bluuebunny/crossref_metadata_2025 huggingface dataset:
The Human Migration in 21st Century India: Intensity, Trends, Flow and Opportunities for Economic Development of Migrants
Authors: Firdaus Ghuncha
Published: May 2021

Migration has been an inherent part of human existence since the dawn of human civilisation, shaped by numerous socio-economic factors. Since 1991 India has been experiencing an upsurge in migration, largely affectingurbanisation, social transformation and economic development of the country. The objective of the present study isto analyse spatial-temporal variation in trends, pattern, and reasons for migration, and its impact on society. Based on secondary sources of information and simple statistical methods, the study finds that increasing trends of migration in the country are closely related to the liberalisation of the economy. Excluding marriage-related migration, migration is mainly a male dominated, employment oriented and long distance phenomena.Given the spatial variation in economic development, people migrate from under-developed regions to developed regions to improve their living conditions. Migration is a livelihood strategy for majority of the people and therefore, it should be viewed in the context of regional disparity in economic development.
The analogy of the need for knowledge to seek all the basic education in the society of Duhok
Authors:   Psychology Department, College of Basic Education, Duhok University, Adil Jihan Saeed
Published: May 2021

The need for knowledge is one of the most important human needs. It drives individuals to obtain more information continuously and continuously in order to acquire and increase information. These individuals, through their search for information and new attitudes develop their mental and cognitive abilities, especially in the field of creative thinking and detail, so the current research aims to identify the: 1 - The level of the need for knowledge among students of the Faculty of Basic Education. 2 - Differences in the variable need for knowledge according to two variables: Sex (male, female) (B)- Specialization (scientific, human) In order to achieve the objectives of this research, a tool was used to measure the need for knowledge prepared by the researcher after the preparation of an open survey questionnaire and access to the literature and previous studies, a tool consisting of (27) paragraphs was prepared and composed of four alternatives (always, often, rarely) Consisting of (100) students were randomly selected from the departments of the Faculty of Basic Education at the University of Dohuk, and was investigated from the validity of the tool and the apparent honesty with the stability extracted by half-way. After analyzing the data and processing them statistically using the t-test for one sample and the t-test for two independent samples, the current research results show that the research sample has a high level of need for knowledge and the existence of statistically significant differences between males and females in favor of males, there are statistically significant differences between scientific departments and human departments for the benefit of scientific departments. In the light of the results, the researcher recommends a number of recommendations and suggestions.
Theft and Banditry in Iraq during the reign of the Ottomans from the lens of the Travelers
Authors:   History department, Faculty of Arts, Soran University, Mahmood Neamat Ali
Published: May 2021

Travelers’ books are considered one of the most reliable historical sources for recognizing and the descriptions of those cities they passed through. And also, they are significant references for determining theft and banditry in the last decade of new history. This research is a modest attempt to track impressions of foreign travelers who traveled to Iraqi cities in modern era whether from road routes or river. Registering theft and banditry misbehaviour in the ruling time of Ottoman Empire while they visited Iraqi cities. It is worth mentioning, most of the travelers took notes about their commercial caravans who exposed to robbery and looting and even killing by thieves and bandits, whether the caravans were big, medium or small in size. Furthermore, they noted the associated factors to the phenomenon in regard to the privacy and distinguished one place to another. Key words: travelers, theft, bandits, Arab Bedouins, Kurds, Iraq, the Ottomans.
Application of ultrasound and contrast-enhanced ultrasound to distinguish salivary focal inflammatory masses from malignant masses: A retrospective observational study
Authors: Zhao Yanan , Jiang Tao , Lv Kun , Pan Minqiang , Wen Qing , Huang Pintong
Published: May 2021

BACKGROUND: The aim was to retrospectively analyze the ultrasonographic and clinical characteristics of focal inflammatory masses and malignant masses of salivary gland by using B-mode ultrasound (US) and contrast-enhanced ultrasound (CEUS) for differential analysis. METHODS: The features of US and CEUS were retrospectively analyzed for 19 cases of focal salivary inflammatory masses and 45 cases of malignant salivary masses. All cases were confirmed by pathohistological examination. RESULTS: On B-mode US, the incidence of expansive growth patterns of malignant salivary masses (44.4%, 20/45) was significantly higher than that of focal salivary inflammatory masses (15.8%, 3/19) (p = 0.029). The rate of lymphadenopathy surrounding salivary glands of malignant salivary masses (42.2%, 19/45) was significantly higher than that of focal salivary inflammatory masses (15.8%, 3/19) (p = 0.042). On CEUS, clear enhancement margins were more common in malignant salivary masses (44.4%, 20/45) compared to focal salivary inflammatory masses (15.8%, 3/19) (p = 0.029); Rapid washout was more common in malignant salivary masses (82.2%, 37/45) than focal salivary inflammatory masses (31.6%, 6/19) (p < 0.001). Rapid washout on CEUS and craniocaudal diameter were independent predictive factors in differentiating salivary inflammatory masses and malignant masses according to binary logistic regression analysis. US and CEUS achieved a sensitivity of 80.0%, a specificity of 78.9% and an accuracy of 80.0% for discrimination between salivary inflammatory masses and malignant masses. CONCLUSION: Therefore, a multimodal ultrasonographic pathway combining clinical manifestations, B-mode US and CEUS was needed to differentiate between salivary focal inflammatory masses and malignancies to avoid unnecessary biopsies.
Reduced microvascular reactivity in patients with diabetic neuropathy
Authors: Krasulina Ksenia A. , Glazkova Polina A. , Glazkov Alexey A. , Kulikov Dmitry A. , Rogatkin Dmitry A. , Kovaleva Yulia A. , Bardeeva Julia N. , Dreval Alexander V.
Published: May 2021

