bluuebunny/crossref_metadata_2025 huggingface dataset:
Abnormal blood supply to a normal lung: left circumflex artery branch supplying the right lung
Authors: Shrimanth Yamasandi Siddegowda , Sahitya Mandava Satya , Maralakunte Muniraju , Sihag Bhupendra Kumar
Published: March 2022

A middle-aged woman with hypertension presented with atypical chest pain of 1 month duration and had a positive exercise stress test. She underwent diagnostic coronary angiography which demonstrated an anomalous branch arising from the proximal part of the left circumflex artery supplying the right lung. She had atherosclerotic plaques in the right coronary artery and left anterior descending artery. Stress myocardial perfusion imaging did not reveal any inducible ischaemia in the left circumflex artery territory. She was started on medical therapy for coronary artery disease and is doing well on follow-up.
Effect of lactate administration on cerebral blood flow during hypoglycemia in people with type 1 diabetes
Authors: van Meijel Lian A , van Asten Jack J A , Grandjean Joanes , Heerschap Arend , Tack Cornelis J , van der Graaf Marinette , Wiegers Evita C , de Galan Bastiaan E
Published: March 2022

Introduction

Impaired awareness of hypoglycemia, clinically reflected by the inability to timely detect hypoglycemia, affects approximately 25% of the people with type 1 diabetes. Both altered brain lactate handling and increased cerebral blood flow (CBF) during hypoglycemia appear to be involved in the pathogenesis of impaired awareness of hypoglycemia. Here we examine the effect of lactate on CBF during hypoglycemia.

Research design and methods

Nine people with type 1 diabetes and normal awareness of hypoglycemia underwent two hyperinsulinemic euglycemic-hypoglycemic (3.0 mmol/L) glucose clamps in a 3T MR system, once with sodium lactate infusion and once with sodium chloride infusion. Global and regional changes in CBF were determined using pseudocontinuous arterial spin labeling.

Results

Lactate (3.3±0.6 vs 0.9±0.2 mmol/L during lactate infusion vs placebo infusion, respectively) suppressed the counter-regulatory hormone responses to hypoglycemia. Global CBF increased considerably in response to intravenous lactate infusion but did not further increase during hypoglycemia. Lactate also blunted the hypoglycemia-induced regional redistribution of CBF towards the thalamus.

Conclusions

Elevated lactate levels enhance global CBF and blunt the thalamic CBF response during hypoglycemia in patients with type 1 diabetes, mimicking observations of impaired awareness of hypoglycemia. These findings suggest that alteration of CBF associated with lactate may play a role in some aspects of the development of impaired awareness of hypoglycemia.

Trial registration number

NCT03730909.
Using human factors and ergonomics principles to prevent inpatient falls
Authors: Kwok Yick-ting , Lam Ming-sang
Published: March 2022

Inpatient falls are frequently reported incidents in hospitals around the world. The recent COVID-19 pandemic has further exacerbated the risk. With the rising importance of human factors and ergonomics (HF&E), a fall prevention programme was introduced by applying HF&E principles to reduce inpatient falls from a systems engineering perspective. The programme was conducted in an acute public hospital with around 750 inpatient beds in Hong Kong. A hospital falls review team (the team) was formed in June 2020 to plan and implement the programme. The ‘Define, Measure, Analyse, Improve and Control’ (DMAIC) method was adopted. Improvement actions following each fall review were implemented. Fall rates in the ‘pre-COVID-19’ period (January–December 2019), ‘COVID-19’ period (January–June 2020) and ‘programme’ period (July 2020–August 2021) were used for evaluation of the programme effectiveness. A total of 120, 85 and 142 inpatient falls in the ‘pre-COVID-19’, ‘COVID-19’ and ‘programme’ periods were reviewed, respectively. Thirteen areas with fall risks were identified by the team where improvement actions applying HF&E principles were implemented accordingly. The average fall rates were 0.476, 0.773 and 0.547 per 1000 patient bed days in these periods, respectively. The average fall rates were found to be significantly increased from the pre-COVID-19 to COVID-19 periods (mean difference=0.297 (95% CI 0.068 to 0.526), p=0.009), which demonstrated that the COVID-19 pandemic might have affected the hospitals fall rates, while a significant decrease was noted between the COVID-19 and programme periods (mean difference=−0.226 (95% CI −0.449 to –0.003), p=0.047), which proved that the programme in apply HF&E principles to prevent falls was effective. Since HF&E principles are universal, the programme can be generalised to other healthcare institutes, which the participation of staff trained in HF&E in the quality improvement team is vital to its success.
High level of lactate dehydrogenase and ischaemia–reperfusion injury regulate the multiple organ dysfunction in patients with COVID-19
Authors: Ashraf Aleena , Liaquat Afrose , Shabbir Sana , Bokhari Saleem Ahmed , Tariq Zainab , Furrukh Zainab , Raja Afraz Ahmad , Khan Muhammad Jawad
Published: March 2022

Background

Multiple organ damage has been observed in patients with COVID-19, but the exact pathway is not known. Vital organs of the human body may get affected after replication of SARS-CoV-2, including the lungs, heart, kidneys, liver and brain. It triggers severe inflammation and impairs the function of two or more organ systems. Ischaemia–reperfusion (IR) injury is a phenomenon that can have disastrous effects on the human body.

