bluuebunny/crossref_metadata_2025 huggingface dataset:
The Connection Between Depression and Ischemic Heart Disease: Analyzing Demographic Characteristics, Risk Factors, Symptoms, and Treatment Approaches to Identify Their Relationship
Authors: Bondar Laura Ioana , Osser Brigitte , Osser Gyongyi , Mariș Mariana Adelina , Piroș Ligia Elisaveta , Almășan Robert , Toth Csongor , Miuta Caius Calin , Marconi Gabriel Roberto , Bouroș-Tataru Ana-Liana , Măduța Victor , Tăședan Dana , Popescu Mircea Ioachim
Published: October 2024

Background: This study investigates the association between depression and ischemic heart disease (IHD), conditions that often coexist and complicate patient management. Understanding the impact of demographic factors, risk factors, symptoms, and medical approaches in these patients is essential to develop effective clinical strategies. Objectives: The aim of this study is to investigate how demographic characteristics, risk factors, symptoms, and treatment methods differ between patients with depression alone and those with both depression and IHD. It seeks to identify how these factors influence patient outcomes, providing insights to improve management and treatment approaches for this complex patient group. Materials and Methods: This cross-sectional study included a sample of 332 patients diagnosed with depression, with a specific subgroup consisting of individuals who also had comorbid IHD. Statistical analyses were performed to compare the patients with depression, focusing on those with IHD. Data on demographic characteristics (e.g., gender, environment, social status), risk factors (e.g., hypertension, diabetes), symptom severity, and treatments (e.g., antidepressants, antipsychotics, anxiolytics, hypnotics) were analyzed. The study also evaluated the frequency of cardiac examinations and emergency hospitalizations. Results: Significant demographic differences were found between the two groups. Patients with both depression and IHD had higher rates of hypertension and diabetes mellitus and experienced more severe depressive symptoms, including reduced mood, energy, and activity levels. The treatment patterns were similar in terms of antidepressant use, but the IHD group had a higher use of antipsychotics, anxiolytics, and hypnotics. Additionally, these patients required more cardiac examinations and emergency hospitalizations. Conclusions: Comorbidity between depression and IHD presents complex clinical challenges, and it is crucial to implement an integrated management approach that addresses both mental and physical health. This study highlights the need for comprehensive therapeutic strategies to improve the quality of life and outcomes for patients with these coexisting conditions.
Predicting the Ecological Risks of Phytoestrogens in Coastal Waters Using In Silico and In Vitro Approaches
Authors: Guimarães Luciana Lopes , Lourenço Bárbara Faria , Pusceddu Fabio Hermes , Cortez Fernando Sanzi , Kiyotani Rafael Barreiros , dos Santos Gilmar Aparecido , Toma Walber , Roveri Vinicius
Published: October 2024

Emerging pollutants, like phytoestrogens, are gaining attention in the scientific community for their impact on aquatic organisms. Nevertheless, there is a paucity of studies examining their effects on tropical aquatic species. In this context, the objective of this study was to (i) conduct chronic ecotoxicological assays with the sea urchin Echinometra lucunter with two phytoestrogens, namely genistein and daidzein (both derived from soy plant), and compare the results to the synthetic estrogen ‘estradiol valerate’; (ii) predict the potential risks of these phytoestrogens through an ecological risk assessment; and (iii) create a prioritization list of the most hazardous phytoestrogens using environmental persistence, bioaccumulation, and toxicity (PBT criteria). The results of chronic exposure demonstrated the following order of toxicity: daidzein (IC50 = 2.60 mg/L); genistein (IC50 = 3.37 mg/L); and estradiol valerate (IC50 = 28.40 mg/L). The results classify genistein and daidzein as “toxic” and estradiol valerate as “harmful” to the sea urchin. The final ranking of the PBT approach in coastal waters was as follows: biochanin A (the highest priority), followed by formononetin, genistein, enterolactone, daidzein, estradiol valerate, coumestrol, and 8-prenylnaringenin. The dataset highlights the importance of environmental monitoring to track phytoestrogens in Latin American coastal areas, particularly in developing countries.
Exploring the Antifungal Effectiveness of a Topical Innovative Formulation Containing Voriconazole Combined with Pinus sylvestris L. Essential Oil for Onychomycosis
Authors: Al-Suwaytee Safaa Halool Mohammed , Ben Hadj Ayed Olfa , Chaâbane-Banaoues Raja , Kosksi Tahsine , Shleghm Maytham Razaq , Chekir-Ghedira Leila , Babba Hamouda , Sfar Souad , Lassoued Mohamed Ali
Published: October 2024

