bluuebunny/crossref_metadata_2025 huggingface dataset:
Bedrock gorge incision via anthropogenic meander cutoff
Authors: Bender Adrian M.
Published: November 2021

Bedrock river-gorge incision represents a fundamental landscape-shaping process, but a dearth of observational data at >10 yr timescales impedes understanding of gorge formation. I quantify 102 yr rates and processes of gorge incision using historical records, field observations, and topographic and image analysis of a human-caused bedrock meander cutoff along the North Fork Fortymile River in Alaska (USA). Miners cut off the meander in 1900 CE, abruptly lowering local base level by 6 m and forcing narrowing and steepening of the channel across a knickpoint that rapidly incised upstream. Tectonic quiescence, consistent rock erosivity, and low millennial erosion rates provide ideal boundary conditions for this 102 yr gorge-formation experiment. Initial fast knickpoint propagation (23 m/yr; 1900–1903 CE) slowed (4 m/yr; 1903–1981 CE) to diffusion (1981–2019 CE) as knickpoint slope decreased, yielding an ~350-m-long, 6-m-deep gorge within the pre–1900 CE channel. Today, diffusion dominates incision of a 500-m-long knickzone upstream of the gorge, where sediment transport likely limits ongoing adjustments to the anthropogenic cutoff. Results elucidate channel width, slope, discharge, and sediment dynamics consistent with a gradual transition from detachment- to transport-limited incision in fluvial adjustment to local base-level lowering.
Water in omphacite fingerprints the thermal history of eclogites
Authors: Jiang Peilin , Liu Hanyong , Skogby Henrik , Chen Ren-Xu , Yang Xiaozhi
Published: November 2021

Omphacite is a diagnostic mineral of high- and ultrahigh-pressure rocks, and its association with garnet is characteristic of eclogites from subduction-related massifs and volcano-entrained xenoliths. Omphacite can accommodate significant amounts of water as structurally bound hydroxyl (OH) groups, and is able to convey water into Earth's interior. We show, for the first time, experimental evidence that the infrared absorption patterns of water in omphacite are temperature sensitive. This provides a new framework for discriminating water in natural omphacite equilibrated at different temperatures. We also demonstrate that in low-temperature omphacite, the integral absorbance ratio between the infrared OH absorption bands at 3620 cm−1 and 3450 cm−1 is linearly related to temperature. Water in omphacite of massif eclogites records the temperature of OH equilibrium, allowing reconstruction of the fluid-involved thermal history and tectonics of rock evolution.
Late Cretaceous upper-crustal thermal structure of the Sevier hinterland: Implications for the geodynamics of the Nevadaplano
Authors: Blackford Nolan R. , Long Sean P. , Stout Austin , Rodgers David W. , Cooper C.M. , Kramer Kimberly , Di Fiori Russell V. , Soignard Emmanuel
Published: November 2021

Crustal temperature conditions can strongly influence the evolution of deformation during orogenesis. The Sevier hinterland plateau in Nevada and western Utah (“Nevadaplano”) experienced a Late Cretaceous episode of shallow-crustal metamorphism and granitic magmatism. Here, we investigate the thermal history of the Nevadaplano by measuring peak thermal field gradients attained in the upper 10–20 km of the crust along an east-west transect through nine ranges in eastern Nevada and western Utah, by integrating Raman spectroscopy of carbonaceous material thermometry and published conodont alteration indices with reconstructed cross sections. Thermal field gradients of 29 ± 3 °C/km were obtained in the House and Confusion Ranges in westernmost Utah. The Deep Creek, Schell Creek, and Egan Ranges in easternmost Nevada yielded elevated gradients of 49 ± 7 °C/km, 36 ± 3 °C/km, and 32 ± 6 °C/km, respectively. Moving westward, the White Pine, Butte, Pancake, and Fish Creek Ranges exhibit gradients typically between ~20–30 °C/km. The elevated thermal gradients in easternmost Nevada are interpreted to have been attained during ca. 70–90 Ma granitic magmatism and metamorphism and imply possible partial melting at ~18 km depths. Our data are compatible with published interpretations of Late Cretaceous lithospheric mantle delamination under the Sevier hinterland, which triggered lower-crustal anatexis and the resulting rise of granitic melts. The lack of evidence for structures that could have accommodated deep burial of rocks in the nearby Northern Snake Range metamorphic core complex, combined with thermal gradients from adjacent ranges that are ~1.5–3 times higher than those implied by thermobarometry in the Northern Snake Range, further highlights the debate over possible tectonic overpressure in Cordilleran core complexes. Cross-section retro-deformation defines 73.4 ± 4.6 km (76 ± 8%) of extension across eastern Nevada and 15 km of shortening in the Eastern Nevada fold belt.
Epitope spreading driven by the joint action of CART cells and pharmacological STING stimulation counteracts tumor escape via antigen-loss variants
Authors: Conde Enrique , Vercher Enric , Soria-Castellano Marta , Suarez-Olmos Jesús , Mancheño Uxua , Elizalde Edurne , Rodriguez M Luis , Glez-Vaz Javier , Casares Noelia , Rodríguez-García Estefanía , Hommel Mirja , González-Aseguinolaza Gloria , Uranga-Murillo Iratxe , Pardo Julian , Alkorta Gorka , Melero Ignacio , Lasarte Juan , Hervas-Stubbs Sandra
Published: November 2021

Background

Target antigen (Ag) loss has emerged as a major cause of relapse after chimeric antigen receptor T (CART)-cell therapy. We reasoned that the combination of CART cells, with the consequent tumor debulking and release of Ags, together with an immunomodulatory agent, such as the stimulator of interferon gene ligand (STING-L) 2′3′-cyclic GMP-AMP (2′3′-cGAMP), may facilitate the activation of an endogenous response to secondary tumor Ags able to counteract this tumor escape mechanism.

