bluuebunny/crossref_metadata_2025 huggingface dataset:
Umysł podczas snu z perspektywy funkcjonalnego neuroobrazowania
Authors: Markiewicz Piotr
Published: March 2021

Celem artykułu jest krytyczna analiza wybranych wyników neuroobrazowania procesów snu w kontekście specyfiki umysłu śniącego. Kombinacja danych hemodynamicznych i magnetycznych oraz danych fenomenologicznych i kognitywnych dopuszcza wyróżnienie czterech specyficznych typów umysłu podczas snu. Dzięki temu ogólna wizja mózgu/umysłu podczas snu, typowo sprowadzana do dystynkcji NREM/REM, jest bardziej adekwatna. Dodatkowo, kognitywna interpretacja danych neuroobrazowych pozwala na ustalenie możliwych funkcji adaptacyjnych umysłu podczas snu.
Rola archetypów muzycznych w epoce hellenizmu
Authors: Nowak Andrzej T.
Published: March 2021

Autor artykułu przedstawia w syntetycznym skrócie zasady kształtowania się dwóch podstawowych form wypowiedzi literacko-muzycznej w antycznym świecie cywilizacji greckiej i hellenistycznej. Pokrótce omawia sposoby przejawiania się muzyki, traktowanej jako ważny element obiegu kulturowego w ówczesnej rzeczywistości. Archetypiczne wzorce hymnu i peanu - podstawowych form literacko-muzycznych kultury greckiej - zostały omówione według charakterystycznych cech oraz poparte konkretnymi przykładami literackimi. Wskazano, że synkretyzm form literacko-muzycznych, charakterystyczny dla antycznej kultury śródziemnomorskiej, był powiązany z elementami kultu religijnego (zwłaszcza misteriami). Wymiar religijny stanowił ważne uzupełnienie praktycystycznego sposobu traktowania muzyki w świecie cywilizacji antycznej, niekiedy wysuwające się na pierwszy plan. Szczególnie widoczne było to w przypadku wczesnochrześcijańskiej twórczości hymnograficznej, opartej na syntezie tradycji hellenistyczno-rzymskiej i judeochrześcijańskiej.
Nietzsche a faszyzm
Authors: Pieniążek Paweł
Published: March 2021

Moim celem jest przedstawienie nazistowskich interpretacji myśli Nietzschego oraz interpretacji Lukacsa – oskarżającej ją o protofaszyzm. Następnie omawiam znane interpretacje z lat czterdziestych i pięćdziesiątych ubiegłego wieku, które broiły Nietzschego, choć wskazywały na pewne dwuznaczności jego myśli. Na końcu przedstawiam własne stanowisko, wskazując na bezpodstawność oskarżeń wobec Nietzschego, którego utopijny projekt był oparty na elitystycznej idei aktywności kulturotwórczej.
Psychoanalityczne i egzystencjalne problemy twórczości
Authors: Maj Filip
Published: March 2021

W tekście podjęty zotał problem twórczości i osobowości artysty z perspektywy niektórych XX-wiecznych teorii, m.in. psychoanalizy, psychologii analitycznej i egzystencjalnej. Twórczość może być formą rozwiązania konfliktu i przemiany energii seksualnej (S. Freud), formą obrony psychologicznej i odbudowy swojego ,,ja” (O. Rank), czynnością harmonizowania swojego ,,cienia” ze sobą i wyrazem archetypu (C. G. Jung), sposobem przekroczenia swojego typu psychologicznego i rozwoju osobowości (K. Dąbrowski), a także mistycznym połączeniem przedmiotu i podmiotu oraz egzystencjalną psychosyntezą (H. Elzenberg).
A need for Metaphysics of Respect for Humans
Authors: Omielczenko Nikolaj
Published: March 2021

Niniejsza praca poświęcona jest pozycji człowieka we współczesnym świecie. Autor wychodzi do przedstawienia status quo Milana Kundery. Następnie omawia takie zagadnienia jak ,,wolność jest czynnikiem bezpieczeństwa”, ,,własność i wolność”. Jego zdaniem wolność i bezpieczeństwo nie mogą być przeciwstawiane. Pewne bezpieczeństwo nie może być rozumiane z perspektywy praw człowieka i wolności. Uważa on, że wolność jest atrybutem istoty ludzkiej, a humanizm entelechią ludzkiej natury. Porównuje liberalne hasło ,,własność jest wolnością” z definicją ekonomiczną ,,płaca jest tożsama z własnością prywatną”.

Autor analizuje Fabrykę os Iaina Banksa oraz Pachnidło Patricka Suskinda. Uważa, że obydwie powieści opowiadają o braku miłości, a cieszą się taką popularnością, ponieważ niewielu ludzi potrafi kochać, ale każdy chce wiedzieć, co to znaczy kochać i być kochanym. Powieści na swój sposób zaświadczają, że bez miłości zanika osobowość, że to miłość czyni człowieka ludzkim.

