bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Enhancement of Induction Motor Based on Three-Level T-Type Inverter Using DTC-SVM
Authors: Abbas Ismail M. , Hassan Raaed F.
Published: December 2022

Induction motors (IM) that are driven using the conventional direct torque control algorithm (DTC) suffer from vital drawbacks which are high ripples in the torque and flux. These ripples result due to the use of a look-up table and hysteresis comparators which causes variable switching frequency. Moreover, the use of a traditional two-level inverter leads to the production of low-quality voltage and current. The work presented in this paper proposed a modified control system to overcome these drawbacks. The proposed control system is based on the use of the space vector modulation-based DTC algorithm (DTC-SVM) for driving three-phase IM via a three-level T-Type inverter. The conventional DTC-SVM algorithm has been modified to match the work of the proposed inverter. The modification process was based on the mapping of the standard DTC-SVM algorithm in the space vector of the three-level inverter. The conventional and the modified control systems are implemented using MATLAB/Simulink package. The comparison of the standard and the modified DTC-SVM has been performed by simulation. Simulation results showed the superiority of the proposed algorithm in terms of reducing ripple in torque and flux and improving the quality of current and voltage supplied to the motor.
Psychometrische Prüfung des deutschsprachigen
„Neurologischen Fragebogens zur Müdigkeit bei Multipler Sklerose
(NFI-MS-G)“ bei Rehabilitanden mit Multipler Sklerose
Authors: Seebacher Barbara , Horton Mike C. , Reindl Markus , Brenneis Christian , Ehling Rainer , Deisenhammer Florian , Mills Roger J.
Published: December 2022

Ziel Ziel dieser Studie war es, ein Instrument zur
Selbsteinschätzung von Fatigue für Multiple Sklerose (MS)
Patientinnen und Patienten zu erstellen, welches das Konstrukt der Fatigue
umfassend abbildet und anhand der Annahmen des Rasch-Modells, entwickelt wurde.
Der Neurological Fatigue Index – Multiple Sclerosis (NFI-MS) basiert
sowohl auf einem medizinischen als auch von MS Betroffenen beschriebenen
Bezugsrahmen von Fatigue Symptomen und wurde stringent validiert. Daher wurde in
dieser Studie die deutsche Fassung des NFI-MS, der Neurologische Fragebogen zur
Müdigkeit bei Multipler Sklerose (NFI-MS-G), bestehend aus einer
physischen und kognitiven Subskala, validiert.

Methodik In dieser bizentrischen Studie komplettierten 309 MS Betroffene
im Rahmen ihrer ambulanten Rehabilitation oder≥2 Monate vor bzw. nach
ihrer stationären Rehabilitation zu zwei Testzeitpunkten innerhalb von
14–21 Tagen den NFI-MS-G sowie weitere Fragebögen. Die
Validierung erfolgte anhand von Korrelationen mit etablierten Fragebögen
und der Rasch Analyse. Zusätzlich wurden psychometrische
Gütekriterien der Known-Groups Validität, internen Konsistenz,
Test-Retest Reliabilität, Messgenauigkeit und Lesbarkeit evaluiert.
Abschließend wurden die englische NFI-MS und deutsche NFI-MS-G
miteinander verglichen, um zu überprüfen, ob die Sprachversionen
einander entsprechen.

Ergebnisse Die NFI-MS-G zeigte eine gute interne
Konstruktvalidität, konvergente und Known-Groups Validität und
interne Konsistenz (Cronbach Alpha 0,84–0,93). Die physische Subskala
zeigte geringgradige Abhängigkeiten zwischen Items 1 und 7, 2 und 3 und
4 bis 6, die mittels einer Kombination betroffener Items zu Testlets behandelt
werden konnten. Die physische und kognitive Subskala zeigten sich
eindimensional, nicht jedoch die Summenskala. Anstelle der Summenskala wurde ein
2-Domänen Subtest erstellt, der ein Fatigue-Konstrukt höherer
Ordnung misst. Des Weiteren wurde eine gute Test-Retest Reliabilität
(Konkordanzkorrelations-Koeffizient nach Lin 0,86–0,90), geringe Boden-
und Deckeneffekte, leichte Lesbarkeit und Invarianz für Gruppen
unterschiedlichen Geschlechts, Alters, Krankheitsdauer, Testzeitpunkt und
Zentrum festgestellt.

Schlussfolgerung Die deutsche Fassung des NFI-MS bildet das Konstrukt der
Fatigue umfassend ab und besitzt eine adäquate psychometrische
Güte. Die deutsche Fassung unterscheidet sich von der englischen
Originalversion hinsichtlich mangelnder Eindimensionalität der
Summenskala und geringgradiger lokaler Abhängigkeiten der physischen
Subskala, die mittels einer Testlet-Analyse ausgeglichen werden konnten.
Early phase trial of intracystic injection of large surface area microparticle paclitaxel for treatment of mucinous pancreatic cysts
Authors: Othman Mohamed , Patel Kalpesh , Krishna Somashekar G. , Mendoza-Ladd Antonio , Verco Shelagh , Abidi Wasif , Verco James , Wendt Alison , diZerega Gere
Published: December 2022

Background and study aims Mucinous pancreatic cystic lesions (PCLs) have the potential for malignant transformation, for which the only accepted curative modality is surgery. A novel intracystic therapy with large surface area microparticle paclitaxel (LSAM-PTX) may treat PCLs without local or systemic toxicities. Safety and preliminary efficacy of LSAM-PTX for the treatment of PCLs administered by endoscopic ultrasound-guided fine-needle injection (EUS-FNI) was evaluated.

