bluuebunny/crossref_metadata_2025 huggingface dataset:
Early Fire Detection Using Long Short-Term Memory-Based Instance Segmentation and Internet of Things for Disaster Management
Authors: Malebary Sharaf J.
Published: November 2023

Fire outbreaks continue to cause damage despite the improvements in fire-detection tools and algorithms. As the human population and global warming continue to rise, fires have emerged as a significant worldwide issue. These factors may contribute to the greenhouse effect and climatic changes, among other detrimental consequences. It is still challenging to implement a well-performing and optimized approach, which is sufficiently accurate, and has tractable complexity and a low false alarm rate. A small fire and the identification of a fire from a long distance are also challenges in previously proposed techniques. In this study, we propose a novel hybrid model, called IS-CNN-LSTM, based on convolutional neural networks (CNN) to detect and analyze fire intensity. A total of 21 convolutional layers, 24 rectified linear unit (ReLU) layers, 6 pooling layers, 3 fully connected layers, 2 dropout layers, and a softmax layer are included in the proposed 57-layer CNN model. Our proposed model performs instance segmentation to distinguish between fire and non-fire events. To reduce the intricacy of the proposed model, we also propose a key-frame extraction algorithm. The proposed model uses Internet of Things (IoT) devices to alert the relevant person by calculating the severity of the fire. Our proposed model is tested on a publicly available dataset having fire and normal videos. The achievement of 95.25% classification accuracy, 0.09% false positive rate (FPR), 0.65% false negative rate (FNR), and a prediction time of 0.08 s validates the proposed system.
Practical Considerations for Laser-Induced Graphene Pressure Sensors Used in Marine Applications
Authors: Van Volkenburg Tessa , Ayoub Daniel , Alemán Reyes Andrea , Xia Zhiyong , Hamilton Leslie
Published: November 2023

Small, low-power, and inexpensive marine depth sensors are of interest for a myriad of applications from maritime security to environmental monitoring. Recently, laser-induced graphene (LIG) piezoresistive pressure sensors have been proposed given their rapid fabrication and large dynamic range. In this work, the practicality of LIG integration into fieldable deep ocean (1 km) depth sensors in bulk is explored. Initially, a design of experiments (DOEs) approach evaluated laser engraver fabrication parameters such as line length, line width, laser speed, and laser power on resultant resistances of LIG traces. Next, uniaxial compression and thermal testing at relevant ocean pressures up to 10.3 MPa and temperatures between 0 and 25 °C evaluated the piezoresistive response of replicate sensors and determined the individual characterization of each, which is necessary. Additionally, bare LIG sensors showed larger resistance changes with temperature (ΔR ≈ 30 kΩ) than pressure (ΔR ≈ 1–15 kΩ), indicating that conformal coatings are required to both thermally insulate and electrically isolate traces from surrounding seawater. Sensors encapsulated with two dip-coated layers of 5 wt% polydimethylsiloxane (PDMS) silicone and submerged in water baths from 0 to 25 °C showed significant thermal dampening (ΔR ≈ 0.3 kΩ), indicating a path forward for the continued development of LIG/PDMS composite structures. This work presents both the promises and limitations of LIG piezoresistive depth sensors and recommends further research to validate this platform for global deployment.
On the Benefits of Listen before Talk Scheme for NB-Fi Networks
Authors: Pavlova Irina , Bankov Dmitry , Khorov Evgeny , Lyakhov Andrey
Published: November 2023

NB-Fi (Narrow Band Fidelity) is a promising protocol for low-power wide-area networks. NB-Fi networks use license-exempt Industrial, Scientific, and Medical (ISM) bands and, thus, NB-Fi devices can work in two modes: with and without Listen Before Talk (LBT). This paper compares these modes with different implementations of LBT in terms of packet loss rate (PLR), delay, energy consumption, and throughput. Interestingly, in some scenarios, the results contradict expectations from the classic papers on channel access because of the peculiarities of the NB-Fi technology. These contradictions are explained in the paper. The results show that LBT can significantly improve all the considered performance indicators when the network load exceeds 40 packets per second. With extensive simulation, we show that in a small NB-Fi network, the optimal PLR, delay, and energy consumption are obtained with the implementation of LBT that corresponds to non-persistent CSMA. In a large NB-Fi network, where some devices can be hidden from others, the best strategy to improve PLR, delay, throughput, and energy consumption is to use the implementation of LBT that corresponds to p-persistent CSMA.
Ultrasonic Thickness Measurement Method and System Implementation Based on Sampling Reconstruction and Phase Feature Extraction
Authors: Gong Wenqiang , Wang Xuanze , Yang Zhenyu , Zhai Zhongsheng , Feng Wei , Liu Da
Published: November 2023