Autor utrzymuje, że pojmowanie człowieka jako istoty stwarzającej sprawia, że czynienie ostatecznych sądów o nim jest wysoce problematyczne. Poza czysto teoretycznymi ujęciami, morderstwo, samobójtwo, kara śmierci, dożywocie, eutanazja, wojna, ludobójstwo oraz inne metody mogą się do nich zaliczać. Takie działania ,,kategoryczne” są na porządku dziennym we współczesnym świecie. Z tego powodu zasadniczo eleganckie, spekulatywne usprawiedliwienie stoi za brutalną przemocą fizyczną. Jednocześnie autor proponuje metafizyczny argument przeciwko karze śmierci. Jego zdaniem ostateczne wyroki na istotach ludzkich są niedopuszczalne.
Szczęście jako (najwyższy) sposób bycia człowieka (Arystoteles, Etyka nikomachejska 1098 a 7-18)
Authors: Matuszak Małgorzata
Published: March 2021

Według Arystotelesa szczęście jest osiągalne, bo jest dziełem człowieka; takim działaniem, którego ,,po co” osiągane jest równocześnie z nim samym: wtedy, gdy działanie jest właśnie dokonywane. Odpowiedź natomiast na pytanie, jakie to jest działanie, związane jest z ontologią życia człowieka, ze sposobem, w jaki winno być dokonywane, aby było sobą. I by sobą był człowiek. Związane jest zatem z odpowiedzią na pytanie, kim jest człowiek i jakie jest jego miejsce pośród innych bytów, a przede wszystkim jakie jest jego odniesienie z jednej strony do innych istot żyjących – roślin i zwierząt, z drugiej – do Boga. Usytuowanie człowieka w pewnego rodzaju ,,pomiędzy” określa sposób jego życia, a więc także działanie, które ów sposób bycia (życia) najlepiej charakteryzuje. Problematyka szczęścia człowieka najlepiej zaś owo ,,pomiędzy” wyraża i naznaczona jest jego ambiwalencją, dźwiga jej brzemię.
The green tea polyphenol EGCG is differentially associated with telomeric regulation in normal human fibroblasts versus cancer cells
Authors: Pointner Angelika , Mölzer Christine , Magnet Ulrich , Zappe Katja , Hippe Berit , Tosevska Anela , Tomeva Elena , Dum Elisabeth , Gessner Diana , Lilja Stephanie , Switzeny Olivier Jerome , Krammer Ulrike , Haslberger Alexander
Published: March 2021

Introduction: Topical investigations have demonstrated that oxidative stress and inflammation play key roles in biological aging and determine incidence and course of age-related diseases. Lifestyle and environmental factors hugely impact epigenetic regulation and DNA stability with telomere attrition and epigenetic instability providing a potential record of the cumulative burden of endogenous and exogenous oxidative noxae. Certain physiologically active plant components exhibit antioxidative activities affecting epigenetic regulation of inflammation response and DNA repair.Methods: Against this background, the present study investigated green tea polyphenol epigallocatechin gallate (EGCG) in the context of telomere regulation in Caco-2 colorectal adenocarcinoma cells vs. ES-1 primary skin fibroblasts. Cell lines were treated with 20 and 200 µM EGCG for 36, 72 and 144 hours, respectively. Telomerase activity, relative telomere length as well as methylation status of hTERT and c-Myc from different culture conditions were assessed. Malondialdehyde (MDA) served as a surrogate marker of potential pro-oxidative effects of EGCG in a physiologically relevant tissue model.Results: EGCG incubation was associated with telomere shortening and decreased telomerase activity in Caco-2 cells, and relatively longer telomeres along with increased methylation of six 5'—C—phosphate—G—3' (CpG) sites in the promoter region of human Telomerase Reverse Transcriptase (hTERT) in fibroblasts. At low concentrations, EGCG significantly decreased oxidative damage to lipids in Caco-2 cells and attenuated H2O2 induced oxidation at higher concentrations.Conclusion: These results suggest differential EGCG-mediated telomeric modulation in cancer vs. primary cells and a specific antioxidant activity of EGCG against oxidative damage to lipids in abnormal cells.Keywords: Caco-2, epigallocatechin gallate, telomeres, hTERT, DNA methylation, telomerase, oxidative stress, malondialdehyde
Shared learning activity labels across heterogeneous datasets
Authors: Ye Juan
Published: March 2021

Nowadays, the advancement of sensing and communication technologies has led to the possibility of collecting a large amount of sensor data, however, to build a reliable computational model and accurately recognise human activities we still need the annotations on sensor data. Acquiring high-quality, detailed, continuous annotations is a challenging task. In this paper, we explore the solution space on sharing annotated activities across different datasets in order to enhance the recognition accuracies. The main challenge is to resolve heterogeneity in feature and activity space between datasets; that is, each dataset can have a different number of sensors in heterogeneous sensing technologies and deployed in diverse environments and record various activities on different users. To address the challenge, we have designed and developed sharing data and sharing classifiers algorithms that feature the knowledge model to enable computationally-efficient feature space remapping and uncertainty reasoning to enable effective classifier fusion. We have validated the algorithms on three third-party real-world datasets and demonstrated their effectiveness in recognising activities only with annotations from as little as 0.1% of each dataset.
Ontologies for information entities: State of the art and open challenges
Authors: Sanfilippo Emilio M.
Published: March 2021

