bluuebunny/crossref_metadata_2025 huggingface dataset:
Work engagement of psychiatric nurses: a scoping review protocol
Authors: Mukaihata Tsuyoshi , Kato Yuichi , Swa Toshiyuki , Fujimoto Hirokazu
Published: July 2022

Introduction

Psychiatric nurses face various stressors related to nurse–patient relationships, workplace interpersonal relationships and organisational problems, and are required to perform excellent work under stressful situations. As work engagement (a counterconcept of burnout) is a key factor that improves the performance of nurses, clarifying how to improve work engagement is an essential topic among researchers. Although some knowledge has been accumulated on the subject, no reviews have been conducted on the work engagement of psychiatric nurses. To fill the gap, this scoping review will examine the status of research activity on the work engagement of psychiatric nurses and identify related factors, consequently mapping the available research in this area.

Methods and analysis

The review will be conducted according to established scoping review methodological guidelines. The inclusion criteria will be based on nurses (participants), work engagement (concept), and psychiatric settings (context) without language or date restrictions. Regardless of the methodology or study design, research related to the work engagement of psychiatric nurses will be included. A systematic search will be conducted for MEDLINE, CINAHL and PsycINFO, with the searches being arranged by an information specialist through discussion. The first author will screen all potentially relevant publications, and the second author will independently screen a random sample comprising 10% of the manuscripts. Any disagreement will be resolved by a review team. Data will be extracted using a standardised extraction form, subsequently summarised through quantitative (frequencies) and qualitative analyses (narrative synthesis), and reported in the results of the review.

Ethics and dissemination

As the data will be collected from existing literature, ethical approval is not required. The findings will be disseminated through conference presentations and publication in a peer-reviewed journal. They are expected to help researchers enhance psychiatric nurses’ work engagement, consequently contributing to improving their performance.
CD47/SIRPα axis: bridging innate and adaptive immunity
Authors: van Duijn Anneloes , Van der Burg Sjoerd H , Scheeren Ferenc A
Published: July 2022

Myeloid immune cells are frequently present in the tumor environment, and although they can positively contribute to tumor control they often negatively impact anticancer immune responses. One way of inhibiting the positive contributions of myeloid cells is by signaling through the cluster of differentiation 47 (CD47)/signal regulatory protein alpha (SIRPα) axis. The SIRPα receptor is expressed on myeloid cells and is an inhibitory immune receptor that, upon binding to CD47 protein, delivers a ‘don’t eat me’ signal. As CD47 is often overexpressed on cancer cells, treatments targeting CD47/SIRPα have been under active investigation and are currently being tested in clinical settings. Interestingly, the CD47/SIRPα axis is also involved in T cell-mediated antitumor responses. In this perspective we provide an overview of recent studies showing how therapeutic blockade of the CD47/SIRPα axis improves the adaptive immune response. Furthermore, we discuss the interconnection between the myeloid CD47/SIRPα axis and adaptive T cell responses as well as the potential therapeutic role of the CD47/SIRPα axis in tumors with acquired resistance to the classic immunotherapy through major histocompatibility complex downregulation. Altogether this review provides a profound insight for the optimal exploitation of CD47/SIRPα immune checkpoint therapy.
Influence of time metrics on the treatment effect of intravenous alteplase prior to endovascular treatment in MR CLEAN-NO IV
Authors: Rinkel Leon A , Treurniet Kilian Maurizio , Kappelhof Manon , LeCouffe Natalie E , Bruggeman Agnetha A E , Nieboer Daan , van Zwam Wim H , Uyttenboogaart Maarten , Dippel Diederik W J , Emmer Bart J , Roos Yvo B W E M , Majoie Charles B L M , Coutinho J M
Published: July 2022

Background

We assessed whether the treatment effect of intravenous alteplase (IVT) prior to endovascular treatment (EVT) on functional outcome is modified by time metrics.

Methods

We used data from all patients included in MR CLEAN-NO IV, a randomized trial of IVT followed by EVT versus EVT alone in patients who presented directly to EVT-capable hospitals. The primary outcome was the modified Rankin Scale score at 90 days. We used ordinal regression with a multiplicative interaction term to assess if the effect of IVT is modified by onset-to-randomization (OTR), onset-to-IV-needle (OTN), door-to-groin (DTG) or needle-to-groin (NTG) times. Secondary outcomes included successful reperfusion (extended Thrombolysis In Cerebral Infarction Scale 2b–3) and symptomatic intracranial hemorrhage (sICH).

Results

In 539 included patients (266 allocated to IVT+EVT and 273 to EVT alone), median workflow times were OTR: 93 (IQR 71–145) min; OTN: 98 (IQR 75–156) min; DTG: 64 (IQR 51–78) min; and NTG: 28 (IQR 20–41) min. There was a significant association between worse outcomes and longer time intervals for all metrics except NTG. We found no interaction between any of the time metrics and IVT for the effect on functional outcome (p values for interaction: OTR=0.40, OTN=0.39, DTG=0.61, NTG=0.56). We also did not observe any significant interaction for successful reperfusion or sICH.