Methods

In this study, we analysed the laboratory data of 7052 hospitalised patients with COVID-19 including lactate dehydrogenase (LDH). A total of 66.4% patients were men and 33.6% were women, which indicated gender difference as a prominent factor to be considered.

Results

Our data showed high levels of inflammation and elevated markers of tissue injury from multiple organs C reactive protein, white blood cell count, alanine transaminase, aspartate aminotransferase and LDH. The number of red blood cells, haemoglobin concentration and haematocrit were lower than normal which indicated a reduction in oxygen supply and anaemia.

Conclusion

On the basis of these results, we proposed a model linking IR injury to multiple organ damage by SARS-CoV-2. COVID-19 may cause a reduction in oxygen towards an organ, which leads to IR injury.
Daily and fasting variation in blood parameters and HL ratio in House Sparrow (Passer domesticus)
Authors: Chediack Juan Gabriel , Padrones Marcelo Nicolás , Ronchi Germán , Arias Rodolfo J. , Cid Fabricio Damián
Published: March 2022

Fluctuations in food supply are frequent in nature during seasons, in different stages of annual cycle of animals, and lately, climate change has become a strong driving force that could affect food supply. An animal's capacity to resist fasting is, therefore, determined by its ability to store energy and control its allocation during periods of food restriction. Daily variations of metabolic substrates and their fluctuations during fasting are relevant to understand the acclimation to fasting. Since fasting is an ecological stressor, we investigated the daily variation of corticosterone levels in feeding and fasting in House Sparrows ( Passer domesticus (Linnaeus, 1758)), and its short-term effect on some biochemical parameters. We found daily variations in body mass, glucose, triglycerides, plasma total protein, uric acid, and corticosterone. However, we did not find diurnal variations of hematocrit and the heterophil:lymphocyte ratio (HL ratio). Moreover, we did not find sex-related differences in any parameter. Throughout fasting, we found variations of glucose, triglycerides, total protein, uric acid, HL ratio, and corticosterone. During the photophase, biochemical and physiological responses to food deprivation contributed to the efficient use of resources in this small bird. In the course of fasting period, corticosterone could be responsible for alterations of some blood parameters such as glucose.
Petrographic and diagenetic investigation of the distal Triassic ‘Budleighensis’ fluvial system in the Solway and Carlisle Basins for potential CO
2
storage
Authors: Marsh J. R. , Jones S. J. , Meadows N. S. , Gluyas J. G.
Published: March 2022

Failure to find hydrocarbon prospects in the Solway Basin region has resulted in a lack of research into the local Sherwood Sandstone Group petrography, reservoir quality and depositional history compared to the analogous southern reservoirs in the EISB which will be utilized for carbon storage. A detailed petrographic study is presented which aims to understand if the Solway Firth could have similar utility. The Permo–Triassic Sherwood Sandstone Group is believed to be deposited in depocentres connected during the Early Triassic by the extensive ‘Budleighensis’ fluvial system. Here, the Solway and Carlisle basins are proposed as terminal sites for this endorheic system, with the Lower Triassic Annan Sandstone Formation ascribed to the distal region of a fluvial distributary zone and the overlying Kirklinton Sandstone Formation thought to mark a transition to a basinal zone, depositing aeolian sandstones and locally associated playa lake facies. Fluid inclusion, stable isotope burial history modelling and field observations have been used to assess the relative timing and importance of different diagenetic cements. Early diagenetic cements include grain-rimming haematite and patchy calcite cement, especially in the Annan Sandstone Formation. Later burial diagenesis sees further calcite cement, quartz overgrowths and, restricted to the Kirklinton Sandstone Formation, ferroan dolomite. Porosity and permeability show significant differences between fluvial Annan and aeolian Kirklinton facies associations. Despite the finer grain size, a reservoir with excellent porosity and permeability as well as no hydrocarbon charging or legacy hydrocarbon extraction is persevered, suggesting the Solway Basin could be a secure CO
2
storage site.

This article is part of the Energy Geoscience Series available at
https://www.lyellcollection.org/cc/energy-geoscience-series

Supplementary material:
An overview of the primary and secondary data collected and utilised in this study, as well as raw data values are available at
https://doi.org/10.6084/m9.figshare.c.5906677
Efficient Light Field Image Compression with Enhanced Random Access
Authors: Amirpour Hadi , Pinheiro Antonio , Pereira Manuela , Lopes Fernando J. P. , Ghanbari Mohammad
Published: March 2022

