bluuebunny/crossref_metadata_2025 huggingface dataset:
Online Surface Roughness Prediction for Assembly Interfaces of Vertical Tail Integrating Tool Wear under Variable Cutting Parameters
Authors: Wang Yahui , Wang Yiwei , Zheng Lianyu , Zhou Jian
Published: March 2022

Monitoring surface quality during machining has considerable practical significance for the performance of high-value products, particularly for their assembly interfaces. Surface roughness is the most important metric of surface quality. Currently, the research on online surface roughness prediction has several limitations. The effect of tool wear variation on surface roughness is seldom considered in machining. In addition, the deterioration trend of surface roughness and tool wear differs under variable cutting parameters. The prediction models trained under one set of cutting parameters fail when cutting parameters change. Accordingly, to timely monitor the surface quality of assembly interfaces of high-value products, this paper proposes a surface roughness prediction method that considers the tool wear variation under variable cutting parameters. In this method, a stacked autoencoder and long short-term memory network (SAE–LSTM) is designed as the fundamental surface roughness prediction model using tool wear conditions and sensor signals as inputs. The transfer learning strategy is applied to the SAE–LSTM such that the surface roughness online prediction under variable cutting parameters can be realized. Machining experiments for the assembly interface (using Ti6Al4V as material) of an aircraft’s vertical tail are conducted, and monitoring data are used to validate the proposed method. Ablation studies are implemented to evaluate the key modules of the proposed model. The experimental results show that the proposed method outperforms other models and is capable of tracking the true surface roughness with time. Specifically, the minimum values of the root mean square error and mean absolute percentage error of the prediction results after transfer learning are 0.027 μm and 1.56%, respectively.
Missing and Corrupted Data Recovery in Wireless Sensor Networks Based on Weighted Robust Principal Component Analysis
Authors: He Jingfei , Li Yunpei , Zhang Xiaoyue , Li Jianwei
Published: March 2022

Although wireless sensor networks (WSNs) have been widely used, the existence of data loss and corruption caused by poor network conditions, sensor bandwidth, and node failure during transmission greatly affects the credibility of monitoring data. To solve this problem, this paper proposes a weighted robust principal component analysis method to recover the corrupted and missing data in WSNs. By decomposing the original data into a low-rank normal data matrix and a sparse abnormal matrix, the proposed method can identify the abnormal data and avoid the influence of corruption on the reconstruction of normal data. In addition, the low-rankness is constrained by weighted nuclear norm minimization instead of the nuclear norm minimization to preserve the major data components and ensure credible reconstruction data. An alternating direction method of multipliers algorithm is further developed to solve the resultant optimization problem. Experimental results demonstrate that the proposed method outperforms many state-of-the-art methods in terms of recovery accuracy in real WSNs.
Real-Time Multi-Class Disturbance Detection for Φ-OTDR Based on YOLO Algorithm
Authors: Xu Weijie , Yu Feihong , Liu Shuaiqi , Xiao Dongrui , Hu Jie , Zhao Fang , Lin Weihao , Wang Guoqing , Shen Xingliang , Wang Weizhi , Wang Feng , Liu Huanhuan , Shum Perry Ping , Shao Liyang
Published: March 2022

This paper proposes a real-time multi-class disturbance detection algorithm based on YOLO for distributed fiber vibration sensing. The algorithm achieves real-time detection of event location and classification on external intrusions sensed by distributed optical fiber sensing system (DOFS) based on phase-sensitive optical time-domain reflectometry (Φ-OTDR). We conducted data collection under perimeter security scenarios and acquired five types of events with a total of 5787 samples. The data is used as a spatial–temporal sensing image in the training of our proposed YOLO-based model (You Only Look Once-based method). Our scheme uses the Darknet53 network to simplify the traditional two-step object detection into a one-step process, using one network structure for both event localization and classification, thus improving the detection speed to achieve real-time operation. Compared with the traditional Fast-RCNN (Fast Region-CNN) and Faster-RCNN (Faster Region-CNN) algorithms, our scheme can achieve 22.83 frames per second (FPS) while maintaining high accuracy (96.14%), which is 44.90 times faster than Fast-RCNN and 3.79 times faster than Faster-RCNN. It achieves real-time operation for locating and classifying intrusion events with continuously recorded sensing data. Experimental results have demonstrated that this scheme provides a solution to real-time, multi-class external intrusion events detection and classification for the Φ-OTDR-based DOFS in practical applications.
Flexible Ceramic Film Sensors for Free-Form Devices
Authors: Nakajima Tomohiko , Fujio Yuki , Sugahara Tohru , Tsuchiya Tetsuo
Published: March 2022

