bluuebunny/crossref_metadata_2025 huggingface dataset:
Fitness Movement Types and Completeness Detection Using a Transfer-Learning-Based Deep Neural Network
Authors: Chen Kuan-Yu , Shin Jungpil , Hasan Md. Al Mehedi , Liaw Jiun-Jian , Yuichi Okuyama , Tomioka Yoichi
Published: August 2022

Fitness is important in people’s lives. Good fitness habits can improve cardiopulmonary capacity, increase concentration, prevent obesity, and effectively reduce the risk of death. Home fitness does not require large equipment but uses dumbbells, yoga mats, and horizontal bars to complete fitness exercises and can effectively avoid contact with people, so it is deeply loved by people. People who work out at home use social media to obtain fitness knowledge, but learning ability is limited. Incomplete fitness is likely to lead to injury, and a cheap, timely, and accurate fitness detection system can reduce the risk of fitness injuries and can effectively improve people’s fitness awareness. In the past, many studies have engaged in the detection of fitness movements, among which the detection of fitness movements based on wearable devices, body nodes, and image deep learning has achieved better performance. However, a wearable device cannot detect a variety of fitness movements, may hinder the exercise of the fitness user, and has a high cost. Both body-node-based and image-deep-learning-based methods have lower costs, but each has some drawbacks. Therefore, this paper used a method based on deep transfer learning to establish a fitness database. After that, a deep neural network was trained to detect the type and completeness of fitness movements. We used Yolov4 and Mediapipe to instantly detect fitness movements and stored the 1D fitness signal of movement to build a database. Finally, MLP was used to classify the 1D signal waveform of fitness. In the performance of the classification of fitness movement types, the mAP was 99.71%, accuracy was 98.56%, precision was 97.9%, recall was 98.56%, and the F1-score was 98.23%, which is quite a high performance. In the performance of fitness movement completeness classification, accuracy was 92.84%, precision was 92.85, recall was 92.84%, and the F1-score was 92.83%. The average FPS in detection was 17.5. Experimental results show that our method achieves higher accuracy compared to other methods.
UAV-Based Smart Educational Mechatronics System Using a MoCap Laboratory and Hardware-in-the-Loop
Authors: Luque-Vega Luis F. , Lopez-Neri Emmanuel , Arellano-Muro Carlos A. , González-Jiménez Luis E. , Ghommam Jawhar , Saad Maarouf , Carrasco-Navarro Rocío , Ruíz-Cruz Riemann , Guerrero-Osuna Héctor A.
Published: August 2022

Within Industry 4.0, drones appear as intelligent devices that have brought a new range of innovative applications to the industrial sector. The required knowledge and skills to manage and appropriate these technological devices are not being developed in most universities. This paper presents an unmanned aerial vehicle (UAV)-based smart educational mechatronics system that makes use of a motion capture (MoCap) laboratory and hardware-in-the-loop (HIL) to teach UAV knowledge and skills, within the Educational Mechatronics Conceptual Framework (EMCF). The macro-process learning construction of the EMCF includes concrete, graphic, and abstract levels. The system comprises a DJI Phantom 4, a MoCap laboratory giving the drone location, a Simulink drone model, and an embedded system for performing the HIL simulation. The smart educational mechatronics system strengthens the assimilation of the UAV waypoint navigation concept and the capacity for drone flight since it permits the validation of the physical drone model and testing of the trajectory tracking control. Moreover, it opens up a new range of possibilities in terms of knowledge construction through best practices, activities, and tasks, enriching the university courses.
Simulation Study of High Sensitivity Fiber SPR Temperature Sensor with Liquid Filling
Authors: Xiong Min , Teng Chuanxin , Chen Ming , Cheng Yu , Deng Shijie , Li Fuwang , Deng Hongchang , Liu Houquan , Yuan Libo
Published: August 2022

In this paper, a high sensitivity fiber temperature sensor based on surface plasmon resonance is designed and studied. In the simulation, the single mode fiber is polished to remove most of the cladding, and then gold and silver films are added. Finally, it is embedded in the heat shrinkable tube filled with a thermo-optic coefficient liquid for curing. The numerical simulation results show that the sensing characteristics are sensitive to the remaining cladding thickness of the fiber, the thickness of the gold film and the thickness of the silver film. When the thermo-optic coefficient of the filling liquid is −2.8 × 10−4/°C, the thickness of the gold film, the thickness of the silver film and the thickness of the remaining cladding of the fiber are 30 nm, 20 nm and 1 μm, respectively. The sensitivity of the sensor designed in this paper can reach −6 nm/°C; this result is slightly higher than that of similar research in recent years. It will have a promising application prospect in flexible wearable temperature sensors, smart cities and other fields.
ECG Patient Simulator Based on Mathematical Models
Authors: Quiroz-Juárez Mario Alan , Rosales-Juárez Juan Alberto , Jiménez-Ramírez Omar , Vázquez-Medina Rubén , Aragón José Luis
Published: August 2022