BACKGROUND: Neurogenic regulation is involved in the development of microcirculation response to local heating. We suggest that microvascular reactivity can be used to estimate the severity of diabetic polyneuropathy (DPN). OBJECTIVE: To evaluate the prospects for using the parameters of skin microvascular reactivity to determine the severity of DPN. METHODS: 26 patients with diabetes mellitus were included in the study (patients with retinopathy (n = 15), and without retinopathy (n = 11)). The severity of DPN was assessed using Michigan Neuropathy Screening Instrument (MNSI) and Norfolk QOL-DN (NQOLDN). Skin microcirculation was measured by laser Doppler flowmetry with local heating test. RESULTS: There were revealed moderate negative correlations between microvascular reactivity and the severity of DPN (for MNSI (Rs = –0.430), for NQOLDN (Rs = –0.396)). In patients with retinopathy, correlations were stronger than in the general group (for MNSI (Rs = –0.770) and NQOLDN (Rs = –0.636)). No such correlations were found in patients without retinopathy. CONCLUSION: Correlation of the microvascular reactivity and DPN was revealed in patients with registered structural disorders in microvessels (retinopathy). The lack of such correlation in patients without retinopathy may be explained by the intact compensatory mechanisms of microvessels without severe disorders.
Study on correlation between two-dimensional ultrasound, contrast-enhanced ultrasound and microvascular invasion in hepatocellular carcinoma
Authors: Wang Peihua , Nie Fang , Dong Tiantian , Wang Guojuan , Wang Lan , Fan Xiao
Published: May 2021

OBJECTIVE: To explore the correlation between two-dimensional ultrasound (2D-US), contrast-enhanced ultrasound (CEUS) and microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS: In this retrospective study, 56 patients with surgically pathologically confirmed HCC lesions were included. Patients were classified according to the presence of MVI: MVI positive group (n = 17) and MVI negative group (n = 39). 2D-US and CEUS examinations were performed within two weeks before surgery. The 2D-US and CEUS features were analyzed for correlation with MVI. Statistically significant parameters of ultrasound characteristic were scored, and the results of the scores were analyzed by ROC curve. RESULTS: There were statistically significant differences in tumor shape, boundary, capsule, CEUS portal phase and delayed phase enhancement pattern, time to wash out, and tumor margin after enhancement (P < 0.05), while there were no statistically significant differences in tumor location and size, CEUS arterial phase enhancement pattern, initial time, time to peak, and peritumor enhancement (P > 0.05). When diagnosing the presence of MVI in HCC patients with cut-off value of the score combined 2D-US and CEUS features≥3, the maximum Jorden index was 0.58, and its diagnostic sensitivity and specificity were 94.10% and 64.1%, respectively, meaning that the total score≥3 was highly suspicious of the presence of MVI. CONCLUSIONS: 2D-US and CEUS are feasible methods for preoperative prediction of MVI in HCC, and can provide some theoretical basis for individualized clinical treatment.
A net-flow based approach to detect outliers in multicriteria decision problems
Authors: Rouba Baroudi
Published: May 2021

Detecting outliers in multicriteria decision aid (MCDA) field is a new research direction that has not been enough explored. This paper tackles this problem by proposing a statistical approach based on PROMETHEE method net-flow. To consider the multicriteria character of the problem, the net-flow of each object is computed by applying PROMETHEE method. According to the normal distribution of the net-flow values, the standard deviation (SD) or interquartile range (IQR) statistical methods are used to detect outliers. To prove its applicability, the proposed approach is evaluated on real life problem.
Comparative investigation of machine learning algorithms for detection of epileptic seizures
Authors: Sharma Akash , Kumar Neeraj , Kumar Ayush , Dikshit Karan , Tharani Kusum , Singh Bharat
Published: May 2021