In light field image compression, facilitating random access to individual views plays a significant role in decoding views quickly, reducing memory footprint, and decreasing the bandwidth requirement for transmission. Highly efficient light field image compression methods mainly use inter view prediction. Therefore, they typically do not provide random access to individual views. On the other hand, methods that provide full random access usually reduce compression efficiency. To address this trade-off, a light field image encoding method that favors random access is proposed in this paper. Light field image views are grouped into independent (3× 3) views, which are called
Macro View Images (MVIs)
. To encode MVIs, the central view is used as a reference to compress its adjacent neighboring views using a hierarchical reference structure. To encode the central view of each MVI, the most central view along with the center of a maximum of three MVIs, are used as reference images for the disparity estimation. In addition, the proposed method allows the use of parallel processing to reduce the maximum encoding/decoding time-complexity in multi-core processors. Tile partitioning can also be used to randomly access different regions of the light field images. The simulation results show that the proposed method outperforms other state-of-the-art methods in terms of compression efficiency while providing random access to both views and regions of interest.
Photo Realistic Generation from Arabic Text Description Based on Generative Adversarial Networks
Authors: Mathematics Sara Maher , Loey Mohamed
Published: March 2022

Generating accurate high-resolution images from text representations is a difficult problem in computer vision that has a wide range of functional applications. Text-to-image conversion is not dissimilar to the difficulties inherent in language processing. For example, each text meaning can be encoded in two distinct human languages, while photographs and text are two distinct encoding languages for similar data. However, these are two distinct issues, since text-to-image or image-to-text conversions are extremely multimodal in nature. The proposed model for creating 256 × 256 realistic images from Arabic text descriptions is discussed in this article. The relationship between an Arabic word in a sentence and its component in a picture as introduced in this paper using the DAMSM model. This model teaches two neural networks how to map the Arabic picture and word sub-regions of a full sentence to a shared semantic model. It performs well as an Arabic-text encoder and a picture encoder. We start with the Modified-Arabic dataset and train the model from scratch. The proposed model establishes a new standard for the conversion of Arabic text to realistic pictures. A mutation happens when Arabic is used as the primary language for converting Arabic texts to real images. The inception score of the newly introduced model reported by 3.42 ± .05 on the CUB database.
Transparency’s Influence on Human-collective Interactions
Authors: Roundtree Karina A. , Cody Jason R. , Leaf Jennifer , Demirel H. Onan , Adams Julie A.
Published: March 2022

Collective robotic systems are biologically inspired and advantageous due to their apparent global intelligence and emergent behaviors. Many applications can benefit from the incorporation of collectives, including environmental monitoring, disaster response missions, and infrastructure support. Transparency research has primarily focused on how the design of the models, visualizations, and control mechanisms influence human-collective interactions. Traditionally most transparency research has evaluated one system design element. This article analyzed two models and visualizations to understand how the system design elements impacted human-collective interactions, to quantify which model and visualization combination provided the best transparency, and provide design guidance, based on remote supervision of collectives. The consensus decision-making and baseline models, as well as an individual collective entity and abstract visualizations, were analyzed for sequential best-of-
n
decision-making tasks involving four collectives, composed of 200 entities each. Both models and visualizations provided transparency and influenced human-collective interactions differently. No single combination provided the best transparency.
A Survey on Active Deep Learning: From Model Driven to Data Driven
Authors: Liu Peng , Wang Lizhe , Ranjan Rajiv , He Guojin , Zhao Lei
Published: March 2022

Which samples should be labelled in a large dataset is one of the most important problems for the training of deep learning. So far, a variety of active sample selection strategies related to deep learning have been proposed in the literature. We defined them as Active Deep Learning (ADL) only if their predictor or selector is a deep model, where the basic learner is called the predictor and the labeling schemes are called the selector. In this survey, we categorize ADL into model-driven ADL and data-driven ADL by whether its selector is model driven or data driven. We also introduce the different characteristics of the two major types of ADL, respectively. We summarized three fundamental factors in the designation of a selector. We pointed out that, with the development of deep learning, the selector in ADL also is experiencing the stage from model driven to data driven. The advantages and disadvantages between data-driven ADL and model-driven ADL are thoroughly analyzed. Furthermore, different sub-classes of data-drive or model-driven ADL are also summarized and discussed emphatically. Finally, we survey the trend of ADL from model driven to data driven.
Optimizing Hyperparameters and Performance Analysis of LSTM Model in Detecting Fake News on Social media
Authors: Rajalaxmi R.R. , Narasimha Prasad L.V. , Janakiramaiah B. , Pavankumar C.S. , Neelima N. , Sathishkumar V.E.
Published: March 2022

Fake news detection recently received a lot of attention from the scientific community and demands an optimal solution with high efficiency. Several studies were conducted using unsupervised and supervised learning techniques to address the fake news identification problem. These studies, on the other hand, have some limitations like inefficient model design, improper pre-processing, and poor accuracy. Some factors contributing to poor accuracy include irrelevant features, improper model parameters, imbalanced datasets, and so on. This work proposes an optimized deep learning model for detecting fake news. The developed model uses Long Short-Term Memory (LSTM) to classify fake and real news and utilizes hyperparameter tuning methods such as grid search and random search to customize the hyperparameters of the model. The experimental results indicate that the optimized LSTM model yields 99.65% accuracy using the ISOT dataset and 45.23% accuracy using the LIAR dataset.
Measuring 9 Emotions of News Posts from 8 News Organizations across 4 Social Media Platforms for 8 Months
Authors: Aldous Kholoud Khalil , An Jisun , Jansen Bernard J.
Published: March 2022