The existing ultrasonic thickness measurement systems require high sampling frequencies for echo signal acquisition, leading to complex circuit designs and high costs. Moreover, extracting the characteristics of ultrasonic echo signals for accurate thickness measurement poses significant challenges. To address these issues, this paper proposes a method that utilizes conventional sampling frequencies to acquire high-frequency ultrasonic echo signals, overcoming the limitations of high-frequency data acquisition imposed by the Nyquist–Shannon sampling theorem. By employing an improved sampling reconstruction technique, the multi-cycle sampling signals are reconstructed and rearranged within a single cycle, effectively increasing the equivalent sampling frequency. Additionally, a combination of coarse estimation using fast Fourier transform (FFT) and precise phase extraction using the moving sine fitting algorithm is proposed for accurate thickness measurement, resolving the limitations of common thickness measurement methods such as peak detection, envelope detection, and Hilbert autocorrelation in terms of low measurement accuracy. Experimental results obtained from thickness measurements on 45 steel ultrasonic test blocks within the range of 3 mm to 20 mm indicate a measurement error of ±0.01 mm, while for thicknesses ranging from 1 mm to 50 mm, the measurement error is ±0.05 mm.
Real-Time Optimal States Estimation with Inertial and Delayed Visual Measurements for Unmanned Aerial Vehicles
Authors: Sun Xinxin , Zhang Chi , Zou Le , Li Shanhong
Published: November 2023

Motion estimation is a major issue in applications of Unmanned Aerial Vehicles (UAVs). This paper proposes an entire solution to solve this issue using information from an Inertial Measurement Unit (IMU) and a monocular camera. The solution includes two steps: visual location and multisensory data fusion. In this paper, attitude information provided by the IMU is used as parameters in Kalman equations, which are different from pure visual location methods. Then, the location of the system is obtained, and it will be utilized as the observation in data fusion. Considering the multiple updating frequencies of sensors and the delay of visual observation, a multi-rate delay-compensated optimal estimator based on the Kalman filter is presented, which could fuse the information and obtain the estimation of 3D positions as well as translational speed. Additionally, the estimator was modified to minimize the computational burden, so that it could run onboard in real time. The performance of the overall solution was assessed using field experiments on a quadrotor system, compared with the estimation results of some other methods as well as the ground truth data. The results illustrate the effectiveness of the proposed method.
A Methodology of Condition Monitoring System Utilizing Supervised and Semi-Supervised Learning in Railway
Authors: Shim Jaeseok , Koo Jeongseo , Park Yongwoon
Published: November 2023

In this paper, research was conducted on anomaly detection of wheel flats. In the railway sector, conducting tests with actual railway vehicles is challenging due to safety concerns for passengers and maintenance issues as it is a public industry. Therefore, dynamics software was utilized. Next, STFT (short-time Fourier transform) was performed to create spectrogram images. In the case of railway vehicles, control, monitoring, and communication are performed through TCMS, but complex analysis and data processing are difficult because there are no devices such as GPUs. Furthermore, there are memory limitations. Therefore, in this paper, the relatively lightweight models LeNet-5, ResNet-20, and MobileNet-V3 were selected for deep learning experiments. At this time, the LeNet-5 and MobileNet-V3 models were modified from the basic architecture. Since railway vehicles are given preventive maintenance, it is difficult to obtain fault data. Therefore, semi-supervised learning was also performed. At this time, the Deep One Class Classification paper was referenced. The evaluation results indicated that the modified LeNet-5 and MobileNet-V3 models achieved approximately 97% and 96% accuracy, respectively. At this point, the LeNet-5 model showed a training time of 12 min faster than the MobileNet-V3 model. In addition, the semi-supervised learning results showed a significant outcome of approximately 94% accuracy when considering the railway maintenance environment. In conclusion, considering the railway vehicle maintenance environment and device specifications, it was inferred that the relatively simple and lightweight LeNet-5 model can be effectively utilized while using small images.
Cognitive Support Technology for People with Intellectual Disabilities: Factors for Successful Implementation
Authors: Looze Michiel de , Wilschut Ellen , Könemann Reinier , Kranenborg Kim , De Boer Harry
Published: November 2023

In Europe, large numbers of people with disabilities are willing to work but have problems finding a job. One of the barriers to this is job complexity, particularly for those with low education, low IQ, or cognitive impairments. Digital technologies might help. Specifically, cognitive support technology (CST) has the potential to make jobs less complex and thus more accessible. CST may concern step-by-step digital instructions presented with monitors, tablets, smart phones, beamer projections, or near-eye displays. Based on cross-case evaluations, we aimed to define the success factors in the process of technology selection, development, and implementation. Four cases, situated at public social firms which offer jobs to people with disabilities, were selected. In each case, the optimal form of CST was selected. A qualitative analysis of subjective experiences of work accessibility, performance, usability, and acceptance was applied. The results were positive for most participants in most cases. Once installed, the CST was successful in simplifying jobs. A proportion of the workforce for which a specific job had been considered too complex was able to perform that job when supported by CST. Moreover, a majority of people judged the usability of the technology positively. For the consecutive steps of selection, development, and implementation, we ended up with eleven factors of success; these included, among others, shared and transparent decision making (in technology selection), the iterative and active involvement of workers to optimally adjust work instructions (in technology development), and explicit attention for psychosocial barriers (in technology implementation).
Maritime Network Analysis Based on Geographic Information System for Water Supply Using Shipboard Seawater Desalination System
Authors: Shin Yonghyun , Koo Jaewuk , Lee Juwon , Nam Sook-Hyun , Kim Eunju , Hwang Tae-Mun
Published: November 2023

