bluuebunny/crossref_metadata_2025 huggingface dataset:
INTELLECTUAL CAPITAL IN THE PROCESSES OF DIGITALIZATION OF ENTREPRENEURSHIP ACTIVITY
Authors:   Kyiv National Economic University Named after Vadym Hetman, RIEPINA I. , GONCHAR A. ,   Kyiv National Economic University Named after Vadym Hetman
Published: May 2021

International integration and globalization processes, increased competition as characteristics of the business environment and entrepreneurial activity, digitalization of society affect the transformational changes not only in the economic development of national economies, but also business structures in particular. Under these conditions, the main resource to increase the competitiveness of the enterprise is intellectual capital. The need of business structures in the improvement of management technologies for the formation of intellectual capital, capacity development, rapid adaptation to digitalization processes and enabling the use of Smart-technologies. The article considers the essence and features of intellectual capital formation of business structures, establishes the relationship of intellectual potential and intellectual capital, identifies the components of their formation. Based on a study of important foreign ratings, concludes that the dynamics of innovative enterprises of Ukraine and development indicators intellectual capital are often lower than foreign leaders. That is why the conclusion was made about the need to introduce modern innovative technologies, development of innovative products, which is impossible without the widespread use of digital technologies. The conclusion on the role of the information system of the enterprise in realization of current tasks and prospects of development of business structures is made, and the position of intellectual capital and Smart-technologies in the management system of the modern enterprise is substantiated.
The Effectiveness of Kesum Leaves (Polygonum Minus) In Reducing of Free Fatty Acids In Used Cooking Oil
Authors: Ratnawaty Gervacia Jenny , Indrawati Ratih
Published: May 2021

This study aims to determine the effect of adding kesum leaves (polygonum minus) to used cooking oil on reducing levels of free fatty acids. This type of research is quasi experimental. The population in this study is used cooking oil and the sample used is used cooking oil that has been added with the leaves of kesum with 5 treatments and replicated 5 times so that the total sample is 25.From the results, it was found that the average reduction in free fatty acid levels in used cooking oil before adding the leaves of kesum was 7,12%, which had added kesum leaves as much as 20 grams of 6.93%, 40 grams of 5.36%, 60 gr at 3.93%, 80 gr at 3.26% and 100 gr at 1.62%. The results of the analysis using linear regression test, it is known that the addition of 20 grams and 40 grams of p-value is 0.026 and 0.021 (p <0.05), respectively, so Ha is accepted, that is, there is a relationship between the effectiveness of leaves of kesum (polygonum minus) in reducing levels of fatty acid numbers. free of used cooking oil, namely the addition of 20 and 40 grams. Whereas in the addition of 60, 80 and 100 grams of kesum leaves there was no relationship that was shown with a p value> 0.05.
Pemanfaatan Google Classroom Sebagai Media Pembelajaran Di Masa Pandemi Covid-19
Authors: Atikah Rini - , Prihatin Rani Titik , Hernayati Herni , Misbah Jajang
Published: May 2021

Abstrak – Penelitian ini menekankan pada pemanfaatan pembelajaran dengan menggunakan google classroom memiliki dampak yang positif dapat dilihat dari hasil belajar siswa yang semakin meningkat setiap harinya melalui tugas dan kuis. Persepsi siswa mengenai mata pelajaran yang dilakukan melalui daring menggunakan aplikasi Google classroom yaitu siswa merasa senang menggunakan Google classroom karena mudah dan guru/pendidik tidak memberatkan dengan memberikan banyak tugas, Google classroom bersifat fleksibel yaitu mudah di akses dimana saja dan kapan saja, terkendala akses internet dari tidak adanya jaringan data maupun smartphone yang digunakan sebagai pendukung semua siswa untuk pelaksanaan pembelajaran e-learning. Adapun metode penelitian yang digunakan adalah Metode studi literatur adalah serangkaian kegiatan yang berkenaan dengan metode pengumpulan data pustaka, membaca dan mencatat, serta mengelolah bahan penelitian Kata kunci: google classroom, pemanfaatan, media pembelajaran daring.
GREEN AND ENERGY EFFICIENT SOLUTIONS IN THE CONSTRUCTION INDUSTRY
Authors: f Švajlenka Joze , Kozlovská Mária , Spišáková Marcela
Published: May 2021

Ecology and environmental protection have been discussed more and more in the last few years. This trend was also affected by the construction and architecture department. Concepts such as green building, environmentally friendly materials, alternative energy sources and energy-efficient construction systems of buildings are depressed. All of this comes under the name "Green Buildings". Wood-based construction and material solutions are a response to these trends. Investors and users are gradually starting to think more environmentally friendly and therefore many times also make decisions for wood-based constructions. There are several systems that fall into the category of so-called crushed buildings. The aim of this work is to provide a look at the "greener" options offered in the construction industry with an emphasis on their energy and thermal characteristics. The subject of the research was selected structural parts of timber-based buildings applied to model constructions by means of which selected thermal-technical characteristics were evaluated. This work points out the differences between the compared design variants of wooden buildings in terms of their ability to effectively save energy sources for heating inserted during the operation of wood-based buildings.
CULTURAL TOURISM IN ROMANIA – A GENERAL OUTLINE OF THE CONCEPTUAL FRAMEWORK
Authors: Mitrică Bianca , Mocanu Irena , Grigorescu Ines , Dumitraşcu Monica
Published: May 2021

