bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on an SICM Scanning Image Resolution Enhancement Algorithm
Authors: Quan Zhenhua , Xu Shilin , Liao Xiaobo , Wu Bin , Luo Liang
Published: May 2024

Scanning ion conductance microscopy (SICM) enables the non-invasive three-dimensional imaging of live cells and other structures in physiological environments. However, when imaging complex samples, SICM faces challenges such as having a low temporal resolution during slow scanning and a reduced signal-to-noise ratio during fast scanning, making it difficult to simultaneously improve both temporal and spatial resolution. To address these issues, this paper proposes an algorithm for enhancing image resolution under high-speed scanning. Firstly, scanning images are preprocessed using a median filtering algorithm to remove the salt-and-pepper noise generated during high-speed scanning. Next, the Canny edge detection algorithm is employed to extract the edges of the image targets. To avoid blurring the edges, the new edge-directed interpolation (NEDI) algorithm is then used to fill the edges, while non-edge areas are filled using bilinear interpolation, thereby enhancing the image resolution. Finally, the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) are used to analyze the imaging of articular chondrocytes. The results show that under a scanning speed of 480 nm/ms, the proposed algorithm improves the temporal resolution of imaging by 60% compared to traditional 2× resolution imaging, increases the peak signal-to-noise ratio of the scanning images by 7 dB, and achieves a structural similarity of 0.97. Therefore, the proposed algorithm effectively removes noise during high-speed scanning and improves the SICM scanning imaging resolution, thereby avoiding the reduction in temporal resolution when scanning larger resolution samples and effectively enhancing the performance of SICM scanning imaging.
Advancements in Cerebrospinal Fluid Biosensors: Bridging the Gap from Early Diagnosis to the Detection of Rare Diseases
Authors: Hatami-Fard Ghazal , Anastasova-Ivanova Salzitsa
Published: May 2024

Cerebrospinal fluid (CSF) is a body fluid that can be used for the diagnosis of various diseases. However, CSF collection requires an invasive and painful procedure called a lumbar puncture (LP). This procedure is applied to any patient with a known risk of central nervous system (CNS) damage or neurodegenerative disease, regardless of their age range. Hence, this can be a very painful procedure, especially in infants and elderly patients. On the other hand, the detection of disease biomarkers in CSF makes diagnoses as accurate as possible. This review aims to explore novel electrochemical biosensing platforms that have impacted biomedical science. Biosensors have emerged as techniques to accelerate the detection of known biomarkers in body fluids such as CSF. Biosensors can be designed and modified in various ways and shapes according to their ultimate applications to detect and quantify biomarkers of interest. This process can also significantly influence the detection and diagnosis of CSF. Hence, it is important to understand the role of this technology in the rapidly progressing field of biomedical science.
Assessment of Panorama Photogrammetry as a Tool for Long-Range Deformation Monitoring
Authors: Javadi Peyman , García-Asenjo Luis , Luján Raquel , Lerma José Luis
Published: May 2024

This study investigates panorama photogrammetry (PPh) as a potential method to collect massive 3D information for long-range deformation monitoring. Particularly, this study focuses on areas with measuring restrictions, i.e., inaccessible objects and distances above 0.6 km. Under these particular conditions, geodetic techniques based on Electromagnetic Distance Meters (EDMs) or Total Stations (TSs) can provide coordinates with a precision better than 1 cm, but only for a limited number of discrete points. For mass capture, Terrestrial Laser Scanning (TLS) is normally the preferred solution, but long-range instruments are expensive, and drawbacks such as weak return signals and non-automatic target recognition appear. As an alternative, PPh is investigated in the well-controlled area of La Muela in Cortes de Pallas, where images are automatically captured from geodetic pillars using a GigaPan device, processed, and then rigorously compared to TLS point clouds. The results obtained after integrating both techniques into a high-accuracy geodetic reference frame show that PPh and TLS provide similar precision to within approximately 4 cm in the range of 0.6–1.0 km. Therefore, considering cost-effectiveness and ease of use, the proposed method can be considered a low-cost alternative to TLS for long-range deformation monitoring.
Effect of Skin Pigmentation and Finger Choice on Accuracy of Oxygen Saturation Measurement in an IoT-Based Pulse Oximeter
Authors: Haxha Shyqyri , Nwibor Chike , Ali Mian , Sakel Mohamed , Saunders Karen , Dyo Vladimir , Nabakooza Shakira
Published: May 2024

Pulse oximeters are widely used in hospitals and homes for measurement of blood oxygen saturation level (SpO2) and heart rate (HR). Concern has been raised regarding a possible bias in obtaining pulse oximeter measurements from different fingertips and the potential effect of skin pigmentation (white, brown, and dark). In this study, we obtained 600 SpO2 measurements from 20 volunteers using three UK NHS-approved commercial pulse oximeters alongside our custom-developed sensor, and used the Munsell colour system (5YR and 7.5YR cards) to classify the participants’ skin pigmentation into three distinct categories (white, brown, and dark). The statistical analysis using ANOVA post hoc tests (Bonferroni correction), a Bland–Altman plot, and a correlation test were then carried out to determine if there was clinical significance in measuring the SpO2 from different fingertips and to highlight if skin pigmentation affects the accuracy of SpO2 measurement. The results indicate that although the three commercial pulse oximeters had different means and standard deviations, these differences had no clinical significance.
Impact of Insertion Speed, Depth, and Robotic Assistance on Cochlear Implant Insertion Forces and Intracochlear Pressure: A Scoping Review
Authors: Hrnčiřík Filip , Nagy Leo , Grimes Hannah L. , Iftikhar Haissan , Muzaffar Jameel , Bance Manohar
Published: May 2024

