bluuebunny/crossref_metadata_2025 huggingface dataset:
Features of the Circulation of ARVI Pathogens During of Emergence and Widespread of SARS-CoV-2 in the 2018–2021
Authors: Burtseva E. I. , Kolobukhina L. V. , Voronina O. L. , Ignatjeva A. V. , Mukasheva E. A. , Panova A. D. , Feodoritova E. L. , Krasnoslodotsev K. G. , Trushakova S. V. , Merkulova L. N. , Khlopova I. N. , Breslav N. V. , Ryzhova N. N. , Kunda M. S. , Aksenova E. I. , Vartanyan R. V. , Kisteneva L. B. , Burgasova O. A. , Rosatkevich A. G. , Kruzhkova I. S. , Bazarova M. V. , Smetanina S. V. , Tsvetkova N. A. , Levochkina Yu. S. , Kozlova M. V. , Korostin D. O. , Botsmanov E. I.
Published: September 2022

Relevance. The long-term leadership of ARVI pathogens determines their significance in the damage caused to both health and the economy of the country. Aim. To identify the features of the structure of ARVI during the emergence and widespread spread of SARS-CoV-2. Materials and methods. The article uses methods used in epidemiological surveillance of acute respiratory viral infections. Results and discussion. The results of the diagnostic available ARVI pathogens monitoring during epidemic seasons 2018-2021 are presented. The tendency of greater engagement of aged group 15 y.o. and older in epidemic process by morbidity and hospitalization due to SARI was shown. 49 818 nasal swabs from patients with influenza infection, 36 044 – with ARVI and 59 062 – with SARS-CoV-2 were tested. The top three in the structure of ARVI were INF, HEV-D and HRSV (in the 2018–2019 season); INF, SARS-CoV-2 and HEV-D (2019–2020); SARS-CoV-2, HEV-D and HPIV/HCoV (2020–2021). The activity of viral pathogens also differed: for HPIV, HAdV, HEV-D, HMPV, a decrease in activity was noted during the appearance of SARS-CoV-2 (2019–2020) and some of its growth in the following season; in relation to HRSV and INF - a decrease in activity during the last two seasons, and for INF – extremely low activity in the 2020-2021 season; the activity of seasonal HCoV even increased slightly. The data of genetic analyses of SARS-CoV-2 positive samples showed the heterogeneity of its population with a representative of variants (Alfa, Delta) as well as endemic for Russia and Moscow variants only. The recommended composition of influenza virus vaccines for use in the 2021–2022 northern hemisphere influenza season and in the 2022 southern hemisphere influenza season are presented due to their drift changeability. Conclusions. SARS-CoV-2 was influenced by the activity of ARVI pathogens with the almost complete displacement of influenza viruses from the circulation in the period 2020–2021.
Combined Foci of Tularemia, Leptospirosis and Hemorrhagic Fever with Renal Syndrome in the South of the Arkhangelsk region
Authors: Mikhailova T. V. , Emelyanova L. G. , Podobedova Y. S. , Demidova T. N. , Kormilitsyna M. I. , Semikhin A. S. , Amirkhanyan A. V. , Sharapova N. E. , Savelyeva O. V. , Popova Y. V.
Published: September 2022

Relevance. Combined foci of zoonotic infections are found in all regions of the Russian Federation. A feature of combined foci is the common biocenosis for populations of pathogens of various etiologies (bacteria, viruses, parasitic infections) and the formation of natural foci by them. Aim. Epizootological study of the territory in the south of the Arkhangelsk region for the presence of combined foci of zoonotic infections (tularemia, leptospirosis and hemorrhagic fever with renal syndrome – HFRS). Materials and methods. 135 small mammals were captured and examined in the Ustyansky district of the Arkhangelsk region. Established the species composition and mixed infection among small mammals pathogens of tularemia, leptospirosis, hemorrhagic fever with renal syndrome. Results. In the south of the Arkhangelsk Region in the Ustyansky District, in 2019, for the first time, a combined natural focus of the forest type was identified and characterized. The bank vole and the common shrew are the main carriers of the causative agents of these infections. Five species of small mammals are mixed-infected with the causative agents of these infections. Infected animals with one, two or three pathogens were simultaneously detected in all studied biotopes. This indicates the presence of a combined natural focus of tularemia, leptospirosis, and HFRS. Conclusion. The existence of a combined natural focus of tularemia, leptospirosis and HFRS in middle taiga ecosystems in the south in the Ustyansky district of the Arkhangelsk region was revealed for the first time. Thus, this area can be considered enzootic for tularemia, leptospirosis and HFRS. This focus belongs to the forest type in terms of landscape and geographical characteristics. Mixed infection of small mammals suggests the possibility of simultaneous infection with pathogens of two or more infections, not only animals, but also people located on the territory of natural foci. and non-simultaneous infection of humans with tularemia, leptospirosis and HFRS in combined foci.
Gene expression analysis during progression of malignant meningioma compared to benign meningioma
Authors: Maier Andrea D. , Meddis Alessandra , Mirian Christian , Haslund-Vinding Jeppe , Bartek Jiri , Krog Sebastian M. , Nguyen Thi Uyen Phuong , Areškevičiūtė Aušrinė , Melchior Linea C. , Heegaard Steffen , Kristensen Bjarne W. , Munch Tina N. , Fugleholm Kåre , Ziebell Morten , Raleigh David R. , Poulsen Frantz R. , Gerds Thomas A. , Litman Thomas , Scheie David , Mathiesen Tiit
Published: September 2022

OBJECTIVE

Meningioma is the most common primary intracranial neoplasm. Only 1%–3% of meningiomas are malignant according to the 2016 WHO criteria (WHO grade III). High-grade meningiomas present specific gene expression signatures indicating aggressive growth or recurrence. However, changes in gene expression and in neuroinflammatory gene expression signatures in WHO grade III meningiomas and during progression from WHO grade I or II to grade III are unknown.