Recent technological innovations, such as material printing techniques and surface functionalization, have significantly accelerated the development of new free-form sensors for next-generation flexible, wearable, and three-dimensional electronic devices. Ceramic film sensors, in particular, are in high demand for the production of reliable flexible devices. Various ceramic films can now be formed on plastic substrates through the development of low temperature fabrication processes for ceramic films, such as photocrystallization and transferring methods. Among flexible sensors, strain sensors for precise motion detection and photodetectors for biomonitoring have seen the most research development, but other fundamental sensors for temperature and humidity have also begun to grow. Recently, flexible gas and electrochemical sensors have attracted a lot of attention from a new real-time monitoring application that uses human breath and perspiration to accurately diagnose presymptomatic states. The development of a low-temperature fabrication process of ceramic film sensors and related components will complete the chemically stable and reliable free-form sensing devices by satisfying the demands that can only be addressed by flexible metal and organic components.
A Cluster-Based Approach Using Smartphone Data for Bike-Sharing Docking Stations Identification: Lisbon Case Study
Authors: Fontes Tiago , Arantes Miguel , Figueiredo Paulo V. , Novais Paulo
Published: March 2022

Urban mobility is a massive issue in the current century, being widely promoted the need of adopting sustainable solutions regarding transportation within large urban centres. The evolution of technologies has democratised smart cities to better plan and manage their mobility solutions, without compromising the social, economic, and environmental impacts. Pursuing the carbon neutrality and the climate agreement goals, soft mobility is one of the most popular emerging methods to provide greener alternatives regarding mobility. Among these transportation modes are the bicycle, which has been widely used in several public systems across the world, one of them being in Lisbon. This article provides a decision support system for bike-sharing docking stations for three council parishes of the city, namely, Parque das Nações, Marvila, and Beato. Taking advantage of clustering methods and GSM data from a telecommunication operator, this study pretends to highlight a novel approach to identify soft mobility hotspots, in specific bike-sharing docking stations, for suited mobility management systems in Lisbon’s city centre.
Fostering Equality in Education: The Blockchain Business Model for Higher Education (BBM-HE)
Authors: Son-Turan Semen
Published: March 2022

This paper seeks to address which business model in higher education that fosters SDG 4, is adequate for the post-pandemic period. To that end, it introduces the “Blockchain Business Model for Higher Education” (BBM-HE) and a transformed business model canvas framework based on existing literature, concepts, theories and findings relating to most of the pressing issues in higher education from the present study. To determine these issues, secondary data is used in the qualitative research design by applying inductive content analysis techniques to online reports. The originality of this study lies in the “adaptive” perspective to the requirements of the post-pandemic higher education landscape, which consists of modifications to the core elements of higher education, the integration of blockchain technology into the entire system, and a stronger approach to sustainability practice through sustainability tokens. The envisaged model sets out to provide a roadmap for all stakeholders, but most importantly, “decentralized” higher education institutions of the future and the “employable skills-seeking” proactive students all over the world, as opposed to the former “solely degree-focused and affluent” consumers of educational offerings. This study contributes to higher education literature in terms of business models, blockchains, pandemics, and sustainability.
Lost Gardens: From Knowledge to Revitalization and Cultural Valorization of Natural Elements
Authors: Hosseini Zohreh , Caneva Giulia
Published: March 2022

Gardens constantly change during their lifetime due to the growth and death of plants and to the effects (or lack) of management activities. The loss of garden areas, as well as the building’s collapse, can drastically impact the view and understanding of archaeological areas. The study and reconstruction of ancient lost gardens is a complex topic, and it seems that there is a lack of a general methodological approach for assessing the revitalization and valorization activities of these gardens, especially when considering the floristic features. Here, we discuss the required steps for developing the various intervention components for achieving a deep knowledge and understanding of natural, historical, and philosophical features of the place and its culture, from the past to the current conditions. Considering this knowledge, we propose a revitalization and a cultural valorization approach of the natural elements, and we discuss the limitations and issues arising in lost garden studies.
Urban Gardens’ Potential to Improve Stormwater Management: A Comparative Analysis among Urban Soils in Sorocaba, São Paulo, Brazil
Authors: Corrêa Carina Júlia Pensa , Nnadi Ernest O. , Mbanaso Fredrick U. , Tonello Kelly Cristina
Published: March 2022

Permeable surfaces are increasingly rare in urban centers, but they have the utmost importance for stormwater infiltration. In this context, green spaces are key to reducing problems caused by runoff. This work aimed to evaluate the physical characteristics of the soil used for agroecological gardening, in comparison with parks, wasteland, and riparian forest in Sorocaba, São Paulo, Brazil. During the one-year data collection, urban gardens were superior to other areas in hydraulic conductivity (35.8 mm h−1), humidity (25.8%), and soil penetration resistance (1.21 MPa). On the other hand, the riparian forest showed signs of soil degradation, with low water infiltration rates (121.9 mm h−1) and humidity (14.4%). These findings highlight the importance of better soil management solutions to avoid compaction, such as the protection and conservation of riparian forests. Furthermore, the encouragement of urban gardens and parks with multiple uses can be an option for the enhancement of stormwater management in cities, since this practice has the potential to improve the physical characteristics of urban soils and provide several ecosystem services.
Effect of Leaf Area Index on Green Facade Thermal Performance in Buildings
Authors: Convertino Fabiana , Schettini Evelia , Blanco Ileana , Bibbiani Carlo , Vox Giuliano
Published: March 2022