Conclusion

In MR CLEAN-NO IV, the effect of IVT prior to EVT was not modified by OTR, OTN, DTG or NTG times. Our results do not support the use of these metrics to guide IVT treatment decisions prior to EVT in comprehensive stroke centres.

Trial registration number

ISRCTN80619088.
Durability of concrete containing gypsum powder recycled from waste drywalls combined with high content of fly ash as supplementary cementing materials
Authors: Hansen Sarah , Sadeghian Pedram
Published: July 2022

To address the negative contribution of cement production on global carbon emissions, this study aims to reduce the cement content typically required in concrete by using partial replacement by gypsum powder recycled from waste drywalls (15%) and fly ash (50%), by weight. The durability of concrete cylinders made of the mixture was evaluated by testing the cylinders in compression after exposure to various environmental conditions for 1000, 3000, and 5000 h. A total of 45 specimens under 5 exposure conditions were considered. The conditions included dry, submerged in fresh water, submerged in seawater, and two groups rotated weekly between dry and submerged in either fresh water or seawater. Overall, specimens in both freshwater and seawater conditions after 5000 h showed strength higher than control specimens. Results indicate that the strength of the concrete specimens containing recycled gypsum powder and fly ash was not adversely affected by exposure to the conditions.
Rapid improvement of lake acid–base status in Atlantic Canada following steep decline in precipitation acidity
Authors: Houle Daniel , Augustin Fougère , Couture Suzanne
Published: July 2022

Policy measures resulted in reductions in acidic emission of sulfur and nitrogen in North America. Here, we conducted trend analyses on a 37-year database for atmospheric depositions and lake ( n = 78) chemistry in the provinces of Nova Scotia, New Brunswick, and Newfoundland and Labrador, in Canada. Sulfate, and particularly nitrate deposition, began to decrease strongly around the year 2000, resulting in strong pH increases in precipitation. Recovery was observed in most lakes with significant increases in pH and Gran alkalinity (AlcG). A piecewise regression approach detected coherent breaks and overlapping confidence intervals in the break years for precipitation pH and lake AlcG (to a lesser extent for lake pH), suggesting a rapid lake response to the sudden changes in acidic inputs. However, an increase in organic acid after 2000 decreases the rate of acid neutralizing capacity recovery nearly by half in about a third of the studied lakes. Despite the positive pH and AlcG trends, a significant proportion of lakes still have pH and calcium values below the recommended thresholds for aquatic life.
$$H_0$$ tension or M overestimation?
Authors: Mazo Brayan Yamid Del Valle , Romano Antonio Enea , Quintero Maryi Alejandra Carvajal
Published: July 2022

There is a strong discrepancy between the value of the Hubble parameter $$H_0^P$$

H
0
P

obtained from large scale observations such as the Planck mission, and the small scale value $$H_0^R$$

H
0
R

, obtained from low redshift supernovae (SNe). The value of the absolute magnitude $$M^{Hom}$$

M

Hom

used as prior in analyzing observational data is obtained from low-redshift SNe, assuming a homogeneous Universe, but the distance of the anchors used to calibrate the SNe to obtain M would be affected by a local inhomogeneity, making it inconsistent to test the Copernican principle using $$M^{Hom}$$

M

Hom

, since M estimation itself is affected by local inhomogeneities. We perform an analysis of the luminosity distance of low redshift SNe, using different values of M, $$\{M^P,M^R\}$$

{

M
P

,

M
R

}

, corresponding to different values of $$H_0$$

H
0

, $$\{H_0^P,H_0^R\}$$

{

H
0
P

,

H
0
R

}

, obtained from the model independent consistency relation between $$H_0$$

H
0

and M which can be derived from the definition of the distance modulus. We find that the value of M can strongly affect the evidence of a local inhomogeneity. We analyze data from the Pantheon catalog, finding no significant statistical evidence of a local inhomogeneity using the parameters $$\{M^R,H_0^R\}$$

{

M
R

,

H
0
R

}

, confirming previous studies, while with $$\{M^P,H_0^P\}$$

{

M
P

,

H
0
P

}

we find evidence of a small local void, which causes an overestimation of $$M^R$$

M
R

with respect to $$M^P$$

M
P

. An inhomogeneous model with the parameters $$\{M^P,H_0^P\}$$

{

M
P

,

H
0
P

}

fits the data better than a homogeneous model with $$\{M^R,H_0^R\}$$

{

M
R

,

H
0
R

}

, resolving the apparent $$H_0$$

H
0

tension. Using $$\{M^P,H_0^P\}$$

{

M
P

,

H
0
P

}

, we obtain evidence of a local inhomogeneity with a density contrast $$-0.140 \pm 0.042 $$

-
0.140
±
0.042

, extending up to a redshift of $$z_v =0.056 \pm 0.0002$$

z
v

=
0.056
±
0.0002

, in good agreement with recent results of galaxy catalogs analysis (Wong et al. in The local hole: a galaxy under-density covering 90 mpc, 2021).
The partial offloading algorithm of medical computing task based on intelligent sensing in ICU
Authors: Xiao Shengchun , Zhang Wenshui
Published: July 2022