Patients and methods Ten subjects with confirmed PCLs (size > 1.5 cm) received intracystic LSAM-PTX via EUS-FNI at volumes equal to those aspirated from the cyst in sequential cohorts at 6, 10, and 15 mg/mL in a standard “3 + 3” dose-escalation protocol. The highest dose with acceptable safety and tolerability was taken into the confirmatory phase where nine additional subjects received two injections of LSAM-PTX 12 weeks apart. Subjects were followed for 6 months after initial LSAM-PTX treatment for endpoints including: adverse events (AEs), tolerability, pharmacokinetic analysis of systemic paclitaxel drug levels, and change in cyst volume.

Results Nineteen subjects completed the study. No dose-limiting toxicities, treatment-related serious AEs, or clinically significant laboratory changes were reported. Systemic paclitaxel concentrations did not exceed 3.5 ng/mL at any timepoint measured and fell below 1 ng/mL by Week 2, supporting the lack of systemic toxicity. By Week 24 a cyst volume reduction (10–78 %) was seen in 70.6 % of subjects.

Conclusions Intracystic injection of LSAM-PTX into mucinous PCLs resulted in no significant AEs, a lack of systemic absorption, and resulted in reduction of cyst volume over a 6 month period.
Oxidativer Stress, Oxidantien und Antioxidantien in der Medizin
Authors: Siems Werner , Brenke Rainer
Published: December 2022

Freie Radikale sind Atome oder Moleküle mit mindestens einem ungepaarten Valenzelektron.Radikale, etwa Sauerstoff-Radikale oder auch reaktive Sauerstoffspezies (ROS) genannt, spielen bei einer Vielzahl biologischer Prozesse eine wichtige Rolle. Liegen sie im Übermaß im Körper vor, kommt es zu oxidativem Stress. Hierbei werden die Zellen und Gewebe im Körper durch freie Radikale zerstört. Dies kann verschiedene Erkrankungen mit begünstigen, wie zum Beispiel Krebserkrankungen oder Typ-2-Diabetes mellitus.

Freie Radikale entstehen durch Belastungen aus der Umwelt, zum Beispiel Chemie- oder Strahlenexposition, aber auch durch zu viel Stress, Nikotin- und Alkoholkonsum. Antioxidantien neutralisieren freie Radikale und können so Zellschäden vorbeugen. Sie finden sich zum Beispiel in verschiedenen Obst- und Gemüsesorten. Durch Bewegung und Kaltreize lässt sich zudem die Produktion körpereigener Antioxidantien ankurbeln.
Sauerstoff – immer notwendig, gezielt sparen kann helfen
Authors: Stange Rainer
Published: December 2022

Erst seit relativ kurzer Zeit werden biopositive wie -negative Folgen von Hypoxie gleichermaßen konsequent untersucht. Parallel hat sich mit der IHHT bereits eine Therapierichtung etabliert, die technisch zeitgemäß handhabbar ist und bislang keine größeren Sicherheitsprobleme erkennen ließ. Ein therapeutischer Nutzen jenseits der Leistungssteigerung für Gesunde scheint sich vor allem in Fragen der Neuroprotektion und Alternsverzögerung zu manifestieren.
Numerical simulation of aerosol permeation through microstructure of face masks coordinating with x-ray computed tomography images
Authors: Hada Kodai , Shirzadi Mohammadreza , Fukasawa Tomonori , Fukui Kunihiro , Ishigami Toru
Published: December 2022

Face masks act as air filters that collect droplets and aerosols, and they are widely used to prevent infectious diseases, such as COVID-19. Herein, we present a numerical simulation model to understand the collection behavior of aerosols containing submicron-sized droplets inside a realistic microstructure of commercially available face masks. Three-dimensional image analysis by x-ray computed tomography is used to obtain the microstructures of two types of commercial face masks, and the aerosol permeation behavior in the obtained microstructures is investigated with a numerical method coupled with computational fluid dynamics and a discrete phase model. To describe the complex geometry of the actual fibers, a wall boundary model is used, in which the immersed boundary method is used for the fluid phase, and the signed distance function is used to determine the contact between the droplet and fiber surface. Six different face-mask domains are prepared, and the pressure drop and droplet collection efficiency are calculated for two different droplet diameters. The face-mask microstructure with the relatively larger pore, penetrating the main flow direction, shows a high quality factor. A few droplets approach the pore accompanied by fluid flow and fibers collect them near the pore. To verify the effect of the pore on the collection behavior, six different model face-mask domains of variable pore sizes were created. Additionally, droplet collection near the pore is observed in the model face-mask domains. Specific pore-sized model masks performed better than those without, suggesting that the large pore may enhance performance.
Effects of activity distance on dynamics of bio-molecules in the multidimensional potential energy model
Authors: Zheng Yue , Xu Junjun , Tang Ke
Published: December 2022