METHODS

The authors used a NanoString targeted gene expression panel with focus on 787 genes relevant in meningioma pathology and neuroinflammatory pathways to investigate patients with grade III meningiomas treated at Rigshospitalet from 2000 to 2020 (n = 51). A temporal dimension was added to the investigation by including samples from patients’ earlier grade I and II meningiomas and grade III recurrences (n = 139 meningiomas). The authors investigated changes in neuroinflammatory gene expression signatures in 1) grade I meningiomas that later transformed into grade III meningiomas, and 2) grade III meningiomas compared with nonrecurrent grade I meningiomas.

RESULTS

The authors’ data indicate that FOXM1, TOP2A, BIRC5, and MYBL2 were enriched and the HOTAIR regulatory pathway was enriched in grade III meningiomas compared with nonrecurrent grade I meningiomas. They discovered a separation of malignant and benign meningiomas based only on genes involved in microglia regulation with enrichment of P2RY12 in grade I compared with grade III meningiomas. Interestingly, FOXM1 was upregulated in premalignant grade I meningioma years before the grade III transformation.

CONCLUSIONS

The authors found gene expression changes in low-grade meningiomas that predated histological transformation to grade III meningiomas. Neuroinflammation genes distinguished grade III from grade I meningiomas.
A robotic MR-guided high-intensity focused ultrasound platform for intraventricular hemorrhage: assessment of clot lysis efficacy in a brain phantom
Authors: Raghuram Hrishikesh , Looi Thomas , Pichardo Samuel , Waspe Adam C. , Drake James M.
Published: September 2022

OBJECTIVE

Intraventricular hemorrhage (IVH) is a neurovascular complication due to premature birth that results in blood clots forming within the ventricles. Magnetic resonance–guided high-intensity focused ultrasound (MRgHIFU) has been investigated as a noninvasive treatment to lyse clots. The authors designed and constructed a robotic MRgHIFU platform to treat the neonatal brain that facilitates ergonomic patient positioning. The clot lysis efficacy of the platform is quantified using a brain phantom and clinical MRI system.

METHODS

A thermosensitive brain-mimicking phantom with ventricular cavities was developed to test the clot lysis efficacy of the robotic MRgHIFU platform. Whole porcine blood was clotted within the phantom’s cavities. Using the MRgHIFU platform and a boiling histotripsy treatment procedure (500 W, 10-msec pulse duration, 1.0% duty cycle, and 40-second duration), the clots were lysed inside the phantom. The contents of the cavities were vacuum filtered, and the remaining mass of the solid clot particles was used to quantify the percentage of clot lysis. The interior of the phantom’s cavities was inspected for any collateral damage during treatment.

RESULTS

A total of 9 phantoms were sonicated, yielding an average (± SD) clot lysis of 97.0% ± 2.57%. Treatment resulted in substantial clot lysis within the brain-mimicking phantoms that were apparent on postsonication T2-weighted MR images. No apparent collateral damage was observed within the phantom after treatment. The results from the study showed the MRgHIFU platform was successful at lysing more than 90% of a blood clot at a statistically significant level.

CONCLUSIONS

The robotic MRgHIFU platform was shown to lyse a large percentage of a blood clot with no observable collateral damage. These results demonstrate the platform’s ability to induce clot lysis when targeting through simulated brain matter and show promise toward the final application in neonatal patients.
The Basis of John Chrysostom’s Teaching on Widowhood
Authors: Konieczko Michał , Uciecha Andrzej
Published: September 2022

The paper presents the origins of John Chrysostom's teaching on widowhood. The author analyses the most important factors that contributed to the shaping of John’s teaching aimed at widows. The first factor was his personal experience, such as the relationship with his mother or with befriended widows. The second factor was being under a strong influence of St. Paul’s teachings, especially the Letter to the Ephesians and the First Letter to the Corinthians. The last factor was a consequence of John's distinction between the existential and essential sources of widowhood. The existential sources, i.e. mainly the imitation of virginity, are the result of John’s understanding of anthropology, while the essential sources are rooted in the unity of divine hypostases and arise from his view on Christian marriage. Chrysostom’s concept of widowhood takes on a concrete and vertical structure in which one can see a trace of the influence of philosophy and education which he received.
Bias-Corrected IDF Curves From Satellite-Based Rainfall for HoaBinh Province, Vietnam
Authors: Doan Thi Noi , Nguyen Tien Thanh
Published: September 2022