Methods

Mice bearing B16-derived tumors expressing prostate-specific membrane Ag or gp75 were treated systemically with cognate CART cells followed by intratumoral injections of 2′3′-cGAMP. We studied the target Ag inmunoediting by CART cells and the effect of the CART/STING-L combination on the control of STING-L-treated and STING-L-non-treated tumors and on the endogenous antitumor T-cell response. The role of Batf3-dependent dendritic cells (DCs), stimulator of interferon gene (STING) signaling and perforin (Perf)-mediated killing in the efficacy of the combination were analyzed.

Results

Using an immune-competent solid tumor model, we showed that CART cells led to the emergence of tumor cells that lose the target Ag, recreating the cancer immunoediting effect of CART-cell therapy. In this setting, the CART/STING-L combination, but not the monotherapy with CART cells or STING-L, restrained tumor progression and enhanced overall survival, showing abscopal effects on distal STING-L-non-treated tumors. Interestingly, a secondary immune response against non-chimeric antigen receptor-targeted Ags (epitope spreading), as determined by major histocompatibility complex-I-tetramer staining, was fostered and its intensity correlated with the efficacy of the combination. This was consistent with the oligoclonal expansion of host T cells, as revealed by in-depth T-cell receptor repertoire analysis. Moreover, only in the combination group did the activation of endogenous T cells translate into a systemic antitumor response. Importantly, the epitope spreading and the antitumor effects of the combination were fully dependent on host STING signaling and Batf3-dependent DCs, and were partially dependent on Perf release by CART cells. Interestingly, the efficacy of the CART/STING-L treatment also depended on STING signaling in CART cells.

Conclusions

Our data show that 2′3′-cGAMP is a suitable adjuvant to combine with CART-cell therapy, allowing the induction of an endogenous T-cell response that prevents the outgrowth of Ag-loss tumor variants.
Impact of cancer on short-term in-hospital mortality after primary acute myocardial infarction
Authors: Zheng Robert , Kusunose Kenya , Okushi Yuichiro , Okayama Yoshihiro , Nakai Michikazu , Sumita Yoko , Ise Takayuki , Yamaguchi Koji , Yagi Shusuke , Fukuda Daiju , Yamada Hirotsugu , Soeki Takeshi , Wakatsuki Tetsuzo , Sata Masataka
Published: November 2021

Background

Cardiovascular diseases are the second most common cause of mortality among cancer survivors, after death from cancer. We sought to assess the impact of cancer on the short-term outcomes of acute myocardial infarction (AMI), by analysing data obtained from a large-scale database.

Methods

This study was based on the Diagnosis Procedure Combination database in the Japanese Registry of All Cardiac and Vascular Diseases and the Diagnosis Procedure Combination. We identified patients who were hospitalised for primary AMI between April 2012 and March 2017. Propensity Score (PS) was estimated with logistic regression model, with cancer as the dependent variable and 21 clinically relevant covariates. The main outcome was in-hospital mortality.

Results

We split 1 52 208 patients into two groups with or without cancer. Patients with cancer tended to be older (cancer group 73±11 years vs non-cancer group 68±13 years) and had smaller body mass index (cancer group 22.8±3.6 vs non-cancer 23.9±4.3). More patients in the non-cancer group had hypertension or dyslipidaemia than their cancer group counterparts. The non-cancer group also had a higher rate of percutaneous coronary intervention (cancer 92.6% vs non-cancer 95.2%). Patients with cancer had a higher 30-day mortality (cancer 6.0% vs non-cancer 5.3%) and total mortality (cancer 8.1% vs non-cancer 6.1%) rate, but this was statistically insignificant after PS matching.

Conclusion

Cancer did not significantly impact short-term in-hospital mortality rates after hospitalisation for primary AMI.
Value of imaging to guide interventional procedures in rheumatic and musculoskeletal diseases: a systematic literature review informing EULAR points to consider
Authors: Bosch Philipp , Carubbi Francesco , Scirè Carlo Alberto , Baraliakos Xenofon , Falzon Louise , Dejaco Christian , Machado Pedro M
Published: November 2021

Objectives

To summarise current data on the value of imaging to guide interventional procedures in patients with rheumatic and musculoskeletal disease (RMDs) informing an European Alliance of Associations for Rheumatology taskforce.