In modern day Psychiatric analysis, Epileptic Seizures are considered as one of the most dreadful disorders of the human brain that drastically affects the neurological activity of the brain for a short duration of time. Thus, seizure detection before its actual occurrence is quintessential to ensure that the right kind of preventive treatment is given to the patient. The predictive analysis is carried out in the preictal state of the Epileptic Seizure that corresponds to the state that commences a couple of minutes before the onset of the seizure. In this paper, the average value of prediction time is restricted to 23.4 minutes for a total of 23 subjects. This paper intends to compare the accuracy of three different predictive models, namely – Logistic Regression, Decision Trees and XGBoost Classifier based on the study of Electroencephalogram (EEG) signals and determine which model has the highest rate of detection of Epileptic Seizure.
Learn-and-play personalised reasoning from point-and-click to virtual reality mobile educational games
Authors: Papadimitriou Spyros , Kamitsios Margaritis , Chrysafiadi Konstantina , Virvou Maria
Published: May 2021

Nowadays, the use of digital games for educational purposes becomes increasingly popular. The immersive environment of a digital game causes pleasant feelings to players motivating them to participate more actively in the learning process. However, there is a variety of educational games in terms of graphics and mechanics, and each player prefers to play different game categories. For maximizing the learner’s engagement and educational results, the incorporation of the same educational content into multiple games’ categories is the solution. Nevertheless, the update of the educational content in all games increases complexity. In this paper, a mechanism that uses web services and achieves the portability of the same educational content in two completely different categories of mobile games (a point-and-click game and a virtual reality game) is presented. The gain of this innovative work is that the same educational content and mechanism can be accessible by any game’s category and platform, taking advantage of the game’s characteristics, in order to motivate the student to participate in the learning process and increase her/his engagement in it. The evaluation of the presented system indicates that the integration of the same educational content to different games has a positive effect on educational results.
Expression and Localization of AβPP in SH-SY5Y Cells Depends on Differentiation State
Authors: Riegerová Petra , Brejcha Jindřich , Bezděková Dagmar , Chum Tomáš , Mašínová Eva , Čermáková Nikola , Ovsepian Saak V. , Cebecauer Marek , Štefl Martin
Published: May 2021

Neuroblastoma cell line SH-SY5Y, due to its capacity to differentiate into neurons, easy handling, and low cost, is a common experimental model to study molecular events leading to Alzheimer’s disease (AD). However, it is prevalently used in its undifferentiated state, which does not resemble neurons affected by the disease. Here, we show that the expression and localization of amyloid-β protein precursor (AβPP), one of the key molecules involved in AD pathogenesis, is dramatically altered in SH-SY5Y cells fully differentiated by combined treatment with retinoic acid and BDNF. We show that insufficient differentiation of SH-SY5Y cells results in AβPP mislocalization.
Benefits in Alzheimer’s Disease of Sensory and Multisensory Stimulation
Authors: Yang Hong , Luo Yinpei , Hu Qingrong , Tian Xuelong , Wen Huizhong
Published: May 2021

Alzheimer’s disease (AD) is a serious neurodegenerative disease, which seriously affects the behavior, cognition, and memory of patients. Studies have shown that sensory stimulation can effectively improve the cognition and memory of AD patients, and its role in brain plasticity and neural regulation is initially revealed. This paper aims to review the effect of various sensory stimulation and multisensory stimulation for AD, and to explain the possible mechanism, so as to provide some new ideas for further research in this field. We searched the Web of Science and PubMed databases (from 2000 to October 27, 2020) for literature on the treatment of AD with sensory and multisensory stimulation, including music therapy, aromatherapy, rhythmic (e.g., visual or acoustic) stimulation, light therapy, multisensory stimulation, and virtual reality assisted therapy, then conducted a systematic analysis. Results show these sensory and multisensory stimulations can effectively ameliorate the pathology of AD, arouse memory, and improve cognition and behaviors. What’s more, it can cause brain nerve oscillation, enhance brain plasticity, and regulate regional cerebral blood flow. Sensory and multisensory stimulation are very promising therapeutic methods, and they play an important role in the improvement and treatment of AD, but their potential mechanism and stimulation parameters need to be explored and improved.
Relationship of Homocysteine Plasma Levels with Mild Cognitive Impairment, Alzheimer’s Disease, Vascular Dementia, Psychobehavioral, and Functional Complications
Authors: Lauriola Michele , D’Onofrio Grazia , Ciccone Filomena , Germano Carmela , Cascavilla Leandro , Paris Francesco , Greco Antonio
Published: May 2021

