bluuebunny/crossref_metadata_2025 huggingface dataset:
P53 expression correlates with low axillary tumor burden in breast cancer
Authors: Nicolau Pau , Masó Paula , Argudo Núria , Jiménez Marta , Martínez Ana Isabel , Vázquez Ivonne , Comerma Laura , Vernet-Tomás Maria
Published: December 2023

BACKGROUND: The p53 mutation in breast cancer confers a worse prognosis and is usually associated with p53 overexpression (p53+) on immunohistochemistry. Previous studies have shown that p53+ tumors could be associated with low axillary tumor burden (ATB). OBJECTIVE: We aimed to evaluate the association between p53+ and ATB in a large series of breast cancers as an aid to personalizing axillary surgical treatment. METHODS: We retrieved 1762 infiltrating breast carcinomas from our database that were treated with upfront surgery in Hospital del Mar from 2004 to 2018. We compared p53+ and p53-negative (p53-) tumors in terms of the percentage of cases with high ATB and overall survival. This comparison was made overall and for each immunophenotype. RESULTS: Overall, 18.7% of breast tumors were p53+. High ATB was less common in p53+ tumors than in p53- tumors in the luminal B-Her2-negative immunophenotype (6.2% versus 16.9%, respectively, P = 0.025), but not in the other immunophenotypes or overall. Overall survival was worse in patients with p53+ breast cancer (P = 0.002). CONCLUSION: p53+ breast cancers were associated with worse overall survival. However, low ATB was more common in these tumors than in p53- tumors in the luminal B-Her2-negative subtype. Information on p53 expression could be of use to predict ATB in some breast cancer tumors.
A clinical spectrum of resectable lung adenocarcinoma with micropapillary component (MPC) concurrently presenting as mixed ground-glass opacity nodules
Authors: Zhu Ziwen , Jiang Weizhen , Zhou Danhong , Zhu Weidong , Chen Cheng
Published: December 2023

BACKGROUND: In clinical practice, preoperative identification of mixed ground-glass opacity (mGGO) nodules with micropapillary component (MPC) to facilitate the implementation of individualized therapeutic strategies and avoid unnecessary surgery is increasingly important OBJECTIVE: This study aimed to build a predictive model based on clinical and radiological variables for the early identification of MPC in lung adenocarcinoma presenting as mGGO nodules. METHODS: The enrolled 741 lung adenocarcinoma patients were randomly divided into a training cohort and a validation cohort (3:1 ratio). The pathological specimens and preoperative images of malignant mGGO nodules from the study subjects were retrospectively reviewed. Furthermore, in the training cohort, selected clinical and radiological variables were utilized to construct a predictive model for MPC prediction. RESULTS: The MPC was found in 228 (43.3%) patients in the training cohort and 72 (41.1%) patients in the validation cohort. Based on the predictive nomogram, the air bronchogram was defined as the most dominant independent risk factor for MPC of mGGO nodules, followed by the maximum computed tomography (CT) value (> 200), adjacent to pleura, gender (male), and vacuolar sign. The nomogram demonstrated good discriminative ability with a C-index of 0.783 (95%[CI] 0.744–0.822) in the training cohort and a C-index of 0.799 (95%[CI] 0.732–0.866) in the validation cohort Additionally, by using the bootstrapping method, this predictive model calculated a corrected AUC of 0.774 (95% CI: 0.770–0.779) in the training cohort. CONCLUSIONS: This study proposed a predictive model for preoperative identification of MPC in known lung adenocarcinomas presenting as mGGO nodules to facilitate individualized therapy. This nomogram model needs to be further externally validated by subsequent multicenter studies.
How much partiality is needed for a theory of computability?
Authors: Spreen Dieter
Published: December 2023

Partiality is a natural phenomenon in computability that we cannot get around. So, the question is whether we can give the areas where partiality occurs, that is, where non-termination happens, more structure. In this paper we consider function classes which besides the total functions only contain finite functions whose domain of definition is an initial segment of the natural numbers. Such functions appear naturally in computation. We show that a rich computability theory can be developed for these functions classes which embraces the central results of classical computability theory, in which all partial (computable) functions are considered. To do so, the concept of a Gödel number is generalised, resulting in a broader class of numberings. The central algorithmic idea in this approach is to search in enumerated lists. In this way, function computability is reduced to set listability. Besides the development of a computability theory for the functions classes, the new numberings – called quasi-Gödel numberings – are studied from a numbering-theoretic perspective: they are complete, and each of the function classes numbered in this way is a retract of the Gödel numbered set of all partial computable functions. Moreover, the Rogers semi-lattice of all computable numberings of the considered function classes is studied and results as in the case of the computable numberings of the partial computable functions are obtained. The function classes are shown to be effectively given algebraic domains in the sense of Scott–Ershov. The quasi-Gödel numberings are exactly the admissible numberings of the computable elements of the domain. Moreover, the domain can be computably mapped onto every other effectively given one so that every admissible numbering of the computable domain elements is generated by a quasi-Gödel numbering via this mapping.
Time-series bioinformatics analysis of SARS-CoV-infected cells to identify the biological processes associated with severe acute respiratory syndrome
Authors: Fatehi Razieh , Khosravian Farinaz , Salehi Mansoor , Kazemi Mohammad
Published: December 2023