Methods

A systematic literature review was conducted to retrieve prospective and retrospective studies published in English and comparing different (imaging) techniques, different settings and procedural protocols to guide interventions in patients with RMDs. MEDLINE, EMBASE, the Cochrane Library and Epistemonikos databases were searched through October 2021. Risk of bias (RoB) was assessed using the Cochrane RoB tool for randomised trials V.2 (ROB2), the RoB tool for Non-Randomised Studies of Interventions and the appraisal tool for cross-sectional studies.

Results

Sixty-six studies were included (most with moderate/high RoB); 49 were randomised controlled trials, three prospective cohort studies and 14 retrospective studies. Fifty-one studies compared either one imaging technique with another imaging technique, or with palpation-guided interventions. Ultrasound (US) was most frequently studied (49/51), followed by fluoroscopy (10/51). Higher accuracy was found for US or fluoroscopy compared with palpation-guided interventions. Studies comparing different imaging techniques (12/51) did not endorse one specific method. Different settings/equipment for imaging-guided procedures (eg, automatic vs manual syringes) were investigated in three studies, reporting heterogeneous results. Fifteen studies compared different imaging-guided procedures (eg, intra-articular vs periarticular injections).

Conclusion

Higher accuracy of needle positioning at joints and periarticular structures was seen in most studies when using imaging (especially US) guidance as compared with palpation-guided interventions with the limitation of heterogeneity of data and considerable RoB.
Peat surface compression reduces smouldering fire potential as a novel fuel treatment for boreal peatlands
Authors: Deane P.J. , Wilkinson S.L. , Verkaik G.J. , Moore P.A. , Schroeder D. , Waddington J.M.
Published: November 2021

The wildfire regime in Canada’s boreal region is changing; extended fire seasons are characterized by more frequent large fires (≥200 ha) burning greater areas of land, whilst climate-mediated drying is increasing the vulnerability of peatlands to deep burning. Proactive management strategies, such as fuel modification treatments, are necessary to reduce fire danger at the wildland–human interface (WHI). Novel approaches to fuel management are especially needed in peatlands where deep smouldering combustion is a challenge to suppression efforts and releases harmful emissions. Here, we integrate surface compression within conventional stand treatments to examine the potential for reducing smouldering of near-surface moss and peat. A linear model (adj. R2 = 0.62, p = 2.2e−16) revealed that ground cover (F[2,101] = 60.97, p < 0.001) and compression (F[1,101] = 56.46, p < 0.001) had the greatest effects on smouldering potential, while stand treatment did not have a significant effect (F[3,101] = 0.44, p = 0.727). On average, compressed Sphagnum and feather moss plots showed 57.1% and 58.7% lower smouldering potential, respectively, when compared to uncompressed analogs. While practical evaluation is warranted to better understand the evolving effectiveness of this strategy, these findings demonstrate that a compression treatment can be successfully incorporated within both managed and unmanaged peatlands to reduce fire danger at the WHI.
Searching for clusters of targets under stochastic resetting
Authors: Calvert Georgia R. , Evans Martin R.
Published: November 2021

We consider diffusion under stochastic resetting to the origin in one dimension and compute the mean time to find both of two targets placed either side of the origin. A surprising result is that increasing the distance between two targets can decrease the overall search time. We compute the optimal arrangement of two targets in limiting cases. We generalise to obtain recursive expressions for the mean time to find all of multiple targets. We discuss the relevance to real-world problems of locating multiple targets such as proteins locating clusters of DNA lesions.

Graphic abstract
Observational appearances of a f(R) global monopole black hole illuminated by various accretions
Authors: Li Guo-Ping , He Ke-Jian
Published: November 2021

In this paper, we explore three simple models of accretions on a global monopole black hole in f(R) theory, and numerically study the corresponding observational appearances as seen by an observer located at the asymptotic infinity and the certain region out of black hole. For the thin-disk accretion, the results here show that the brighter lensing ring and the darker photon ring that around black hole shadow, always make a small contribution and a negligible contribution to total observed intensity respectively. While, the direct emission of disk contributes a dominant part, and the size of shadow always depends on the disk’s location. For the static and infalling spherical accretions, it turns out that the radiuses of the shadows and photon spheres are always same for both accretions, which implies that the boundary of shadow represents the signature of the spacetime geometry in this case. However, we also find that the brightness of shadow in infalling accretion is darker than that in static case since the Doppler effect is taken into account. In addition, the effect of the global monopole parameter $$\eta $$
η
and f(R) parameter $$\psi _0$$

ψ
0

on observational appearances of black hole are clearly emphasized throughout of this paper. Finally, we conclude that black hole shadows and the related rings with some different observable features can be used for us to distinguish black holes from different gravity theories and set the upper limits to the f(R) parameter $$\psi _0$$

ψ
0

.
Density functional theory study of adsorption and diffusion of potassium atoms on zigzag graphene nanoribbons with different terminal groups
Authors: Yang Junwei , Zhao Hua , Ke Lei , Liu Xing , Cao Shengbin
Published: November 2021