Activity distance, which is commonly used to describe the transformation from a bound state to a transition state in the potential energy landscape model, is the key factor in the bio-molecular system to study dynamic properties. Adopted both in phenomenological theory and the statistical model, activity distance is the fundamental parameter to describe the kinetic characteristics of bio-molecules and is usually connected with the change in the pulling force F. The effects of activity distance Δx‡ are easy to be detected in a single dimensional landscape model because the force only expresses the mechanical work −Fx, which mainly overlaps with the fluctuation of the configuration of bio-molecules. However, as the force cannot affect the transformation directly in the multidimensional landscape model, the deflection angle φ is introduced in our work to discuss the pulling force, which has partial effects on the Q dimension. By comparing the mean waiting time ⟨t⟩ under the conditions of normal kinetics and dynamic disorder, in this study, we show the typical results from the effects of activity distance on the multidimensional potential energy model.
A 5.8 GHz high-gain flexible receiving antenna for wireless power transmission
Authors: Peng Wenxiong , Li Xinyuan , Zhang Huaiqing , Liu Zhewei , Song Wei
Published: December 2022

In this paper, a 5.8 GHz, high-gain flexible receiving antenna (FRA) is proposed, which can be used for wireless power transmission (WPT) systems. The FRA is designed by an iterative process and is etched on Kapton, with a coplanar waveguide (CPW) feed. In order to improve the gain of the FRA, an air-gap and a flexible reflector are loaded, and the gain is improved from 2.79 to 9.51 dBi at 5.8 GHz. To validate the stability of FRA, the fabricated prototype uses three configurations of 80, 70, and 50 mm. The impedance matching keeps well, and the gain of the FRA can sustain above 8.96 dBi. In addition, a miniaturized WPT system was built. The measured results show that the proposed FRA has a maximum harvesting efficiency (HE) of 71.3%, and it can maintain the maximum HE above 63% in bending conditions. The lightweight, high-gain, and high HE in various cases prove the huge potential of the FRA in WPT applications.
Key properties governing sorption–desorption behaviour of poly- and perfluoroalkyl substances in saturated and unsaturated soils: a review
Authors: Kookana Rai S. , Navarro Divina A. , Kabiri Shervin , McLaughlin Mike J.
Published: December 2022

Poly- and perfluoroalkyl substances (PFAS) have been widely used worldwide over the last seven decades in >200 diverse industrial applications. Thousands of different PFAS have been used in a wide range of products, such as food packaging, water-repellent and stain-resistant clothing and fire-fighting foams. Partially due to their extreme stability and high mobility, PFAS are now ubiquitous in the environment. Due to their prolonged persistence, some PFAS have been added to the list of persistent organic pollutants. Sorption is one of the fundamental processes that governs environmental fate and effects of organic chemicals. In recent years, a significant body of literature has been published on sorption of PFAS in soils. However, there are conflicting reports about the soil or sediment properties that may be used to predict the mobility of PFAS in the soil environment. This is not surprising because PFAS have complex chemical properties (anionic, cationic and zwitterionic charges together with surface active properties) that influence their sorption–desorption behaviour. Additionally, PFAS show a fluid–water interfacial adsorption phenomenon and such interfaces offer additional retention mechanisms in unsaturated or oil-contaminated soils. In this review, we analyse the literature on sorption and desorption of PFAS to evaluate the dominant soil and solution properties that govern their sorption–desorption behaviour in saturated and unsaturated soils. We also identify the knowledge gaps that need to be addressed in order to gain a sound understanding of their sorption–desorption behaviour in saturated as well as unsaturated soils.
Reintroducing a Kitten to a Resident Senior Cat
Authors: Chamberlain Sally
Published: December 2022

This case study describes how to reintroduce a kitten to a resident senior cat after the initial introduction did not go well. The resident cat did not accept the kitten and was spending more time outside. When she came into contact with the kitten, she would hiss and growl. A slow reintroduction was carried out which was unique to this particular set of circumstances by allowing the kitten to interact in a controlled way with the older cat whilst on a harness and lead outside. A similar method can also be used indoors with a barrier in-between the cats, tailored to suit each case, which is described under Option 2 in the ‘Courses of Action and Treatment’ section.
Economic impacts of variable rate nitrogen fertilization: Input saving and yield increase in cereals
Authors: Medici Marco , Canavari Maurizio
Published: December 2022

The purpose of this study is to discuss the economic impacts stemming from variable-rate (VR) nitrogen fertilization, one of the main precision agriculture practices. Economic impacts are related to reduced nitrogen use and increased crop yields thanks to a better distribution of inputs, net from possible spatial and temporal uncertainty. This paper reviews N=31 case studies (in 29 articles) that compared the performance of VR nitrogen applications versus uniform treatments. The comparisons covered nitrogen fertilization for cereal crops, in particular wheat and maize, for different years and in different countries. Findings highlight relevant changes in amounts of nitrogen applied, with the evidence of higher nitrogen efficiency resulting in reduced operating costs, while changes in crop yields are less evident: VR applications and uniform applications substantially reach the same production level, and higher nitrogen use efficiencies are achievable without significantly compromising yields. Overall, net economic impacts are in favour of VR fertilization. This work can raise farmers’ and other stakeholders’ knowledge of the actual economic impacts stemming from the adoption of VR fertilization and helps policymakers to understand the economic impact of precision agriculture and the need to foster sustainability-based policies.
Memory for polarization state of light based on atomic frequency comb in a 153Eu:Y2SiO5 crystal
Authors: Akhmedzhanov R A , Gushchin L A , Kalachev A A , Nizov N A , Nizov V A , Sobgayda D A , Zelensky I V
Published: December 2022