BACKGROUND: The COVID-19 pandemic, caused by the new virus of the coronavirus family, SARS-CoV-2, could lead to acute respiratory syndrome. The molecular mechanisms related to this disorder are still debatable. METHODS: In this study to understand the pathogenicity mechanism of SARS-CoV-2, using the bioinformatics approaches, we investigated the expression of involved genes, their regulatory, and main signaling pathways during the time on days 1, 2, 3, and 4 of SARS-CoV infected cells. RESULTS: Here, our investigation shows the complex changes in gene expression on days 2 and 3 post-infection. The functional analysis showed that especially related to immune response, response to other organisms, and defense response. IL6-AS1 is the predicted long non-coding RNA and is a key regulator during infection. In this study, for the first time has been reported the role of IL6-AS1. Also, the correlation of differential expression genes with the level of immune infiltration was shown in the relationship of Natural killer cells and T cell CD 4+ with DE genes. CONCLUSION: In the current study, identification of the altered expression pattern of genes in SARS-CoV-infected cells in time course also can help identify and link the molecular mechanisms and explore the holistic view of infection of SARS-CoV-2.
Building knowledge graphs from technical documents using named entity recognition and edge weight updating neural network with triplet loss for entity normalization
Authors: Jeon Sung Hwan , Lee Hye Jin , Park Jihye , Cho Sungzoon
Published: December 2023

Attempts to express information from various documents in graph form are rapidly increasing. The speed and volume in which these documents are being generated call for an automated process, based on machine learning techniques, for cost-effective and timely analysis. Past studies responded to such needs by building knowledge graphs or technology trees from the bibliographic information of documents, or by relying on text mining techniques in order to extract keywords and/or phrases. While these approaches provide an intuitive glance into the technological hotspots or the key features of the select field, there still is room for improvement, especially in terms of recognizing the same entities appearing in different forms so as to interconnect closely related technological concepts properly. In this paper, we propose to build a patent knowledge network using the United States Patent and Trademark Office (USPTO) patent filings for the semiconductor device sector by fine-tuning Huggingface’s named entity recognition (NER) model with our novel edge weight updating neural network. For the named entity normalization, we employ edge weight updating neural network with positive and negative candidates that are chosen by substring matching techniques. Experiment results show that our proposed approach performs very competitively against the conventional keyword extraction models frequently employed in patent analysis, especially for the named entity normalization (NEN) and document retrieval tasks. By grouping entities with named entity normalization model, the resulting knowledge graph achieves higher scores in retrieval tasks. We also show that our model is robust to the out-of-vocabulary problem by employing the fine-tuned BERT NER model.
Robust partial face recognition using multi-label attributes
Authors: Sang Gaoli , Zeng Dan , Yan Chao , Veldhuis Raymond , Spreeuwers Luuk
Published: December 2023

Partial face recognition (PFR) is challenging as the appearance of the face changes significantly with occlusion. In particular, these occlusions can be due to any item and may appear in any position that seriously hinders the extraction of discriminative features. Existing methods deal with PFR either by training a deep model with existing face databases containing limited occlusion types or by extracting un-occluded features directly from face regions without occlusions. Limited training data (i.e., occlusion type and diversity) can not cover the real-occlusion situations, and thus training-based methods can not learn occlusion robust discriminative features. The performance of occlusion region-based method is bounded by occlusion detection. Different from limited training data and occlusion region-based methods, we propose to use multi-label attributes for Partial Face Recognition (Attr4PFR). A novel data augmentation is proposed to solve limited training data and generate occlusion attributes. Apart from occlusion attributes, we also include soft biometric attributes and semantic attributes to explore more rich attributes to combat the loss caused by occlusions. To train our Attr4PFR, we propose an implicit attributes loss combined with a softmax loss to enforce Attr4PFR to learn discriminative features. As multi-label attributes are our auxiliary signal in the training phase, we do not need them in the inference. Extensive experiments on public benchmark AR and IJB-C databases show our method is 3% and 2.3% improvement compared to the state-of-the-art.
Screen-level bureaucrats in the age of algorithms: An ethnographic study of algorithmically supported public service workers in the Netherlands Police
Authors: Soares Carlos , Grimmelikhuijsen Stephan , Meijer Albert
Published: December 2023

