bluuebunny/crossref_metadata_2025 huggingface dataset:
Interfacial Behavior of Solid- and Liquid-like Polyelectrolyte Complexes as a Function of Charge Stoichiometry
Authors: Li Hongwei , Fauquignon Martin , Haddou Marie , Schatz Christophe , Chapel Jean-Paul
Published: November 2021

We systematically investigate in this work the surface activity of polyelectrolyte complex (PECs) suspensions as a function of the molar charge ratio Z (= [-]/[+]) from two model systems: the weakly and strongly interacting poly (diallyldimethylammonium chloride)/poly (acrylic acid sodium salt) (PDADMAC/PANa) and poly (diallyldimethylammonium chloride)/poly (sodium 4- styrenesulfonate) (PDADMAC/PSSNa) pairs, respectively. For both systems, the PEC surface tension decreases as the system approaches charge stoichiometry (Z = 1) whenever the complexation occurs in the presence of excess PDADMAC (Z < 1) or excess polyanion (Z > 1) consistent with an increased level of charge neutralization of PEs forming increasingly hydrophobic and neutral surface-active species. The behavior at stoichiometry (Z = 1) is also particularly informative about the physical nature of the complexes. The PDADMAC/PANa system undergoes a liquid–liquid phase transition through the formation of coacervate microdroplets in equilibrium with macroions remaining in solution. In the PDADMAC/PSSNa system, the surface tension of the supernatant was close to that of pure water, suggesting that the PSSNa-based complexes have completely sedimented, consistent with a complete liquid–solid phase separation of an out-of-equilibrium system. Besides, the high sensitivity of surface tension measurements, which can detect the presence of trace amounts of aggregates and other precursors in the supernatant, allows for very accurate determination of the exact charge stoichiometry of the complexes. Finally, the very low water/water interfacial tension that develops between the dilute phase and the denser coacervate phase in the PDADAMAC/PANa system was measured using the generalized Young–Laplace method to complete the full characterization of both systems. The overall study showed that simple surface tension measurements can be a very sensitive tool to characterize, discriminate, and better understand the formation mechanism of the different structures encountered during the formation of PECs.
Coastal Image Classification and Pattern Recognition: Tairua Beach, New Zealand
Authors: Liu Bo , Yang Bin , Masoud-Ansari Sina , Wang Huina , Gahegan Mark
Published: November 2021

The study of coastal processes is critical for the protection and development of beach amenities, infrastructure, and properties. Many studies of beach evolution rely on data collected using remote sensing and show that beach evolution can be characterized by a finite number of “beach states”. However, due to practical constraints, long-term data displaying all beach states are rare. Additionally, when the dataset is available, the accuracy of the classification is not entirely objective since it depends on the operator. To address this problem, we collected hourly coastal images and corresponding tidal data for more than 20 years (November 1998–August 2019). We classified the images into eight categories according to the classic beach state classification, defined as (1) reflective, (2) incident scaled bar, (3) non-rhythmic, attached bar, (4) attached rhythmic bar, (5) offshore rhythmic bar, (6) non-rhythmic, 3-D bar, (7) infragravity scaled 2-D bar, (8) dissipative. We developed a classification model based on convolutional neural networks (CNN). After image pre-processing with data enhancement, we compared different CNN models. The improved ResNext obtained the best and most stable classification with F1-score of 90.41% and good generalization ability. The classification results of the whole dataset were transformed into time series data. MDLats algorithms were used to find frequent temporal patterns in morphology changes. Combining the pattern of coastal morphology change and the corresponding tidal data, we also analyzed the characteristics of beach morphology and the changes in morphodynamic states.
The Non-Tightness of a Convex Relaxation to Rotation Recovery
Authors: Alfassi Yuval , Keren Daniel , Reznick Bruce
Published: November 2021

We study the Perspective-n-Point (PNP) problem, which is fundamental in 3D vision, for the recovery of camera translation and rotation. A common solution applies polynomial sum-of-squares (SOS) relaxation techniques via semidefinite programming. Our main result is that the polynomials which should be optimized can be non-negative but not SOS, hence the resulting convex relaxation is not tight; specifically, we present an example of real-life configurations for which the convex relaxation in the Lasserre Hierarchy fails, in both the second and third levels. In addition to the theoretical contribution, the conclusion for practitioners is that this commonly-used approach can fail; our experiments suggest that using higher levels of the Lasserre Hierarchy reduces the probability of failure. The methods we use are mostly drawn from the area of polynomial optimization and convex relaxation; we also use some results from real algebraic geometry, as well as Matlab optimization packages for PNP.
Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study
Authors: Won Yuchang , Kim Seunghyeon , Park Kyung-Joon , Eun Yongsoon
Published: November 2021

