bluuebunny/crossref_metadata_2025 huggingface dataset:
Conditions associated with the initiation of domiciliary care following a hospital admission: a cohort study in East London, England
Authors: Grimm Fiona , Lewer Dan , Craig John , Rogans-Watson Rafi , Shand Jenny
Published: September 2022

Objective

Older people and people with complex needs often require both health and social care services, but there is limited insight into individual journeys across these services. To help inform joint health and social care planning, we aimed to assess the relationship between hospital admissions and domiciliary care receipt.

Design

Retrospective cohort study, using linked data on primary care activity, hospital admissions and social care records.

Setting

London Borough of Barking and Dagenham, England.

Participants

Adults aged 19 and over who lived in the area on 1 April 2018 and who were registered at a general practice in East London between 1 April 2018 and 31 March 2020 (n=140 987).

Outcome measures

The outcome was initiation of domiciliary care. We estimated the rate of hospital-associated care package initiation, and of care packages unrelated to hospital admission. We also described the characteristics of hospital admissions that preceded domiciliary care, including primary diagnosis codes.

Results

2041/140 987 (1.4%) participants had a domiciliary care package during a median follow-up of 1.87 years. 32.6% of packages were initiated during a hospital stay or within 7 days of discharge. The rate of new domiciliary care packages was 120 times greater (95% CI 110 to 130) during or after a hospital stay than at other times, and this association was present for all age groups. Primary admission reasons accounting for the largest number of domiciliary care packages were hip fracture, pneumonia, stroke, urinary tract infection, septicaemia and exacerbations of long-term conditions (chronic obstructive pulmonary disease and heart failure). Admission reasons with the greatest likelihood of a subsequent domiciliary care package were fractures and strokes.

Conclusion

Hospitals are a major referral route into domiciliary care. While patients admitted due to new and acute illnesses account for many domiciliary care packages, exacerbations of long-term conditions and age-related and frailty-related conditions are also important drivers.
Impact of spiritual healing on moderate depression in adults: a study protocol of a pilot randomised controlled trial (RCT)
Authors: Stub Trine , Irgens Audun Campell , Hansen Anne Helen , Knudsen-Baas Olav , Gåskjenn Cornelia , Kristoffersen Agnete E
Published: September 2022

Introduction

Depression is a common mental disorder and the (global) leading cause of all non-fatal burden of disease worldwide. Currently, supported treatment for depression is antidepressant medication and different psychotherapeutic interventions. Many patients experience, however, adverse effects of antidepressant medication, while at the same time the access to psychotherapeutic interventions are limited. Many patients who suffer from depression turn to complementary medicine and among those modalities often spiritual healing. There is some evidence that consulting a spiritual healer can be beneficial for patients who suffer from depression, and that spiritual healing is associated with low risk. The aim of this protocol is to conduct a pilot randomised controlled trial (RCT) (spiritual healing as addition to usual care vs usual care alone) in preparation of a larger trial in adults with moderate depression, to examine feasibility and individuals’ experience of spiritual healing.

Methods and analysis

This study is a pilot RCT with two parallel groups. A total of 28 adult patients with moderate depression, diagnosed by the physician and according to the Montgomery and Åsberg Depression Rating Scale criteria will be randomised to spiritual healing in addition to usual care (n=14) or usual care alone (n=14). To determine if there is a statistical indication of an effect of healing warranting a full-scale study; the separation test will be used. To investigate participants’ experience with spiritual healing, a qualitative study will be included using semistructured interviews. The data will be analysed based on a direct content analysis.

Ethics and dissemination

This protocol was approved by regional committees for medical and health research ethics by the identifier (63692). The results will be disseminated through open-access, peer-reviewed publications, in addition to stakeholders’ reporting and presenting at conferences.

Trial registration

Norwegian Centre for Research Data (845302) and clinicaltrials.gov (ID: NCT04766242)
GATA4 and GATA6 loss-of-expression is associated with extinction of the classical programme and poor outcome in pancreatic ductal adenocarcinoma
Authors: de Andrés Mónica P , Jackson Richard J , Felipe Irene , Zagorac Sladjana , Pilarsky Christian , Schlitter Anna Melissa , Martinez de Villareal Jaime , Jang Gun Ho , Costello Eithne , Gallinger Steve , Ghaneh Paula , Greenhalf William , Knösel Thomas , Palmer Daniel H , Ruemmele Petra , Weichert Wilko , Buechler Markus , Hackert Thilo , Neoptolemos John P , Notta Faiyaz , Malats Núria , Martinelli Paola , Real Francisco X
Published: September 2022

Objective

GATA6 is a key regulator of the classical phenotype in pancreatic ductal adenocarcinoma (PDAC). Low GATA6 expression associates with poor patient outcome.GATA4is the second most expressed GATA factor in the pancreas. We assessed whether, and how, GATA4 contributes to PDAC phenotype and analysed the association of expression with outcome and response to chemotherapy.

Design

We analysed PDAC transcriptomic data, stratifying cases according toGATA4andGATA6expression and identified differentially expressed genes and pathways. The genome-wide distribution of GATA4 was assessed, as well as the effects ofGATA4knockdown. A multicentre tissue microarray study to assess GATA4 and GATA6 expression in samples (n=745) from patients with resectable was performed. GATA4 and GATA6 levels were dichotomised into high/low categorical variables; association with outcome was assessed using univariable and multivariable Cox regression models.

