bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Study on the Impact of Low-Carbon Policies on New Energy Vehicle Marketing in the Age of Artificial Intelligence
Authors: Li Xudong , He Shoukui , Wang Bo , Ma Weiwen 
Published: December 2023

Abstract
The country’s low-carbon policy makes the new energy industry vigorously promoted, and at the same time, the addition of artificial intelligence technology also makes the new energy and traditional fuel vehicles pull apart. This paper decomposes the influencing factors of transportation carbon emission by measuring the energy saving and emission reduction of transportation of new energy vehicles, using the extended Kaya constant equation of transportation carbon emission and the generalized Fisher index method. From the government subsidies and tax incentives in low carbon policies, the impact of policies on the performance of new energy vehicle enterprises is explored by analyzing the empirical regression results. The results show that the correlation coefficients of financial subsidies and enterprise performance are 0.135, 0.09, and 0.081, and the correlation coefficients of tax preferences and enterprise performance are 0.075, 0.172, 0.08, respectively, which indicate that low-carbon policies have positive incentive effects on new energy vehicle marketing. This paper provides a reference for the related low-carbon policy incentive theory.
Research on the Application of Chinese Cultural Elements in Product Packaging Design under the Background of Big Data
Authors: Yang Caijun 
Published: December 2023

Abstract
The K-means color extraction method based on clustering is used to extract Chinese cultural color elements in this paper, and they are intelligently laid out to design product packaging colors. In the processing of graphic elements, a SIFT-based algorithm is used to match the feature points, and the Chinese cultural graphic elements are aligned to design the graphics of product packaging. To investigate the extraction and application effects of color elements and graphic elements, a validation test was conducted on this basis. The results show that the overall effect value of traditional packaging color design is between [0.6, 0.7], the overall effect value of intelligent packaging design based on Chinese cultural elements is between [0.88,0.96], and the overall effect of the application of graphic elements of Chinese culture to product packaging design is high, with a difference of about 0.1 from the expected effect. Based on this study is able to apply the elements of Chinese culture to product packaging design.
Big data-based digital management system for the whole process of financial reporting in SMEs
Authors: Yu Xiaoli 
Published: December 2023

Abstract
Based on big data technology, this paper designs a digital management system for the whole process of financial reimbursement and gives the automatic transformation process of digitalization of financial reimbursement claims and accounting documents. In the K-Means algorithm, the AHC algorithm idea is introduced to construct the DH-K-Means clustering algorithm, which in turn enables the financial reimbursement behavioral portrait of enterprise employees to be constructed. To confirm the effectiveness of the system application in this paper, performance testing and portrait analysis were carried out. The results show that the maximum memory utilization of the database server is 50.42% when the number of concurrent users is 100, and the average response time of the system reaches a maximum of 825.63ms when the number of concurrent users is 200. Based on big data, the whole process of financial reporting digital management system has good stability, which can make enterprises more aware of their financial situation and then develop appropriate financial reimbursement strategies.
Deep neural network based acoustic pattern recognition system for fault localization application
Authors: Cui Yao , Huang Xin , Zhang Xin 
Published: December 2023

Abstract
This paper explores the process of traditional voiceprint recognition, analyzes the traditional GMM recognition algorithm, and proposes a GE2E-based voiceprint recognition algorithm by combining it with the deep neural network. It firstly uses the Bi-GRU network to replace the LSTM network to prevent the lack of semantic information, then adds the SGD algorithm to optimize the speech features, and finally improves the stability and accuracy of recognition by the GE2E loss function. On this basis, a voiceprint recognition system based on GE2E is designed, and the overall performance of the system is tested. Additionally, a voiceprint recognition system is being explored for fault localization. The results show that the recognition accuracy of male voiceprints in the test is at [0.89,0.95], and the recognition accuracy of female voiceprints is at [0.88,0.96], and there is not much difference in the voiceprint recognition accuracy of the voiceprint recognition system for both male and female students, and the overall recognition accuracy is greater than 0.9. When applied in fault location, the error between the measured distance and the actual fault distance is within 0.1 meters, enabling fault location.
Modeling Method of Multiplexed Sampling Electrical Parameter Characteristics Based on AIOT Sensing Module
Authors: Li Congcong , Jing Zhen , Zhu Hongxia , Zhang Zhi , Wang Qing , Zhao Xi 
Published: December 2023