Algorithms are rapidly transforming government bureaucracies. The implications of this transformation for the work of public service employees are not yet well understood. So far, the literature has mostly neglected the use of algorithms by these “screen-level bureaucrats”, and this constitutes a major gap in our knowledge about how algorithms affect bureaucracies. To understand the work of screen-level bureaucrats and to explore how they actively engage with algorithmic software to support their assessment of online fraud, we analyzed 45 hours of observations and 12 in-depth interviews at the Netherlands Police. We employ a socio-material perspective to analyze the dynamics between screen-level bureaucrats and algorithms. We conclude that for administrative tasks, algorithms help screen-level bureaucrats to perform their work by providing structured data and allowing them to focus more on assessments which need a nuanced judgement. At the same time, algorithmic advice in a decision-making task is simply ignored by the screen-level bureaucrats as they predominantly rely on their professional judgement in the assessment of online fraud reports. This highlights the need to further investigate how an algorithm should not only provide accurate advice to the screen-level bureaucrats but also convince them to follow it.
Investigating Sex Differences in Risk and Protective Factors in the Progression of Mild Cognitive Impairment to Dementia: A Systematic Review
Authors: Martin Jissa , Reid Natasha , Ward David D. , King Shannon , Hubbard Ruth E. , Gordon Emily H.
Published: December 2023

Background: Developing effective strategies for reducing dementia risk requires a detailed understanding of the risk and protective factors associated with the progression of mild cognitive impairment (MCI) to dementia. Objective: We aimed to systematically review the evidence for sex differences in these factors. Methods: Five online databases (PubMed/CINAHL/EMBASE/PsycINFO/Cochrane) were searched from inception until 17 October 2022 for cohort studies that focused on sex differences in risk and protective factors in the progression of MCI to dementia. Results: A total of 2,972 studies were identified, of which 12 studies from five countries were included in the systematic review. There was substantial variability in study designs, study populations and outcome measures. Sex differences were present in the associations of sociodemographic, health, psychological factors, genetic and other biomarkers with the progression of MCI to dementia. APOE ɛ4 status and depression appeared to increase the risk of progression for females, whereas history of stroke, MRI markers and cerebrospinal fluid biomarkers appeared to increase the risk of progression for males. APOE ɛ2 status and marital status (unmarried) were observed to reduce risk of progression in males and females, respectively. Conclusions: The ability of studies to accurately detail risk factors for dementia are likely limited when solely controlling for the effects of sex. Although the heterogeneity and underpowered nature of the studies made it difficult to synthesize the findings for each risk factor, this study highlights the apparent need for further research examining risk factors for dementia in males and females with MCI separately.
Correlation Between Amyloid PET Imaging and Discordant Cerebrospinal Fluid Biomarkers Results in Patients with Suspected Alzheimer’s Disease
Authors: Lojo-Ramírez Jose Antonio , Guerra-Gómez Miriam , Marín-Cabañas Alba Marta , Fernández-Rodríguez Paula , Bernal Sánchez-Arjona María , Franco-Macías Emilio , García-Solís David
Published: December 2023

Background: Although the concordance between cerebrospinal fluid (CSF) Alzheimer’s disease (AD) biomarkers and amyloid-PET findings is well known, there are no data regarding the concordance of amyloid-PET with inconclusive CSF values of amyloid-β (Aβ)1 - 42 and p-tau for the diagnosis of AD. Objective: To investigate the relationship between the amyloid-PET results with discordant AD biomarkers values in CSF (Aβ1 - 42+/p-tau–or Aβ1 - 42–/p-tau+). Methods: An observational retrospective study, including 62 patients with mild cognitive impairment (32/62) or dementia (30/62), suspicious of AD who had undergone a lumbar puncture to determine CSF AD biomarkers, and presented discordant values in CSF between Aβ1 - 42 and p-tau (Aβ1 - 42+/p-tau–or Aβ1 - 42–/p-tau+). All of them, underwent an amyloid-PET with 18F-Florbetaben. An extensive neuropsychological testing as part of their diagnostic process (MMSE and TMA-93), was performed, and it was also obtained the Global Deterioration Scale. Results: Comparing the discordant CSF results of each patient with the cerebral amyloid-PET results, we found that in the group with Aβ1 - 42+ and p-tau–CSF values, the amyloid-PET was positive in 51.2% and negative in 48.8% of patients, while in the group with Aβ1 - 42–and p-Tau+ CSF values, the amyloid-PET was positive in 52.6% of patients and negative in 47.4% of them. No significant association was found (p = 0.951) between the results of amyloid-PET and the two divergent groups in CSF. Conclusions: No significant relationship was observed between the results of discordant AD biomarkers in CSF and the result of amyloid-PET. No trend in amyloid-PET results was observed in relation to CSF biomarker values.
Herpes Simplex Virus 1 Infection Does Not Increase Amyloid-β Pathology in APP/PS1 Mice
Authors: Lapeyre Lina , Piret Jocelyne , Rhéaume Chantal , Pons Vincent , Uyar Olus , Préfontaine Paul , Rivest Serge , Boivin Guy
Published: December 2023