(1) Background: The present study aimed to assess the antifungal effectiveness of a topical innovative formulation containing the association of an antifungal agent, voriconazole (VCZ), and the essential oil of Pinus sylvestris L. (PSEO). (2) Methods: Pseudo-ternary phase diagram and D-optimal mixture design approaches were applied for the development and the optimization of the o/w nanoemulsion. The optimized formulation (NE) was subjected to physicochemical characterization and to physical stability studies. In vitro permeation studies were carried out using the Franz cell diffusion system. The antimycotic efficacy against Microsporum canis was carried out in vitro. (3) Results: Optimal nanoemulsion showed great physical stability and was characterized by a small droplet size (19.015 nm ± 0.110 nm), a PDI of 0.146 ± 0.011, a zeta potential of −16.067 mV ± 1.833 mV, a percentage of transmittance of 95.352% ± 0.175%, and a pH of 5.64 ± 0.03. Furthermore, it exhibited a significant enhancement in apparent permeability coefficient (p < 0.05) compared to the VCZ free drug. Finally, NE presented the greatest antifungal activity against Microsporum canis in comparison with VCZ and PSEO tested alone. (4) Conclusions: These promising results suggest that this topical innovative formulation could be a good candidate to treat onychomycosis. Further ex vivo and clinical investigations are needed to support these findings.
Analysis of Parent and F1 Progeny Verification in African Yam Bean (Sphenostylis stenocarpa Hochst, Ex. A. Rich. Harms) Using Cowpea SSR Markers
Authors: Adefiranye Abimbola O. , Ogunkanmi Liasu A. , Adeyemo Oyenike A. , Shonde Olatunde Temitope E. , Paliwal Rajneesh , Abberton Michael T. , Oyatomi Olaniyi A.
Published: October 2024

African yam bean (Sphenostylis stenocarpa Hochst, Ex. A. Rich. Harms) is an important grain legume in Sub-Saharan Africa because of its nutritional value and adaptability to various agroecological zones. To foster the varietal development of improved African yam bean (AYB) genotypes with economic traits, it is necessary to validate parental polymorphism for key markers in selecting progenies from crosses between desired parents. This study aims to analyze the genetic fidelity between parents and F1 progenies in African yam bean through putative cowpea simple sequence repeat (SSR) markers. Hence, a total of seventy-seven progenies were derived from four sets of biparental crossings using drought-susceptible (TSs-96, TSs-363, and TSs-274) and drought-tolerant (TSs-417, TSs-111, and TSs-78) AYB accessions. These were validated using 120 cowpea primers targeting SSRs under optimal PCR conditions, and the size of the PCR-amplified DNA fragments was checked using gel electrophoresis. Twenty primers exhibited polymorphism in the parental lines, while ten displayed higher levels of the same polymorphism. The average polymorphism level for the surveyed SSR markers was 0.36. Given these findings, our study demonstrates that cowpea SSR markers are a reliable method for the regular testing and clear identification of AYB crosses, indicating potential AYB improvements.
Canadian National Pancreas Conference 2023: A Review of Multidisciplinary Engagement in Pancreatic Cancer Care
Authors: Nickerson Jessica L. , Cyr Chloe , Arseneau Riley J. , Lee Stacey N. , Condon-Oldreive Stefanie , Zogopoulos George , Roberts Keith , Kim Christina A. , Ng Sylvia S. W. , Haider Masoom , Villalba Eva , Stephenson Leah , Tsang Erica , Johnston Brent , Gala-Lopez Boris , Cooper Valerie , Hannon Breffni , Gangloff Anne , Gill Sharlene , Servidio-Italiano Filomena , Ramjeesingh Ravi
Published: October 2024

Pancreatic cancer is a complex malignancy associated with poor prognosis and high symptom burden. Optimal patient care relies on the integration of various sectors in the healthcare field as well as innovation through research. The Canadian National Pancreas Conference (NPC) was co-organized and hosted by Craig’s Cause Pancreatic Cancer Society and The Royal College of Physicians and Surgeons in November 2023 in Montreal, Canada. The conference sought to bridge the gap between Canadian healthcare providers and researchers who share the common goal of improving the prognosis, quality of life, and survival for patients with pancreatic cancer. The accredited event featured discussion topics including diagnosis and screening, value-based and palliative care, pancreatic enzyme replacement therapy, cancer-reducing treatment, and an overview of the current management landscape. The present article reviews the NPC sessions and discusses the presented content with respect to the current literature.
Timely Treatment and No Change in Thyroid Cancer Mortality During COVID-19 Pandemic. Reply to Nocini et al. No Impact of COVID-19 Pandemic on Early Mortality for Thyroid Cancer in the US. Comment on “Lee et al. Impact of the COVID-19 Pandemic on Thyroid Cancer Surgery. Curr. Oncol. 2024, 31, 3579–3590”
Authors: Lee Max L. , Chen Michelle M.
Published: October 2024

We thank Nocini et al [...]
Are Optometrists Prepared to Be Involved in Post-Stroke Rehabilitation?
Authors: Stalin Amritha , Leat Susan J. , Labreche Tammy
Published: October 2024