Satellite-based rainfall is extremely valuable data to quantify the probability of occurrence of rainfall events but is still uncertain to a certain extent. Therefore, this study firstly evaluates the performance of the satellite-based rainfall, PERSIANN-CCS, with rain gauge rainfall. The power transformation method is then applied to correct the satellite-based rainfall. Importantly, the Intensity-Duration-Frequency (IDF) curves are then constructed with the return periods of 5, 10, 25, 50, 100 and 200 years using the Gumbel probability distribution. The results show an efficiency of power transformation on satellite-based rainfall for both rainfall amount and events. It is especially noticed that it is well matched between bias-corrected satellite-based and rain gauge IDF curves duration 12-, 24-, 48- and 72-hour as a particular. For the duration of less than 12-hour, satellite-based IDF curves without bias correction significantly fit the rain-gauge IDF curves within the considered periods.
Pollution Control and Monitoring System with ML Based Analysis
Authors: Bhatnagar Ekansh , Sharma Manoj
Published: September 2022

With climate change showing real and measurable effects on the day-to-day lives of millions around the world, it is high time to take necessary actions to curb pollution and greenhouse gases. Planning for a sustainable future has become a necessity. But to solve a problem of this scale and nature one needs to first understand it fully. Climate Change is not a localised problem, it is an effect of a global scale cause. Pollution and uncontrolled usage of unrenewable resources are two major factors in this global causation. To understand the extent of our effect on climate, an easy to use and distribute system for measurement will be crucial. In the reported work, the authors have designed and implemented an end-to-end Pollution Detection System with Machine Learning (ML) analysis of the data captured. It consists of two major parts, (a) Client-side Pollution Box which will be compact and cheap, fully integrated with sensors able to capture measurement points for air, water, light and noise pollution and (b) Server-side Cloud Data processing using Machine Learning techniques help to find patterns and correlation using data from the mesh. Mesh would be created by distributing these cheap pollution boxes over a locality or area.
Regulatory Effect of Thyroxine on Calcium and Phosphorus Metabolism in Tissues of Common Indian Toad
Authors: Mohanty K. , Pattnaik S. , Mishra G. , Kar B.B.
Published: September 2022

Thyroxine (T4) plays a vital role in the metabolic processes of animals. It influences the storage and mobilisation of minerals and their utilisation according to the requirement of the body. It is also involved in the early development of vertebrates, especially in amphibian metamorphosis. It has shown anabolic and catabolic effects at a lower dose and higher dose, respectively. The present study aims to identify the role of thyroxine in regulating calcium and phosphorous metabolism in the blood, muscle and bone tissues of Bufo melanostictus. Toads of various sizes and different age groups were chosen, showing a positive correlation between body weight and snout to vent length, indicating overall continuous growth as observed for a large number of poikilothermic animals. As per an earlier report, thyroxine has been shown to have a direct catabolic effect on bone mineral homeostasis leading to an increase in bone mineral resorption and calcium loss through the kidney. Results of the present study indicate that thyroxine treatment in Bufo melanostictus caused depletion of calcium and phosphorous in muscle and bone, while their level increased in the serum at both doses (0.5 μg/gm and 2 μg/gm) during short term i.e. a one-day T4 treatment. Such results are very much consistent with many of the earlier obscurations that, T4 causes an increase in serum calcium and phosphorous levels, while their level in muscle and bone decreased. When the level of these two minerals falls in the serum due to any other condition, the bone resorption under the influence of thyroxine maintains the concentration in serum, consequently, there is a loss in bone density due to resorption and in muscle due to utilisation. However, if the exogenous supply is adequate, the loss caused as above is compensated for, in both bone and muscle.
Application of Remote Sensing and GIS Techniques to Evaluate the Morphological Analysis of the Tehlawi River Basin, Diyala District, Eastern Iraq
Authors: Al–Shammary Sarteel Hamid Enad , Al–Mayyahi Sattar Obaid Maiws
Published: September 2022

In the Tahlawi River Basin in Diyala Province in eastern Iraq and the corresponding areas in Iran, GIS and remote sensing approaches are used to classify the morphological characteristics of watersheds and assess their characteristics. Morphometric parameters such as aerial and linear aspects of the basin of the Tahlawi River were determined and measured. The drainage pattern of the river is dendritic, and it also stands 6th in the order of river basins. This means that the drainage density flow is medium. The circularity ratio value shows that the basin’s geological components are homogeneous. This study provides important information for the population of the basin in investing its resources for development.
Evaluation of different remineralization agents in the treatment of natural caries-affected dentin in permanent teeth
Authors: Turkay Ece Yilmazkasapoglu , Kargul Betul , Aydinoglu Aysu Karakas , Yoruc Afife Binnaz Hazar
Published: September 2022