Using APP/PS1 mice that overproduce amyloid-β (Aβ) peptides, we investigated whether intranasal infection with a neurovirulent clinical strain of herpes simplex virus 1 (HSV-1) before Aβ deposition could accelerate or increase Alzheimer’s disease-like pathology. After HSV-1 infection, APP/PS1 mice presented a similar disease as wild type animals based on body weight changes, clinical symptoms, and survival rates. The number and volume of Aβ plaques, the number of microglia, and the percentages of circulating monocyte subsets were similar in APP/PS1 mice infected or not with HSV-1. Thus, intranasal infection with HSV-1 does not alter Aβ pathology in this mouse model.
Aberrant Cortical Activity in 5xFAD Mice in Response to Social and Non-Social Olfactory Stimuli
Authors: Kosel Filip , Hartley Mackenzie Rae , Franklin Tamara Brook
Published: December 2023

Background: Neuroimaging studies investigating the behavioral and psychological symptoms of dementia (BPSD)— such as apathy, anxiety, and depression— have linked some of these symptoms with altered neural activity. However, inconsistencies in operational definitions and rating scales, limited scope of assessments, and poor temporal resolution of imaging techniques have hampered human studies. Many transgenic (Tg) mouse models of Alzheimer’s disease (AD) exhibit BPSD-like behaviors concomitant with AD-related neuropathology, allowing examination of how neural activity may relate to BPSD-like behaviors with high temporal and spatial resolution. Objective: To examine task-dependent neural activity in the medial prefrontal cortex (mPFC) of AD-model mice in response to social and non-social olfactory stimuli. Methods: We previously demonstrated age-related decreases in social investigation in Tg 5xFAD females, and this reduced social investigation is evident in Tg 5xFAD females and males by 6 months of age. In the present study, we examine local field potential (LFP) in the mPFC of awake, behaving 5xFAD females and males at 6 months of age during exposure to social and non-social odor stimuli in a novel olfactometer. Results: Our results indicate that Tg 5xFAD mice exhibit aberrant baseline and task-dependent LFP activity in the mPFC— including higher relative delta (1–4 Hz) band power and lower relative power in higher bands, and overall stronger phase-amplitude coupling— compared to wild-type controls. Conclusions: These results are consistent with previous human and animal studies examining emotional processing, anxiety, fear behaviors, and stress responses, and suggest that Tg 5xFAD mice may exhibit altered arousal or anxiety.
Diagnostic Accuracy of the Swedish Version of the Multicultural Cognitive Examination for Cognitive Assessment in Swedish Memory Clinics
Authors: Torkpoor Rozita , Frolich Kristin , Londos Elisabet , Nielsen T. Rune
Published: December 2023

Background: Cognitive assessment for foreign-born individuals is suboptimal. The Multicultural Cognitive Examination (MCE) was developed for use in culturally, linguistically and educationally diverse populations. The MCE includes the Rowland Universal Dementia Assessment Scale (RUDAS) and performs assessment of memory, verbal fluency, and visuospatial function. Objective: To compare the psychometric properties of the Swedish version of the Multicultural Cognitive Examination (MCE-S) with the Swedish versions of the RUDAS (RUDAS-S), the Mini-Mental State Examination (MMSE-SR), and the Clock Drawing Test (CDT), and to explore the ability of the MCE-S test to differentiate patients with and without dementia in a multicultural population. Methods: 117 outpatients at four memory clinics were tested using the MCE-S to complement the routine cognitive assessment. Results: Significant differences between patients with and without dementia were observed for all MCE-S components. There were significant differences between foreign-born and Swedish-born patients in the MMSE-SR, but not in the MCE-S or the RUDAS-S. The MCE-S, had good diagnostic performance for detecting dementia (AUC, 0.82), and was at least as good as the RUDAS-S alone (AUC, 0.79). The MCE-S also distinguished Alzheimer’s disease (AD) from non-AD dementia. Contrary to expectations, the MCE-S was also at least as good as the MMSE-SR among the Swedish-born patients. Conclusions: The MCE-S is adequate for detecting dementia in both foreign-born and Swedish-born populations. Based on the cultural diversity of general society, adapted cognitive tests that can be used for everyone are practical and beneficial for both patients and health-care professionals. Further studies are needed within primary care.
Sex-Specific Early Retinal Dysfunction in Mutant TDP-43 Transgenic Mice
Authors: Gao Ju , Leinonen Henri , Wang Evan J. , Ding Mao , Perry George , Palczewski Krzysztof , Wang Xinglong
Published: December 2023