Abstract
In order to further reduce the errors arising in synchronous sampling, this paper designs a multi-channel hybrid sampling electrical parametric feature modeling method based on an AIOT sensing module in the process of design. The AIOT sensing module is used to process the received RF signals using a transconductance amplifier to improve the digitization and reconfigurability of the RF front-end circuit. The signal is transformed and calculated using the Fast Fourier Transform to obtain electrical parameters such as the amplitude of each harmonic and the power factor. The results show that the variation amplitude of the window function of the design method in this paper is generally maintained between -1.5 and 1.5, the amplitude accuracy of the active power rate is within 3.17555%, and the relative error accuracy is within 0.000951%. It can be seen that the AIOT-based sensing module can significantly improve the calculation accuracy of electrical parameters and can be applied to the process of sampling digital measurements of other power signal characteristics.
Deep learning-based visual navigation control method for autonomous trajectory of UAVs
Authors: Lv Jing , Tu Lianghui 
Published: December 2023

Abstract
In this paper, a UAV intelligent visual navigation system is designed based on deep learning. To convert the pixel gray values, a Gaussian smoothing function is employed, which ensures that the main features of the visual image are preserved. A convolutional neural network is employed to mark the target with a frame using image pixels and obtain the coordinate position of the center point. Finally, the initial particles generated near the beacon are analyzed by particle filtering with color histograms, which are used to predict the position of the UAV at each autonomous trajectory point location. The control method proposed in this paper can keep the UAV attitude angle control error within 15%, and the minimum velocity error is 0.07%, as shown in the results. A deep learning-based visual navigation control system can guarantee that the UAV can accurately recognize the target in every autonomous trajectory.
Non-convex perturbation to evolution problems involving Moreau’s sweeping process
Authors: Boudjerida Nouha , Affane Doria , Yarou Mustapha Fateh 
Published: December 2023

Abstract
Along this paper, we study an evolution inclusion governed by the so-called sweeping process. The right side of the inclusion contains a set-valued perturbation, supposed to be the external forces exercised on the system. We prove existence and relaxation results under weak assumptions on the perturbation by taking a truncated Lipschitz condition. These perturbations have non-convex and unbounded values without any compactness condition; we just assume a linear growth assumption on the element of minimal norm. The approach is based on the construction of approximate solutions. The relaxation is obtained by proving the density of the solution set of the original problem in a closure of the solution set of the relaxed one.
Convex Least Angle Regression Based LASSO Feature Selection and Swish Activation Function Model for Startup Survival Rate
Authors: Allu Ramakrishna , Padmanabhuni Venkata Nageswara Rao 
Published: December 2023

Abstract
A startup is a recently established business venture led by entrepreneurs, to create and offer new products or services. The discovery of promising startups is a challenging task for creditors, policymakers, and investors. Therefore, the startup survival rate prediction is required to be developed for the success/failure of startup companies. In this paper, the feature selection using the Convex Least Angle Regression Least Absolute Shrinkage and Selection Operator (CLAR-LASSO) is proposed to improve the classification of startup survival rate prediction. The Swish Activation Function based Long Short-Term Memory (SAFLSTM) is developed for classifying the survival rate of startups. Further, the Local Interpretable Model-agnostic Explanations (LIME) model interprets the predicted classification to the user. Existing research such as Hyper Parameter Tuning (HPT)-Logistic regression, HPT-Support Vector Machine (SVM), HPT-XGBoost, and SAFLSTM are used to compare the CLAR-LASSO. The accuracy of the CLAR-LASSO is 95.67% which is high when compared to the HPT-Logistic regression, HPT-SVM, HPT-XGBoost, and SAFLSTM.
A Comprehensive Approach for Monitoring Student Satisfaction in Blended Learning Courses
Authors: Gaftandzhieva Silvia N. , Doneva Rositsa Zh. , Bliznakov Milen P. 
Published: December 2023