BACKGROUND: In the preventive treatment protocol, providing remineralization of the tissue in demineralized dentin caries is an important step. OBJECTIVE: In this in vitro study, the effectiveness of remineralization agents in natural caries-affected dentin (NCAD) were investigated. METHODS: Forty caries slices were prepared from permanent molar dentin with International Caries Detection and Assessment System (ICDAS 2) (Code 3). The interventions with 8 days pH cycling were as follows: Deionized water (DW); 5% Sodium Fluoride (5% NaF) Varnish; Casein Phosphopeptide-Amorphous Calcium Fluoride Phosphate (CPP-ACFP); Calcium Glyserophosphate (CaGP) + Magnesium (Mg) + Xylitol. DIAGNOdent (Laser Fluorescence, LF), Surface Microhardness (SMH), and X-ray Fluorescence (XRF) Spectroscopy measurements were calculated before and after pH cycling. RESULTS: LF values decreased between 5% NaF, CCP-ACFP and CaGP. NCAD treated with 5% NaF, CaGP and CCP-ACFP exhibited statistically higher hardness compared to the control group. After 5% NaF application, SMH values were significantly higher than the others. There was no statistically significant difference between baseline and after pH cycling hardness of the control group. After cycling, XRF showed that Ca and P concentrations were increased in all groups. CONCLUSION: The application of agents used in the study could be recommended and promoted as a treatment option of caries dentin for conventional management of caries.
A case report of lumbosacral plexopathy in a patient with a history of sacral chordoma and radiotherapy: Will the detection of myokymia on the EMG help to solve the case?1
Authors: Giray Esra , Albayrak Osman , Kenis-Coskun Ozge , Yagci Ilker , Gündüz Osman Hakan
Published: September 2022

BACKGROUND: When a patient with a prior history of malignancy and radiotherapy develops progressive weakness as a presentation of plexus involvement, the differential diagnosis usually rests between radiation-induced plexopathy and invasion from recurrent tumor. The presence of myokymic discharges is helpful in differentiating radiation-induced from neoplastic plexopathy. OBJECTIVE: To present a case report of a patient with chordoma, a locally aggressive tumor, who was diagnosed with recurrent tumor accompanied by the occurrence of myokymia in needle electromyographic examination. METHOD: A 55-year-old male patient with a history of chordoma and radiotherapy presented to our outpatient clinic with complaints of foot drop, and impaired walking for two months. His latest magnetic resonance imaging (MRI) which was performed three months earlier did not show recurrence. Upon electromyographic evaluation, myokymia, the pathognomic electromyography abnormal wave for radiation plexopathy was detected supporting a diagnosis of radiation plexitis rather than recurrent neoplastic invasion. One month later he presented with more severe pain and was re-evaluated by an MRI, on which a mass was detected indicating relapse. CONCLUSION: With this case report, we would like to emphasize that the behaviour of the tumor should be considered and imaging should be repeated when tumors display aggressive or recurrent behaviour.
A randomized controlled trial on pain, grip strength, and functionality in lateral elbow pain: Mulligan vs muscle energy techniques
Authors: Bagcaci Sinan , Unuvar Bayram Sonmez , Gercek Hasan , Ugurlu Ibrahim , Sert Ozlem Akkoyun , Yilmaz Kamil
Published: September 2022

BACKGROUND: Lateral elbow tendinopathy (LET) is one of the most common lesions of the upper extremity. The level of evidence from studies on LET treatment protocols is insufficient. OBJECTIVE: The aim of this study was to compare the acute effects of mobilization with movement (MWM) and muscle energy technique (MET) on pain, grip strength, and functionality in patients diagnosed with LET. METHODS: Forty-five patients with LET aged 30–55 years were enrolled in this study. Patients were divided into three groups: MWM, MET, and control group. The control group received a 4-week home exercise program. In addition to the home exercise program in the MWM group, 12 sessions of MWM and 12 sessions of MET were performed in the MET group. Participants’ pain, grip strength, and functionality were assessed before and after the study. RESULTS: After the treatment period, greater improvement in pain, grip strength, finger strength, and functionality were observed in the MWM and MET groups than in the control group (p< 0.05), but no statistically significant difference was found between the MWM and MET groups (p> 0.05). CONCLUSIONS: This study shows that MWM and MET, used in addition to home exercises, can be used to relieve pain and increase grip strength, finger strength, and functionality.
Identification and validation of real hub genes in hepatocellular carcinoma based on weighted gene co-expression network analysis
Authors: Qiao Yu , Yuan Fahu , Wang Xin , Hu Jun , Mao Yurong , Zhao Zhigang
Published: September 2022

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common liver malignancies in the world. With highly invasive biological characteristics and a lack of obvious clinical manifestations, hepatocellular carcinoma usually has a poor prognosis and ranks fourth in cancer mortality. The etiology and exact molecular mechanism of primary hepatocellular carcinoma are still unclear. OBJECTIVE: This work aims to help identify biomarkers of early HCC diagnosis or prognosis based on weighted gene co-expression network analysis (WGCNA). METHODS: Expression data and clinical information of HTSeq-Counts were downloaded from The Cancer Genome Atlas (TCGA) database, and gene expression map GSE121248 was downloaded from Gene Expression Omnibus (GEO). By differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) searched for modules in the two databases that had the same effect on the biological characteristics of HCC, and extracted the module genes with the highest positive correlation with HCC from two databases, and finally obtained overlapping genes. Then, we performed functional enrichment analysis on the overlapping genes to understand their potential biological functions. The top ten hub genes were screened according to MCC through the string database and Cytoscape software and then subjected to survival analysis. RESULTS: High expression of CDK1, CCNA2, CDC20, KIF11, DLGAP5, KIF20A, ASPM, CEP55, and TPX2 was associated with poorer overall survival (OS) of HCC patients. The DFS curve was plotted using the online website GEPIA2. Finally, based on the enrichment of these genes in the KEGG pathway, real hub genes were screened out, which were CDK1, CCNA2, and CDC20 respectively. CONCLUSIONS: High expression of these three genes was negatively correlated with survival time in HCC, and the expression of CDK1, CCNA2, and CDC20 were significantly higher in tumor tissues of HCC patients than in normal liver tissues as verified again by the HPA database. All in all, this provides a new feasible target for early and accurate diagnosis of HCC, clinical diagnosis, treatment, and prognosis.
ASSIST-IoT: A Reference Architecture for Next Generation Internet of Things
Authors: Fornés-Leal Alejandro , Lacalle Ignacio , Palau Carlos E. , Szmeja Paweł , Ganzha Maria , Paprzycki Marcin , Garro Eduardo , Blanquer Francisco
Published: September 2022