Cochlear implants are crucial for addressing severe-to-profound hearing loss, with the success of the procedure requiring careful electrode placement. This scoping review synthesizes the findings from 125 studies examining the factors influencing insertion forces (IFs) and intracochlear pressure (IP), which are crucial for optimizing implantation techniques and enhancing patient outcomes. The review highlights the impact of variables, including insertion depth, speed, and the use of robotic assistance on IFs and IP. Results indicate that higher insertion speeds generally increase IFs and IP in artificial models, a pattern not consistently observed in cadaveric studies due to variations in methodology and sample size. The study also explores the observed minimal impact of robotic assistance on reducing IFs compared to manual methods. Importantly, this review underscores the need for a standardized approach in cochlear implant research to address inconsistencies and improve clinical practices aimed at preserving hearing during implantation.
Combining Dipole and Loop Coil Elements for 7 T Magnetic Resonance Studies of the Human Calf Muscle
Authors: Cap Veronika , Rocha dos Santos Vasco Rafael , Repnin Kostiantyn , Červený David , Laistler Elmar , Meyerspeer Martin , Frass-Kriegl Roberta
Published: May 2024

Combining proton and phosphorus magnetic resonance spectroscopy offers a unique opportunity to study the oxidative and glycolytic components of metabolism in working muscle. This paper presents a 7 T proton calf coil design that combines dipole and loop elements to achieve the high performance necessary for detecting metabolites with low abundance and restricted visibility, specifically lactate, while including the option of adding a phosphorus array. We investigated the transmit, receive, and parallel imaging performance of three transceiver dipoles with six pair-wise overlap-decoupled standard or twisted pair receive-only coils. With a higher SNR and more efficient transmission decoupling, standard loops outperformed twisted pair coils. The dipoles with standard loops provided a four-fold-higher image SNR than a multinuclear reference coil comprising two proton channels and 32% more than a commercially available 28-channel proton knee coil. The setup enabled up to three-fold acceleration in the right–left direction, with acceptable g-factors and no visible aliasing artefacts. Spectroscopic phantom measurements revealed a higher spectral SNR for lactate with the developed setup than with either reference coil and fewer restrictions in voxel placement due to improved transmit homogeneity. This paper presents a new use case for dipoles and highlights their advantages for the integration in multinuclear calf coils.
Evaluation of EEG Signals by Spectral Peak Methods and Statistical Correlation for Mental State Discrimination Induced by Arithmetic Tasks
Authors: Coman Daniela Andreea , Ionita Silviu , Lita Ioan
Published: May 2024

Bringing out brain activity through the interpretation of EEG signals is a challenging problem that involves combined methods of signal analysis. The issue of classifying mental states induced by arithmetic tasks can be solved through various classification methods, using diverse characteristic parameters of EEG signals in the time, frequency, and statistical domains. This paper explores the results of an experiment that aimed to highlight arithmetic mental tasks contained in the PhysioNet database, performed on a group of 36 subjects. The majority of publications on this topic deal with machine learning (ML)-based classification methods with supervised learning support vector machine (SVM) algorithms, K-Nearest Neighbor (KNN), Linear Discriminant Analysis (LDA), and Decision Trees (DTs). Also, there are frequent approaches based on the analysis of EEG data as time series and their classification with Recurrent Neural Networks (RNNs), as well as with improved algorithms such as Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BLSTM), and Gated Recurrent Units (GRUs). In the present work, we evaluate the classification method based on the comparison of domain limits for two specific characteristics of EEG signals: the statistical correlation of pairs of signals and the size of the spectral peak detected in theta, alpha, and beta bands. This study provides some interpretations regarding the electrical activity of the brain, consolidating and complementing the results of similar research. The classification method used is simple and easy to apply and interpret. The analysis of EEG data showed that the theta and beta frequency bands were the only discriminators between the relaxation and arithmetic calculation states. Notably, the F7 signal, which used the spectral peak criterion, achieved the best classification accuracy (100%) in both theta and beta bands for the subjects with the best results in performing calculations. Also, our study found the Fz signal to be a good sensor in the theta band for mental task discrimination for all subjects in the group with 90% accuracy.
Quantifying Changes in Dexterity as a Result of Piano Training in People with Parkinson’s Disease
Authors: Tamir-Ostrover Hila , Hassin-Baer Sharon , Fay-Karmon Tsvia , Friedman Jason
Published: May 2024