Despite the extensive use of graphene-based materials in K-ion batteries, the effects of various edge morphologies of graphene on K atom adsorption and diffusion are unclear. In this study, the effects of K atom adsorption and diffusion on zigzag graphene nanoribbons (ZGNRs) with hydrogen (−H), ketone (=O), hydroxyl (−OH), and carboxyl (−COOH) terminal groups were investigated by density functional theory calculations. ZGNRs terminating with −H, =O and −COOH promote K atom adsorption, whereas those terminating with −OH suppress it. The −H, =O, −OH and −COOH terminations have a negligible effect on K atom diffusion in the inner region of ZGNRs. In the edge region, the diffusion barriers are nearly unchanged for −H and −OH terminations; however, they are increased for =O and −COOH terminations in the edge region compared to those in the inner region. All the terminal groups hinder K atom diffusion from the edge region toward the inner region. Our results suggest that −H termination enhances K atom adsorption and has a negligible effect on the diffusion barrier of K atom in the edge region. Therefore, the ZGNR with −H termination could be a promising candidate for K-ion batteries.
Evidence for exon shuffling is sensitive to model choice
Authors: Cui Xiaoyue , Stolzer Maureen , Durand Dannie
Published: November 2021

The exon shuffling theory posits that intronic recombination creates new domain combinations, facilitating the evolution of novel protein function. This theory predicts that introns will be preferentially situated near domain boundaries. Many studies have sought evidence for exon shuffling by testing the correspondence between introns and domain boundaries against chance intron positioning. Here, we present an empirical investigation of how the choice of null model influences significance. Although genome-wide studies have used a uniform null model, exclusively, more realistic null models have been proposed for single gene studies. We extended these models for genome-wide analyses and applied them to 21 metazoan and fungal genomes. Our results show that compared with the other two models, the uniform model does not recapitulate genuine exon lengths, dramatically underestimates the probability of chance agreement, and overestimates the significance of intron-domain correspondence by as much as 100 orders of magnitude. Model choice had much greater impact on the assessment of exon shuffling in fungal genomes than in metazoa, leading to different evolutionary conclusions in seven of the 16 fungal genomes tested. Genome-wide studies that use this overly permissive null model may exaggerate the importance of exon shuffling as a general mechanism of multidomain evolution.
A new Bayesian approach for QTL mapping of family data
Authors: Zuanetti Daiane Aparecida , Milan Luis Aparecido
Published: November 2021

In this paper, we propose a new Bayesian approach for QTL mapping of family data. The main purpose is to model a phenotype as a function of QTLs’ effects. The model considers the detailed familiar dependence and it does not rely on random effects. It combines the probability for Mendelian inheritance of parents’ genotype and the correlation between flanking markers and QTLs. This is an advance when compared with models which use only Mendelian segregation or only the correlation between markers and QTLs to estimate transmission probabilities. We use the Bayesian approach to estimate the number of QTLs, their location and the additive and dominance effects. We compare the performance of the proposed method with variance component and LASSO models using simulated and GAW17 data sets. Under tested conditions, the proposed method outperforms other methods in aspects such as estimating the number of QTLs, the accuracy of the QTLs’ position and the estimate of their effects. The results of the application of the proposed method to data sets exceeded all of our expectations.
Hecke operators in Bredon (co)homology, K-(co)homology and Bianchi groups
Authors: Muñoz David , Plazas Jorge , Velásquez Mario
Published: November 2021

In this paper, we provide a framework for the study of Hecke operators acting on the Bredon (co)homology of an arithmetic discrete group. Our main interest lies in the study of Hecke operators for Bianchi groups. Using the Baum–Connes conjecture, we can transfer computations in Bredon homology to obtain a Hecke action on the [Formula: see text]-theory of the reduced [Formula: see text]-algebra of the group. We show the power of this method giving explicit computations for the group [Formula: see text]. In order to carry out these computations we use an Atiyah–Segal type spectral sequence together with the Bredon homology of the classifying space for proper actions.
Optical angiography for diabetes-induced pathological changes in microvascular structure and function: An overview
Authors: Zhu Jingtan , Li Dongyu , Yu Tingting , Zhu Dan
Published: November 2021

Diabetes mellitus (DM) is a kind of metabolic disorder characterized by chronic hyperglycemia and glucose intolerance due to absolute or relative lack of insulin, leading to chronic damage of vasculature within various organ systems. These detrimental effects on the vascular networks will result in the development of various diseases associated with microvascular injury. Modern optical imaging techniques provide essential tools for accurate evaluation of the structural and functional changes of blood vessels down to capillaries level, which can offer valuable insight on understanding the development of DM-associated complications and design of targeted therapy. This review will briefly introduce the DM-induced structural and functional alterations of vasculature within different organs such as skin, cerebrum and kidneys, as well as how novel optical imaging techniques facilitate the studies focusing on exploration of these pathological changes of vasculature caused by DM both in-vivo and ex-vivo.
Dynamic Structural Role Node Embedding for User Modeling in Evolving Networks
Authors: Wang Lili , Huang Chenghan , Lu Ying , Ma Weicheng , Liu Ruibo , Vosoughi Soroush
Published: November 2021