Background: Alzheimer’s disease (AD) may be a vascular disorder with neurodegenerative consequences opening possibility of preventing AD by targeting vascular risk factors including homocysteine. Objective: The study aims were to assess homocysteine distribution in different forms and severity of cognitive impairment (CogI) [mild cognitive impairment (MCI), probable AD (Prob-AD), possible AD (Poss-AD), and vascular dementia (VaD)] and in NoCogI, and to estimate possible association between hyperhomocysteinemia levels with functional deficit severity and psychobehavioral complications. Methods: In total, 929 (M = 366, F = 563; mean age of 72.55±6.24 years) patients were evaluated with cognitive, neuropsychiatric, affective, and functional assessment scales. Homocysteine serum was set on two levels: between 0 and 10μmol/L and > 10μmol/L. For each patient, blood concentration of folate, vitamin B12, hemoglobin, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), cholesterol, triglycerides, and glycemia were measured. Results: CogI patients demonstrated significantly a higher frequency of homocysteine > 10 (p = 0.003), than NoCogI patients. Patients with moderate and severe dementia had a higher frequency of homocysteine > 10 (p < 0.0001), than MCI and mild dementia. Poss-AD and VaD had a higher frequency of homocysteine > 10 (p = 0.003), than Prob-AD patients. Homocysteine > 10 frequency is directly proportional to increased neuropsychiatric symptom severity (p < 0.0001), and functional impairment severity respectively for ADL (p < 0.0001) and IADL (p < 0.0001). Conclusion: Higher homocysteine level seems to be significantly related to cognitive impairment frequency and severity, possible AD and VaD, neuropsychiatric symptom severity, and functional impairment severity.
Benson’s Disease or Posterior Cortical Atrophy, Revisited
Authors: Yerstein Oleg , Parand Leila , Liang Li-Jung , Isaac Adrienne , Mendez Mario F.
Published: May 2021

Background: D. Frank Benson and colleagues first described the clinical and neuropathological features of posterior cortical atrophy (PCA) from patients in the UCLA Neurobehavior Program. Objective: We reviewed the Program’s subsequent clinical experience with PCA, and its potential for clarifying this relatively rare syndrome in comparison to the accumulated literature on PCA. Methods: Using the original criteria derived from this clinic, 65 patients with neuroimaging-supported PCA were diagnosed between 1995 and 2020. Results: On presentation, most had visual localization complaints and related visuospatial symptoms, but nearly half had memory complaints followed by symptoms of depression. Neurobehavioral testing showed predominant difficulty with visuospatial constructions, Gerstmann’s syndrome, and Balint’s syndrome, but also impaired memory and naming. On retrospective application of the current Consensus Criteria for PCA, 59 (91%) met PCA criteria with a modification allowing for “significantly greater visuospatial over memory and naming deficits.” There were 37 deaths (56.9%) with the median overall survival of 10.3 years (95% CI: 9.6–13.6 years), consistent with a slow neurodegenerative disorder in most patients. Conclusion: Together, these findings recommend modifying the PCA criteria for “relatively spared” memory, language, and behavior to include secondary memory and naming difficulty and depression, with increased emphasis on the presence of Gerstmann’s and Balint’s syndromes.
Numerical study on key parameters of a Magnetorheological Fluid reciprocating seal with increasing width of pole teeth and pole piece
Authors: Yang Xiaolong , Guan Ying , Li You , Gao Shanghan
Published: May 2021

In order to solve the problem of reciprocating seal for hydraulic cylinder, a new structure of Magnetorheological fluid (MRF) reciprocating seal with increasing width of pole teeth and pole piece was designed. The theoretical analysis of MRF reciprocating seal is carried out. The magnetic field intensity distribution in the sealing gap of MRF reciprocating seal was analyzed by finite element method. According to the pressure capability formula of MRF, the theoretical pressure capability is calculated. The influences of structure parameters such as the number of magnetic sources, sealing gap height, pole teeth length, the ratio of permanent magnet height to its length, the ratio of pole piece height to shaft radius on the sealing capabilities were studied. The results showed that the pressure capability of MRF reciprocating seal increases with the increase of the number of magnetic sources and with the decrease of the sealing gap height. With the increase of the pole tooth length, the pressure capability of the reciprocating seal increases. With the increase of the ratio of permanent magnet height to its length, the pressure capability of the reciprocating seal increases first and then decreases. With the increase of the ratio of the pole piece height to shaft radius, the pressure capability of the MRF reciprocating seal increases first and then decreases.
Decision-making support for transportation and logistics combining rough set fuzzy logic algorithm
Authors: Chen Tian
Published: May 2021

To lower the operating cost of an enterprise, improving the efficiency of logistics, or reducing the cost of circulation is one of the crucial means for the enterprise to cut the costs. In this paper, combined with the rough set fuzzy logic algorithm, in response to the features of the large-scale vehicle scheduling problem, the data collected by monitoring in real time provided by the tracking technology, in conjunction with the data mining technology, are used to support the decision making based on the reverse logistics mode and establish a vehicle scheduling optimization model with the purpose to support the decision making in transportation logistics.
Some self-evaluation models of enterprise’s credit based on some probabilistic double hierarchy linguistic aggregation operators
Authors: Lei Fan , Wei Guiwu , Chen Xudong
Published: May 2021