People with Parkinson’s disease often show deficits in dexterity, which, in turn, can lead to limitations in performing activities of daily life. Previous studies have suggested that training in playing the piano may improve or prevent a decline in dexterity in this population. In this pilot study, we tested three participants on a six-week, custom, piano-based training protocol, and quantified dexterity before and after the intervention using a sensor-enabled version of the nine-hole peg test, the box and block test, a test of finger synergies using unidimensional force sensors, and the Quantitative Digitography test using a digital piano, as well as selected relevant items from the motor parts of the MDS-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) and the Parkinson’s Disease Questionnaire (PDQ-39) quality of life questionnaire. The participants showed improved dexterity following the training program in several of the measures used. This pilot study proposes measures that can track changes in dexterity as a result of practice in people with Parkinson’s disease and describes a potential protocol that needs to be tested in a larger cohort.
Drug Delivery Nano-Platforms for Advanced Cancer Therapy
Authors: Naumenko Ekaterina , Guryanov Ivan , Gomzikova Marina
Published: May 2024

The incidence of cancer is growing every year and covers all age groups, including the working population, which makes cancer socially significant. Existing methods of treatment, despite the effectiveness of individual compounds in relation to cancer cells, are not perfect due to a number of side effects associated with high doses that physicians are forced to administer when using treatment protocols. A particularly difficult issue is the creation of effective functional containers that would have the properties of targeting certain types of cells. The solution of this problem is currently relevant, which is reflected in the growth of publications on this subject in recent years. The most promising is the use of nanotechnology in the development of bioengineered therapeutics and containers for chemotherapeutic agents. In this review, we tried to assess the trends that exist in this area of research, as well as show the wide using of some commercially available formulations based on the nano-sized vehicles.
Delineating Priority Areas for Preservation and Restoration across Production–Living–Ecological Spaces in Ganzi, China
Authors: Chen Shengbin , Deng Xingwei , Wu Lilei , Zhao Kunming , Huang Zengjing , Chen Qi , Zhang Xuan
Published: May 2024

Delineating conservation priority areas for both preservation and restoration is essential for developing adaptive ecosystem management strategies across production–living–ecological spaces (PLES). This study developed a coherent framework with four steps: (1) mapping spatial distributions of biodiversity and ecosystem services, (2) ranking the relative importance of ecosystems across spaces, (3) delineating priority areas for preservation and restoration according to the human footprint and priority ranks, and (4) contrasting with current conservation networks and overlapping with PLES. This framework was applied in Ganzi, China, to delineate the preservation priority areas (PPAs) of 8714.2 km2 and 11,308.1 km2, and restoration priority areas (RPAs) of 36,817.7 km2 and 63,578.4 km2 under the target to conserve 30% and 50% of territories, respectively. The priority areas, including PPAs and RPAs, achieve higher conservation capacity than the current Ecological Conservation Redline (ECR) in terms of biodiversity conservation or ecosystem service delivery. Roughly 67% of PPAs, 40% of RPAs, and a total of 75% of large patches with high priority are covered by ECR, indicating the necessity to adjust boundary and conduct restoration for ECR. As for PLES, the conservation priority areas encompass proportionally more ecological space (67–76%) than ECR (63.5%) or Ganzi (61.4%), implying the lower potential conflict between local residents’ production and conservation, and meanwhile, new opportunities and challenges in sustainable development in human-dominated spaces. The coherent framework to delineate PPAs and RPAs is flexible in terms of threshold in human impact or ecological degradation and can be improved by considering the complex relationships between indicators of biodiversity and ecosystem services. This study highlights the importance of incorporating ecosystem features, land uses, and human activities in developing different strategies according to different conservation purposes in the context of sustainable development.
Deformation Risk Assessment of the Lar Dam: Monitoring Its Stability Condition
Authors: Ghadimi Mehrnoosh , Kiani Mohammadali
Published: May 2024

Dam stability is one of the most essential geotechnical engineering challenges. Studying the structural behavior of dams during their useful life is an essential component of their safety. Terrestrial surveying network approaches are typically expensive and time-consuming. Over the last decade, the interferometric synthetic aperture radar (InSAR) method has been widely used to monitor millimeter displacements in dam crests. This research investigates the structural monitoring of the Lar Dam in Iran, using InSAR and the terrestrial surveying network technique to identify the possible failure risk of the dam. Sentinel-1A images taken from 5 February 2015 to 30 September 2019 and TerraSAR-X (09.05.2018 to 16.08.2018) images were analyzed to investigate the dam’s behavior. The InSAR results were compared with those of the terrestrial surveying network for the period of 1992 to 2019. The Sentinel-1 results implied that the dam on the left side moved over 8 mm/yr. However, the pillars to the left abutment indicated an uplift, which is consistent with the TerraSAR-X results. Also, the TerraSAR-X data indicated an 8 mm displacement over a three-month period. The terrestrial surveying showed that the largest uplift was 19.68 mm at the TB4 point on the left side and upstream of the body, while this amount was 10 mm in the interferometry analysis for the period of 2015–2020. The subsidence rate increased from the middle part toward the left abutment. The geological observations made during the ninth stage of the terrestrial surveying network indicate that there was horizontal and vertical movement over time, from 1992 to 2019. However, the results of the InSAR processing in the crown were similar to those of the terrestrial surveying network. Although different comparisons were used for the measurements, the difference in the displacement rates was reasonable, but all three methods showed the same trend in terms of uplift and displacement.
Driving Safety Area Classification for Automated Vehicles Based on Data Augmentation Using Generative Models
Authors: Lee Donghoun
Published: May 2024

