Soft Measurements Research Articles

Quantitative in vivo micro-computed tomography for monitoring disease activity and treatment response in a collagen-induced arthritis mouse model

A painful, chronic condition, Rheumatoid Arthritis, is marked by bone erosion and soft tissue swelling at the joint. As treatments are investigated in pre-clinical models, characterizing disease progression is integral to assessing treatment efficacy. Here, in vivo and ex vivo micro-computed tomography (µCT) are used in parallel with traditional caliper score measurement to quantify physiological changes in the tarsal region in a murine, collagen-induced arthritis model. In vivo imaging methods, which are validated here through comparison to ex vivo and caliper methods, afford longitudinal analysis of both bone and soft tissue through a single image acquisition. This method removes the subjectivity of swelling quantification which is inherently associated with traditional caliper measurements. Histopathology offers an additional assessment of bone erosion and inflammation by providing a microscopic characterization of disease activity. In comparison to untreated animals, daily prednisolone (glucocorticoid) treatment is shown to restore bone volume, as reflected through in vivo and ex vivo µCT images, as well as histopathology. Prednisolone-associated reduction in inflammation is shown through in vivo µCT soft tissue volume measurements, paw caliper measurements, and histopathology. The findings reported here provide a comprehensive validation of in vivo µCT with a sensitivity that enables characterization of pre-clinical disease assessment in response to treatment in a murine, collagen-induced arthritis model.

Development of a low-cost textile sensor based insole to monitor foot pressure of diabetic patients

A common but preventable complication of diabetes is diabetic foot ulcer. If appropriate care is not provided such foot lesions progress to the most severe diabetic foot complication, like infection, gangrene, amputation and even death. Diabetic neuropathy results abnormal planter pressure points under the foot and triggers the tendency of foot ulcer. The aim of this paper is to present the development of a low cost, power efficient, soft, lightweight and simple in-shoe planter pressure measurement system. The system is capable to determine the average static pressure under ball and heel of the foot. The insole is comfortable due to the use of textile pressure sensor and its simple data acquisition method makes operation easy for the users. An experiment with 10 participants with and without diabetes was carried out to observe the outcome of the system. The practical implication of this study is to minimise the damage caused by foot ulcer by determining the pressure abnormality at earliest with a fully developed cost effective design. The system is capable to identify the difference in average planter pressure values in different groups of participants. To monitor the foot health proactively, the proposed system is found to be a useful device and can successfully scan the planter pressure under ball and heel of the foot.

Addressing Legitimacy Concerns in Antitrust Private Litigation Involving China’s State-Owned Enterprises

China’s Anti-Monopoly Act (AML) incorporated key antitrust provisions inspired by EU antitrust concepts into China’s law in 2007. By analysing leading post-2007 antitrust cases heard before China’s courts taken by private parties challenging State-Owned Enterprises (SOEs) anti-competitive activities, the authors argue in this significant and original contribution that, despite the AML's enactment, China’s Judiciary has not accepted antitrust Legitimacy. Leading antitrust cases challenging SOEs anti-competitive activities, taken by either consumers or enterprises are analysed, highlighting the contrast with how EU antitrust jurisprudence deals with similar matters. The analysis illustrates how China’s courts have applied key antitrust concepts (such as abuse of dominant position, prohibition of market-sharing; price-fixing; etc.) in a questionable manner. Given that the understanding of such concepts are accepted in over 125 jurisdictions, this raises major questions about the Legitimacy and Effectiveness of antitrust principles in the legal system of the world’s most dynamic economy. That there is an antitrust Legitimacy and Effectiveness problem to be addressed has been recently partially recognized by the State in China, with the putting forward of reform proposals by its antitrust regulator (the State Administration of Markets Regulator (SAMR)) in 2020 in an effort to get major State agencies to recognize the primacy of antitrust. However, these reform proposals omitted reference to the Judiciary’s role in antitrust enforcement against SOEs, even though they play a large role in the economy. The article demonstrates how the reform proposals, which appeared in October 2021 in the AML Amendment Bill 2021, will not solve the private antitrust enforcement Legitimacy problems identified by the authors in cases involving SOEs. Several suggestions to overcome judicial deference to SOEs’ overly robust anti-competitive practices are proposed by the authors, including soft measures that in the long run may be more effective than legislative change. The article also discusses the need for the AML to incorporate a single economic entity test and a collective dominance test in order to give the courts dealing with allegations of SOE anti-competitive behaviour a more comprehensive conceptual toolbox to assist the courts make findings of dominance. Without movement also on the judicial side, the authors conclude that the Legitimacy of antitrust principles will continue to be in question inside China’s legal framework, and consequently the Effectiveness of private antitrust remedies will continue to be weak in one of the world’s largest economies. * Anti-Monopoly Act 2007, Competition Law, China Antitrust, Abuse of Dominance, Price-Fixing, SAMR, SOEs, private antitrust enforcement, Court of Justice, Anti-Monopoly Amendment Bill

