bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review on the Performance of Concrete Containing Non-Potable Water
Authors: Ali Babar , Kurda Rawaz , Brito Jorge de , Alyousef Rayed
Published: July 2021

Construction industries consume huge amounts of potable water during activities such as washing of aggregates, stone crushing, manufacturing, and curing of concrete, mortars, grouts, and wetting of masonry bricks. It is also responsible for wastewater generated during the finishing and cleaning of buildings and construction equipment. Therefore, the water-footprint of construction industry cannot be ignored to reach the state-of-the art sustainability. This study reviewed the technical properties of construction materials made with non-potable water (NPW), i.e., domestic and industrial sewage. The study identified the positive and negative effects of non-potable water on the fresh- and hardened-state properties of concrete. This study also identified the gaps in the literature that can be analysed in order to produce reliable information related to the use of different types of NPW on the properties of concrete.
A Software-in-the-Loop Simulation of Vehicle Control Unit Algorithms for a Driverless Railway Vehicle
Authors: Vignati Michele , Debattisti Nicola , Bacci Maria Laura , Tarsitano Davide
Published: July 2021

The realization of the first prototype of a vehicle requires several tests of the algorithms implemented on the electronic control unit (ECU). This represents an important step for conventional vehicles, which becomes fundamental when dealing with unmanned vehicles. Since there is no human supervision, most critical tasks are handled by the control unit, which results in higher complexity for the control algorithms. In this work, a software-in-the-loop (SiL) test bench is used to validate the control algorithms of a vehicle control unit (VCU) for a driverless railway vehicle (DLRV). The VCU manages the control of the traction motors, pneumatic braking systems, and range extender, as well as control of the hybrid powertrain configuration to guarantee a high level of availability via the use of redundant systems. The SiL test bench has been developed in a Simulink real-time environment, where the vehicle model is simulated along with its fundamental subsystems. The model communicates with the VCU through a CAN bus protocol in the same way that it will operate with a real vehicle. The proposed method can be used to simulate many mission profiles for the DLRV, which may last several hours each. Moreover, this kind of test bench ensures a high time resolution, which allows one to find solutions for problems which occur with a time scale that is much smaller than the simulation time scale.
Temporal and Spatial Groundwater Contamination Assessment Using Geophysical and Hydrochemical Methods: The Industrial Chemical Complex of Estarreja (Portugal) Case Study
Authors: Marques Tiago , Matias Manuel Senos , Silva Eduardo Ferreira da , Durães Nuno , Patinha Carla
Published: July 2021

With more than a half-century in operation, the industrial chemical complex of Estarreja (ICCE) in northern Portugal has left serious environmental liabilities in the region. Although protective measures were implemented, soils, surface, and groundwater contamination caused by persistent pollutants are still prevalent. This study presents data from several geophysical and hydrochemical campaigns carried out to monitor groundwater contamination in the Estarreja region over a period of 30 years. Both geophysical and hydrochemical data showed a good agreement and revealed an important anomaly caused by groundwater contamination (high levels of Na, Cl, SO4, and Fe, among others) in 2006–2007, likely caused by the remobilization of waste pollutants (roasted pyrites, soils, and sludge) during their deposition in a sealed landfill (operating between 2003 and 2005). More recently, in 2016, this impact persists, but was more attenuated and showed a general migration pattern from E to SW according to one of the main groundwater flow paths. Groundwater flow in this region has a local radial behaviour. Drainage effluent systems, such as ditches and buried pipes formerly used by ICCE, are also likely to contribute to some contamination “hotspots”. Finally, the results obtained by the combined use of these two approaches allowed for the delineation of the contamination plume for future monitoring.
Terahertz and Microwave Optical Properties of Single-Crystal Quartz and Vitreous Silica and the Behavior of the Boson Peak
Authors: Naftaly Mira , Gregory Andrew
Published: July 2021

Z-cut single-crystal quartz and vitreous silica (silica glass or fused silica) were evaluated for use as reference materials for terahertz and microwave measurements of complex permittivity, with Z-cut quartz confirmed as being suitable. Measurements of refractive indices and absorption coefficients for o-ray and e-ray in quartz and for vitreous silica are reported at frequencies between 0.2 and 6 THz and at 36 and 144 GHz, and compared with data reported in the literature. A previously unreported broad band was seen in the extraordinary absorption of quartz. The Boson peak in silica glass absorption was examined, and for the first time, two negative relationships have been observed: between the refractive index and the Boson peak frequency, and between the Boson peak height and its frequency.
A New Characterization Method for Rock Joint Roughness Considering the Mechanical Contribution of Each Asperity Order
Authors: Yuan Zhouhao , Ye Yicheng , Luo Binyu , Liu Yang
Published: July 2021