In this work, we propose a versatile, low-cost, and tunable electronic device to generate realistic electrocardiogram (ECG) waveforms, capable of simulating ECG of patients within a wide range of possibilities. A visual analysis of the clinical ECG register provides the cardiologist with vital physiological information to determine the patient’s heart condition. Because of its clinical significance, there is a strong interest in algorithms and medical ECG measuring devices that acquire, preserve, and process ECG recordings with high fidelity. Bearing this in mind, the proposed electronic device is based on four different mathematical models describing macroscopic heartbeat dynamics with ordinary differential equations. Firstly, we produce full 12-lead ECG profiles by implementing a model comprising a network of heterogeneous oscillators. Then, we implement a discretized reaction–diffusion model in our electronic device to reproduce ECG waveforms from various rhythm disorders. Finally, in order to show the versatility and capabilities of our system, we include two additional models, a ring of three coupled oscillators and a model based on a quasiperiodic motion, which can reproduce a wide range of pathological conditions. With this, the proposed device can reproduce around thirty-two cardiac rhythms with the possibility of exploring different parameter values to simulate new arrhythmias with the same hardware. Our system, which is a hybrid analog–digital circuit, generates realistic ECG signals through digital-to-analog converters whose amplitudes and waveforms are controlled through an interactive and friendly graphic interface. Our ECG patient simulator arises as a promising platform for assessing the performance of electrocardiograph equipment and ECG signal processing software in clinical trials. Additionally the produced 12-lead profiles can be tested in patient monitoring systems.
Optical Fiber Sensors for High-Temperature Monitoring: A Review
Authors: Ma Shaonian , Xu Yanping , Pang Yuxi , Zhao Xian , Li Yongfu , Qin Zengguang , Liu Zhaojun , Lu Ping , Bao Xiaoyi
Published: August 2022

High-temperature measurements above 1000 °C are critical in harsh environments such as aerospace, metallurgy, fossil fuel, and power production. Fiber-optic high-temperature sensors are gradually replacing traditional electronic sensors due to their small size, resistance to electromagnetic interference, remote detection, multiplexing, and distributed measurement advantages. This paper reviews the sensing principle, structural design, and temperature measurement performance of fiber-optic high-temperature sensors, as well as recent significant progress in the transition of sensing solutions from glass to crystal fiber. Finally, future prospects and challenges in developing fiber-optic high-temperature sensors are also discussed.
Low-Cost Wireless Structural Health Monitoring of Bridges
Authors: Komarizadehasl Seyedmilad , Lozano Fidel , Lozano-Galant Jose Antonio , Ramos Gonzalo , Turmo Jose
Published: August 2022

Nowadays, low-cost accelerometers are getting more attention from civil engineers to make Structural Health Monitoring (SHM) applications affordable and applicable to a broader range of structures. The present accelerometers based on Arduino or Raspberry Pi technologies in the literature share some of the following drawbacks: (1) high Noise Density (ND), (2) low sampling frequency, (3) not having the Internet’s timestamp with microsecond resolution, (4) not being used in experimental eigenfrequency analysis of a flexible and a less-flexible bridge, and (5) synchronization issues. To solve these problems, a new low-cost triaxial accelerometer based on Arduino technology is presented in this work (Low-cost Adaptable Reliable Accelerometer—LARA). Laboratory test results show that LARA has a ND of 51 µg/√Hz, and a frequency sampling speed of 333 Hz. In addition, LARA has been applied to the eigenfrequency analysis of a short-span footbridge and its results are compared with those of a high-precision commercial sensor.
Novel Method to Assess Endothelial Function via Monitoring of Perfusion Response to Local Heating by Imaging Photoplethysmography
Authors: Kamshilin Alexei A. , Zaytsev Valeriy V. , Belaventseva Anzhelika V. , Podolyan Natalia P. , Volynsky Maxim A. , Sakovskaia Anastasiia V. , Romashko Roman V. , Mamontov Oleg V.
Published: August 2022

Endothelial dysfunction is one of the most important markers of the risk of cardiovascular complications. This study is aimed to demonstrate the feasibility of imaging photoplethysmography to assess microcirculation response to local heating in order to develop a novel technology for assessing endothelial function. As a measure of vasodilation, we used the relative dynamics of the pulsatile component of the photoplethysmographic waveform, which was assessed in a large area of the outer surface of the middle third of the subject’s forearm. The perfusion response was evaluated in six healthy volunteers during a test with local skin heating up to 40–42 °C and subsequent relaxation. The proposed method is featured by accurate control of the parameters affecting the microcirculation during the prolonged study. It was found that in response to local hyperthermia, a multiple increase in the pulsation component, which has a biphasic character, was observed. The amplitude of the first phase of the perfusion reaction depends on both the initial skin temperature and the difference between the basal and heating temperatures. The proposed method allows the assessment of a reproducible perfusion increase in response to hyperthermia developed due to humoral factors associated with the endothelium, thus allowing detection of its dysfunction.
Strategies for the Accurate Measurement of the Resonance Frequency in QCM-D Systems via Low-Cost Digital Techniques
Authors: Addabbo Tommaso , Fort Ada , Landi Elia , Moretti Riccardo , Mugnaini Marco , Vignoli Valerio
Published: August 2022