Green facades applied on a building’s envelope allow achieving the building’s passive thermal control and energy consumption reduction. These are complex systems and many site- and plant-specific parameters influence their energy behavior. The leaf area index (LAI) is a relevant plant characteristic to consider. Solar shading and latent heat loss of plant evapotranspiration are the two main cooling mechanisms. The aim of this study was to assess the cooling effect provided by an evergreen south oriented green facade in summer in a Mediterranean area and to investigate what happens when LAI changes. Experimental data were used to calculate the cooling effect provided by the facade. Simulations with different LAI values were performed to determine the related cooling effect. The canopy solar transmissivity decreased by 54% for every LAI unit increase. LAI significantly influenced the green facade cooling performance. As LAI increased, solar shading and latent heat increased; this was relevant until an upper limit value of 6. An exponential equation to calculate the mean extinction coefficient (km), and a polynomial relationship, with very good agreement, were proposed to calculate shading and latent heat as function of LAI. The findings of this research can effectively contribute to fill still existing gaps on green facades’ energy performance and to the energy simulation of buildings equipped with them.
Can the Economic Value Added Be Used as the Universal Financial Metric?
Authors: Dobrowolski Zbysław , Drozdowski Grzegorz , Panait Mirela , Babczuk Arkadiusz
Published: March 2022

Previous research into Economic Value Added (EVA) has extensively described it as a business metric of firms. Still, no studies have confirmed or denied that EVA is a universal metric and that one may use EVA in unstable markets in the same way as in stable and developed economies. Meanwhile, the green energy revolution, ensuring carbon neutrality through green innovations, requires enormous investments, and the projects realised must be appropriately tailored. These projects are realised by different firms, including those from developing countries, and investors need solid financial metrics. The study determines whether EVA is a universal metric of owners’ value in the energy sector. The research proves that this metric does not correctly reflect the limitations of emerging markets, can lead to incorrect managerial decisions and limit shareholders’ value. Therefore, there is a need to reanalyse financial metrics used in financial planning, including EVA. The study eliminates this research gap and, based on data from seven countries and the Euro Zone, explains why one may not perceive the currently used EVA formula as a universal financial metric. Consequently, the study modifies the EVA formula and presents a universal solution tailored to unstable economies. In the conducted research, literature studies were used, taking into account the methodology of a systematic literature review, including bibliometric analysis. Based on this review, it is shown that little is known about whether EVA as a financial measure can be used in energy management. Two conclusions emerged: first, the research contributes to developing the business and management science; second, identifying risks associated with EVA metrics helps practitioners. In addition, the study defined further research directions.
Forty Years of Soil and Water Conservation Policy, Implementation, Research and Development in Indonesia: A Review
Authors: Nugroho Hunggul Yudono Setio Hadi , Basuki Tyas Mutiara , Pramono Irfan Budi , Savitri Endang , Purwanto  , Indrawati Dewi Retna , Wahyuningrum Nining , Adi Rahardyan Nugroho , Indrajaya Yonky , Supangat Agung Budi , Putra Pamungkas Buana , Auliyani Diah , Priyanto Eko , Yuwati Tri Wira , Pratiwi  , Narendra Budi Hadi , Sukmana Asep , Handayani Wuri , Setiawan Ogi , Nandini Ryke
Published: March 2022

Dominated by mountainous topography, high rainfall, and erosion-sensitive soil types, and with the majority of its population living in rural areas as farmers, most of Indonesia’s watersheds are highly vulnerable to erosion. In 1984, the Government of Indonesia established 22 priority watersheds to be handled, which marked the start of formal soil and water conservation activities. Although it has not fully succeeded in improving watershed conditions from all aspects, something which is indicated by fluctuations in the area of degraded land, over the past 40 years the Indonesian government has systematically implemented various soil and water conservation techniques in various areas with the support of policies, laws and regulations, and research and development. These systematic efforts have shown positive results, with a 40% reduction in the area of degraded land over the last 15 years from 2004–2018. This paper reviews policy, implementation, and research and development of soil and water conservation activities in Indonesia over the last 40 years from the 1980s to 2020 and explores the dynamics of the activities.
Multi-Objective Optimization of Customer-Centered Intermodal Freight Routing Problem Based on the Combination of DRSA and NSGA-III
Authors: Shao Chunjiao , Wang Haiyan , Yu Meng
Published: March 2022

The satisfaction of requirements and preferences of shippers is critical to enable the practicability of solutions that are derived from intermodal transportation routing problems. This study aims to propose a decision process to help shippers participate better in routing decisions. First, we considered shippers’ requests on transportation cost, timeliness, reliability, and flexibility to construct a multi-objective optimization model. Then, to solve the interactive optimization method that was proposed, NSGA-III was applied to obtain the Pareto front and dominance-based rough set approach to model the preference information. Finally, a case study was conducted and an expert was invited as decision-maker to demonstrate the applicability of the proposed model and the effectiveness of the interactive method for shippers. The results are expected to provide shippers with more rational transportation schemes and insights for the sustainable development of intermodal transportation.
Purely Virtual Particles in Quantum Gravity, Inflationary Cosmology and Collider Physics
Authors: Anselmi Damiano
Published: March 2022