In the face of increasing application requirements for instantaneous transmission in ICU. Many medical devices collect large-scale data but do not have the computing power to match. Features such as low latency, fast response and privacy encryption are becoming more and more urgent. So far, traditional IoT cloud computing has been unable to solve this problem, and only edge computing has the potential to solve these problems. Edge computing is an open platform that provides endpoint services close to the side of the object or data source using core capabilities such as network, computing, storage and application as one. There are two types of task offloading, binary offloading and partial offloading. Binary offloading is the classic task offloading method, especially in traditional cloud computing, but this offloading method has its own drawbacks. We propose a group wisdom-aware partial offloading algorithm that addresses a series of challenges posed by binary offloading. The algorithm introduces the concept of group wisdom awareness and compares several other mainstream task offloading strategies through experiments. The experimental results show that the algorithm has certain theoretical value and reference significance.
Fault Tolerance Method for Memory Based on Inner Product Similarity and Experimental Study on Heavy Ion Irradiation
Authors: Shao Cuiping , Li Huiyun , Du Guanghua , Guo Jinlong , Miao Zujia , Zhu Hongmei
Published: July 2022

As the feature sizes of integrated circuits are reduced to the nanometer scale, the total soft error rate (SER) in memory and the proportion of multiple bit upsets (MBUs) are significantly increasing. In order to ensure the information reliability, many error correction codes with strong error correction ability were proposed, such as Reed–Somolon (RS) code and Bose–Chaudhuri–Hocquenghem (BCH) code. However, these error correction codes have limited error correction capability, high algorithm complexity and large data redundancy. In this paper, a novel fault tolerance method for locating and correcting multiple bit errors in memory is proposed based on data similarity. The proposed method uses the inner product as the metric to analyze the similarity of the pre-protected data from the vertical and horizontal dimensions, respectively, and to construct the model of error location and correction. This method performs encoding and decoding in units of blocks and detecting and correcting in units of words, so it can correct any number of bits in a corrupted word with low redundancy overhead. Finally, irradiation tests were conducted on a commercial SRAM, and the feasibility of the proposed method is verified by using heavy ion [Formula: see text]Kr[Formula: see text] as irradiation source.
TS Model-LMI Based Observer for Improving Active Power Filter Performance
Authors: Terán R. A. de J. , Pérez J. , Beristáin J. A.
Published: July 2022

To avoid the negative effects of using a control signal with a ripple, which is generated by the feedback of measured active power filter (APF) variables, a nonlinear observer is employed in this paper. The observer design, through the use of exact TS models and Lyapunov-based LMI conditions, is achieved. Both the APF output current and the DC voltage are estimated by the observer, and they are used in the cascade control feedback. In this way, high gains in the inner control loop are employed, giving place to a control signal without undesired harmonic components or overmodulation. This allows an APF performance improvement for compensation tasks and for reducing the undesired components injection to the mains. A simulation and experimental comparison between APF results using observer and APF results without using observer is presented. Better results are achieved for the observer version case, reducing the THD from 47.6% to 4.8% in experimental conditions, satisfying the IEEE Standard 519TM-2014. Also, load change tests are carried out, where the stability of the system is kept. Moreover, by using the observer, a DC voltage sensor was not required, reducing the number of system sensors.
Prognosis of Cervical Cancer Disease by Applying Machine Learning Techniques
Authors: Kumawat Gaurav , Vishwakarma Santosh Kumar , Chakrabarti Prasun , Chittora Pankaj , Chakrabarti Tulika , Lin Jerry Chun-Wei
Published: July 2022

Cervical cancer is one of the deadliest diseases in women worldwide. It is caused by long-term infection of the skin cells and mucosal cells of the genital area of women. The most disturbing thing about this cancer is the fact that it does not show any symptoms when it occurs. In the diagnosis and prognosis of cervical cancer disease, machine learning has the potential to help detect it at an early stage. In this paper, we analyzed different supervised machine learning techniques to detect cervical cancer at an early stage. To train the machine learning model, a cervical cancer dataset from the UCI repository was used. The different methods were evaluated using this dataset of 858 cervical cancer patients with 36 risk factors and one outcome variable. Six classification algorithms were applied in this study, including an artificial neural network, a Bayesian network, an SVM, a random tree, a logistic tree, and an XG-boost tree. All models were trained with and without a feature selection algorithm to compare the performance and accuracy of the classifiers. Three feature selection algorithms were used, namely (i) relief rank, (ii) wrapper method and (iii) LASSO regression. The maximum accuracy of 94.94% was recorded using XG Boost with complete features. It is also observed that for this dataset, in some cases, the feature selection algorithm performs better. Machine learning has been shown to have advantages over traditional statistical models when it comes to dealing with the complexity of large-scale data and uncovering prognostic features. It offers much potential for clinical use and for improving the treatment of cervical cancer. However, the limitations of prediction studies and models, such as simplified, incomplete information, overfitting, and lack of interpretability, suggest that further efforts are needed to improve the accuracy, reliability, and practicality of clinical outcome prediction.
Gravitational cracking of stellar models with like-Tolman IV complexity factor
Authors: Andrade J. , Fuenmayor E. , Contreras E.
Published: July 2022