Dissemination of terrorist content online and service provider liability: an overview of the EU legal framework

Nowadays, due to the global reach of technology, the Internet is the most commonly used medium of information. The purpose of this article is to illustrate what the European Union (EU) has done so far regarding the fight against dissemination of terrorist content through digital platforms. Both hard law and soft measures were adopted to set rules and obligations the service providers must comply with in order to prevent the dissemination of terrorist content through their services. The conclusion discusses the need to find a balance between the protection of fundamental rights and public security and includes some suggestions to improve existing rules. The methodology used includes documentary analysis and bibliographic research.

Reliability of cone beam CT for morphometry of nasolabial soft tissue in patients with skeletal class III malocclusion: A qualitative and quantitative analysis.

To assess reliability of cone-beam CT (CBCT) for nasolabial soft tissue measurements in patients with skeletal class III malocclusion based on 3-dimensional (3D) facial scanner results. CBCT and 3D facial scan images of 20 orthognathic patients are used in this study. Eleven soft tissue landmarks and 15 linear and angular measurements are identified and performed. For qualitative evaluation, Shapiro-Wilk test and Bland-Altman plots are applied to analyze the equivalence of the measurements derived from these two kinds of images. To quantify specific deviation of CBCT measurements from facial scanner, the latter is set as a benchmark, and mean absolute difference (MAD) and relative error magnitude (REM) for each variable are also calculated. Statistically significant differences are observed in regions of nasal base and lower lip vermilion between two methods. MAD value for all length measurements are less than 2 mm and for angular variables < 8°. The average MAD and REM for length measurements are 0.94 mm and 5.64%, and for angular measurements are 2.27° and 3.78%, respectively. The soft tissue results measured by CBCT show relatively good reliability and can be used for 3D measurement of soft tissue in the nasolabial region clinically.

Sentiment and firm behavior during the COVID-19 pandemic

How did optimism or pessimism about the duration of shutdowns during the COVID-19 pandemic affect firms’ business outlook and behavior? In a large panel of German firms, we identify sentiment as the only plausible determinant of the cross-sectional variation in the expected shutdown length because this variation is uncorrelated with fundamentals. Firms incorporate this sentiment regarding the shutdown duration in their more general business outlook. Sentiment was also an important determinant of firms’ crisis response: More pessimistic firms—those that perceived the shutdown to last longer—were more likely to implement strong measures like layoffs or canceling investments. The implementation of soft measures, e.g., working from home, was unrelated to the sentiment regarding the shutdown length.

Electron-momentum dependence of electron-phonon coupling underlies dramatic phonon renormalization in YNi2B2C

Electron-phonon coupling, i.e., the scattering of lattice vibrations by electrons and vice versa, is ubiquitous in solids and can lead to emergent ground states such as superconductivity and charge-density wave order. A broad spectral phonon line shape is often interpreted as a marker of strong electron-phonon coupling associated with Fermi surface nesting, i.e., parallel sections of the Fermi surface connected by the phonon momentum. Alternatively broad phonons are known to arise from strong atomic lattice anharmonicity. Here, we show that strong phonon broadening can occur in the absence of both Fermi surface nesting and lattice anharmonicity, if electron-phonon coupling is strongly enhanced for specific values of electron-momentum, k. We use inelastic neutron scattering, soft x-ray angle-resolved photoemission spectroscopy measurements and ab-initio lattice dynamical and electronic band structure calculations to demonstrate this scenario in the highly anisotropic tetragonal electron-phonon superconductor YNi2B2C. This new scenario likely applies to a wide range of compounds.