New requirements, posed by the Next Generation IoT, demand design of novel reference architectures, providing foundation for implementation of Internet of Things (IoT) ecosystems. Building on cloud-native concepts (e.g. microservices, virtualisation, and containerization), a flexible architecture that answers requirements present in recent IoT deployments is introduced. A general description of components of the architecture (grouped in horizontal planes and vertical capabilities) is provided, together with formal definition of architectural views. Moreover, ground is laid for upcoming validation in real-world-anchored scenarios. Functional, node, deployment and data views are presented, each of them addressing concerns of different stakeholder groups, typically involved in an IoT deployments.
SpamDL: A High Performance Deep Learning Spam Detector Using Stanford Global Vectors and Bidirectional Long Short-Term Memory Neural Networks
Authors: Fattahi Jaouhar , Mejri Mohamed , Ziadia Marwa , Ghayoula Ridha
Published: September 2022

Spam consists of unwanted messages that are often containers of malicious code and/or links pointing to shady sites or objects that pose real dangers to a company’s machines, software, or data. Spam detection is therefore a primary security objective. Nevertheless, the detection tools available on the market are few in number and their efficiency is often limited. In this paper, we propose a spam detection tool based on deep-learning. Our tool uses bidirectional Long-Short Term Memory networks while relying on Stanford Global Vectors for word representation. We present the techniques we use. Then, we conduct a series of experiments on a family of candidate detectors. Finally, we present the performance of the selected detector.
Anti-Obfuscation Techniques: Recent Analysis of Malware Detection
Authors: Gorment Nor Zakiah , Selamat Ali , Krejcar Ondrej
Published: September 2022

One of the challenging issues in detecting the malware is that modern stealthy malware prefers to stay hidden during their attacks on our devices and be obfuscated. They can evade antivirus scanners or other malware analysis tools and might attempt to thwart modern detection, including altering the file attributes or performing the action under the pretense of authorized services. Therefore, it’s crucial to understand and analyze how malware implements obfuscation techniques to curb these concerns. This paper is dedicated to presenting an analysis of anti-obfuscation techniques for malware detection. Furthermore, an empirical analysis of the performance evaluation of malware detection using machine learning algorithms and the obfuscation techniques was conducted to address the associated issues that might help researchers plan and generate an efficient algorithm for malware detection.
Infected Mosquito Detection System Using Spectral Analysis
Authors: Haro Marco , Nakano-Miyatake Mariko , Cime-Castillo Jorge , Lanz-Mendoza Humberto , Gonzalez-Lee Mario , Perez-Meana Hector
Published: September 2022

Considering that an accurate detection of infected mosquitos may directly avoid the propagation of mosquito-borne disease; in this paper, we propose a detection system of infected mosquitos by Dengue virus type II, that uses seven spectral feature measures, which are applied to the spectrogram estimated from wingbeat signal emitted by mosquito’s flight. To evaluate the proposed system, we construct our own dataset with 20 infected Aedes aegypti by Dengue and 20 healthy ones. Seven spectral analysis methods, such as Spectral Rolloff, Spectral Centroide, etc., are applied to the spectrogram obtained by using the Short Time Fourier Transform (STFT) to generate feature vectors with 15 elements. These are feed into common machine learning techniques, such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Logistic Regression to detect the infected mosquitos differentiating form the healthy ones. Evaluation results show that, the best detection accuracy (84.32%) is provided by the KNN with K=3.
The making of digitalization: Like nailing jelly to a wall
Authors: Heidlund Marcus , Gidlund Katarina L.
Published: September 2022

Though ‘digitalization’ has become a buzzword and policy objective in public-sector development, the struggle to grasp and define it as a modern phenomenon continues. Furthermore, research has long shown that it is difficult to extract the value with which digitalization is associated. Against this backdrop, the aim of this paper is to uncover the enactment by a specific set of actors of digitalization as production and reproduction practices. We interviewed a group of governmentally sanctioned regional digitalization coordinators to identify how digitalization was translated and implemented by the appointed professionals. We applied Orlikowski and Gash’s three levels of technology (nature, strategy, and use) and combined these with Feenberg’s matrix of four views on technology to produce an analytical framework. Our findings show that the making of digitalization can be described like ‘nailing jelly to a wall’, owing to the lack description of its capabilities and functionalities, coupled with a raison d’etre that is highly elusive beyond ‘change’, in very general terms.
A Combination of Neurofilament Light, Glial Fibrillary Acidic Protein, and Neuronal Pentraxin-2 Discriminates Between Frontotemporal Dementia and Other Dementias
Authors: Bolsewig Katharina , Hok-A-Hin Yanaika S. , Sepe Federica N. , Boonkamp Lynn , Jacobs Dirk , Bellomo Giovanni , Paoletti Federico Paolini , Vanmechelen Eugeen , Teunissen Charlotte E. , Parnetti Lucilla , Willemse Eline A. J.
Published: September 2022