Small islands are supplied with water from underground sources, simple seawater desalination facilities, or water supply shipment. However, this water supply can be interrupted because of the sudden depletion of groundwater, as groundwater level prediction is inaccurate. Additionally, seawater desalination facilities are difficult to maintain, resulting in frequent breakdowns. When the water tank capacity is below a certain level, island residents contact the water supply shipment manager to request a shipment from land. In Korea, a seawater desalination plant project using ships was newly attempted to solve the water supply problem for island regions. Through this project, an attempt was made to supply water to many island areas suffering water supply disruptions due to drought. The purpose of this study is to compare water supply routes to multiple island regions using existing water supply shipment with desalination plants on ships through network analysis based on a geographic information system. To optimize sailing route, length (m), road connection type, and name of each road section, actual operation data, distance, etc., were set up on a network dataset and analyzed. In addition, the operational model predicted the stability of water supply using the GoldSim simulator. As a result, when sailing on the optimal route based on network analysis, the existing water supply routes could be reduced (2153 km -> 968 km) by more than 55%, and operational costs can be verified to be reduced. Additionally, the validity of the network analysis results was confirmed through actual travel of the representative route.
Global Digital Analysis for Science Diplomacy on Climate Change and Sustainable Development
Authors: Fuentes Miguel , Cárdenas Juan Pablo , Olivares Gastón , Rasmussen Eric , Salazar Soledad , Urbina Carolina , Vidal Gerardo , Lawler Diego
Published: November 2023

Addressing climate change requires innovative, collective action and robust international collaboration. Through joint efforts, nations can significantly reduce greenhouse gas emissions, pioneer sustainable technologies, and implement effective adaptation measures. Science diplomacy and knowledge sharing hold the potential to bolster global stability and peace by directly confronting climate change challenges. Therefore, it becomes imperative to evaluate a country’s alignment of its scientific knowledge system (SKS) with international guidelines. This study delineates the global scientific discourse on climate change and juxtaposes the alignment between an individual nation’s research endeavors and United Nations resolutions concerning climate change and sustainable development. Our methodology integrates data extraction from scientific research databases with advanced textual analysis tools, highlighting this study’s unique focus on the intersection of climate change and UN resolutions. To deliver an empirical analysis, we leveraged complex network theory and advanced text-processing techniques. Our findings demonstrate the trajectory of global scientific output related to these themes, segmented by countries and coupled with CO2 emissions data, key disciplines, and collaboration networks. These insights are instrumental for leaders, policymakers, and stakeholders, highlighting areas of convergence and divergence in national research initiatives essential for achieving global climate goals. Such knowledge is strategically useful for crafting purpose-driven public policies and honoring enduring multilateral pledges to address the climate crisis proactively.
Preliminary Risk Assessment of Geological Disasters in Qinglong Gorge Scenic Area of Taihang Mountain with GIS Based on Analytic Hierarchy Process and Logistic Regression Model
Authors: Ma Ruixia , Lyu Yan , Chen Tianbao , Zhang Qian
Published: November 2023

Qinglong Gorge Scenic Area (QGSA) boasts stunning natural landscapes, characterized by towering peaks and extensive cliffs. Nevertheless, the intricate geological backdrop and distinctive topographical conditions of this area give rise to various geological disasters, posing a substantial safety concern for tourists and presenting ongoing operational and safety management challenges for the scenic area. In light of these challenges, this study placed its focus on the geological disasters within QGSA and sought to assess risks across various scales. The assessment was accomplished through a combination of methods, including field surveys conducted in 2022, remote sensing interpretation, and comprehensive data collection and organization. For the geological disaster risk assessment of the scenic area, this research selected seven key indicators, encompassing terrain factors, geological elements, structural characteristics, and other relevant factors. The assessment utilized a logistic regression model, which yielded satisfactory results with an AUC value of 0.8338. Furthermore, a model was constructed incorporating seven indicators, encompassing factors such as population vulnerability, material susceptibility, and the vulnerability of tourism resources. To assess vulnerability to geological disasters, the Analytic Hierarchy Process (AHP) was employed, resulting in a CR of 0, thus ensuring the reliability of the findings. The outcomes of the risk assessment indicate that the low-risk area covers a substantial expanse of 5.45 km2, representing 53.66% of the total area. The moderate-risk area extends over 3.59 km2, constituting 35.43%, while the high-risk area encompasses 0.72 km2, accounting for 7.14%. Additionally, the very high-risk area encompasses 0.38 km2, making up 3.77% of the total area. Consequently, building upon the findings of the risk assessment, this paper introduces a risk classification and control prevention system. This system provides invaluable insights for disaster prevention and control in mountainous and canyon-type scenic areas.
Decarbonization in the Automotive Sector: A Holistic Status Quo Analysis of Original Equipment Manufacturer Strategies and Carbon Management Activities
Authors: Poligkeit Joseph , Fugger Thomas , Herrmann Christoph
Published: November 2023