The morphology of the joint surface is multi-scale, and it can be divided into first-order asperity (waviness) and second-order asperity (unevenness). At present, the joint roughness characterization formula considers only the morphology contribution of waviness and unevenness components and does not fully consider their mechanical contribution. At same time, the relationship between the mechanical contribution and the morphology contribution is still unclear. Thus, the characterization formula considering the mechanical contribution of waviness and unevenness needs to be further studied. In this study, the standard joint roughness coefficient (JRC) profiles were first decomposed into waviness and unevenness. Then, three types of joint specimens with different asperity orders (flat, the standard JRC profile, and the profile containing only waviness) were prepared by the 3D engraving technique. Finally, direct shear tests were carried out on 39 sets of red sandstone joint specimens under three normal stresses. The mechanical contributions of waviness and unevenness were studied, the relationship between the mechanical contribution and the morphology contribution of waviness and unevenness was analyzed, and the characterization formula considering the mechanical contribution of waviness and unevenness was established. The results showed that the following: (1) the method combining the ensemble empirical mode decomposition (EEMD) and the critical decomposition level could be used to separate the waviness and unevenness from the joint surface; (2) the mechanical contribution of the waviness and unevenness decreased with the increase in normal stress; (3) the relationship between the mechanical contribution ratio and the statistical parameter ratio of the waviness and unevenness can be describe by power function; and (4) the roughness characterization formula considering the mechanical contribution and morphology contribution was established. This study will enhance the accurate evaluation of the roughness coefficient and shear strength of the joint specimen.
Design of Fiber-Tip Refractive Index Sensor Based on Resonant Waveguide Grating with Enhanced Peak Intensity
Authors: Yao Yicun , Xie Yanru , Chen Nan-Kuang , Pfalzgraf Ivonne , Suntsov Sergiy , Kip Detlef , Ren Yingying
Published: July 2021

Resonant waveguide gratings (RWG) are widely used as on-chip refractometers due to their relatively high sensitivity to ambient refractive index changes, their possibility of parallel high-throughput detection and their easy fabrication. In the last two decades, efforts have been made to integrate RWG sensors onto fiber facets, although practical application is still hindered by the limited resonant peak intensity caused by the low coupling efficiency between the reflected beam and the fiber mode. In this work, we propose a new compact RWG fiber-optic sensor with an additional Fabry-Pérot cavity, which is directly integrated onto the tip of a single-mode fiber. By introducing such a resonant structure, a strongly enhanced peak reflectance and improved figure of merit are achieved, while, at the same time, the grating size can be greatly reduced, thus allowing for spatial multiplexing of many sensors on a tip of a single multi-core fiber. This paves the way for the development of probe-like reflective fiber-tip RWG sensors, which are of great interest for multi-channel biochemical sensing and for real-time medical diagnostics.
Coherent Image Source Modeling of Sound Fields in Long Spaces with a Sound-Absorbing Ceiling
Authors: Min Hequn , Xu Ke
Published: July 2021

Sound-absorbing boundaries can attenuate noise propagation in practical long spaces, but fast and accurate sound field modeling in this situation is still difficult. This paper presents a coherent image source model for simple yet accurate prediction of the sound field in long enclosures with a sound absorbing ceiling. In the proposed model, the reflections on the absorbent boundary are separated from those on reflective ones during evaluating reflection coefficients. The model is compared with the classic wave theory, an existing coherent image source model and a scale-model experiment. The results show that the proposed model provides remarkable accuracy advantage over the existing models yet is fast for sound prediction in long spaces.
Inferring Long-Term Demand of Newly Established Stations for Expansion Areas in Bike Sharing System
Authors: Hsieh Hsun-Ping , Lin Fandel , Jiang Jiawei , Kuo Tzu-Ying , Chang Yu-En
Published: July 2021

Research on flourishing public bike-sharing systems has been widely discussed in recent years. In these studies, many existing works focus on accurately predicting individual stations in a short time. This work, therefore, aims to predict long-term bike rental/drop-off demands at given bike station locations in the expansion areas. The real-world bike stations are mainly built-in batches for expansion areas. To address the problem, we propose LDA (Long-Term Demand Advisor), a framework to estimate the long-term characteristics of newly established stations. In LDA, several engineering strategies are proposed to extract discriminative and representative features for long-term demands. Moreover, for original and newly established stations, we propose several feature extraction methods and an algorithm to model the correlations between urban dynamics and long-term demands. Our work is the first to address the long-term demand of new stations, providing the government with a tool to pre-evaluate the bike flow of new stations before deployment; this can avoid wasting resources such as personnel expense or budget. We evaluate real-world data from New York City’s bike-sharing system, and show that our LDA framework outperforms baseline approaches.
Arthrospira platensis as a Feasible Feedstock for Bioethanol Production
Authors: Gonzalez Bautista Enrique , Laroche Céline
Published: July 2021