In this work, we analyze the appearance of cracking/overturning of a family of self-gravitating spheres. The models under consideration correspond to four anisotropic solutions with like-Tolman IV complexity factor obtained in the context of gravitational decoupling. The models present both cracking/overturning depending on the values of the free parameter involved. A detailed analysis and physical interpretation of the results obtained for each models are shown.
CNS: Interactive Intelligent Analysis of Financial Management Software Based on Apriori Data Mining Algorithm
Authors: Guo Yanlin
Published: July 2022

With the steady development of information technology, efficient, fast and safe enterprise financial management has received the focused attention of enterprise managers. Not only that, the integration of enterprise departments and financial operations is getting closer and closer. With the increasing business volume of enterprises, the interactive data generated by the data management system of the financial departments of enterprises has become increasingly prominent. Based on the research and analysis of enterprise financial data, combined with Apriori, clustering, decision tree and other data mining technologies, this paper extracts and utilizes massive financial data generated by the enterprise financial department in the daily management process, and designs and implements an intelligent analysis system of enterprise financial data based on data mining. It provides helpful financial information for the financial management department and senior management and assists the enterprise in making quick decisions.
The combination of resonance Raman spectroscopy and site directed mutagenesis to study the diverse aspects of heme protein structure and function
Authors: Sebastiani Federico , Dali Andrea , Smulevich Giulietta
Published: July 2022

This review provides examples illustrating the powerful combination of resonance Raman spectroscopy and site-directed mutagenesis to investigate the structure-function relationship in structurally different heme proteins with diverse physiological functionality. The selective mutation of key amino acid residues gives rise to distinct spectroscopic fingerprints, as a result of the subtle alterations of the heme pocket environment. This review includes, but it is not limited to, the study of: i) the interactions between bound exogenous ligands with distal residues, ii) the effects of hydrogen bonds between the proximal residues and the surrounding cavity, iii) the interaction between the peripheral substituents of the heme group with the protein matrix with the concomitant effect on specific biological processes.
Synergistic photodynamic and photothermal effects of organic nanomaterials derived from cross-linked porphyrin polymer
Authors: Zhang Ruilin , Zhu Yuyan , Luo Xiaogang , Zhang Quanquan , Wu Fengshou
Published: July 2022

Photodynamic therapy (PDT) and photothermal therapy (PTT) are promising therapeutic methods for cancer treatment. However, both PDT and PTT have their own limitations. Thus, it is highly desirable to synthesize a single photosensitizer, which exhibits both PDT and PTT therapeutic performances. We have designed and synthesized a new porphyrin-based polymer (ZP-PT) by cross-linking fluoroporphyrins (ZnPor) and HS-terminated pentaerythritol tetra(3-mercaptopropionate) (PETMP). After being transformed into nanoparticles (ZP-PT NPs), they showed excellent water dispersity with the average size of about 100 nm. ZP-PT NPs could generate reactive oxygen species (ROS) and thermal energy under 635 nm laser irradiation. The singlet oxygen yield and the photothermal conversion efficiency (PCE) of ZP-PT NPs were calculated to be 0.46 and 27.07% respectively, which were apparently higher than that of ZnPor NPs. In addition, ZP-PT NPs exhibited higher colloidal stability and photostability than that of ZnPor NPs. All these results suggested that ZP-PT NPs had great potential in photodynamic and photothermal synergistic treatment of cancer.
A Survey on NLP Resources, Tools, and Techniques for Marathi Language Processing
Authors: Lahoti Pawan , Mittal Namita , Singh Girdhari
Published: July 2022

Natural Language Processing (NLP) has been in practice for the past couple of decades, and extensive work has been done for the Western languages, particularly the English language. The Eastern counterpart, especially the languages of the Indian subcontinent, needs attention as not much language processing work has been done on these languages. Western languages are rich in dictionaries, WordNet, and associated tools, while Indian languages are lagging behind in this segment. Marathi is the third most spoken language in India and the 15th most spoken language worldwide. Lack of resources, complex linguistic facts, and the inclusion of prevalent dialects of neighbors have resulted in limited work for Marathi. The aim of this study is to provide an insight into the various linguistic resources, tools, and state-of-the-art techniques applied to the processing of the Marathi language. Initially, morphological descriptions of the Marathi language are provided, followed by a discussion on the characteristics of the Marathi language. Thereafter, for Marathi language, the availability of corpus, tools, and techniques to be used to develop NLP tasks is reviewed. Finally, gap analysis is discussed in current research and future directions for this new and dynamic area of research are listed that will benefit the Marathi Language Processing research community.
Polycrystalline Silicon Nanowire Field Effect Transistor Biosensors for SARS-CoV-2 Detection
Authors: Wu Chi-Chang
Published: July 2022