The integration of automated vehicles (AVs) into existing road networks for mobility services presents unique challenges, particularly in discerning the driving safety areas associated with the automation mode of AVs. The assessment of AV’s capability to safely operate in a specific road section is contingent upon the occurrence of disengagement events within that section, which are evaluated against a predefined operational design domain (ODD). However, the process of collecting comprehensive data for all roadway areas is constrained by limited resources. Moreover, challenges are posed in accurately classifying whether a new roadway section can be safely operated by AVs when relying on restricted datasets. This research proposes a novel framework aimed at enhancing the discriminative capability of given classifiers in identifying safe driving areas for AVs, leveraging cutting-edge data augmentation algorithms using generative models, including generative adversarial networks (GANs) and diffusion-based models. The proposed framework is validated using a field test dataset containing disengagement events from expressways in South Korea. Performance evaluations are conducted across various metrics to demonstrate the effectiveness of the data augmentation models. The evaluation study concludes that the proposed framework significantly enhances the discriminative performance of the classifiers, contributing valuable insights into safer AV deployment in diverse road conditions.
Exploring the Impact of Digital Transformation on Manufacturing Environment, Social Responsibility, and Corporate Governance Performance: The Moderating Role of Top Management Teams
Authors: Yang Qin , Jin Shanyue
Published: May 2024

In the digital economy era, digital transformation is crucial for competitiveness in traditional industries, particularly in manufacturing. This study aimed to examine how digital transformation impacts the manufacturing environment, social responsibility, and corporate governance (ESG), with a focus on the role of senior executive teams. Using empirical analysis of Chinese A-share listed companies from 2010 to 2019, this study found that digital transformation promotes ESG performance in the manufacturing industry. The findings revealed that the educational level, CEO tenure, and professional background diversity of senior management teams moderate this relationship, enhancing ESG performance. This study enriches and expands the existing knowledge system on this topic by integrating theories related to the digital economy and resource-based theories. It provides methodological guidance for the manufacturing industry to improve its environmental, social, and governance performance and achieve rapid development. Additionally, it offers practical suggestions for the government, manufacturing enterprises, and senior executive teams on how to better play their performance in digital transformation and ESG governance. This will assist the manufacturing industry enhance its level of digital transformation and continuously improve its ESG management and governance.
Roots of Resilience: Uncovering the Secrets behind 25+ Years of Inclusive Education Sustainability
Authors: Kamran Mahwish , Siddiqui Sohni
Published: May 2024

Over the last quarter of a century, there has been a growing global interest in inclusive education, and the promotion of equality and acceptance for children with special educational needs. While some studies have explored sustainable practices for inclusion in international research, there is a notable lack of studies conducted in Pakistan that aim to identify best practices to not only promote inclusion, but also to sustain it over time. The current study uses a qualitative case study approach to explore one sustainable inclusive education setting in depth and identify the factors that contribute to its longevity. The thematic analysis revealed significant themes that reflect the practices that have enabled the institution to thrive for more than 25 years. These include the implementation of welcoming policies and supportive attitudes among all stakeholders, the provision of essential resources, the creation of adapted learning environments, the promotion of parental and peer support, the continuous professional development of staff, advocacy for acceptance and equality, and outstanding leadership in promoting inclusive support. The authors acknowledge the limitations of a single case study; however, this study represents the first attempt to provide guidance to institutions adopting inclusive education models in Pakistan.
Demand-Responsive Transport for Urban Mobility: Integrating Mobile Data Analytics to Enhance Public Transportation Systems
Authors: Melo Sandra , Gomes Rui , Abbasi Reza , Arantes Amílcar
Published: May 2024

Transport-on-demand services, such as demand-responsive transport (DRT), involve a flexible transportation service that offers convenient and personalised mobility choices for public transport users. Integrating DRT with mobile data and data analytics enhances understanding of travel patterns and allows the development of improved algorithms to support design-optimised services. This study introduces a replicable framework for DRT that employs an on-demand transport simulator and routing algorithm. This framework is supported by a mobile data set, enabling a more accurate service design grounded on actual demand data. Decision-makers can use this framework to understand traffic patterns better and test a DRT solution before implementing it in the actual world. A case study was conducted in Porto, Portugal, to demonstrate its practicality and proof of concept. Results show that the DRT solution required 135% fewer stops and travelled 81% fewer kilometres than the existing fixed-line service. Findings highlight the potential of this data-driven framework for urban public transportation systems to improve key performance metrics in required buses, energy consumption, travelled distance, and stop frequency, all while maintaining the number of served passengers. Under specific circumstances, embracing this approach can offer a more efficient, user-centric, and environmentally sustainable urban transportation service.
Beyond Urban-Centered Responses: Overcoming Challenges to Build Disaster Resilience and Long-Term Sustainability in Rural Areas
Authors: García Ivis
Published: May 2024