Using Plutchik’s wheel of emotions framework, we identify the emotional content of 133,487 social media posts and the audience’s emotional engagement expressed in 2,824,162 comments on those posts. We measure nine emotions (anger, anticipation, anxiety, disgust, joy, fear, sadness, surprise, trust) and two sentiments (positive and negative) using two extraction resources (EmoLex, LIWC) for eight major news outlets across four social media platforms (Facebook, Instagram, Twitter, and YouTube) during eight months. We then apply two approaches (Logistic Regression, Long Short-Term Memory) to predict emotional audience reactions before and after publishing the posts. Findings show significant differences for positive emotions but not for negative in the comments among the platforms. F1-scores for predicting emotional audience engagement are more than 70% for some emotions for some news outlets. Implications are that news outlets have leverage in steering emotional engagement for posts on social media platforms. The findings have theoretical and practical implications for understanding the complex emotional and informational interplay among social media content, platforms, and audiences.
Membership Inference Attacks on Machine Learning: A Survey
Authors: Hu Hongsheng , Salcic Zoran , Sun Lichao , Dobbie Gillian , Yu Philip S. , Zhang Xuyun
Published: March 2022

Machine learning (ML) models have been widely applied to various applications, including image classification, text generation, audio recognition, and graph data analysis. However, recent studies have shown that ML models are vulnerable to membership inference attacks (MIAs), which aim to infer whether a data record was used to train a target model or not. MIAs on ML models can directly lead to a privacy breach. For example, via identifying the fact that a clinical record that has been used to train a model associated with a certain disease, an attacker can infer that the owner of the clinical record has the disease with a high chance. In recent years, MIAs have been shown to be effective on various ML models, e.g., classification models and generative models. Meanwhile, many defense methods have been proposed to mitigate MIAs. Although MIAs on ML models form a newly emerging and rapidly growing research area, there has been no systematic survey on this topic yet. In this article, we conduct the first comprehensive survey on membership inference attacks and defenses. We provide the taxonomies for both attacks and defenses, based on their characterizations, and discuss their pros and cons. Based on the limitations and gaps identified in this survey, we point out several promising future research directions to inspire the researchers who wish to follow this area. This survey not only serves as a reference for the research community but also provides a clear description for researchers outside this research domain. To further help the researchers, we have created an online resource repository, which we will keep updated with future relevant work. Interested readers can find the repository at https://github.com/HongshengHu/membership-inference-machine-learning-literature.
The Planning and Care of Data
Authors: Neville-Neil George V.
Published: March 2022

Questions such as, "How do we secure this data?" work only if you ask them at the start, and not when some lawyers or government officials are sitting in a conference room, rooting through your data and logs, and making threatening noises under their breath. All the things we care about with our data require forethought, but it seems in our rush to create "stakeholder value" we are willing to sacrifice these important attributes and just act like data gourmands, until, like Mr. Creosote in Monty Python's The Meaning of Life, we explode, scattering half-digested data all over the dining room.
A Federated Deep Learning Empowered Resource Management Method to Optimize 5G and 6G Quality of Services (QoS)
Authors: Alsulami Hemaid , Serbaya Suhail H. , Abualsauod Emad H. , Othman Asem Majed , Rizwan Ali , Jalali Asadullah
Published: March 2022

The quality of service (QoS) in 5G/6G communication enormously depends upon the mobility and agility of the network architecture. An increase in the possible uses of 5G vehicular network simultaneously expands the scope of the network’s quality of service (QoS). To this end, a safety-critical real-time system has become one of the most demanding criteria for the vehicular network. Although different mathematical and computation methods have traditionally been used to optimize the allocation of resources, but the nonconvexity of optimization issues creates unique type of challenges. In recent years, machine learning (ML) has emerged as a valuable tool for dealing with computational complexity that involves large amounts of data in heterogeneous vehicular networks. By using optimization and cutting-edge machine learning techniques, this article gives readers an insight about how 5G vehicular network resources can be allocated to reinforce network communication. Furthermore, a new federated deep reinforcement learning- (FDRL-) based vehicle communication method is presented as a new insight. Finally, a UAV-aided vehicular communication system based on FDRL-based UAVs is proposed as a novel resource management technique to optimize 5G and 6G quality of services.
Investigation of the Flow and Heat Transfer Characteristics and Erosion Law of Particulate in LBE on the Subchannel
Authors: Zhu Bingheng , Xu Qi , Li Pengxiang
Published: March 2022