Results

GATA4messenger RNA is enriched in classical, compared with basal-like tumours. We classified samples in 4 groups as high/low forGATA4andGATA6. Reduced expression ofGATA4had a minor transcriptional impact but low expression ofGATA4enhanced the effects ofGATA6low expression. GATA4 and GATA6 display a partially overlapping genome-wide distribution, mainly at promoters. Reduced expression of both proteins in tumours was associated with the worst patient survival.GATA4andGATA6expression significantly decreased in metastases and negatively correlated with basal markers.

Conclusions

GATA4andGATA6cooperate to maintain the classical phenotype. Our findings provide compelling rationale to assess their expression as biomarkers of poor prognosis and therapeutic response.
Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm
Authors: Ebigbo Alanna , Mendel Robert , Scheppach Markus W , Probst Andreas , Shahidi Neal , Prinz Friederike , Fleischmann Carola , Römmele Christoph , Goelder Stefan Karl , Braun Georg , Rauber David , Rueckert Tobias , de Souza Luis A , Papa Joao , Byrne Michael , Palm Christoph , Messmann Helmut
Published: September 2022

In this study, we aimed to develop an artificial intelligence clinical decision support solution to mitigate operator-dependent limitations during complex endoscopic procedures such as endoscopic submucosal dissection and peroral endoscopic myotomy, for example, bleeding and perforation. A DeepLabv3-based model was trained to delineate vessels, tissue structures and instruments on endoscopic still images from such procedures. The mean cross-validated Intersection over Union and Dice Score were 63% and 76%, respectively. Applied to standardised video clips from third-space endoscopic procedures, the algorithm showed a mean vessel detection rate of 85% with a false-positive rate of 0.75/min. These performance statistics suggest a potential clinical benefit for procedure safety, time and also training.
Identifying rotation and tillage practices that maintain or enhance soil carbon and its relation to soil health
Authors: Wepruk Erin , Diochon Amanda , Van Eerd Laura L. , Gregorich Edward , Deen Bill , Hooker David
Published: September 2022

Physical fractions of soil organic matter (SOM) are established indicators of management-induced change and have been used to estimate the soil carbon storage capacity and storage potential. Here, we use SOM physical fractions and soil textures to identify management practices that maintain or enhance soil health and carbon storage in agricultural soils in Ontario. Metadata from the National Soil Database were used to estimate carbon storage potentials and calculate carbon deficits. A map was created showing carbon deficits in Ontario's agricultural soils and indicates that these soils have the potential to store an additional 0 to 2 kg m−2 in the top 20 cm of the soil. Tillage system generally had no effect on the size of the carbon deficit at four long-term agricultural experiments (Delhi, Elora, Ottawa, and Ridgetown). There was only a significant tillage effect at Ridgetown and only in the maize–soybean crop rotation, where the carbon deficit was 2.95 g C kg soil−1 under conventional tillage compared to 8.97 g C kg soil−1 with no tillage. A statistically significant effect of crop rotation was detected in Elora and Ridgetown. In Elora, continuous alfalfa had the smallest carbon deficit (7.25 g C kg soil−1) and maize–soybean rotation had the largest deficit (12.07 g C kg soil−1). In Ridgetown, the maize–soybean rotation had the smallest carbon deficit (2.95 g C kg soil−1). Regression analysis showed a weak negative relationship ( R2 = 0.11; P < 0.001) between carbon storage deficits and soil health scores. This suggests that increasing SOM levels alone may not improve soil health.
Unitarity problems for an effective field theory description of early universe cosmology
Authors: Brandenberger Robert , Kamali Vahid
Published: September 2022

In the context of Effective Field Theory, the Hilbert space of states increases in an expanding universe. Hence, the time evolution cannot be unitary. The formation of structure is usually studied using effective field theory techniques. We study the constraints on effective field theory analyses of early universe models which come from demanding that the factor of the space of states corresponding to length scales where the primordial fluctuations are manifest does not suffer from the unitarity problem. For bouncing and emergent cosmologies, no constraints arise provided that the energy scale of the bounce or emergent phases is smaller than the ultraviolet (UV) cutoff scale. On the other hand, in the case of the inflationary scenario, non-trivial upper bounds on the energy scale of inflation arise.
Remittances, Household Welfare, and the COVID-19 Pandemic in Tajikistan
Authors: YAMADA EIJI , SHIMIZUTANI SATOSHI , MURAKAMI ENERELT
Published: September 2022

Remittance inflows are now the largest source of external financing to developing countries, but little research has yet firmly established the effect of remittances on household welfare. We investigate the case of Tajikistan, one of the most heavily remittance-dependent countries in the world. We use a panel dataset collected nationwide and employ an instrumental variable estimation to confirm a positive relationship between receiving remittances and household welfare after correcting for endogeneity. Moreover, we find that the effect of remittances on household spending is more pronounced in households whose head is male, older, and/or less educated. Then, we combine our estimated coefficients with the projected decline of remittance inflows as a result of the coronavirus disease (COVID-19) outbreak and show the pandemic’s adverse effect on household spending per capita.
Bank Credit Growth and Trust: Does Institutional Quality Matter? Evidence from the Association of Southeast Asian Nations
Authors: ALBAITY MOHAMED , MALLEK RAY SAADAOUI , MD. NOMAN ABU HANIFA , AL-TAMIMI HUSSEIN A. HASSAN
Published: September 2022