This study delves into the difficulties in rural areas of building resilience to disasters and ensuring long-term sustainability. While cities typically receive attention during disaster recovery efforts, previous research shows that rural regions encounter obstacles such as geographic limitations, transportation issues, financial constraints, and a lack of media attention. This study aims to better understand rural disaster resilience and recovery by examining the impact of Hurricane Maria on Puerto Rico through interviews with 18 professionals involved in the recovery process from a variety of sectors including governmental organizations, emergency managers, non-governmental organizations (NGOs), and community leaders from community-based organizations (CBOs). The key findings stress the importance of implementing initiatives in rural areas that bolster sustainability—addressing economic, social, and environmental aspects. This study highlights the importance of customizing disaster response and resilience strategies to meet the needs of rural communities as opposed to a one-size-fits-all approach. It also offers insights for policymakers and urban planners seeking to develop disaster response plans tailored to address the distinctive challenges faced by rural areas.
Assessing Waterway Carrying Capacity from a Multi-Benefit Synergistic Perspective
Authors: Chen Yanyi , Zhou Bozhong , Pan Xiaofeng , Zhang Hao , Qian Honglu , Cheng Wen , Yin Weiqing
Published: May 2024

To support decision-making on the sustainable development of inland waterways, this paper proposes a framework for evaluating their waterway carrying capacity (WCC) from the perspective of different stakeholders and introduces an improved assessment method for WCC that combines the fuzzy belief rule and Bayesian network. Compared with traditional assessment methods, the proposed one can integrate the synergy of waterway multi-benefits into the carrying capacity and improve the accuracy of WCC assessment with data uncertainty. The method was applied to an empirical case of the middle Yangtze River from Yichang to Hukou, in which the current development status and the optimal development size in the future were obtained. The results and conclusions can provide insights and support for decision-making toward the development and maintenance of inland waterways.
Review of City-Wide 30 km/h Speed Limit Benefits in Europe
Authors: Yannis George , Michelaraki Eva
Published: May 2024

To date, more and more European cities are systematically working to expand the proportion of their street network with a speed limit of 30 km/h. This paper endeavored to assess the effectiveness of city-wide 30 km/h speed limits in Europe. In an effort to condense research outputs, a quantitative approach along with qualitative assessments were implemented. This study described the changes in safety, environment, energy, traffic, livability, and health before and after the phased implementation of city-wide 30 km/h speed limits. The systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Results from 40 different cities across Europe, including Brussels, Paris, and Zurich, indicated that reductions in speed limits improved road safety by decreasing the likelihood of crash risk and the severity of crashes that do occur. On average, the implementation of 30 km/h speed limits in European cities demonstrated a 23%, 37%, and 38% reduction in road crashes, fatalities, and injuries, respectively. Lower speed limits also yielded environmental benefits, with emissions decreasing on average by 18%, noise pollution levels by 2.5 dB, and fuel consumption by 7%, indicating enhanced fuel efficiency and reduced environmental impact. Encouraging citizens to embrace walking, cycling and utilizing public transit services can further contribute to a safer and environmentally sustainable urban environment.
Citizens’ Perception of Blockchain-Based E-Voting Systems: Focusing on TAM
Authors: Mannonov Kamoliddin Murodjon ugli , Myeong Seunghwan
Published: May 2024

Digital transformation and new technologies have made people’s lives easier and led to great results in most areas of business and society. Implementing blockchain technology is one of the best tools for establishing sustainable smart cities and societies. In terms of sustainable governance sophisticated and secure voting systems are necessary to achieve high integrity and transparency and null election fraud, and, in environmental sustainability, e-voting systems eliminate the mass waste of paper and transportation gas emissions; namely, e-voting systems are eco-friendly with high democratic outcomes. Blockchain technology can revolutionize e-voting by increasing the security and transparency of the voting process. Integrating artificial intelligence (AI) and machine learning (ML) into blockchain-based e-voting systems further augments their effectiveness. AI algorithms can analyze voting patterns and detect irregularities, supporting the prevention of fraudulent activities and coercion. ML procedures can enhance voter authentication processes, improve accessibility for diverse demographics, and optimize the productivity of blockchain networks during peak voting periods. This study focuses on understanding citizen perceptions of blockchain-based e-voting in a smart city context using the Technology Acceptance Model (TAM). The study’s results indicate that perceived ease of use and perceived usefulness are important factors in determining citizens’ intentions to use blockchain-based e-voting. Furthermore, trust in the technology and perceived security were found to influence the usefulness of blockchain-based e-voting positively. This study provides important insights for policymakers and technologists seeking to promote the adoption of blockchain-based e-voting systems in smart cities. The findings of the research supported the research model with positive results. In conclusion, our research model encourages the adoption of a blockchain-based e-voting system to enhance the future voting environment.
Implementation of Renewable Energy from Solar Photovoltaic (PV) Facilities in Peru: A Promising Sustainable Future
Authors: Cacciuttolo Carlos , Guardia Ximena , Villicaña Eunice
Published: May 2024