At the international and national level there is a strong connection between culture and tourism, tourism representing an important factor of the economic development by capitalizing the tourist potential of the cultural elements. Romania has a rich and valuable heritage potential with tourist attractions included on the map of European cultural routes. The challenge for Romania is the weak promotion of the cultural tourism due to the difficulties in developing a better infrastructure for a high accessibility to cultural attractions. The literature offers a wide range of definitions of cultural tourism which emphasize the complexity of this phenomenon. The Romanian literature lacks a thorough documentation on the cultural tourism as a whole, most of studies being concentrated on general approaches i.e. introduction to cultural tourism, analysis of the cultural tourism trends, sustainable development and perspectives, Romanian heritage, promoting strategies. Some papers are concentrated on specific areas of Romania such as Transylvania, with the medieval cities, fortresses and castles, Bucovina, with the painted monasteries and traditional artefacts, Maramureş, with the rural tourism and cultural heritage, as well as Black Sea Coast and Danube Delta. Other papers are related to cultural attractions like museums, orchestra performances, restaurants, hotels in some developed areas, and to traditional or religious rituals, popular art or folklore events in some less developed areas and how they could promote and revive the Romanian tourism or other areas with a low or medium level of capitalization of cultural attractions. Within this broader context, the paper aims to review and discuss the definitions and concepts of cultural tourism in Romania and identify the main types of cultural tourism practiced and addressed by the literature.
TEMPORARY CULTURAL FACILITIES AS AN ELEMENT OF REBUILDING STRATEGIES FOR CITIES AFFECTED BY EARTHQUAKES
Authors: Rogulska Aleksandra
Published: May 2021

The Apennine Peninsula is one of the most densely-populated and most seismically active regions of Europe, possessing a wealth of cultural heritage. Historical cities and buildings are a part of this heritage. The earthquake damage prevention programme implemented in Italy does not cover existing buildings, and reconstruction plans for damaged cities, because of the threat's specificity, are always prepared after a disaster. In the case of heritage buildings, particularly those of super-local significance, decisions involving a complete reconstruction of their original form are typically made, erasing all traces of the tragedy. Reconstruction can take years, during which society is left without cultural facilities that are key to good morale. Opportunities provided by the phase between a disaster and restoring the buildings are too often underappreciated, while the time spent making the decision what and how to rebuild should be spent on action. Strategies involving temporary buildings allow to prevent the disappearance of public functions during the period preceding the reconstruction of major cultural facilities. These buildings should be designed as resilient, assuming a capacity to adapt to changing conditions and upholding or rapidly returning to a functional state after a disaster. They can enable the time between the disaster and making the decision about reconstruction to be used to identify and test new relations in the surroundings created through the loss of a section of substance. They provoke a debate about what must be rebuilt and at what cost, they facilitate understanding of the goals of a planned reconstruction. But most importantly, they sustain the genius loci, in order to affect the city's reconstruction process in its social, psychological and economic aspects. By analysing temporary cultural facilities built in Italian cities damaged by earthquakes, the study discusses methods of building temporary public buildings and features an attempt at assessing interventions that precede reconstruction. Based on the experiences of the city of L'Aquila severely damaged in 2009 and drawing conclusions from mistakes made during the implementation of pre-reconstruction strategies in the town, the author developed a proposal of a temporary intervention for the Basilica of St. Benedict of Nursia, which collapsed on the 30th of October 2016 as an effect of the Amatrice-Visso-Norcia seismic sequence. The proposal stresses the preservation of the previous function of the complex at its original site. This is meant to maintain the occupancy of Norcia's centre by the Benedictine monks, whose tradition is strongly linked with the city and makes it a major pilgrimage destination that is important to Christians.
Multicriteria decision making based optimum virtual machine selection technique for smart cloud environment
Authors: Singh Raman , Singh Maninder , Garg Sheetal , Perl Ivan , Kalyonova Olga , Penskoi Aleksandr
Published: May 2021