Complex user behavior, especially in settings such as social media, can be organized as time-evolving networks. Through network embedding, we can extract general-purpose vector representations of these dynamic networks which allow us to analyze them without extensive feature engineering. Prior work has shown how to generate network embeddings while preserving the structural role proximity of nodes. These methods, however, cannot capture the temporal evolution of the structural identity of the nodes in dynamic networks. Other works, on the other hand, have focused on learning microscopic dynamic embeddings. Though these methods can learn node representations over dynamic networks, these representations capture the local context of nodes and do not learn the structural roles of nodes. In this article, we propose a novel method for learning structural node embeddings in discrete-time dynamic networks. Our method, calledHR2vec, tracks historical topology information in dynamic networks to learn dynamic structural role embeddings. Through experiments on synthetic and real-world temporal datasets, we show that our method outperforms other well-known methods in tasks where structural equivalence and historical information both play important roles.HR2veccan be used to model dynamic user behavior in any networked setting where users can be represented as nodes. Additionally, we propose a novel method (called network fingerprinting) that usesHR2vecembeddings for modeling whole (or partial) time-evolving networks. We showcase our network fingerprinting method on synthetic and real-world networks. Specifically, we demonstrate how our method can be used for detecting foreign-backed information operations on Twitter.
Universal Equivalence and Majority of Probabilistic Programs over Finite Fields
Authors: Barthe Gilles , Jacomme Charlie , Kremer Steve
Published: November 2021

We study decidability problems for equivalence of probabilistic programs for a core probabilistic programming language over finite fields of fixed characteristic. The programming language supports uniform sampling, addition, multiplication, and conditionals and thus is sufficiently expressive to encode Boolean and arithmetic circuits. We consider two variants of equivalence: The first one considers an interpretation over the finite field
F

q

, while the second one, which we call universal equivalence, verifies equivalence over all extensions
F

q
k

of
F

q

. The universal variant typically arises in provable cryptography when one wishes to prove equivalence for any length of bitstrings, i.e., elements of
F

2
k

for any
k
. While the first problem is obviously decidable, we establish its exact complexity, which lies in the counting hierarchy. To show decidability and a doubly exponential upper bound of the universal variant, we rely on results from algorithmic number theory and the possibility to compare local zeta functions associated to given polynomials. We then devise a general way to draw links between the universal probabilistic problems and widely studied problems on linear recurrence sequences. Finally, we study several variants of the equivalence problem, including a problem we call majority, motivated by differential privacy. We also define and provide some insights about program indistinguishability, proving that it is decidable for programs always returning 0 or 1.
Hierarchical Scheduling of an SDF/L Graph onto Multiple Processors
Authors: Oldja Mari-Liis , Kim Jangryul , Jeong Dowhan , Ha Soonhoi
Published: November 2021

Although dataflow models are known to thrive at exploiting task-level parallelism of an application, it is difficult to exploit the parallelism of data, represented well with loop structures, since these structures are not explicitly specified in existing dataflow models. SDF/L model overcomes this shortcoming by specifying the loop structures explicitly in a hierarchical fashion. We introduce a scheduling technique of an application represented by the SDF/L model onto heterogeneous processors. In the proposed method, we explore the mapping of tasks using an evolutionary meta-heuristic and schedule hierarchically in a bottom-up fashion, creating parallel loop schedules at lower levels first and then re-using them when constructing the schedule at a higher level. The efficiency of the proposed scheduling methodology is verified with benchmark examples and randomly generated SDF/L graphs.
Metformin improves relevant disease parameters in an autosomal dominant polycystic kidney disease mouse model
Authors: Pastor-Soler Núria M. , Li Hui , Pham Jessica , Rivera Daniel , Ho Pei-Yin , Mancino Valeria , Saitta Biagio , Hallows Kenneth R.
Published: November 2021

Metformin treatment improved ADPKD disease severity in a relevant, slowly progressive ADPKD mouse model that recapitulates a PKD-associated PKD1 mutation. Relative to controls, metformin reduced kidney weight/body weight, cystic index and BUN levels, while improving GFR, blood pressure and anemia. Metformin also reduced key inflammatory and injury markers, along with cell proliferation markers. These findings suggest several beneficial effects of metformin in this ADPKD mouse model, which may help inform new ADPKD therapies in patients.
Competencies in Digitalization: An Experiment in an International Course
Authors: Erro-Garcés Amaya , Hernández Palaceto Celia
Published: November 2021

This research aims to explore competencies in the digital global context through an international experiment conducted at the Veracruzana University in Mexico and the Public University of Navarre in Spain. In this paper, we report test scores of a course from both universities (N = 85). The course was grounded on Industry 4.0 and digital transformation. Students were required to work in international teams through virtual communication and coworking tools. The main findings show that digital competencies though necessary, do not seem sufficient. Additionally, the research identifies the most developed competencies (decision-making and cognitive development competencies) and the competencies that need to be strengthened (digital competencies). From a practical perspective, the international experiment facilitates a collaborative learning scenario.
Neural Network for Intelligent and Efficient Volleyball Passing Training
Authors: Liu Bo , Yang Ning , Han Xiangwei , Liu Chen
Published: November 2021