Background/Objectives: Stroke survivors often experience various visual consequences that impact their daily life and may benefit from visual interventions. However, some of these usually go unaddressed as optometrists are rarely included in the post-stroke care pathway. Yet, optometrists are interested in contributing to the care of these patients. This survey evaluated the readiness of optometrists in diagnosing and managing visual disorders specific to stroke survivors. Methods: A questionnaire was developed by the researchers, pilot tested by 5 research optometrists and 15 community optometrists, and modified based on the feedback. Practicing optometrists were invited to complete the anonymous online survey through optometric organizations in Canada, the US, Hong Kong, India, and the UK. Results: Most respondents displayed strong knowledge, but 61.6% indicated that enhancing their knowledge would be helpful. The majority (87%) agreed that stroke is related to an increased incidence of falls. Participants’ knowledge regarding the natural history of post-stroke visual disorders was poorer. There were also inconsistencies regarding what optometrists considered ideal interventions and what they undertook in practice. More than 50% of respondents reported that the quality of published evidence on post-stroke visual consequences was low or nonexistent. Conclusions: Overall, survey respondents displayed sufficient knowledge. However, there are areas of uncertainty in their knowledge, which in many cases correspond to real gaps in the available evidence. There is a need to identify and remediate these gaps to enable optometrists to deliver quality optometric care as collaborative members of the post-stroke professional team, which would eventually improve the rehabilitation of stroke survivors.
A Latent Class Analysis of Nutrition Impact Symptoms in Cancer Survivors
Authors: Keaver Laura , McLaughlin Christopher
Published: October 2024

Those with a cancer diagnosis report experiencing a wide range of nutrition impact symptoms, the prevalence of which varies by study, group, and cancer type. We aimed to identify groups of cancer survivors with specific patterns of nutrition impact symptoms. Two hundred and twenty-nine individuals attending oncology day ward and outpatient clinics completed a series of questionnaires and physical measurements. A latent class analysis was performed to identify subgroups based on 13 nutrition impact symptoms taken from the Patient Generated Subjective Global Assessment short form. The identified classes were subsequently compared using analysis of variance and chi-square tests, by sociodemographic, clinical and nutritional variables, and by the Global Health Status (GHS) and five functioning scales determined using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30). Three latent subtypes were identified: (1) Fatigue (n = 58, 28%); (2) Low Symptom Burden (n = 146, 64%), and (3) High Symptom Burden (n = 25, 11%). Those in the High Symptom Burden group were more likely to be female, were currently receiving some form of treatment, were diagnosed ≥two years, and had consumed less food than usual in the last month compared to those in the Low Symptom Burden group. Those in the Fatigue group were less likely to have reported their food intake to be unchanged and more likely to be diagnosed ≥two years than those in the Low Symptom Burden group. The EORTC-QLQ-C30 functioning and GHS scores were all significantly different between the three nutrition impact symptoms classes (p < 0.001). This is the first study to examine heterogeneity of nutrition impact symptoms in Irish cancer survivors. The findings of this work will inform and allow for more individualised nutrition care. By tailoring interventions to these specific groups, we can enhance the precision of care, improve prognostic accuracy, and significantly elevate the quality of life of survivors. This work underscores the critical importance of symptom management in the continuum of cancer care, ensuring that every survivor receives comprehensive support tailored to their unique journey.
Pilot Testing and Validation of an Educational Game on Transportation Challenges for Mobility Device Users
Authors: Candiotti Jorge L. , Park Sangmi , Lee Chang Dae , Rafferty Evan J. , Cooper Rosemarie , Cooper Rory A.
Published: October 2024

Despite the increasing use of assistive mobility devices, practical education to navigate real-world ground transportation barriers is lacking. The educational board game, called HERL-Town, was developed to teach safe and effective navigation for mobility device users (MDUs) in the community. The study examined the initial validity, reliability, and overall quality of HERL-Town as an educational tool for overcoming transportation barriers in real-world environments. HERL-Town featured fifty scenarios focused on transportation barriers and strategies, which were assessed for content validity, while the game quality was evaluated using the Model for the Evaluation of Educational Games (MEEGA+) tool. Twenty-three experienced MDUs and four caregivers participated in the study. The results indicated a good quality score of 60.15 and forty-five scenarios met the content validity standards. The overall reliability of the scenarios was moderate (ICC = 0.729). Early psychometric findings suggest HERL-Town as a promising effective educational game for helping new MDUs and their travel companions navigate safe and effective ground transportation barriers, hence enhancing their confidence, independence, and participation in the community.
Evolution of Acquired Drug Resistance in BRAF-Mutant Melanoma
Authors: Ballesteros-Álvarez Josué , Blázquez-Medela Ana M.
Published: October 2024

Melanoma is a highly aggressive type of skin cancer. Metastatic melanoma tumors have historically featured a particularly poor prognosis and have often been considered incurable. Recent advances in targeted therapeutic interventions have radically changed the landscape in metastatic melanoma management, significantly increasing the overall survival of patients. Hyperactive BRAF is the most common mutational event found in metastatic melanoma and its inhibition has proven to be a successful approach in a number of patients. Unfortunately, initial tumor retreat is followed by relapse in most cases, highlighting the elusiveness of finding a widely effective treatment. Melanoma tumors often carry a particularly high number of mutations in what is known as a high level of inter- and intra-patient tumor heterogeneity, driving resistance to treatment. The various mutations that are present in these tumors, in addition to impacting the root cause of the malignancy and the potential for therapeutic interventions, have also been known to arise during tumor clonal evolution leading to the establishment of drug resistance, a major issue in melanoma management.
Automated Unmanned Aerial System for Camera-Based Semi-Automatic Triage Categorization in Mass Casualty Incidents
Authors: Mösch Lucas , Pokee Diana Queirós , Barz Isabelle , Müller Anna , Follmann Andreas , Moormann Dieter , Czaplik Michael , Pereira Carina Barbosa
Published: October 2024