The automotive sector is a significant contributor to global carbon emissions and, as such, to climate change. However, there is currently no publicly available sector-wide insight into the extent to which Original Equipment Manufacturers (OEMs) in the automotive sector have implemented decarbonization strategies and carbon management activities. This paper addresses this issue by collecting and analyzing the implementation status of all OEMs with annual sales of more than 500,000 light-duty vehicles. For this purpose, a structured set of criteria is developed that allows conclusions to be drawn for several areas of corporate carbon management. The analysis shows a sector-wide implementation of decarbonization strategies and carbon management activities. However, significant regional differences in external communication, data transparency and methodological inconsistencies emerge. This study provides both academics and practitioners in the automotive industry with valuable insights into current reporting practices, target setting and communicated mitigation actions. On this basis, scientists can project possible greenhouse gas (GHG) emission pathways, align their research with the focus of practitioners to provide them with science-based data, and work on the methodological inconsistencies. Furthermore, the developed criteria provide a useful toolbox for the holistic analysis of other industries.
Physical Asset Life Cycle Evaluation Models—A Comparative Analysis towards Sustainability
Authors: Farinha José Torres , Raposo Hugo D. N. , de-Almeida-e-Pais José Edmundo , Mendes Mateus
Published: November 2023

In order to reach a sustainable circular economy, it is important to maximise the life cycle of a Physical Asset. An evaluation of a Physical Asset Life Cycle can be conducted via several approaches, and these may provide different results. The differences may be insignificant, but they must be taken into consideration because they have consequences for a manager’s decisions. This allows for a wider time interval to decide when to withdraw a Physical Asset or renew it and/or if it ought to continue functioning when profits are higher than expenses, thus allowing for a reduction in waste and increase in sustainability. These are some of the aspects that are discussed in this paper; it presents several models for the evaluation of the Physical Asset Life Cycle, considering the market value, devaluation methods and a more generalised use of Fisher’s Equation, which can include the Risk Tax, among others. The results are discussed based on data that support evaluations obtained with the models, and these are used for each Life Cycle model with the aim of evaluating the differences among them. Not only do all of the models consider expenses, namely those in Investment and Functioning, but also profits, which allows for a more holistic evaluation of the Physical Asset Life Cycle. The models are significantly versatile, allowing for a quantitative evaluation of changes in maintenance policies, energy price variations, risks, variations of profits according to the real market and so on. The results demonstrate the robustness of the approach described and indicate that it maximises the Physical Asset Life Cycle, allowing for the consumption of world resources to be minimised and, as a result, contributing to a more sustainable world.
Local Government Debt and Corporate Investment Behavior in China: Real versus Financial Investment
Authors: Wu Yuanlin , Tian Cunzhi , Wang Guannan
Published: November 2023

The ongoing expansion of local government debt (LGD) in China constitutes a significant impediment to economic development, while the existing literature predominantly concentrates on macro-level investigations, neglecting the repercussions of government debt expansion on firms. Firms serve as fundamental constituents of the real economy, and the suitability of their investment structure is a pivotal determinant of their robust development. Therefore, it is of great significance to investigate whether the investment structure of non-financial firms will undergo deviations attributable to the expansion of local government debt. This paper uses a two-way fixed-effects model to examine the causal effect of local government debt on firms’ investment structures. The quasi-natural experiment using the DID model with “Document 43” issued by China on local government debt governance as a policy shock can be a good endogeneity test. It is found that local government debt exacerbates the trend of “exit from real to virtual” of enterprises, leading to a bias towards financial investment in the investment structure of enterprises, and this result is still robust after a series of robustness tests. A heterogeneity analysis shows that the impact of LGD on the investment structure of firms mainly exists in non-state-owned firms, small-scale firms, and firms with high financing constraints. Overall, this study provides new evidence on how the government influences the investment structure of Chinese firms through the perspective of LGD, which helps firms to prevent and cope with the risks associated with LGD. Furthermore, it offers practical references and policy insights for government initiatives in the realm of local debt governance.
Sustainable Multi-Objective Models for Waste-to-Energy and Waste Separation Site Selection
Authors: Taghipour Atour , Foukolaei Parvaneh Zeraati , Ghaedi Maryam , Khazaei Moein
Published: November 2023