This study investigated whether the quality of governance, trustworthiness, and confidence impacts bank credit growth. In addition, we examined credit growth cyclicality in 10 members of the Association of Southeast Asian Nations. By employing data concerning 282 banks between 2012 and 2019, this study found that trustworthiness boosted bank credit growth. Overall, the increased quality of governance was found to increase credit growth, except for the specific indicators of voice and accountability and political stability, which were found not to influence bank credit growth. Moreover, similar to prior findings in related fields, the empirical results of this study confirmed the complementary effect of informal and formal institutions on bank credit growth. Lastly, results indicated that banks were pro-cyclical regarding credit growth. Overall, the results of this study highlighted the role of the supervisory powers of governments in boosting credit expansion, mainly during economic upturns.
DeltaDroid
: Dynamic Delivery Testing in Android
Authors: Ghorbani Negar , Jabbarvand Reyhaneh , Salehnamadi Navid , Garcia Joshua , Malek Sam
Published: September 2022

Android is a highly fragmented platform with a diverse set of devices and users. To support the deployment of apps in such a heterogeneous setting, Android has introduced
dynamic delivery
—a new model of software deployment in which optional, device- or user-specific functionalities of an app, called
Dynamic Feature Modules (DFMs)
, can be installed, as needed, after the app’s initial installation. This model of app deployment, however, has exacerbated the challenges of properly testing Android apps. In this article, we first describe the results of an extensive study in which we formalized a defect model representing the various conditions under which DFM installations may fail. We then present
DeltaDroid
—a tool aimed at assisting the developers with validating dynamic delivery behavior in their apps by augmenting their existing test suite. Our experimental evaluation using real-world apps corroborates
DeltaDroid
’s ability to detect many crashes and unexpected behaviors that the existing automated testing tools cannot reveal.
A Low-code Development Framework for Cloud-native Edge Systems
Authors: Zhang Wenzhao , Zhang Yuxuan , Fan Hongchang , Gao Yi , Dong Wei
Published: September 2022

Customizing and deploying an edge system are time-consuming and complex tasks because of hardware heterogeneity, third-party software compatibility, diverse performance requirements, and so on. In this article, we present TinyEdge, a holistic framework for the low-code development of edge systems. The key idea of TinyEdge is to use a top-down approach for designing edge systems. Developers select and configure TinyEdge modules to specify their interaction logic without dealing with the specific hardware or software. Taking the configuration as input, TinyEdge automatically generates the deployment package and estimates the performance with sufficient profiling. TinyEdge provides a unified development toolkit to specify module dependencies, functionalities, interactions, and configurations. We implement TinyEdge and evaluate its performance using real-world edge systems. Results show that: (1) TinyEdge achieves rapid customization of edge systems, reducing 44.15% of development time and 67.79% of lines of code on average compared with the state-of-the-art edge computing platforms; (2) TinyEdge builds compact modules and optimizes the latent circular dependency detection and message routing efficiency; (3) TinyEdge performance estimation has low absolute errors in various settings.
Effect of Calcar Screw in Locking Compression Plate System for Osteoporotic Proximal Humerus Fracture: A Finite Element Analysis Study
Authors: Lee Jung-Soo , Kim Jong Hoon , Kim Kwang Gi , Yoon Yong-Cheol
Published: September 2022

This study proposes a finite element analysis (FEA) model for complex fractures at the osteoporotic proximal humerus and investigates the relevance of using a calcar screw in surgical treatments using this model. Two types of three‐dimensional (3D) fracture models of patients with osteoporotic humerus were constructed reflecting the mechanical properties of the osteoporotic humerus, such as the Young’s modulus and Poisson’s ratio, and two load conditions mimicking the clinical environment were applied for simulation. Using the 3D models and the conditions, the FEA software calculated the concentration and distribution of stresses developing in the humerus, locking compression plate (LCP), and screws. Then, we evaluated and predicted the fixed state of a LCP system depending on whether the maximum stress value exceeded tensile strength. When axial force was applied, insertion of the calcar screw led to significant reduction of stress applied on screws in the fracture model having a medial gap by approximately 61%, from 913.20 MPa to 351.84 MPa. Based on the results, it was clearly confirmed that using of calcar screws improved the stability of a three‐part fractures and simultaneously reinforced medial support.
Analysis of Convolutional Neural Network Segmentation Algorithm of Adenomyoma
Authors: Jin Yi , Huang Wendi , Qu Qinghong
Published: September 2022