In the popular field of cloud computing, millions of job requests arrive at the data centre for execution. The job of the data centre is to optimally allocate virtual machines (VMs) to these job requests in order to use resources efficiently. In the future smart cities, huge amount of job requests and data will be generated by the Internet of Things (IoT) devices which will influence the designing of optimum resource management of smart cloud environments. The present paper analyses the performance efficiency of the data centre with and without job request consolidation. First, the work load performance of the data centre was analysed without job request consolidation, exhibiting that the job requests to VM assignment was highly imbalanced, and only 5% of VMs were running with a load factor of more than 70%. Then, the technique for order of preference by similarity to ideal solution-based VM selection algorithm was applied, which was able to select the best VM using parameters such as the provisioned or available central processing unit capacity, provisioned or available memory capacity, and state of machine (running, hibernated, or available). The Bitbrains dataset consisting of 1750 VMs was used to analyse the performance of the proposed methodology. The analysis concluded that the proposed methodology was capable of serving all job requests using less than 24% VMs with improved load efficiency. The fewer number of VMs with an improved load factor guarantees energy saving and an increase in the overall running efficiency of the smart data centre environment.
Smart contracts for automated control system in Blockchain based smart cities
Authors: Pradhan Nihar Ranjan , Singh Akhilendra Pratap
Published: May 2021

Nowadays, smart applications are increasing day by day to improve the standard of living in smart cities. A modern-day smart city is characterized by the presence of numerous smart Information and Communication Technology (ICT)-enabled services such as automated healthcare, automatic building monitoring, home automation, smart parking, traffic management, data security, among others. Such cities employ multitudes of Internet of Things (IoT) devices to collect and share data between trusted users by means of a centralized intermediary for monitoring and control of the myriad automatic activities. However, a centralized intermediary is plagued by issues such as single point of failure, risk of data loss, man-in-the-middle attack, and so forth. Blockchain-based smart contracts for automated control in smart cities provide a decentralized and secure alternative. In this paper, an Ethereum based system design for decentralized applications in smart cities has been proposed that enables systems to share data without an intermediary between trusted and non-trusted stakeholders using Ethereum based self-executing contracts. Such contracts allow automated multi-step workflows for smart applications. Two use cases, have been considered namely smart healthcare and smart building monitoring, as proof of stake of the proposed Ethereum based contract. The performance of the proposed scheme for these use cases has been presented with Keccack 256 transaction hash, the total number of transactions, gas consumed by each contract. Such an attempt is a worthwhile addition to state of the art as evident from the results presented herein. The modeling simulation and analysis of hashing power shows that for hashing power greater than 55% the probability of double spending attack reaches to 42% maximum. So it is concluded that the probability of double spending increases with the increase of transaction values.
Reduced IL-37 gene expression and CD8 T lymphocytes in patients with metastatic breast cancer
Authors: Farahani Najmeh , Mohagheghi Fathollah , Mosayebi Ghasem , Ghazavi Ali , Ganji Ali
Published: May 2021

BACKGROUND: The exact immunopathological mechanisms in the progression of breast cancer are not clearly understood, but various factors including CD8 T lymphocytes have lethal properties on tumor cells. On the other hand, interleukin-37 (IL-37), as a new member of the IL-1 family, is an anti-inflammatory cytokine. The exact role of IL-37 in breast cancer has not yet been determined. OBJECTIVE: This study aimed to evaluate the CD8 T lymphocytes count and IL-37 gene expression in newly diagnosed breast cancer patients with and without metastasis. METHODS: In this study, blood samples from 36 metastatic and 36 non-metastatic breast cancer patients and 36 healthy individuals as control were collected. After RNA extraction and cDNA synthesis, the relative gene expression was performed using real-time PCR. Also, counting the CD8 T lymphocytes was done by flow cytometry technique. RESULTS: The results of this study showed that the gene expression of IL-37 in blood samples of metastatic and non-metastatic breast cancer patients was significantly lower than in healthy individuals (P < 0.05). The relative gene expression of the IL-37 in ER+/PR+/HER2+ patients with non-metastatic breast cancer had a significant increase compared to HER2+ patients (P < 0.05). Also, CD8 T lymphocytes count in the samples of patients including non-metastatic and metastatic breast cancer was significantly decreased compared to the healthy individuals (P < 0.05). CONCLUSIONS: Our findings provide evidence that IL-37 gene expression and CD8 T lymphocytes count, significantly decreased in non-metastatic and metastatic breast cancer. Considering the possible effects of IL-37 on TCD8 cells in tumor immune responses, more research will be done to benefit from the therapeutic effects of this cytokine in the future.
A comparison of the effects of static stretching and the fascial distortion model (FDM) on hamstring flexibility
Authors: Kim Ji Young , Kim Seong Yoel
Published: May 2021