Using drones to obtain vital signs during mass-casualty incidents can be extremely helpful for first responders. Thanks to technological advancements, vital parameters can now be remotely assessed rapidly and robustly. This motivates the development of an automated unmanned aerial system (UAS) for patient triage, combining methods for the automated detection of respiratory-related movements and automatic classification of body movements and body poses with an already published algorithm for drone-based heart rate estimation. A novel UAS-based triage algorithm using UAS-assessed vital parameters is proposed alongside a robust UAS-based respiratory rate assessment and pose classification algorithm. A pilot concept study involving 15 subjects and 30 vital sign measurements under outdoor conditions shows that with our approach, an overall triage classification accuracy of 89% and an F1 score of 0.94 can be achieved, demonstrating its basic feasibility.
Efficient Ensemble Adversarial Attack for a Deep Neural Network (DNN)-Based Unmanned Aerial Vehicle (UAV) Vision System
Authors: Zhang Zhun , Liu Qihe , Zhou Shijie , Deng Wenqi , Wu Zhewei , Qiu Shilin
Published: October 2024

In recent years, unmanned aerial vehicles (UAVs) vision systems based on deep neural networks (DNNs) have made remarkable advancements, demonstrating impressive performance. However, due to the inherent characteristics of DNNs, these systems have become increasingly vulnerable to adversarial attacks. Traditional black-box attack methods typically require a large number of queries to generate adversarial samples successfully. In this paper, we propose a novel adversarial attack technique designed to achieve efficient black-box attacks with a minimal number of queries. We define a perturbation generator that first decomposes the image into four frequency bands using wavelet decomposition and then searches for adversarial perturbations across these bands by minimizing a weighted loss function on a set of fixed surrogate models. For the target victim model, the perturbation images generated by the perturbation generator are used to query and update the weights in the loss function, as well as the weights for different frequency bands. Experimental results show that, compared to state-of-the-art methods on various image classifiers trained on ImageNet (such as VGG-19, DenseNet-121, and ResNext-50), our method achieves a success rate over 98% for targeted attacks and nearly a 100% success rate for non-targeted attacks with only 1–2 queries per image.
Measurement Equivalence and Feasibility of the Electronic and Paper Versions of the POSAS, EQ-5D, and DLQI: A Randomized Crossover Trial
Authors: Meirte Jill , Hellemans Nick , Van Daele Ulrike , Maertens Koen , Denteneer Lenie , Anthonissen Mieke , Moortgat Peter
Published: October 2024

Patient-reported outcome measures (PROMs) are crucial within person-centered care. The use of electronic PROMs (ePROMs) is increasing and multiple advantages have been described. The Patient and Observer Scar Assessment Scale (POSAS) is a validated paper questionnaire to assess patient-reported scar quality in the burn and scar population. In burn and scar rehabilitation, quality of life questionnaires such as the Euroqol 5 Dimensions 5 level (EQ-5D-5L) and the Dermatology Life Quality Index (DLQI) allow us to measure physical and psychosocial impact. The goal of this research was to compare the equivalence of the electronic versions of the POSAS, the EQ-5D-5L, and the DLQI with their original paper counterparts. To ensure the psychometric properties of the electronic versions, we assessed the equivalence of scores, the differences in completion time, and patients’ preferred mode and ease of use. We used a randomized crossover design using a within-subject comparison of the formats of the questionnaires. Participants aged over 18 with a scar were recruited from an outpatient after-care and research center for burns and scars in Antwerp, Belgium. The equivalence of the electronic questionnaires POSAS, EQ-5D-5L, and DLQI is assumed based on the findings of this study. Completion times were faster for all the electronic versions but only statistically different (p = 0.002) for the electronic version of the EQ-5D-5L. The number of missing answers could be reduced to 0. The electronic assessment was preferred in >75% of the cases and subjects found it easy to use, and a tool that could improve the quality of care. Our findings support the electronic delivery of POSAS, EQ-5D, and DLQI, within the burn and scar population.
A Review of Photovoltaic Waste Management from a Sustainable Perspective
Authors: Babaei Abolfazl , Nasr Esfahani Ali
Published: October 2024

The rapid deployment of solar photovoltaic (PV) systems underscores their potential as vital clean energy solutions with reduced carbon emissions and increasingly competitive installation costs. This review examines PV waste management from a sustainable perspective, focusing on environmental impacts and technological advancements. Various solar cell technologies, including crystalline silicon, thin-film, and emerging third-generation cells like perovskite and organic photovoltaics, are analyzed for their life cycle and environmental effects. Effective disposal and recycling methods, such as physical separation and thermal and chemical treatments, are critically evaluated to mitigate ecological harm. The study highlights the need for improved recycling processes and sustainable practices to enhance the environmental benefits of PV systems. Future solutions call for better recycling techniques, increased efficiency in renewable materials, and comprehensive life cycle assessments to support the global transition to sustainable energy. This review aims to foster the integration of sustainable practices in the renewable energy sector, ensuring that PV systems contribute to a cleaner and more sustainable future.
An Optimal SVD Filtering Method for Measurement Accuracy Improvement against Harmonic Disturbance in Grid-Connected Inverters
Authors: Song Hua , Wang Yanbo , Sun Xiang-E
Published: October 2024