In this work we realize an optical memory for polarization state of light that is based on atomic frequency comb protocol in a 153Eu:Y2SiO5 crystal. In order to compensate for the absorption and refraction anisotropy of the crystal we use a setup with multiple passes through the sample with intermediary rotation of polarization. We obtain memory efficiency of ∼25% with a storage time of ∼165 ns and fidelity of over 85%.
A Double-Layer Voltage Control Model for Distributed Photovoltaic in Distribution Network
Authors: Zhao Zhiyu , Zhao Tianqi , Xu Peng , Wang Zesen , Xie Huan , Li Xuan , Li Yu
Published: December 2022

With the increasing penetration of distributed photovoltaic (PV) in distribution network (DN), and the randomness of PV power output, so the DN with PV is prone to voltage fluctuation or even overvoltage. In this paper, a double-layer distributed PV voltage control strategy is proposed. This strategy takes full advantage of reactive power of PV inverter connected to DN and aims at reducing the loss of uploading power of PV, so as to achieve collaborative control of buses voltage. It adopts the double-layer control strategy of PV system in DN, as well as the three modes switching of maximum power point tracking (MPPT), reactive power regulating and power factor regulating of PV. On the premise of realizing the effective control of buses voltage, it can reduce the loss of uploading power of PV to the greatest extent. Finally, the proposed distributed PV voltage control strategy is verified through a typical DN case based on the real time digital simulation (RTDS).
A Large-Range Ultrasonic Distance Measuring Device Based on Improved Time Difference Method
Authors: Liao Yubin , Ye Qingzhou , Zhang Maolin
Published: December 2022

Ultrasonic ranging by using the time difference method generally has the problems of inaccurate measurement of echo arrival time and small range. To solve the above problems, firstly, this paper proposes a method to detect the arrival time of the echo by using the inflection point of the echo envelope with the combination of logarithmic characteristics of the logarithmic amplifier and improves the peak detection of the traditional TDOA by changing the characteristic point of the arrival time of the echo. Secondly, an ultrasonic distance measuring device is designed, in which the transmitting power and the sensitivity of the receiving end can be adjusted automatically with the echo signal strength to improve the measurement accuracy and broaden the measuring range. The experimental results show that the range of the device is expanded from 0.5-12 m to 0.3-20 m, and the distance measurement error is reduced from 1% to 0.5% when the improved time difference method is adopted and the self-tuning of the transmitting and receiving parameters is enabled. It shows that the improved time difference method can improve the measurement accuracy and can effectively expand the ultrasonic ranging range by using the self-tuning of the transmitting and receiving parameters.
Distribution Network Distributed Energy Storage Configuration Optimization Method Considering Variance of Network Loss Sensitivity
Authors: Shi Yan , Huang Maoyi
Published: December 2022

With the wide application of distributed generation technology, in order to maintain the stable and safe operation of the distribution network, this paper considers the uncertainty of power generation and a load of distributed energy storage. It takes the distribution network with distributed energy storage as the research object, models and analyzes the optimization problem, and studies the problem of DG configuration by using the reinforcement learning method. In the case of distributed grid connection, the voltage distribution change of the distribution network and the impact of network loss are analyzed. The line power flow of the distribution network is calculated by using the MATLAB platform as a platform, and the power flow calculation of the distribution network is simulated and analyzed by the MATLAB platform. The system loss is significantly reduced. The experimental results show that the system loss variance is 29.19. After adding energy storage, the loss variance is 14.77, which is reduced by 49.41%. According to the scheme, the voltage stability and operating loss of the system can be effectively improved.
Identification Technology of Relationship Between User Meter and Transformer Based on Spatial-Temporal Correlation of Data
Authors: Ye Aliaosha , Zheng Guoquan , Zhu Enguo , Lu Jizhe
Published: December 2022

Due to the inability to accurately gain the changes of transformer archives, there are often problems such as confusion and loss of control of the station area archives in the electricity consumption information collection system, which seriously affects the work of line loss management and fault operation and maintenance, and it is difficult to achieve refined management. Existing manual identification methods are time-consuming and labor-intensive, while the dedicated device identification method is costly and requires a device-independent identification technology. Aiming at the above problems, a data analysis method based on temporal and spatial correlation is studied to analyze the temporal and spatial correlation of the voltage data of the power collection equipment. On this basis, use the classification method in data mining to divide collection equipment of each station area into one category, and calculate the probability that the acquisition equipment to be identified belongs to each category, to determine the belonging relationship of its station area. By simulating the user situation of the real station area, the simulation verifies the effectiveness of the intelligent station area identification method based on the spatial and temporal correlation of data, which can not only ensure the accuracy and efficiency of station area identification, but also does not depend on equipment and labor, and can meet the application requirements.
Land Subsidence Time Series Prediction Method Based on LSTM-AMSGD
Authors: Qian Cheng , Shi Menglu , Lv Xiaoxia , Wu Dicong , Du Xiang , Liu Jing
Published: December 2022