Passing is a relatively basic technique in volleyball. In volleyball passing teaching, training the correct passing technique plays a very important role. The correct pass can not only accurately grasp the direction of the ball point and the drop point but also effectively connect the defense and the offense. In order to improve the efficiency and quality of volleyball passing training, improve the precise extraction of sport targets, reduce redundant feature information, and improve the generalization performance and nonlinear fitting capabilities of the algorithm, this paper studies volleyball based on the nested convolutional neural network model and passing training wrong movement detection method. The structure of the convolutional neural network is improved by nesting mlpconv layers, and the Gaussian mixture model is used to effectively and accurately extract the foreground objects in the video. The nested multilayer mlpconv layer automatically learns the deep-level features of the foreground target, and the generated feature map is vectorized and input to the Softmax classifier connected to the fully connected layer for passing wrong behavior detection in volleyball training. Based on the detection of nearly 1,000 athletes’ action datasets, the simulation experiment results show that the algorithm reduces the acquisition of redundant information and shortens the calculation time and learning time of the algorithm, and the improved convolutional neural network has generalization performance and nonlinearity. The fitting ability has been improved, and the detection of abnormal volleyball passing behaviors has achieved a higher accuracy rate.
Intelligent Monitoring of Care Status for COPD Patients Based on Deep Learning
Authors: Chen Xiaoqun , Yao Yufen
Published: November 2021

To discuss the application method and effect of COPD patients in deep learning in intelligent monitoring, two groups were used under a reasonable selection of antibiotics specifically including reasonable and effective oxygen administration, atomization, sputum discharge treatment, psychotherapy, and rehabilitation training and treatment. Results were indicated, and there were significant differences between the lung function evaluation index and the two groups. Its intelligent monitoring mode was 97.5% and 80.0%, while the red blood cell ratio, arterial oxygen partial pressure (PaO2), pulse blood oxygen saturation (SpO2), arterial carbon dioxide partial pressure (PaCO2), and symptom improvement were better than artificial and were statistically significant (

P
<
0.05

). Therefore, the training of the anti-inspiratory muscle can effectively improve the lung function and dyspnea symptoms of COPD patients at the stable stage, thus greatly improving their respiratory function and ensuring the quality of life of patients, which is worthy of clinical application.
Artificial Intelligence in Geospatial Analysis for Flood Vulnerability Assessment: A Case of Dire Dawa Watershed, Awash Basin, Ethiopia
Authors: Tamiru Habtamu , Dinka Megersa O.
Published: November 2021

This study presents the novelty artificial intelligence in geospatial analysis for flood vulnerability assessment in Dire Dawa, Ethiopia. Flood-causing factors such as rainfall, slope, LULC, elevation NDVI, TWI, SAVI, K-factor, R-factor, river distance, geomorphology, road distance, SPI, and population density were used to train the ANN model. The weights were generated in the ANN model and prioritized. Initial values were randomly assigned to the NN and trained with the feedforward processes. Ground-truthing points collected from the historical flood events of 2006 were used as targeting data during the training. A rough flood hazard map generated in feedforward was compared with the actual data, and the errors were propagated back into the NN with the backpropagation technique, and this step was repeated until a good agreement was made between the result of the GIS-ANN and the historical flood events. The results were overlapped with ground-truthing points at 88.46% and 89.15% agreement during training and validation periods. Therefore, the application of the GIS-ANN for the assessment of flood vulnerable zones for this city and its catchment was successful. The result of this study can also be further considered along with the city and its catchment for practical flood management.
Identification of the Active Constituents and Significant Pathways of Shen-qi-Yi-zhu Decoction on Antigastric Cancer: A Network Pharmacology Research and Experimental Validation
Authors: Zeng Shuhong , Yu Zhibao , Xu Xintian , Liu Yuanjie , Li Jiepin , Zhao Danya , Song Changjuan , Lu Haixia , Zhao Yudong , Lu Weimin , Zou Xi
Published: November 2021

Shen-qi-Yi-zhu decoction (SQYZD) is an empirical prescription with antigastric cancer (GC) property created by Xu Jing-fan, a National Chinese Medical Master. However, its underlying mechanisms are still unclear. Based on network pharmacology and experimental verification, this study puts forward a systematic method to clarify the anti-GC mechanism of SQYZD. The active ingredients of SQYZD and their potential targets were acquired from the TCMSP database. The target genes related to GC gathered from GeneCards, DisGeNET, OMIM, TTD, and DrugBank databases were imported to establish protein-protein interaction (PPI) networks in GeneMANIA. Cytoscape was used to establish the drug-ingredients-targets-disease network. The hub target genes collected from the SQYZD and GC were parsed via GO and KEGG analysis. Our findings from network pharmacology were successfully validated using an in vitro HGC27 cell model experiment. In a word, this study proves that the combination of network pharmacology and in vitro experiments is effective in clarifying the potential molecular mechanism of traditional Chinese medicine (TCM).
Research on School Classroom Teaching Model Based on Clustering Algorithm and Fuzzy Control
Authors: Zhang Fujun , Li Aichuan , Shi Jianfei , Wang Dongxin
Published: November 2021

