0.012) and IL‐10 (p = 0.021) in AR children. Besides, lnc‐PVT1 and TNSS were reduced at W4 after treatment in AR children (both p < 0.001); notably, lnc‐PVT1 expression decline was correlated with TNSS decline during treatment (p = 0.013).ConclusionLnc‐PVT1 works as a biomarker, whose aberrant expression is related to disease severity, Th1/Th2 imbalance, and its decrement can reflect treatment outcome in AR children.
Adolescent social media user types and their mental health and well‐being: Results from a longitudinal survey of 13–14‐year‐olds in the United Kingdom
Authors: Winstone Lizzy , Mars Becky , Haworth Claire M. A. , Heron Jon , Kidger Judi 
Published: March 2022

AbstractBackgroundThere is mixed evidence as to the effects of different types of social media use on mental health, but previous research has been platform‐specific and has focused on an oversimplified distinction between active and passive use. This study aimed to identify different underlying subgroups of adolescent social media user based on their pattern of social media activities and test associations between user type and future mental health.MethodsStudents from 19 schools (N = 2456) in south‐west England completed an online survey measuring 13 social media activities and four psychosocial outcomes (past year self‐harm, depression, anxiety and poor well‐being) at age 13 years (October 2019) and repeated a year later (October 2020; aged 14 years). Latent class analysis using Mplus identified distinct classes of social media user and stability of these classes was examined using latent transition analysis. A bias‐adjusted three‐step model was used to test associations between class membership at baseline and mental health at follow‐up. Analyses were adjusted for gender, ethnicity, sexual orientation, socioeconomic status, disability, social media screen‐time and baseline mental health.ResultsA four‐class model of social media user at baseline was selected based on fit statistics and interpretability. User types were labelled High Communicators; Moderate Communicators; Broadcasters; and Minimal users. Users became more active over time. Broadcasters at age 13 had the poorest mental health outcomes at age 14, with mental health and well‐being generally better among the High and Moderate Communicators.ConclusionsFindings suggest that broadcasters—adolescents with high levels of content sharing in addition to messaging and browsing online—are most likely to be experiencing poor mental health a year later. Recommendations regarding social media use should expand to consider different user types, and mental health implications of their engagement with different online activities in addition to screen‐time.