We review the concept of purely virtual particle and its uses in quantum gravity, primordial cosmology and collider physics. The fake particle, or “fakeon”, which mediates interactions without appearing among the incoming and outgoing states, can be introduced by means of a new diagrammatics. The renormalization coincides with one of the parent Euclidean diagrammatics, while unitarity follows from spectral optical identities, which can be derived by means of algebraic operations. The classical limit of a theory of physical particles and fakeons is described by an ordinary Lagrangian plus Hermitian, micro acausal and micro nonlocal self-interactions. Quantum gravity propagates the graviton, a massive scalar field (the inflaton) and a massive spin-2 fakeon, and leads to a constrained primordial cosmology, which predicts the tensor-to-scalar ratio r in the window 0.4≲1000r≲3.5. The interpretation of inflation as a cosmic RG flow allows us to calculate the perturbation spectra to high orders in the presence of the Weyl squared term. In models of new physics beyond the standard model, fakeons evade various phenomenological bounds, because they are less constrained than normal particles. The resummation of self-energies reveals that it is impossible to get too close to the fakeon peak. The related peak uncertainty, equal to the fakeon width divided by 2, is expected to be observable.
Symmetric versus Asymmetric Features of Homologous Homodimeric Amine Oxidases: When Water and Cavities Make the Difference
Authors: Nicolai Eleonora , Minicozzi Velia , Di Paola Luisa , Medda Rosaria , Pintus Francesca , Mei Giampiero , Di Venere Almerinda
Published: March 2022

Symmetry is an intrinsic property of homo-oligomers. Amine oxidases are multidomain homodimeric enzymes that contain one catalytic site per subunit, and that share a high homology degree. In this paper, we investigated, by fluorescence spectroscopy measurements, the conformational dynamics and resiliency in solutions of two amine oxidases, one from lentil seedlings, and one from Euphorbia characias latex, of which the crystallographic structure is still unknown. The data demonstrate that slight but significant differences exist at the level of the local tridimensional structure, which arise from the presence of large internal cavities, which are characterized by different hydration extents. Molecular dynamics and a contact network methodology were also used to further explore, in silico, the structural features of the two proteins. The analysis demonstrates that the two proteins show similar long-range symmetrical connectivities, but that they differ in their local (intra-subunit) contact networks, which appear mostly asymmetric. These features have been interpreted to suggest a new rationale for the functioning of amino oxidases as obligate homodimers.
Global Impact of Ergot Alkaloids
Authors: Klotz James L.
Published: March 2022

For many years, ergot alkaloids have been considered both a problem to be mitigated and a potential medical cure [...]
The Potential of Fatty Acids and Their Derivatives as Antifungal Agents: A Review
Authors: Guimarães Ana , Venâncio Armando
Published: March 2022

Fungal contamination presents several problems: in humans, health issues arise from infections with opportunistic filamentous fungi and yeast, while in food, fungi cause spoilage and, in particular, in the case of mycotoxigenic fungi, can cause serious health issues. Several types of fatty acids and their derivatives, oxylipins, have been found to have inhibitory effect towards fungal growth and the production of mycotoxins. The use of fatty acids as antifungals could fulfil consumer’s requests of more natural and environmentally friendly compounds, while being less likely to promote fungal resistance. In addition, due to their nature, fatty acids are easily used as food additives. In this work, we review the most relevant and recent studies on the antifungal ability of fatty acids. We focused on saturated fatty acids, unsaturated fatty acids, and oxylipins, their different impact on fungal inhibition, their proposed modes of action, and their ability to impair mycotoxin production. Applications of fatty acids as antifungals and their limitations are also addressed.
Delayed Diagnosis of Whipple’s Disease Complicated by Jarisch–Herxheimer Reaction to Ceftriaxone Treatment: A Case Report and Literature Review
Authors: Clarke Marcus C. C. , Price Ric N.
Published: March 2022

Whipple’s disease is a rare chronic infection caused by the actinomycete Tropheryma whipplei. Patients commonly present with gastrointestinal symptoms. We present a case of classic Whipple’s disease complicated by a probable Jarisch–Herxheimer reaction following the initiation of ceftriaxone treatment.
Detectability of the Cross-Correlation between CMB Lensing and Stochastic GW Background from Compact Object Mergers
Authors: Capurri Giulia , Lapi Andrea , Baccigalupi Carlo
Published: March 2022