In the last two decades, Peru has experienced a process of transformation in the sources of its energy matrix, increasing the participation of clean energy such as solar photovoltaic (PV), on-shore wind, biomass, and small hydro. However, hydropower and natural gas remain the main sources of electricity, whereas off-shore wind, biogas, waves, tidal, and geothermal sources are currently underdeveloped. This article presents the enormous potential of Peru for the generation of electrical energy from a solar source equivalent to 25 GW, as it has in one of the areas of the world with the highest solar radiation throughout the year. In addition, this article presents the main advantages, benefits, and considerations of the implementation of solar photovoltaic technology, with emphasis on (i) the potential of solar energy, showing the available potential and an installed capacity by the year 2024 equivalent to 398 MW, (ii) current solar energy sources, characterizing existing industrial solar photovoltaic (PV) energy plants, and (iii) future solar energy facilities projections, stating the portfolio of solar renewable energy plant projects to be implemented in the future considering an installed capacity of 7.2 GW by 2028. Additionally, lessons learned, challenges, and directions for the future development of solar energy in the country are presented. Finally, the article concludes that if Peru takes advantage of solar potential by considering a sustainable future perspective and implementing strategic land-use planning, the southern region will be transformed into a world-class territory for renewable energy development considering the hybridization of concentrated solar power (CSP) systems with solar photovoltaic (PV) systems and solar energy storage systems.
The Action of Environmental Factors on Carbon Dioxide Efflux per Growing Season and Non-Growing Season
Authors: Kochiieru Mykola , Veršulienė Agnė , Feiza Virginijus , Feizienė Dalia , Shatkovska Kateryna , Deveikytė Irena
Published: May 2024

The intensity of carbon dioxide can vary depending on land management practices, temperature of the soil, and soil moisture. The soil CO2 efflux per non-growing season was 61% lower than per growing season. The CO2 efflux, averaged across data, tended to decrease in the following orders: grassland > forest > no-tillage > reduced tillage > conventional tillage (per non-growing season and measurement period) and grassland > forest > no-tillage > conventional tillage > reduced tillage (per growing season). Soil temperature averaged; in the natural land uses, it was 18% lower than in the anthropogenic land uses. Soil temperature averaged; in the non-growing season, it was 55% lower than under the growing season. The temperature (up to 25 °C) increased the soil CO2 efflux per measurement period. By increasing the temperature in the soil, the soil efflux decreased in natural land use under growing season, but in anthropogenic land use, it increased per measurement period. The volumetric water content averaged; in the non-growing season, it was 3% lower than under the growing season. The volumetric water content had a positive effect on CO2 efflux, but when the water content was higher than 15% in anthropogenic land use, and 20% in natural land use per growing season, the relationships were negative.
Understanding the Dermoscopic Patterns of Basal Cell Carcinoma Using Line-Field Confocal Tomography
Authors: Barbarossa Lorenzo , D’Onghia Martina , Cartocci Alessandra , Suppa Mariano , Tognetti Linda , Cappilli Simone , Peris Ketty , Perez-Anker Javiera , Malvehy Josep , Baldino Gennaro , Militello Caterina , Perrot Jean Luc , Rubegni Pietro , Cinotti Elisa
Published: May 2024

Basal cell carcinoma (BCC) is the most frequent malignancy in the general population. To date, dermoscopy is considered a key tool for the diagnosis of BCC; nevertheless, line-field confocal optical coherence tomography (LC-OCT), a new non-invasive optical technique, has become increasingly important in clinical practice, allowing for in vivo imaging at cellular resolution. The present study aimed to investigate the possible correlation between the dermoscopic features of BCC and their LC-OCT counterparts. In total, 100 histopathologically confirmed BCC cases were collected at the Dermatologic Clinic of the University of Siena, Italy. Predefined dermoscopic and LC-OCT criteria were retrospectively evaluated, and their frequencies were calculated. The mean (SD) age of our cohort was 65.46 (13.36) years. Overall, BCC lesions were mainly located on the head (49%), and they were predominantly dermoscopically pigmented (59%). Interestingly, all dermoscopic features considered had a statistically significant agreement with the LC-OCT criteria (all p < 0.05). In conclusion, our results showed that dermoscopic patterns may be associated with LC-OCT findings, potentially increasing accuracy in BCC diagnosis. However, further studies are needed in this field.
Spider and Wasp Acylpolyamines: Venom Components and Versatile Pharmacological Leads, Probes, and Insecticidal Agents
Authors: Rádis-Baptista Gandhi , Konno Katsuhiro
Published: May 2024