In the past, the Iranian government has excessively relied on fossil fuels, gas, and oil resources, leading to energy-related issues and increasing power outages in the provinces during peak seasons. One of the best opportunities for energy production in Iran is through the establishment of bio-methane and waste-based energy parks. This research aims to determine the optimal locations for waste sorting centers and the establishment of waste-to-energy plants. The coexistence and interaction of these two facilities will enhance system efficiency. To achieve this goal, two mathematical models, with three objectives, have been designed. The static allocation model assigns each industrial park to a waste sorting center, while the dynamic allocation model selects the shortest route from the industrial park to the waste-to-energy center. The first objective is to minimize establishment costs, while the second and third objectives aim to reduce the system’s waiting costs. Waiting for waste shipments leads to pollution, and the desirability and route length can increase the likelihood of organic pollution. Therefore, this research seeks to minimize these factors. The model results indicate that the sorting and energy production centers have been selected to incur the lowest establishment, transportation, and waiting costs. Additionally, the sensitivity analysis section of the model reveals the impact of coefficient changes on the model’s results.
TiO2/Arabic Gum for Degradation of Pollutants in Water
Authors: Lopes Anderson , Araújo Francisca P. , Damasceno Dihego , Honório Luzia M. C. , Morais Alan I. S. , Almeida Luciano C. , Garcia Ramón Peña , Silva-Filho Edson C. , Furtini Marcelo B. , Osajima Josy A.
Published: November 2023

Emerging contaminants and pollution are environmental problems threatening public health. Antibiotic ciprofloxacin and methylene blue dye are pollutants frequently detected in water systems worldwide. Photocatalysis is a process for water treatment. TiO2-based catalysts synthesized with natural gums show improved photocatalytic properties. Here, the sol–gel method synthesized TiO2/Arabic gum for photocatalytic performance. The innovation of this work was synthesized at 400 °C and investigated their photocatalytic proprieties using methylene blue and ciprofloxacin as model pollutants. XRD showed that the photocatalyst was in the anatase phase. The result showed that TiO2 with a band gap of 3.29 eV was achieved at a calcination temperature of 400 °C. Corresponding FTIR results suggest only the existence of functional groups related to TiO2. The SEM and BET method characterization indicated that TiO2/Arabic gum were spherical-shaped nanoparticles arranged in clusters with a mesoporous structure, contributing to photocatalytic performance. In addition, photocatalytic studies showed that the methylene blue dye and ciprofloxacin antibiotic degradation rates reached 99% and 94% under UV light, respectively. The hole (h+) and OH ⦁ radicals are essential in photodegradation. The synthesized material showed excellent photostability and maintained almost the same degradation percentage in the three consecutive cycles tested on the different pollutants. The TiO2/Arabic gum is an excellent candidate for future use in treating contaminants in aqueous media using photocatalysis. Therefore, TiO2/Arabic gum nanoparticles are a promising material for wastewater treatment.
Investigating the Effect of an Elliptical Bluff Body on the Behavior of a Galloping Piezoelectric Energy Harvester
Authors: Roohi Reza , Akbari Masoud , Karimzadeh Ali , Amiri Mohammad Javad
Published: November 2023

The extraction of energy from naturally oscillating objects has recently garnered considerable attention from researchers as a robust and efficient method. This study specifically focuses on investigating the performance of a galloping piezoelectric micro energy harvester (GPEH) designed for self-powered microelectromechanical systems (MEMS). The proposed micro energy harvester comprises a cantilever beam composed of two layers, one being silicon and the other being a piezoelectric material (PZT-5A). The harvester is equipped with an elliptical tip cylinder, and the entire system is modeled using lumped parameters. To simulate the response of the system, the size-dependent coupled governing equations are numerically solved, enabling the extraction of the dynamic behavior of the energy harvester. Furthermore, computational fluid dynamics (CFD) simulations are employed to model the effect of the flow field on the oscillations of the beam. Different aspect ratios (AR) of the elliptical cylinder are taken into account in the simulations. The study examines the impact of the aspect ratio and mass of the elliptical tip cylinder on the harvested power of the system. The results demonstrate a notable decrease in the extracted power density for AR = 1 and 2 compared to higher aspect ratios. In the case of AR = 5, the device exhibits an onset wind speed of 7 m/s. However, for AR = 10, the onset wind speed occurs at a lower wind velocity of 5.5 m/s, resulting in a 66% increase in extracted power compared to AR = 5. Additionally, the results reveal that increasing the normalized mass from 10 to 60 results in a 60% and 70% increase in the output power for AR = 5 and AR = 10, respectively. This study offers valuable insights into the design and optimization of galloping piezoelectric micro energy harvesters, aiming to enhance their performance for MEMS applications.
Contributions of the 5G Network with Respect to Decent Work and Economic Growth (Sustainable Development Goal 8): A Systematic Review of the Literature
Authors: Beltozar-Clemente Saul , Iparraguirre-Villanueva Orlando , Pucuhuayla-Revatta Félix , Sierra-Liñan Fernando , Zapata-Paulini Joselyn , Cabanillas-Carbonell Michael
Published: November 2023