Background: Increasing evidence has highlighted retinal impairments in neurodegenerative diseases. Dominant mutations in TAR DNA-binding protein 43 (TDP-43) cause amyotrophic lateral sclerosis (ALS), and the accumulation of TDP-43 in the cytoplasm is a pathological hallmark of ALS, frontotemporal dementia (FTD), and many other neurodegenerative diseases. Objective: While homozygous transgenic mice expressing the disease-causing human TDP-43 M337V mutant (TDP-43M337V mice) experience premature death, hemizygous TDP-43M337V mice do not suffer sudden death, but they exhibit age-dependent motor-coordinative and cognitive deficits. This study aims to leverage the hemizygous TDP-43M337V mice as a valuable ALS/FTD disease model for the assessment also of retinal changes during the disease progression. Methods: We evaluated the retinal function of young TDP-43M337V mice by full field electroretinogram (ERG) recordings. Results: At 3–4 months of age, well before the onset of brain dysfunction at 8 months, the ERG responses were notably impaired in the retinas of young female TDP-43M337V mice in contrast to their male counterparts and age-matched non-transgenic mice. Mitochondria have been implicated as critical targets of TDP-43. Further investigation revealed that significant changes in the key regulators of mitochondrial dynamics and bioenergetics were only observed in the retinas of young female TDP-43M337V mice, while these alterations were not present in the brains of either gender. Conclusions: Together our findings suggest a sex-specific vulnerability within the retina in the early disease stage, and highlight the importance of retinal changes and mitochondrial markers as potential early diagnostic indicators for ALS, FTD, and other TDP-43 related neurodegenerative conditions.
Teaching quality evaluation of college civic and political science courses based on BP neural algorithm
Authors: Wang Chen
Published: December 2023

Constructing the evaluation system of ideological and political education of new media in colleges is both beneficial to evaluate the established ideological and political education work and an important guide to improve the corresponding work. At present, promoting ideological and political education work with high integration of information technology has become an important way of ideological and political education work in colleges. However, the theoretical circles are still not focused enough on how to evaluate the ideological and political education work in colleges. Based on the characteristics of the information age, this paper establishes the teaching quality evaluation system of ideological and political education courses in colleges, introduces BP neural network evaluation method, and obtains strong empirical support through simulation experiments, so as to build a feasible teaching quality evaluation model of ideological and political courses in colleges. At the same time, the corresponding optimization suggestions are put forward, including improving the relevance of ideological and political education work, dynamically grasping students’ ideological and political information and doing a good job of data processing, and improving the professional information literacy of the ideological and political work team, in order to provide some reference for the efficient development of ideological and political education work in colleges.
External communication of Chinese traditional culture under the background of big data
Authors: Li Xiaohan , Chai Wang
Published: December 2023

Traditional culture is a symbol of a country’s existence and history. The external dissemination of traditional culture is the key to expanding the country’s influence and enhancing the country’s international image. The external dissemination of culture also poses a potential impact on the country’s economy and development. In the context of the information age, the dissemination of Chinese traditional culture is attached great importance. The culture of the Forbidden City, from self-construction to borrowing, from online to offline all-media communication channels, unique and novel cultural and creative products and a young brand image provide it with a unique means of communication. The dissemination of the Forbidden City culture is of positive significance to the demonstration of cultural confidence and the innovation and development of culture, and it can be used as a typical case of the dissemination of Chinese traditional culture. Big data technology analyzes the research object through the process of data collection, data screening and data processing, combined with various data analysis tools, and the ultimate goal is to obtain favorable results for the analyst based on the analysis. The use of big data technology in cultural communication research has gradually become the focus of current scholars. This paper takes the Forbidden City culture as the research object, analyzes the current situation of the foreign communication of the traditional culture of the Forbidden City, puts forward the dilemma of the current external communication of Chinese traditional culture based on the current situation, summarizes the problems and reasons of traditional cultural communication, and designs corresponding solutions combined with big data technology. Through the data simulation of Chinese traditional cultural communication using big data solutions, it is found that the demand satisfaction, cultural benefits after cultural communication, and the direction of cultural influence have all improved after analyzing the user’s individual needs combined with big data technology.
Multi-scale flexibility assessment of electrical, thermal and gas multi-energy systems based on morphological decomposition
Authors: Jia Xiaoqiang , Wang Zhiwei , Wang Songcen , Liu Kaicheng , Zhang Xinhe , Zhang Jiajun
Published: December 2023

The rapid development of renewable energy has also had an impact on the flexibility of multi energy systems such as electricity, heat, and gas. To analyze the flexible characteristics of multi energy systems at multiple time scales, a multi-scale flexibility evaluation method based on morphological decomposition is proposed. The net load curve is decomposed using mathematical morphology methods, and a multi-scale energy storage configuration method based on the flexibility of electric heating systems is proposed. The analysis data shows that the probability of insufficient upward flexibility, margin expectation, and insufficient expectation of the scale weighted flexibility index are 1.12%, 3.98%, and 1.16%, respectively, while the probability of insufficient downward flexibility, margin expectation, and insufficient expectation are 0.73%, 4.54%, and 0.56%, respectively. The introduction of energy storage and controllable load simultaneously results in an overall downward flexibility index of 0.92% for the system. The results indicate that controllable load can improve the economy of system peak shaving, providing more options for energy storage and configuration in multi energy systems.
Research on fracture mechanism and mechanical properties of polycrystalline graphene by nanoindentation: A molecular dynamics study
Authors: Wang Yingsheng , Liu Yongkun , Ding Sha
Published: December 2023