This paper presents a case study of continuous productivity improvement of an automotive parts production line using Internet of Everything (IoE) data for fault monitoring. Continuous productivity improvement denotes an iterative process of analyzing and updating the production line configuration for productivity improvement based on measured data. Analysis for continuous improvement of a production system requires a set of data (machine uptime, downtime, cycle-time) that are not typically monitored by a conventional fault monitoring system. Although productivity improvement is a critical aspect for a manufacturing site, not many production systems are equipped with a dedicated data recording system towards continuous improvement. In this paper, we study the problem of how to derive the dataset required for continuous improvement from the measurement by a conventional fault monitoring system. In particular, we provide a case study of an automotive parts production line. Based on the data measured by the existing fault monitoring system, we model the production system and derive the dataset required for continuous improvement. Our approach provides the expected amount of improvement to operation managers in a numerical manner to help them make a decision on whether they should modify the line configuration or not.
Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision
Authors: Lee Gihun , Kim Mihui
Published: November 2021

Recently, artificial intelligence has been successfully used in fields, such as computer vision, voice, and big data analysis. However, various problems, such as security, privacy, and ethics, also occur owing to the development of artificial intelligence. One such problem are deepfakes. Deepfake is a compound word for deep learning and fake. It refers to a fake video created using artificial intelligence technology or the production process itself. Deepfakes can be exploited for political abuse, pornography, and fake information. This paper proposes a method to determine integrity by analyzing the computer vision features of digital content. The proposed method extracts the rate of change in the computer vision features of adjacent frames and then checks whether the video is manipulated. The test demonstrated the highest detection rate of 97% compared to the existing method or machine learning method. It also maintained the highest detection rate of 96%, even for the test that manipulates the matrix of the image to avoid the convolutional neural network detection method.
Video Packet Distribution Scheme for Multimedia Streaming Services in VANETs
Authors: Shin Yongje , Choi Hyunseok , Nam Youngju , Lee Euisin
Published: November 2021

By leveraging the development of mobile communication technologies and due to the increased capabilities of mobile devices, mobile multimedia services have gained prominence for supporting high-quality video streaming services. In vehicular ad-hoc networks (VANETs), high-quality video streaming services are focused on providing safety and infotainment applications to vehicles on the roads. Video streaming data require elastic and continuous video packet distributions to vehicles to present interactive real-time views of meaningful scenarios on the road. However, the high mobility of vehicles is one of the fundamental and important challenging issues for video streaming services in VANETs. Nevertheless, previous studies neither dealt with suitable data caching for supporting the mobility of vehicles nor provided appropriate seamless packet forwarding for ensuring the quality of service (QoS) and quality of experience (QoE) of real-time video streaming services. To address this problem, this paper proposes a video packet distribution scheme named Clone, which integrates vehicle-to-vehicle and vehicle-to-infrastructure communications to disseminate video packets for video streaming services in VANETs. First, an indicator called current network quality information (CNQI) is defined to measure the feature of data forwarding of each node to its neighbor nodes in terms of data delivery ratio and delay. Based on the CNQI value of each node and the trajectory of the destination vehicle, access points called clones are selected to cache video data packets from data sources. Subsequently, packet distribution optimization is conducted to determine the number of video packets to cache in each clone. Finally, data delivery synchronization is established to support seamless streaming data delivery from a clone to the destination vehicle. The experimental results show that the proposed scheme achieves high-quality video streaming services in terms of QoS and QoE compared with existing schemes.
Evaluation of Deep Learning Methods in a Dual Prediction Scheme to Reduce Transmission Data in a WSN
Authors: Morales Carlos R. , Rangel de Sousa Fernando , Brusamarello Valner , Fernandes Nestor C.
Published: November 2021

One of the most important challenges in Wireless Sensor Networks (WSN) is the extension of the sensors lifetime, which are battery-powered devices, through a reduction in energy consumption. Using data prediction to decrease the amount of transmitted data is one of the approaches to solve this problem. This paper provides a comparison of deep learning methods in a dual prediction scheme to reduce transmission. The structures of the models are presented along with their parameters. A comparison of the models is provided using different performance metrics, together with the percent of points transmitted per threshold, and the errors between the final data received by Base Station (BS) and the measured values. The results show that the model with better performance in the dataset was the model with Attention, saving a considerable amount of data in transmission and still maintaining a good representation of the measured data.
Control and Diagnostics System Generator for Complex FPGA-Based Measurement Systems
Authors: Zabołotny Wojciech M. , Gumiński Marek , Kruszewski Michał , Müller Walter F.J.
Published: November 2021