The anisotropies of the Stochastic Gravitational-Wave Background (SGWB), produced by merging compact binaries, constitute a possible new probe of the Large-Scale Structure (LSS). However, the significant shot noise contribution caused by the discreteness of the GW sources and the poor angular resolution of the instruments hampers the detection of the intrinsic anisotropies induced by the LSS. In this work, we investigate the potential of cross-correlating forthcoming high precision measurements of the SGWB energy density and the Cosmic Microwave Background (CMB) lensing convergence to mitigate the effect of shot noise. Combining a detailed model of stellar and galactic astrophysics with a novel framework to distribute the GW emitters in the sky, we compute the auto- and cross-correlation power spectra for the two cosmic fields, evaluate the shot noise contribution and predict the signal-to-noise ratio. The results of our analysis show that the SGWB energy density correlates significantly with the CMB lensing convergence and that the cross-correlation between these two cosmic fields reduces the impact of instrumental and shot noise. Unfortunately, the S/N is not high enough to detect the intrinsic SGWB anisotropies. Nevertheless, a network composed of both present and future generation GW interferometers, operating for at least 10 yrs, should be able to measure the shot noise contribution.
City-Wide Firearm Violence Spikes in Minneapolis following the Murder of George Floyd: A Comparative Time-Series Analysis of Three Cities
Authors: Boehme Hunter M. , Kaminski Robert J. , Nolan Melissa S.
Published: March 2022

This study investigates the aftermath of a high-profile violent police incident as it relates to city-wide firearm violence. Utilizing two Midwest cities (Kansas City, Missouri and Omaha, Nebraska) as comparison cities, we assess whether violent firearm incidents increased in Minneapolis after the murder of George Floyd. Multiple interrupted time-series analyses showed statistically significant increases in weekly firearm incidents in Minneapolis (AME = 10.63, p < 0.05) and Omaha (AME = 1.47, p < 0.5) following the murder of George Floyd. No significant results were found in Kansas City. Similar relationships were found when examining monthly firearm incidents. The firearm spike in Minneapolis thus represents an approximate 10-fold increase in weekly firearm incidents relative to that observed in Omaha. We conclude, therefore, that the murder of George Floyd was associated with a substantially greater increase in firearm violence in Minneapolis than in the two comparison cities. Police training to reduce police violence and public health approaches to reduce urban firearm violence will alleviate the social and economic impacts of violence on federal and state governments.
The Role of Nucleoprotein in Immunity to Human Negative-Stranded RNA Viruses—Not Just Another Brick in the Viral Nucleocapsid
Authors: Šantak Maja , Matić Zrinka
Published: March 2022

Negative-stranded RNA viruses (NSVs) are important human pathogens, including emerging and reemerging viruses that cause respiratory, hemorrhagic and other severe illnesses. Vaccine design traditionally relies on the viral surface glycoproteins. However, surface glycoproteins rarely elicit effective long-term immunity due to high variability. Therefore, an alternative approach is to include conserved structural proteins such as nucleoprotein (NP). NP is engaged in myriad processes in the viral life cycle: coating and protection of viral RNA, regulation of transcription/replication processes and induction of immunosuppression of the host. A broad heterosubtypic T-cellular protection was ascribed very early to this protein. In contrast, the understanding of the humoral immunity to NP is very limited in spite of the high titer of non-neutralizing NP-specific antibodies raised upon natural infection or immunization. In this review, the data with important implications for the understanding of the role of NP in the immune response to human NSVs are revisited. Major implications of the elicited T-cell immune responses to NP are evaluated, and the possible multiple mechanisms of the neglected humoral response to NP are discussed. The intention of this review is to remind that NP is a very promising target for the development of future vaccines.
Transcriptome and Small RNA Profiling of Potato Virus Y Infected Potato Cultivars, Including Systemically Infected Russet Burbank
Authors: Ross Brian T. , Zidack Nina , McDonald Rose , Flenniken Michelle L.
Published: March 2022

Potatoes are the world’s most produced non-grain crops and an important food source for billions of people. Potatoes are susceptible to numerous pathogens that reduce yield, including Potato virus Y (PVY). Genetic resistance to PVY is a sustainable way to limit yield and quality losses due to PVY infection. Potato cultivars vary in their susceptibility to PVY and include susceptible varieties such as Russet Burbank, and resistant varieties such as Payette Russet. Although the loci and genes associated with PVY-resistance have been identified, the genes and mechanisms involved in limiting PVY during the development of systemic infections have yet to be fully elucidated. To increase our understanding of PVY infection, potato antiviral responses, and resistance, we utilized RNA sequencing to characterize the transcriptomes of two potato cultivars. Since transcriptional responses associated with the extreme resistance response occur soon after PVY contact, we analyzed the transcriptome and small RNA profile of both the PVY-resistant Payette Russet cultivar and PVY-susceptible Russet Burbank cultivar 24 hours post-inoculation. While hundreds of genes, including terpene synthase and protein kinase encoding genes, exhibited increased expression, the majority, including numerous genes involved in plant pathogen interactions, were downregulated. To gain greater understanding of the transcriptional changes that occur during the development of systemic PVY-infection, we analyzed Russet Burbank leaf samples one week and four weeks post-inoculation and identified similarities and differences, including higher expression of genes involved in chloroplast function, photosynthesis, and secondary metabolite production, and lower expression of defense response genes at those time points. Small RNA sequencing identified different populations of 21- and 24-nucleotide RNAs and revealed that the miRNA profiles in PVY-infected Russet Burbank plants were similar to those observed in other PVY-tolerant cultivars and that during systemic infection ~32% of the NLR-type disease resistance genes were targeted by 21-nt small RNAs. Analysis of alternative splicing in PVY-infected potato plants identified splice variants of several hundred genes, including isoforms that were more dominant in PVY-infected plants. The description of the PVYN-Wi-associated transcriptome and small RNA profiles of two potato cultivars described herein adds to the body of knowledge regarding differential outcomes of infection for specific PVY strain and host cultivar pairs, which will help further understanding of the mechanisms governing genetic resistance and/or virus-limiting responses in potato plants.
Simulation and Prediction of the Impact of Climate Change Scenarios on Runoff of Typical Watersheds in Changbai Mountains, China
Authors: Li Zhaoyang , Cao Yidan , Duan Yucong , Jiang Zelin , Sun Feihu
Published: March 2022