Information entities are used in ontologies to represent engineering technical specifications, health records, pictures or librarian data about, e.g., narrative fictions, among others. The literature in applied ontology lacks a comparison of the state of the art, and foundational questions on the nature of information entities remain open for research. The purpose of the paper is twofold. First, to compare existing ontologies with both each other and theories proposed in philosophy, semiotics, librarianship, and literary studies in order to understand how the ontologies conceive and model information entities. Second, to discuss some open research challenges that can lead to principled approaches for the treatment of information entities, possibly by getting into account the variety of information entity types found in the literature.
Development of biliary stent applying the antibacterial activity of silver: A literature review
Authors: Yamabe Akane , Irisawa Atsushi , Kunogi Yasuhito , Kashima Ken , Nagashima Kazunori , Minaguchi Takahito , Yamamiya Akira , Izawa Naoya , Takimoto Yoichi , Hoshi Koki , Nonaka Lisa , Masuda Michiaki , Tominaga Keiichi , Goda Kenichi , Iijima Makoto
Published: March 2021

BACKGROUND: Endoscopic transpapillary stenting is commonly performed in patients with obstructive jaundice caused by a biliary stricture. Although the plastic stent (PS) is widely used for biliary drainage because of the low-cost and easy procedure, patency is short after placement in the bile duct because of the small diameter. Dysfunction of PS is primarily caused by biliary sludge that forms as a result of bacterial adhesion and subsequent biofilm formation on the inner surface of the stent. It is well known that silver ions have excellent antibacterial activity against a wide range of microorganisms. OBJECTIVE: This review provides an overview and perspective of the significance of silver-coated biliary stents. METHODS: We collected literature regarding silver-coated biliary stents, reviewed the current research/development status and discussed their possible usefulness. RESULTS: To date, several in vivo/vitro studies evaluated the patency of silver-blended or silver-coated biliary stents. These studies suggested that the silver coating on a PS was likely to prolong the patency period. CONCLUSION: The development of biliary stents using silver is expected to prolong stent patency and prevent frequent stent replacement.
Photochemical stability of warfarin potassium in powdered pharmaceutical tablets
Authors: Horiguchi-Babamoto Emi , Otsuka Makoto
Published: March 2021

BACKGROUND: Warfarin potassium (Wf) commercial tablets originally formulated for adults are ground before administration to pediatric patients and elderly patients with dysphagia. OBJECTIVE: The present study investigated the effect of tablet grinding on the photostability of four types of commercial Wf tablets and predicted the photostability of the tablet powders by chemometric analysis. METHODS: The photodegradation of Wf content was evaluated by reversed-phase column high-performance liquid chromatography with ultraviolet (HPLC-UV). RESULTS: The bulk Wf powder was relatively photostable, whereas ground Wf tablets underwent substantial photodegradation. The photostability of the ground powders of a brand-name Wf commercial tablet and three generic Wf commercial tablets was quantitatively assessed and compared. In certain cases, the Wf in all the three ground generic tablets was less photostable than in the ground brand-name tablets. After 28 days of light irradiation, the Wf content decreased to 69.79% in the brand-name tablets, while it was 31.90% in some generic tablets. To clarify the factors influencing the relative photostability in various Wf formulations, we analyzed the intermolecular interactions between the active ingredient and the excipients by partial least-squares regression analysis based on photostability screening for each additive. CONCLUSION: The results suggested that the additives light anhydrous silicic acid and povidone adversely affect the stability of Wf tablets. In addition, the light stability of ground tablets was affected considerably by their formulation.
Servant leadership and nurses’ upward voice behavior in an Egyptian hospital: Does prosocial motivation matter?
Authors: Abdelmotaleb Moustafa , Metwally Abdelmoneim , Saha Sudhir K.
Published: March 2021

BACKGROUND:

Servant leadership can be viewed as a leadership theory that stresses personal integrity and focuses on protecting and promoting the interests of others.

OBJECTIVE:

This article investigates whether the relationship between servant leadership and nurses’ upward voice behavior in an Egyptian hospital is contingent on prosocial motivation. Invoking substitutes for leadership theory, we propose that the relationship between servant leadership and nurses’ upward voice will be attenuated when nurses have a strong desire to protect and promote the well-being of others.

METHODS:

Using a sample of 341 nurses working in a large governmental hospital in Egypt, this proposition was tested using PROCESS Macro for SPSS.

RESULTS:

The results revealed that the relationship between servant leadership and nurses’ upward voice was stronger for those lower in prosocial motivation than for those higher in prosocial motivation.

CONCLUSION:

These results were explained through communal impulsion which adds a new insight into Greenleaf’s theory of servant leadership. Overall, the results of the study shed new light on the conditions through which servant leadership enhances upward voice behavior in an Egyptian hospital.
An efficient method for time series similarity search using binary code representation and hamming distance
Authors: Zhang Haowen , Dong Yabo , Li Jing , Xu Duanqing
Published: March 2021

Time series similarity search is an essential operation in time series data mining and has received much higher interest along with the growing popularity of time series data. Although many algorithms to solve this problem have been investigated, there is a challenging demand for supporting similarity search in a fast and accurate way. In this paper, we present a novel approach, TS2BC, to perform time series similarity search efficiently and effectively. TS2BC uses binary code to represent time series and measures the similarity under the Hamming Distance. Our method is able to represent original data compactly and can handle shifted time series and work with time series of different lengths. Moreover, it can be performed with reasonably low complexity due to the efficiency of calculating the Hamming Distance. We extensively compare TS2BC with state-of-the-art algorithms in classification framework using 61 online datasets. Experimental results show that TS2BC achieves better or comparative performance than other the state-of-the-art in accuracy and is much faster than most existing algorithms. Furthermore, we propose an approximate version of TS2BC to speed up the query procedure and test its efficiency by experiment.
Deep spatial-temporal fusion network for fine-grained air pollutant concentration prediction
Authors: Ge Liang , Wu Kunyan , Chang Feng , Zhou Aoli , Li Hang , Liu Junling
Published: March 2021