FPGA-based data acquisition and processing systems play an important role in modern high-speed, multichannel measurement systems, especially in High-Energy and Plasma Physics. Such FPGA-based systems require an extended control and diagnostics part corresponding to the complexity of the controlled system. Managing the complex structure of registers while keeping the tight coupling between hardware and software is a tedious and potentially error-prone process. Various existing solutions aimed at helping that task do not perfectly match all specific requirements of that application area. The paper presents a new solution based on the XML system description, facilitating the automated generation of the control system’s HDL code and software components and enabling easy integration with the control software. The emphasis is put on reusability, ease of maintenance in the case of system modification, easy detection of mistakes, and the possibility of use in modern FPGAs. The presented system has been successfully used in data acquisition and preprocessing projects in high-energy physics experiments. It enables easy creation and modification of the control system definition and convenient access to the control and diagnostic blocks. The presented system is an open-source solution and may be adopted by the user for particular needs.
An X-Band CMOS Digital Phased Array Radar from Hardware to Software
Authors: Wu Yue-Ming , Chou Hao-Chung , Ke Cheng-Yung , Wang Chien-Cheng , Li Chien-Te , Chang Li-Han , Su Borching , Chu Ta-Shun , Wang Yu-Jiu
Published: November 2021

Phased array technology features rapid and directional scanning and has become a promising approach for remote sensing and wireless communication. In addition, element-level digitization has increased the feasibility of complicated signal processing and simultaneous multi-beamforming processes. However, the high cost and bulky characteristics of beam-steering systems have prevented their extensive application. In this paper, an X-band element-level digital phased array radar utilizing fully integrated complementary metal-oxide-semiconductor (CMOS) transceivers is proposed for achieving a low-cost and compact-size digital beamforming system. An 8–10 GHz transceiver system-on-chip (SoC) fabricated in 65 nm CMOS technology offers baseband filtering, frequency translation, and global clock synchronization through the proposed periodic pulse injection technique. A 16-element subarray module with an SoC integration, antenna-in-package, and tile array configuration achieves digital beamforming, back-end computing, and dc–dc conversion with a size of 317 × 149 × 74.6 mm3. A radar demonstrator with scalable subarray modules simultaneously realizes range sensing and azimuth recognition for pulsed radar configurations. Captured by the suggested software-defined pulsed radar, a complete range–azimuth figure with a 1 km maximum observation range can be displayed within 150 ms under the current implementation.
Services on Platform Ecosystems in the Smart Home 2.0 Era: Elements Influencing Consumers’ Value Perception for Smart Home Products
Authors: Tang Ruiyang , Inoue Yuki
Published: November 2021

Recently, smart home products have shown signs of rapid development and increasing awareness of smart home platforms. In order to make smart home enterprises enter the era of Smart Home 2.0, it is necessary to consider the elements related to smart home platforms. This study examines the relationship between consumers’ value perception and the platform ecosystem theory and how this relationship contributes to their perception of smart home products’ value. This study aims to reveal the influence of smart home platform elements on the value perception of consumers regarding consumers’ perception of the smart home products’ value. To achieve this goal, an online survey (n = 595) was implemented to collect data from Japanese respondents. The analytical results presented in this study indicated that consumers, who sense the value of modularization of smart home products and inter-consumer connectivity, can sense the value of smart home products. In addition, consumers who can perceive the value of a platform service can indirectly feel the value of smart home products through modularity and inter-consumer connectivity. The results presented in this study provide new insights into product development in Smart Home 2.0.
Polarimetric SAR Speckle Filtering Using a Nonlocal Weighted LMMSE Filter
Authors: Shen Yinbin , Ma Xiaoshuang , Zhu Shengyuan , Xu Jiangong
Published: November 2021

Despeckling is a key preprocessing step for applications using PolSAR data in most cases. In this paper, a technique based on a nonlocal weighted linear minimum mean-squared error (NWLMMSE) filter is proposed for polarimetric synthetic aperture radar (PolSAR) speckle filtering. In the process of filtering a pixel by the LMMSE estimator, the idea of nonlocal means is employed to evaluate the weights of the samples in the estimator, based on the statistical equalities between the neighborhoods of the sample pixels and the processed pixel. The NWLMMSE estimator is then derived. In the preliminary processing, an effective step is taken to preclassify the pixels, aiming at preserving point targets and considering the similarity of the scattering mechanisms between pixels in the subsequent filter. A simulated image and two real-world PolSAR images are used for illustration, and the experiments show that this filter is effective in speckle reduction, while effectively preserving strong point targets, edges, and the polarimetric scattering mechanism.
Lightweight Deep Neural Network Method for Water Body Extraction from High-Resolution Remote Sensing Images with Multisensors
Authors: Wang Yanjun , Li Shaochun , Lin Yunhao , Wang Mengjie
Published: November 2021