The increasing penetration of power electronics, such as grid-connected inverters and active loads may cause power quality issues, which reduce the sensitivity of monitoring and control systems due to measurement noises. This article presents an optimal singular value decomposition (SVD) filtering method for grid-connected inverters to improve sampling accuracy against measurement noises. First, the principle of this proposed method is based on the Hankel matrix theory, and then the implementation process is explained, during which the relationship between the Hankel matrix dimension and noise reduction is discussed. Furthermore, the optimal singular value is analyzed and proposed to determine the reconstruction order. Then, the comparative analysis of the proposed optimal SVD filtering method and difference spectrum method is given to explain the optimal reconstruction order. Finally, simulation verifications are implemented to validate the effectiveness of the proposed filtering method, considering the Hankel matrix dimension, reconstruction order, and different signal–noise ratio (SNR). The verification results show that the proposed optimal SVD filtering method can accurately identify the sampling current of grid-connected inverters, even if severe harmonic noises and oscillation happen. The proposed method can reduce the effects of harmonic disturbance on measurement accuracy and control performance of grid-connected inverters, which can improve the robustness of grid-connected inverters.
D3AT-LSTM: An Efficient Model for Spatiotemporal Temperature Prediction Based on Attention Mechanisms
Authors: Tian Ting , Wu Huijing , Liu Xianhua , Hu Qiao
Published: October 2024

Accurate temperature prediction is essential for economic production and human society’s daily life. However, most current methods only focus on time-series temperature modeling and prediction, ignoring the complex interplay of meteorological variables in the spatial domain. In this paper, a novel temperature prediction model (D3AT-LSTM) is proposed by combining the three-dimensional convolutional neural network (3DCNN) and the attention-based gated cyclic network. Firstly, the historical meteorological series of eight surrounding pixels are combined to construct a multi-dimensional feature tensor that integrates variables from the temporal domain as the input data. Convolutional units are used to model and analyze the spatiotemporal patterns of the local sequence in CNN modules by combining them with parallel attention mechanisms. The fully connected layer finally makes the final temperature prediction. This method is subsequently compared with both classical and state-of-art prediction models such as ARIMA (AR), long short-term memory network (LSTM), and Transformer using three indices: the root mean square error (RMSE), the mean absolute error (MAE), and the coefficient of determination (R2). The results indicate that the D3AT-LSTM model can achieve good prediction accuracy compared to AR, LSTMs, and Transformer.
Deep Learning-Based Stopped Vehicle Detection Method Utilizing In-Vehicle Dashcams
Authors: Park Jinuk , Lee Jaeyong , Park Yongju , Lim Yongseok
Published: October 2024

In complex urban road conditions, stationary or illegally parked vehicles present a considerable risk to the overall traffic system. In safety-critical applications like autonomous driving, the detection of stopped vehicles is of utmost importance. Previous methods for detecting stopped vehicles have been designed for stationary viewpoints, such as security cameras, which consistently monitor fixed locations. However, these methods for detecting stopped vehicles based on stationary views cannot address blind spots and are not applicable from driving vehicles. To address these limitations, we propose a novel deep learning-based framework for detecting stopped vehicles in dynamic environments, particularly those recorded by dashcams. The proposed framework integrates a deep learning-based object detector and tracker, along with movement estimation using the dense optical flow method. We also introduced additional centerline detection and inter-vehicle distance measurement. The experimental results demonstrate that the proposed framework can effectively identify stopped vehicles under real-world road conditions.
Educational Constructivism
Authors: Taber Keith S.
Published: October 2024

A perspective on learning and teaching that considers knowledge must be constructed by the individual learner using available interpretive resources, and where learners are likely to misconstrue instruction without well-designed teaching that is informed by knowledge of learners’ ideas.
Synthetic Fuels for Decarbonising UK Rural Transport
Authors: Dabo Al-Amin Abba , Gough Andrew , Alparslan F. Frank
Published: October 2024

Decarbonising transport is a crucial element of the UK’s strategy to achieve net-zero carbon emissions by 2050, as the transport sector is currently the largest contributor to the UK’s greenhouse gas emissions. Rural communities face distinct challenges in this effort due to their reliance on internal combustion engines (ICEs) across vehicles and machinery essential for daily life, including farming equipment and private transport. While the upcoming ban on new petrol and diesel vehicles paves the way for the adoption of Electric Vehicles (EVs), this solution may not fully address the unique needs of rural areas where infrastructure limitations and specific mobility requirements pose significant barriers. In this context, synthetic fuels, produced using renewable energy sources, offer a potential alternative. These fuels can be used directly in existing internal combustion engines without requiring major modifications and have the added benefit of reducing overall greenhouse gas emissions by capturing CO2 during production. This entry explores the potential advantages of adopting synthetic fuels, particularly in rural areas, and examines how community-based buying cooperatives could support their wider use through bulk purchasing, cost reduction, and community empowerment.
Efficient Runtime Firmware Update Mechanism for LoRaWAN Class A Devices
Authors: Neves Bernardino Pinto , Valente António , Santos Victor D. N.
Published: October 2024