In this paper, an FPGA (Field Programmable Gate Array)-based digital architecture for the measurement of quartz crystal microbalance (QCM) oscillating frequency of transient responses, i.e., in QCM-D (QCM and Dissipation) applications, is presented. The measurement system is conceived for operations in liquid, with short QCM transient responses due to the large mechanical load. The proposed solution allows for avoiding the complex processing systems typically required by the QCM-D techniques and grants frequency resolutions better than 1 ppm. The core of the architecture is a reciprocal digital frequency meter, combined with the preprocessing of the QCM signal through mixing operations, such as a step-down of the input frequency and reducing the measurement error. The measurement error is further reduced through averaging. Different strategies are proposed to implement the proposed measurement solution, comprising an all-digital circuit and mixed analog/digital ones. The performance of the proposed architectures is theoretically derived, compared, and analyzed by means of experimental data obtained considering 10 MHz QCMs and 200 μs long transient responses. A frequency resolution of about 240 ppb, which corresponds to a Sauerbrey mass resolution of 8 ng/cm2, is obtained for the all-digital solution, whereas for the mixed solution the resolution halves to 120 ppb, with a measurement time of about one second over 100 repetitions.
Convolutional Neural Network Applied to SARS-CoV-2 Sequence Classification
Authors: Câmara Gabriel B. M. , Coutinho Maria G. F. , Silva Lucileide M. D. da , Gadelha Walter V. do N. , Torquato Matheus F. , Barbosa Raquel de M. , Fernandes Marcelo A. C.
Published: August 2022

COVID-19, the illness caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus belonging to the Coronaviridade family, a single-strand positive-sense RNA genome, has been spreading around the world and has been declared a pandemic by the World Health Organization. On 17 January 2022, there were more than 329 million cases, with more than 5.5 million deaths. Although COVID-19 has a low mortality rate, its high capacities for contamination, spread, and mutation worry the authorities, especially after the emergence of the Omicron variant, which has a high transmission capacity and can more easily contaminate even vaccinated people. Such outbreaks require elucidation of the taxonomic classification and origin of the virus (SARS-CoV-2) from the genomic sequence for strategic planning, containment, and treatment of the disease. Thus, this work proposes a high-accuracy technique to classify viruses and other organisms from a genome sequence using a deep learning convolutional neural network (CNN). Unlike the other literature, the proposed approach does not limit the length of the genome sequence. The results show that the novel proposal accurately distinguishes SARS-CoV-2 from the sequences of other viruses. The results were obtained from 1557 instances of SARS-CoV-2 from the National Center for Biotechnology Information (NCBI) and 14,684 different viruses from the Virus-Host DB. As a CNN has several changeable parameters, the tests were performed with forty-eight different architectures; the best of these had an accuracy of 91.94 ± 2.62% in classifying viruses into their realms correctly, in addition to 100% accuracy in classifying SARS-CoV-2 into its respective realm, Riboviria. For the subsequent classifications (family, genera, and subgenus), this accuracy increased, which shows that the proposed architecture may be viable in the classification of the virus that causes COVID-19.
Application of Internet of Things and Sensors in Healthcare
Authors: Al-kahtani Mohammad S. , Khan Faheem , Taekeun Whangbo
Published: August 2022

The Internet of Things (IoT) is an innovative technology with billions of sensors in various IoT applications. Important elements used in the IoT are sensors that collect data for desired analyses. The IoT and sensors are very important in smart cities, smart agriculture, smart education, healthcare systems, and other applications. The healthcare system uses the IoT to meet global health challenges, and the newest example is COVID-19. Demand has increased during COVID-19 for healthcare to reach patients remotely and digitally at their homes. The IoT properly monitors patients using an interconnected network to overcome the issues of healthcare services. The aim of this paper is to discuss different applications, technologies, and challenges related to the healthcare system. Different databases were searched using keywords in Google Scholar, Elsevier, PubMed, ACM, ResearchGate, Scopus, Springer, etc. This paper discusses, highlights, and identifies the applications of IoT healthcare systems to provide research directions to healthcare, academia, and researchers to overcome healthcare system challenges. Hence, the IoT can be beneficial by providing better treatments using the healthcare system efficiently. In this paper, the integration of the IoT with smart technologies not only improves computation, but will also allow the IoT to be pervasive, profitable, and available anytime and anywhere. Finally, some future directions and challenges are discussed, along with useful suggestions that can assist the IoT healthcare system during COVID-19 and in a severe pandemic.
Identifying Irregular Potatoes Using Hausdorff Distance and Intersection over Union
Authors: Yu Yongbo , Jiang Hong , Zhang Xiangfeng , Chen Yutong
Published: August 2022