Adenomoma is a common disease occurring in the female uterus. The symptoms and pain of adenomoma seriously troubled the physical and mental health of contemporary women. However, because of the significant advantages of nondestructive and low price, ultrasound examination is used as the main imaging method for clinical diagnosis of gynecological diseases at the present stage and is often used in the initial screening and postoperative diagnosis and treatment of uterine diseases. Imaging provides a very rich information in the medical diagnosis of tumor and is a very important basis for the disease diagnosis and treatment at this stage. Ultrasound images are different from medical images such as X-ray and MRI. Because of the characteristics of imaging principles and noise interference, ultrasound images need to rely on rich clinical experience of doctors in the process of disease diseases, which increases the difficulty and work burden of doctors to some extent. Therefore, the project aims to study the deep learning segmentation method suitable for ultrasonic images. Combined with the Deeplab network in the convolutional neural network, comparing the results of the FCN network, and then finding that the Deeplab network has obvious advantages as an image segmentation model of uterine adenomyoma. In clinical practice, it can reduce the work burden of doctors and try in the direction of uterine adenomyomas ultrasound image segmentation, to fill the gap in this field.
A Noval Established Cuproptosis-Associated LncRNA Signature for Prognosis Prediction in Primary Hepatic Carcinoma
Authors: Luo Lan , Hu Xiaoyan , Huang Aoshuang , Liu Xiaofang , Wang Lingyun , Du Tao , Liu Lei , Li Ming
Published: September 2022

The copper ion content in the body maintains homeostasis, and when dysregulated, it can produce cytotoxicity and induce cell death through a variety of pathways. Cuproptosis refers to copper ions combining directly with acylated molecules, leading to the accumulation of oligomerization of lipoylated protein and subsequent downregulation of iron-sulfur cluster proteins; this induces proteotoxic stress and cell death. This study on the relationship between cuproptosis-related lncRNAs (CRLns) and the prognosis of primary hepatic carcinoma (PHC) has important clinical guiding significance for the diagnosis and treatment of PHC. Prognosis-related CRLRs were identified via rank-sum tests, correlational analyses, and univariate Cox regression, and a CRLR risk-scoring model (CRLRSM) was constructed using LASSO Cox regression. Patients were divided into high-risk and low-risk groups based on the median CRLRSM scores. Variance analysis for cuproptosis-related genes, gene set enrichment analysis, and correlational analysis for risk and immunity were performed using boxplots. Quantitative polymerase chain reactions were used to verify the CRLR levels in PHC cell lines. The study results showed that patients in the CRLRSM high-risk group had worse survival rates than those in the low-risk group. The PHC stage and risk score were independent prognostic factors for hepatocellular carcinoma. There were 7 CRLRs (MIR210HG, AC099850.3, AL031985.3, AC012073.1, MKLN1-AS, KDM4A-AS1, and PLBD1-AS1) associated with PHC prognosis, primarily through cellular metabolism, growth, proliferation, apoptosis, and immunity. In conclusion, the overexpression of 7 CRLRs in patients with PHC indicates a poor prognosis.
3D-VR Based Color Design Method for Interior Space in Iot Applications
Authors: Yang Mei
Published: September 2022

Virtual reality technology has grown in popularity as the economy and society have changed dramatically, and it is now being used in a wide range of applications. Interactive virtual technology’s deployment in the field of art has a wide range of possibilities due to its interaction, immersion, and real-time capabilities. The advantages of this technology, extremely in interiors and design, are unrivalled by other technologies. Virtual reality interior design can help designers and consumers understand the influence of “what you see is what you get,” while also expecting people to feel the visual concept in the 3D content of this model. The research and studies of interior decoration are conducted in this paper using visually stunning virtual reality technology, with the viewing public housing developments as the research object, creating a conceptual framework for successful research and innovation of interior design assisted by visually stunning Virtual reality (VR) technology. In this paper we applied the reliability to check the accuracy of questionnaire and descriptive statistics which summarises all the data.
Bioinformatic Data Mining for Candidate Drugs Affecting Risk of Bisphosphonate-Related Osteonecrosis of the Jaw (BRONJ) in Cancer Patients
Authors: Zhuang Jinpeng , Zu Jianing , Zhou Changlong , Sun Yi , Kong Pengyu , Jing Yongbin
Published: September 2022

Background. Bisphosphonate-related osteonecrosis of the jaw (BRONJ) leads to significant morbidity. Other coadministered drugs may modulate the risk for BRONJ. The present study aimed to leverage bioinformatic data mining to identify drugs that potentially modulate the risk of BRONJ in cancer. Methods. A GEO gene expression dataset of peripheral blood mononuclear cells related to BRONJ in multiple myeloma patients was downloaded, and differentially expressed genes (DEGs) in patients with BRONJ versus those without BRONJ were identified. A protein-protein interaction network of the DEGs was constructed using experimentally validated interactions in the STRING database. Overrepresented Gene Ontology (GO) molecular function terms and KEGG pathways in the network were analysed. Network topology was determined, and ‘hub genes’ with degree ≥2 in the network were identified. Known drug targets of the hub genes were mined from the ‘drug gene interaction database’ (DGIdb) and labelled as candidate drugs affecting the risk of BRONJ. Results. 751 annotated DEGs (