This paper presents an efficient and secure method for updating firmware in IoT devices using LoRaWAN network resources and communication protocols. The proposed method involves dividing the firmware into fragments, storing them in the application server’s database, and transmitting them to remote IoT devices via downlink messages, without necessitating any changes to the device’s class. This approach can be replicated across any IoT LoRaWAN device, offering a robust and scalable solution for large-scale firmware updates while ensuring data security and integrity. The proposed method significantly reduces the downtime of IoT devices and enhances the energy efficiency of the update process. The method was validated by updating a block in the program memory, associated to a specific functionality of the IoT end device. The associated Intel Hex file was segmented into 17 LoRaWAN downlink frames with an average size of 46 bytes. Upon receiving the complete firmware update, the microcontroller employs self-programming techniques that restrict the update process to specific rows of the program memory, avoiding interruptions or reboots. The update process was successfully completed in 51.33 ms, resulting in a downtime of 16.88 ms. This method demonstrates improved energy efficiency compared to existing solutions while preserving the communication network’s capacity, making it an adequate solution for remote devices in LoRaWAN networks.
A Comprehensive Review on Various Phases of Wastewater Technologies: Trends and Future Perspectives
Authors: Fernandes José , Ramísio Paulo J. , Puga Hélder
Published: October 2024

Wastewater Treatment Plants (WWTPs) encompass a range of processes from preliminary to advanced stages. Conventional treatments are increasingly inadequate for handling emergent pollutants, particularly organic compounds with carcinogenic potential that pose risks to aquifers. Recent advancements prioritize integrating Advanced Oxidation Processes (AOPs) and adsorbents with conventional methods to effectively retain organic pollutants and enhance mineralization. There is a growing preference for non-chemical or minimally chemical approaches. Innovations such as combining ozone and other biological processes with photo-sono-assisted methods, alongside integrating AOPs with adsorbents, are promising. These approaches leverage catalyst-assisted reactions to optimize oxidation efficiency. This review aims to provide a holistic perspective on WWTP processes, spanning wastewater intake to the production of potable water, highlighting key technologies, operational challenges, and future trends. The focus is on advancing sustainable practices and enhancing treatment efficacy to safeguard water quality and address evolving environmental concerns effectively.
Landscape Dynamics, Succession, and Forecasts of Cunninghamia lanceolata in the Central Producing Regions of China
Authors: Liu Zejie , Zhong Yongde , Chen Zhao , Wei Juan , Li Dali , Zhang Shuangquan
Published: October 2024

Cunninghamia lanceolata (Lamb.) Hook accounts for 12% of the total forest area in southern China, second only to Masson pine forests, and is an important part of the forest landscape in this region, which has a significant impact on the overall forest structure in southern China. In this study, we used kernel density analysis, landscape index calculation, variance test, and Markov prediction to analyze and forecast the evolution trend of landscape pattern in the central area of C. lanceolata in ten years. The objective is to investigate the change trend of the spatial pattern of C. lanceolata landscape in the long time series and its possible impact on zonal vegetation, as well as the macro-succession trend of C. lanceolata under the current social and economic background, and to make a scientific and reasonable prediction of its future succession trend. The current and future forecast results show that the landscape fragmentation degree of C. lanceolata is intensified, the erosion of bamboo forest is continuously intensified, and the landscape quality is continuously low. These results provide a reference for the future development direction of C. lanceolata and emphasize the need for targeted C. lanceolata management strategies in the future development of C. lanceolata, emphasizing the strengthening of monitoring, controlling harvesting, and managing bamboo competition in order to balance wood production with landscape quality and ecosystem stability.
Fractal Analysis of GPT-2 Token Embedding Spaces: Stability and Evolution of Correlation Dimension
Authors: Lee Minhyeok
Published: October 2024

This paper explores the fractal properties of token embedding spaces in GPT-2 language models by analyzing the stability of the correlation dimension, a measure of geometric complexity. Token embeddings represent words or subwords as vectors in a high-dimensional space. We hypothesize that the correlation dimension D2 remains consistent across different vocabulary subsets, revealing fundamental structural characteristics of language representation in GPT-2. Our main objective is to quantify and analyze the stability of D2 in these embedding subspaces, addressing the challenges posed by their high dimensionality. We introduce a new theorem formalizing this stability, stating that for any two sufficiently large random subsets S1,S2⊂E, the difference in their correlation dimensions is less than a small constant ε. We validate this theorem using the Grassberger–Procaccia algorithm for estimating D2, coupled with bootstrap sampling for statistical consistency. Our experiments on GPT-2 models of varying sizes demonstrate remarkable stability in D2 across different subsets, with consistent mean values and small standard errors. We further investigate how the model size, embedding dimension, and network depth impact D2. Our findings reveal distinct patterns of D2 progression through the network layers, contributing to a deeper understanding of the geometric properties of language model representations and informing new approaches in natural language processing.
Laparoscopic Splenectomy for a Congenital Epidermoid Cyst in a 15-Year-Old Child—Case Report
Authors: Kofinova Denitza , Pahnev Yanko , Rangelov Edmond , Vasilevski Ivan , Bogdanova Olga , Ilieva Elena , Shivachev Hristo
Published: October 2024