Further processing and the added value of potatoes are limited by irregular potatoes. An ellipse-fitting-based Hausdorff distance and intersection over union (IoU) method for identifying irregular potatoes is proposed to solve the problem. First, the acquired potato image is resized, translated, segmented, and filtered to obtain the potato contour information. Secondly, a least-squares fitting method fits the extracted contour to an ellipse. Then, the similarity between the irregular potato contour and the fitted ellipse is characterized using the perimeter ratio, area ratio, Hausdorff distance, and IoU. Next, the characterization ability of the four features is analyzed, and an identification standard of irregular potatoes is established. Finally, we discuss the algorithm’s shortcomings in this paper and draw the advantages of the algorithm by comparison. The experimental results showed that the characterization ability of perimeter ratio and area ratio was inferior to that of Hausdorff distance and IoU, and using Hausdorff distance and IoU as feature parameters can effectively identify irregular potatoes. Using Hausdorff distance separately as a feature parameter, the algorithm achieved excellent performance, with precision, recall, and F1 scores reaching 0.9423, 0.98, and 0.9608, respectively. Using IoU separately as a feature parameter, the algorithm achieved a higher overall recognition rate, with precision, recall, and F1 scores of 1, 0.96, and 0.9796, respectively. Compared with existing studies, the proposed algorithm identifies irregular potatoes using only one feature, avoiding the complexity of high-dimensional features and significantly reducing the computing effort. Moreover, simple threshold segmentation does not require data training and saves algorithm execution time.
A Convolutional Neural-Network-Based Training Model to Estimate Actual Distance of Persons in Continuous Images
Authors: Tsai Yu-Shiuan , Modales Alvin V. , Lin Hung-Ta
Published: August 2022

Distance and depth detection plays a crucial role in intelligent robotics. It enables drones to understand their working environment to avoid collisions and accidents immediately and is very important in various AI applications. Image-based distance detection usually relies on the correctness of geometric information. However, the geometric features will be lost when the object is rotated or the camera lens image is distorted. This study proposes a training model based on a convolutional neural network, which uses a single-lens camera to estimate humans’ distance in continuous images. We can partially restore depth information loss using built-in camera parameters that do not require additional correction. The normalized skeleton feature unit vector has the same characteristics as time series data and can be classified very well using a 1D convolutional neural network. According to our results, the accuracy for the occluded leg image is over 90% at 2 to 3 m, 80% to 90% at 4 m, and 70% at 5 to 6 m.
Natural Materials Modified and Applied to the Detection of Drugs In Situ: Modification of Eggshell and Quantification of Oxytetracycline
Authors: Gomes Helena I. A. S. , Sales M. Goreti F.
Published: August 2022

This work describes a novel sensing system using eggshells as substrate for the first time, targeting the detection and semiquantitative determination of antibiotics in waters from aquaculture, enabling simple, inexpensive, and in situ drug monitoring. Eggshell was ground and the resulting powder was modified by adsorption of suitable reagents, and it takes a typical colour after contact with the antibiotic. The colour intensity is correlated with the concentration of the antibiotic. This novel approach was applied to oxytetracycline, one of the antibiotics commonly used in aquaculture. The chemical changes on the eggshell powder were evaluated and optimised to produce an intense colour change as a function of the concentration of the antibiotic. The colour changes were evaluated by visual comparison with images taken with a digital camera, applying an appropriate mathematical treatment to the colour coordinates of the HSL system used by Windows. The selectivity of the response was tested against other antibiotic drugs. The materials were also used in the analysis of a spiked environmental water sample. Overall, this work presents a rapid, inexpensive, simple and equipment-free method for screening and discrimination of tetracycline drugs in aquaculture. The method is a green approach by reusing eggshells and decreasing the level of contamination correlated to analytical methods, thus being a promising tool for local, rapid, and cost-effective antibiotic monitoring.
Optical Fiber Probe Microcantilever Sensor Based on Fabry–Perot Interferometer
Authors: Chen Yongzhang , Zheng Yiwen , Xiao Haibing , Liang Dezhi , Zhang Yufeng , Yu Yongqin , Du Chenlin , Ruan Shuangchen
Published: August 2022

Optical fiber Fabry–Perot sensors have long been the focus of researchers in sensing applications because of their unique advantages, including highly effective, simple light path, low cost, compact size, and easy fabrication. Microcantilever-based devices have been extensively explored in chemical and biological fields while the interrogation methods are still a challenge. The optical fiber probe microcantilever sensor is constructed with a microcantilever beam on an optical fiber, which opens the door for highly sensitive, as well as convenient readout. In this review, we summarize a wide variety of optical fiber probe microcantilever sensors based on Fabry–Perot interferometer. The operation principle of the optical fiber probe microcantilever sensor is introduced. The fabrication methods, materials, and sensing applications of an optical fiber probe microcantilever sensor with different structures are discussed in detail. The performances of different kinds of fiber probe microcantilever sensors are compared. We also prospect the possible development direction of optical fiber microcantilever sensors.
Leveraging Intellectual Property to Prevent Nuclear War
Authors: Pearce Joshua M.
Published: August 2022