A triangle subchannel model was established to study the flow and heat transfer characteristics of lead-bismuth eutectic (LBE) alloy and the erosion rate of the core channel by the particulate in LBE. Under different inlet velocities, particle types, particle diameters, and particle concentrations, the erosion law of the channel wall in LEB was investigated by using a discrete phase model (DPM). The results of this study showed that with the increase of inlet velocity, the outlet temperature of the LEB decreases and the heat transfer capacity was strengthened. The increase of inlet velocity will lead to the increase of erosion rate on the wall, and the change is exponential. The erosion rate of particulate in the low concentration is small but cannot be ignored; with increasing concentration of particulates, the erosion of the wall by particulates becomes serious. The effect of particulate density on the wall erosion rate can be ignored. The effect of changing the particle size on the erosion rate is more significant when the particle size is small, and at the same time, the erosion rate of the particles on the wall increases with the increase of the particle size.
Implementation of Discourse Network Analysis Related to News regarding PT Pertamina's Consumer Needs, Satisfaction, and Engagement
Authors: Fernandes Adji Achmad Rinaldo , Solimun Solimun , Muflikhah Lailil
Published: March 2022

The purpose of this study is to implement Discourse Network Analysis (DNA) and analyze the results in the formation of networks related to issues and actors in a news regarding consumer needs, satisfaction, and attachment to PT Pertamina. This study is the qualitative method that applies a qualitative Discourse Network Analysis (DNA) approach. Sources of DNA data come from various information in cyberspace (mass media, journals, articles, etc.) that are by the research context. Based on the search results in cyberspace, we obtained about 68 relevant news sources discussing consumer service on BBM products PT. Results of DNA taken from 68 news stories in cyberspace show that there are 45 actors from 14 different organizations who have opinions about PT Pertamina's consumers. Two actors only have a negative opinion, two actors have positive and negative opinions, and 41 actors have a positive opinion about the main issue of consumer needs. And we obtained 74 issues from the news obtained grouped into 3 main issues, namely, consumer needs, consumer satisfaction, and consumer engagement. And from 45 actors obtained from online news sources, they are grouped into 11 actor themes. Based on DNA results, it can be seen that there are several variables that have a possible influence on customer service. Variables that are likely to affect customer service include consumer needs, consumer satisfaction, and consumer engagement. The originality of this research lies in the application of DNA regarding consumer needs, satisfaction, and attachment to PT Pertamina.
Effect of Cerium Oxide on Kidney and Lung Tissue in Rats with Testicular Torsion/Detorsion
Authors: Ozdemirkan Aycan , Kurtipek Ali Can , Kucuk Aysegül , Ozdemir Cagri , Yesil Suleyman , Sezen Saban Cem , Kavutcu Mustafa , Arslan Mustafa
Published: March 2022

Introduction. Testicular torsion is a surgical emergency that results in testicular ischemia as a result of rotation of the spermatic cord around itself. Oxidative damage occurs in the testis and distant organs with the overproduction of free radicals and overexpression of proinflammatory cytokines by reperfusion after surgery. In this study, we aimed to investigate the effects of cerium oxide (CeO2), an antioxidant nanoparticle, on lung and kidney tissues in testicular torsion/detorsion (T/D) in rats. Materials and Methods. After ethics committee approval, 24 rats were equally (randomly) divided into 4 groups. Left inguinoscrotal incision was performed in the control (C) group. In group CeO2, 0.5 mg/kg CeO2 was given intraperitoneally 30 minutes before inguinoscrotal incision. In group T/D, unilateral testicular T/D was achieved by performing an inguinoscrotal incision and rotating the left testis 720° clockwise, remaining ischemic for 120 minutes, followed by 120 minutes of reperfusion. In group CeO2‐T/D, 0.5 mg/kg CeO2 was given intraperitoneally 30 minutes before testicular T/D. At the end of the experiment, lung and kidney tissues were removed for histopathological and biochemical examinations. Results. Glomerular vacuolization (GV), tubular dilatation (TD), tubular cell degeneration and necrosis (TCDN), leukocyte infiltration (LI), and tubular cell spillage (TCS) in renal tissue were significantly different between groups (p = 0.012, p = 0.049, p < 0.003, p = 0.046, and p = 0.049, respectively). GV and TCDN were significantly decreased in group CeO2‐T/D compared to group T/D (p = 0.042 and p = 0.029, respectively). Lung tissue neutrophil infiltration, alveolar thickening, and total lung injury score (TLIS) were significantly different between groups (p = 0.006, p = 0.001, and p = 0.002, respectively). Neutrophil infiltration and TLIS were significantly decreased in group CeO2‐T/D compared to group T/D (p = 0.013 and p = 0.033, respectively). Lung and kidney tissue oxidative stress parameters were significantly different between groups (p < 0.05). Renal tissue glutathione‐s‐transferase (GST), catalase (CAT), and paraoxonase (PON) activities were significantly higher, and malondialdehyde (MDA) levels were significantly lower in group CeO2‐T/D than in group T/D (p = 0.049, p = 0.012, p < 0.001, and p = 0.004, respectively). GST and PON activities were higher, and MDA levels were lower in group CeO2‐T/D than in group T/D in the lung tissue (p = 0.002, p < 0.001, and p = 0.008, respectively). Discussion. In our study, cerium oxide was shown to reduce histopathological and oxidative damage in the lung and kidney tissue in a rat testis torsion/detorsion model.
Regional Alteration within the Cerebellum and the Reorganization of the Cerebrocerebellar System following Poststroke Aphasia
Authors: Zhang Xiaotong , Chen Zhaocong , Li Na , Liang Jingfeng , Zou Yan , Wu Huixiang , Kang Zhuang , Dou Zulin , Qiu Weihong
Published: March 2022