Probabilistic double hierarchy linguistic term set (PDHLTS) can not only express the complex linguistic information that the probabilistic linguistic term set (PLTS) cannot express, but also reflect the frequency or importance of linguistic term set (LTS)that cannot be reflected by the double hierarchy linguistic term set (DHLTS). It is an effective tool to deal with multiple attribute group decision making (MAGDM) problems. Therefore, in this paper, we propose several aggregation operators which can aggregate PDHLTS information and apply them to MAGDM problems. Firstly, the basic notion of PDHLTS is reviewed, and the distance formula and algorithm of PDHLTS are defined; then, extant weighted averaging (WA) operator, weighted geometric(WG) operator and power weighted averaging (PWA) operator, power weighted geometric(PWG) operator to PDHLTS, and establish probability double hierarchy linguistic weighted averaging (PDHLWA) operator, probability double hierarchy linguistic weighted geometric (PDHLWG) operator, probability double hierarchy linguistic power weighted averaging (PDHLPWA) operator, probability double hierarchy linguistic power weighted geometric (PDHLPWG) operator; in addition, The idempotency, boundedness and monotonicity of these aggregation operators are studied; what’s more, those aggregation operators are proposed to establish the enterprise credit self-evaluation model; Finally, compared with the available probabilistic double hierarchy linguistic MAGDM methods, the defined model is proved to be scientific and effective.
Fuzzy processing system for psychological pressure of English teachers at work based on analysis of online teaching video
Authors: Jin Zheng
Published: May 2021

Due to the fast pace of modern online English teaching and the complicated teaching relationship, English teachers face increasing pressure in teaching work, which easily leads to various psychological problems. In view of this, based on theoretical results and expert experience in the field of psychological pressure of English teachers, this paper uses fuzzy processing systems and fuzzy weighted logic inference theory to establish a knowledge base in the field of psychological health and an evaluation model for psychological pressure of English teachers. Moreover, this paper carries out knowledge representation and reasoning on the knowledge of psychological health theory, and applies the evaluation reasoning model to the expert system of psychological health evaluation of English teachers to finally design and realize the expert system of psychological health evaluation of English teachers based on fuzzy weighted logic. Finally, this paper designs experiments to verify the system performance. The research results show that the system’s data processing speed and the accuracy of the evaluation results of psychological stress of English teachers meet the actual needs.
Chemical static equipment commonly used sensor fault detection and isolation methods
Authors: Peng Fang , Yang Wei
Published: May 2021

This paper conducts a study on the faults of common sensors involved in chemical static equipment. Firstly, the types and characteristics of commonly used sensors of chemical static equipment are analyzed, and the characteristics of sensor output signal changes are summarized with the working characteristics of chemical equipment. Then the faults of static equipment sensors are classified and a fault model is established. Through the study of sensor fault detection and isolation methods at home and abroad, the overall scheme of sensor system fault detection and isolation combining single sensor fault detection and isolation method and multi-sensor fault detection and isolation method is proposed. According to the characteristics that chemical processes are generally in a dynamic and stable state and there is a certain correlation between the signals of each detection point in the equipment, a sensor system model is established by using the correlation of multiple sensors on the equipment, and when a sensor in the sensor system fails, the system model changes beyond the threshold value, and a different form of residual generation is used to determine which sensor is faulty and achieve the detection and isolation of faulty sensors. The fault detection method is simulated and studied by using relevant software, combined with a support vector machine and neural network toolbox. The results show that the method proposed in this paper can effectively complete the fault detection and isolation of sensors commonly used in chemical static equipment. The accuracy and reliability of the prediction model are high.
Information asymmetric enterprise management incentive mechanism based on dissipative structure
Authors: Wu Lingling
Published: May 2021

Because the enterprise management incentive mechanism operates in the complexity and nonlinearity of the enterprise system, its life evolution process is full of uncertainty and chaos. The theory of management entropy and management dissipative structure reveals two trends in the development of corporate organizational structure and incentive mechanism. Through the analysis of information asymmetry in corporate activities, we can know that information asymmetry absolutely exists. In order to weaken the information asymmetry, the enterprise must design an effective management system to make the company management more systematic. Based on the analysis of the basic theories of management entropy and management dissipative structure, this paper applies the two to the study of corporate incentives. Then, based on the self-organization theory of dissipative structure, we discussed the orderly evolution mechanism of the enterprise management system, and judged the development trend of corporate management performance from the perspective of system changes. The order degree calculation model can then evaluate the efficiency of corporate management and provide a new perspective for corporate management. Judging the role and development stage of management entropy and management dissipative structure in the enterprise’s incentive mechanism, so that the incentive can play an effective role, and provide theoretical support and practical methods for the enterprise to establish a good incentive mechanism.
Research on the model of smart grid wide-area measurement cyber-physical fusion system based on data fusion
Authors: Yang Xinhui , Xue Wei
Published: May 2021