log
 
FC
≥
1.5

,

p
<
0.05

) were obtained from the microarray gene expression dataset GSE7116. A PPI network with 633 nodes and 168 edges was constructed. Data mining for drugs interacting with 49 gene nodes was performed. 37 drug interactions were found for 9 of the hub genes including TBP, TAF1, PPP2CA, PRPF31, CASP8, UQCRB, ACTR2, CFLAR, and FAS. Interactions were found for several established and novel anticancer chemotherapeutic, kinase inhibitor, caspase inhibitor, antiangiogenic, and immunomodulatory agents. Aspirin, metformin, atrovastatin, thrombin, androgen and antiandrogen drugs, progesterone, Vitamin D, and Ginsengoside 20(S)-Protopanaxadiol were also documented. Conclusions. A bioinformatic data mining strategy identified several anticancer, immunomodulator, and other candidate drugs that may affect the risk of BRONJ in cancer patients.
Analysis of the Potential and Influencing Factors of Regional Logistics Industry Development from the Perspective of Supply Chain
Authors: Jiang Fang
Published: September 2022

The logistics sector has grown to be the most significant component of the modern service sector, and to some extent, it not only directly supports economic growth but also indirectly creates favorable conditions for business operations. Modern logistics can meet the needs of the modern economy and society by taking advantages and prospects of digitization and information technology. However, China has a number of difficulties while switching to the development of logistics since the level of modern Chinese logistics development differs. Additionally, the supply chain mode’s logistics is a comprehensive and integrated operation, so based on the issues with Chinese regional logistics development from a supply chain viewpoint, this study evaluates the development potential of logistics supply chain and the influencing factors from many angles.
Recent Developments in Stimuli Responsive Smart Materials and Applications: An Overview
Authors: Ramakrishnan T. , Kumar S. Senthil , Chelladurai Samson Jerold Samuel , Gnanasekaran S. , Sivananthan S. , Geetha N. K. , Arthanari Ramesh , Assefa Gizachew Balcha
Published: September 2022

The term “smart materials” can be used to refer a wide variety of different kinds of substances. One capacity that is shared by all of them is the capability to radically alter one or more aspects while operating inside carefully controlled conditions. The age of intelligent materials is arrived, and we are living in it right now. An older definition of smart material described it as a substance that responds swiftly to the environment in which it is located. It has been argued that the word “smart material” now refers to any substance that is capable of detecting, transmitting, or processing a stimulus in order to produce a beneficial effect. This idea has been put forward as a possible expansion of the original meaning of the term. The purpose of this research is to define and categorize different types of intelligent materials. Uses of smart materials are being contemplated in a wide variety of domains, spanning from the realm of technology to that of the modern environment.
The Effect of Continuing Chemotherapy after Chemoradiotherapy during the Time to Surgery on Tumor Response and Survival for Local Advanced Rectal Cancer
Authors: Demiray Atike Gökçen , Yaren Arzu , Sungurtekin Uğur , Baltalarlı Papatya Bahar , Demirkan Neşe , Herek Duygu , Taşköylü Burcu Yapar , Gököz Doğu Gamze , Değirmencioğlu Serkan , Özgen Utku , Sağınç Halil , Çakıroğlu Umut , Özhan Nail , Karan Canan , Demirel Burçin Çakan , Doğan Tolga , Özdemir Melek
Published: September 2022

Aim. The current standard treatment of locally advanced rectal carcinoma is total mesorectal excision and postoperative adjuvant chemotherapy after neoadjuvant concurrent chemoradiotherapy (NCRT). Many studies have shown that pathological complete response (pCR) is an important prognostic factor for patients receiving NCRT. Many studies have therefore been conducted to increase pCR rates by changing the perioperative treatment strategies. Prolonging the chemotherapy time may be a reasonable way to increase the effectiveness of NCRT, pCR, and survival rates. We investigated whether neoadjuvant consolidation chemotherapy had an effect on tumor response and survival. Methods. The data of 163 patients diagnosed with locally advanced rectal carcinoma were evaluated. The data of 107 patients (Group 1) who were radiologically T3–T4 and/or N+ and received chemotherapy after NCRT until their operations were compared with the data of 56 patients (Group 2) who were operated after NCRT. Results. Group 1 patients had tumor and node downstaging. Their pCR was found significantly higher than in Group 2 (

p
=
0.005

). In Group 1 patients with T3, pCR was significantly higher than for those with T4. The elapsed time between NCRT and surgery was significantly longer in patients with pCR (respectively,

p
=
0.012

and

p
=
0.008

). Conclusion. Neoadjuvant consolidation chemotherapy after NCRT is a safe approach that can lead to higher pathological complete response rates. The time until surgery with neoadjuvant consolidation chemotherapy may provide the chance to follow the patient without surgery in addition to increasing pCR.
Optimization of Human Resource Administration System Based on DM Technology and Random Forest Algorithm
Authors: Ding Gongci
Published: September 2022