In recent decades and to deal with the scarcity of fossil fuels, many studies have been developed in order to set up a sustainable biofuel production sector. This new sector must be efficient (high productivity), economically profitable (low production costs and therefore acceptable fuel prices), and ethical (low carbon balance, no competition with food resources). The production of bioethanol is based on the fermentation of reserve sugars, accumulated in the form of starch in microalgae and glycogen in cyanobacteria. The advantage of this bioenergy production route lies in the fact that the post-crop fermentation process is at the industrial stage since it has already been tested for many years for the production of bioethanol from agricultural resources. One of the most cultivated cyanobacteria is Arthrospira (“Spirulina”) and its production is also already at industrial scale. Depending on the cultivation conditions, this cyanobacteria is able to accumulate up to 65% DW (dry weight) of glycogen, making it a feasible feedstock for bioethanol production. The aim of this review is to provide a clear overview of these operating conditions for glycogen accumulation.
Research Hotspots and Frontiers of Product R&D Management under the Background of the Digital Intelligence Era—Bibliometrics Based on Citespace and Histcite
Authors: Liu Hongda , Luo Yuxi , Geng Jiejun , Yao Pinbo
Published: July 2021

The rise of “cloud-computing, mobile-Internet, Internet of things, big-data, and smart-data” digital technology has brought a subversive revolution to enterprises and consumers’ traditional patterns. Product research and development has become the main battlefield of enterprise competition, facing an environment where challenges and opportunities coexist. Regarding the concepts and methods of product R&D projects, the domestic start was later than the international ones, and many domestic companies have also used successful foreign cases as benchmarks to innovate their management methods in practice. “Workers must first sharpen their tools if they want to do their jobs well”. This article will start from the relevant concepts of product R&D projects and summarize current R&D management ideas and methods. We combined the bibliometric analysis software Histcite and Citespace to sort out the content of domestic and foreign literature and explore the changing trends of research hotspots. Finally, combined with the analysis of confirmed cases in domestic masters and doctoral dissertations to test the theory, the literature review of the product R&D project management theme was carried out from the dual perspectives of comprehensive theory and practice. This study uses the core collection library of Web of Science as the object of document extraction. Based on the search conditions of “Product development” or “Intergrat* product development”, 8998 sample documents were initially retrieved. The search deadline was June 2019, with a time range from 2000 to June 2019. Then, using the record number of 50 as the critical condition, 5007 analysis samples were deleted, refined, and cleaned. Through the review and measurement of 5007 papers, the analysis showed that: (1) in the last ten years, sustainability, consumer focus, new approaches to product development management, and organizational design have become critical considerations in the product development process stage; (2) at this stage, researchers are paying more attention to the innovation, design, product development, identification, simultaneous engineering, consequence, and stage/gate model aspects of product development; and (3) factors such as long development cycles, high costs, and poor organizational design are now common problems in the product development process.
Multi-Link Magnet Device with Electromagnetic Manipulation System for Assisting Finger Movements with Wireless Operation
Authors: Ji Dong-Min , Kim Min-Su , Kim Sung-Hoon
Published: July 2021

We introduce a new mechanism and control system for wireless assistive finger training. The proposed mechanism and control system can provide natural finger flexion and extension via magnetic force and torque between a driving coil and a multi-link magnetic assist device placed on the fingers. The proposed mechanism is designed to allow normal movement while maintaining a natural finger shape, even when multiple magnets are applied to the fingers. Anatomical features were considered in the design to accommodate the angular changes between the fingers during hand extension and flexion. The magnetic force between the control system and the device on the hand allows extension and flexion of the fingers without the use of wires and electrical motors. The performance of the driving system and the magnetic device were verified through various simulations and experiments. A control program with motion tracking is also developed using LabView software. Hence, a wireless assistive finger training system is successfully realized.
Soil Erosion Estimates in Arid Region: A Case Study of the Koutine Catchment, Southeastern Tunisia
Authors: Ben Zaied Mongi , Jomaa Seifeddine , Ouessar Mohamed
Published: July 2021

Soil erosion remains one of the principal environmental problems in arid regions. This study aims to assess and quantify the variability of soil erosion in the Koutine catchment using the RUSLE (Revised Universal Soil Loss Equation) model. The Koutine catchment is located in an arid area in southeastern Tunisia and is characterized by an annual mean precipitation of less than 200 mm. The model was used to examine the influence of topography, extreme rainstorm intensity and soil texture on soil loss. The data used for model validation were obtained from field measurements by monitoring deposited sediment in settlement basins of 25 cisterns (a traditional water harvesting and storage technique) over 4 years, from 2015 to 2018. Results showed that slope is the most controlling factor of soil loss. The average annual soil loss in monitoring sites varies between 0.01 and 12.5 t/ha/y. The storm events inducing the largest soil losses occurred in the upstream part of the Koutine catchment with a maximum value of 7.3 t/ha per event. Soil erosion is highly affected by initial and preceding soil conditions. The RUSLE model reasonably reproduced (R2 = 0.81) the spatiotemporal variability of measured soil losses in the study catchment during the observation period. This study revealed the importance of using the cisterns in the data-scarce dry areas as a substitute for the classic soil erosion monitoring fields. Besides, combining modeling of outputs and field measurements could improve our physical understanding of soil erosion processes and their controlling factors in an arid catchment. The study results are beneficial for decision-makers to evaluate the existing soil conservation and water management plans, which can be further adjusted using appropriate soil erosion mitigation options based on scientific evidence.
Credit Card Fraud Detection in Card-Not-Present Transactions: Where to Invest?
Authors: Mekterović Igor , Karan Mladen , Pintar Damir , Brkić Ljiljana
Published: July 2021

