bluuebunny/crossref_metadata_2025 huggingface dataset:
A Data-Driven Approach to Enhance the Prediction of Bacteria–Metabolite Interactions in the Human Gut Microbiome Using Enzyme Encodings and Metabolite Structural Embeddings
Authors: Srivastava Gopal , Brylinski Michal
Published: January 2025

Background: The human gut microbiome is critical for host health by facilitating essential metabolic processes. Our study presents a data-driven analysis across 312 bacterial species and 154 unique metabolites to enhance the understanding of underlying metabolic processes in gut bacteria. The focus of the study was to create a strategy to generate a theoretical (negative) set for binary classification models to predict the consumption and production of metabolites in the human gut microbiome. Results: Our models achieved median balanced accuracies of 0.74 for consumption predictions and 0.95 for production predictions, highlighting the effectiveness of this approach in generating reliable negative sets. Additionally, we applied a kernel principal component analysis for dimensionality reduction. The consumption model with a polynomial kernel, and the production model with a radial basis function with 32 reduced features, showed median accuracies of 0.58 and 0.67, respectively. This demonstrates that biological information can still be captured, albeit with some loss, even after reducing the number of features. Furthermore, our models were validated on six previously unseen cases, achieving five correct predictions for consumption and four for production, demonstrating alignment with known biological outcomes. Conclusions: These findings highlight the potential of integrating data-driven approaches with machine learning techniques to enhance our understanding of gut microbiome metabolism. This work provides a foundation for creating bacteria–metabolite datasets to enhance machine learning-based predictive tools, with potential applications in developing therapeutic methods targeting gut microbes.
From Evidence to Practice: A Narrative Framework for Integrating the Mediterranean Diet into Inflammatory Bowel Disease Management
Authors: Naik Riya Gautam , Purcell Sarah A. , Gold Stephanie L. , Christiansen Victoria , D’Aloisio Leah D. , Raman Maitreyi , Haskey Natasha
Published: January 2025

Emerging evidence underscores the pivotal role of diet in preventing and managing inflammatory bowel disease (IBD). As our comprehension of the microbiome’s role in IBD expands, dietary modifications are increasingly recognized as potential adjuncts or primary therapeutic strategies. Key components of the Mediterranean diet (MD)—including microbiota-accessible carbohydrates, omega-3 fatty acids, polyphenols, and antioxidants—have demonstrated promise in enhancing gut microbiota diversity and reducing intestinal inflammation, making it a practical approach for managing IBD. Moreover, the MD offers additional benefits considering the rising prevalence of comorbid chronic inflammatory conditions such as diabetes, cardiovascular disease, and obesity in IBD patients. The purpose of this narrative review was to provide an overview of the feasibility and clinical outcomes of the MD and offer evidence-based guidance for researchers and practitioners on how to adapt the MD to patients with IBD. According to several cross-sectional and interventional studies, the MD is feasible for patients with IBD and confers several benefits, such as reduced inflammation, improved disease activity, and enhanced quality of life, with a strong adherence rate and minimal adverse effects. To facilitate knowledge translation, we provide a practical framework for integrating the MD as a nutritional therapy for IBD, including specific recommendations and messaging that researchers, practitioners, and patients can use. By synthesizing current evidence and offering actionable insights, the aim is to facilitate the integration of the MD into IBD management, with the potential to improve patient outcomes.
Exploring Emotional, Restrained, and External Eating Behaviors: Impacts on Energy and Nutrient Intakes Among Korean Adults
Authors: Ryu Geum-Bi , Heo Young-Ran
Published: January 2025

Background/Objectives: This study aimed to investigate the levels of emotional, restrained, and external eating behaviors (EBs) among adults, categorize them, and analyze their energy and nutrient intake. Methods: A self-reported survey was administered to 522 Korean adults aged 19–64 years to evaluate their emotional, restrained, and external EBs. They were categorized into five types: Non-specific (NS), Emotional (Emo), Restrained (Res), External (Ext), and Combined (Com) EB types. Subsequently, energy intake, intake ratios and levels, and vitamin and mineral intakes were compared after adjusting for sex and age. Results: The Ext type participants consumed energy and an average of 3003.01 kcal per day, while those with Res type consumed 2415.77 kcal. Notably, both the Ext and Com types had higher proportions of excessive energy intake, while the NS and Res types displayed higher proportions of insufficient energy intake. The Emo type yielded a high ratio of lipid intake, while the Com type exhibited high ratios of both lipid and protein intakes. Furthermore, the Res type demonstrated lower vitamin E, niacin, and potassium intakes than the other types. Conclusions: Since the Ext type suggests excessive energy intake, and the Res type suggest intake of vitamin E, niacin, and potassium, identifying EB types provides a novel perspective for nutritional improvement strategies.
Comparative Efficacy and Safety of JAK Inhibitors in the Management of Rheumatoid Arthritis: A Network Meta-Analysis
Authors: Almoallim Hani M. , Omair Mohammed A. , Ahmed Sameh A. , Vidyasagar Kota , Sawaf Bisher , Yassin Mohamed A.
Published: January 2025