Air pollution is a serious environmental problem that has attracted much attention. Predicting air pollutant concentration can provide useful information for urban environmental governance decision-making and residents’ daily health control. However, existing methods fail to model the temporal dependencies or have suffer from a weak ability to capture the spatial correlations of air pollutants. In this paper, we propose a general approach to predict air pollutant concentration, named DSTFN, which consists of a data completion component, a similar region selection component, and a deep spatial-temporal fusion network. The data completion component uses tensor decomposition method to complete the missing data of historical air quality. The similar region selection component uses region metadata to calculate the spatial similarity between regions. The deep spatial-temporal fusion network fuses urban heterogeneous data to capture factors affecting air quality and predict air pollutant concentration. Extensive experiments on a real-world dataset demonstrate that our model achieves the highest performance compared with state-of-the-art models for air quality prediction.
Microbloggers’ interest inference using a subgraph stream
Authors: Huang Xiaoling , Wang Hao , Li Lei , Zhu Yi , Hu Chengxiang
Published: March 2021

Inferring user interest over large-scale microblogs have attracted much attention in recent years. However, the emergence of the massive data, dynamic change of information and persistence of microblogs pose challenges to interest inference. Most of the existing approaches rarely take into account the combination of these microbloggers’ characteristics within the model, which may incur information loss with nontrivial magnitude in real-time extraction of user interest and massive social data processing. To address these problems, in this paper, we propose a novel User-Networked Interest Topic Extraction in the form of Subgraph Stream (UNITE_SS) for microbloggers’ interest inference. To be specific, we develop several strategies for the construction of subgraph stream to select the better strategy for user interest inference. Moreover, the information of microblogs in each subgraph is utilized to obtain a real-time and effective interest for microbloggers. The experimental evaluation on a large dataset from Sina Weibo, one of the most popular microblogs in China, demonstrates that the proposed approach outperforms the state-of-the-art baselines in terms of precision, mean reciprocal rank (MRR) as well as runtime from the effectiveness and efficiency perspectives.
Deep multiple non-negative matrix factorization for multi-view clustering
Authors: Du Guowang , Zhou Lihua , Lü Kevin , Ding Haiyan
Published: March 2021

Multi-view clustering aims to group similar samples into the same clusters and dissimilar samples into different clusters by integrating heterogeneous information from multi-view data. Non-negative matrix factorization (NMF) has been widely applied to multi-view clustering owing to its interpretability. However, most NMF-based algorithms only factorize multi-view data based on the shallow structure, neglecting complex hierarchical and heterogeneous information in multi-view data. In this paper, we propose a deep multiple non-negative matrix factorization (DMNMF) framework based on AutoEncoder for multi-view clustering. DMNMF consists of multiple Encoder Components and Decoder Components with deep structures. Each pair of Encoder Component and Decoder Component are used to hierarchically factorize the input data from a view for capturing the hierarchical information, and all Encoder and Decoder Components are integrated into an abstract level to learn a common low-dimensional representation for combining the heterogeneous information across multi-view data. Furthermore, graph regularizers are also introduced to preserve the local geometric information of each view. To optimize the proposed framework, an iterative updating scheme is developed. Besides, the corresponding algorithm called MVC-DMNMF is also proposed and implemented. Extensive experiments on six benchmark datasets have been conducted, and the experimental results demonstrate the superior performance of our proposed MVC-DMNMF for multi-view clustering compared to other baseline algorithms.
Automatic image detection of multi-type surface defects on wind turbine blades based on cascade deep learning network
Authors: Mao Yulin , Wang Shuangxin , Yu Dingli , Zhao Juchao
Published: March 2021

A safe operation protocol of the wind blades is a critical factor to ensure the stability of a wind turbine. Sensors are most commonly applied for defect detection on wind turbine blades (WTBs). However, due to the high cost and the sensitivity to stochastic noise, computer vision-guided automatic detection remains a challenge for surface defect detection on WTBs in particularly, its accuracy in locating defects is yet to be optimized. In this paper, we developed a visual inspection model that can automatically and precisely classify and locate the surface defects, through the utilization of a deep learning framework based on the Cascade R-CNN. In order to obtain high mean average precision (mAP) according to the characteristics of the dataset, a model named Contextual Aligned-Deformable Cascade R-CNN (CAD Cascade R-CNN) using improved strategies of transfer learning, Deformable Convolution and Deformable RoI Align, as well as context information fusion is proposed and a dataset with surface defects categorized and labeled as crack, breakage and oil pollution is generated. Moreover to alleviate the problem of false detection under a complex background, an improved bisecting k-means is presented during the test process. The adaptability and generalization of the proposed CAD Cascade R-CNN model were validated by each type of defects in dataset and different IoU thresholds, whereas, each of the above improved strategies was verified by gradual ablation experiments. Finally experiments that compared with the baseline Cascade R-CNN, Faster R-CNN and YOLO-v3 demonstrate its superiority over these existing approaches with a maximum of 92.1% mAP.
Clinicopathological Correlation: Dopamine and Amyloid PET Imaging with Neuropathology in Three Subjects Clinically Diagnosed with Alzheimer’s Disease or Dementia with Lewy Bodies
Authors: Gupta Harsh V. , Beach Thomas G. , Mehta Shyamal H. , Shill Holly A. , Driver-Dunckley Erika , Sabbagh Marwan N. , Belden Christine M. , Liebsack Carolyn , Dugger Brittany N. , Serrano Geidy E. , Sue Lucia I. , Siderowf Andrew , Pontecorvo Michael J. , Mintun Mark A. , Joshi Abhinay D. , Adler Charles H.
Published: March 2021