BACKGROUND: Hamstring flexibility plays a significant role in physiotherapy. Various stretching studies have been conducted to increase hamstring flexibility, but the effects of the Fascial Distortion Model (FDM) on hamstring flexibility have not yet been investigated. Moreover, no studies have compared the effects of FDM and static stretching. OBJECTIVES: To investigate the effects of the FDM on hamstring flexibility compared with static stretching. METHODS: Thirthy healthy adults were divided into two groups: static stretching and FDM groups. Static stretching was performed to hamstring in the supine position. The FDM was performed using trigger band techniques that followed the hamstring in a longitudinal direction. Hamstring flexibility was measured using the active knee extension angle (KEA), passive straight leg raising (SLR), sit-and-reach (SR), and finger-floor distance (FFD) tests. A paired t-test and an independent t-test were performed to compare the hamstring flexibility measurements. RESULTS: Both groups showed significant differences (p< 0.05) in KEA, SLR, SR, and FFD before and after. However, no significant difference (p> 0.05) was found between the two groups. CONCLUSIONS: There was no difference in the effects of FDM and static stretching on hamstring flexibility.
Improved microsatellite instability detection in colorectal cancer patients by a combination of fourteen markers especially DNMT3a, DCD, and MT1X
Authors: Khaligh Ali , Fazeli Mohammad Sadegh , Mahmoodzadeh Habibollah , Mehrtash Amirhosein , Kompanian Setareh , Zeinali Sirous , Teimoori-Toolabi Ladan
Published: May 2021

BACKGROUND: Microsatellite instability (MSI) results from genetic and epigenetic changes. Studying Microsatellite instability can help in treatment and categorization of colorectal cancer (CRC) patients. OBJECTIVES: We aimed to investigate whether 14 genomic markers consisting of BAT-62, BAT-60, BAT-59a, BAT-56a, BAT-56b, DCD, RIOX, RNF, FOXP, ACVR, CASP2, HSP110, MT1X, and DNMT3a can increase the detection rate of MSI in CRC. METHODS: Samples were stratified by pentaplex panel (Promega) and 14 markers using multiplex PCR and fragment analysis. In MSI+ samples, to identify the pattern of BRAF V600E mutation and MLH1 promoter methylation, ARMS-scorpion, and Methylation-Specific High-Resolution Melting Curve analysis, were applied respectively. RESULTS: Totally, 35 MSI+ cases identified by 14 marker panel. Only 18 cases of them were detected by both panels which are pentaplex and 14 marker. On the other hand, 17 new MSI+ cases just were identified by 14 markers panel. The highest diagnostic value among 14 markers is related to three makers, namely DCD, MT1X, and DNMT3a. In MSI+ cases, the rate of MLH1 promoter methylation was insignificant, (P value = 0.3979) while the rate of observed BRAFV600E mutation was significantly higher (P value = 0.0002). CONCLUSION: Fourteen marker panel showed higher sensitivity in comparison with the pentaplex panel increasing the detection rate of MSI+ cases up to 1.94 fold. Three markers namely DNMT3a, DCD, and MT1X of 14 marker panel were the best among them showing excellent diagnostic value. A combination of these markers showed 100% sensitivity and specificity in the studied group. In contrary to the markers in the pentaplex panel, these markers had the ability to detect MSI without any bias for the clinicopathological features. These markers will help to identify more end-stage MSI+ tumors which are located distal colon.
Functional Connectivity Between the Posterior Default Mode Network and Parahippocampal Gyrus Is Disrupted in Older Adults with Subjective Cognitive Decline and Correlates with Subjective Memory Ability
Authors: Sharma Namita , Murari Geetanjali , Vandermorris Susan , Verhoeff Nicolaas Paul L.G. , Herrmann Nathan , Chen J. Jean , Mah Linda
Published: May 2021

Background: Subjective cognitive decline (SCD) is associated with increased risk of developing Alzheimer’s disease (AD). However, the underlying mechanisms for this association remain unclear. Neuroimaging studies suggest the earliest AD-related changes are large-scale network disruptions, beginning in the posterior default mode (pDMN) network. Objective: To examine the association between SCD and pDMN network connectivity with medial temporal lobe (MTL) regions using resting-state functional magnetic resonance imaging. Methods: Forty-nine participants with either SCD (n = 23, 12 females; mean age: 70.7 (5.5)) or who were cognitively unimpaired (CU; n = 26, 16 females, mean age: 71.42 (7.3)) completed the Memory Functioning Questionnaire, a measure of subjective memory, and underwent resting state functional MRI at 3 Tesla. Functional connectivity between the posterior cingulate cortex (PCC), as the key pDMN node, and MTL regions were compared between SCD and CU groups. Further, the association between pDMN-MTL connectivity and the Frequency of Forgetting subscale of the Memory Functioning Questionnaire was examined. Results: Connectivity between the PCC-MTL was observed in the CU group but was absent in SCD (t(47) = 2.69, p = 0.01). Across all participants, self-perception of frequency of forgetting, but not objective memory, was strongly correlated with connectivity between the PCC-left parahippocampal gyrus (r = 0.43, p = 0.002). Conclusion: These findings support the hypothesis that increased AD risk in SCD may be mediated by disrupted pDMN-parahippocampal connectivity. In addition, these findings suggest that frequency of forgetting may serve as a potential biomarker of SCD due to incipient AD.
Cerebral Blood Flow Predicts Conversion of Mild Cognitive Impairment into Alzheimer’s Disease and Cognitive Decline: An Arterial Spin Labeling Follow-up Study
Authors: Duan Wenna , Zhou Grace D. , Balachandrasekaran Arvind , Bhumkar Ashish B. , Boraste Paresh B. , Becker James T. , Kuller Lewis H. , Lopez Oscar L. , Gach H. Michael , Dai Weiying
Published: May 2021