Shaping inclusiveness of a transportation system: Factors affecting seat-yielding behavior of university students in public transportation

The continuous increase in the elderly population and the need for disability-inclusive public transportation propelled authorities to implement policies to ensure seat availability for vulnerable users. Although most public transportation provides a few priority seats for vulnerable users, the seat availability problem remains due to its small quantity and its usage by normal passengers. To extend the theory of planned behavior (TPB), this study aims to evaluate how empathic concerns, attitude, injunctive norms, descriptive norms, and perceived behavioral control contribute to the behavioral intentions and actual conducts of yielding seats to vulnerable passengers with university students’ survey responses in China. A partial least square path modeling based structural equation modeling (SEM) approach is employed to test the postulated hypotheses. Findings reveal that empathic concerns significantly promote the yielding seat intention and, thus, the actual conduct through its impacts on attitude, injunctive norms, and perceived behavioral control. This study also aims at capturing sociodemographic heterogeneity through multi-group comparison. It is found that a university student passenger who is older or more educated perceives greater control about seat yielding behavior, positively influencing their intention to yield their seat to a vulnerable person. In addition, less frequent public transportation usage is found to significantly accompany a higher tendency to yield a seat when required. The implications of “soft measures” to support the transportation policy for a sustainable and disability-inclusive public transportation service are discussed accordingly.

МЯГКИЕ ИЗМЕРЕНИЯ, КАК ЭФФЕКТИВНЫЙ ИНСТРУМЕНТ АНАЛИЗА И ОЦЕНКИ ПРИНИМАЕМЫХ УПРАВЛЕНЧЕСКИХ РЕШЕНИЙ

In the realities of today, soft measurements and calculations are part of new information technologies, computer technology (sixth generation). The branch of soft computing represents the direction of soft measurements. It should be noted that the information technologies of the components in this branch are implemented according to the principle of unity of measurement processes (with metrological support of solutions). The consequence of this is the possibility of applying the advantages of soft computing to a new direction of soft measurements. This advantage may be the speed of processing or a variety of forms of presentation of results. The application of these advantages is aimed at improving the measurement result in the process of its implementation. The areas of application for soft computing systems are becoming wider, the computing power is increasing, and for the first time we are also able to purposefully assess the quality of the result obtained and regulate it.

A newly designed compact CEY-XAFS cell in the soft X-ray region and its application to surface XAFS measurements under ambient-pressure conditions without photoinduced side effects.

We report a newly designed compact cell to measure XAFS spectra with the conversion electron yield (CEY) method in the soft X-ray region under ambient-pressure gas conditions. Secondary electrons generated from the gas and sample by collision of X-ray-absorption-induced Auger electrons are collected by a positively biased collector electrode to obtain XAFS spectra. It was confirmed that this cell is applicable to soft X-ray surface XAFS measurements for different types of materials such as insulating organic materials and metal oxides under 1 bar gas conditions. During the measurements, photoinduced side effects were observed; i.e. photoinduced degradation of organic materials and photoinduced reduction/oxidation of metal oxides. We found that these photoinduced side effects can be sufficiently suppressed by controlling the measuring conditions. The presented measuring approach will enable surface XAFS spectra to be obtained in the soft X-ray region for various types of functional materials under ambient-pressure working conditions.

Design scheme of metal wastewater purification device in industrial park

Due to the limitation of chemical process technology and management system, the traditional treatment mode of heavy metal waste liquid pollution has many problems, such as high power consumption in the process, high wear of consuming steel, high management cost, and secondary pollution caused by complex solid waste residue in data detection. Team based on the front end of deep learning module and backend soft measurement model of collaborative structures, design and improvement of the learning algorithm combined with nested integration depth control series new front end treatment module, the successful implementation of heavy metal ions in industrial wastewater concentration of accurate prediction, and according to the predicted results and the analysis of liquid ingredients, targeted treatment after intelligent classification.

Novel SVD integrated with GBDT based Virtual Sample Generation and Its Application in Soft Sensor

With the coming of the big data era, data-driven based modeling approaches have become the hot research topic in recent years. Unfortunately, due to the limitation of the actual process, the data is basically in a steady state and it is difficult to obtain enough high-quality data, which is defined as the small sample (SS) problem. Recently, to deal with the SS problem, a virtual sample generation (VSG) approach based on the distribution of the original data has been taken into account. In this paper, a VSG method based on singular value decomposition (SVD) feature decomposition and gradient boosting decision tree (GBDT) prediction model (SVD-GBDT) is proposed. In the proposed SVD-GBDT method, firstly, the distribution characteristics of the original data are used to extract the main features and expand the number of samples by using the SVD algorithm. Then the GBDT algorithm is used to find the virtual output of the virtual samples by the SVD method. Finally, SVD and GBDT are combined to complete the sample expansion (SVD-GBDT-VSG). In this paper, we choose the purified terephthalic acid (PTA) industrial process to verify the effectiveness of the proposed methodology. Simulation results show that compared with related methods, the proposed SVD-GBDT-VSG algorithm in this paper can achieve sample expansion well and at the same time can effectively improve the accuracy performance of soft measurement.