Accurate prediction of geological subsidence is of great importance for geological hazard risk assessment. Various existing prediction models do not take into account the time correlation between geological subsidence, and the prediction effect lacks practical significance. In this paper, an LSTM-AMSGD-based land subsidence prediction method is proposed. Firstly, the high-precision time series inversion results of large-area land surface deformation are obtained by the small baseline interference technique with multiple principal image coherent targets. Secondly, a recurrent neural network (LSTM-AMSGD) is used as the network architecture. The final cumulative subsidence prediction error is within 0.3 mm, and the single-step prediction of more than 400,000 observation points can be completed in 126s. Therefore, the LSTM-AMSGD model in this paper is effective for the prediction of geological subsidence.
Detection and Tracking of Infrared Small Targets in Complex Dynamic Backgrounds by Using Image Registration and Pipeline Filter
Authors: Zhu Zhiping , Li Hongxia , Xia Mingxia
Published: December 2022

This paper propses an infrared small target detection method in complex dynamic backgrounds in sequence images by using image registration and pipeline filter. For dynamic scenes caused by camera movements, registration of image frames and reference frame images is conducted by using the feature point matching algorithm. Next, the frame difference method is used to detect small mobile target in video image sequences. Finally, the impact of ground clutter noise and random noise are eliminated by using a pipeline filter to precisely track the trajectory of small moving targets. The experiment results show that the proposed method is superior to the classic infrared small target detection algorithm in terms of accuracy and stability in complex ground backgrounds.
A Blockchain-Based IoT Terminal Trust Mechanism Management Scheme
Authors: Zhang Guanqun , Liu Mengxi , Zai Guangjun
Published: December 2022

Traditional centralized Internet of Things (IoT) management cannot effectively defend against internal attacks from compromised devices due to its own limitations, while distributed IoT node management has certain requirements for the communication environment and resource consumption of the nodes themselves. And the trust authentication of the nodes cannot be easily resolved in a distributed manner. This paper presents a blockchain-based trust management solution. Trust management of nodes based on blockchain also greatly reduces resource consumption. Specifically, the trust value is derived by weighting the historical trust value and the direct trust value, so that the evaluation node does not rely solely on historical trust data to derive its own independent trust evaluation. A separate system node level mechanism exists in the scheme, and the system increases the system node level trust value for the node when this evaluation reaches a trusted level. If this evaluation is malicious, the system node-level trust value for the evaluation is initialized. Security analysis and experiments have shown that this scheme can effectively detect malicious nodes and takes less time.
Research on Optimal Scheduling of Power System Based on Ant Colony Algorithm
Authors: Wang Haiji , Hu Jiankun
Published: December 2022

With the development of new energy technology, the installation of new energy is becoming more and more. After a large number of new energy sources are connected to the power system, the capacity of peak regulation and frequency modulation is gradually insufficient, resulting in poor stability of the power system. Aiming at the problem of poor operation stability after new energy is connected to power system, a power system optimization scheduling method based on ant colony algorithm is proposed. In the model, the objective function is to minimize the total operating cost. The improved ant colony algorithm is used to solve the optimal scheduling model, and the effectiveness of the method is verified by simulation. The results show that this method has better ability of peak regulation and frequency modulation after new energy is added to the power system network, the frequency value and active power value of the power system are reduced, the load fluctuation value of the grid is reduced obviously, and the operation of the power system is more stable.
Simulation Research of Electricity-Hydrogen Coupled DC Microgrid Based on Parallel Computing
Authors: Wu Yetian , Bo Yaolong , Zhao Bo , Xia Yanghong , Wei Wei
Published: December 2022

Electricity-hydrogen coupled DC microgrid is of great significance for energy structure adjustment and efficient consumption of renewable energy. However, at present, such systems lack high-precision simulation support, and the transient simulation technology for large-scale microgrid systems is not perfect. In order to solve these problems, this paper form an electricity-hydrogen coupled DC microgrid simulation platform, and studies the function realization and the efficiency improvement of transient simulation. Firstly, the Euler algorithm is adopted to realize the transient simulation of the microgrid system for the functional requirements of the electricity-hydrogen coupled DC microgrid. Secondly, for different system sizes and computing platforms, an adaptive parallel computing optimal mode selection algorithm is proposed to improve the simulation efficiency. The experimental results show that the algorithm improves the computing efficiency of the large-scale electricity-hydrogen coupled DC microgrid system by about 40%.
Research on Power Grid Over-voltage Anomaly Data Management Based on the Improved Clustering Algorithm
Authors: Jia Lixia , Zeng Xiangming , Lin Fangman
Published: December 2022

The relational database uses distributed storage for grid over-voltage anomaly data, which lacks the division of the anomaly data, resulting in a long query time for anomaly data management. For this reason, the research of grid over-voltage anomaly data management based on the clustering algorithm is proposed. The clustering algorithm is combined with the outlier detection to divide the anomaly data and improve the query efficiency. The data are classified according to their characteristics. Row storage is selected as the main storage method for grid over-voltage anomaly data, and a three-dimensional model library is used to build out the management framework of the anomaly data to realize the efficient management of the anomaly data. In the experiment, the query time consumption of the proposed method is tested, and the analysis of the experimental results shows that the proposed method has a high query efficiency in managing the grid over-voltage anomaly data.
Estimation of Zernike polynomials for a highly focused electromagnetic field using polarimetric mapping images and neural networks
Authors: Ahmadi Kavan , Carnicer Artur
Published: December 2022