Background: This is the first longitudinal study to assess regional cerebral blood flow (rCBF) changes during the progression from normal control (NC) through mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Objective: We aim to determine if perfusion MRI biomarkers, derived from our prior cross-sectional study, can predict the onset and cognitive decline of AD. Methods: Perfusion MRIs using arterial spin labeling (ASL) were acquired in 15 stable-NC, 14 NC-to-MCI, 16 stable-MCI, and 18 MCI/AD-to-AD participants from the Cardiovascular Health Study (CHS) cognition study. Group comparisons, predictions of AD conversion and time to conversion, and Modified Mini-Mental State Examination (3MSE) from rCBF were performed. Results: Compared to the stable-NC group: 1) the stable-MCI group exhibited rCBF decreases in the right temporoparietal (p = 0.00010) and right inferior frontal and insula (p = 0.0094) regions; and 2) the MCI/AD-to-AD group exhibited rCBF decreases in the bilateral temporoparietal regions (p = 0.00062 and 0.0035). Compared to the NC-to-MCI group, the stable-MCI group exhibited a rCBF decrease in the right hippocampus region (p = 0.0053). The baseline rCBF values in the posterior cingulate cortex (PCC) (p = 0.0043), bilateral superior medial frontal regions (BSMF) (p = 0.012), and left inferior frontal (p = 0.010) regions predicted the 3MSE scores for all the participants at follow-up. The baseline rCBF in the PCC and BSMF regions predicted the conversion and time to conversion from MCI to AD (p < 0.05; not significant after multiple corrections). Conclusion: We demonstrated the feasibility of ASL in detecting rCBF changes in the typical AD-affected regions and the predictive value of baseline rCBF on AD conversion and cognitive decline.
Altered Amyloid-β and Tau Proteins in Neural-Derived Plasma Exosomes of Type 2 Diabetes Patients with Orthostatic Hypotension
Authors: Zhang Jinbiao , Chi Haiyan , Wang Tong , Zhang Shukun , Shen Tengqun , Leng Bing , Sun Hairong , Li Zhenguang , Li Fang
Published: May 2021

Background: Emerging evidence suggests a role for orthostatic hypotension (OH) in contributing to the progression of Alzheimer’s disease (AD). The exosomes in the blood can reflect the pathological changes in the brain. Objective: To investigate whether neural-derived plasma exosomes pathogenic proteins of AD levels are associated with OH in diabetes mellitus (DM) patients. Methods: There were 274 subjects without dementia included in the study: 81 control participants (controls), 101 normotensive patients with DM without OH, and 92 patients with DM and neurogenic OH (DMOH). Neural-derived exosomal proteins were measured by ELISA kits for amyloid-β (Aβ) and tau. Results: The neural-derived exosome levels of Aβ42, total tau (T-tau), and tau phosphorylated at threonine 181 (P-T181-tau) in the DM with OH group were higher than those in the DM and control groups. Multivariable linear regression analysis showed that the presence of OH in patients with DM was associated with elevated exosomal Aβ42 (β= 0.172, p = 0.018), T-tau (β= 0.159, p = 0.030), and P-T181-tau (β= 0.220, p = 0.003) levels after adjustment for age, sex, APOE ɛ4, duration of type 2 diabetes, HbA1c, and cardiovascular risk factors. Furthermore, the levels of Aβ42, T-tau, and P-T181-tau in neural-derived exosomes were correlated with HIF-1α levels and the drop in mean cerebral blood flow velocity from the supine to upright position. Conclusion: The presence of OH in DM patients was independently associated with elevated the Aβ42, T-tau, and P-T181-tau levels in neural-derived plasma exosomes. Cerebral hypoperfusion from DM with OH are likely candidate mechanisms.
Dimensional and Discrete Emotional Reactivity in Alzheimer’s Disease: Film Clips as a Research Tool in Dementia
Authors: Fernández-Aguilar Luz , Lora Yaiza , Satorres Encarnación , Ros Laura , Melendez Juan C. , Latorre Jose Miguel
Published: May 2021