As the first resource of an enterprise, human resources are the core competitiveness of the enterprise and are paid more and more attention by the enterprise, so that the administration means and technology of human resources are constantly improved, and the human resource administration information system is gradually emerging in the enterprise. As enterprise manpower administration, how to make enterprise administration scientific and rational with the help of data mining(DM) technology, and how to mine information beneficial to enterprise decision-making from a large amount of data, has become an important issue to be considered at present. Based on DM technology and random forest algorithm, this paper studies the human resource administration (HRM) system. There are many different algorithms to realize the unique tree in a random forest. When the number of features reaches 8, the index value of Gini is 0.116, and the index value of Entropy is 0.106. From this, it can be seen that in a random forest, the effect of using the Gini index to manage human resources is better. The random forest can avoid overfitting, and its flexible report generation and analysis functions make human resource managers free from tedious daily work and focus on more challenging and creative human resource analysis, planning, employee motivation, and strategy.
Parameter Optimization of PET Plastic Preform Bottles in Injection Molding Process Using Grey-Based Taguchi Method
Authors: Berihun Ermias Aswossie , Bogale Teshome Mulatie
Published: September 2022

The paper investigated the optimization design of plastic injection molding process parameters for preformed bottle production using the grey-Taguchi method to minimize shrinkage defects. Diametrical (radial) and length (axial) shrinkage were taken as the responses for one-liter PET plastic preform bottle to perform optimization by controlling four injection molding process parameters. The obtained optimum parameter combination was 260°C melting temperature, 70°C molding temperature, 120 MPa holding pressure, and 15 s cooling time. Melting temperature was the most significant factor according to the ANOVA in PET plastic preform of bottle production. The experimental validation test was also performed using the optimal level settings, five samples of preforms were taken, and the result showed that the shrinkage of the preform was reduced by 22.55%. The average grey relational grade, 0.853, of the confirmation results was found between the confidence intervals of 0.581 and 1.125 for the 95% confidence level. Therefore, the confirmation test showed a good agreement between the predicted and experimental values.
Diagnostic and Prognostic Role of Serum Omentin and NGAL Levels in Egyptian Breast Cancer Patients
Authors: Abas Al-Shimaa Mahmoud , Sherif Mohamed H. , Elmoneam Farag Sara A.
Published: September 2022

Background. Breast cancer (BC) is globally the main cause of cancer-related deaths in women. Tumor biomarkers have significant role in diagnosis and predicting the prognosis and decide the specific therapy to each patient. Aim. In this study, we investigated whether omentin and NGAL levels were altered in patients with breast cancer and the relationship between these markers and their clinicopathological parameters. Subjects and Methods. This study included 120 patients with breast cancer and 30 healthy individuals served as controls. We measured the serum level of omentin and NGAL by ELISA technique. Results. Our results showed that there were statistically significant differences in serum omentin and NGAL levels between two groups. Also, in breast cancer patients, there was significant difference between omentin level, the same results with NGAL level and patient’s age, tumor size, lymph node, and metastasis. No significant relationship was found between omentin level and tumor grade, ER, PR, and HER2. The cutoff value for the prediction of breast cancer was determined at >113.2 ng/ml for omentin and >145.3 ng/ml for NGAL with a sensitivity of 91.7% and 100%, specificity of 100% and 80%, positive predictive value of 100% and 90.9%, negative predictive value of 85.7% and 100%, and accuracy of 94.4% and 93.3%, respectively. In conclusion, serum omentin and NGAL can be used as strong diagnostic markers for breast cancer.
Research on Tax Collection and Administration Application and Legal Issues Based on Big Data Analysis
Authors: Liuhong Chen
Published: September 2022

In the twenty-first century, in the era of rapid development of big data, people can make some basic problem analysis of the application of tax collection and administration and legal problems through big data. Between taxpayers and the tax collection and management system, the law is used to protect the legitimate rights and interests of taxpayers. Through the improvement and management of the supervision system, it can ensure that taxpayers can clearly know how much tax they should pay when paying taxes. At present, the urgent problem is to adjust the concept of tax, reconstruct the scope of tax, scientifically design the tax rate, and simplify the tax collection and administration procedures. This paper puts forward a more efficient tax process by comparing the tax data, the econometric study of tax, and the secret tax avoidance while the burden of the more poor rural tax class. Through the experiment proved, this paper studies the best tax collection and management mode, so that taxpayers can pay taxes more convenient and fast. The tax collection and administration system have been improved to make taxpayers’ information more comprehensive, which is very important for us to improve the efficiency in the twenty-first century, which is also a great breakthrough in the application of tax collection and administration. Due to the limitations of incomplete information, or that the information cannot keep up with the times, the tax collection and management system cannot completely correspond to the complete information of the correct taxpayers. Therefore, for the study of the taxation supervision system, it is necessary to use more algorithms in a more comprehensive way, so as to reduce the number of tax evaders and the number of active taxpayers.
Aberrant Expression of SIRT6 and VNN1 in Peripheral Blood Monocytes of Children with Primary Nephrotic Syndrome and Its Diagnostic and Prognostic Values
Authors: Han Peitong , Xi Xiaohong , Yuan Xiaoying , Li Chunzhen , Liu Ling , Cui Jieyuan
Published: September 2022