Background: Imaging biomarkers have the potential to distinguish between different brain pathologies based on the type of ligand used with PET. AV-45 PET (florbetapir, Amyvid™) is selective for the neuritic plaque amyloid of Alzheimer’s disease (AD), while AV-133 PET (florbenazine) is selective for VMAT2, which is a dopaminergic marker. Objective: To report the clinical, AV-133 PET, AV-45 PET, and neuropathological findings of three clinically diagnosed dementia patients who were part of the Avid Radiopharmaceuticals AV133-B03 study as well as the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND). Methods: Three subjects who had PET imaging with both AV-133 and AV-45 as well as a standardized neuropathological assessment were included. The final clinical, PET scan, and neuropathological diagnoses were compared. Results: The clinical and neuropathological diagnoses were made blinded to PET scan results. The first subject had a clinical diagnosis of dementia with Lewy bodies (DLB); AV-133 PET showed bilateral striatal dopaminergic degeneration, and AV-45 PET was positive for amyloid. The final clinicopathological diagnosis was DLB and AD. The second subject was diagnosed clinically with probable AD; AV-45 PET was positive for amyloid, while striatal AV-133 PET was normal. The final clinicopathological diagnosis was DLB and AD. The third subject had a clinical diagnosis of DLB. Her AV-45 PET was positive for amyloid and striatal AV-133 showed dopaminergic degeneration. The final clinicopathological diagnosis was multiple system atrophy and AD. Conclusion: PET imaging using AV-133 for the assessment of striatal VMAT2 density may help distinguish between AD and DLB. However, some cases of DLB with less-pronounced nigrostriatal dopaminergic neuronal loss may be missed.
Tooth Loss Induces Memory Impairment and Gliosis in App Knock-In Mouse Models of Alzheimer’s Disease
Authors: Taslima Ferdous , Jung Cha-Gyun , Zhou Chunyu , Abdelhamid Mona , Abdullah Mohammad , Goto Tetsuya , Saito Takashi , Saido Takaomi C. , Michikawa Makoto
Published: March 2021

Background: Epidemiological studies have shown that tooth loss is associated with Alzheimer’s disease (AD) and dementia. However, the molecular and cellular mechanisms by which tooth loss causes AD remain unclear. Objective: We investigated the effects of tooth loss on memory impairment and AD pathogenesis in AppNL-G-F mice. Methods: Maxillary molar teeth on both sides were extracted from 2-month-old AppNL-G-F mice, and the mice were reared for 2 months. The short- and long-term memory functions were evaluated using a novel object recognition test and a passive avoidance test. Amyloid plaques, amyloid-β (Aβ) levels, glial activity, and neuronal activity were evaluated by immunohistochemistry, Aβ ELISA, immunofluorescence staining, and western blotting. The mRNA expression levels of neuroinflammatory cytokines were determined by qRT-PCR analysis. Results: Tooth loss induced memory impairment via an amyloid-cascade-independent pathway, and decreased the neuronal activity, presynaptic and postsynaptic protein levels in both the cortex and hippocampus. Interestingly, we found that tooth loss induced glial activation, which in turn leads to the upregulation of the mRNA expression levels of the neuroinflammation cytokines tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-1β in the hippocampus. We also found that tooth loss activated a stress-activated protein kinase, c-Jun N-terminal kinase (JNK), and increased heat shock protein 90 (HSP90) levels in the hippocampus, which may lead to a glial activation. Conclusion: Our findings suggest that taking care of teeth is very important to preserve a healthy oral environment, which may reduce the risk of cognitive dysfunction.
Exposure to Anticholinergic and Sedative Drugs and Healthcare Costs in Older Patients with Neurocognitive Disorders
Authors: Gervais Frederic , Dauphinot Virginie , Mouchoux Christelle , Krolak-Salmon Pierre
Published: March 2021