Simulating the hydrological process of a river basin helps to understand the evolution of water resources in the region and provides scientific guidance for water resources allocation policies between different river basins and water resources management within the river basin. This paper provides a scientific basis for the sustainable development of regional water resources and an accurate grasp of the future change trend of runoff by analyzing the hydrological process response of runoff in typical watersheds in Changbai Mountains, China, to climate change. The applicability of the HEC-HMS (The Hydrologic Engineering Center’s-Hydrologic Modeling System) hydrological model in the watershed is verified by calibrating and verifying the daily rainfall-runoff process in the watershed during the wet season from 2006 to 2017. The daily rainfall data of the two scenarios SSP2-4.5 and SSP5-8.5 under the BCC-CSM2-MR model in the 2021–2050 CMIP6 plan were downscaled and interpolated to in-basin stations to generate future daily precipitation series to predict runoff response to future climate change. The daily rainfall data of the two scenarios were downscaled and interpolated to the stations in the basin to generate future daily rainfall series to predict the runoff response under future climate changes. The average certainty coefficient of the HEC-HMS model for daily runoff simulation reached 0.705; the rainfall in the basin under the two climate scenarios of SSP2-4.5 and SSP5-8.5 in the next 30 years (2021–2050) will generally increase, and rainfall will be more evenly distributed in the future; the outlet flow of the basin will increase during the wet season (June–September) in the next 30 years, but it is lower than the historically measured value; the peak flow of the future will appear at most in August and September. The peak flow current time mostly appears in July and August. The time of peak occurrence has been delayed.
Vortex Impeller-Based Aeration of Groundwater
Authors: van de Griend Maarten V. , Warrener Francis , van den Akker Meike , Song Yanru , Fuchs Elmar C. , Loiskandl Willibald , Agostinho Luewton L. F.
Published: March 2022

Iron oxidation and removal from groundwater is a necessary and costly process in drinking water production. In most cases, iron removal is done via aeration, succeeded by precipitation. Most systems for aeration are based on increasing the interfacial area via injecting air in the system or spraying. Both methods have disadvantages, like clogging and formation of aerosols. In this study, a new vortex-based flow-through reactor consisting of a cylindrical tank with an impeller located at the bottom was studied regarding its aeration and iron oxidation capabilities in groundwater. During the aeration experiments, the flow rate, impeller rotation and aerated volume were varied. A nondimensional constant α was proposed to relate the system’s physical characteristics and its aeration capabilities, expressed in dissolved oxygen and system volumetric mass transfer coefficient (KLa). Three distinct operational regimes were defined: formation, complete and bubble regime. These regimes showed very specific characteristics regarding the air–water interface structure and the area to volume ratio, resulting in different aeration capabilities and iron oxidation efficiency values. The system presented KLa values similar to commercially available aeration systems, especially inside the bubble regime. By using dimensionless coefficients, the presented analysis provided the basis for the design of continuous impeller aeration and oxidation systems of arbitrary size.
Experimental Study on the Effect of Gas Volume Fraction on the Cavitation Performance of a Low-Specific-Speed Centrifugal Pump
Authors: Jiang Linglin , Liu Houlin , Wang Yong , Mao Yanhong , Zhou Runze , Gu Jianbin
Published: March 2022

In order to study the cavitation performance of centrifugal pumps with low specific speeds under the condition of gas–liquid two-phase flow, a cavitation test rig for pumping gas–liquid two-phase flow was set up. The cavitation performance of the pump with a specific speed of 32 was studied. The variation of the head, pressure pulsation intensity, and vibration intensity with the cavitation allowance NPSHa (Net Positive Suction Head available) of the centrifugal pump were obtained at different inlet gas volume fraction (IGVF) conditions of 0, 1%, 2%, and 3%. The results show that the cavitation performance of a low-specific-speed centrifugal pump can be improved obviously in a certain liquid flow range when the IGVF is 1%, especially at a low liquid flow rate. When cavitation did not occur or the degree of cavitation was low, a lower IGVF can reduce pressure pulsation intensity at the pump outlet and the vibration intensity at the pump inlet under design flow rate and high flow rate conditions. Additionally, all performances of the low-specific-speed pump are more sensitive to gas when the liquid flow rate is low. The results can provide a reference for improving the cavitation performance of low-specific-speed pumps for transporting gas–liquid two-phase flow and single-phase liquids.
Lost in Optimization of Water Distribution Systems: Better Call Bayes
Authors: Candelieri Antonio , Ponti Andrea , Giordani Ilaria , Archetti Francesco
Published: March 2022