Randomness of grain boundaries makes it difficult to reach a broad consensus about mechanical properties of polycrystalline graphene (PG). In the present paper, based on principle of Voronoi diagram, the models of PG with different grain sizes were established, and the fracture mechanism and mechanical properties were investigated by molecular dynamics (MD). The results showed that the crack initiation point of PG always located at the multiple junction of grain boundaries, and the crack propagation and fracture mode of PG was mainly dependent on not only the relative size but also the relative location of the indenter and grain boundaries. Additionally, the effects of grain size, indentation speed, temperature and indenter diameter on the mechanical properties were studied, which showed some interesting and different phenomena from the tensile case, e.g., the grain size seems no regular effect on mechanical properties. Furthermore, the ultimate indentation force, indentation depth and fracture showed an increase trend with the increase of indenter diameter and indentation speed, while they decreased with the increase of temperature. But when it came to the elastic modulus, it showed a decreasing trend with the increase of indenter diameter and indentation speed, while it first increased and then decreased with the increase of temperature.
Evaluation of county-level integrated health organizations: Combination of the weighting-grey synthetic evaluation method
Authors: Wu Qianqian , Chen Kejia
Published: December 2023

This paper aims to improve the efficacy assessment of County-level Integrated Health Organizations (CIHOs) in China. By analyzing CIHOs in Fujian Province, an empirical study was done to confirm the efficacy of the combined weighted-grey synthetic evaluation approach. The combined weights of evaluation indicators are calculated using the suggested method, which combines the analytical network process method and the coefficient of variation method. The grey center points of the CIHOs to be evaluated are determined, the whitenization weight functions is constructed, a comprehensive evaluation matrix is established, and then the composite score values are calculated and ranked. A more thorough evaluation of CIHOs can be accomplished scientifically using this comprehensive approach.
Identification and modelling of parameters for the information-physical-social convergence characteristics of user-side flexible resources
Authors: Dou Zhenlan , Zhang Chunyan , Wu Juntao , Wen Xuan
Published: December 2023

The use of flexible resource information on the user side helps to increase system efficiency. Power system power variation becomes more pronounced with the access to renewable resources. Therefore, the study proposes a parameter identification and modeling method for the physical and social integration characteristics of flexible resource information on the user side. Taking the user’s air conditioning load as the object, the thermal dynamic model of the air conditioning building is constructed using equivalent thermal parameters, and the variable frequency air conditioning load is embedded in the battery model. The model parameter identification is carried out using high-dimensional model expression technology. According to the experimental data, in options 2 and 3, the system operator makes power purchases based on the storage status of the lithium battery or virtual battery, increasing the number of power purchases when the price of electricity is low and decreasing the number of power purchases when the price of electricity is high. This effectively reduces the system operator’s electricity costs. The error of multiple linear regression modelling varies widely, with relative errors up to 0.75 and an average relative error of 15.1%. The relative error of modelling based on the high-dimensional model expression technique is in the range of 0 to 0.2, with an average relative error of 5.5%. The results show that compared with multiple linear regression models, high-dimensional model representation technology has higher modeling accuracy and can accurately identify the parameters of the air conditioning load aggregation model, solving the problem of difficult parameter calculation in the practical application of the air conditioning load aggregation model, and providing technical support for power system regulation.
High performance low power CMOS temperature sensor
Authors: Peng Hua
Published: December 2023

A temperature sensor based on the combination of a temperature variable oscillator and a linear controlled oscillator is proposed, which can realize temperature detection through the characteristic of frequency changing with temperature. The changing frequency is generated by the two oscillators, and by adjusting the frequency linear change, the linearity of the sensor is also increased. Through the frequency digitizer, the digital signal can be output. Compensation through a process compensator improves the accuracy of the sensor after a single point correction. After conducting tests on 15 experimental samples, the accuracy was achieved within ± 1.2∘C across the temperature range of 0 to 125∘C, demonstrating a highly favorable level of precision.
A novel object recognition method for photovoltaic (PV) panel occlusion based on deep learning
Authors: Yu Jing , Guan Rongqiang , Zhang Cungui , Shao Fang
Published: December 2023