Background: Literature supports an increasing number of older patients living with neurocognitive disorders alongside with their annual worldwide costs. Therapeutic management of behavioral and psychological symptoms includes the use of anticholinergic and sedative drugs for which significant exposure is negatively associated with clinical outcomes. Objective: The aim of this study was to assess the healthcare costs differences related to an increase in the exposure to anticholinergic and sedative drugs in older patients with neurocognitive disorder. Methods: A longitudinal study was conducted during 3 years on 1,604 participants of the MEMORA cohort linked with both regional public health insurance and hospital discharge databases between 2012 and 2017. Direct medical and non-medical costs were included. Exposure to anticholinergic and sedative drugs was measured by the drug burden index (DBI). Results: Costs difference associated with a DBI≥0.5 were + 338€ (p < 0.001). After adjustment on comorbidities, NCD stage, cognitive impairment, functional limitation, polypharmacy, and sociodemographic characteristics, a DBI≥0.5 was found to be an independent predictor of an increase of total healthcare costs by 22%(p < 0.001). Conclusion: Anticholinergic and sedative drugs have a substantial economic burden among older patients with neurocognitive disorder. More studies are required to assess the clinical and economic impact of an efficient strategy based on the reduction of the exposure to anticholinergic and sedative drugs and the promotion of non-pharmacological interventions.
Relevance of a Truncated PRESENILIN 2 Transcript to Alzheimer’s Disease and Neurodegeneration
Authors: Moussavi Nik Seyyed Hani , Porter Tenielle , Newman Morgan , Bartlett Benjamin , Khan Imran , Sabale Miheer , Eccles Melissa , Woodfield Amy , Groth David , Dore Vincent , Villemagne Victor L. , Masters Colin L. , Martins Ralph N. , Laws Simon M. , Lardelli Michael , Verdile Giuseppe
Published: March 2021

Background: The PRESENILIN genes (PSEN1, PSEN2) encoding for their respective proteins have critical roles in many aspects of Alzheimer’s disease (AD) pathogenesis. The PS2V transcript of PSEN2 encodes a truncated protein and is upregulated in AD brains; however, its relevance to AD and disease progression remains to be determined. Objective: Assess transcript levels in postmortem AD and non-AD brain tissue and in lymphocytes collected under the Australian Imaging Biomarker and Lifestyle (AIBL) study. Methods: Full length PSEN2 and PS2V transcript levels were assessed by quantitative digital PCR in postmortem brain tissue (frontal cortex and hippocampus) from control, AD, frontotemporal dementia (FTD), and Lewy body dementia (LBD). Transcript levels were also assessed in lymphocytes obtained from the Perth subset of the AIBL study (n = 160). Linear regression analysis was used to assess correlations between transcript copy number and brain volume and neocortical amyloid load. Results: PS2V levels increased in AD postmortem brain but PS2V was also present at significant levels in FTD and LBD brains. PS2V transcript was detected in lymphocytes and PS2V/PSEN2 ratios were increased in mild cognitive impairment (p = 0.024) and AD (p = 0.019) groups compared to control group. Increased ratios were significantly correlated with hippocampal volumes only (n = 62, β= –0.269, p = 0.03). Conclusion: Taken together, these results suggest that PS2V may be a marker of overall neurodegeneration.
Relationships Between Chronic Pain Stage, Cognition, Temporal Lobe Cortex, and Sociodemographic Variables
Authors: Tanner Jared J. , Hanchate Shivani , Price Catherine C. , Garvan Cynthia , Lai Song , Staud Roland , Deshpande Hrishikesh , Deutsch Georg , Goodin Burel R. , Fillingim Roger B. , Sibille Kimberly T.
Published: March 2021

Background: Non-Hispanic black (NHB) individuals have increased risk of Alzheimer’s disease (AD) relative to non-Hispanic whites (NHW). Ethnicity/race can serve as a proxy sociodemographic variable for a complex representation of sociocultural and environmental factors. Chronic pain is a form of stress with high prevalence and sociodemographic disparities. Chronic pain is linked to lower cognition and accelerated biological aging. Objective: The purpose of this study is to seek understanding of potential cognitive and temporal lobe structural brain AD vulnerabilities based on chronic pain stage and ethnicity/race. Methods: Participants included 147 community dwelling NHB and NHW adults without dementia between 45–85 years old who had or were at risk of knee osteoarthritis. All participants received an MRI (3T Philips), the Montreal Cognitive Assessment (MoCA), and assessment of clinical knee pain stage. Results: There were ethnic/race group differences in MoCA scores but no relationships with chronic knee pain stage. Ethnicity/race moderated the relationship between AD-related temporal lobe thickness and chronic pain stage with quadratic patterns suggesting thinner cortex in high chronic pain stage NHB adults. Conclusion: There appear to be complex relationships between chronic knee pain stage, temporal lobe cortex, and sociodemographic variables. Specifically, NHB participants without dementia but with high chronic knee pain stage appeared to have thinner temporal cortex in areas associated with AD. Understanding the effects of sociocultural and socioeconomic factors on health outcomes is the first step to challenging the disparities in healthcare that now appear to link disease conditions to neurodegenerative processes.
The Cognition and Flow Study: A Feasibility Randomized Controlled Trial of the Effects of Cognitive Training on Cerebral Blood Flow
Authors: Beishon Lucy C. , Panerai Ronney B. , Budgeon Charley , Subramaniam Hari , Mukaetova-Ladinska Elizabeta , Robinson Thompson G. , Haunton Victoria J.
Published: March 2021