Evolution of Flood Defense Strategies: Toward Nature-Based Solutions

Flood defense strategies have evolved from hard-engineered systems to nature-based solutions that advocate for sustainability to meet today’s environmental, social, and economic goals. This paper aims to analyze the historical progression and evolutionary trends in flood control strategies that have led to nature-based solutions. An evaluative literature review was conducted to narrate the evolution of nature-based flood management approaches for different flood types, river floods, coastal floods, and stormwater run-offs. The analysis reflected three evolutionary trends: the transformation of hard measures to soft measures; secondly, the increase in society’s attention to ecosystems and their services; and, finally, divergence from single-function solutions to multi-function solutions. However, continuous monitoring and evaluation of the previous projects and adapting to the lessons learned are the key to progress towards sustainable flood management strategies and their societal acceptance.

Soft measurement of effluent index in sewage treatment process based on overcomplete broad learning system

To measure whether the sewage treatment meets the standards, biochemical oxygen demand (BOD5) is often used to determine, but the measurement of this indicator often has a long time lag and difficult to observe the real-time changes of BOD5, which brings inconvenience to the industrial process. The soft measurement technology based on neural network can realize BOD5 prediction at every moment by means of auxiliary variables, which has attracted people’s attention. However, there are still two problems with soft measurement technology, neural network-based soft measurement technology has high computational complexity and a certain time delay in measurement; and it cannot handle non-Gaussian data well. To solve them, this paper introduces an over-complete broad learning system (OBLS) based on feature fusion to deal with the problems of real-time measurement of BOD5 in sewage treatment industrial process. In view of the data characteristics, the feature extraction ability of the BLS is improved, the non-Gaussian characteristic of sewage data is captured by the method of Overcomplete Independent Component Analysis (OICA), and the OBLS is used to deal with the real-time soft measurement. Compared with state-of-the-art methods on the sewage standard test platform, the measurement accuracy of the proposed algorithm is found to be higher and the performance is more stable.

Research on variable pitch control strategy of direct-driven offshore wind turbine using KELM wind speed soft sensor

This study proposes a modeling method of soft measurement of offshore wind speed using Kernal Extreme Learning Machine (KELM). The soft measurement model of offshore wind speed is presented based on the data-driven method and kernel function extreme learning machine. An improved gray Wolf optimization algorithm is applied to optimize its parameters to enhance the measurement accuracy. Finally, based on the established offshore wind speed measurement model, a feedforward and feedback variable rotor controller is designed and verified by simulation, which proves the effectiveness of the research in this study.

Developing policy packages for low-carbon passenger transport: A mixed methods analysis of trade-offs and synergies

Transformation to climate neutrality of the transport sector raises multiple challenges at a time, with potentially conflicting objectives and further external effects. This calls for a balanced policy package of which empirical assessment is needed in order to i) quantify its effectiveness and ii) reveal effects of potential overlaps and interactions associated with individual measures within the package. This paper analyses the economic, environmental and distributional effects of a policy package that supports low-carbon passenger transport in Austria, co-developed with policy experts and stakeholders. The package includes hard measures such as a mandated phase-out of conventional cars and explicit road pricing, as well as soft measures to foster the uptake of public transportation. To assess these packages we make use of a computable general equilibrium model for Austria that incorporates heterogeneous household groups, CO2 emissions and a detailed representation of the transport sector. We show that the decoupling of economic welfare and negative external effects of passenger transport is possible with a balanced policy package. Our analysis also highlights potential urban-rural conflicts, regressive impacts and negative public budget implications of single policy measures, issues that the suggested policy package as a whole can mitigate.