Online shopping, already on a steady rise, was propelled even further with the advent of the COVID-19 pandemic. Of course, credit cards are a dominant way of doing business online. The credit card fraud detection problem has become relevant more than ever as the losses due to fraud accumulate. Most research on this topic takes an isolated, focused view of the problem, typically concentrating on tuning the data mining models. We noticed a significant gap between the academic research findings and the rightfully conservative businesses, which are careful when adopting new, especially black-box, models. In this paper, we took a broader perspective and considered this problem from both the academic and the business angle: we detected challenges in the fraud detection problem such as feature engineering and unbalanced datasets and distinguished between more and less lucrative areas to invest in when upgrading fraud detection systems. Our findings are based on the real-world data of CNP (card not present) fraud transactions, which are a dominant type of fraud transactions. Data were provided by our industrial partner, an international card-processing company. We tested different data mining models and approaches to the outlined challenges and compared them to their existing production systems to trace a cost-effective fraud detection system upgrade path.
An Accelerated Slicing Algorithm for Frep Models
Authors: Maltsev Evgenii , Popov Dmitry , Chugunov Svyatoslav , Pasko Alexander , Akhatov Iskander
Published: July 2021

Complex 3D objects with microstructures can be modelled using the function representation (FRep) approach and then manufactured. The task of modelling a geometric object with a sophisticated microstructure based on unit cell repetition is often too computationally expensive for CAD systems. FRep provides efficient tools to solve this problem. However, even for FRep the slicing step required for manufacturing can take a significant amount of time. An accelerated slicing algorithm for FRep 3D objects is proposed in this paper. This algorithm allows the preparation of FRep models for 3D printing without surface generation stage. The spatial index is employed to accelerate the slicing process. A novel compound adaptive criterion and a novel acceleration criterion are proposed to speed up the evaluation of the defining function of an FRep object. The use of these criteria is significantly reducing the computational time for contour construction during the slicing process. The K-d tree and R-tree data structures are used as spatial indexes. The performance of the accelerated slicing algorithm was tested. The contouring time was reduced 100-fold due to using the novel compound adaptive criterion with the novel acceleration criterion.
Determination of the Optimal Neural Network Transfer Function for Response Surface Methodology and Robust Design
Authors: Le Tuan-Ho , Jang Hyeonae , Shin Sangmun
Published: July 2021

Response surface methodology (RSM) has been widely recognized as an essential estimation tool in many robust design studies investigating the second-order polynomial functional relationship between the responses of interest and their associated input variables. However, there is scope for improvement in the flexibility of estimation models and the accuracy of their results. Although many NN-based estimations and optimization approaches have been reported in the literature, a closed functional form is not readily available. To address this limitation, a maximum-likelihood estimation approach for an NN-based response function estimation (NRFE) is used to obtain the functional forms of the process mean and standard deviation. While the estimation results of most existing NN-based approaches depend primarily on their transfer functions, this approach often requires a screening procedure for various transfer functions. In this study, the proposed NRFE identifies a new screening procedure to obtain the best transfer function in an NN structure using a desirability function family while determining its associated weight parameters. A statistical simulation was performed to evaluate the efficiency of the proposed NRFE method. In this particular simulation, the proposed NRFE method provided significantly better results than conventional RSM. Finally, a numerical example is used for validating the proposed method.
Degradation Monitoring in Reinforced Concrete with 3D Localization of Rebar Corrosion and Related Concrete Cracking
Authors: Van Steen Charlotte , Verstrynge Els
Published: July 2021