Splenic epidermoid cysts are rare benign congenital tumors. However, if the cyst is not completely removed, it can reoccur. Laparoscopic splenectomy in children is being conducted more often, but it is a therapeutic challenge in cases of a giant cyst. We report a case of a 15-year-old girl who presented with nausea, anorexia and abdominal pain. The ultrasound showed a giant well-defined hypoechoic cyst with diffuse internal echoes. Computed tomography revealed a cystic mass (92/124/102 mm) without contrast enhancement. Anti-Echinococcus ELISA IgG was negative, and serum tumor markers CA 19-9 79.1 U/mL (N < 34) and CA-125 39.6 U/ML (N < 35) were elevated. Before the operation, the girl was vaccinated for Haemophilus influenzae, Pneumococci and Meningococci. Laparoscopic splenectomy was performed. The patient’s postoperative course was uneventful. Histopathology indicated a cyst walled by multilayered squamous epithelium positive for cytokeratin AE1/AE3. The diagnosis epidermoid cyst was confirmed.
UNESCO Global Geoparks vs. Generative AI: Challenges for Best Practices in Sustainability and Education
Authors: Martínez-Martín Jesús Enrique , Rosado-González Emmaline M. , Martínez-Martín Beatriz , Sá Artur A.
Published: October 2024

Artificial intelligence (AI) has become one of the most controversial tools of recent times. Offering an extremely simple operating system, users can generate texts, images, videos and even human voices. The possibility of using such a powerful tool creates new paths and challenges in the field of environmental education: How does it influence natural heritage protection? Is it considered positive within sustainability and quality education? The reality is very different, showing algorithms trained with information of dubious quality and, on many occasions, obtained without permission from authors and artists around the world. UNESCO Global Geoparks (UGGps) are international references in education at all levels, related to territorial development and geoscience education. This article discusses if generative AI is, nowadays, an effective and applicable educational tool for the strategies developed and promoted by UGGps. This designation exists for people’s opportunities. The use of these tools in their current state could make the UGGp figure change its values and fundamental pillars in the future.
Performance of Micropiled-Raft Foundations in Sand
Authors: Hanna Adel , Nabizadeh Farhad
Published: October 2024

Micropiles were first used to repair the damaged structures of “Scuola Angiulli” in Naples after World War II. They are known as small versions of regular piles, with a diameter of less than 30 cm, and are made of high-strength, steel casing and/or threaded bars, produce minimal noise and vibration during installation, and use lightweight machinery. They are capable to withstand axial loads and moderate lateral loads. They are used for underpinning existing foundations and to restore historical buildings and to support moderate structures. In the literature, several reports can be found dealing with micropiles, yet little has been reported on Micropiled-Raft Foundations (MPR). This technology did not receive the recognition it deserved until the 1970s when its technical and economic benefits were noted. A series of laboratory tests and numerical modeling were developed to examine the parameters governing the performance of MPR, including the relative density of the sand, the micropile spacing, and the rigidity of the raft. The numerical model, after being validated with the present experimental results, was used to generate data for a wide range of governing parameters. The theory developed by Poulos (2001) (PDR) to predict the capacity of pile-raft foundations was adopted for the design of MPR. The PDR method is widely used by geotechnical engineers because of its simplicity.
Trabecular Attenuation of L1 in Adult Patients with Multiple Myeloma: An Observational Study on Low-Dose CT Images
Authors: Mallio Carlo Augusto , Tomarchio Valeria , Pulcini Francesco , Verducci Edoardo , Bernetti Caterina , Tafuri Maria Antonietta , Greco Federico , Rigacci Luigi , Zobel Bruno Beomonte , Annibali Ombretta
Published: October 2024

Background: The aim of this study was to evaluate the impact of trabecular attenuation of the L1 vertebral body in low-dose CT in adult patients with multiple myeloma (MM), smoldering multiple myeloma (SMM), and monoclonal gammopathy of undetermined significance (MGUS). Materials and Methods: The study population consisted of 22 patients with MGUS and 51 consecutive patients with newly diagnosed MM (SMM, n = 21; symptomatic MM, n = 36). CT scans were conducted using a 128-slice CT scanner (Somatom go.Top, Siemens, Munich, Germany). Low-dose whole-body CT scans were performed at a single time point for each patient. Trabecular bone density values were obtained by defining regions of interest on non-contrast images at the level of L1 vertebra. A threshold of p = 0.05 was applied to determine statistical significance. Results: The median Hounsfield unit (HU) value in patients with MGUS, SMM, and MM was 148 HU (range 81–190), 130 HU (range 93–193), and 92 HU (range 26–190), respectively, with a statistically significant difference between the groups (p = 0.0015). Patients with HU values ≤ 92 had lower progression-free survival with statistically significant differences compared to the group with HU values > 92 (p < 0.0499). Conclusions: This is the earliest evidence of the importance of evaluating L1 attenuation values in low-dose CT images in patients with MGUS, SMM, and MM. Further prospective studies could contribute to reinforcing these results and exploring the clinical applicability and generalization of L1 attenuation values in low-dose whole-body CT scans in routine clinical practice.
Recurrent Flooding and Household Food Access in Central Java, Indonesia
Authors: Langlois Breanne K. , Ismanto Aris , Beaulac Leah , Berry Katherine , Koch Magaly , Griffin Timothy , Coughlan de Perez Erin , Naumova Elena N.
Published: October 2024