Objective. The objective is to explore the aberrant sirtuin-6 (SIRT6) and Vanin-1 (VNN1) protein expression in peripheral blood monocytes (PBM) of children with primary nephrotic syndrome (PNS) and its diagnostic and prognostic values. Methods. 83 child patients with nephrotic syndrome (NS) and 65 healthy volunteers were enrolled in the study. The test of SIRT6 and VNN1 was performed by the Western blot. The receiver operator characteristic (ROC) curve was used to analyze the diagnostic and prognostic value of SIRT6 and VNN1 for child patients with NS. The logistic regression was used to analyze the association of SIRT6 and VNN1 with the prognosis of NS child patients. Results. SIRT6 in monocytes in the study group was inferior versus the control, while VNN1 outweighed it. The AUC of the combined detection of SIRT6 and VNN1 for the diagnosis of NS was 0.854, with a sensitivity of 80.0% and a specificity of 80.7%. The AUC of combined detection of SIRT6 and VNN1 for the prognosis of NS was 0.860, with a sensitivity of 84.6% and a specificity of 79.2%. The logistic regression analysis showed that less than 21.09 in SIRT6 was the number of risk factors for the prognosis of NS child patients (

P
<
0.05

). Conclusion. SIRT6 and VNN1 are provided with diagnostic and prognostic values for NS.
MANet: End-to-End Learning for Point Cloud Based on Robust Pointpillar and Multiattention
Authors: Gan Xingli , Shi Hao , Yang Shan , Xiao Yao , Sun Lu
Published: September 2022

Detecting 3D objects in a crowd remains a challenging problem since the cars and pedestrians often gather together and occlude each other in the real world. The Pointpillar is the leader in 3D object detection, its detection process is simple, and the detection speed is fast. Due to the use of maxpooling in the Voxel Feature Encode (VFE) stage to extract global features, the fine-grained features will disappear, resulting in insufficient feature expression ability in the feature pyramid network (FPN) stage, so the object detection of small targets is not accurate enough. This paper proposes to improve the detection effect of networks in complex environments by integrating attention mechanisms and the Pointpillar. In the VFE stage of the model, the mixed-attention module (HA) was added to retain the spatial structure information of the point cloud to the greatest extent from the three perspectives: local space, global space, and points. The Convolutional Block Attention Module (CBAM) was embedded in FPN to mine the deep information of pseudoimages. The experiments based on the KITTI dataset demonstrated our method had better performance than other state-of-the-art single-stage algorithms. Compared with another model, in crowd scenes, the mean average precision (mAP) under the bird’s-eye view (BEV) detection benchmark increased from 59.20% of Pointpillar and 66.19% of TANet to 69.91 of ours, the mAP under the 3D detection benchmark was increased from 62% of TANet to 65.11% of ours, and the detection speed only dropped from 13.1 fps of Pointpillar to 12.8 fps of ours.
Simulation Design of a Live Working Manipulator for Patrol Inspection in Power Grid
Authors: Xie Tao , Li Zhengyu , Zhang Yongyun , Yuan Bin , Liu Xiao
Published: September 2022

The distribution line network is the electric power infrastructure directly facing the users, with the characteristics of large coverage and complex network, and its operation safety is directly related to the stability and reliability of the power supply system, which is the key link to ensure the safety of power supply and the reliability of residential electricity consumption. In order to realize the autonomous obstacle avoidance and autonomous navigation of the live working manipulator for inspection and maintenance of the power grid equipment, a mobile manipulator intelligent control method combining SumTree-weighted sampling and deep deterministic policy gradient (DDPG) is proposed. Firstly, the traditional DDPG algorithm is improved to optimize the action value function of Q-learning to get a better control strategy, and the weighted sampling technique is used to add priority to each sample in the replay buffer, which improves the learning speed and accelerates the convergence speed. The corresponding environmental state space is designed, and simulation experiments are conducted to verify the proposed manipulator control method. Simulation results demonstrate that the proposed method performs better than traditional DDPG and DQN methods in obstacle avoidance and navigation tasks, with faster convergence, better path planning ability, and lower offset cost, which can provide theoretical and technical references for realizing fully autonomous power grid inspection operations.
Mixture of Gaussian Processes Based on Bayesian Optimization
Authors: Mao Runjun , Cao Chengdong , Qian James Jing Yue , Wang Jiufan , Liu Yunpeng
Published: September 2022

This paper gives a detailed introduction of implementing mixture of Gaussian process (MGP) model and develops its application for Bayesian optimization (BayesOpt). The paper also develops techniques for MGP in finding its mixture components and introduced an alternative gating network based on the Dirichlet distributions. BayesOpt using the resultant MGP model significantly outperforms the one based on Gaussian process regression in terms of optimization efficiency in the test on tuning the hyperparameters in common machine learning algorithms. This indicates the success of the methods, implying a promising future of wider application for MGP model and the BayesOpt based on it.
Novel Curcumin‐Encapsulated α‐Tocopherol Nanoemulsion System and Its Potential Application for Wound Healing in Diabetic Animals
Authors: Ali Muhammad , Khan Nauman Rahim , Subhan Zakia , Mehmood Saima , Amin Adnan , Rabbani Imran , -Rehman Fazal-ur , Basit Hafiz Muhammad , Syed Haroon Khalid , Khan Ikram Ullah , Khan Muhammad Shuaib , Khattak Sehrish
Published: September 2022