Corrosion of the reinforcement is a major degradation mechanism affecting durability and safety of reinforced concrete (RC) structures. As the corrosion process starts internally, it can take years before visual damage can be noticed on the surface, resulting in an overall degraded condition and leading to large financial costs for maintenance and repair. The acoustic emission (AE) technique enables the continuous monitoring of the progress of internal cracking in a non-invasive way. However, as RC is a heterogeneous material, reliable damage detection and localization remains challenging. This paper presents extensive experimental research aiming at localizing internal damage in RC during the corrosion process. Results of corrosion damage monitoring with AE are presented and validated on three sample scales: small mortar samples (scale 1), RC prisms (scale 2), and RC beams (scale 3). For each scale, the corrosion process was accelerated by imposing a direct current. It is found that the AE technique can detect damage earlier than visual inspection. However, dedicated filtering is necessary to reliably localize AE events. Therefore, AE signals were filtered by a newly developed post-processing protocol which significantly improves the localization results. On the smallest scale, results were confirmed with 3D micro-CT imaging, whereas on scales 2 and 3, results were compared with surface crack width measurements and resulting rebar corrosion levels.
Investigation into the Influence of Division Pier on the Internal Flow and Pulsation in the Outlet Conduit of an Axial-Flow Pump
Authors: Yang Fan , Jiang Dongjin , Wang Tieli , Chang Pengcheng , Liu Chao , Liu Dongsheng
Published: July 2021

The outlet conduit is an important construction connecting the outlet of the pump guide vane and the outlet pool; in order to study the hydraulic performance of the straight outlet conduit of the axial-flow pump device, this paper adopts the method of numerical simulation and analyzes the influence of the division pier on the pressure and velocity distribution inside and near the wall of the straight outlet conduit based on three design schemes. Four pressure pulsation measuring points were arranged in the straight outlet conduit, and the low-frequency pulsation characteristic information inside the straight outlet conduit with and without the division pier was extracted by wavelet packet reconstruction. The results show that the addition of a division pier has an effect on the hydraulic loss, near-wall pressure and velocity distribution in the straight outlet conduit. A small high-pressure zone is formed near the wall at the starting position of the division pier, and a large high-speed zone is formed on the left side at the starting position of the division pier. The length of the division pier has no significant effect on the flow distribution of the straight outlet conduit and the pressure and velocity distribution near the wall. Under different working conditions, each monitoring point has the maximum energy in the sub-band (0~31.25 Hz). With the increase of the flow rate, the total pressure energy of the straight outlet conduit decreases gradually. Under each condition, the difference of the energy proportion of the horizontal monitoring points of the straight outlet conduit is small, and the difference of the energy proportion of the two monitoring points at the top and bottom of the outlet channel is relatively large. The energy of the two monitoring points in the straight outlet conduit with a division pier is smaller than that of the two monitoring points in the straight outlet conduit without a division pier. There are differences in the main frequency and the power spectrum corresponding to the main frequency of the monitoring points in the straight outlet conduit, and the reasonable setting of the division pier is conducive to reducing the pressure pulsation of the flow in the straight outlet conduit and is beneficial to the safe and stable operation of the pump device.
Improving Farmers’ Revenue in Crop Rotation Systems with Plot Adjacency Constraints in Organic Farms with Nutrient Amendments
Authors: Fendji Jean Louis Ebongue Kedieng , Kenmogne Clovis Tchuinte , Fotsa-Mbogne David Jaurès , Förster Anna
Published: July 2021

The search for sustainable agriculture is leading many economies to turn to crop rotation systems and to abandon monoculture systems which generally require increased use of pesticides and synthetic fertilizers. But the optimization of crop rotation remains a challenge, especially when considering organic farming. This work tackles the optimization of crop rotation in traditional organic farms with plot adjacency constraints and nutrient amendments. In the present configuration, each farmer owns a certain quantity of rudimentary equipment and a number of workers, all considered as resources. Farms are subdivided into plots and each plot allows only one crop at a given period. At a given interval of time, each plot receives a certain quantity of nutrient. The generated rotations are of fixed durations for all plots and the objective is to maximize farmers’ income. A linear programming approach is used to determine the solution of the proposed farming model. Three levels of constraints are combined in the linear program to generate realistic rotations: (i) biophysical constraints including crop succession and plot adjacency; (ii) structural constraints including budget and resources; (iii) organizational constraints such as nutrient amendment and market demand. To evaluate the performance of the model, scenarios based on real-world data has been defined and solved using free solvers. The solutions obtained indicate that all the constrains are satisfied. In addition, farmers’ revenue is improved, reaching a stationary position when the quantity of available resources is equal or greater than the quantity of required resources. Finally, Cbc solver is faster than GLPK solver; and it provides solutions on larger instances where GLPK does not.
Will Zirconia Implants Replace Titanium Implants?
Authors: Webber Liana Preto , Chan Hsun-Liang , Wang Hom-Lay
Published: July 2021