Abstract
Due to the great importance of student satisfaction with educational services, many HEIs conduct annual surveys. Analyzing the results of such surveys, tracking trends, and comparing the evaluation results to help governing bodies make data-driven decisions to take measures to improve the quality of courses is time-consuming and requires a lot of manual work. As a solution to the problem, this paper proposes a comprehensive approach to monitoring student satisfaction with the quality of blended learning courses. The developed software tool analyzes results and enables users with different roles to generate reports with aggregated results at different levels, allowing them to make informed decisions and take measures to ensure a higher quality of courses. The generated reports during the pilot experiments proved the tool’s applicability. This tool can be implemented in any HEI, regardless of the software systems used.
The Role of Integration Between Target Costing and Time-Driven Activity-Based Budgeting Techniques in Managing Time and Cost and its Reflection in Achieving Competitive Advantage
Authors: Al-Kawaz Salah Mahdi Jawad , Al-Daami Ahmed Naser Abbas , Abbas Ali Abdulhassan 
Published: December 2023

Abstract
Traditional cost systems are no longer able to provide the appropriate information in line with the developments and changes of the contemporary and competitive business environments. However, with a vibrant change in the functioning of businesses today, such cost system features have also been replaced to meet the dynamic business environments. If these two techniques are applied in coalition, it is possible for the economic units to manage their time and costs easily, which acts as a competitive advantage for those units. The current research study aims at studying the complementary relationships of these two techniques by applying them in one of the laboratories of General Company for Textile Industries in Hilla, which represents the men’s clothing factory in Najaf. Based on the analytical results, the researchers arrived at several conclusions, while the most important conclusion was the identification of the absence of features to apply the target costing and time-driven activity-based budgeting techniques. The most important recommendation made to the men’s clothing factory in Najaf is the need to pay adequate attention for the application of two techniques to achieve their goals.
The divergent legacies of the Yugoslav architectural heritage: The afterlives of “mesna zaednica” in Taftalidže, Skopje
Authors: Brsakoska Jana , Spasevska Danica , Daskalov Blagoj , Ilievski Ilcho 
Published: December 2023

Abstract
Ongoing urban developments and contemporary social challenges increase the need for different typologies of new urban and architectural concepts, where the issue of built heritage, specifically in the case of Skopje, has become a vast problem. With the decomposition of the former Yugoslavia states in the 1990s, each of these new states inherited a significant amount of built heritage, including monuments, buildings, landscapes, and infrastructure, constructed according to the prevailing socialist urban-planning and architectural doctrines, and directed within and towards the immediate contexts of the Yugoslav community. Most of this inherited architecture vanished across the ex-Yugoslav space, while a large part of it is still left in a state of limbo.
This article aims to show the socialist built heritage's adaptation, or transformation, into new urban scenarios, using the case of Skopje to reveal more about the relationship between the heritage and the local inhabitants. It will closely examine the socialist architecture and its relation with the local memory communities, or the locals’ memories. More precisely, we will focus on one unique construct that has slowly vanished in the modern-day living: the notion of mesna zaednica. In focusing on this notion in the urban district of Taftalidže, Skopje, we will discuss the means of transposing socialist communal features into the new, post-socialist architectural rhetoric and way of life, as well as engage with various discourses about urban heritage emerging in the urban context. Finally, we will argue in favor of several heritage and urban development theses, which can be applied to the particular case study. The article is part of an ongoing research project that presents its results in English for the first time.
Nanopore Formation at the Junctions of the Polycrystal Intergranular Boundary Under Plastic Deformation
Authors: Suchikova Y. , Kovachov S. , Lazarenko A. , Bohdanov I. , Popov A. I. 
Published: December 2023

Abstract
The article is devoted to the study of the mechanism of nanopore formation in the junctions of polycrystal grains under the plastic deformation of a polycrystal due to the conservative sliding of lattice dislocations. A mechanism for the formation of a stress concentrator at the junction of the polycrystal grain boundaries is proposed. The possibility of relaxation of the stress state due to the formation of a junction nanopore is considered in the paper.
Breast-lesion assessment using amide proton transfer-weighted imaging and dynamic contrast-enhanced MR imaging
Authors: Zhuang Lulu , Lian Chun , Wang Zehao , Zhang Ximin , Wu Zhigang , Huang Rong 
Published: December 2023

Abstract

Background
Previous studies have indicated that amide proton transfer-weighted imaging (APTWI) could be utilized for differentiating benign and malignant tumors. The APTWI technology has increasingly being applied to breast tumor research in recent years. However, according to the latest literature retrieval, no relevant previous studies compared the value of APTWI and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in distinguishing benign lesions from malignant lesions. In the present study, the application of APTWI and DCE for differentiating the benign and malignant breast lesions was investigated.