Disease detection and monitoring play a critical role in the ongoing COVID-19 pandemic. A comprehensive detection platform that enables early virus detection can effectively stem the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, a polycrystalline silicon nanowire field-effect transistor (NWFET) was developed to detect the spike protein of SARS-CoV-2. The NWFET were fabricated through the application of sidewall spacer etching to maintain a nanowire diameter of less than 100 nm. The on–off current ratio of the transistor reached 106, and its subthreshold swing was 125 mV/decade, indicating the transistor’s strong attributes and stability. The biosensor based on this transistor reached a sensitivity of 59 mV pH−1 when used to test solutions with a pH value ranging between 6 and 9. We employed the biosensor in the detection of the SARS-CoV-2 spike protein, and the results revealed that the characteristic curve gradually shifted toward the left as the antigen of spike protein progressively increased in concentration. The limit of detection was estimated to be 0.51 ag ml−1. The results of the real-time testing of the spike protein were also successful, verifying the performance and applicability of the biosensor as a rapid screening tool for SARS-CoV-2.
Arginine-induced glucagon secretion and glucagon-induced enhancement of amino acid catabolism are not influenced by ambient glucose levels in mice
Authors: Maruszczak Katharina , Rasmussen Christine , Ceutz Frederik R. , Ørgaard Anne , Elmelund Emilie , Richter Michael M. , Holst Jens J. , Winther-Sørensen Marie , Wewer Albrechtsen Nicolai J.
Published: July 2022

Glucagon is an essential regulator of our metabolism. Recent evidence suggests that the physiological actions of glucagon reside in amino acid catabolism in the so-called liver-α cell axis, in which amino acids stimulate glucagon secretion and glucagon enhances hepatic amino acid catabolism. Here, it is demonstrated that this feedback system is independent of glycemia possibly explaining why hyperglycemia in diabetes may not suppress α cell secretion.
Causal evidence for the higher-order origin of serial dependence suggests a multi-area account
Authors: Tschiersch Melanie
Published: July 2022

There has been recent interest in whether serial dependence, a temporal bias in working memory and perception, is generated by higher-order cognitive or sensory areas. Based on the literature suggesting prefrontal areas combined with a recent article by de Azevedo Neto and Bartels (de Azevedo Neto RM, Bartels A. J Neurosci 41: 9392–9402, 2021), providing causal evidence for serial dependence relying on premotor cortex but not on the visual area hV5/MT+, I here argue for a higher-order and multiarea origin of serial dependence.
Oropharyngeal capsaicin exposure improves infant feeding performance in an animal model of superior laryngeal nerve damage
Authors: Edmonds Chloe E. , German Rebecca Z. , Bond Laura E. , Mayerl Christopher J.
Published: July 2022

Chemical sensory interventions alter swallow physiology, which is well-documented in adults but relatively unexplored in infants. Using videofluoroscopy, we found that capsaicin exposure limited infant pigs’ bolus sizes to improve swallow performance without changing swallow frequency. Capsaicin increased the likelihood of safe swallowing with more moderately sized boluses and changed relationships between bolus size and tongue movements, which may impact performance. This work highlights the potential role of capsaicin in treating acute infant dysphagia.
Don’t watch your step: gaze behavior adapts with practice of a target stepping task
Authors: Cates Alexander , Gordon Keith E.
Published: July 2022

People consistently vary how they use visual information to inform walking. However, what drives this variation and how sampled visual information changes with locomotor learning is not well understood. Here, we find that gaze fixation locations moved farther ahead while step error decreases as participants practice a target stepping task. The results suggest that participants increasingly used a feedforward locomotor control strategy with practice.
Contribution of individual features to repetition suppression in macaque inferotemporal cortex
Authors: Williams Nathaniel P. , Olson Carl R.
Published: July 2022

When an image is presented twice in rapid succession, neurons of inferotemporal cortex exhibit repetition suppression, responding less strongly to the second than to the first presentation. It has been unclear whether this phenomenon depends on the selectivity of the neuron under study. Here, we show that, for a given neuron, suppression is deepest when features preferred by that neuron are repeated. The results argue for a mechanism based either on feature-specific suppression or fatigue.
[Retracted] General Industrial Environment and Health Design Software Using a Small Data‐Driven Neural Network Model
Authors: Xu Lijun , Zheng Jing , Gao Jun , Chen Wei , Chen Lu
Published: July 2022

The developed enterprise intellectual brain neural network platform for industrial environment and health design driven by small data converts the wisdom knowledge of enterprise designers into data and helps enterprises retain design experience, accumulate design knowledge results, sort out the design process, and shorten the design cycle. The goal of this project is to combine artificial intelligence, big data, the Internet of things, parameterization, and other computer technologies with the industrial environment and health design and development process of manufacturing enterprises to solve pain points for businesses and designers, as well as to develop and create a large‐scale product‐level general parameter intelligent design software. The development of this software project can greatly improve the work efficiency of designers, save the time spent by designers on low‐end repetitive labor, and in turn promote designers to engage in more valuable creative work and realize the digitization of entire product life cycle. It can also improve the inefficient and redundant work efficiency of designers, and designers can switch between multiple roles. At the same time, a design think tank is formed through the accumulation of enterprise design knowledge through data, and the neural network platform development of big data drives the design brain, that is, an efficient and intelligent industrial environment and health design expert system is generated, just like the enterprise brain, including expert think tanks, internal technical data encryption of enterprises interface, enterprise core technology think tank, enterprise production resources, risk control standard library, etc.
Research on Distributed Cooperative Intelligent Spectrum Sensing of UAV Cluster
Authors: Chi Wensheng , Wang Hai , Xie Wenjun , Zhang Peng , Ru Le
Published: July 2022