This review aims to discuss the advantages and disadvantages of zirconia implants compared with titanium implants. Moreover, it intends to review the relevant available long-term literature of these two materials regarding osteointegration, soft-tissue, microbiota, and peri-implantitis, focusing on clinical results. Briefly, titanium implants are a reliable alternative for missing teeth; however, they are not incapable of failure. In an attempt to provide an alternative implant material, implants made from ceramic-derivate products were developed. Owing to its optimal osseointegration competence, biocompatibility, and esthetic proprieties, zirconium dioxide (ZrO2), also known as zirconia, has gained popularity among researchers and clinicians, being a metal-free alternative for titanium implants with its main use in the anterior esthetic zones. This type of implant may present similar osseointegration as those noted on titanium implants with a greater soft-tissue response. Furthermore, this material does not show corrosion as its titanium analog, and it is less susceptible to bacterial adhesion. Lastly, even presenting a similar inflammatory response to titanium, zirconia implants offer less biofilm formation, suggesting less susceptibility to peri-implantitis. However, it is a relatively new material that has been commercially available for a decade; consequently, the literature still lacks studies with long follow-up periods.
Buckling Behavior of Thin-Walled Stainless-Steel Lining Wrapped in Water-Supply Pipe under Negative Pressure
Authors: Lu Chunqing , Ariaratnam Samuel T. , Yan Xuefeng , Ma Baosong , Zhao Yahong , Xiang Weigang
Published: July 2021

This paper presents a study about the buckling behavior of thin stainless-steel lining (SSL) for trenchless repair of urban water supply networks under negative pressure. The critical buckling pressure and displacement (p–δ) curves, temperature changing curves, hoop and axial strain of the lining monitoring section and the strain changes with system pressure (p–ε) of the lining under the action of different diameters, different lining wall thickness and different ventilation modes were obtained through five groups of full-scale tests. The variation principles of the post-buckling pressure and the reduction regularity of the flowing section of the lining were further investigated. By comparing different pipeline buckling models and introducing thin-shell theory, the buckling model of liner supported by existing pipe was established. The comparison between the test results and thin-shell theory indicates that one of the significances of the enhancement coefficient k value is to change the constraint condition of the aspect ratio, l/R, thus increasing the critical buckling pressure of the lining. Finally, an improved lining buckling prediction model (enhancement model) is presented. A previous test is used as a case study with the results showing that the enhanced model is able to predict critical buckling pressure and lobe-starting amount of the liner, which can provide guidance for trenchless restoration of the liner with thin-walled stainless steel.
Multi-Scale Wind Turbine Bearings Supervision Techniques Using Industrial SCADA and Vibration Data
Authors: Natili Francesco , Daga Alessandro Paolo , Castellani Francesco , Garibaldi Luigi
Published: July 2021

Timely damage diagnosis of wind turbine rolling elements is a keystone for improving availability and eventually diminishing the cost of wind energy: from this point of view, it is a priority to integrate high-level practices into the real-world operation and maintenance of wind farms. On this basis, the present study is devoted to the formulation of reliable methodologies for the supervision of wind turbine bearings, which possibly can be integrated in the industrial practice. For this reason, this study is a collaboration between a company (ENGIE Italia), the University of Perugia and the Politecnico di Torino. The analysis is based on the exploitation of the data types which are available to wind farm managers from industrial control systems: SCADA (Supervisory Control And Data Acquisition) and TCM (Turbine Condition Monitoring). Due to the intrinsic sampling time difference between SCADA and TCM data (a few minutes the former, up to the millisecond for the latter), the proposed methodology is designed as multi-scale. At first, historical SCADA data are processed and the behavior of the oil filter pressure is analyzed for all the wind turbines in the farm: this provides preliminary advice for identifying presumably healthy wind turbines from those suspected of damage. A second step for the SCADA analysis is then represented by the study of the temperature trends of the bearings through a Support Vector Regression: the incoming damage is individuated from the analysis of the mismatch between measurements and estimates provided by the normal behavior model. Finally, the healthy units are selected as the reference and the faulty as the target for the analysis of TCM vibration data in the time domain: statistical features are computed on independent chunks of the signals and, using a Novelty Index, it was possible to distinguish the damaged wind turbines with respect to the reference ones. In light of the interest in application of the proposed methodology, good practice criteria in selecting and managing the data are discussed as well.
Automotive OEM Demand Forecasting: A Comparative Study of Forecasting Algorithms and Strategies
Authors: Rožanec Jože M. , Kažič Blaž , Škrjanc Maja , Fortuna Blaž , Mladenić Dunja
Published: July 2021

Demand forecasting is a crucial component of demand management, directly impacting manufacturing companies’ planning, revenues, and actors through the supply chain. We evaluate 21 baseline, statistical, and machine learning algorithms to forecast smooth and erratic demand on a real-world use case scenario. The products’ data were obtained from a European original equipment manufacturer targeting the global automotive industry market. Our research shows that global machine learning models achieve superior performance than local models. We show that forecast errors from global models can be constrained by pooling product data based on the past demand magnitude. We also propose a set of metrics and criteria for a comprehensive understanding of demand forecasting models’ performance.
Histopathological Evaluation of Tumor-Infiltrating Lymphocytes (TILs) as Predictive Biomarker for Hormone Receptors Status, Proliferative Activity and Clinical Outcome in Her-2 Positive Breast Cancer
Authors: Angelico Giuseppe , Broggi Giuseppe , Caltabiano Rosario , Santoro Angela , Spadola Saveria , D’Alessandris Nicoletta , Scaglione Giulia , Valente Michele , Arciuolo Damiano , Sanchez Alejandro Martin , Franceschini Gianluca , Masetti Riccardo , Mulè Antonino , Zannoni Gian Franco
Published: July 2021