The method of computational intelligence to monitor and evaluate the concentration of students in the teaching process can promptly and effectively adjust the learning plan and improve the learning effect. In this article, clustering algorithm and fuzzy control methods are used to construct a research model of students’ attention in class. In addition, this article uses the existing MATLAB-based image feature recognition algorithm to detect and obtain facial features and analyze the main features of facial expressions through computational techniques to realize the judgment of attention. In addition, this article optimizes the traditional AdaBoost algorithm to save computing time and improve operating efficiency and system performance stability. Finally, this article constructs the functional modules of the research model according to actual needs and designs experiments to verify the performance of the model. Experimental research results show that the model constructed in this article has a certain effect.
Prognostic Value of MTV and TLG of 18F-FDG PET in Patients with Stage I and II Non-Small-Cell Lung Cancer: a Meta-Analysis
Authors: Wen Weibo , Piao Yongnan , Xu Dongyuan , Li Xiangdan
Published: November 2021

Purpose. The present systematic literature review and meta-analysis focused on examining the significance of total lesion glycolysis (TLG) and metabolic tumor volume (MTV) in predicting the prognosis of stages I/II non-small-cell lung cancer (NSCLC) based on 18F-FDG PET parameters. Methods. Electronic databases, including Cochrane Library, PubMed, and EMBASE, were comprehensively searched for retrieving relevant articles published in the English language. Furthermore, the significance of TLG and MTV in prognosis prediction was analyzed by pooled hazard ratios (HRs). Results. This work enrolled eight primary studies with 1292 I/II-stage NSCLC cases. The pooled HR (95% confidence interval [CI]) for the ability of increased TLG to predict progression-free survival (PFS) was 2.02 (1.30–2.13) (

P
=
0.350

), while for increased MTV it was 3.04 (1.92–4.81) (

P
=
0.793

). In addition, the pooled HR (95% CI) for the ability of increased TLG to predict overall survival (OS) was 2.16 (1.49–3.14) (

P
=
0.624

). However, higher MTV correlated with OS, and sensitivity analysis showed that the results were not stable. Multivariate and univariate analyses by subgroup analyses stratified by PFS of MTV and OS of TLG exhibited statistically significant differences, without any statistical heterogeneity across various articles. Conclusion. The present work suggests the predictive value of PET/CT among stage I and II NSCLC patients. Our results verified that stage I/II NSCLC cases with increased TLG and MTV had a higher risk of side reactions, and TLG is related to increased mortality risk.
Circ-DONSON Knockdown Inhibits Cell Proliferation and Radioresistance of Breast Cancer Cells via Regulating SOX4
Authors: Zhu Xiufang , Li Lei
Published: November 2021

Background. Circular RNAs have been validated as critical regulators in the development of breast cancer (BC). Circ-DONSON is involved in the progression of glioma and gastric cancer. However, the biological role of circ-DONSON in BC remains unclear, and the aim of this study was to explore the biological role of circ-DONSON in BC. Methods. Human tissue samples and BC cell lines were collected in this study. siRNAs against circ-DONSON were transfected into BC cell lines for silencing of circ-DONSON. Quantitative real-time PCR was used to test the circ-DONSON expression. Cell counting kit-8 (CCK-8), 5-bromo-2′ deoxyuridine enzyme-linked immunosorbent assay (BrdU-ELISA), colony formation, and caspase-3 activity assays were used to assess cell proliferation, cell survival, and cell viability. Western blotting analysis was used to detect the protein expression levels. Results. Our findings showed that circ-DONSON showed high expression in BC tissues and cell lines. CCK-8 and BrdU-ELISA assays showed that circ-DONSON knockdown inhibited BC cell proliferation. Moreover, cell survival, cell viability, and caspase-3 activity assays showed that circ-DONSON knockdown reduced the radioresistance of BC cells. Mechanistically, circ-DONSON regulated BC cell proliferation and radioresistance via SRY-box transcription factor 4 (SOX4). SOX4 overexpression significantly rescued the effect of circ-DONSON knockdown on BC cell proliferation and radioresistance. Moreover, circ-DONSON activated the Wnt/β-catenin pathway in BC cells via SOX4. Conclusion. Our study concluded that circ-DONSON knockdown hindered cell proliferation and radioresistance through the SOX4/Wnt/β-catenin pathway in BC.
Federated Learning Model with Adaptive Differential Privacy Protection in Medical IoT
Authors: Ni Lina , Huang Peng , Wei Yongshan , Shu Minglei , Zhang Jinquan
Published: November 2021

With the proliferation of intelligent services and applications authorized by artificial intelligence, the Internet of Things has penetrated into many aspects of our daily lives, and the medical field is no exception. The medical Internet of Things (MIoT) can be applied to wearable devices, remote diagnosis, mobile medical treatment, and remote monitoring. There is a large amount of medical information in the databases of various medical institutions. Nevertheless, due to the particularity of medical data, it is extremely related to personal privacy, and the data cannot be shared, resulting in data islands. Federated learning (FL), as a distributed collaborative artificial intelligence method, provides a solution. However, FL also involves multiple security and privacy issues. This paper proposes an adaptive Differential Privacy Federated Learning Medical IoT (DPFL‐MIoT) model. Specifically, when the user updates the model locally, we propose a differential privacy federated learning deep neural network with adaptive gradient descent (DPFLAGD‐DNN) algorithm, which can adaptively add noise to the model parameters according to the characteristics and gradient of the training data. Since privacy leaks often occur in downlink, we present differential privacy federated learning (DP‐FL) algorithm where adaptive noise is added to the parameters when the server distributes the parameters. Our method effectively reduces the addition of unnecessary noise, and at the same time, the model has a good effect. Experimental results on real‐world data show that our proposed algorithm can effectively protect data privacy.
A Corpus-Based Study of the Linguistic Errors Committed by the Iranian EFL Learners in English Translation of MA Research Abstracts of Educational Management Based on Liao’s (2010) Model
Authors: Pourshahian Bahar
Published: November 2021