Hierarchical soft measurement of load current and state of charge for future smart lithium-ion batteries

Accurate current measurement is indispensable for the management of lithium-ion battery (LIB), especially for the state-of-charge (SOC) estimation. However, accurate current sensing is challenging in electric vehicles (EVs) due to the electromagnetic interference. Moreover, the currents across the parallel branches of battery pack are even unmeasurable due to the absence of current sensor. Motivated by this, this paper proposes a hierarchical soft measurement framework for the load current and SOC addressing different degrees of current sensor uncertainty. Rooted from a common least squares (LS)-based state optimization problem, a total least square (TLS)-based modification is proposed and solved to compensate for the measurement disturbances, and in accordance to estimate the SOC more accurately. One step further, an input-free optimization method is proposed to co-estimate the SOC and load current without using the current measurements. Simulation and experimental results suggest that the proposed hierarchical framework can realize high-fidelity co-estimation of the SOC and load current, especially in the adverse scenarios of both strong noise corruption and current sensor malfunction/missing. The encouraging results open new paradigms for both the high-robustness current-free SOC estimation and the hardware-free soft current measurement of LIB.

Characterization of an X-ray Source Generated by a Portable Low-Current X-Pinch

An X-pinch scheme of a low-current generator (45 kA, 50 ns rise time) is characterized as a potential efficient source of soft X-rays. The X-pinch target consists of wires of 5 μm in diameter—made from either tungsten (W) or gold (Au)-plated W—loaded at two angles of 55° and 98° between the crossed wires. Time-resolved soft X-ray emission measurements are performed to provide a secure correlation with the optical probing results. A reconstruction of the actual photodiode current profile procedure was adopted, capable of overcoming the limits of the slow rising and falling times due to the “slow” response of the diodes and the noise. The pure and Au-plated W deliver an average X-ray yield, which depends only on the angle of the crossed wires, and is measured to be ~50 mJ and ~70 mJ for the 98° and 55° crossed wire angles, respectively. An additional experimental setup was developed to characterize the X-pinch as a source of X-rays with energy higher than ~6 keV, via time-integrated measurements. The X-ray emission spectrum was found to have an upper limit at 13 keV for the Au-plated W configuration at 55°. The portable tabletop X-pinch proved to be ideal for use in X-ray radiography applications, such as the detection of interior defects in biological samples.

Application of the Coastal Hazard Wheel for Coastal Multi-Hazard Assessment and Management in the Guang-Dong-Hongkong-Macao Greater Bay Area

The coasts of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) are facing threats and challenges from rising sea levels, frequent extreme events and human intervention. In this study, the Coastal Hazard Wheel (CHW) was used to classify the coasts of GBA, assess its hazard change from 2010 to 2020, identify hazards hotspots and explore available coastal management options. The results show that the coastal types of GBA in 2010 and 2020 are consistent, with delta/low estuary island and hard rock slope as the main types. GBA is vulnerable to ecosystem disruption, saltwater intrusion, gradual inundation and flooding hazards. Compared with 2010, the high risk proportion of each hazard in 2020 decreased significantly, but the high risk of flooding increased slightly. All kinds of hazards are interdependent and influenced by each other. The Pearl River Estuary, the east bank of Yamen Waterway, the west bank of Huangmao Sea and Dapeng Bay show very high hazard vulnerability, and the flooding risk is the highest. Soft measures such as coastal zoning, tsunami warning systems, wetland restoration and hazard simulation are most widely used in coastal management. CHW is applicable to GBA’s coastal hazard vulnerability assessment, which provides a case study for coastal risk assessment of GBA and has certain reference significance for hazard management and sustainable development for the Bay Area.

Recommendations for Creating Codes of Conduct for Processing Personal Data in Biobanking Based on the GDPR art.40.

Personal data protection has become a fundamental normative challenge for biobankers and scientists researching human biological samples and associated data. The General Data Protection Regulation (GDPR) harmonises the law on protecting personal data throughout Europe and allows developing codes of conduct for processing personal data based on GDPR art. 40. Codes of conduct are a soft law measure to create protective standards for data processing adapted to the specific area, among others, to biobanking of human biological material. Challenges in this area were noticed by the European Data Protection Supervisor on data protection and Biobanking and BioMolecular Resources Research Infrastructure–European Research Infrastructure Consortium (BBMRI.ERIC). They concern mainly the specification of the definitions of the GDPR and the determination of the appropriate legal basis for data processing, particularly for transferring data to other European countries. Recommendations indicated in the article, which are based on the GDPR, guidelines published by the authority and expert bodies, and our experiences regarding the creation of the Polish code of conduct, should help develop how a code of conduct for processing personal data in biobanks should be developed.