Background/objective: Janus Kinase inhibitors (JAKinibs) are effective and well-tolerated targeted therapies for rheumatoid arthritis (RA). The comparative efficacy and safety of different JAKinibs remains unclear. This network meta-analysis (NMA) aimed to assess the relative efficacy and safety of different available JAKinibs. Methods: Searches were conducted on PubMed, CENTRAL, and ClinicalTrials.gov for randomized, double-blind, placebo-controlled trials comparing JAKinibs in RA patients. A frequentist NMA using the Netmeta package in R (R.4.3.0) was performed to evaluate both efficacy and safety outcomes. Continuous outcomes were presented as mean differences (MDs) and binary outcomes as relative risks (RR) with 95% confidence intervals (CI). The Cochrane risk of bias tool was used to assess the risk of bias in the included trials. Results: The analysis encompassed 39 trials with a total of 16,894 participants. Six JAKinibs (tofacitinib, baricitinib, upadacitinib, decernotinib, peficitinib, and filgotinib) were compared. Decernotinib at a dose of 300 mg showed a higher ACR50 response than other JAKinibs (RR = 7.55, 95% CI: 3.48 to 16.39, p < 0.01, surface under the cumulative ranking curve (SUCRA): 0.92). Tofacitinib at a dose of 1 mg twice daily had a significantly lower incidence of adverse drug reactions (ADRs) compared to other JAKinibs (RR = 0.80, 95% CI: 0.65 to 0.99, p = 0.04, SUCRA: 0.89), filgotinib 100 mg had a significantly lower infection risk (RR = 0.40, 95% CI: 0.21 to 0.79, p < 0.01, SUCRA: 0.90), whereas baricitinib 4 mg had the significantly highest herpes zoster risk (RR = 4.79, 95% CI: 1.03 to 22.21, p = 0.05, SUCRA: 0.11) compared to other JAKinibs. Conclusions: This NMA’s results indicate that commercially available JAKinibs show superior ACR responses and have comparable tolerability to placebo.
Formulation and Evaluation of Polymeric Spherical Agglomerates-Based Porous Orodispersible Tablets of Cilnidipine
Authors: Alhamhoom Yahya , Prakash Sanjana S. , Kumar Avichal , Nanjappa Shivakumar Hagalavadi , Rahamathulla Mohamed , Kamath Megha S. , Farhana Syeda Ayesha , Ahmed Mohammed Muqtader , Boreddy-Shivanandappa Thippeswamy
Published: January 2025

Background/Objectives: Cilnidipine (CIL) is a calcium channel blocker that exhibits low bioavailability (~13%) due to poor aqueous solubility and extensive pre-systemic gut wall metabolism. The current study aimed to enhance the oral bioavailability of CIL by formulation of polymeric spherical agglomerates (CILSAs)-based orodispersible tablets (ODTs). Methods: Eight different batches of CILSAs were prepared by a crystallo-co-agglomeration technique using different proportions of hydrophilic polymers like hydroxy propyl methyl cellulose E50, polyvinyl pyrrolidone K30, or polyethylene glycol (PEG) 6000 as carriers. Fourier transform infrared spectroscopy (FTIR) of CILSAs proved the chemical integrity of CIL in SAs, while scanning electron microscopy revealed the spherical shape of CILSAs. Results: Differential scanning calorimetry and powder X-ray diffraction studies confirmed that CIL was rendered more amorphous in CILSAs. CILSAs displayed good flow behavior, high percentage yield, and high drug loads. The batch F4 composed of PEG 6000 emerged as the optimized batch as it displayed high percentage dissolution efficiency (57.01 ± 0.01%), which was significantly greater (p < 0.001) compared to CIL (26.27 ± 0.06%). The optimized formulation of CILSAs was directly compressed into ODTs that were rendered porous by vacuum drying. The optimized formulation of porous ODTs (T3) displayed low friability (0.28 ± 0.03%), short disintegration time (6.26 ± 0.29 s), and quicker dissolution (94.16 ± 1.41% in 60 min) as compared to marketed tablet Cildipin® 10 mg (85 ± 2.3%). Conclusions: Thus, porous ODTs of CILSAs can rapidly release the drug, bypass gut metabolism, enhance oral bioavailability, and improve CIL’s therapeutic effectiveness for angina and hypertension.
Therapeutic Effects of Nanocoating of Apitoxin (Bee Venom) and Polyvinyl Alcohol Supplemented with Zinc Oxide Nanoparticles
Authors: Qanash Husam , Bazaid Abdulrahman S. , Alharbi Shahad F. , Binsaleh Naif K. , Barnawi Heba , Alharbi Bandar , Alsolami Ahmed , Almashjary Majed N.
Published: January 2025