Background: No studies have been conducted to date on the dimensional and discrete classification of emotions to study the emotional reactivity of older adults with Alzheimer’s disease (AD). Additionally, the presentation of film clips with affective content is currently one of the most effective and widely used Mood Induction Procedures (MIPS). However, it has been scarcely used in AD patients. Objective: Based on the dimensional and discrete models of emotion, this study examines the emotional reactivity of older adults with AD, using a popular set of film clips to induce emotions. Methods: We compared the responses of older adults aged over 65-years with mild to moderate AD (n = 15) and a healthy comparison group (n = 17) to six target emotions: disgust, fear, anger, sadness, amusement, and tenderness. Results: The results showed significant differences in the reactivity of fear, anger, and sadness between AD patients and healthy comparison group. However, the responses of the two groups to positive film clips were similar. Only in the amusement clip did the AD participants show a higher intensity response. Conclusion: These findings suggest that the characteristic loss of cognitive abilities in AD is related to a reduction in the ability to react to emotional stimuli, especially negative ones. However, these abilities seem to be preserved when it comes to positive emotions. Future research is necessary to investigate whether the positivity effect is present in AD patients.
Insulin Resistance as a Common Link Between Current Alzheimer’s Disease Hypotheses
Authors: Alves Suélen Santos , Silva-Junior Rui Milton Patrício da , Servilha-Menezes Gabriel , Homolak Jan , Šalković-Petrišić Melita , Garcia-Cairasco Norberto
Published: May 2021

Almost 115 years ago, Alois Alzheimer described Alzheimer’s disease (AD) for the first time. Since then, many hypotheses have been proposed. However, AD remains a severe health public problem. The current medical approaches for AD are limited to symptomatic interventions and the complexity of this disease has led to a failure rate of approximately 99.6%in AD clinical trials. In fact, no new drug has been approved for AD treatment since 2003. These failures indicate that we are failing in mimicking this disease in experimental models. Although most studies have focused on the amyloid cascade hypothesis of AD, the literature has made clear that AD is rather a multifactorial disorder. Therefore, the persistence in a single theory has resulted in lost opportunities. In this review, we aim to present the striking points of the long scientific path followed since the description of the first AD case and the main AD hypotheses discussed over the last decades. We also propose insulin resistance as a common link between many other hypotheses.
Moment analysis in collision-induced absorption: Determination of a single parameter empirical model for the induced dipole moment of He-Ar gas mixtures
Authors: El-Kader M.S.A. , Maroulis G.
Published: May 2021

We present a method for the construction of a one-adjustable-parameter empirical model for the induced dipole moment. The method is based on classical physics principles and relies on the first three spectral moments of the collision-induced absorption spectra at various temperatures and new interaction potentials. In this work it is applied to the spectra of He-Ar mixtures. Our values are in good agreement with the available ab initio data. The profiles calculated with these models at various temperatures are in excellent agreement with experiment.
Fatigue damage risk assessment of airport concrete runway based on intelligent algorithm
Authors: Shuai Fu , Kai Sheng , Qingmin Si , Xinyao Guo , Feiyin Wang
Published: May 2021

Fatigue failure issues of runway at airports have become one of core tasks in airport safety management. How to recognize fatigue failure risk factors of concrete runways at airports and implement a quantitative assessment on failure risks of runways is a key topic that is studied in the industrial circle and academic circle at present. For this reason, an integral analysis on internal and external causes of fatigue failure of runways was carried out, which recognized and extracted 18 risk factors. Evaluation values of quantitative risk factors were calculated through a threshold method and evaluation values of qualitative factors were determined by expert scoring. Subsequently, weights of all risk factors were given by G1 method. Finally, the comprehensive risk evaluation value of concrete runways was gained through layer-by-layer coupling. A case study was carried out in the A airport. Results show that the calculated comprehensive risk evaluation value of fatigue failure of concrete runways at airports by the proposed method is basically consistent with engineering objective practical value. The proposed method is expected to be applicable in other airports. The comprehensive risk evaluation value of the concrete runway failure at A airport is 0.49, indicating certain risks of fatigue failure. It is necessary to adopt engineering and management measures according to risk factors with large evaluation values to control the fatigue failure risks. This study concludes that the proposed fatigue failure risk index system of concrete runway of airports is scientific and effective. Moreover, the proposed risk evaluation method is feasible and it provides a new idea and method to fatigue failure risk evaluation of concrete runways at airports.
Psychological analysis of classroom learning based on face recognition and neural network
Authors: Sun Feifei
Published: May 2021

With the rapid development of deep learning and parallel computing, deep learning neural network based on big data has been applied to the field of facial nerve recognition. This innovative operation has attracted extensive attention of scholars. The reason why the application of neural network is realized lies in deep learning, which can reduce the error and change the weight by means of back propagation and error optimization, so as to extract more key points and features. In spite of this, data collection and key points extraction is still a very complex problem. This paper mainly aims at the above problems, studies the way of deep learning and information extraction and its internal structure, and optimizes its application to classroom learning, so as to provide effective help for the realization of distance education.
Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic
Authors: Xu Honglei , Wang Linhuan
Published: May 2021

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.
Dynamic control analysis of charging and discharging power for electric vehicles with adaptive optimal fuzzy control
Authors: Meng Fanzi , Zhang Yu
Published: May 2021