Decent work and economic growth are fundamental elements for the sustainable development of a society, with Sustainable Development Goal 8 (SDG8) being one of the key objectives of the United Nations’ 2030 Agenda. The 5G network has great potential to contribute significantly to the achievement of SDG8, offering faster and more reliable connectivity, which opens up new possibilities for innovation, operational efficiency, and job creation. The present study aimed to investigate the role of 5G technologies concerning decent work and economic growth (SDG8). As part of the method, 265 articles extracted from main databases such as Scopus, IEEExplore, and ScienceDirect were analyzed using the PRISMA methodology, resulting in 74 relevant articles after applying the inclusion and exclusion criteria. As a result, a greater contribution to the use of the 5G network was identified in sectors such as manufacturing, health, and transportation, generating greater economic growth and job creation. It was also found that the technological applications with the greatest contributions are “Internet of Things” and “Artificial intelligence”. Finally, it was concluded that the results of this review are useful for future research on technologies that support 5G networks, contributing to economic growth and equitable and sustainable decent work in a wide range of sectors and rural areas.
Creating the Culture for Sustainable Innovation: A Gamified Approach
Authors: Bellosi Francesco , Spadafora Maria , Rapaccini Mario
Published: November 2023

This research proposes a gamified approach to creating a culture for sustainable-oriented innovation. Specifically, we use action research to explore the mechanisms through which business decision-makers (such as entrepreneurs, executives and managers) reflect on their practices and obstacles to innovation, and then we use gamification to stimulate the involvement and creativity of managers. The main contribution of this paper is the design of a one-day gamified workshop in which participants collaborate first to identify common values and then to drive the co-creation of sustainable innovations. The workshop has been applied with managers of a real company to evaluate its playability and to validate its effectiveness in creating a culture for sustainable innovation.
Multifunctional Forest Restoration in Brazil: A Critical Analysis of the Trends and Knowledge Gaps in the Scientific Literature
Authors: Santos João Paulo Bispo , Romanelli João Paulo , Gardon Fernando Ravanini , Krainovic Pedro Medrado , de Resende Angélica Faria , Souza Lukas Rodrigues , Piotto Daniel , Rodrigues Ricardo Ribeiro
Published: November 2023

The global demand for forest products will increase in the coming decades due to population growth and increasing environmental awareness. Therefore, the production of forest products through multifunctional forest restoration could be a meaningful opportunity for large-scale restoration while promoting sustainability and vegetation recovery. We conducted a comprehensive literature review to explore how forest restoration in Brazil can meet the growing global demand for forest products, thereby promoting the widespread adoption of restoration practices. The number of forest restoration publications addressing forest product supply has increased, but remains limited. Notably, only studies on payments for environmental services have increased significantly over the years, while studies on non-timber forest products and timber have not increased significantly. Similar patterns and trends were found in earlier studies. Many studies do not provide insights into the socioeconomic outcomes of multifunctional forest restoration, which is consistent with other research findings. The studies cited 108 native species of commercial value. According to the literature, these species can provide multiple forest products, making their management economically attractive. Multifunctional restoration in Brazil has the potential for meeting global demand for forest products and supporting large-scale restoration. However, advancing scientific and technological knowledge in this area is needed to make this feasible.
Proposed Theorems on the Lifts of Kenmotsu Manifolds Admitting a Non-Symmetric Non-Metric Connection (NSNMC) in the Tangent Bundle
Authors: Kumar Rajesh , Colney Lalnunenga , Khan Mohammad Nazrul Islam
Published: November 2023

The main aim of the proposed paper is to investigate the lifts of Kenmotsu manifolds that admit NSNMC in the tangent bundle. We investigate several properties of the lifts of the curvature tensor, the conformal curvature tensor, and the conharmonic curvature tensor of Kenmotsu manifolds that admit NSNMC in the tangent bundle. We also study and discover that the lift of the Kenmotsu manifold that admit NSNMC is regular in the tangent bundle. Additionally, we find that the data provided by the lift of Ricci soliton on the lift of Ricci semi-symmetric Kenmotsu manifold that admits NSNMC in the tangent bundle are expanding.
Thermo-Mechanical and Mechano-Thermal Effects in Liquids Explained by Means of the Dual Model of Liquids
Authors: Peluso Fabio
Published: November 2023

We pursue to illustrate the capabilities of the Dual Model of Liquids (DML) showing that it may explain crossed effects notable in Non-Equilibrium Thermodynamics (NET). The aim of the paper is to demonstrate that the DML may correctly model the thermodiffusion, in particular getting formal expressions for positive and negative Soret coefficient, and another “unexpected” mechano-thermal effect recently discovered in liquids submitted to shear strain, for which the first-ever theoretical interpretation is provided. Both applications of the DML are supported by the comparison with experimental data. The phenomenology of liquids, either pure or mixtures, submitted to external force fields is characterized by coupled effects, for instance mechano-thermal and thermo-mechanical effects, depending on whether the application of a mechanical force field generates a coupled thermal effect in the liquid sample or vice-versa. Although these phenomena have been studied since their discoveries, dating back to the XIX century, no firm theoretical interpretation exists yet. Very recently the mesoscopic model of liquids DML has been proposed and its validity and applicability demonstrated in several cases. According to DML, liquids are arranged on a mesoscopic scale by means of aggregates of molecules, or liquid particles. These structures share the liquid world with a population of lattice particles, i.e., elastic waves that interact with the liquid particles by means of an inertial force, allowing the mutual exchange of energy and momentum between the two populations. The hit particle relaxes the acquired energy and momentum due to the interaction, giving them back to the system a step forward and a time-lapse later, alike in a tunnel effect.
Prophylactic Lymphadenectomy in Patients with Penile Cancer: Is Sooner Better?
Authors: Cai Tommaso , Capece Marco , Zorzi Maria Grazia , Palmieri Alessandro , Nesi Gabriella , Barbareschi Mattia , Bjerklund Johansen Truls E.
Published: November 2023