Background: In the present study, we evaluated the prognostic value of TILs as well their relation with clinicopathological factors in patients affected by HER-2 positive breast cancer. Methods: We evaluated 47 patients with a histologically confirmed diagnosis of invasive breast carcinoma showing an immunohistochemically confirmed (score 3+) amplification of the c-erbB-2 gene for the presence of TILs and categorized in three predefined groups of low (0–10% immune cells in stromal tissue within the tumor), intermediate (11–40%), and high TILs (>40%). Results: Low, intermediate and high TILs were found in 17/47 (36%), 23/47 (49%) and 7/47(15%) cases, respectively. It was found that 6/47 cases treated with adjuvant chemotherapy plus trastuzumab underwent progression of the disease; none of these cases exhibited high TILs. It was found that 12/47 patients with a prognostically unfavorable stage of III and IV showed low and intermediate levels of TILs, while high TILs were never observed. A significant association between intermediate/high-levels of TILs, elevated KI 67 index and hormone receptors nuclear staining was observed. High concordance in TILs distribution was observed between preoperative breast biopsies and surgical samples. Conclusions: We observed a positive correlation between the TILs and the response to both adjuvant and neoadjuvant treatments in HER-2 positive BC. High TILs were also related to increased KI-67 index and to the expression of hormone receptors.
Physical Side-Channel Attacks on Embedded Neural Networks: A Survey
Authors: Méndez Real Maria , Salvador Rubén
Published: July 2021

During the last decade, Deep Neural Networks (DNN) have progressively been integrated on all types of platforms, from data centers to embedded systems including low-power processors and, recently, FPGAs. Neural Networks (NN) are expected to become ubiquitous in IoT systems by transforming all sorts of real-world applications, including applications in the safety-critical and security-sensitive domains. However, the underlying hardware security vulnerabilities of embedded NN implementations remain unaddressed. In particular, embedded DNN implementations are vulnerable to Side-Channel Analysis (SCA) attacks, which are especially important in the IoT and edge computing contexts where an attacker can usually gain physical access to the targeted device. A research field has therefore emerged and is rapidly growing in terms of the use of SCA including timing, electromagnetic attacks and power attacks to target NN embedded implementations. Since 2018, research papers have shown that SCA enables an attacker to recover inference models architectures and parameters, to expose industrial IP and endangers data confidentiality and privacy. Without a complete review of this emerging field in the literature so far, this paper surveys state-of-the-art physical SCA attacks relative to the implementation of embedded DNNs on micro-controllers and FPGAs in order to provide a thorough analysis on the current landscape. It provides a taxonomy and a detailed classification of current attacks. It first discusses mitigation techniques and then provides insights for future research leads.
Art Galleries in Transformation: Is COVID-19 Driving Digitisation?
Authors: Habelsberger Beatrix E. M. , Bhansing Pawan V.
Published: July 2021

Compared to other consumer goods markets, art galleries have long been reluctant to innovate through digitisation. However, the global outbreak of COVID-19 forces art galleries to reconsider the role of digital channels. This study aims to provide a better understanding of the art gallery business model and its related difficulties of integrating digital channels into marketing, communication, and sales. Twenty interviews with gallery owners and managers in Vienna and Salzburg were conducted. They were asked about their attitudes towards, opinions on, and experiences with digital channels, and how they reacted to the restrictions caused by COVID-19. The findings verify that COVID-19 has led galleries of any type to reconsider their digital strategy. We identified limitations with respect to digital channels: plain presentation of information online; lacking or distanced personal interaction; online anonymity that disconnects from the social art environment; increased information and price transparency; a more commercial appearance; limited resources for digital adaptations. Galleries striving to integrate digital channels into their business model should pay attention to ensuring that analogue, as well as digital, channels are integrated into a coherent system where personal contact and the physical location remain the core of the business.
The Role of Microbiota in the Pathogenesis of Esophageal Adenocarcinoma
Authors: Gillespie Megan R. , Rai Vikrant , Agrawal Swati , Nandipati Kalyana C.
Published: July 2021