Spectrum sensing is important to improving the survivability of unmanned aerial vehicles (UAVs) in complex electromagnetic environments. At a low signal-to-noise ratio (SNR), a UAV cluster has more prominent advantages in cluster distributed cooperative sensing than a single UAV. Aiming at this urgent need, joint optimal design is carried out for adaptive spectrum sensing algorithm and distributed estimation algorithm to realize the distributed cooperative intelligent spectrum sensing of UAV cluster. In this paper, the adaptive theory is analyzed first, and the performance of the conventional energy-aware sensing method and the least mean square (LMS) spectrum sensing algorithm is compared. In a complex electromagnetic environment, it is proposed to replan the real-time network by deleting erroneous data nodes in order to eliminate parameter estimation deviations caused by data errors. Under the condition of ensuring detection probability, the fast spectrum sensing algorithm based on SNR estimation is optimized by adaptively selecting and setting the SNR threshold to solve the problem of complex and slow calculation. The superiority of distributed spectrum estimation algorithm without erroneous data nodes is verified at a low SNR, showing that the algorithm has a good steady-state error curve and avoids the impact of data errors on detection results. In addition, the effectiveness of optimizing the fast spectrum sensing algorithm by selecting and setting the SNR threshold is verified to improve the distributed cooperative intelligent spectrum sensing rate of UAV cluster.
Identifying Active Compounds and Mechanisms of Citrus changshan-Huyou Y. B. Chang against URTIs-Associated Inflammation by Network Pharmacology in Combination with Molecular Docking
Authors: Chen Shiyi , Huang Wenkang , Li Xiaoyu , Gao Lijuan , Ye Yiping
Published: July 2022

Purpose. The ripe fruits of Citrus changshan-huyou, known as Quzhou Fructus Aurantii (QFA), have been commonly used for respiratory diseases. The purpose of this study was to investigate their active compounds and demonstrate their mechanism in the treatment of upper respiratory tract infections (URTIs) through network pharmacology and molecular docking. Methods. The prominent compounds of QFA were acquired from TCMSP database. Their targets were retrieved from SwissTargetPrediction database, and target genes associated with URTIs were collected from DisGeNET and GeneCards databases. The target protein-protein interaction (PPI) network was constructed by using STRING database and Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were enriched. Visual compound-target-pathway network was established with Cytoscape. The effects of compounds were verified on the inhibitory activities against phosphoinositide 3-kinases (PI3Ks). Finally, the molecular docking was carried out to confirm the binding affinity of the bioactive compounds and target proteins. Results. Five important active compounds, naringenin (NAR), tangeretin (TAN), luteolin (LUT), hesperetin (HES), and auraptene (AUR), were obtained. The enrichment analysis demonstrated that the pathways associated with inflammation mainly contained PI3K/Akt signalling pathway, TNF signalling pathway, and so on. The most important targets covering inflammation-related proteins might be PI3Ks. In vitro assays and molecular docking exhibited that TAN, LUT, and AUR acted as PI3Kγ inhibitors. Conclusion. The results revealed that QFA could treat URTIs through a multi-compound, multi-target, multi-pathway network, in which TAN, LUT, and AUR acted as PI3Kγ inhibitors, probably contributing to a crucial role in treatment of URTIs.
Risk Factors of Acute Radiation-Induced Lung Injury Induced by Radiotherapy for Esophageal Cancer
Authors: Zhang Faen , Liao Lihua , Wei Song , Lu Yuqing
Published: July 2022

Objective. To investigate the risk factors of acute radiation-induced lung injury (acute RILI) induced by radiotherapy for esophageal cancer. Methods. A total of 206 patients with esophageal cancer who received radiotherapy in our hospital from January 2017 to March 2020 were selected. The general data such as gender, age, and comorbidities of the patients were collected, as well as the levels of cytokines (TNF-α, TNF-β, and IL-6) in peripheral blood before radiotherapy; radiotherapy dose-related parameters were recorded during radiotherapy. Follow-up was 12 months after radiotherapy. The patients with induced acute RILI after radiotherapy were set as the observation group (

n
=
75

). Patients without acute RILI after radiotherapy were set as the control group (

n
=
131

). Univariate and multivariate logistic regression analysis was performed on the risk factors of acute RILI induced by radiotherapy for esophageal cancer. Results. Univariate analysis and multivariate logistic regression analysis showed that the combined diabetes, total radiation dose, combined lung disease, physical factors (V30, Dmean), and preradiotherapy cytokine (TNF-α, TNF-β, and IL-6) elevated level was an independent risk factor for radiotherapy-induced acute RILI in esophageal cancer (