Regarding the increasingly severe energy crisis and environmental issues, a dynamic control of the charging and discharging of electric vehicles into the grid that is universally adapted to optimal control is proposed in this study. When the charging control system is based on the load function of the current distribution network, the electric vehicles connected to the charging station are charged and deployed, and the best fuzzy control is adopted to calculate the electric power to be transmitted to each charging hub, so as to improve the load characteristics of the regional grid to reach the grid The highest efficiency of use. Finally, after repeated trials and studies, the orderly charging and deployment system when meeting the charging requirements of electric vehicles, the load of electric vehicles can exert its flexibility.
A multi-level fuzzy comprehensive assessment for supply chain risks
Authors: Wang Leyan
Published: May 2021

Potential supply chain risks are one of the hidden dangers that may undermine the reliable and stable operation of enterprises. Due to the practicality and complexity of supply chain risk management, the field has attracted wide attention from researchers. The urgent problems of supply chain management at present include how to help enterprises analyze and identify supply chain risk factors, predict and control the potential risks, and provide the corresponding preventive measures for various risks. There are many assessment methods in the research process of supply chain risks. In this paper, a multi-level fuzzy comprehensive assessment method is adopted. Based on the current risk status of the traffic enterprises in our country, an attempt is made to apply the multi-level fuzzy comprehensive assessment method to risk assessment. The main risk factors faced by traffic enterprises in the supply chain are analyzed to obtain the assessment results, which can provide ideas for further research in the future.
Autonomous driving of vehicles based on artificial intelligence
Authors: Gao Xianping , Bian Xueliang
Published: May 2021

With the fast development, Internet technology has become a game-changer to the automotive industry. The advances and general applications of high-precision maps make it possible for accurate real-time positioning of vehicles. Meanwhile, the extensive applications of intelligent driving technology make it easier and more intelligent to drive vehicles. This paper reviewed the application of artificial intelligence (AI) in the field of autonomous driving comprehensively and explored the innovative studies of other unmanned motion systems at the same time. Firstly, the hardware architecture of the autonomous driving system is introduced, including five modules as follows: sensing, autonomous driving computer, power supply, signal communication, execution and braking. In addition, General Motors autonomous vehicle is used as an example to introduce its differences from the traditional vehicles in the hardware part. Subsequently, the autonomous driving software is divided into four modules according to functions: positioning, sensing, planning, and control, and the innovative application of artificial intelligence algorithms is introduced. Finally, this paper expands from autonomous driving technology and puts forward an innovative research idea for the intelligent unmanned system.
A deep metric learning approach for weakly supervised loan default prediction1
Authors: Zhuang Kai , Wu Sen , Gao Xiaonan
Published: May 2021

To deal with the systematic risk of financial institutions and the rapid increasing of loan applications, it is becoming extremely important to automatically predict the default probability of a loan. However, this task is non-trivial due to the insufficient default samples, hard decision boundaries and numerous heterogeneous features. To the best of our knowledge, existing related researches fail in handling these three difficulties simultaneously. In this paper, we propose a weakly supervised loan default prediction model WEAKLOAN that systematically solves all these challenges based on deep metric learning. WEAKLOAN is composed of three key modules which are used for encoding loan features, learning evaluation metrics and calculating default risk scores. By doing so, WEAKLOAN can not only extract the features of a loan itself, but also model the hidden relationships in loan pairs. Extensive experiments on real-life datasets show that WEAKLOAN significantly outperforms all compared baselines even though the default loans for training are limited.
Optimization of security check efficiency in subway station based on Anylogic: A case study of Nanchang Metro
Authors: Wan Ming , Chen Zhifang , Guo Junhua , Wan Ping
Published: May 2021

Rational and orderly passenger organization in subway station can improve travel efficiency and safety. How to improve the efficiency of security check, which has a significant impact on the passenger organization, to reduce passengers staying time in the terminal level has the potential to improve service satisfaction. The Weidong Station of Line 1 of Nanchang Metro was selected as the research object. Anylogic software was used to simulate the process of arrival, ticket purchase, security check, gate-crossing machine etc. The results indicate that the dynamic adjustment of security checkpoints and fast passage for passengers without luggage can improve the security efficiency and relieve the congestion in the station hall.
The impact of high-speed rail operations: A case study in Shanghai-Kunming line
Authors: Zhang Cheng , Liu Min , Wan Ping , Guo Junhua
Published: May 2021

High-speed railway is an indispensable part of the transportation system. The construction and opening of high-speed railway will contribute to the economic development of cities along the route, but it will also have an adverse impact on peripheral areas. The research of the article is mainly carried out from an empirical point of view, using comparative analysis, regression analysis and other methods to measure and quantitatively describe the impact of high-speed railways on urban and regional spatial development. The study found that the operation of the Shanghai-Kunming high-speed rail had a siphon effect on cities along the Jiangxi Province, leading to unbalanced regional development.
The impact of subway operation on urban traffic: A GRA-BNs based study
Authors: Yan Lixin , Zeng Tao , Xiong Yubing , Li Zhenyun , Liu Qingmei
Published: May 2021