Objective. This project was aimed at formulating a novel nanoemulsion system and evaluating it for open incision wound healing in diabetic animals. Methods. The nanoemulsions were characterized for droplet size and surface charge, drug content, antioxidant and antimicrobial profiling, and wound healing potential in diabetic animals. The skin samples excised were also analyzed for histology, mechanical strength, and vibrational and thermal analysis. Results. The optimized nanoemulsion (CR‐NE‐II) exhibited droplet size of26.76 ± 0.9 nm with negative surface charge (−10.86 ± 1.06 mV), was homogenously dispersed with drug content of68.05 ± 1.2%, released almost82.95 ± 2.2%of the drug within first 2 h of experiment with synergistic antioxidant (95 ± 2.1%) and synergistic antimicrobial activity against selected bacterial strains in comparison to blank nanoemulsion, and promoted significantly fast percent reepithelization (96.47%). The histological, vibrational, thermal, and strength analysis of selected skin samples depicted a uniform and even distribution of collagen fibers which translated into significant increase in strength of skin samples in comparison to the control group. Conclusions. The optimized nanoemulsion system significantly downregulated the oxidative stress, enhanced collagen deposition, and precluded bacterial contamination of wound, thus accelerating the skin tissue regeneration process.
Macroeconomic Multivariate Statistics and Regionalization Management Strategy Based on Random Matrix
Authors: Tan Juhua
Published: September 2022

This paper adopts the method of the random matrix to conduct an in-depth study and analysis of the management of macroeconomic multivariate statistics and regionalization, and to design its management strategy based on a random matrix. A combination of theoretical and applied research, combined with the experience of other cities, is used to study regional economic management using literature analysis, comparative analysis, and deductive induction by summarizing the results achieved in community management, studying its experience, exploring the significance of community management in ETDZs for social development, analyzing the current obstacles and contradictions affecting community management in Suqian ETDZ, and proposing relevant countermeasures for the problems arising therein to enrich the relevant theories and thus promote the level of community management in ETDZs to a higher level. Macroeconomic uncertainty refers to the changes that cannot be accurately observed, analyzed, and foreseen, i.e., the deviation of the expected value of the economy from the actual value. Not all macroeconomic fluctuations belong to the category of macroeconomic uncertainty, only unpredictable economic fluctuations are uncertain. It can be seen from the above that there is a corresponding relationship between the financial income correlation matrix and the random correlation matrix, and both are affected by the same random factors. The importance of uncertainty for macroeconomic policy making is undeniable, and its quantification is a key step. In this paper, we propose an econometric model to eliminate expectations and compare the advantages and disadvantages of different measurement models; we measure a system of fourteen macroeconomic indicators to reflect macroeconomic uncertainty and provide quantitative measurement results for the correct understanding of macroeconomic uncertainty and economic policy making. Factor analysis is used to analyze these six comprehensive aspects to obtain the six-dimensional comprehensive scores of each province and city, and the scores are normalized and visualized. Based on a certain understanding of the economic equilibrium structure of each province and city in China, and a certain control of the overall development of each region itself at this stage, the future economic development trend is studied.
Simulation Analysis of Physical Fitness Training via Deep Learning Algorithm
Authors: Ling Qingdong
Published: September 2022

Physical fitness is defined as a person’s capacity to perform at a high level in terms of their strength, speed, endurance, coordination, flexibility, agility, and other athletic attributes. The morphological and functional aspects of the human body are intimately linked when it comes to determining one’s level of physical fitness. It is possible to categorize physical fitness into two types: healthy physical fitness and competitive physical fitness, depending on the performance and role it plays in various groups of individuals. Competitive physical fitness is built on the foundation of healthy physical fitness, which is the ability of the organ systems to work properly for a particular set of people. Healthful physical fitness is a prerequisite for the future growth of competitive competition. The simulation study of physical fitness training is an important topic, regardless of whether the goal is to achieve healthy physical fitness or competitive physical fitness. This work combines it with deep learning algorithms to propose a strategy MPRN-ATT-LSTM for physical training simulation analysis. First, this work proposes the idea of a hybrid model, which uses a residual network structure (MPRN) with a pooling layer to learn features from time series to reduce the dimension. Then, the extracted feature vector is sent to the LSTM model for further feature extraction. Considering that the LSTM model has high requirements on sequence of input sequence, when input sequence is changed or unreasonable, it may lead to inaccurate feature extraction and affect the classification results. This work solves this problem by adding a self-attention mechanism, which can better focus on information important for classification and give higher weights. Finally, a large number of experiments are carried out in this work to verify the superiority of this method for simulation analysis of physical training.
Analysis of the Influencing Factors of Urban Sports Brand Sales Volume Based on AHP
Authors: Zhang Mingyue , Wu Yuxin , Zhou Xiaolong
Published: September 2022

In order to evaluate the brand image and help enterprises to build an ideal brand image, the influence factors of urban sports brand sales volume based on AHP are studied. The article takes the A sports brand as the research object, selects six dimensions including product dimension, enterprise dimension, and service image dimension, establishes a brand image evaluation model, and uses the AHP to study the A sports brand image. The experimental results show that: it is found that the overall evaluation value of A sports brand image is 81.153 points, which is rated as very satisfactory, it is proven that the research gives relevant recommendations for maintaining and developing brand image.