Background: The differential diagnosis of frontotemporal dementia (FTD) is still a challenging task due to its symptomatic overlap with other neurological diseases and the lack of biofluid-based biomarkers. Objective: To investigate the diagnostic potential of a combination of novel biomarkers in cerebrospinal fluid (CSF) and blood. Methods: We included 135 patients from the Center for Memory Disturbances, University of Perugia, with the diagnoses FTD (n = 37), mild cognitive impairment due to Alzheimer’s disease (MCI-AD, n = 47), Lewy body dementia (PDD/DLB, n = 22), and cognitively unimpaired patients as controls (OND, n = 29). Biomarker levels of neuronal pentraxin-2 (NPTX2), neuronal pentraxin receptor, neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) were measured in CSF, as well as NfL and GFAP in serum. We assessed biomarker differences by analysis of covariance and generalized linear models (GLM). We performed receiver operating characteristics analyses and Spearman correlation to determine biomarker associations. Results: CSF NPTX2 and serum GFAP levels varied most between diagnostic groups. The combination of CSF NPTX2, serum NfL and serum GFAP differentiated FTD from the other groups with good accuracy (FTD versus MCI-AD: area under the curve (AUC) [95% CI] = 0.89 [0.81–0.96]; FTD versus PDD/DLB: AUC = 0.82 [0.71–0.93]; FTD versus OND: AUC = 0.80 [0.70–0.91]). CSF NPTX2 and serum GFAP correlated positively only in PDD/DLB (ρ= 0.56, p < 0.05). NPTX2 and serum NfL did not correlate in any of the diagnostic groups. Serum GFAP and serum NfL correlated positively in all groups (ρ= 0.47–0.74, p < 0.05). Conclusion: We show the combined potential of CSF NPTX2, serum NfL, and serum GFAP to differentiate FTD from other neurodegenerative disorders.
Brain Deep Medullary Veins on 7T MRI in Dutch-Type Hereditary Cerebral Amyloid Angiopathy
Authors: van Harten Thijs W. , Heijmans Anne , van Rooden Sanneke , Wermer Marieke J.H. , van Osch Matthias J.P. , Kuijf Hugo J. , van Veluw Susanne J. , Greenberg Steven M. , van Buchem Mark A. , van der Grond Jeroen , van Walderveen Marianne A.A.
Published: September 2022

Background: Deep medullary vein (DMV) changes occur in cerebral small vessel diseases (SVD) and in Alzheimer’s disease. Cerebral amyloid angiopathy (CAA) is a common SVD that has a high co-morbidity with Alzheimer’s disease. So far, DMVs have not been evaluated in CAA. Objective: To evaluate DMVs in Dutch-type hereditary CAA (D-CAA) mutation carriers and controls, in relation to MRI markers associated with D-CAA. Methods: Quantitative DMV parameters length, tortuosity, inhomogeneity, and density were quantified on 7 Tesla 3D susceptibility weighted MRI in pre-symptomatic D-CAA mutation carriers (n = 8), symptomatic D-CAA mutation carriers (n = 8), and controls (n = 25). Hemorrhagic MRI markers (cerebral microbleeds, intracerebral hemorrhages, cortical superficial siderosis, convexity subarachnoid hemorrhage), non-hemorrhagic MRI markers (white matter hyperintensities, enlarged perivascular spaces, lacunar infarcts, cortical microinfarcts), cortical grey matter perfusion, and diffusion tensor imaging parameters were assessed in D-CAA mutation carriers. Univariate general linear analysis was used to determine associations between DMV parameters and MRI markers. Results: Quantitative DMV parameters length, tortuosity, inhomogeneity, and density did not differ between pre-symptomatic D-CAA mutation carriers, symptomatic D-CAA mutation carriers, and controls. No associations were found between DMV parameters and MRI markers associated with D-CAA. Conclusion: This study indicates that vascular amyloid-β deposition does not affect DMV parameters. In patients with CAA, DMVs do not seem to play a role in the pathogenesis of MRI markers associated with CAA.
Relationships Between the Deposition of Amyloid-β and Tau Protein and Glymphatic System Activity in Alzheimer’s Disease: Diffusion Tensor Image Study
Authors: Ota Miho , Sato Noriko , Nakaya Moto , Shigemoto Yoko , Kimura Yukio , Chiba Emiko , Yokoi Yuma , Tsukamoto Tadashi , Matsuda Hiroshi
Published: September 2022