It is unknown how recurring flooding impacts household diet in Central Java. We aimed to assess how recurrent flooding influenced household food access over 22 years in Central Java by linking the Global Surface Water dataset (GSW) to the Indonesian Family Life Survey. We examined linear and nonlinear relationships and joint effects with indicators of adaptive capacity. We measured recurrent flooding as the fraction of district raster cells with episodic flooding from 1984–2015 using GSW. Food access outcomes were household food expenditure share (FES) and dietary diversity score (DDS). We fit generalized linear mixed models and random forest regression models. We detected joint effects with flooding and adaptive capacity. Wealth and access to credit were associated with improved FES and DDS. The effect of wealth on FES was stronger in households in more flood-affected districts, while access to credit was associated with reduced odds of DDS in more flood-affected districts. Flooding had more predictive importance for FES than for DDS. Access to credit, a factor that ordinarily improves food access, may not be effective in flood-prone areas. Wealthier households may be better able to adapt in terms of food access. Future research should incorporate land use data to understand how different locales are affected and further understand the complexity of these relationships.
Seasonal Variations in Multiple Sclerosis Relapses in Oman: A Single Tertiary Centre Experience
Authors: Al-Shibli Rashid , Al-Asmi Abdullah , Islam M. Mazharul , Al Sabahi Fatema , Al-Aamri Amira , Butt Mehwish , Al-Lawati Meetham , Al-Hashmi Lubna , Al-Yahmadi Jihad
Published: October 2024

(1) Background and Aims: The seasonal factors influencing multiple sclerosis (MS) relapses remain elusive. This study aims to investigate the seasonal variation of MS relapses in Oman and compare it globally. (2) Subject and Methods: This retrospective study was conducted on N = 183 Omani MS patients treated at Sultan Qaboos University Hospital, a tertiary hospital in Muscat, Oman, over sixteen-year period (2007–2022). Demographic and clinical data of all MS patients were juxtaposed with the monthly weather data during this period, using descriptive and inferential statistical techniques. (3) Results: Among the N = 183 MS patients studied, 508 relapses were recorded during the study period. The average number of relapses per patient was 2.8 (range: 1–15). There were significant seasonal variations in MS relapse rate, with the highest prevalence in the winter months of January and February. However, no correlation was found between MS relapses and other climatic parameters (humidity, temperature, and rainfall). (4) Conclusion: The seasonal patterns of MS relapses in Oman differ from other parts of the world, which the local clinicians should take into account while diagnosing and making management decisions. The potential impact of climate change on the anomalous changes in the seasonality of MS relapses warrants further investigation.
Relationship Between C-Peptide Levels, Clinical Features, and Serum Data in a Brazilian Type 1 Diabetes Population with Large Variations in Genomic Ancestry
Authors: Azulay Rossana Sousa , Rodrigues Vandilson , Lago Débora Cristina Ferreira , Almeida Ana Gregória Ferreira Pereira de , Abreu Joana D’Arc Matos França de , Matos Lincoln , Andrade Caio , Nascimento Gilvan Cortês , Magalhães Marcelo , Facundo Alexandre , Oliveira Neto Clariano Pires de , Sá Adriana Guimarães , Silva Dayse Aparecida , Gomes Marília Brito , Faria Manuel dos Santos
Published: October 2024

Type 1 diabetes (T1D) is a chronic disease characterized by the immune-mediated destruction of the pancreatic beta cells responsible for insulin production. The secreted insulin and C-peptide are equimolar. Due to its longer half-life, C-peptide has become a safer means of assessing the pancreatic reserve. C-peptide levels were evaluated in a population of patients with T1D, focusing on the relationship between this variable and other factors. In addition, the influence of C-peptide on metabolic control and microvascular complications was investigated. This cross-sectional study included 95 patients who had been diagnosed with T1D at least five years earlier. These patients were evaluated using a clinical demographic survey, anthropometric data, laboratory tests, and fundoscopy. This study showed that 29.5% of patients had residual insulin secretion, which correlated directly with their age at diagnosis. No statistically significant differences in metabolic control or microvascular complications were observed between the C-peptide level groups. In addition, our results indicate that ancestry does not influence the persistence of residual C-peptide function in our highly mixed population. It is recommended that future research consider incorporating new variables, such as HLA and pancreatic autoimmunity, as factors that may influence residual β-cell function.