Due to price and technical reasons, it is currently impossible to install phasor measurement units in the entire network. How to use the minimum number of phasor measurement units to maximize the observation of the state or dynamic behavior of the power grid is the first consideration for the wide-area measurement system at this stage. This paper proposes a method to optimize the configuration of the phasor measurement unit while ensuring that the power grid is fully observable and can capture the dynamic behavior of the power grid under transient conditions. This paper proposes a load modeling method based on wide-area measurement. Aiming at the problems of traditional large-area power grid load modeling based on load characteristic measurement devices and the characteristics of the current wide-area measurement system, a load modeling method based on local PMU observations is proposed. This method combines particle swarm optimization algorithm and time. Domain simulation calculation can identify the load models at all load nodes of the system at the same time. This paper proposes a CPPS information flow transmission model based on graph theory and information flow dynamics. This model considers the coupling effect of CPPS, the processing capacity of communication equipment and the transmission mode of CPPS information flow, and constructs a CPPS dynamics model from the perspective of communication transmission. In the analysis of the calculation example, by applying the information flow transmission model to CPPS topologies generated by different scales and different modeling methods, the influence of network scale, key nodes and network topology structure on the efficiency of CPPS information transmission was explored, and the effectiveness of the model was verified.
Robust feature collection and classification of network culture
Authors: Gao Ya
Published: May 2021

The network provides a convenient mechanism for publishing and obtaining documents, and has now become a gathering place for all kinds of information. In the network, the amount of information increases exponentially, and how to dig useful patterns or knowledge from the massive network culture has become a hot topic for scholars. In data mining, in order to enable readers to quickly obtain the content of interest, research text classification, and automatically classify text data according to a certain classification model. Internet cultural text data has the characteristics of unstructured, subjective, high-dimensional, etc., which makes it difficult for text mining algorithms to extract effective and easy-to-understand classification rules, and the computational complexity is too high. This paper proposes a feature selection method based on robust features, using sample deviation and variance as the criteria for feature attributes to rank the importance of feature attributes, and select the best feature attribute subset. The experimental results show that the classification accuracy of the feature selection method based on sample deviation and variance proposed in this paper is higher than the traditional word frequency as the feature selection method, which proves the feasibility and superiority of the feature selection method proposed in this paper.
Intelligent data-driven in shanghai stock exchange options based on state space model
Authors: Li Huahua , Gu Lihan
Published: May 2021

The current relevant models for the analysis of SSE options, whether for the study of theoretical algorithms or for the application of verification, are still at the beginning of the research stage. Based on this, this study combines the status quo of China’s SSE options to construct a state space model with certain flexibility and combines image processing technology to extract model features. At the same time, this study obtained the experimental data of this study through network data collection method and analyzed the performance of the algorithm by comparison method, recorded the data obtained by the model operation, and turned the result into a visually identifiable feature result through image processing. The research indicates that the state space model has certain effects in the analysis of SSE option and can provide theoretical reference for subsequent related research.
Internet of things image recognition system based on deep learning
Authors: Li Jing , Li Xinfang , Ning Yuwen
Published: May 2021

At present, many exciting results have been achieved in the application of deep learning to image recognition. However, there are still many problems to be overcome before deep learning is used in practical applications such as image retrieval, image annotation, and image-text conversion. This paper studies the structure of deep learning, improves the commonly used training algorithms, and proposes two new neural network models for different application scenarios. This paper uses Support Vector Machine (SVM) as the main classifier for Internet of Things image recognition and uses the database of this paper to train SVM and CNN. At the same time, the effectiveness of the two for image recognition is tested, and the trained classifier is used for image recognition. The result surface: In the labeled data set, the rank-1 accuracy of CNN is 85.77%, which is higher than 90.28% of the SVM method. In the detection data, CNN’s rank-1 accuracy rate is 83.11%, which also exceeds SVM’s 80.22%. SVM+CNN has a rank 1 value of 84.69% for the detection data set. This shows that deep learning can map the feature representation of the image and the feature representation of the word to the same space, making the calculation of the similarity and correlation between the image and the text easier and more straightforward.
An analysis of deep neural network models for image recognition applications
Authors: Wang Lin , Wang Xingfu , Hawbani Ammar , Xiong Yan , Zhang Xu
Published: May 2021

The development of hardware technology and information technology has promoted the development of image recognition technology. Today, image recognition technology has been applied to many national defense technologies; especially target image recognition technology is widely used in the field of air threat prevention. However, nowadays, the air target recognition technology has the disadvantage of high misjudgment rate. The main reason is that the sky is too large and the distance gap makes it difficult to distinguish the target image from other noise images. This paper takes the neural network as the classification tool, through image preprocessing and contour extraction, establishes the recognition model of the target image. The simulation results of 10 data sets show that the method used in this paper is more than 85% accurate, but the error rate is only 0.7%. The simulation results show that the model designed in this paper can achieve air target recognition very well.
Continuous energy restriction (CER) plus 16/8 time-restricted feeding improve body composition and metabolic parameters in overweight and obese, but no more than CER alone
Authors: Ribeiro Daiani Evangelista , Santiago Andrezza Fernanda , Abreu Wilson Cesar de
Published: May 2021

BACKGROUND:

Current guidelines recommend continuous energy restriction (CER) and lifestyle change as the basis of obesity treatment. Recently, several intermittent fasting protocols have received considerable interest as an alternative weight loss strategy.