Although international law forbids nuclear attacks, only nine states have mutually assured destruction available to prevent direct attacks against themselves, while non-nuclear states have few substantive options to deter a nuclear attack. This study analyzes the economic impacts of a theoretical international agreement that eliminates patent rights for any nuclear aggressor (i.e., free global compulsory licensing of all intellectual property (IP) for a nuclear aggressor). The results found that all but one of the nuclear states would have a significant economic disincentive to start a nuclear attack if the proposal was put into force. Payback times ranged from 1.2 to 40 years, where the entire GDP of a nuclear aggressor would be needed to offset the loss for aggression, indicate such a mechanism as a whole would be an effective nuclear deterrent. This method would not be universally effective without ensuring all nuclear states are members of the international economy and IP processes. With the growth of open-source products and reduced value of patents, this mechanism does have a limited effectiveness time. Currently it appears to be a policy trajectory worthy of future work that can enhance safety from nuclear threat without causing harm to countries of goodwill.
Mechanism on the Separation of Vanadium and Titanium from Vanadium Slag by Roasting with Ammonium Sulfate
Authors: Zhang Guoquan , Wang Kun , Luo Mingzhi
Published: August 2022

The technology of simultaneously recovering V and Ti from vanadium slag via ammonium salt roasting has proven to be an efficient route. However, due to the phase stability and complex chemical composition of vanadium slag, intermediate materials containing Fe, V, Ti and Mn are difficult to be characterized critically. This work aims to investigate the decomposition and transformation of vanadium slag during ammonium salt roasting, using a combination of FT-IR, XRD, XPS and SEM techniques. It was found that the lattice structure of Fe-contained spinel would be transformed from FeV2O4 to Fe2+VnFe2−nO4 (0 < n < 2) during directly roasting in the air. However, there is no obvious change for Ti-contained and Mn-contained spinel. Using NH4HSO4 (ABS) as an additive and roasting the slag in the N2 atmosphere, those spinels would be decomposed into various sulfate salts. Meanwhile, when the slag was roasted with NH4HSO4 in the air, a part of Fe(II) in (NH4)2Fe(SO4)2 would be transferred into Fe(III), but V(III), Ti(IV) and Mn(II) from those salts would remain the same valance state. Ultimately, about 88% V and 81% Ti were recovered, when vanadium slag was roasted at 663.15 K with a 1:5 ratio of slag-to-NH4HSO4 and followed by 8 vol.% H2SO4 leaching.
Development and Validation of a Novel HPLC Method for the Determination of Ephedrine Hydrochloride in Nasal Ointment
Authors: Kallinteris Konstantinos , Gkountanas Kostas , Karamitros Iοannis , Boutsikaris Haris , Dotsikas Yannis
Published: August 2022

A simple, precise, and cost-effective reverse phase ion pair chromatographic (RP-IP-HPLC) method was developed and validated for the determination of Ephedrine Hydrochloride in a nasal ointment. A simple and fast extraction protocol was developed for the effective recovery of the analyte, and for this purpose, Bromhexine Hydrochloride was used as the internal standard. The mobile phase consisted of MeOH, Sodium Lauryl Sulfate (SLS) 49.8 mM, triethylamine (ET3N) in the ratio of 65:34.6:0.4%, respectively, with pH = 2.20. The detection of the compounds was carried out at 206 nm, and we used a PDA detector. A short run time was achieved with retention times of 6.3 min and 9.8 min for ephedrine hydrochloride and the internal standard, respectively. The proposed method was validated according to ICH guidelines. Linearity was confirmed in the range of 50–150 μg/mL. Recoveries results were within the range of 98–102% and precision < 2% for the analyte in spiked blank matrix. Robustness testing was conducted via a fractional factorial experimental design. The method was found to fulfill the required specifications for specificity and stability for both standard solutions and samples, as well and applied to the determination of ephedrine hydrochloride in nasal ointments produced by the Greek Military Pharmaceutical Laboratories.
Complaints Analysis as an Opportunity to Counteract Social Transport Exclusion in Shared Mobility Systems
Authors: Turoń Katarzyna
Published: August 2022