Patients and methods
APTWI was performed on 40 patients (42 lesions) who were enrolled in this prospective study. The lesions were split into two groups, one with malignant breast lesions (n = 28) and the other with benign breast lesions (n = 14), based on the results of the histology. The measured image characteristics (APT value, apparent diffusion coefficient [ADC] value, and time-of-intensity-curve [TIC] type) were compared between the two groups, and the ROC curve was used to quantify the diagnostic performance on the basis of these factors. The correlation between the APT values and the estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 expression levels and histological grades was examined using Spearman's correlation coefficient.

Results
The measured APT and ADC values showed a strong inter-observer agreement according to the intraclass correlation coefficients (0.954 and 0.825). Compared to benign lesions, malignant lesions had significantly higher APT values (3.18 ± 1.07 and 2.01 ± 0.51, p < 0.001). Based on APTWI, DCE, diffusion-weighted imaging (DWI), and ADC + APTWI, ADC + DCE, and DCE + APTWI, the area-under-the-curve values were 0.915, 0.815, 0.878, 0.921, 0.916, and 0.936, respectively.

Conclusions
APTWI is a potentially promising method in differentiating benign and malignant breast lesions, and may it become a great substitute for DCE examination in the future.
Post-radiation xerostomia therapy with allogeneic mesenchymal stromal stem cells in patients with head and neck cancer: study protocol for phase I clinical trial
Authors: Strojan Primoz , Plavc Gaber , Kokalj Marko , Mitrovic Goran , Blatnik Olga , Lezaic Luka , Socan Aljaz , Bavec Aljosa , Tesic Natasa , Hartman Katrina , Svajger Urban 
Published: December 2023

Abstract

Background
Xerostomia is a common side effect of radiotherapy in patients with head and neck tumors that negatively affects quality of life. There is no known effective standard treatment for xerostomia. Here, we present the study protocol used to evaluate the safety and preliminary efficacy of allogeneic mesenchymal stromal stem cells (MSCs) derived from umbilical cord tissue.

Patients and methods
Ten oropharyngeal cancer patients with post-radiation xerostomia and no evidence of disease recurrence 2 or more years after (chemo)irradiation (intervention group) and 10 healthy volunteers (control group) will be enrolled in this nonrandomized, open-label, phase I exploratory study. MSCs from umbilical cord tissue will be inserted under ultrasound guidance into both parotid glands and both submandibular glands of the patients. Toxicity of the procedure will be assessed according to CTCAE v5.0 criteria at days 0, 1, 5, 28, and 120. Efficacy will be assessed by measuring salivary flow and analyzing its composition, scintigraphic evaluation of MSC grafting, retention, and migration, and questionnaires measuring subjective xerostomia and quality of life. In addition, the radiological, functional, and morphological characteristics of the salivary tissue will be assessed before, at 4 weeks, and at 4 months after the procedure. In the control group subjects, only salivary flow rate and salivary composition will be determined.

Discussion
The use of allogeneic MSCs from umbilical cord tissue represents an innovative approach for the treatment of xerostomia after radiation. Due to the noninvasive collection procedure, flexibility of cryobanking, and biological advantages, xerostomia therapy using allogeneic MSCs from umbilical cord tissue may have an advantage over other similar therapies.
Management of tumor volume changes during preoperative radiotherapy for extremity soft tissue sarcoma: a new strategy of adaptive radiotherapy
Authors: De Lamarliere Marion Geneau , Lusque Amélie , Khalifa Justine Attal , Esteyrie Vincent , Chevreau Christine , Valentin Thibaud , Gangloff Dimitri , Meresse Thomas , Courtot Louis , Rochaix Philippe , Boulet Bérénice , Graulieres Eliane , Ducassou Anne 
Published: December 2023

Abstract

Background
Using adaptive radiotherapy (ART), to determine objective clinical criteria that identify extremity soft tissue sarcoma (ESTS) patients requiring adaptation of their preoperative radiotherapy (RT) plan.