OBJECTIVE:

This study compared the effects of 8-week CER versus CER along with 16/8 time-restricted feeding (16/8 TRF) on body composition and metabolic markers in excess weight physically active subjects.

METHODS:

Twenty-four physically active obese or overweight adults, from both genders, were split into two groups: CER plus 16/8 TRF (CER + TRF) and CER. Both groups consumed a 20%energy restriction diet. CER plus 16/8 TRF were asked to consume their meals during an 8-hour open window (12 to 20 pm). We evaluated body composition and metabolic biomarkers before and after the intervention.

RESULTS:

We observed a reduction in body weight (BW), body mass index (BMI), waist circumference (WC), and fat mass (FM) in both groups. However, a decrease in fat-free mass (FFM) and skeletal muscle mass (SMM) was seen only in the CER. Although fasting glucose did not change, we observed a decrease in fasting insulin and HOMA-IR in both groups. Leptin decrease in both treatments. Cortisol levels increased only in the CER group.

CONCLUSIONS:

We can conclude that CER + TRF is as effective as CER to promote weight and fat loss, but, CER + TRF seems to be more efficient in maintaining lean body mass.
Automatic modelling of human musculoskeletal ligaments – Framework overview and model quality evaluation
Authors: Hamze Noura , Nocker Lukas , Rauch Nikolaus , Walzthöni Markus , Carrillo Fabio , Fürnstahl Philipp , Harders Matthias
Published: May 2021

BACKGROUND: Accurate segmentation of connective soft tissues in medical images is very challenging, hampering the generation of geometric models for bio-mechanical computations. Alternatively, one could predict ligament insertion sites and then approximate the shapes, based on anatomical knowledge and morphological studies. OBJECTIVE: In this work, we describe an integrated framework for automatic modelling of human musculoskeletal ligaments. METHOD: We combine statistical shape modelling with geometric algorithms to automatically identify insertion sites, based on which geometric surface/volume meshes are created. As clinical use case, the framework has been applied to generate models of the forearm interosseous membrane. Ligament insertion sites in the statistical model were defined according to anatomical predictions following a published approach. RESULTS: For evaluation we compared the generated sites, as well as the ligament shapes, to data obtained from a cadaveric study, involving five forearms with 15 ligaments. Our framework permitted the creation of models approximating ligaments’ shapes with good fidelity. However, we found that the statistical model trained with the state-of-the-art prediction of the insertion sites was not always reliable. Average mean square errors as well as Hausdorff distances of the meshes could increase by an order of magnitude, as compared to employing known insertion locations of the cadaveric study. Using those, an average mean square error of 0.59 mm and an average Hausdorff distance of less than 7 mm resulted, for all ligaments. CONCLUSIONS: The presented approach for automatic generation of ligament shapes from insertion points appears to be feasible but the detection of the insertion sites with a SSM is too inaccurate, thus making a patient-specific approach necessary.
Cutting and Pasting: What L.M. Montgomery’s Island Scrapbooks Reveal about Her Reading
Authors: Strom Collins Carolyn
Published: May 2021

The text below is an introduction to and synopsis of “Cutting and Pasting: What L.M. Montgomery’s Island Scrapbooks Reveal about Her Reading,” a paper (available below in video form) first presented to the L.M. Montgomery international conference L.M. Montgomery and Reading in June 2018 and recorded on 31 July 2018 at the University of Prince Edward Island.
Red Hair in a Global World: A Japanese History of Anne of Green Gables and Prince Edward Island
Authors: Pass Michael B.
Published: May 2021

There is likely no version of Anne of Green Gables more mythologized than Muraoka Hanako’s 1952 Japanese translation, Akage no An. While many arguments have been offered to explain Anne’s Japanese success, this article moderates some of the more sensationalized while also situating the book within Japan’s wider cultural history.
Reading as Empowerment: Lost in the Swedish Translations of L.M. Montgomery’s Emily Books
Authors: Leden Laura
Published: May 2021