Modern cities are associated with efficient transportation, including modern transportation solutions that reflect the trend towards sustainable development. These solutions, for example, are shared mobility services, which have gained popularity in recent years. The systems present in the markets, as well as each transport service, aimed at meeting the transport needs of the society, are also associated with the occurrence of many problems. Many of the problems can turn into transport barriers and have a real impact on the quality of transport services and the life of society in the city. To check whether transport problems occurring in shared mobility may translate into transport exclusion, the author’s own research was proposed. The aim of the study was to analyze the public negative opinions of the shared mobility services and to determine the existence of their connection with the main areas of the phenomenon of transport exclusion. The Desk Research method was used for the study, due to which 1500 opinions and complaints regarding 60 bike-, car-, and scooter-sharing applications operating in six European countries were analyzed. As a result of the research, it was shown that in all types of shared mobility, there are barriers that users complain about. These barriers are connected to the main transport social exclusion aspects indicated in the Church’s method framework. The leading areas of grievance are the system infrastructure and operational aspects. The mobile applications used to run the systems turned out to be the least problematic. Based on the results obtained, recommendations for the elimination of transportation social barriers were developed. The work supports municipalities and operators who wish to reduce the problems associated with shared mobility systems in cities.
Museums as a Means to (Re)Make Regional Identities: The Oltenia Museum (Romania) as Case Study
Authors: Popescu Liliana , Albă Claudia
Published: August 2022

In recent decades, ever more museums have begun to put a new emphasis on the education of the public, playing an important role in creating national or regional identities. This paper aims to assess the strategy chosen by the History Section of the Oltenia Museum in Craiova (Romania) to use knowledge, objects and narratives to create a sense of belonging and negotiate identities. Site visits, participant observations and discussions with museum curators, the analysis of texts and discourses were used in order to see if there is a master narrative related to regional identity and to determine the elements used to shape this identity. The results of this study point to the fact that there is an underlying master narrative of the exhibition, stressing the dominant understanding of Oltenia’s identity stemming mainly from cultural markers such as religion and language, while acknowledging wider European influences on the national and regional identity.
RETRACTED: The Commodification Dilemma: Tourism Pressure and Heritage Conservation in Barcelona
Authors: Mazzamuto Marina , Picone Marco
Published: August 2022

In recent years, the proliferation of tourists in the urban environment has generated several issues in the functioning of cities. As urban tourism has historically been linked to cultural and architectural attractions, this increased tourism pressure has involved and often compromised the common heritage uses. Therefore, many cases saw the implementation of measures that, if on the one hand reduced tourist flows, on the other also drastically restricted the access for residents and totally altered the sense of place in the community. This article explores this topic by applying a Critical Discourse Analysis methodology to the dispute that took place in Barcelona regarding the restricted access to Park Güell. The main results of this work concern the instrumentalisation of both the UNESCO label and participatory processes in the case of Barcelona, along with the failure of regulative measures to solve the problems related to tourism pressure. The article advocates the usage of more qualitative-oriented analyses to address the relationships between urban planning, heritage management and tourism management.
When Higher Education Meets Sustainable Development of Rural Areas: Lessons Learned from a Community–University Partnership
Authors: Mancini Maria Cecilia , Arfini Filippo , Guareschi Marianna
Published: August 2022

Sustainable development in mountain areas faces numerous socioenvironmental and economic challenges that public institutions have sought to address for decades. The EU is increasingly demanding Higher Education Institutions be more socially relevant and responsible in addressing the needs of these often-underserved communities. To this end, one central principle of the Erasmus+ Project 2014–2020, also consolidated by the Programme 2021–2027, has been to enhance the development, transfer, and implementation of innovative practices fostering social engagement at the local and international levels. The paper describes a case study developed in the “Socially Engaged Universities—(SEU)” project, co-funded by the Erasmus+ Programme 2014–2020, which aimed to strengthen the cooperation between universities and local communities. A local foundation and the University of Parma co-piloted a project to strengthen the short supply chains of a group of farmers in the Italian Appennines. The partnership identified factors that fostered and hampered the effectiveness of community–university partnerships. We propose some final recommendations to ensure that sustainable rural development fully leverages university resources. This includes higher education teaching and research programmes tailored toward the needs of the local community.
Enough Crises to Choose from: The Perceived Sense of Crisis in Panama
Authors: Barsallo Gabisel , Mendoza Elisa
Published: August 2022

The COVID-19 health crisis and its consequences have exacerbated existing issues in the political, economic, and cultural spheres of societies. An exploratory, descriptive, mixed-method study using a phenomenological interpretative approach was conducted to identify the perceptions of Panamanian residents on what type of crisis the country is facing, who is responsible, and how should it be dealt with? This study relies on one online survey distributed across social media platforms over a 5-month period in 2020, generating a non-probabilistic convenience sample of 561 persons. Demographic variables and open-ended questions were included in the survey. We conclude that education, health, and labor were the most commonly identified crises. Training, civic engagement, and solidarity were acknowledged as critical in overcoming the crisis. There is a strong tendency to delegate these overcoming responsibilities exclusively to government authorities. The perception of the crisis varies depending on the respondent’s educational level. Higher educational levels encourage a more active and self-reflective response to the circumstances, and the desire to seek social support through community networks corresponds to this perception. This encompasses positive aspects such as the opportunity for a change and improving one’s quality of life, and negative aspects such as increased distrust of government institutions and ruling politicians.
‘Live with the Virus’ Narrative and Pandemic Amnesia in the Governance of COVID-19
Authors: Davis Mark David McGregor
Published: August 2022