P
<
0.05

).Conclusion. Concomitant diabetes, total radiation dose, lung disease, physical factors (V30, Dmean), and levels of cytokines (TNF-α, TNF-β, and IL-6) before radiation therapy are risk factors for acute RILI induced by radiation therapy in esophageal cancer. The possibility of acute RILI should be comprehensively assessed according to the patient’s condition, and the radiotherapy regimen should be adjusted to reduce and avoid the induction of acute radiation-induced lung injury.
Self-Study System Evaluation of Oral English Based on Limit Theory
Authors: Ming Xing , Wang Xihong , Liu Wenlan
Published: July 2022

With the globalization of the contemporary social economy and its ever-increasing influence, it is particularly important to master a common language in the world at this stage English. For the subjects who have the opportunity to learn English, their listening, reading, writing, and other abilities are relatively good, but the speaking ability is relatively lacking. Therefore, the self-study of spoken English is particularly important for the improvement of the practical application ability of English, and an efficient self-study system will also play a better role in the self-study process. The efficiency of a system depends on the maximum and minimum magnitudes that the system can carry. Therefore, for the self-learning system of spoken English in this paper, it is necessary to calculate the maximum and minimum carrying capacity. Therefore, it is necessary to deal with the limit thinking of the maximum and minimum carrying capacity of the system. The evaluation based on limit theory in this paper is a kind of evaluation of the maximum and minimum carrying capacity of the English oral self-learning system by using the convergence and dispersion characteristics of limit thinking. In order to evaluate the performance of the oral English self-learning system, this paper implements the dynamic evaluator of the oral English self-learning system, and constructs a hardware system for the self-learning oral English. This paper also uses the hidden Markov model in the self-learning system and the application of the central limit theory. The corresponding experimental results show that the mean value of the spoken English test data is 25.1337, and the standard deviation is 2.01385, which is in line with the normal distribution. It shows that the evaluation based on the limit theory can make the operation of the spoken English self-learning system stable.
KIF26B Is Overexpressed in Medulloblastoma and Promotes Malignant Progression by Activating the PI3K/AKT Pathway
Authors: Liu Yajun , Zhang Xi , Pan Ruihan , Liang Xiaolong , Liu Qichang , Yang Chao , Li Xu
Published: July 2022

Medulloblastoma is one of the most common malignant tumors of the central nervous system in children. Although KIF2B was reported as an oncogene in several malignant tumor types, its role in medulloblastoma has not been studied so far. The PCR results of our study showed that KIF26B is highly expressed in medulloblastoma, and its high expression is associated with a high clinical stage. Knockdown the expression of KIF26B could significantly impair the proliferation and migration of medulloblastoma cells. KIF26B promotes the malignant progression of medulloblastoma by affecting the expression of phosphorylation of key proteins in the PI3K/AKT signaling pathway. With the help of 740 Y-P, activating the pi3k signaling pathway can partially rescue the phenotype. Therefore, our experimental results suggest that KIF26B is a potential target for medulloblastoma.
Application and Development of Computer-Aided Design Methods in Clothing Design under the Environment of Internet of Things
Authors: Li Yuan
Published: July 2022

With the rapid development of Internet technology, its computer-assisted functions are also rapidly improving and the changes in computer functions have brought great convenience to all the aspects of life. In the clothing industry, the application of computer-aided technology and the production of sample clothing and the rendering of clothing have been introduced. This method greatly shortens the cycle of making and designing clothes and also greatly reduces the workload of the staff. The main content of this article is to explore the influence of the application of CAD on clothing design. Starting from the actual needs of digitally designed clothing, the formation model of clothing and the basis of digital application are derived. In this article, computer-aided technique is used as a modeling development tool and its related functions are introduced through methods such as multideformation modeling and NURBS surface modeling. According to the functional characteristics of the computer-aided dye applicator, it is concluded that the dyeing effect of the model is also diverse, and then the virtual display effect of the digital three-dimensional model of the clothing is obtained. Through the digital design, the clothing design can not only meet the functional requirements but its performance also meets the reliability, stability, and safety. The experimental results show that with the increase of W, the area of the two-dimensional unfolding film gradually increases and the amplitude becomes smaller and finally stabilizes at 0.1263.
Emotion Monitoring of Hotel Staff Based on Mobile Network and Resource Allocation Algorithm
Authors: Lei Minghua
Published: July 2022

With the continuous growth of the number of mobile devices and the continuous development of the mobile internet, people’s demand for mobile communication services is also increasing. However, the wireless spectrum resources of cellular mobile communication networks are limited and are becoming increasingly scarce and tense. In order to improve the utilization of wireless spectrum resources, people have proposed the concept of device-to-device communication. In order to improve the robustness of the system and transmission delay tolerance service, which allows users to interrupt the probability method has certain tolerance, the maximum transmission power is greater than that of the traditional robust algorithm. By monitoring the emotions of hotel employees, it can be seen that the performance accuracy of the robust algorithm in this paper is high. Low job burnout will have a negative impact on hurt job satisfaction, while emotional fatigue and depersonalization will not directly affect job satisfaction. Among the two outcome variables of job burnout and job satisfaction, surface behavior positively affects emotional exhaustion and depersonalization but has no significant effect on job satisfaction. Deep behavior negatively affects depersonalization and low sense of accomplishment and positively affects work satisfaction.
Study on Mechanical Evolution Characteristics of Overburden Rock in “Knife Handle”-Type Fully Mechanized Top-Coal Caving Face
Authors: Li Ruilin , Jia Baoshan , Shen Zhuo , Zhang Maowei , Wang Zhiwen , Liu Linjie
Published: July 2022