Given the importance and the precision required in the translation of research abstracts, this descriptive quantitative research made an attempt to investigate the analysis of the type and frequency of the linguistic errors occurring in the English translations of 40 academic MA research abstracts in the field of educational management. To this end, 40 academic MA thesis abstracts in the field of educational management from 2009 to 2019 were gathered from Shiraz Azad University through the saturation method. Then, the errors were categorized based on the classification of error types adapted from Liao’s model (2010). The results of the study revealed that based on Liao’s categorization (2010), the frequencies of possible linguistic errors by educational management include grammatical mistake or ungrammatical syntax of target language (F = 190), excessive literal translation, which leads to ambiguous translation (F = 30), awkward expression, including ambiguous meaning, mismatch, redundant words, and unnecessary repetition, (F = 29), incorrect character, improper punctuation marks, or inconsistency in term translation (F = 26), excessive free translation, which differentiates the translation from the original text (F = 6), and inappropriate register (F = 6).
Molecular and Clinical Characterization of Postpartum-Associated Breast Cancer in the Carolina Breast Cancer Study Phase I–III, 1993–2013
Authors: Vohra Sanah N. , Walens Andrea , Hamilton Alina M. , Sherman Mark E. , Schedin Pepper , Nichols Hazel B. , Reeder-Hayes Katherine E. , Olshan Andrew F. , Love Michael I. , Troester Melissa A.
Published: November 2021

Background:

Breast cancers in recently postpartum women may have worse outcomes, but studies examining tumor molecular features by pregnancy recency have shown conflicting results.

Methods:

This analysis used Carolina Breast Cancer Study data to examine clinical and molecular tumor features among women less than 50 years of age who were recently (≤10 years prior) or remotely (>10 years prior) postpartum, or nulliparous. Prevalence odds ratios (POR) and 95% confidence intervals (CI) were estimated using multivariable models.

Results:

Recently postpartum women (N = 618) were more frequently lymph node–positive [POR (95% CI): 1.66 (1.26–2.19)], estrogen receptor (ER)-negative [1.37 (1.02–1.83)], and IHC-based triple negative [1.57 (1.00–2.47)] compared with nulliparous (N = 360) women. Some differences were identified between recent versus remotely postpartum; smaller tumor size [0.67 (0.52–0.86)], p53 wildtype [0.53 (0.36–0.77)], and non–basal-like phenotype [0.53 (0.33–0.84)] were more common among recently postpartum. Recently postpartum (vs. nulliparous) had significant enrichment for adaptive immunity, T cells, B cells, CD8 T cells, activated CD8 T cells/natural killer (NK) cells, and T follicular helper (Tfh) cells and higher overall immune cell scores. These differences were attenuated in remotely (compared with recently) postpartum women.

Conclusions:

These results suggest a dominant effect of parity (vs. nulliparity) and a lesser effect of pregnancy recency on tumor molecular features, although tumor immune microenvironments were altered in association with pregnancy recency.

Impact:

Our study is unique in examining tumor immune microenvironment and RNA-based markers according to time since last childbirth. Future studies should examine the interplay between tumor features, postdiagnostic treatment, and outcomes among recently postpartum women.

See related commentary by McDonald et al., p. 518
Silent Information Regulator 1 Promotes Proliferation, Migration, and Invasion of Cervical Cancer Cells and Is Upregulated by Human Papillomavirus 16 E7 Oncoprotein
Authors: Wang Yujing , Wang Jing , Liu Chunmei , Li Min
Published: November 2021

Objective: Silent information regulator 1 (SIRT1), an NAD+-dependent III class histone deacetylase, plays crucial roles in cell proliferation, apoptosis, senescence, metabolism, and stress responses. Nevertheless, the role of SIRT1 in tumorigenesis remains unclear. Methods: In the present study, we measured expression levels of SIRT1 and HPV16 E7 protein in cervical cancer (CC) tissue and calculated their correlations. We measured the effect of silencing SIRT1 on the proliferation, migration, invasion, and apoptosis in human CC SiHa cells. Results: Immunohistochemistry results revealed that the expression of SIRT1 was upregulated with progression from CIN II–III to CC, but was not expressed in normal cervical tissues and CIN I. There was a positive correlation between SIRT1 expression and HPV16 E7 expression in CC tissues, and silencing of HPV16 E7 downregulated the expression of SIRT1. Depletion of SIRT1 downregulated SIRT1 expression, and inhibited proliferation, migration, and invasion of SiHa cells, inducing apoptosis. Conclusions: Taken together, the data suggest that SIRT1 promotes CC carcinogenesis. SIRT1 inhibition is a potential treatment strategy for CC.