The main goal of this paper is to show that Bayesian optimization can be regarded as a general framework for the data-driven modelling and solution of problems arising in water distribution systems. Scenario-based hydraulic simulation and Monte Carlo are key tools in modelling in water distribution systems. The related optimization problems fall into a simulation/optimization framework in which objectives and constraints are often black box. Bayesian optimization (BO) is characterized by a surrogate model, usually a Gaussian process but also a random forest, as well as neural networks and an acquisition function that drives the search for new evaluation points. These modelling options make BO nonparametric, robust, flexible, and sample efficient, making it particularly suitable for simulation/optimization problems. A defining characteristic of BO is its versatility and flexibility, given, for instance, by different probabilistic models, in particular different kernels, different acquisition functions. These characteristics of the Bayesian optimization approach are exemplified by two problems: cost/energy optimization in pump scheduling and optimal sensor placement for early detection of contaminant intrusion. Different surrogate models have been used both in explicit and implicit control schemes, showing that BO can drive the process of learning control rules directly from operational data. BO can also be extended to multi-objective optimization. Two algorithms are proposed for multi-objective detection problems using two different acquisition functions.
Index System of Water Resources Development and Utilization Level Based on Water-Saving Society
Authors: Dai Ce , Tang Jie , Li Zhaoyang , Duan Yucong , Qu Yunke , Yang Yao , Lyu Hang , Zhang Dan , Wang Yongtai
Published: March 2022

The notion of a ‘Water-saving society’ may help China achieve sustainable development and high-quality development. In this paper, the concept of water resources development and utilization level is discussed from the perspective of a water-saving society, and an evaluation index system including 33 indicators is constructed. This paper takes the evaluation of water resources development and utilization level of Jingyu County from 2009 to 2018 as an example to verify the rationality of the indicator system of this study. Additionally, by changing the sensitivity analysis method of indicator weights, the indicators with greater influence on the evaluation results are screened to reduce the uncertainty of too many indicators and low correlation. The results show that the evaluation value of water resources development and utilization level in Jingyu County from 2009 to 2018 was improved from V to II, and the improvement of industrial and domestic water use efficiency and effectiveness improved the water resource problems in the study area. Sensitivity analysis showed that the sensitivity parameters are the degree of water resources development and utilization (8.7%), water consumption per CNY 10,000 of industrial value added (11.2%), water consumption per CNY 10,000 of GDP (9.3%), leakage rate of the urban water supply network (8.4%), per capita water resources (10.1%), per capita COD emissions (9.3%) and urbanization rate (8.2%).
Cultural Values in Water Management and Governance: Where Do We Stand?
Authors: Heinrichs Danielle H. , Rojas Rodrigo
Published: March 2022

Research in water governance and management is a complex subject that involves the appraisal of social, economic, and environmental–biophysical aspects. Cultural and social values are regarded as key drivers in decision-making processes in both domains. Identifying relevant cultural values however is difficult given the interdisciplinary nature of theoretical frameworks and the implementation and operational needs of water governance/management research. In this work, we conduct a systematic literature review and thematic analysis of existing theories of culture (ToC) to identify common cultural values, theoretical frameworks, disciplinary trajectories and implementation trends relevant to water management and governance. Results indicate that the dominant ToC corresponds to Cultural Theory with its four defined categories (Egalitarian–Hierarchist–Individualist–Fatalist). In addition, results show emergent cultural values linked to “local” place-based knowledge perspectives indicating a more pluriversal understanding of cultural values. Cultural values associated with water management revolve around anthropocentrism, whereas values associated with water governance revolve around concepts of provenance/places. Implementation of ToC/cultural values is limited in practical applications, and we provide an example on how to improve on that. We suggest a succinct theory of culture such as Schwartz’s cultural values be considered to be an alternative to capture a greater heterogeneity across the breadth of water governance/management-related and basin-specific contexts.
Pandemic and isolation: cultural aspects
Authors:   Institute of Philosophy, St. Petersburg State University, Kamneva L.S. , Pirogov А.А. ,   St. Petersburg State Budgetary Educational Institution “Medical College No. 2”
Published: March 2022

The article analyzes isolation and pandemic in the cultural context. Authors examines the international scientific search for a solution to the problem in the context of the global pandemic. General reasons are stressed that apply to the current Russian situation. The author offers the philosophical and cultural analysis of the European isolation model as applied to Russian conditions. Authors emphasize the features of the Russian solution of problems and the importance of turning to historical experience in understanding the issues of the isolation. English version of the article is available at URL:https://panor.ru/articles/pandemic-and-isolation-cultural-aspects/79580.html
Social partnership in Russia and abroad: problems and prospects
Authors:   journal “Questions of cultural studies”, Agoshkov A.V.
Published: March 2022