Patients and methods
We included 17 patients with a lower extremity ESTS treated between 2019 and 2021 with preoperative RT, using helicoidal intensity-modulated RT (IMRT) tomotherapy, before surgical resection. We collected clinical, tumor parameters and treatment data. Repositioning was ascertained by daily Megavoltage computed tomography (MVCT) imaging. Using the PreciseART technology we retrospectively manually delineated at least one MVCT for each patient per week and recorded volume and dosimetric parameters. A greater than 5% change between target volume and planned target volume (PTV) dosimetric coverage from the initial planning CT scan to at least one MVCT was defined as clinically significant.

Results
All 17 patients experienced significant tumor volume changes during treatment; 7 tumors grew (41%) and 10 shrank (59%). Three patients (18%), all undifferentiated pleomorphic sarcomas (UPS) with increased volume changes, experienced significant reductions in tumor dose coverage. Seven patients required a plan adaptation, as determined by practical criteria applied in our departmental practice. Among these patients, only one ultimately experienced a significant change in PTV coverage. Three patients had a PTV decrease of coverage. Among them, 2 did not receive plan adaptation according our criteria. None of the patients with decreased tumor volumes had reduced target volume coverage. Monitoring volume variations by estimating gross tumor volume (GTV) on MVCT, in addition to axial and sagittal linear tumor dimensions, appeared to be most effective for detecting reductions in PTV coverage throughout treatment.

Conclusions
Variations in ESTS volume are evident during preoperative RT, but significant dosimetric variations are rare. Specific attention should be paid to grade 2–3 UPSs during the first 2 weeks of treatment. In the absence of dedicated software in routine clinical practice, monitoring of tumor volume changes by estimating GTV may represent a useful strategy for identifying patients whose treatment needs to be replanned.
Locoregional therapy combined with systemic therapy (LRT + ST) for unresectable and metastatic intrahepatic cholangiocarcinoma: a systematic review and meta-analysis
Authors: Zhang Mengqi , Qi Weiwei , Qiu Xiaofei , Yu Chunpeng , Qiu Wensheng , Wang Song , Qiu Zhenkang 
Published: December 2023

Abstract

Background
The outcome of systemic therapy (ST) for unresectable and metastatic intrahepatic cholangiocarcinoma (iCCA) is poor. This study aims to further evaluate the efficacy and safety of locoregional therapy combined with systemic therapy (LRT + ST) compared with only ST in unresectable and metastatic iCCA by performing a systematic literature review and meta-analysis.

Methods
A comprehensive search was performed in PubMed, Web of Science, EMBASE, and the Cochrane Library up to November 3, 2022. The primary outcome was overall survival (OS), and the secondary outcomes were progression-free survival (PFS), objective response rate (ORR), and adverse events (AEs).

Results
Ten retrospective cohort studies with 3,791 unresectable or metastatic iCCA patients were enrolled in this study, including 1,120 who received ablation, arterially directed therapy (ADT), or external beam radiation therapy (EBRT) combined with ST. The meta-analysis showed that the LRT + ST group had a better OS (HR = 0.51; 95% CI =0.41–0.64; p value < 0.001), PFS (HR = 0.40, 95% CI = 0.22–0.71, p value = 0.002) and ORR (RR = 1.68; 95% CI = 1.17–2.42; p value = 0.005). Subgroup analysis showed that both ST combined with ADT (HR = 0.42, 95% CI = 0.31–0.56, p value < 0.001) and EBRT (HR = 0.67, 95% CI = 0.63–0.72, p value < 0.001) could improve OS. Neutropenia, thrombocytopenia, anemia, anorexia, and vomiting did not show significant differences between the groups (p value > 0.05).

Conclusions
Compared with only ST, LRT + ST improved survival outcomes for unresectable and metastatic iCCA patients without increasing severe AEs, which can further provide a basis for guidelines.