Rapid and accurate extraction of water bodies from high-spatial-resolution remote sensing images is of great value for water resource management, water quality monitoring and natural disaster emergency response. For traditional water body extraction methods, it is difficult to select image texture and features, the shadows of buildings and other ground objects are in the same spectrum as water bodies, the existing deep convolutional neural network is difficult to train, the consumption of computing resources is large, and the methods cannot meet real-time requirements. In this paper, a water body extraction method based on lightweight MobileNetV2 is proposed and applied to multisensor high-resolution remote sensing images, such as GF-2, WorldView-2 and UAV orthoimages. This method was validated in two typical complex geographical scenes: water bodies for farmland irrigation, which have a broken shape and long and narrow area and are surrounded by many buildings in towns and villages; and water bodies in mountainous areas, which have undulating topography, vegetation coverage and mountain shadows all over. The results were compared with those of the support vector machine, random forest and U-Net models and also verified by generalization tests and the influence of spatial resolution changes. First, the results show that the F1-score and Kappa coefficients of the MobileNetV2 model extracting water bodies from three different high-resolution images were 0.75 and 0.72 for GF-2, 0.86 and 0.85 for Worldview-2 and 0.98 and 0.98 for UAV, respectively, which are higher than those of traditional machine learning models and U-Net. Second, the training time, number of parameters and calculation amount of the MobileNetV2 model were much lower than those of the U-Net model, which greatly improves the water body extraction efficiency. Third, in other more complex surface areas, the MobileNetV2 model still maintained relatively high accuracy of water body extraction. Finally, we tested the effects of multisensor models and found that training with lower and higher spatial resolution images combined can be beneficial, but that using just lower resolution imagery is ineffective. This study provides a reference for the efficient automation of water body classification and extraction under complex geographical environment conditions and can be extended to water resource investigation, management and planning.
Vital Signal Detection Using Multi-Radar for Reductions in Body Movement Effects
Authors: Jang Ah-Jung , Lee In-Seong , Yang Jong-Ryul
Published: November 2021

Vital signal detection using multiple radars is proposed to reduce the signal degradation from a subject’s body movement. The phase variation in the transceiving signals of continuous-wave radar due to respiration and heartbeat is generated by the body surface movement of the organs monitored in the line-of-sight (LOS) of the radar. The body movement signals obtained by two adjacent radars can be assumed to be the same over a certain distance. However, the vital signals are different in each radar, and each radar has a different LOS because of the asymmetric movement of lungs and heart. The proposed method uses two adjacent radars with different LOS to obtain correlated signals that reinforce the difference in the asymmetrical movement of the organs. The correlated signals can improve the signal-to-noise ratio in vital signal detection because of a reduction in the body movement effect. Two radars at different frequencies in the 5.8 GHz band are implemented to reduce direct signal coupling. Measurement results using the radars arranged at angles of 30°, 45°, and 60° showed that the proposed method can detect the vital signals with a mean accuracy of 97.8% for the subject moving at a maximum velocity of 53.4 mm/s.
Short-Term Waterlogging Depresses Early Growth of Sunflower (Helianthus annuus L.) on Saline Soils with a Shallow Water Table in the Coastal Zone of Bangladesh
Authors: Paul Priya Lal Chandra , Bell Richard W. , Barrett-Lennard Edward G. , Kabir Enamul , Mainuddin Mohammed , Sarker Khokan Kumer
Published: November 2021

Sunflower (Helianthus annuus L.), which is widely grown globally for its high-quality edible oil, is reasonably salt and drought tolerant but it is susceptible to waterlogging. In the saline coastal zone of the Ganges delta, sunflower is often exposed to sudden heavy rainfall during early growth but plant tolerance to such events is not known. Hence, we evaluated the effect of short-term soil inundation (referred to as waterlogging) for 0, 24, 48 and 72 h on sunflower at emergence, 2-leaf, and 4-leaf stages in early- and late-sown crops under field conditions (saline, clay-textured soil, and shallow groundwater). Waterlogging for 24 h did not affect sunflower at any stage but waterlogging for 48 and 72 h suppressed emergence and growth at the 2 and 4-leaf stages. Waterlogging for 72 h completely prevented the emergence for early sowing, whereas emergence was less affected for later sowing. Shoot and root dry weight were most affected at the emergence and 2-leaf stage, not at the 4-leaf stage. In conclusion, waterlogging caused by more than 24 h soil inundation at up to the 4-leaf stage severely depressed emergence and growth, indicating the need for effective drainage at sowing of sunflower in the low-lying coastal saline zone of Bangladesh.
Standards for the Weighting of Criteria and the Measurement of Interaction
Authors: Sant’Anna Annibal Parracho
Published: November 2021

This article discusses the need for standards for the assignment of importance to criteria and the measurement of interaction between them in multiple criteria analyses of complex systems. A strategy for criteria evaluation is considered that is suitable to account for the interaction among a wide variety of imprecisely assessed criteria applied simultaneously. It is based on the results of collecting sample information on preferences according to the specified criteria instead of merely an abstract comparison of the criteria. The comparison of alternatives is based on objectives that determine the formation of preferences. It is facilitated by a rating in terms of preference probabilities. Probabilistic standards grant homogeneity of measurements by different criteria, which is useful for the combination of the criteria. These standards apply to a sampling evaluation conducted via pairwise trichotomic comparison of the alternatives according to each criterion, followed by the combination of these multiple evaluations into a single global score by means of the Choquet Integral with respect to a capacity determined by applying preference concentration to the sets of probabilistic assessments. Examples of practical application are discussed.
Simulation-Assisted Design Process of a 22 kW Wireless Power Transfer System Using Three-Phase Coil Coupling for EVs
Authors: Wu Chia-Hsuan , Lai Ching-Ming , Mishima Tomokazu , Liang Zheng-Bo
Published: November 2021