Background: Management of penile cancer patients has its grey zones. In particular, no strong evidence or recommendations exist regarding the timing of prophylactic lymphadenectomy. Here, we aim to review the impact that the timing of inguinal and pelvic prophylactic lymph node dissection has on patient outcome. Methods: All relevant databases were searched following the preferred reporting items for systematic reviews and meta-analysis guidelines. A narrative review of indications for lymph node dissection and pathological considerations precede a systematic review of the impact of prophylactic lymph node dissection timing on prognosis. The primary endpoint is disease-free and overall survival in patients undergoing early or late lymph node dissection after penile cancer diagnosis. Results: Four clinical trials, all focusing on the role of inguinal lymph node dissection, are included. Despite the lack of randomized and controlled trials, this review suggests that lymph node dissection should be performed as soon as possible after diagnosis, with 3 months as a realistic cut-off. Conclusions: Survival of penile cancer patients is strictly related to the timing of prophylactic pelvic lymph node dissection. All patients at high risk of nodal metastasis should be offered lymph node dissection within three months of diagnosis, until new predicting tools are validated.
Characterization of Two Aggressive PepMV Isolates Useful in Breeding Programs
Authors: Alcaide Cristina , Méndez-López Eduardo , Úbeda Jesús R. , Gómez Pedro , Aranda Miguel A.
Published: November 2023

Pepino mosaic virus (PepMV) causes significant economic losses in tomato crops worldwide. Since its first detection infecting tomato in 1999, aggressive PepMV variants have emerged. This study aimed to characterize two aggressive PepMV isolates, PepMV-H30 and PepMV-KLP2. Both isolates were identified in South-Eastern Spain infecting tomato plants, which showed severe symptoms, including bright yellow mosaics. Full-length infectious clones were generated, and phylogenetic relationships were inferred using their nucleotide sequences and another 35 full-length sequences from isolates representing the five known PepMV strains. Our analysis revealed that PepMV-H30 and PepMV-KLP2 belong to the EU and CH2 strains, respectively. Amino acid sequence comparisons between these and mild isolates identified 8 and 15 amino acid substitutions for PepMV-H30 and PepMV-KLP2, respectively, potentially involved in severe symptom induction. None of the substitutions identified in PepMV-H30 have previously been described as symptom determinants. The E236K substitution, originally present in the PepMV-H30 CP, was introduced into a mild PepMV-EU isolate, resulting in a virus that causes symptoms similar to those induced by the parental PepMV-H30 in Nicotiana benthamiana plants. In silico analyses revealed that this residue is located at the C-terminus of the CP and is solvent-accessible, suggesting its potential involvement in CP–host protein interactions. We also examined the subcellular localization of PepGFPm2E236K in comparison to that of PepGFPm2, focusing on chloroplast affection, but no differences were observed in the GFP subcellular distribution between the two viruses in epidermal cells of N. benthamiana plants. Due to the easily visible symptoms that PepMV-H30 and PepMV-KLP2 induce, these isolates represent valuable tools in programs designed to breed resistance to PepMV in tomato.
In Vivo and In Vitro Characterization of the Recently Emergent PRRSV 1-4-4 L1C Variant (L1C.5) in Comparison with Other PRRSV-2 Lineage 1 Isolates
Authors: Rawal Gaurav , Almeida Marcelo N. , Gauger Phillip C. , Zimmerman Jeffrey J. , Ye Fangshu , Rademacher Christopher J. , Armenta Leyva Betsy , Munguia-Ramirez Berenice , Tarasiuk Grzegorz , Schumacher Loni L. , Aljets Ethan K. , Thomas Joseph T. , Zhu Jin-Hui , Trexel Jolie B. , Zhang Jianqiang
Published: November 2023