Background: Amyloid-β (Aβ) and tau protein accumulation in the brain is thought to be one of the causes of Alzheimer’s disease (AD). Recent study found that the glymphatic system was waste drainage system in the brain and promoting the elimination of Aβ and tau protein. Objective: We evaluated the relationships between the glymphatic system activity and the Aβ and tau protein deposition. Methods: Subjects were 21 patients with AD and 36 healthy subjects who underwent diffusion tensor imaging (DTI) scan and the positron emission tomography (PET) using with the Aβ tracer: 11C-PiB and the tau/inflammatory tracer: 18F-THK5351. We computed diffusion tensor image analysis along the perivascular space (DTI-ALPS) index as the proxy of glymphatic system activity, and estimated the relationships between the DTI-ALPS index and Aβ and tau protein/inflammatory deposition. Results: We found significant negative correlations between DTI-ALPS index and the standard uptake value ratio (SUVR) of 11C-PiB in the bilateral temporal and left parietal cortices and left posterior cingulate gyrus in all subjects. Further, we detected significant negative correlations between DTI-ALPS index and the SUVR of 18F-THK5351 in the bilateral temporal cortices and right parietal cortex in all participants, too. Conclusion: Our data suggested that DTI-ALPS index was a good biomarker for the evaluation of Aβ and tau deposition and neuroinflammation, and this marker might be effective to estimate the glymphatic system activity.
The architecture of network virtual experiment environment based on cloud computing
Authors: Liu Zhijie
Published: September 2022

In order to improve the user access success rate, cloud service success rate and experiment resource sharing and retrieval efficiency of network virtual experiment environment, a network virtual experiment environment architecture based on cloud computing was proposed. Through the CVM cloud virtual experiment platform and LIMP Laboratory integrated management platform, the system architecture of network virtual experiment environment is designed. Based on cloud computing, the access control algorithm of network virtual experiment environment is designed, and the resource sharing of network virtual experiment environment is realized by data mining technology. The experimental results show that the architecture proposed in this paper has a high success rate of user access and cloud service, and a good efficiency of experimental resource sharing and retrieval, indicating that the architecture proposed in this paper has a good application effect.
Stability control of cyclic signal transmission in high power drive circuit
Authors: Yan Honglai
Published: September 2022

In order to reduce the influence of noise on the stability of cyclic signal transmission and improve the effect of signal control, a method to control the stability of cyclic signal transmission of high-power driving circuit is proposed. The main components of the driving circuit and the characteristics of its cyclic signal are analyzed. According to the analysis results, a cyclic signal transmission interference detection module is designed, and the source interference detection is realized by using this module; Considering the electromagnetic influence of the circulating signal and the power part, the optocoupler isolation method is used to isolate the circulating signal; On the basis of detecting and isolating the transmission interference of circulating signal, the primary pulse width modulation signal and the secondary fault feedback signal are modulated by a single pulse transformer to realize the bidirectional transmission design of circulating signal; The internal optimization design of the high-power drive circuit is carried out, the error correction of the signal transmission stability control is carried out by using the linearized small interference error compensation method, and the empirical mode decomposition method is applied to the cyclic signal analysis of the high-power drive circuit to solve the cross term interference problem in the cyclic signal analysis. Finally, the stability control of cyclic signal transmission is realized by using double quasi PR controller. The experimental results show that the signal transmission time of this method is short, the minimum value is less than 0.5 s, the signal transmission deviation is only 0.22, the transmission rate is high, the signal transmission deviation is small, and the signal waveform is stable, which fully shows that its control effect is good.
Exploring a new method to identify hidden danger space in the post-pandemic period: Taking Beian city in China as a case
Authors: Sun Ming , Liu Mengmeng
Published: September 2022

COVID-19 has become a major public health emergency in the world, which seriously affects the normal operation of cities. Epidemic prevention and control is not only needed in big cities, but also in small and medium-sized cities. In view of this, the paper takes Beian city, China as the research area. This study establishes a street network model through spatial syntax, and predicts the crossing potential and arrival potential of its street network. This will play a reference role for traffic flow control in Beian city. The article uses emerging data. Through GIS spatial analysis method, we identify the hidden danger space of city. Therefore, this summarizes the places where people are easy to gather and some problems of the current situation of the city. The results show that: (1) Beian bridge and Wuyuer street have a good traffic potential. The intersection of Longjiang Road and Beidahuang street and the intersection of Tianyuan North Road and Baocheng road have good accessibility. (2) The intersection of Ping’an Street and Shanghai road is a potential hidden danger space of the city, and the focus of epidemic prevention and control. (3) The coverage rate of urban community medical services to residential land is 58.61%, and the existing medical infrastructure is insufficient. Under public health emergencies, the paper will argue a new development ideas for health and safety small town planning by visualizing the hidden danger space of the city.
Energy efficient resource optimization algorithm for cloud infrastructure
Authors: Shally  , Kumar Sunil , Gupta Punit
Published: September 2022

The proliferation of cloud computing infrastructure has increased the energy demand remarkably. Energy-efficient resource management is essential for running a cost effective and environment friendly data center. Virtual Machine (VM) consolidation is a well-accepted method for reducing the energy consumption of the cloud data center. Quality of service is an equally important aspect of cloud services. VM migrations caused by consolidation often cause degradation in QoS. These two parameters have been dealt with individually in most research and very few addressed both energy efficiency and QoS simultaneously. We have proposed a new Energy and QoS Efficient (EQSE) VM selection and placement method for improving the energy efficiency along with quality of service (QoS). VM selection and placement are two critical steps of VM consolidation. EQSE uses Resource Gap Minimization (RGM) algorithm for VM selection and Utilization-Aware Best-Fit Decreasing (UABFD) algorithm for placement of these VMs. EQSE along with dynamic thresholds reduces energy consumption and improves the quality of service by reducing the number of VM migrations. CloudSim simulation performed on PlanetLab data establishes the superiority of the proposed method compared to the existing state of the art methods of VM consolidation.
ADGWN: adaptive dual-channel graph wavelet neural network for topology identification of low-voltage distribution grid
Authors: Hu Kekun , Zhu Zheng , Xu Yukun , Jiang Chao , Dai Chen
Published: September 2022