Recently, an increasing number of studies have highlighted the role of the cerebellum in language processing. However, the role of neural reorganization within the cerebellum as well as within the cerebrocerebellar system caused by poststroke aphasia remains unknown. To solve this problem, in the present study, we investigated regional alterations of the cerebellum as well as the functional reorganization of the cerebrocerebellar circuit by combining structural and resting-state functional magnetic resonance imaging (fMRI) techniques. Twenty patients diagnosed with aphasia following left-hemispheric stroke and 20 age-matched healthy controls (HCs) were recruited in this study. The Western Aphasia Battery (WAB) test was used to assess the participants’ language ability. Gray matter volume, spontaneous brain activity, functional connectivity, and effective connectivity were examined in each participant. We discovered that gray matter volumes in right cerebellar lobule VI and right Crus I were significantly lower in the patient group, and the brain activity within these regions was significantly correlated with WAB scores. We also discovered decreased functional connectivity within the crossed cerebrocerebellar circuit, which was significantly correlated with WAB scores. Moreover, altered information flow between the cerebellum and the contralateral cerebrum was found. Together, our findings provide evidence for regional alterations within the cerebellum and the reorganization of the cerebrocerebellar system following poststroke aphasia and highlight the important role of the cerebellum in language processing within aphasic individuals after stroke.
The Effects of Letrozole and Metformin Combined with Targeted Nursing Care on Ovarian Function, LH, and FSH in Infertile Patients with Polycystic Ovary Syndrome
Authors: Jiang Shuai , Tang Ting , Sheng Yongmei , Li Rui , Xu Hua
Published: March 2022

Background. Polycystic ovary syndrome (PCOS) is a common gynecological endocrine disorder in women of gestational age and the most common cause of female infertility. This study aimed to investigate the effect of letrozole and metformin combined with targeted nursing on ovarian function, LH, and FSH in infertile patients with PCOS. Methods. A total of 72 infertile patients with PCOS were divided into the control group and combined group. The control group was given metformin tablets combined with targeted nursing therapy. The combined group was treated with letrozole on the basis of the control group. Ovarian function, LH, and FSH were compared between the two groups before and after treatment. Results. After treatment, the total effective rate (94.44%) of the combined group was significantly higher than that of the control group (80.56%). After treatment, the levels of HbA1c, FINS, HOMA-IR, TG, and TC in the two groups were lower than those before treatment, and the HDL-C level was higher than that before treatment. The full-term delivery rate, ovulation rate, and normal menstrual rate in the combined group were higher than those in the control group. After treatment, the LH level in the combined group was lower than that in the control group, and the FSH level was higher than that in the control group. After 1 month, 3 months, and 5 months of treatment, RI, PI, and ovarian volume were decreased, and the endometrial thickness was increased in both groups. Also, after 5 months of treatment, the RI, PI, and ovarian volume in the combined group were significantly lower than those in the control group, and the endometrial thickness was significantly higher than that in the control group. There was no statistically significant difference in the incidence of adverse reactions between the two groups. Conclusion. The combination of letrozole and metformin with targeted nursing in the treatment of infertility patients with PCOS has better clinical effect and high safety. It can improve endometrial receptivity and ovarian reserve function and regulate LH and FSH levels.
Collaborative Filtering Recommendation Algorithm Based on User Attributes and Item Score
Authors: Liu Chaohui , Kong Xianjin , Li Xiang , Zhang Tongxin
Published: March 2022

To solve the problems of cold start and data sparseness existing in traditional collaborative filtering recommendation algorithm, a collaborative filtering recommendation algorithm based on user attributes and item scoring is proposed. Firstly, we improve the credibility of user similarity and explore the potential interests of users, a new user rating similarity calculation method is constructed by introducing confidence, item popularity, and Pearson weighting. Secondly, we construct a user attribute similarity measurement method by introducing cultural distance, age attribute similarity, and user label similarity. Finally, user rating similarity and user attribute similarity are weighted to form a new similarity measurement model. Through simulation comparison between the collaborative filtering recommendation algorithm and the traditional recommendation algorithm, our results show that the collaborative filtering recommendation algorithm can effectively improve the accuracy of recommendations and the diversity of results and effectively alleviate the problem of data sparseness.
Interference to the Secondary Cable Caused by a Very Fast Transient Overvoltage in a Gas-Insulated Switchgear Substation
Authors: Lin Hanliang , Zhang Zhiyuan , Liu Hongshun , Wang Yifan , Liu Yingnan , Yu Dayang
Published: March 2022