Esophageal adenocarcinoma (EAC) is associated with poor overall five-year survival. The incidence of esophageal cancer is on the rise, especially in Western societies, and the pathophysiologic mechanisms by which EAC develops are of extreme interest. Several studies have proposed that the esophageal microbiome may play an important role in the pathophysiology of EAC, as well as its precursors—gastroesophageal reflux disease (GERD) and Barrett’s esophagus (BE). Gastrointestinal microbiomes altered by inflammatory states have been shown to mediate tumorigenesis directly and are now being considered as novel targets for both cancer treatment and prevention. Elucidating molecular mechanisms through which the esophageal microbiome potentiates the development of GERD, BE, and EAC will provide a foundation on which new therapeutic targets can be developed. This review summarizes current findings that elucidate the molecular mechanisms by which microbiota promote the pathogenesis of GERD, BE, and EAC, revealing potential directions for additional research on the microbiome-mediated pathophysiology of EAC.
Pattern of Urban Flora in Intra-City Railway Habitats (Alexandria, Egypt): A Conservation Perspective
Authors: Heneidy Selim Z. , Halmy Marwa W. A. , Toto Soliman M. , Hamouda Sania K. , Fakhry Amal M. , Bidak Laila M. , Eid Ebrahem M. , Al-Sodany Yassin M.
Published: July 2021

Intra-city railway areas are deemed large greenspaces and are believed to be key in enhancing the diversity and dynamics of urban flora. In the current study, the floristic composition and diversity along intra-city railway and tram tracks in Alexandria were surveyed. The floristic composition of the plant communities in relation to environmental factors, ecological indicators, and level of human impact was analyzed using multivariate analysis (two-way indicator species analysis (TWINSPAN) for classification and detrended correspondence analysis (DECORANA) for ordination. The multivariate ordination techniques (CCA) revealed differences in the environmental factors and climatic factors influencing the floristic composition of the railway and tram track habitats. Tram tracks suffered higher human impact while maintaining higher vitality and cover compared to train tracks. Species recorded were mainly therophytes, followed by phanerophytes and hemicryptophytes dominated by native species; however, invasive species’ contribution was higher compared to surrounding regions. The number of invasive species was greater in railway areas compared to tram track areas (19 and 15, respectively). The occurrence of two endemic species (Sinapis allionii and Sonchus macrocarpus) with limited national distribution highlights the importance of these habitats as valuable refuge areas for rare and endangered species worthy of conservation action.
Repurposing of Antibiotic Sulfisoxazole Inhibits Lipolysis in Pre-Clinical Model of Cancer-Associated Cachexia
Authors: Chitti Sai V. , Marzan Akbar L. , Shahi Sanjay , Kang Taeyoung , Fonseka Pamali , Mathivanan Suresh
Published: July 2021

Clinical management of cancer-associated cachexia, a multi-organ wasting syndrome, has been challenging without effective treatment strategies. An effective treatment that directly targets cancer-induced wasting is desperately needed to improve the quality of life and the survival of cancer patients. Recently, an antibiotic SFX was shown to have anti-tumour and anti-metastatic effects in mouse models of breast cancer. Hence, in this study, we examined the efficacy of SFX in the treatment of cancer-induced cachexia. C26 cachexic mice models were administered with SFX, and the tumour volume and body weight were regularly measured. Blood glucose, skeletal muscles, and adipose tissue were examined at the endpoint. Contrary to a previous study, SFX did not reduce the tumour volume in mice bearing C26 cells. Administration of SFX neither revealed any survival benefit nor rescued C26 cachectic mice from muscle wasting. Interestingly, SFX administration partially rescued (~10%) tumour-induced weight loss by preserving both the subcutaneous and intestinal fat mass. Together, these results suggest that the administration of SFX could partially rescue cancer-induced weight loss by inhibiting lipolysis. As anti-cachexia therapies are scarce, the results could facilitate the design of combinatorial therapies involving SFX, standard-of-care chemotherapeutics, and drugs that inhibit muscle atrophy for the treatment of cancer cachexia.
Optimal Input Representation in Neural Systems at the Edge of Chaos
Authors: Morales Guillermo B. , Muñoz Miguel A.
Published: July 2021

Shedding light on how biological systems represent, process and store information in noisy environments is a key and challenging goal. A stimulating, though controversial, hypothesis poses that operating in dynamical regimes near the edge of a phase transition, i.e., at criticality or the “edge of chaos”, can provide information-processing living systems with important operational advantages, creating, e.g., an optimal trade-off between robustness and flexibility. Here, we elaborate on a recent theoretical result, which establishes that the spectrum of covariance matrices of neural networks representing complex inputs in a robust way needs to decay as a power-law of the rank, with an exponent close to unity, a result that has been indeed experimentally verified in neurons of the mouse visual cortex. Aimed at understanding and mimicking these results, we construct an artificial neural network and train it to classify images. We find that the best performance in such a task is obtained when the network operates near the critical point, at which the eigenspectrum of the covariance matrix follows the very same statistics as actual neurons do. Thus, we conclude that operating near criticality can also have—besides the usually alleged virtues—the advantage of allowing for flexible, robust and efficient input representations.