Political leaders have commonly used the phrase ‘learn to live with the virus’ to explain to citizens how they should respond to the COVID-19 pandemic. I consider how the ‘live with the virus’ narrative perpetrates pandemic amnesia by refusing what is known about pandemic-related inequities and the strategies that can be used to overcome these effects. Advice to ‘live with the virus’ helps to further austerity public policy and therefore individualises the social and health burdens of post pandemic life. ‘Live with the virus’ asks citizens to look only to their own futures, which are political strategies that might work for privileged individuals who have the capacity to protect their health, but less well for those with limited personal resources. I draw on Esposito’s framing of affirmative biopolitics and scholarship on how excluded communities have built for themselves health-sustaining commons in responses to pandemic threats to health. I argue that creating opportunities for a ‘COVID-19 commons’ that can enlarge capacity for citizenly deliberation on how they have been governed and other pandemic related matters is vital for the development of more ethical and equitable post-pandemic politics.
The Rating Scale Paradox: Semantics Instability versus Information Loss
Authors: Giacomelli Jacopo
Published: August 2022

Rating systems are applied to a wide variety of different contexts as a tool to map a large amount of information to a symbol, or notch, chosen from a finite, ordered set. Such a set is commonly known as the rating scale, and its elements represent all the different degrees of quality—in some sense—that a given rating system aims to express. This work investigates a simple yet nontrivial paradox in constructing that scale. When the considered quality parameter is continuous, a bijection must exist between a specific partition of its domain and the rating scale. The number of notches and their meanings are commonly defined a priori based on the convenience of the rating system users. However, regarding the partition, the number of subsets and their amplitudes should be chosen a posteriori to minimize the unavoidable information loss due to discretization. Considering the typical case of a creditworthiness rating system based on a logistic regression model, we discuss to what extent this contrast may impact a realistic framework and how a proper rating scale definition may handle it. Indeed, we show that choosing between a priori methods, which privilege the meaning of the rating scale, and a posteriori methods, which minimize information loss, is not strictly necessary. It is possible to mix the two approaches instead, choosing a hybrid criterion tunable according to the rating model’s user needs.
Reciprocal Data Transformations and Their Back-Transforms
Authors: Griffith Daniel A.
Published: August 2022

Variable transformations have a long and celebrated history in statistics, one that was rather academically glamorous at least until generalized linear models theory eclipsed their nurturing normal curve theory role. Still, today it continues to be a covered topic in introductory mathematical statistics courses, offering worthwhile pedagogic insights to students about certain aspects of traditional and contemporary statistical theory and methodology. Since its inception in the 1930s, it has been plagued by a paucity of adequate back-transformation formulae for inverse/reciprocal functions. A literature search exposes that, to date, the inequality E(1/X) ≤ 1/(E(X), which often has a sizeable gap captured by the inequality part of its relationship, is the solitary contender for solving this problem. After documenting that inverse data transformations are anything but a rare occurrence, this paper proposes an innovative, elegant back-transformation solution based upon the Kummer confluent hypergeometric function of the first kind. This paper also derives formal back-transformation formulae for the Manly transformation, something apparently never done before. Much related future research remains to be undertaken; this paper furnishes numerous clues about what some of these endeavors need to be.
Metro System Inundation in Zhengzhou, Henan Province, China
Authors: Yang Hao , Zhao Linshuang , Chen Jun
Published: August 2022

In this study, we investigated the flooding accident that occurred on Metro Line 5 in the capital city of Zhengzhou, Henan Province, China. On 20 July 2021, owing to an extreme rainstorm, serious inundation occurred in the Wulongkou parking lot of Zhengzhou Metro Line 5 and its surrounding area. Flooding forced a train to stop during operation, resulting in 14 deaths. Based on our preliminary investigation and analysis of this accident, we designed three main control measures to reduce the occurrence of similar accidents and mitigate the impact of similar accidents in the future, given the increasing number of extreme storm weather events in recent years: (1) to conduct subway flood risk assessments and to establish an early warning system, involving real-time monitoring of meteorological information during subway operation and construction; (2) to improve subway flood control emergency plans and to establish a response mechanism for subway flooding; and (3) to strengthen safety awareness training to ensure the orderly evacuation of people after accidents.
The Development of the New Process of Design for Six Sigma (DFSS) and Its Application
Authors: Yang Ching-Chow , Jou Yung-Tsan , Lin Ming-Chang , Silitonga Riana Magdalena , Sukwadi Ronald
Published: August 2022