When a very fast transient overvoltage (VFTO) propagates in a high-voltage bus, the capacitive voltage transformer (CVT) causes considerable interference on its secondary side, which will affect the normal operation of the secondary equipment. In this article, a CVT equivalent calculation circuit model was established, and the disturbance voltage of the secondary cable was deduced and calculated. Using electromagnetic transient simulation software, a simulation model of the secondary cable disturbance caused by the VFTO in a 500 kV gas-insulated switchgear (GIS) substation was established, the disturbance voltage at the end of the secondary cable was simulated and analyzed, and the effects of the length of the secondary cable and the grounding mode of the shield on the disturbance were studied. Combined anti-interference measures are also suggested, which use a spiral tube damping busbar, grounding at both ends of the shield using multistrand conductors and installing filter capacitors, all of which greatly reduce the amplitude and harmonic components of the disturbance voltage of the secondary cable.
Evaluation of Compressive and Tensile Strength of Self-Curing Concrete by Adding Crushed Bricks as Additive Material
Authors: Abdulhussain Sana T.
Published: March 2022

Curing is an essential stage in the production of concrete because it controls cement hydration and strength evolution. One of the methods of curing is the internal or self-curing which can be achieved by using materials of specific characteristics inside concrete to provide moisture from within the concrete as opposed to outside of it. This water should not affect the water-cement ratio. Lightweight coarse or fine aggregate or using absorbent polymer particles with an ability to keep water inside the concrete mixture can be used for this purpose. This study presents the use of crushed brick as a curing agent and evaluate its effects on the compressive and tensile strengths of concrete at different ages. Four mixes were used: M0, M10, M20, and M30. All the aggregates in mix M0 are natural gravel, while mixes M10, M20, and M30 contain 10%, 20%, and 30% crushed bricks, respectively, as replacement of coarse aggregate. The tests results showed that using crushed brick as a self-curing agent gave compressive strength up to 87.8% and splitting tensile strength up to 169% compared to water-cured concrete.
Management of Recurrent Pregnancy-Related Pericarditis
Authors: Ibrahim Michel , Fattouh Michael , Jacobs Alice
Published: March 2022

The evidence on recurrent pregnancy-related pericarditis is limited, and management strategies are based on case reports and expert opinion. We describe a patient with myopericarditis complicated by cardiac tamponade presenting shortly after her first pregnancy, which was then complicated by refractory recurrent pericarditis. She was treated with standard first line therapies, such as NSAIDs, corticosteroids, and colchicine, and eventually initiated on the purine analog, azathioprine. Out of fear of teratogenicity, she self-discontinued her maintenance medications and thereafter, her course was complicated by a recurrent flare of pericarditis during a subsequent pregnancy. Our case illustrates the significant burden on our patient due to the incessant nature of her disease and on the providers due to the therapeutic dilemmas associated with family planning and pregnancy. Further data is required on this unique clinical scenario, and patient-centered management by a multidisciplinary team is critical.
Application of Hybrid Teaching Mode in College Students’ English Reading Using Intelligent Wireless Communication Multimedia
Authors: Yan Jiayun
Published: March 2022

The development of multimedia technology and the rise of mixed teaching modes have introduced new forms of teaching organization to the field of education, the traditional teaching methods have been improved, and the advantages of the traditional teaching methods have been brought into play. At the same time, the development of online courses has also provided a new basis for teaching and improved the current teaching environment. The current rapid development of intelligent technology and wireless communication networks provides opportunities for the innovation of multimedia technology and also provides technical support for offline and online teaching in a hybrid teaching mode. What this article needs to discuss is the application of hybrid teaching mode in the English reading teaching of college students under the background of intelligent wireless communication network multimedia technology and explore whether the combination of hybrid teaching mode and intelligent technology can improve the teaching level of college students’ English reading, etc. This paper shows through experimental research that under the teaching organization form of the mixed teaching mode under the background of intelligent wireless communication multimedia, college students’ interest in the course of English reading has increased significantly, and their English reading scores will increase by at least 93%, which can improve students’ autonomous learning ability for college English reading courses.
Application of Intelligent Detection of Neural Signal in Depth Evaluation of Obstetrics and Gynecology Anesthesia
Authors: Zhang Xiushuang , Xu Mingjun , Li Xiaoguang , Cao Xiuling , Che Xiangming
Published: March 2022