Polyamines (PAs) are polycationic biogenic amines ubiquitously present in all life forms and are involved in molecular signaling and interaction, determining cell fate (e.g., cell proliferation, dif-ferentiation, and apoptosis). The intricate balance in the PAs’ levels in the tissues will determine whether beneficial or detrimental effects will affect homeostasis. It’s crucial to note that endoge-nous polyamines, like spermine and spermidine, play a pivotal role in our understanding of neu-rological disorders as they interact with membrane receptors and ion channels, modulating neuro-transmission. In spiders and wasps, monoamines (histamine, dopamine, serotonin, tryptamine) and polyamines (spermine, spermidine, acyl polyamines) comprise, with peptides and other sub-stances, the low molecular weight fraction of the venom. Acylpolyamines are venom components exclusively from spiders and a species of solitary wasp, which cause inhibition chiefly of iono-tropic glutamate receptors (AMPA, NMDA, and KA iGluRs) and nicotinic acetylcholine receptors (nAChRs). The first venom acylpolyamines ever discovered (argiopines, Joro and Nephila toxins, and philanthotoxins) have provided templates for the design and synthesis of numerous analogs. Thus far, analogs with high potency exert their effect at nanomolar concentrations, with high se-lectivity toward their ionotropic and ligand receptors. These potent and selective acylpolyamine analogs can serve biomedical purposes and pest control management. The structural modification of acylpolyamine with photolabile and fluorescent groups converted these venom toxins into use-ful molecular probes to discriminate iGluRs and nAchRs in cell populations. In various cases, the linear polyamines, like spermine and spermidine, constituting venom acyl polyamine backbones, have served as cargoes to deliver active molecules via a polyamine uptake system on diseased cells for targeted therapy. In this review, we examined examples of biogenic amines that play an essential role in neural homeostasis and cell signaling, contributing to human health and disease outcomes, which can be present in the venom of arachnids and hymenopterans. With an empha-sis on the spider and wasp venom acylpolyamines, we focused on the origin, structure, derivatiza-tion, and biomedical and biotechnological application of these pharmacologically attractive, chemically modular venom components.
Respiratory Syncytial Virus Vaccine Design Using Structure-Based Machine-Learning Models
Authors: McCarty Thomas C. , Vaisman Iosif I.
Published: May 2024

When designing live-attenuated respiratory syncytial virus (RSV) vaccine candidates, attenuating mutations can be developed through biologic selection or reverse-genetic manipulation and may include point mutations, codon and gene deletions, and genome rearrangements. Attenuation typically involves the reduction in virus replication, due to direct effects on viral structural and replicative machinery or viral factors that antagonize host defense or cause disease. However, attenuation must balance reduced replication and immunogenic antigen expression. In the present study, we explored a new approach in order to discover attenuating mutations. Specifically, we used protein structure modeling and computational methods to identify amino acid substitutions in the RSV nonstructural protein 1 (NS1) predicted to cause various levels of structural perturbation. Twelve different mutations predicted to alter the NS1 protein structure were introduced into infectious virus and analyzed in cell culture for effects on viral mRNA and protein expression, interferon and cytokine expression, and caspase activation. We found the use of structure-based machine learning to predict amino acid substitutions that reduce the thermodynamic stability of NS1 resulted in various levels of loss of NS1 function, exemplified by effects including reduced multi-cycle viral replication in cells competent for type I interferon, reduced expression of viral mRNAs and proteins, and increased interferon and apoptosis responses.
Discovery and Genomic Characterization of a Novel Hepadnavirus from Asymptomatic Anadromous Alewife (Alosa pseudoharengus)
Authors: Raines Clayton , Lovy Jan , Phelps Nicolas , Mor Sunil , Ng Terry Fei Fan , Iwanowicz Luke
Published: May 2024

The alewife (Alosa pseudoharengus) is an anadromous herring that inhabits waters of northeastern North America. This prey species is a critical forage for piscivorous birds, mammals, and fishes in estuarine and oceanic ecosystems. During a discovery project tailored to identify potentially emerging pathogens of this species, we obtained the full genome of a novel hepadnavirus (ApHBV) from clinically normal alewives collected from the Maurice River, Great Egg Harbor River, and Delaware River in New Jersey, USA during 2015–2018. This previously undescribed hepadnavirus contained a circular DNA genome of 3146 nucleotides. Phylogenetic analysis of the polymerase protein placed this virus in the clade of metahepadnaviruses (family: Hepadnaviridae; genus: Metahepadnavirus). There was no evidence of pathology in the internal organs of infected fish and virions were not observed in liver tissues by electron microscopy. We developed a Taqman-based quantitative (qPCR) assay and screened 182 individuals collected between 2015 and 2018 and detected additional qPCR positives (n = 6). An additional complete genome was obtained in 2018 and it has 99.4% genome nucleotide identity to the first virus. Single-nucleotide polymorphisms were observed between the two genomes, including 7/9 and 12/8 synonymous vs nonsynonymous mutations across the polymerase and surface proteins, respectively. While there was no evidence that this virus was associated with disease in this species, alewives are migratory interjurisdictional fishes of management concern. Identification of microbial agents using de novo sequencing and other advanced technologies is a critical aspect of understanding disease ecology for informed population management.
Declining Levels of Neutralizing Antibodies to SARS-CoV-2 Omicron Variants Are Enhanced by Hybrid Immunity and Original/Omicron Bivalent Vaccination
Authors: Walmsley Sharon , Nabipoor Majid , Qi Freda , Lovblom Leif Erik , Ravindran Rizani , Colwill Karen , Dayam Roya Monica , Tursun Tulunay R. , Silva Amanda , Gingras Anne-Claude ,   on behalf of the STOPCoV Team
Published: May 2024