The recently emerged PRRSV 1-4-4 L1C variant (L1C.5) was in vivo and in vitro characterized in this study in comparison with three other contemporary 1-4-4 isolates (L1C.1, L1A, and L1H) and one 1-7-4 L1A isolate. Seventy-two 3-week-old PRRSV-naive pigs were divided into six groups with twelve pigs/group. Forty-eight pigs (eight/group) were for inoculation, and 24 pigs (four/group) served as contact pigs. Pigs in pen A of each room were inoculated with the corresponding virus or negative media. At two days post inoculation (DPI), contact pigs were added to pen B adjacent to pen A in each room. Pigs were necropsied at 10 and 28 DPI. Compared to other virus-inoculated groups, the L1C.5-inoculated pigs exhibited more severe anorexia and lethargy, higher mortality, a higher fraction of pigs with fever (>40 °C), higher average temperature at several DPIs, and higher viremia levels at 2 DPI. A higher percentage of the contact pigs in the L1C.5 group became viremic at two days post contact, implying the higher transmissibility of this virus strain. It was also found that some PRRSV isolates caused brain infection in inoculation pigs and/or contact pigs. The complete genome sequences and growth characteristics in ZMAC cells of five PRRSV-2 isolates were further compared. Collectively, this study confirms that the PRRSV 1-4-4 L1C variant (L1C.5) is highly virulent with potential higher transmissibility, but the genetic determinants of virulence remain to be elucidated.
Genotypic and Phenotypic Characterization of Replication-Competent HIV-2 Isolated from Controllers and Progressors
Authors: Lungu Cynthia , Overmars Ronald J. , Grundeken Esmée , Boers Patrick H. M. , van der Ende Marchina E. , Mesplède Thibault , Gruters Rob A.
Published: November 2023

Although some individuals with HIV-2 develop severe immunodeficiency and AIDS-related complications, most may never progress to AIDS. Replication-competent HIV-2 isolated from asymptomatic long-term non-progressors (controllers) have lower replication rates than viruses from individuals who progress to AIDS (progressors). To investigate potential retroviral factors that correlate with disease progression in HIV-2, we sequenced the near full-length genomes of replication-competent viruses previously outgrown from controllers and progressors and used phylogeny to seek genotypic correlates of disease progression. We validated the integrity of all open reading frames and used cell-based assays to study the retroviral transcriptional activity of the long terminal repeats (LTRs) and Tat proteins of HIV-2 from controllers and progressors. Overall, we did not identify genotypic defects that may contribute to HIV-2 non-progression. Tat-induced, LTR-mediated transcription was comparable between viruses from controllers and progressors. Our results were obtained from a small number of participants and should be interpreted accordingly. Overall, they suggest that progression may be determined before or during integration of HIV-2.
Multi-Indicator Early-Warning Model for Mine Water Inrush at the Yushen Mining Area, Shaanxi Province, China
Authors: Liang Jinxi , Sui Wanghua , Chen Ge , Ren Hujun , Li Xibin
Published: November 2023

Previously conducted studies have established that the early warning of water inrush is crucial for the prevention and control of mining water catastrophes in the panel. In order to ensure the safety of coal mining, in this paper, monitoring indicators were determined using the sensitivity analysis method, and then a multi-indicator early-warning model for water inrush was established mainly based on the geological data of the Yanghuopan coal mine. The monitoring stage of the early-warning model should be determined according to the distance between the monitoring borehole and the mining position. Then, the development of a water-conducting fracture zone and the fluctuation and stochastic oscillator of monitoring indicators are comprehensively analyzed to determine the early-warning level. A multi-indicator early-warning model was applied to panel 30302 of the Yanghuopan coal mine and panel 1304 of the Zhaoxian coal mine in the Yushen mining areas. The abnormal warning of the water disaster in panel 1304 was sent 3 days before the disaster, which shows the effectiveness of the model. It can provide a reference for the development of an early-warning model for mine water inrush in Yushen mining areas.
Temporal and Spatial Propagation Characteristics of the Meteorological, Agricultural and Hydrological Drought System in Different Climatic Conditions within the Framework of the Watershed Water Cycle
Authors: Li Yunyun , Huang Yi , Li Yanchun , Zhang Hongxue , Deng Qian , Fan Jingjing , Wang Xuemei
Published: November 2023

Investigating systematic meteorological–agricultural–hydrological drought propagation within an integrated watershed framework is crucial yet challenging for advancing robust early warning systems and targeted resilience strategies. To address this gap, this study employs the standardized precipitation evapotranspiration index (SPEI), standardized soil moisture index (SSMI), and nonlinear joint hydrological drought index (NJHDI) to characterize meteorological, agricultural, and hydrological drought, respectively. Utilizing the strongest correlation method, variations in the propagation time along moisture movement pathways within the system are quantified using the Soil and Water Assessment Tool (SWAT) model. The Yellow River basin (YRB) is selected as the case study area. Key results reveal distinct seasonal patterns in meteorological–agricultural propagation across the basin, with escalated spring and summer timescales. However, weaker correlations and limited seasonality emerge for agricultural–hydrological linkages due to sustaining baseflow buffers. Specifically, the arid and semiarid region exhibited shorter propagation time with 1–5 months, while the semiarid and semihumid region displayed longer timescales with 7–12 months. These findings provide valuable scientific references for enhancing real-time early warning systems tailored to coupled watershed systems. The integrated methodology underscores the importance of unraveling fine-scale spatiotemporal propagation variability for localized drought resilience.