Maintaining accurate topology of the low-voltage distribution grid (LVDG) are critical to the operations and maintenance of power distribution systems. However, this goal is hard to achieve due to the fast-changing LVDG topology. To this end, we focus on the abnormal customer-transformer relationships identification in the LVDG and propose an identification method based on an Adaptive Dual-channel Graph Wavelet Neural Network (ADGWN) consisting of two identical GWNs connected with the attention mechanism. In the proposed ADGWN, two GWNs learn customer embedding simultaneously from the LVDG topology graph and the feature graph that is constructed from customer electricity consumption data with the k-Nearest Neighbor algorithm. The topology identification results of these two GNNs are then adaptively fused to form the ultimate identification result with the attention mechanism by dynamically balancing the aforementioned two types of information. To validate the performance of our proposed method, we further build a real benchmarking dataset from customer electricity consumption data collected from a certain substation in Shanghai, China. Experimental results show that the proposed ADGWN achieves 100.0% LVDG topology identification accuracy and significantly outperforms the state-of-the-art. Our proposed method can help operators of power distribution systems maintain the accurate topology in a timely and economic manner.
A hybrid control technique for small signal stability analysis for microgrids under uncertainty
Authors: Karthika J. , Rajkumar M. , Vishnupriyan J.
Published: September 2022

Distributed generators (DG) with inverter based on renewable sources are generally utilized in microgrids. Most of these sources work in droop control mode to effectively share the load. Higher droop is chosen on these systems to recover dynamic power sharing. This paper proposes a Hybrid Control Technique for Small Signal Stability Analysis for Microgrids under Uncertainty. The proposed topology is to recover the capacity of power system is used to restore the normal operating condition. The proposed hybrid technique is the combination of chaotic Henry gas solubility optimization (CHGSO) and recalling-enhanced recurrent neural network (RENNN) and therefore called the CHGSO-RENNN technique. The proposed technique is used to optimally predict the internal and external current loop control parameters in light and the variety of power and current parameters. The small stability is revealed through the working conditions of the whole machine. The overall stability of the small signal is investigated in a linear model so that both source and load are used to characterize the state matrix of the frame that is used for eigenvalue examination. The PI controller gain parameters are optimally tuned and the controller offers reliable frame operation. The proposed technique is performed on MATLAB/Simulink work platform.
Multi-attention guided and feature enhancement network for vehicle re-identification
Authors: Yu Yang , He Kun , Yan Gang , Cen Shixin , Li Yang , Yu Ming
Published: September 2022

Vehicle Re-Identification (Re-ID) aims to discover and match target vehicles in different cameras of road surveillance. The high similarity between vehicle appearances and the dramatic variations in viewpoints and illumination cause great challenges for vehicle Re-ID. Meanwhile, in safety supervision and intelligent traffic systems, one needs a quick efficient method of identifying target vehicles. In this paper, we propose a Multi-Attention Guided Feature Enhancement Network (MAFEN) to extract robust vehicle appearance features. Specifically, the Fusing Spatial-Channel information multi-receptive fields Feature Enhancement module (FSCFE) is first proposed to aggregate richer and more representative multi-receptive fields features at different receptive fields sizes. It also learned the spatial structure information and channel dependencies of the multi-receptive fields features and embedded them to enhance the feature. Then, we construct the Spatial Attention-Guided Adaptive Feature Erasure (SAAFE) module, which uses spatial attention to erase the most distinguishing features. The network’s attention is shifted to potentially salient features to strengthen the ability of the network to extract salient features. In addition, a multi-loss knowledge distillation (MLKD) method using MAFEN as a teacher network is designed to improve computational efficiency. It uses multiple loss functions to jointly supervise the student network. Experimental results on three public datasets demonstrate the merits of the proposed method over the state-of-the-art methods.
Research on internal control optimization of Financial Sharing Center Based on fuzzy mathematics theory and quality function deployment theory
Authors: Lu Shuya , Cao Minglei
Published: September 2022

Through scientific theoretical methods, we take the internal control optimization of the Financial Sharing Center of H company as the research object. Firstly, we introduce the Financial Sharing Center and the development background and research significance of internal control under this mode, sort out the existing international research and related concepts, analyze the problems existing in the internal control stage of the Financial Sharing Center, and analyze the problems one by one from the five elements of internal control. What is more innovative is that we use the quality function deployment theory in the field of system science, combined with the intuitionistic fuzzy set theory, G1 method and entropy method in fuzzy mathematics to evaluate the five elements affecting the internal control optimization of the Financial Sharing Center of H company, and give the priority of optimization in theory. Finally, according to the implementation conditions of the Financial Sharing Center, this paper puts forward relevant countermeasures and suggestions to optimize the internal control of the financial sharing mode of H company, which can also provide experience for other enterprises that are building the Financial Sharing Center.