We determined neutralizing antibody levels to the ancestral Wuhan SARS-CoV-2 strain and three Omicron variants, namely BA.5, XBB.1.5, and EG.5, in a heavily vaccinated cohort of 178 adults 15–19 months after the initial vaccine series and prospectively after 4 months. Although all participants had detectable neutralizing antibodies to Wuhan, the proportion with detectable neutralizing antibodies to the Omicron variants was decreased, and the levels were lower. Individuals with hybrid immunity at the baseline visit and those receiving the Original/Omicron bivalent vaccine between the two sampling times demonstrated increased neutralizing antibodies to all strains. Both a higher baseline neutralizing antibody titer to Omicron BA.5 and hybrid immunity were associated with protection against a breakthrough SARS-CoV-2 infection during a 4-month period of follow up during the Omicron BA.5 wave. Neither were associated with protection from a breakthrough infection at 10 months follow up. Receipt of an Original/Omicron BA.4/5 vaccine was associated with protection from a breakthrough infection at both 4 and 10 months follow up. This work demonstrates neutralizing antibody escape with the emerging Omicron variants and supports the use of additional vaccine doses with components that match circulating SARS-CoV-2 variants. A threshold value for neutralizing antibodies for protection against reinfection cannot be determined.
Effects of a Protocol Combining a Non-Irritating Shampoo and an Adelmidrol-Based Adsorbent Mousse on Seborrhoea and Other Signs and Symptoms Secondary to Canine Atopic Dermatitis: A Multicenter, Open-Label Uncontrolled Clinical Trial
Authors: Noli Chiara , Morelli Giada , della Valle Maria Federica , Schievano Carlo ,   Skinalia Clinical Research Group
Published: May 2024

The present study aimed at evaluating the effect of a gentle shampoo and a mousse containing Adelmidrol, tapioca starch and a non-prescription antimicrobial complex on seborrhoea and other clinical signs secondary to canine atopic dermatitis (cAD). Forty-six dogs with cAD-associated seborrhoea and/or pruritus > 4 cm on the pruritus visual analogue scale (P-VAS) and/or bacterial/Malassezia overgrowth were enrolled. The mousse was applied twice daily, and dogs were evaluated at days (D)0, 7, 14 and optionally 28, by means of a skin seborrheic index (SSI), P-VAS, cAD lesion index (CADLI), and a semiquantitative cytological score. The mean SSI value improved during the first two weeks (4.1 ± 0.37 to 1.9 ± 0.30; p < 0.0001). The mean P-VAS score (cm) decreased from 6.6 ± 0.19 at D0 to 3.8 ± 0.31 at D14 (p < 0.0001). The mean CADLI score dropped from 13.7 ± 1.24 to 8.5 ± 1.14 at D14 (p < 0.001). The cytological score for bacteria and Malassezia decreased from 3.2 ± 0.10 and 3.2 ± 0.11, respectively, to 1.2 ± 0.19 and 1.2 ± 0.24 (p < 0.0001). All the investigated signs further improved at D28. Altogether, these observations suggest that the tested protocol might be useful in managing cAD-associated signs.
Preparation of 2D/2D CoAl-LDH/BiO(OH)XI1−X Heterojunction Catalyst with Enhanced Visible–Light Photocatalytic Activity for Organic Pollutants Degradation in Water
Authors: Che Liying , Ji Huanhuan
Published: May 2024

Hydrotalcite/bismuth solid solution (2D/2D CoAl-LDH/BiO(OH)XI1−X) heterojunction photocatalysts were fabricated through a hydrothermal route. Because of their identical layered structure and interlayer hydroxides, CoAl-LDH(2D) and BiO(OH)XI1−X(2D) form a tightly bonded heterojunction, resulting in efficient light absorption, excitation, and carrier migration conversion. At the same time, the large specific surface area and abundant hydroxyl groups of the layered structure make the heterojunction catalyst exhibit excellent performance in the photocatalytic degradation of organic pollutants. Under visible light irradiation and in the presence of 1 g/L of the catalyst, 10 mg/L of methyl orange (MO) in water could be completely degraded within 20 min, and the degradation rate of tetracycline (TC) reached 99.23% within 5 min. CoAl-LDH/BiO(OH)XI1−X still maintained good photocatalytic degradation activity of tetracycline after five cycles, and the structure of the catalyst did not change. The reaction mechanism related to the degradation of TC by photocatalytic reactions was explored in detail, and the photoexcitation of the semiconductor heterojunction, as well as the subsequent free radical reaction process and the degradation pathway of TC were clarified. This work provides a promising strategy for the preparation of efficient photocatalytic materials and the development of water purification technology.