During the long-term operation of the photovoltaic (PV) system, occlusion will reduce the solar radiation energy received by the PV module, as well as the photoelectric conversion efficiency and economy. However, the occlusion detection of the PV power station has the defects of low efficiency, poor accuracy, and untimely detection, which will cause unknown system losses. Based on the deep learning algorithm, this paper conducts research on PV module occlusion detection. In order to accurately obtain the occlusion area and position information of the PV panel, a PV module occlusion detection model based on the Segment-You Only Look Once (Seg-YOLO) algorithm is established. Based on the YOLOv5 algorithm, the loss function is modified, the Segment Head detection module is introduced, and the convolutional block attention module (CBAM) attention mechanism is added to achieve the accurate detection of small targets by the algorithm model and the fast detection of the PV module occlusion area identify. The model performance research is carried out on three types of occlusion datasets: leaf, bird dropping, and shadow. According to the experimental results, the proposed model has better recognition accuracy and speed than SSD, Faster-Rcnn, YOLOv4, and U-Net. The precision rate, recall rate, and recognition speed can reach 90.52%, 92.41%, and 92.3 FPS, respectively. This model can lay a theoretical foundation for the intelligent operation and maintenance of PV systems.
Microcosmic characteristics of particulate matter emitted by GDI gasoline engine in plateau environment
Authors: Zhang Jian , Zhou Hao , Liu Xiaoying , He Chao
Published: December 2023

The particulate matter samples of gasoline direction injection (GDI) gasoline engine obtained from road experiments are photographed to obtain the emission particulate matter images based on the transmission electron microscope under high altitude environment. The results show that the micro-morphology characteristics of the particulate matter emitted by GDI gasoline engine in plateau area are similar to those in low altitude area, and the main morphology is cloud-like, filamentous, flocculent, chain-like, cluster-like, like altitude contour line, etc. The images are processed by MATLAB and Python software, and the fractal dimension, average gray value and gray histogram are obtained. The fractal dimensions of the emission particulate data obtained are between 1.81 and 1.89, which has some deviation compared with the fractal dimension of the emission particulate data at low altitude of 1.58 and 1.80. With the increase of altitude, its fractal dimension increases more obviously. It can be seem from the characteristics of gray value and gray histogram of particle images that the average gray value of GDI gasoline engine particles is higher. The gray histogram distribution of 5–50 nm images is uniform, and the individual particles in the images are clear. The gray histogram of 100–500 nm images is scattered, so it is easy to extract and separate the image edge contour. 5–50 nm images are used to study the details and characteristics of individual particles, and 100–500 nm transmission electron microscope images are used to study the overall morphology of particles.
A study on human errors of air traffic controllers based on HFACS-AHP
Authors: Zhu Shouxi , Chen Jian
Published: December 2023

Safety is the lifeline of civil aviation. With the advancement of technology, human factors have become the primary factor affecting aviation safety. Among these, human errors in air traffic control (ATC) account for a significant proportion of aviation accidents. In order to investigate human errors in ATC, this paper introduces two common human factors conceptual models – the Reason model and the HFACS model, and analyzes the specific application of the HFACS model in aviation. It is found that the HFACS model can effectively establish a classification system for human errors in ATC. Moreover, this paper combines the HFACS model with AHP (Analytic Hierarchy Process) and uses the HFACS model to establish a first and second level indicator system for human errors in ATC. We calculated the weights of each specific factor using the Analytic Hierarchy Process. The results show that the most significant influencing factor in the first level indicators is organizational factors, while the most significant influencing factor in the second level indicators is Air Traffic Resource Management. Among the 13 second level indicators, the smallest weight is the controller’s violation. Based on the calculated weight results, in order to improve the safety level of ATC, the first step should be to improve the level of ATC organizational management. This is also of great significance for improving the safety level of the entire aviation system. The findings of this study suggest that the HFACS model, combined with AHP, can be an effective tool for identifying and analyzing human factors in ATC and ultimately improving the safety of the aviation industry.
Research on prediction model of scaling in ASP flooding based on data mining
Authors: Hu Yanan , Lv Mingyang
Published: December 2023

As a result of alkali ASP flooding in oil and gas fields, strata and pipelines become seriously scaled, which poses a threat to the normal operation of crude oil production. We propose an intelligent knowledge reasoning model for dynamic scaling prediction in order to address the problems of high directivity, poor generalization ability, and poor application effect of existing scaling prediction methods. The model framework includes the knowledge acquisition layer which mainly relates to the manual acquisition of scaling prediction knowledge and the intelligent training of the knowledge base, and it includes the knowledge modeling layer that provides a set of standard domain common ontology and knowledge organization system using the ontology modeling technology, it also includes the knowledge inference layer which is the application layer of the model. The three layers collaborate and finally complete the scaling prediction through inference and expression. A total of 238 wells were selected for experimentation in the northern development area of the Xingshugang Oilfield. Experimental results indicate that the model has the highest accuracy of 91.87%. Additionally, the time series prediction trend for the six ions matches the trend of change in ion concentration in the scaling state, verifying the accuracy of the model’s predictions.
RETRACTED: Automated modeling of nonlinear systems using fuzzy modular neural network
Authors: Zhang Zhao Zhao , Pan Hao Ran , Zhu Ying Qin
Published: December 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Enhancing efficiency in electrical distribution systems: A novel approach via modified genetic optimization algorithm for loss reduction in optimal network distribution
Authors: Rajalakshmi K. , Priyan S. Vishnu , Inbakumar J. Parivendhan , Kumar C.
Published: December 2023