In this communication, we present a method to estimate the aberrated wavefront at the focal plane of a vectorial diffraction system. In contrast to the phase, the polarization state of optical fields is simply measurable. In this regard, we introduce an alternative approach for determining the aberration of the wavefront using polarimetric information. The method is based on training a convolutional neural network using a large set of polarimetric mapping images obtained by simulating the propagation of aberrated wavefronts through a high-NA microscope objective; then, the coefficients of the Zernike polynomials could be recovered after interrogating the trained network. On the one hand, our approach aims to eliminate the necessity of phase retrieval for wavefront sensing applications, provided the beam used is known. On the other hand, the approach might be applied for calibrating the complex optical system suffering from aberrations. As proof of concept, we use a radially polarized Gaussian-like beam multiplied by a phase term that describes the wavefront aberration. The training dataset is produced by using Zernike polynomials with random coefficients. Two thousand random combinations of polynomial coefficients are simulated. For each one, the Stokes parameters are calculated to introduce a polarimetric mapping image as the input of a neural network model designed and trained for predicting the polynomial coefficients. The accuracy of the neural network model is tested by predicting an unseen dataset (test dataset) with a high success rate.
Comparison between the scanning pentaprism and the Hartman method for wavefront analysis
Authors: Nuno M. Gonçalves , Abreu Manuel , Alves D. Castro
Published: December 2022

Techniques for wavefront measurement have many applications as optics systems for astronomy and as verification tests for optical surfaces. The development of large aperture optical systems drives the search for low cost and high-resolution wavefront detection sensors. The Hartman technique and its variations (i.e the Shack-Hartman sensor) are the current standards for the characterization of low-order optical aberrations, such as defocus and spherical. The scanning pentaprism method is presented as a simple and low-cost method for the verification of such aberrations. In this method, a transverse section of a wavefront is scanned and sampled into a series of sub-wavefronts with smaller apertures. The relative positions of the produced centroids are measured relative to a calibrated position. This allows for the determination of the optical path difference along the section and consequently the wavefront error. Both techniques were used as tools for collimating a telescope that is part of the on-ground support equipment of ESA PLATO mission. In this work, the results from both methodologies are compared.
Detection of Alzheimer’s by Machine Learning-assisted Vibrational Spectroscopy in Human Cerebrospinal Fluid
Authors: Arévalo Laura A. , Antonova Olga , O’Brien Stephen A. , Singh Gajendra Pratap , Seifert Andreas
Published: December 2022

Nowadays, the diagnosis of Alzheimer’s disease is a complex process that involves several clinical tests. Cerebrospinal fluid contains common Alzheimer-related biomarkers that include amyloid beta 1-42 (Aβ1-42) and tau proteins. In this work, we propose vibrational spectroscopy techniques supported by machine learning for the detection of biomarkers in cerebrospinal fluid that are related with Alzheimer’s by prediction models. Vibrational spectroscopy provides the entire biochemical composition of the body fluid, and thus, small but typical physiological changes related with the pathology can be ascertained. Within a machine learning framework, Raman and FTIR spectra were analyzed, which were taken from samples of healthy volunteers in comparison with samples from patients clinically diagnosed with Alzheimer’s. We find that a logistic regression model can discriminate between healthy control and Alzheimer’s patients with a precision of 98%, when the input for the model combines data from both vibrational spectroscopy methods. Our approach shows high discriminative capabilities and constitutes a proof of concept for an alternative and accurate tool for the diagnosis of Alzheimer’s disease.
Differences in the values of anaglyphs, vectograms and cheiroscopes on participants with low, normal, and high AC/A ratio
Authors: Pena-Verdeal Hugo , Noya-Padin Veronica , Nores-Palmas Noelia , Sabucedo-Villamarin Belen , Giraldez Maria Jesus
Published: December 2022

Purpose: Anaglyphs, Vectograms and Cheiroscopes are visual therapy materials based on red/green, polarized, or black/white targes that used similar but slightly different images for each eye to train fusion and vergence skills. This study aimed to analyse the differences in the results obtained on those devices on participants with low, normal, or high AC/A ratios. Material and methods: three groups of volunteer participants were recruited based on their recent clinical history among patients attending the Optometry Clinic of the centre: 15 participants with low AC/A, 15 participants with normal AC/A and 15 participants with High AC/A ratios. None of them was under any type of medication, have an ocular or systemic disease, or were performing any kind of visual training plan that could affect the study. In two sessions one week apart, following the manufacturer’s instructions, the participants performed in a random order three visual therapy device-based training: one red/green Fixed Demand Anaglyph [FDA], one Variable Demand Polarized Vectogram [VDPV], and one based on the Wheatstone W [WW]. Participants were instructed to indicate the maximum value base-out (BO) where both image fusion and clarity was lost. Results between both sessions were compared with an analysis of differences. Results: There was found higher BO vergences results with the three devices regarding the second to the first session in the Low and Normal AC/A groups (Wilcoxon test, all p ≤ 0.013), but none in the High AC/A group (Wilcoxon test, all p ≥ 0.162). Conclusion: There is an enhancement of BO vergences in Low and normal AC/A participants but not in high AC/A participants by performing visual training with Anaglyphs, Vectograms and Cheiroscopes devices.
Capillary based hybrid fiber sensor in a balloon-like shape for simultaneous measurement of displacement and temperature
Authors: Santos João P , Bierlich Jörg , Kobelke Jens , Ferreira Marta S
Published: December 2022