The article on the settlement of social and labor conflicts and the formation of a culture of labor relations was prepared on the basis of a review of a series of publications “Social and labor conflicts”, prepared in the development of a research project carried out on the basis of the Scientific and Monitoring Center “Labor Conflicts” of St. Petersburg State Unitary Enterprise.
Design and Evaluation of a Cyber Protection Team Planner Work Aid
Authors: Ligg Kristen , Stephenson Arielle , Strang Meghan , Dobson Geoffrey
Published: March 2022

Cyber Protection Teams (CPTs) are responsible for providing mission assurance by ensuring that mission-relevant cyber terrain is secure and protected for operations. In order to do this effectively, CPT planners must correlate and integrate information regarding customers’ missions with information about the systems and networks required to perform those missions. To support this challenge, a CPT Planner work aid was designed and evaluated to assess its effectiveness. The evaluation compared the work aid with current CPT planning methods. Ten participants with varying planning expertise performed four planning tasks (managing approvals, assigning resources, managing accesses, and scheduling meetings). To test the efficacy of the proposed work aid, participants were tasked with planning a fictional mission utilizing both the traditional planning method and the work aid method. Data was collected from objective metrics to include time and task performance score, as well as subjective perception of workload. In addition, participants were asked a series of situation awareness (SA) questions after each task to measure their understanding of the mission-relevant information. Score and time to answer SA questions were also recorded. While CPT planning experience did not have a significant effect on performance, results revealed significant improvements in task time, SA question response time, and perceived workload when using the work aid versus the baseline condition.
Shallow Deep Learning using Space-filling Curves for Malware Classification
Authors: Long David , O'Shaughnessy Stephen
Published: March 2022

The incidents of malware attacks are continually increasing at a rapid rate, thanks to the lucrative potential in schemes such as ransomware, credential stealing Trojans and cryptominers. Their explosive growth is compounded by the ease with which variants can be created from original strains. As a result, anti-virus organisations are struggling to keep up, with some reporting upwards of 14 million samples processed per month. These sheer volumes have caused a shift towards machine learning and artificial intelligence in an effort to alleviate the manual burden of analysis and classification. This research presents a novel framework for the classification of malware into distinct family classes through computer vision and deep learning. In the proposed framework, malware binaries are represented in an abstract form as images mapped through mathematical constructs known as space-filling curves. Convolutional neural networks were constructed and applied to the malware images to build predictive models for classification. The models were optimised using an auto-tuning function for the hyper parameters, which included Bayesian Optimisation, Random search and HyperBand, providing an exhaustive search on the hyper parameters. On a training dataset of 13k malware samples from 23 distinct families, the models yielded an average score of 95% for precision, recall and f1-score.  The final deep learning model was validated for robustness against a dataset of more recent variants, comprising 12,816 samples from 16 malware families, returning classification scores of 95%, 86% and 90% for precision, recall and f1-score. The final model was demonstrated to outperform a similar benchmark model considerably. The results show the potential of the deep learning framework as a viable solution to the classification of malware, without the need for manually intensive feature generation or invasive processing techniques.
Circuit-Variant Moving Target Defense for Side-Channel Attacks
Authors: Mullins Tristen , Baggett Brandon , Andel Todd , McDonald Todd
Published: March 2022

The security of cryptosystems involves preventing an attacker's ability to obtain information about plaintext. Traditionally, this has been done by prioritizing secrecy of the key through complex key selection and secure key exchange. With the emergence of side-channel analysis (SCA) attacks, bits of a secret key may be derived by correlating key values with physical properties of cryptographic process execution. Information such as power consumption and electromagnetic (EM) radiation side-channel properties can be observed during encryption or decryption. These signals reflect data-dependent system behaviours that may reveal secret key information. Power and EM SCA attacks require several measurements of the target process to amplify the signal of interest, filter out noise, and derive the secret key through statistical analysis methods. Differential power and EM analysis attacks rely on correlating actual side-channel measurements to hypothetical models. The goal of this research is to increase the complexity of both power and EM SCA by introducing structural and spatial randomization of the target hardware. We propose a System-on-a-Chip (SOC) countermeasure that will periodically reconfigure an AES scheme using randomly located S-box circuit variants. We hypothesize that changing the location of the target modules between encryption runs will result in a nonconstant EM signal strength for any given point on the chip, increasing the number of traces needed to perform a localized EM SCA attack. Further, each of the S-box circuit variants will consist of functionally equivalent, structurally diverse hardware. By diversifying the implementations at the gate-level, we aim to vary the power behaviour observed by the attacker and disrupt the correlation between the hypothetical and actual power consumption, increasing the complexity of power SCA. This moving target defense aims to disrupt side-channel collection and correlation needed to successfully implement an attack.