The distribution system plays a pivotal role in connecting power generation sources to vital facilities like nuclear reactors. In this intricate network, losses occur while supplying electricity, demanding a reduction for enhanced performance. The quality of power reaching the nuclear plant is imperative due to the susceptibility of sensitive equipment to poor power conditions. This study presents a reconfiguration strategy to bolster dependability and curtail power losses in distribution networks. Leveraging the Modified Genetic Optimization Algorithm (MGOA), the reconfiguration conundrum is tactfully addressed to determine optimal switch operation schemes. The MGOA-based reconfiguration not only minimizes energy wastage but also refines voltage profiles, elevating operational efficiency. The effectiveness of this approach is substantiated through its successful application to radial distribution systems comprising 33, 69, and 136 buses. Embracing diverse scenarios encompassing normal and abnormal operating states, as well as varying loads, the method’s robustness is showcased. The validity of the proposed methodology is reinforced by comprehensive simulation results, underscoring its reliability and potential for real-world implementation.
RETRACTED: Breathing site classification via joint mel frequency cepstral coefficients and gammatone frequency cepstral coefficients approach
Authors: Zhang Jiarui , Ling Bingo Wing-Kuen
Published: December 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Analysis of factors influencing Chinese vocabulary learning level based on big data technology
Authors: Li Yajie , Cai Xirui
Published: December 2023

In recent years, significant progress has been made in the study of Chinese vocabulary acquisition, and the research content and scope have gradually expanded. Chinese vocabulary is the foundation for understanding and using language, and any language has developed on the basis of Chinese vocabulary. Many studies have shown that there are many factors that affect the acquisition of Chinese vocabulary, and the impact on Chinese vocabulary acquisition is also different. Among them, the influencing factors of Chinese vocabulary acquisition have gradually become a research hotspot, and a large number of related empirical studies have emerged. Based on the big data technology and the random effect model, this paper comprehensively analyzes whether the influencing factors of Chinese vocabulary acquisition as a second language are significant and investigates the effects of internal and external influencing factors, delayed post-test, specific factors and experimental interval time on the learning effect. External factors significantly impact Chinese vocabulary acquisition, including learning style, input factors and input methods. Through the subgroup analysis of the experimental interval, we find that the effect of Chinese vocabulary acquisition decreases with the extension of the experimental interval. Therefore, this paper holds an inverse relationship between the experimental interval and the development of Chinese vocabulary acquisition.
A comprehensive automatic labeling and repair strategy for cracks and peeling conditions of literary murals in ancient buildings
Authors: Du Pei
Published: December 2023

To protect the historical and cultural heritage, the application of self-organizing mapping networks and genetic algorithms in the restoration of ancient architectural murals is studied. The results show that the average repair time for different types of mural paintings is less than 60 seconds, and the shortest repair time is only 17.81 seconds. The evaluation effect of the research model is good, and the comprehensive efficiency evaluation of the mural restoration work is improved by about 40.42%. The repair system has excellent performance, and the algorithm has high feasibility and effectiveness. The impact of restoring murals is substantial, and the extent of restoration is highly consequential for the restoration of ancient architectural murals.
RETRACTED: Research on load balance control of power systems based on distributed energy storage technology
Authors: Yin Xiang , Guan Li , Li Bing , Huang Qing , Lin Huijie
Published: December 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Model formulation on efficiency for median estimation under a fixed cost in survey sampling
Authors: Iseh Matthew Joshua
Published: December 2023

In survey sampling, it is observed that researchers and users of statistics sometimes do not take into consideration the tool that will be most appropriate for the measure of location. As a result, they often go for the mean or total, which has wider coverage in the finite population sampling literature, unlike the median, which is more complicated to deal with given that it has to do with ordered data. Keeping in mind the established facts from the literature on the usefulness of the median estimator in estimating economic indicators for high precision and efficiency, this study has made useful improvement in estimating the population median not only for gains in efficiency but also in achieving less biased estimates. The study suggests an estimator of population median in single and double sampling techniques. In addition, minimum mean square error has also been obtained for a given cost function under double sampling. Results obtained from both theoretical and empirical investigations reveal that the proposed estimators perform better when the considered variables are from a highly skewed distribution, such as income, expenditure, scores, etc. Moreso, it is observed that the proposed estimators compete favorably with less bias and outstanding gains in efficiency than the existing estimators of its class. In addition, this study avails us of an appropriate way of constructing the cost function for better evaluations compared to an existing estimator considered in this work.