The Six Sigma program has been widely adopted by industries worldwide since the late-1990s due to GE’s successful implementation, though Motorola initiated it in 1987. Several quality experts, such as Juran and Feigenbaum and several researchers, have concluded that the poor quality in product design will cause vast and chronic costs, which the Six Sigma improvement may not eliminate. The focus of new product development is needed to transfer the quality improvement from the later phases of the Design Life Cycle to the early grades. It is necessary to adopt the “Design for Six Sigma” (DFSS) methodology to achieve the best performance in the early stages and focus on ‘prevention’ instead of ‘problem-solving. In this research, we develop a new DFSS process, including Define, Identify, Measure, Design, Optimize, and Verify (DIMDOV), based on the in-depth study of DFSS and the author’s rich consultant experience. The new DFSS process can be confirmed to be a robust methodology, used to assure the design quality of the product design and manufacturing process design by the application results.
Structuring Circular Objectives and Design Strategies for the Circular Economy: A Multi-Hierarchical Theoretical Framework
Authors: Franconi Alessio , Ceschin Fabrizio , Peck David
Published: August 2022

Most frameworks for dealing with the complexity of designing for the circular economy have limitations in terms of correlating different domains of knowledge, correlating highly complex design strategies, and facilitating the process of design strategies’ discovery and development. This paper discusses how managers and designers can create products that can be circulated for several life cycles by considering five different circular objectives (i.e., maintenance/longevity, reuse, refurbishment, remanufacture and/or recycling). To achieve one or more of these objectives, multiple design strategies can be used at various phases of each product life cycle and throughout the product’s lifetime. A literature review is used in this article to evaluate how circular objectives and design strategies are classified in terms of relevance, product life cycle phases, and product life cycles. The three classifications are merged to create a novel conceptual framework, which is then tested through the use of four circular case studies to map out life cycles, circular objectives, and design strategies. The framework may help managers and designers better understand how their businesses and products interact along the supply chain, allowing them to establish more effective product lifetime plans.
Factors Influencing Interdisciplinary Research and Industry-Academia Collaborations at Six European Universities: A Qualitative Study
Authors: Ursić Luka , Baldacchino Godfrey , Bašić Željana , Sainz Ana Belén , Buljan Ivan , Hampel Miriam , Kružić Ivana , Majić Mia , Marušić Ana , Thetiot Franck , Tokalić Ružica , Markić Leandra Vranješ
Published: August 2022

The introduction of interdisciplinarity and industry-academia collaborations (IAC) into higher education institutions (HEIs) and curricula as tools for promoting sustainable development has been debated both in academic and non-academic contexts. While overall rising trends in the acceptance of interdisciplinarity and IAC exist, research has stressed difficulty in implementation and practices. We conducted eight focus groups at six European Universities (members of the SEA-EU alliance) and analysed the transcripts using Braun and Clarke’s reflexive thematic approach to qualitative analysis in order to develop themes on barriers and facilitators to both conducting interdisciplinarity and IAC, as well as the inclusion of university students in interdisciplinary research. We observed that the main barriers to IR and IAC and the inclusion of students in such activities include traditional HEI structures focused on single-discipline approaches, a lack of joint platforms for IR and IAC, and academic differences (publication outcome differences, academic background). Likewise, a lack of funding (especially for early career researchers), employability (for students willing to do a research career), and a lack of validation by HEIs for researchers conducting IR and IAC are major barriers. To IDR- and IAC-related activities, a top-down approach is needed to restructure HEIs and make them more accommodating to both students and staff willing to conduct IR and IAC activities, thus refocusing them towards sustainability.
Mainstreaming Smart Agroforestry for Social Forestry Implementation to Support Sustainable Development Goals in Indonesia: A Review
Authors: Octavia Dona , Suharti Sri , Murniati  , Dharmawan I Wayan Susi , Nugroho Hunggul Yudono Setio Hadi , Supriyanto Bambang , Rohadi Dede , Njurumana Gerson Ndawa , Yeny Irma , Hani Aditya , Mindawati Nina , Suratman  , Adalina Yelin , Prameswari Diana , Hadi Etik Erna Wati , Ekawati Sulistya
Published: August 2022

The increasing need for forest resources and cultivated land requires a solution in forest management to realize sustainable land use. Smart agroforestry (SAF) is a set of agriculture and silviculture knowledge and practices that is aimed at not only increasing profits and resilience for farmers but also improving environmental parameters, including climate change mitigation and adaptation, biodiversity enhancement, and soil and water conservation, while assuring sustainable landscape management. SAF, a solution for land management systems to reduce the rate of deforestation, is a smart effort to overcome the food crisis and mitigate climate change that is prospectively applied mainly in the social forestry area. Optimized forest land utilization could be achieved by implementing SAF and applying silvicultural and crop cultivation techniques to optimize productivity and meet sustainability and adaptability goals. This paper reviews the existing conditions, opportunities, and challenges in the mainstreaming of SAF in social forestry implementation to support the Sustainable Development Goals in Indonesia. Mainstreaming SAF should include policy innovation and regulation implementation, the use of appropriate technology, and compromises or trade-offs among benefits, risks, and resources. SAF is a strategy to revive the rural economy and community prosperity through the optimal use of local resources as well as a form of smart landscape and land-use management that has significant roles in soil and water conservation, bioenergy, climate change responses, and enhanced biodiversity conservation.