The objective of this paper is to study a 22 kW high-power wireless power transfer (WPT) system for battery charging in electric vehicles (EVs). The proposed WPT system consists of a three-phase half-bridge LC–LC (i.e., primary LC/secondary LC) resonant power converter and a three-phase sandwich wound coil set (transmitter, Tx; receiver, Rx). To transfer power effectively with a 250 mm air gap, the WPT system uses three-phase, sandwich-wound Tx/Rx coils to minimize the magnetic flux leakage effect and increase the power transfer efficiency (PTE). Furthermore, the relationship of the coupling coefficient between the Tx/Rx coils is complicated, as the coupling coefficient is not only dominated by the coupling strength of the primary and secondary sides but also relates to the primary or secondary three-phase magnetic coupling effects. In order to analyze the proposed three-phase WPT system, a detailed equivalent circuit model is derived for a better understanding. To give a design reference, a novel coil design method that can achieve high conversion efficiency for a high-power WPT system was developed based on a simulation-assisted design procedure. A pair of magnetically coupled Tx and Rx coils and the circuit parameters of the three-phase half-bridge LC–LC resonant converter for a 22 kW WPT system are adjusted through PSIM and CST STUDIO SUITE™ simulation to execute the derivation of the design formulas. Finally, the system achieved a PTE of 93.47% at an 85 kHz operating frequency with a 170 mm air gap between the coils. The results verify the feasibility of a simulation-assisted design in which the developed coils can comply with a high-power and high-efficiency WPT system in addition to a size reduction.
Open Source Seeds and the Revitalization of Local Knowledge
Authors: Fredriksson Martin
Published: November 2021

This article engages with the resistance against the global erosion of seed diversity following the modernization and industrialization of agriculture over the 20th century. This resistance spans from local farming communities that preserve and safeguard traditional landraces to international movements which oppose proprietary seed regulations and promote free sharing of seeds. The article focuses on the latter and presents a study of the open source seed movement: an initiative to apply strategies from the open source software movement to ensure the free circulation of seeds. The erosion of seed diversity can be seen not only as a loss of genetic diversity but also a memory loss where traditional, collective knowledge about how to grow certain landraces is forgotten. Consequently, the open source seed movement is not only about saving seeds but also about preserving and revitalizing local and traditional ecological knowledge against privatization and enclosure through intellectual property rights. The aim of this article is, thus, to analyze the open source seed movement as an act of revitalization in relation to intellectual property rights and in the context of information politics.
Sustainable Family Farming Futures: Exploring the Challenges of Family Farm Decision Making through an Emotional Lens of ‘Belonging’
Authors: Holloway Lorraine , Catney Gemma , Stockdale Aileen , Nelson Roy
Published: November 2021

This paper illustrates the importance of moving beyond an economic focus, and towards an emotional one, to gain a more comprehensive understanding of why farmers can be reluctant to retire and/or pass their farm onto the next generation. We report on a two-phase qualitative study of family farm decision-making processes in Northern Ireland, drawing on 62 in-depth oral life history interviews with farmers, farmers’ spouses, and farm successors. In an attempt to gain a deeper understanding of the emotional aspects of retirement and succession decision-making processes, and their relationship with place belonging, in the first phase of this research we employed an innovative ‘Work and Talk’ method, whereby interviews were conducted while shadowing, or in some cases, co-working, with farmers on their land. The second phase of this research responded to restrictions arising from the COVID-19 pandemic, and involved remote telephone or online interviews with family farm members. This research revealed the complex relationships between a ‘longing for belonging’ and emotional attachment to the family farm, and the challenges associated with patrilineal farming structures, expectations and identities, in planning for succession. The emotional impacts of strained relationships with policy makers around support for retirement emerged as a surprisingly dominant theme throughout the interview process, suggesting the need for greater emphasis on the emotional aspects of farming retirement and succession planning to inform future rural development policies targeted towards the sustainability of family farms.
Role of the Project Management Office in University Research Centres
Authors: Fernandes Gabriela , Sousa Hugo , Tereso Anabela , O’Sullivan David
Published: November 2021