In this work, a hybrid sensor based on a silica capillary in a balloon-like shape for simultaneous measurement of displacement and temperature is proposed for the first time, to the best of our knowledge. The sensor is fabricated by splicing a segment of a hollow core fiber between two single mode fibers (SMF) and by bending the fiber in a balloon shape with the capillary at the top-center position. In a transmission scheme, the SMF-capillary-SMF configuration excites an antiresonant (AR) guidance and the balloon shape enhances a Mach-Zehnder interferometer (MZI). The different responses of the interferometers to external displacement and temperature variations are conducive to a hybrid application of the sensor for simultaneous measurement of these parameters. Experimental results show that, for a capillary length of 1.2 cm and a balloon length of 4 cm, AR is insensitive to displacement and its sensitivity to temperature is 14.3 pm/°C, while the MZI has a sensitivity to displacement of 1.68 nm/mm and twice the sensitivity of AR to temperature, of 28.6 pm/°C. The proposed fiber sensor consists of only one sensing element in one configuration exciting two interferometers at the same time, which makes it of simple fabrication as well as low cost.
Strongly coupled plasmonic systems on optical fiber sensors: A study on nanomaterial properties
Authors: dos Santos Paulo S. S. , Mendes João , Dias B. , Pastoriza-Santos I. , de Almeida J. M. M. M. , Coelho Luís C. C.
Published: December 2022

New paths to increase the sensing performance of plasmonic sensors have been reported in recent years. There are several methodologies to achieve such purpose, namely by optimizing the nanostructure, nanomaterial and even the sensing platform. Recently the use nanoparticles over plasmonic thin films have been reported and shown sensitivity enhancement, when compared to a bare thin film. Nevertheless, a nanomaterial combination between NP and thin film has not been studied. In this work it was studied such plasmonic materials in order to optimize not only refractometric sensitivity but also decrease the resultant plasmonic band width. It was found that for Au, Ag and Cu thin films, the deposition of plasmonic nanoparticles resulted in an overall refractometric sensitivity and figure of merit (FOM) increase. The larger FOM increase was obtained for the Ag thin film, from 42 to 162 when coupled to Si nanoparticles. The greater sensitivity increase was achieved for a Cu thin film coupled to a Si nanoparticle, with an increase from 1745 to 3230 nm/RIU.
Modeling electron transport and multiplication in photomultiplier tubes using COMSOL Multiphysics®
Authors: Beavers J. , Huddleston K. , Hines N. , McNeil W.
Published: December 2022

Combining stochastic and finite element methods, a modeling
approach was executed that will inform new photomultiplier tube and
scintillation detector designs. Time-dependent signal formation
within a commercially available photomultiplier tube was modeled
including the release and transport of electrons from the
photocathode through the dynode stages. An ET Enterprises 9214B
photomultiplier tube was digitally reproduced using Computed
Tomography, X-ray radiography, and SolidWorks solid-modeling
software. Simulations were executed with COMSOL
Multiphysics® finite element solving
package. Stochastic models of electron emission from the
photocathode and dynodes were integrated within the COMSOL
framework. Photoelectron emission energy was modeled by combining
NaI(Tl) spectral emission characteristics and K2CsSb
photocathode quantum efficiency. Secondary electron emission yields
were produced to follow nominal photomultiplier gain, while
secondary electron energies were sampled from the Chung-Everhart
distribution. Electron emission trajectories were sampled according
to Lambert's cosine law. Coupling stochastic and finite element
models, simulation reproduced signal formation for the commercial
photomultiplier tube including timing characteristics within 9.5%
and gain within 3% over a voltage range of 900–1250 V.
Turán numbers of sunflowers
Authors: Bradač Domagoj , Bucić Matija , Sudakov Benny
Published: December 2022

A collection of distinct sets is called a sunflower if the intersection of any pair of sets equals the common intersection of all the sets. Sunflowers are fundamental objects in extremal set theory with relations and applications to many other areas of mathematics as well as to theoretical computer science. A central problem in the area due to Erdős and Rado from 1960 asks for the minimum number of sets of size

r
r

needed to guarantee the existence of a sunflower of a given size. Despite a lot of recent attention including a polymath project and some amazing breakthroughs, even the asymptotic answer remains unknown.

We study a related problem first posed by Duke and Erdős in 1977 which requires that in addition the intersection size of the desired sunflower be fixed. This question is perhaps even more natural from a graph theoretic perspective since it asks for the Turán number of a hypergraph made by the sunflower consisting of

k
k

edges, each of size

r
r

and with common intersection of size

t
t

. For a fixed size of the sunflower

k
k

, the order of magnitude of the answer has been determined by Frankl and Füredi. In the 1980’s, with certain applications in mind, Chung, Erdős and Graham considered what happens if one allows

k
k

, the size of the desired sunflower, to grow with the size of the ground set. In the three uniform case,

r
=
3

r=3

, the correct dependence on the size of the sunflower has been determined by Duke and Erdős and independently by Frankl and in the four uniform case by Bucić, Draganić, Sudakov and Tran. We resolve this problem for any uniformity, by determining up to a constant factor the

n
n

-vertex Turán number of a sunflower of arbitrary uniformity

r
r

, common intersection size

t
t

and with the size of the sunflower

k
k

allowed to grow with

n
n

.
A proof of Toponogov’s theorem in Alexandrov geometry
Authors: Hu Shengqi , Su Xiaole , Wang Yusheng
Published: December 2022