In order to evaluate the application of EEG intelligent detection in gynecological anesthesia depth, the application of ANGEL‐6000 EEG depth monitor in laparoscopic gynecological anesthesia was proposed. This method was applied to 60 patients who underwent elective laparoscopic gynecological surgery in our hospital from February to August 2016. Inclusion criteria were ASA i ∼ ii; the average age was (37.8 ± 6.6) years from 20 to 50 years old; the average body weight was (51.53 ± 3.87) kg; conscious and no communication barriers; and patients without instrument ventilation. The patients were divided into observation group and control group according to the random number table method, with 30 patients in each group. The two groups were anesthetized with the same anesthetic drugs, and their consciousness index was monitored. IoC values were recorded before induction of anesthesia (T0), 5 min after intubation (T1), 5 min after operation (T2), intraoperative exploration (T3), at the end of operation (T4), 1 min before extubation (T5), and 5 min after extubation (T6). The dosage of anesthetic drugs, operation time, extubation time, and operation time of the two groups were statistically analyzed. Compared with the operation time of patients in the two groups, the extubation time, awake time, and time out of the operating room of patients in the control group were longer than the observation group. The IoC values of patients in the control group at T0 and T6 time points were lower than those in the observation group at each time point from T1 to T5. Comparison of perioperative dose of remifentanil and atracurium between the two groups was performed. The control group used more propofol dose in perioperative period. The application of neuroelectric signal in laparoscopic gynecological surgery to detect changes in perioperative IoC value can well reflect the level of consciousness of patients and reflect the effect of perioperative stimulation at different time points on the EEG of patients in real time.
A Numerical Study on the Blast Wave Distribution and Propagation Characteristics of Cylindrical Explosive in Motion
Authors: Chen Haojie , Yin Jianping , Li Xudong , Yang Dong , Lu Wenjie
Published: March 2022

In order to study the overpressure distribution law of a shock wave under the dynamic explosion of a cylindrical charge and the influence of the charge speed on the overpressure distribution law, a trinitrotoluene (TNT) cylindrical bare charge was selected. Additionally, a numerical simulation of a cylindrical charge explosion under different motion speeds was carried out using the AUTODYN finite element software. The results showed that during the static explosion of a cylindrical charge, the shock wave propagates outward in the form of an ellipsoid, whereas under the dynamic explosion, the shock wave overpressure field is an irregular ellipsoid, and the shock wave overpressure zone shifts to the velocity direction. With an increase in the charge velocity, the peak value of the shock wave overpressure increases gradually in the moving direction. The simulation data were analyzed, revealing that the calculation model of the dynamic explosion shock wave overpressure field of a cylindrical charge with a scaled distance of 1 m·kg−1/3 ≤ 

R
¯

≤ 1.5 m kg−1/3 can provide a reference basis for the study of dynamic explosion shock waves.
Sports Video Image Segmentation Based on Fuzzy Clustering Algorithm
Authors: Jiang Xingjian , Wu Lei
Published: March 2022

With the development of science and technology, people began to use video image segmentation technology to carry out various research works on sports, to expect effective athlete training effects. Fuzzy clustering algorithm can accurately and quickly extract the distorted data in the process of sports video image segmentation. In order to ensure that the motion curve is not easily affected by noise in the drawing process, this paper studies the sports video segmentation strategy. The fuzzy clustering algorithm can accurately and quickly extract the distortion data in the process of segmentation of sports video images. Therefore, the motion curve is not susceptible to noise during the drawing process, which can be ensured. After completing the above-mentioned sports video segmentation strategy completion experiment, the Release to Manufacturing (RTM) model is used to evaluate the experimental results of the sports video segmentation strategy. According to the RTM model test results, the result of the homogeneity test of variance is that since the result is much larger than 0.10, this can infer that the image quality obtained by the sports video segmentation experiment has reached the Spearman Rank Order Correlation Coefficient (SROCC) standard. Experiments verify the feasibility of applying fuzzy clustering algorithm and moving video image segmentation technology to the segmentation of human model moving video image, so as to obtain more accurate image data.
Numerical Simulation-Based Model for Analyzing the Correlation between GDP Index and Quality of Life
Authors: Jing Leijie
Published: March 2022

As the information carrier of the social economy, the quality of statistical data has become more concerned and sensitive in the society and the data quality of GDP, as one of the core aggregate indicators of national economic accounting, has received more extensive attention. Government statistical departments have placed data quality in a strategic position in the development of statistical undertakings, and the assessment of GDP data quality is an important part of their data production management process. This paper uses the livelihood index to represent the survey data of quality of life level and theoretically analyzes and empirically tests the importance of improving quality of life in the current development stage, the relationship between improving people’s livelihood and economic development, and the population distribution of public service satisfaction and the influence of public service satisfaction on life satisfaction. In response to the major real-life problems in the development of economic and social quality of life, many research institutions have carried out in-depth survey and research work at various levels and in various fields, with large samples and a wide range, accumulating a large number of survey and research reports with detailed data and unique content, the same as thematic research reports with standardized analysis based on survey data. Taking mathematical economics as the basic starting point, this paper conducts an in-depth study on the relationship between GDP index and quality of life from the analysis of the operation law, inner operation mechanism, stability, and other relevant aspects of the model itself. Taking the classical endogenous economic growth model as the starting point, the endogenous theoretical nonlinear dynamical system of GDP index and quality of life, the nonlinear dynamical system of GDP index and quality of life, and the theoretical nonlinear system of GDP index and quality of life supply and demand are constructed; and the stability analysis is conducted for the constructed nonlinear dynamical system, the situation when the model starts to destabilize is discussed and the model is addressed. The theoretical analysis and numerical simulation results are presented for the conditions of existence, bifurcation direction, and stability of the bifurcation period solution of the Hopf bifurcation that may occur.