University Research Centres (URCs) have become a primary organisational structure in universities for bringing together a critical mass of multidisciplinary research interests that can compete for large, funded research projects and create breakthrough research results. Some of the more successful URCs are now developing specialised project management offices (PMOs) that can coordinate key activities, from proposal development to project execution, and ensure that research results are disseminated. A key challenge for URCs is to define what roles, functions, and competencies such a PMO should have. This research identifies a number of key attributes of PMOs that meet the unique challenges of URCs. This paper presents an initial conceptualisation of roles and functions developed from a literature review and that are later tested via a detailed survey among 370 URC participants involved in collaborative R&D projects worldwide. The study suggests that there are three PMO maturity stages: ‘basic’, ‘intermediate’, and ‘advanced’. The resulting conceptualisation highlights six functions for a ‘basic’ PMO stage, an additional ten functions for an ‘intermediate’ PMO stage, and a further ten functions for ‘advanced’ PMO. The research presented provides guidance and decision support to URCs when selecting the role that a PMO should play for achieving tangible and intangible project benefits. Although the study suggests a lengthy list of functions, none of these should be considered in isolation. Most of the functions interact with each other and affect the PMOs’ impact within the URC in various ways. The paper contributes to the transformative and evolutionary nature of PMOs, and illustrates that universities are receptive and even demanding of the need to create an effective PMO to improve the operation of major R&D projects and programs and create greater societal impact by URCs.
Esophageal Stent in Sleeve Gastrectomy Leak Treatment: Observations Based on a Challenging Surgical Case and Literature
Authors: Frattini Francesco , Rizzi Andrea , Segato Sergio , Cortellezzi Claudio Camillo , Rota Bacchetta Gian Luca , Cassinotti Andrea , Gianazza Simone , Conti Lorenzo , Carrano Francesco Maria , Rausei Stefano
Published: November 2021

Gastric leak is a serious complication of sleeve gastrectomy with a well-documented morbidity and mortality. Depending on the series the leak rate ranges between 1 and 5%. The treatment of sleeve gastrectomy leak is still challenging. Different procedures have been described in management of gastric leak, both surgical and endoscopic. The treatment of gastric leaks depends on the extent of the staple-line leak, the site of the leak and its association with stenosis. As published data are limited, there are no still standardized guidelines on best treatment. One of the most commonly used option in the treatment of gastric leak is esophageal stent. Its success rate reaches 70–80% but it is burdened by some complications. Stent migration is the most common complication in the placement of esophageal stent.We present a challenging surgical in which case the use of an esophageal stent for the treatment of a sleeve gastrectomy leak gained the resolution of the leak but was complicated by bowel obstruction due to migration of the stent.
The Predictive Power of Transition Matrices
Authors: Berchtold André
Published: November 2021

When working with Markov chains, especially if they are of order greater than one, it is often necessary to evaluate the respective contribution of each lag of the variable under study on the present. This is particularly true when using the Mixture Transition Distribution model to approximate the true fully parameterized Markov chain. Even if it is possible to evaluate each transition matrix using a standard association measure, these measures do not allow taking into account all the available information. Therefore, in this paper, we introduce a new class of so-called "predictive power" measures for transition matrices. These measures address the shortcomings of traditional association measures, so as to allow better estimation of high-order models.
Classification of Metaplectic Fusion Categories
Authors: Ardonne Eddy , Finch Peter E. , Titsworth Matthew
Published: November 2021

In this paper, we study a family of fusion and modular systems realizing fusion categories Grothendieck equivalent to the representation category for so(2p+1)2. These categories describe non-abelian anyons dubbed ‘metaplectic anyons’. We obtain explicit expressions for all the F- and R-symbols. Based on these, we conjecture a classification for their monoidal equivalence classes from an analysis of their gauge invariants and define a function which gives us the number of classes.
A Survey on the Implementation and Management of Secure Virtual Private Networks (VPNs) and Virtual LANs (VLANs) in Static and Mobile Scenarios
Authors: Gentile Antonio Francesco , Fazio Peppino , Miceli Giuseppe
Published: November 2021

Nowadays, the demand for connection between the remote offices of a company, or between research locations, and constantly increasing work mobility (partly due to the current pandemic emergency) have grown hand in hand with the quality and speed of broadband connections. The logical consequence of this scenario is the increasingly widespread use of Virtual Private Network (VPN) connections. They allow one to securely connect the two ends of a connection via a dedicated network, typically using the Internet and reducing the costs of Content Delivery Network (CDN) lines (dedicated connections). At the same time, Virtual Local Area Networks (VLANs) are able to decrease the impact of some scalability issues of large networks. Given the background above, this paper is focused on overviewing and surveying the main progresses related to VPNs and VLANs in wireless networks, by collecting the most important contributions in this area and describing how they can be implemented. We state that security issues in VLANs can be effectively mitigated through the combination of good network-management practices, effective network design and the application of advanced security products. However, obviously, the implementation of VPNs and VLANs poses specific issues regarding information and network security; thus some good solutions are also surveyed.
Inflationary Implications of the Covariant Entropy Bound and the Swampland de Sitter Conjectures
Authors: Chakraborty Dibya , Damian Cesar , González Bernal Alberto , Loaiza-Brito Oscar
Published: November 2021