This note aims to give an elementary proof for Toponogov’s theorem in Alexandrov geometry with lower curvature bound. The idea of the proof comes from the fact that, in Riemannian geometry, sectional curvature can be embodied in geodesic variations.
Checks and balances
Authors: Ritchie Donald A.
Published: December 2022

Legislative results rank high in measuring the success of a president. But as “Checks and balances” makes clear, Congress is sensitive to its independent role as part of government. While the president, the chief legislator, sets out his legislative program in the State of the Union Address at the start of the annual session of Congress, there are many ways in which Congress can influence the success, or otherwise, of a presidency. Cabinet appointments need Senate approval; Congress has to approve treaties and holds the purse strings; and finally congressional hearings can investigate alleged misdeeds. Congress’s relationship with the judiciary, the other wing of government, is also examined.
Welcome to NanoPut
Authors: Moriarty Philip
Published: December 2022

This chapter introduces the fundamental scientific principles at the core of nanoscience, showing nanotechnology as something new, exciting, and different. It begins by defining what is meant by the terms nanotechnology and nanoscience. Nanotechnology and nanoscience dwell on size-dependent change, elaborating how changing the size of an object at the atomic, molecular, or macromolecular scale can radically change its properties. The field of nanotechnology owes much of its origins to the invention of new ultrahigh resolution microscopes, capable of resolving individual atoms and molecules but involving no optics at all. The chapter highlights remarkable instruments that are central to mapping and manipulating matter at the atomic and (sub)molecular levels.
Nanomachines
Authors: Moriarty Philip
Published: December 2022

This chapter describes how nature has harnessed nanotechnology from the start of life on Earth to perform a variety of essential functions. It analyses the sophistication, intricacy, and elegance of nature’s nanomachinery, which far outstrips anything that scientists are capable of creating. It also discusses how the natural world is awash with molecular machines that achieve unidirectional motion with no need for an external guiding intelligence. The chapter mentions the STM-powered nanocar, a biomolecular motor from the kinesin family that leaves its synthetic counterpart in the dust in very many ways. It explains how kinesin converts chemical energy into mechanical movement, transporting its molecular cargo along tracks known as microtubules.
849 EFFECTS OF INTRA-AORTIC BALLOON PUMP DELAYED DEFLATION TIMING ON CAROTID BLOOD FLOW AND CARDIAC MECHANICS
Authors: Boccellino Antonio , Sacchi Stefania , Pazzanese Vittorio , Calvo Francesco , Gramegna Mario , Ingallina Giacomo , Cappelletti Alberto , Baldetti Luca
Published: December 2022

Background

Intra-Aortic Balloon Pump (IABP) efficacy is critically affected by the inflation/deflation timing. Balloon deflation may cause a sucking effect, and a steal phenomenon on carotid flow. Delaying IABP deflation reduces the degree of this flow reversal, but at the same time exposes patients to the risk of increased proto-systolic afterload with detrimental effects on the LV.

Hypothesis

To investigate the effects of a delayed IABP deflation timing on cerebral blood flow and LV hemodynamics.

Methods

We prospectively evaluated 20 consecutive patients who received transfemoral IABP for cardiogenic shock (CS). Central aortic pressures (augmented diastolic [ADP], end-diastolic [EDP], assisted systolic [ASP] and mean aortic [MAP] pressures) were recorded from the IABP console simultaneously with ultrasound data. First ultrasound and haemodynamic measurements were collected during conventional IABP deflation timing (balloon deflation completed before onset of LV systole by automated ECG gating). Then, IABP deflation was manually delayed to the beginning of the QRS (early LV systole). After adjustment, counterpulsation was performed for a minimum of 2 minutes to achieve steady hemodynamics, then the same ultrasound and haemodynamic measurements were recollected.

Results

Mean age was 67±13 years, LVEF was 25±11%. At the carotid ultrasound, the delayed deflation increased the net forward velocity time integral (VTI) in the common carotid artery (18±9 vs 15±8 cm; p=0.001), by reducing the end-diastolic backward VTI (1±1 vs 4±2 cm; p<0.001) while having no effect on the overall forward VTI (19±9 vs 19±9 cm; p=0.294). Specifically, the delayed deflation increased the diastolic forward VTI (12±5 vs 10±4 cm]; p<0.001) while decreasing the systolic forward VTI (7±4 vs 9±4 cm]; p<0.005). On central aortic hemodynamics, the delayed deflation decreased the ASP (91±21 vs 97±20 mmHg; p=0.001), increased the EDP (60±11 vs 48±9 mmHg; p<0.001), the ADP (123±19 vs 119±19 mmHg; p<0.001) and the MAP (89±14 vs 80±12 mmHg; p<0.001). On echocardiography, the delayed deflation increased the LVOT VTI (15±4 vs 13±4 cm; p<0.001), decreased LV ejection time (202±44 vs 211±43 ms; p=0.005) but did not affect the isovolumetric contraction time (119±56 vs 119±58 ms; p=0.989), eventually reducing the total duration of LV systole (321±54 vs 330±50 ms; p=0.009).

Conclusions

In our cohort, a delayed IABP deflation strategy, evaluated by a multi-parametric yet relatively simple approach, demonstrated to be safe and was associated with both an increase cerebral perfusion and an improvement in cardiac mechanics.