Background: Cognitive training (CT) has demonstrated benefits for healthy older adults (HG) and mild cognitive impairment (MCI), but the effects on vascular function are unknown. Objective: This is a feasibility trial investigating the effects of CT on cerebral blood flow velocity (CBFv). Methods: Twenty HG, 24 with Alzheimer’s disease (AD), and 12 with MCI were randomized to 12 weeks of multi-domain CT or control. Outcomes included: cognition (Addenbrooke’s Cognitive Examination III), mood, quality of life (QoL), physical, and neurovascular function (transcranial Doppler ultrasonography measured task activation of CBFv responses). Data are presented as mean difference (MD) and 95% confidence interval (CI). Results: 47 participants completed the trial. There were three dropouts from the training arm in the AD group, and one in the HG group. The intervention was acceptable and feasible to the majority of participants with a high completion rate (89%). The dropout rate was higher among participants with dementia. Few changes were identified on secondary analyses, but QoL was significantly improved in HG post-training (MD: 4.83 [95% CI: 1.13, 8.54]). CBFv response rate was not significantly different in HG (MD: 1.84 [95% CI: –4.81, 1.12]), but a significant increase was seen in the patient group (MD: 1.79 [95% CI: 0.005, 3.58]), requiring sample sizes of 56 and 84 participants respectively for a fully-powered trial. Conclusion: A 12-week CT program was acceptable and feasible in HG, AD, and MCI. CT may be associated with alterations in vascular physiology which require further investigation in an appropriately powered randomized controlled trial.
Differential Impact of Education on Cognitive Performance in Neurological Patients with Progressive Cognitive Decline
Authors: Zamarian Laura , Karner Elfriede , Bodner Thomas , Djamshidian Atbin , Delazer Margarete
Published: March 2021

Background: Education has a protective effect toward cognitive decline in advanced age and is an important factor contributing to cognitive reserve. Objective: To elucidate the interaction effect of education and global mental status on cognitive performance of older patients with progressive cognitive decline. Methods: This retrospective study included 1,392 patients. We performed moderation regressions to examine the interaction between education and global mental status (Mini-Mental State Examination (MMSE) score) on performance in episodic memory, executive functions (EF), language, and constructional praxis tests. Significant interaction effects were further explored through separate linear regressions by MMSE level (inferior: ≤24; intermediate: 25–27; superior: 28–30). Results: There was an interaction between MMSE and education for some but not all variables. At intermediate and superior MMSE levels, high-educated people had a clear advantage relative to low-educated people in verbal memory and EF tests. This advantage was not significant at an inferior MMSE level. In object naming, constructional praxis recall, and constructional praxis, high-educated people performed better than low-educated people, independently of MMSE level. Conclusion: Education has a differential effect on cognitive performance in patients with cognitive decline. While high education is not helpful for episodic memory and EF at low cognitive levels, it is still beneficial for retrieving words or other semantic knowledge. These findings suggest an interaction between global mental status and education on different cognitive domains and have strong clinical implications. Diagnostic judgments should be based on the knowledge of such interaction. This study highlights the beneficial but selective effects of high education.
Association Between Inflammatory Bowel Disease and Dementia: A Retrospective Cohort Study
Authors: Zingel Rebecca , Bohlken Jens , Kostev Karel
Published: March 2021

Background: The critical role of inflammatory processes in the pathogenesis of dementia has recently been established. Objective: The aim of this study was to investigate the association between inflammatory bowel disease (IBD) and dementia risk in patients followed in general practices in Germany. Methods: This study included patients aged over 60 with an initial diagnosis of IBD (Crohn’s Disease (CD), ulcerative colitis (UC)) who were followed in 1,159 German general practices between January 1995 and December 2014. IBD patients were matched to healthy patients using propensity scores based on age, gender, index year, insurance type and comorbidities. Kaplan-Meier curves were used to study the development of dementia in patients with or without IBD within up to 15 years of the index date. Cox proportional hazard regression models were used to estimate the relationship between IBD and dementia. Results: The study included 3,850 patients with and 3,850 patients without IBD and revealed a higher cumulative incidence of dementia in IBD patients than in non-IBD patients after the follow-up period. The cumulative incidence of dementia differed within IBD subtypes; it was significantly higher in UC patients than in CD patients. Cox proportional hazard models showed that IBD is associated with a 1.22-fold increase in the risk (95% CI: 1,07–1,39) of developing dementia. UC patients had a 1.25-fold higher risk of developing dementia (95% CI: 1.07–1.46). CD is not significantly associated with an increased risk of dementia (HR: 1.17, 95% CI: 0.93–1.47). Conclusion: A positive association between IBD and dementia was found in patients followed in general practices in Germany.
The fuzzy linear regression model for finding sales forcastion from financial leasing in China’s equipment manufacturing industries
Authors: Zhu Chengke , Wang Junshan
Published: March 2021

With the development of technology and artificial intelligence(AI), financial leasing is used frequently in China’s equipment manufacturing industries, especially after 2008, which attracts our attention. This paper focuses on the problem. A theoretical model is provided in the paper to explain the motivation that why financial leasing is used in equipment manufacturing industries. In this paper, we employ multi-level fuzzy linear regression model to analyze data of manufacturing equipment industry of China in order to discover impact between sales revenue and financial leasing. We also discover credit sale forecasting using this model. We discover that economic leasing has a constructive important effect on sales revenue in total samples, which is consistent with the theoretical framework. However, the results are different in sub-industries, which shows that economic leasing has a constructive and important effect on sales profits in some sub-industries, but some of them are not. Furthermore, we also find that asset characteristics has a substantial effect on financial leasing decision. The outcome demonstrates that the more precise the asset, the easier it can be leased.
Influence of virtual reality and 3D printing on architectural innovation evaluation based on quality of experience evaluation using fuzzy logic
Authors: Yangxuan  , Zhaoqianjing
Published: March 2021