We present a proposal to relate the de Sitter conjecture (dSC) with the time dependence of fluxes via the covariant entropy bound (CEB). By assuming an early phase of accelerated expansion where the CEB is satisfied, we take into account a contribution from time-dependent flux compactification to the four-dimensional entropy which establishes a bound on the usual slow-roll parameters ηH and ϵH. We also show an explicit calculation of entropy from a toroidal flux compactification, from a transition amplitude of time-dependent fluxes which allows us to determine the conditions on which the bounds on the slow-roll parameters are in agreement to the dSC.
Cosmological Perturbations via Quantum Corrections in M-Theory
Authors: Hiraga Kazuho , Hyakutake Yoshifumi
Published: November 2021

In the early universe, it is important to take into account the quantum effect of gravity to explain the feature of inflation. In this paper, we consider the M-theory effective action which consists of 11-dimensional supergravity and (Weyl)4 terms. The equations of motion are solved perturbatively, and the solution describes the inflation-like expansion in 4-dimensional spacetime. Equations of motion for tensor perturbations around this background are derived perturbatively. We also check that the equations of motion are obtained from the effective action up to the second order of the perturbations. Finally, we solve the equations of motion for the tensor perturbations perturbatively and obtain analytic expressions for them.
Post-Breakage Vibration Frequency Analysis of In-Service Pedestrian Laminated Glass Modular Units
Authors: Bedon Chiara , Noè Salvatore
Published: November 2021

The vibration performance of pedestrian structures has attracted the attention of several studies, especially with respect to unfavourable operational conditions or possible damage scenarios. Specific vibration comfort levels must be commonly satisfied in addition to basic safety requirements, depending on the class of use, the structural typology and the materials involved. Careful consideration could be thus needed at the design stage (in terms of serviceability and ultimate limit state requirements), but also during the service life of a given pedestrian system. As for structural health monitoring purposes, early damage detection and maintenance interventions on constructed facilities, vibration frequency estimates are also known to represent a preliminary but rather important diagnostic parameter. In this paper, the attention is focused on the post-breakage vibration analysis of in-service triple laminated glass (LG) modular units that are part of a case-study indoor walkway in Italy. On-site non-destructive experimental methods and dynamic identification techniques are used for the vibration performance assessment of a partially cracked LG panel (LGF), compared to an uncracked modular unit (LGU). Equivalent material properties are derived to account for the fractured glass layer, and compared with literature data for post-breakage calculations. The derivation of experimental dynamic parameters for the post-breakage mechanical characterization of the structural system is supported by finite element (FE) numerical models and parametric frequency analyses.
Stochastic Modeling for Estimating Real-Time Inundation Depths at Roadside IoT Sensors Using the ANN-Derived Model
Authors: Wu Shiang-Jen , Hsu Chih-Tsu , Chang Che-Hao
Published: November 2021

This paper aims to develop a stochastic model (SM_EID_IOT) for estimating the inundation depths and associated 95% confidence intervals at the specific locations of the roadside water-level gauges, i.e., Internet of Things (IoT) sensors under the observed water levels/rainfalls and the precipitation forecasts given. The proposed SM_EID_IOT model is an ANN-derived one, a modified artificial neural network model (i.e., the ANN_GA-SA_MTF) in which the associated ANN weights are calibrated via a modified genetic algorithm with a variety of transfer functions considered. To enhance the reliability and accuracy of the proposed SM_EID_IOT model in the estimations of the inundation depths at the IoT sensors, a great number of the rainfall induced flood events as the training and validation datasets are simulated by the 2D hydraulic dynamic (SOBEK) model with the simulated rain fields via the stochastic generation model for the short-term gridded rainstorms. According to the results of model demonstration, Nankon catchment, located in northern Taiwan, the proposed SM_EID_IOT model can estimate the inundation depths at the various lead times with high reliability in capturing the validation datasets. Moreover, through the integrated real-time error correction method integrated with the proposed SM_EID_IOT model, the resulting corrected inundation-depth estimates exhibit a good agreement with the validated ones in time under an acceptable bias.
OpenSAFELY NHS Service Restoration Observatory 1: primary care clinical activity in England during the first wave of COVID-19
Authors: Curtis Helen J , MacKenna Brian , Croker Richard , Inglesby Peter , Walker Alex J , Morley Jessica , Mehrkar Amir , Morton Caroline E , Bacon Seb , Hickman George , Bates Chris , Evans David , Ward Tom , Cockburn Jonathan , Davy Simon , Bhaskaran Krishnan , Schultze Anna , Rentsch Christopher T , Williamson Elizabeth J , Hulme William J , McDonald Helen I , Tomlinson Laurie , Mathur Rohini , Drysdale Henry , Eggo Rosalind M , Wing Kevin , Wong Angel YS , Forbes Harriet , Parry John , Hester Frank , Harper Sam , Evans Stephen JW , Douglas Ian J , Smeeth Liam , Goldacre Ben ,   (The OpenSAFELY Collaborative)
Published: November 2021

Background

The COVID-19 pandemic has disrupted healthcare activity. The NHS stopped non-urgent work in March 2020, later recommending services be restored to near-normal levels before winter where possible.