With the development of urbanization, urban traffic has exposed many problems. To study the subway’s influence on urban traffic, this paper collects data on traffic indicators in Nanchang from 2008 to 2018. The research is carried out from three aspects: traffic accessibility, green traffic, and traffic security. First, Grey Relational Analysis is used to select 18 traffic indicators correlated with the subway from 22 traffic indicators. Second, the data is discretized and learned based on Bayesian Networks to construct the structural network of the subway’s influence. Third, to verify the reliability of using GRA and the effectiveness of Bayesian Networks (GRA-BNs), Bayesian Networks with full indicators analysis and other four algorithms (Naive Bayes, Random Decision Forest, Logistic and regression) are employed for comparison. Moreover, the receiver operating characteristic (ROC) area, true positive (TP) rate, false positive (FP) rate, precision, recall, F-measure, and accuracy are utilized for comparing each situation. The result shows that GRA-BNs is the most effective model to study the impact of the subway’s operation on urban traffic. Then, the dependence relations between the subway and each index are analyzed by the conditional probability tables (CPTs). Finally, according to the analysis, some suggestions are put forward.
Decision-making for location of manufacturing bases in an uncertain demand situation
Authors: Jianzhu Sun , Qingshan Zhang , Yinyun Yu
Published: May 2021

Multi-site selection is a hot research issue for equipment manufacturing enterprises. With the development of smart industry, equipment manufacturing enterprises have entered the era of personalized and small batch manufacturing. Enterprises want to better meet customer needs and win competition, they must carry out scientific factory planning and site selection, so as to ensure quick response to the market. Based on this, this paper proposes a two-stage location selection model. Firstly, the method uses fuzzy numbers to express the demand size of demand points. Secondly, the distance factor is used as a criterion to select the candidate manufacturing bases with sufficient available resources. Next, the location model of enterprise manufacturing base is established which the goal of maximizing service efficiency and the constraints of time, cost and demand. Finally, a random numerical example is used to simulate the model, and lingo is used to solve it.
Pricing and composition of multiple vertically differentiated bundles considering demand uncertainty1
Authors: Ya-Na Wang , Guo-Hua Zhou
Published: May 2021

The aim of this paper is to investigate a profit-maximization firm how to determine the composition and prices of multiple bundles. Bundles are sets of components that must meet some technical constraints; furthermore, customers differ in their quality valuations and choose the bundle that maximizes their utility. A mixed integer non-linear program is proposed to solve this problem. First, a two-step approach is employed to obtain the firm’s optimal decision. The result indicates that when the firm faces deterministic demand, the optimal set of bundles it offers is independent of the distribution of customer valuations and does not contain any dominated bundle. In addition, dominated components cannot be used to construct the optimal bundles. Second, the impact of demand uncertainty on the firm’s performance is explored. The results suggest that disregarding the demand risk may result in broader assortment and suboptimal prices. Finally, numerical experiments and sensitive analysis are conducted to provide managerial insights for the pricing and composition of multiple bundles.
An interval type-2 hesitant fuzzy best-worst method
Authors: Norouzi Ashraf , hajiagha Hossein Razavi
Published: May 2021

Multi criteria decision-making problems are usually encounter implicit, vague and uncertain data. Interval type-2 fuzzy sets (IT2FS) are widely used to develop various MCDM techniques especially for cases with uncertain linguistic approximation. However, there are few researches that extend IT2FS-based MCDM techniques into qualitative and group decision-making environment. The present study aims to adopt a combination of hesitant and interval type-2 fuzzy sets to develop an extension of Best-Worst method (BWM). The proposed approach provides a flexible and convenient way to depict the experts’ hesitant opinions especially in group decision-making context through a straightforward procedure. The proposed approach is called IT2HF-BWM. Some numerical case studies from literature have been used to provide illustrations about the feasibility and effectiveness of our proposed approach. Besides, a comparative analysis with an interval type-2 fuzzy AHP is carried out to evaluate the results of our proposed approach. In each case, the consistency ratio was calculated to determine the reliability of results. The findings imply that the proposed approach not only provides acceptable results but also outperforms the traditional BWM and its type-1 fuzzy extension.
Information structures in a fuzzy β-covering information system
Authors: Liu Rui-Lin , Yang Hai-Long , Zhang Li-Juan
Published: May 2021

This paper studies information structures in a fuzzy β-covering information system. We introduce the concepts of a fuzzy β-covering information system and homomorphism between them, and investigate related properties. The concept of information structure of a fuzzy β-covering information system is given. We discuss the relationships between information structures from the view of dependence and separation. Then granularity measures for a fuzzy β-covering information system are studied. Finally, we discuss invariance of fuzzy β-covering information systems under homomorphism and illustrate its application on data compression.