This case study explores intertextual references in L.M. Montgomery’s Emily trilogy, originally written and marketed for a dual audience of adults and teenage girls. Emily’s reading and interaction with other texts empower her by inspiring her writing, supporting her maturation into womanhood, and underpinning her development as a reader and writer, whereby Montgomery subversively challenges the conventions of traditional female gender roles. In the Swedish 1950s translations abridged for a younger target audience than the originals, many intertextual references are lost. As a result, Swedish readers are presented with a more conventional and constrained and less challenging image of Emily and girlhood because Emily’s reading and writerly ambitions are downplayed.
Le Médium (au) cinéma
Authors: Berton Mireille
Published: May 2021

À partir d’une réflexion sur la polysémie du terme « médium », ainsi que d’une histoire croisée du cinéma et du spiritisme, cet ouvrage propose d’analyser la manière dont l’imaginaire spirite fait l’objet de représentations filmiques nourries par des discours (implicites ou explicites) sur les technologies d’enregistrement et de reproduction, et en particulier sur le cinéma qui devient, sous cet angle, une machine à fantômes particulièrement efficace.
The Serum Level of Midkine in Patients With Multiple Sclerosis and Neuromyelitis Optica
Authors:   Isfahan Neurosciences Research Center, Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran., Moayednia Milad , Dehghani Leila ,   Department of Tissue Engineering and Regenerative Medicine, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran., Safi Amir ,   Isfahan Neurosciences Research Center, Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran., Shaygannejad Vahid ,   Isfahan Neurosciences Research Center, Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran., Sohrabi Karim ,   Isfahan Neurosciences Research Center, Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran., Rezvani Majid ,   Department of Neurosurgery, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran., Soghrati Mojgan ,   Isfahan Neurosciences Research Center, Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran., Aboutalebi Mohammad Mahdi ,   Isfahan Neurosciences Research Center, Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran., Barzegar Mahdi ,   Isfahan Neurosciences Research Center, Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran.
Published: May 2021

Introduction: Midkine (MK), a heparin-binding growth factor, is involved in neurological diseases by mediating the inflammatory responses through enhancing the leukocyte migration. The present study assesses the serum concentration of this growth factor among newly developed Multiple Sclerosis (MS) and Neuromyelitis Optica (NMO) patients. Methods: The present research, as a cross-sectional study, was performed at Isfahan University of Medical Sciences, Isfahan City, Iran. All samples were selected from patients who visited Kashani and Alzahra hospitals for two years (2014 to 2016). The MK level was assessed in 80 new MS cases, 80 NMO patients, and 80 healthy subjects. After collecting blood sera samples, MK serum level was measured using the ELISA. The obtained data were analyzed in SPSS. Results: The Mean±SD MK level was 1038.58±44.73 pg/mL in the MS group, which was significantly higher than the Mean±SD MK level in the NMO (872.62±55.42 pg/mL) and control groups (605.02±9.42 pg/mL). Conclusion: Overall, these results demonstrated that MK plays a prominent role in inflammatory reactions and neuroautoimmune diseases, especially in MS. So, the MK level may be used for earlier diagnosis and also prevention of disease progression by using a special inhibitor.
Report of Field Assessment in the Flooded Areas of Iran, 2019
Authors:   Department of Health in Disasters and Emergencies, Health Human Resources Research Center, School of Management and Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran., Mohammadinia Leila , Ahmadi Marzaleh Milad ,   Department of Health in Disasters and Emergencies, Health Human Resources Research Center, School of Management and Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran., Peyravi Mahmoud Reza ,   Department of Health in Disasters and Emergencies, Health Human Resources Research Center, School of Management and Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
Published: May 2021

Background: Iran is a disaster-prone country, which in recent years has been affected by heavy rainfall and consequent flooding. In March 26, 2019, heavy rainfall in northern parts of Iran resulted in flooding. The situation became more critical when central and western provinces were affected, finally causing significant damages in 25 provinces. The most affected areas were Golestan, and Khuzestan provinces with significant damages to their infrastructure, killing 76 people. Materials and Methods: This qualitative study aims to describe the findings and results of field visits in flood-hit provinces of Lorestan, Khuzestan and Golestan. All interviews were held with experts in late April 2019. Results: Golestan province was in recovery phase and Lorestan and Khuzestan provinces were in response phase. Due to the acute conditions of these two mentioned areas, it was not possible to visit all areas. In Lorestan Province Treatment and Emergency Situations; In Golestan Province Health Status and in Khuzestan Province Pre-hospital Care and Rescue Support were visited and evaluated. The field visited results indicate the presence of government forces and people in the field and provide comprehensive assistance to the flood-affected areas. Conclusion: There are numerous hazards each year, but few documented lessons are available for researchers. Due to the importance of applying lessons for community development it is imperative that special attention be paid to the discussion of emergency and disaster research and the presence of specialized researchers to record lessons learned. Although organizations make significant efforts during disasters, the specialized research force for recording these achievements in disasters remains neglected. Therefore, it is valuable to document and apply appropriate documentation to promote interventions and responses to possible future events.