Aim

To describe the volume and variation of coded clinical activity in general practice, taking respiratory disease and laboratory procedures as examples.

Design and setting

Working on behalf of NHS England, a cohort study was conducted of 23.8 million patient records in general practice, in situ using OpenSAFELY.

Method

Activity using Clinical Terms Version 3 codes and keyword searches from January 2019 to September 2020 are described.

Results

Activity recorded in general practice declined during the pandemic, but largely recovered by September. There was a large drop in coded activity for laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was the international normalised ratio test, with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 6.9). The pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as ‘no change’. Respiratory infections exhibited a sustained drop, not returning to pre-pandemic levels by September. Asthma reviews experienced a small drop but recovered, whereas chronic obstructive pulmonary disease reviews remained below baseline.

Conclusion

An open-source software framework was delivered to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September, with some important tests less affected and recording of respiratory disease codes was mixed.
Pendampingan Penyusunan Pedoman Staffing Model Untuk Meningkatkan Efisiensi Usaha Pada PT. Asuransi Bangun Askrida Bandung
Authors: Ruchiyat Endang Ruchiyat , Rahmat Rahmat , Suryanto Dadang Agus
Published: November 2021

This community service activity was carried out in Kelurahan, Cijagra, Lengkong District, Bandung City, 40253 with the target of PT. Askrida Insurance Bandung. Based on interviews and observations, the problems faced by partners today are the amount of premium rates that are difficult to compete with similar companies, poor work governance that requires employees to work overtime every day and the slow delivery of services to customers. This program has the following objectives: 1) improving the welfare of the community through the improvement of healthy financial institutions, especially insurance 2) improving the skills and professionalism of the community 3) increasing business efficiency for partners so that they are able to compete and serve the community better.

This activity uses two approaches, namely the training and mentoring approach. The training approach includes: 1) job analysis training; 2) training on work load analysis (work load analysis); and 3) skills training for the preparation of staffing model guidelines. While the mentoring methods include: 1) assistance in conducting job analysis; 2) workload analysis assistance; 3) assistance in the preparation of staffing model guidelines. The results of this community service activity have an impact on clients to be able to organize their employees well, so as to improve business efficiency and serve the community better.
Application Research on Optimization Algorithm of sEMG Gesture Recognition Based on Light CNN+LSTM Model
Authors: Bai Dianchun , Liu Tie , Han Xinghua , Yi Hongyu
Published: November 2021

The deep learning gesture recognition based on surface electromyography plays an increasingly important role in human-computer interaction. In order to ensure the high accuracy of deep learning in multistate muscle action recognition and ensure that the training model can be applied in the embedded chip with small storage space, this paper presents a feature model construction and optimization method based on multichannel sEMG amplification unit. The feature model is established by using multidimensional sequential sEMG images by combining convolutional neural network and long-term memory network to solve the problem of multistate sEMG signal recognition. The experimental results show that under the same network structure, the sEMG signal with fast Fourier transform and root mean square as feature data processing has a good recognition rate, and the recognition accuracy of complex gestures is 91.40%, with the size of 1 MB. The model can still control the artificial hand accurately when the model is small and the precision is high.
Developing Prototype Simulants for Surface Materials and Morphology of Near Earth Asteroid 2016 HO3
Authors: Zhang Xiaojing , Luo Yuechen , Xiao Yuan , Liu Deyun , Guo Fan , Guo Qian
Published: November 2021

There are a variety of applications for asteroid simulants in asteroid studies for science advances as well as technology maturation. For specific purpose, it usually requires purpose-specialized simulant. In this study, we designed and developed a set of prototype simulants as S-type asteroid surface materials analogue based on H, L, and LL ordinary chondrites’ mineralogy and terrestrial observations of near-earth asteroid 2016 HO3, which is the Chinese sample return mission target. These simulants are able to simulate morphology and reflectance characteristics of asteroid (469219) 2016 HO3 and, thus, to be used for engineering evaluation of the optical navigation system and the sampling device of the spacecraft during the mission phase. Meanwhile, these prototype simulants are easily to modify to reflect new findings on the asteroid surface when the spacecraft makes proximate observations.
ON THE EFFICIENCY OF ULTRASONIC IMPACT IN THE HOT-DIP ALUMINIZING OF IRON-BASED ALLOYS
Authors: Shmorgun V. G. , Kulevich V. P. , Bogdanov A. I. , Slautin O. V. , Taube A. O. , Chukova O. M.
Published: November 2021

It has been experimentally proven that the effect of ultrasound on the melt during hot-dip aluminizing does not affect the phase composition of the diffusion zone formed as a result of heterogeneous reactions at the interface between aluminum and iron-based alloys. It is shown that at a fixed temperature, the frequency of supplied acoustic vibrations of 18-20 kHz and an amplitude of 10-15 μm, the thickness of the coating and diffusion zone decreases by 30-50 %.