In the last few years, the construction industry’s primary energydem and in developed economies accounted for 30%–40%, and technological innovation is considered to be an urgent need for the transformation and upgrading of the construction industry. New technological innovations are continually changing the way the construction industry is implemented. In the construction industry, artificial intelligence is beginning to change all aspects of the construction industry, in the field of equipment planning, overall layout, safety, management and other fields have caused many changes. The integration of new technologies has revolutionized the traditional construction industry, such as virtual reality technology and 3D printing technology. In this work, we propose a categorization for assessing Virtual reality and 3D printing of Architectural Innovation on the basis of quality of experience (QoE) metric Evaluation of virtual environment using Fuzzy Logic (FL) System. The simulation result is analysed based on the comparative analysis of user experience with Fuzzy logic estimation for perception of virtual environment. The result analysis validated that the proposed FL system replicates the user valuation for architecture innovation applications more precisely and accurately thus FL is efficient method for predicting the inclusive QoE of a virtual reality and 3D printing. This paper will recapitulate the expansion of the two techniques in the manufacture engineering, demeanor examination on the presentation of diverse skills in architectural innovation, as well as explain through real cases how these two techniques have an influence on the improvement of the manufacture engineering. Simultaneously, this paper discourses the limitations of technology mixing and put advancing opinions on the future development of the manufactureengineering.
A cost-effective adaptive random testing algorithm for object-oriented software testing
Authors: Zhou Yue , Wang Xiujun , Guo Shu , Wen Yi , He Jingsha
Published: March 2021

The rapid development of object oriented programming (OOP) technology has made it one of the mainstream programming technologies that has been widely used in the design and development of object oriented software (OOS). The inheritance, encapsulation and polymorphism properties of object-oriented language can improve the reusability, scalability and interoperability of software while increasing the difficulty of testing OOS. Researchers have proposed a variety of testing methods to test OOS among which random testing (RT) has been widely used due to its simplicity and ease of use. An OMISS-ARTsum algorithm is proposed in this paper that uses improved OMISS random test FSCS-ART with max-sum standard, which is an implementation version of fixed-sized-candidate-set ART. The OMISS-ARTsum algorithm calculates the total distance between a candidate test case and the executed test case set before the next test case is selected from the set of candidate test cases. Unlike the traditional max-sum based FSCS-ART algorithm, OMISS-ARTsum does not calculate the distance between each executed test case and the candidate case and then sum up the total distance, but uses the method of summing up all the executed test cases and the candidate cases. The information of executing test cases is saved as a whole and the distance between the executed test case set and candidate cases is calculated at the same time. Experiment shows that compared to the OMISS-ART algorithm, the proposed OMISS-ARTsum algorithm can reduce the time overhead.
Energy consumption simulation of green building based on BIM system and improved neural network
Authors: Liu Chenguang
Published: March 2021

The construction industry is an indispensable and important support in the national economic industry. The characteristics of the construction industry, such as long production cycle, large number of participants and various types, determine that the development of the construction industry is undoubtedly very difficult. In order to realize the rapid development of the construction industry, transformation is the inevitable development direction of the construction industry in the future, which requires the help of science and technology. With the development of science and technology, information technology and big data have been applied to all walks of life, and these are also important means to support the transformation of the construction industry. In order to achieve green development, reducing energy consumption is an inevitable measure. Energy consumption analysis and reduction can be realized by establishing energy consumption monitoring platform based on big data. The application of BIM system is an information-based energy consumption analysis method. This technology can realize the analysis and prediction of energy consumption, so as to determine the appropriate way to save energy, and even estimate the corresponding cost. It is of great significance to establish a suitable energy-saving scheme.
Remote classroom action recognition based on improved neural network and face recognition
Authors: Mao Lijun
Published: March 2021

In recent years, the field of computer vision is promoted by the development of intelligent technology and computer technology, and has made breakthrough progress. Intelligent hardware technology and computer technology lay the foundation for the development of computer vision field. At the same time, the continuous improvement and development of artificial intelligence technology has also promoted the rapid development of educational video system, and the video tracking of educational video system has made breakthrough progress. By fully using intelligent hardware and computer technology, and combining with artificial intelligence technology, the video tracking and recognition technology of educational video system has been further developed, and new recognition algorithm has been adopted. The accuracy of tracking recognition is greatly improved, which can accurately identify the action of the characters. At the same time, through the use of new action recognition algorithm, not only improve the accuracy of educational video recognition, but also improve the speed of recognition, which can accurately capture the changes of people’s behavior in the classroom. The time consumed by the action recognition algorithm is very short, and the speed of the algorithm is very high. This new algorithm greatly improves the efficiency of the education recording and broadcasting system, and improves the accuracy and accuracy of the education recording and broadcasting system. This paper studies a set of intelligent image recognition system for students’ classroom behavior. It compiles and explains the intelligent system software systematically. The operation of this system is no single. It operates through the joint operation of many modules. It can realize online distributed homework, accurately and quickly identify students’ classroom behavior, and can also help students to identify their classroom behavior accurately and quickly. The classroom behavior of the accurate analysis of students’ incorrect classroom behavior to make timely reminders, greatly improve the efficiency of the classroom, improve the degree of concentration of students. In this paper, many classroom behaviors are simulated, and the performance of this software platform is predicted through many experiments.