Compared with that of equal-length working faces, the mechanical evolution mechanism of overburden rocks in “knife handle”-type mining sites is more complex. The form of roof fracture of knife handle-type mines is more variable, and the stress distribution near the interface is more concentrated, thereby severely threatening the safety of mining. To elucidate the mechanical evolution characteristics of rocks in knife handle-type fully mechanized top-coal caving mining sites, the geological conditions of the 22401 fully mechanized top-coal caving face in Hanjiawa coal mine are investigated. FLAC3D software is used to numerically simulate the abutment pressure, horizontal stress, and vertical displacement of the fully mechanized knife handle top-coal caving face. This provides an effective theoretical and technical framework for subsequent problems, such as mine pressure control, roof management, and support withdrawal under similar mining conditions. The simulation results indicate that when the working face is mined within the range 20–30 m before and after the knife handle caving, the stress distribution is considerably asymmetric, the abutment pressure and horizontal stress are overconcentrated, the maximum vertical stress is 18.41 MPa, and the maximum horizontal stress is 16.45 MPa. Influenced by mining stress and self-weight, the roof subsides and the floor bulges. The maximum sinkage of the roof is 268.9 mm and the maximum bottom drum displacement is 10.01 mm.
Monitoring of Sports Health Indicators Based on Wearable Nanobiosensors
Authors: Gong Ruyao , Liu Binghong
Published: July 2022

Biosensors are instruments that are sensitive to biological substances and convert their concentration into electrical signals for detection. Generally speaking, there are two main means to promote health: one is medical intervention, and the other is exercise intervention. Medicine is mainly the second half of the health decay of the whole person, that is, disease treatment and control, while exercise intervention is mainly to prevent and promote the first half of the health decay. The purpose of this paper is to study the biochemical properties of nanomaterials and the exercise health of the elderly. In this paper, an electrochemical research method for detecting the kinase activity of polynucleotides by streptavidin-gold nanoparticles and enzyme amplification is proposed based on the thermophysical properties of materials and the properties of nanoparticles. The experimental results show that, compared with the traditional electrochemical method, the method has the advantages of simple operation, high sensitivity, and high selectivity, its linear range is from 0 U/mL to 5 U/mL, and the detection limit is 0.01 U/mL. In contrast, AgNWs cotton fiber films exhibited lower volume resistivity. The experimental design of this paper provides a theoretical and practical basis for researchers and has great research significance for the innovative research and development of nanomaterials.
[Retracted] Design of Personalized Ideological and Political Education Resource Recommendation System in the Online Education Platform in the Network Environment
Authors: Yang Tao , Duan Zhiqun
Published: July 2022

In the network environment, online ideological and political education is facing many challenges, the mainstream values of education have been impacted, and the backward educational model, single communication method, and solidified educational content are not conducive to the smooth progress of ideological and political education. However, at the same time, its innovation also ushers in development opportunities, rich educational resources, information platforms, diversified education subjects, strongly targeted education models, etc., which can become favorable factors for educational innovation. To this end, online educators should seize the development opportunities, grasp the good network environment, actively build a network platform for ideological and political education, create a personalized ideological and political education resource recommendation system, and reform the ideological and political education classroom, effectively playing the role of the main position of educating people. Online education breaks through the limitations of time and space, allowing students to get guidance from online teachers without leaving home, and is favored by more and more primary and secondary school students because of its unique advantages. At present, the forms of tutoring for off‐campus online education in China are diverse, and there are several specific teaching modes. Whether online teaching can meet the needs of users is a problem worth studying.
Topological Optimization Design for a Multiscale Femoral Prosthesis Model Based on Homogenization Method
Authors: Cheng Cheng , Dai Ning , Huang Jie , Zhuang Yahong , Tang Tao , Yang Mengna
Published: July 2022

Femur is a thigh bone in humans, which is particularly prone to injury and difficult to mend if damaged. The stress shielding effect is caused by a change in bone mechanics transmission route as a result of femur bone damage. The formation of a porous structure provides a better solution to the problem of stress shielding effect reduction. The porous material is basically a solid which has empty space(s) which is not covered by the primary structure of particles that build up the solid’s structure. Traditional porous materials have a uniform density distribution in their microstructure. The density distribution of a material should be established according to different loads in each location of the material to completely represent its characteristics. In this paper, to acquire the ideal density distribution of porous materials and construct high-performance variable-density porous structures, topological optimization is applied into the design of the lattice structure. According to a structure constructed utilising individualised parameters paired with computed tomography (CT) data of the human femur, a topological optimization design of a multiscale femoral prosthesis model based on the homogenization approach is presented. Experiments on different femoral prosthesis architectures revealed that variable-density porous prostheses have superior material and stress distributions than equal-density porous prostheses under the same stress and successfully decreased femoral stress shielding to improve prosthetic stability.