Background/Objectives: Bee venom (BV), as a natural product, is one of the foundations of the pharmaceutical industry, through which many diseases, including serious ones, can be effectively treated. The BV nanofilm is an effective antidote delivered into the human body to target the affected area and address the issue without major side effects. In this study, we investigated the intriguing therapeutic effects of apitoxin (bee venom) used in isolation, combined with the powerful properties of zinc oxide nanoparticles. Methods and Results: BV nanofilm was evaluated using Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD). The BV extract was analyzed using mass spectrometry (MS), which identified 84 active components present at varying concentrations. BV was treated with both polyvinyl alcohol (PVA) and zinc oxide nanoparticles (ZNPs) to increase the intensity of OH and CH2 groups and to enhance the dispersion of C=O. BV has demonstrated anti-type 2 diabetes activity by inhibiting α-amylase and α-glucosidase, which are starch-degrading enzymes. The nanofilm is an active mixture of BV, PVA, and ZNPs, which exhibited the highest antidiabetic activity with IC50 values of 30.33 μg/mL and 5.55 μg/mL for the inhibition of α-amylase and α-glucosidase, compared to IC50 of 51.69 µg/mL and IC50 of 7.30 µg/mL for BV, respectively. The nanofilm also showed higher anti-inflammatory activity by inhibiting red blood cell (RBC) hemolysis, with an IC50 of 16.99 μg/mL in comparison to IC50 of 72.99 µg/mL for BV alone. The nanofilm demonstrated broad-spectrum antimicrobial activity, effectively targeting both Gram-positive (Staphylococcus aureus ATCC 6538 and Bacillus subtilis ATCC 6633) and Gram-negative bacteria (Salmonella typhi ATCC 6539, Escherichia coli ATCC 8739). Furthermore, increased antioxidant activity was recorded by inhibiting the 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging effect with an IC50 of 4.26 μg/mL and 19.43 μg/mL for nanofilm and BV, respectively. BV was found to be more toxic to liver tissue (HepG2 cell line) than nanofilm, with IC50 values of 18.5 ± 0.08 μg/mL and 52.27 ± 0.7 μg/mL, respectively. The BV extract displayed higher toxicity to liver tissue (2.3%) with 97.7% viability at 250 μg/mL, compared to nanofilm, which showed 0.09% toxicity and 99.9% viability at the same concentration. Conclusions: the BV nanofilm emerges as a promising alternative medicine, offering an innovative solution for treating various diseases through its high concentration of therapeutically active compounds and effortless targeting delivery.
Ultraviolet C Decontamination Devices in a Hospital Pharmacy: An Evaluation of Their Contribution
Authors: Baudart Clara , Briot Thomas
Published: January 2025

Purpose: The COVID-19 pandemic led to a major interest in ultraviolet C (UVC) disinfection devices and accelerated the implementation of UVC devices in healthcare facilities due to their proven efficacy in the inactivation of various pathogens. While UVC technology offers several advantages, some drawbacks remain. This report, drawing on studies, guidelines, and practical experiences related to the use of UVC technology in healthcare settings, examines the efficacy, advantages, and drawbacks of UVC devices, and their applications in aseptic drug-compounding pharmaceutical units. Summary: Studies, guidelines, and practical experiences were selected. UVC technology offers advantages such as rapid disinfection, reduced reliance on chemical agents, minimal waste, and freedom from manual disinfection variability, making it particularly valuable for maintaining aseptic conditions in compounding environments. However, some drawbacks persist, as it is a germ-dependent method and there is currently no standardized method for ensuring effectiveness. Conclusions: This opinion paper highlights the effectiveness of UCV technology in pharmaceutical compounding units, proving that it is a viable alternative to the traditionally used manual and operator-dependent methods. However, there is a need for standardized methods to evaluate UVC devices.
On the Plant Developmental Unit: From Virtual Concept to Visual Plantlet
Authors: Bai Shu-Nong
Published: January 2025

This study introduces the concept of the plant developmental unit (PDU) and validates its application using Wolffia Horkel ex Schleid (Araceae) as a model system for exploring fundamental processes in plant morphogenesis. Revisiting long-standing contradictions in plant biology, the author proposes viewing plants as coral-like colonies composed of multiple developmental units rather than as unitary-animal-like organisms. Utilizing the “Plant-on-Chip” culture platform, the research demonstrates Wolffia’s minimalist structure as a powerful model for investigating core regulatory mechanisms of plant development. The study emphasizes the pivotal role of “induction” in morphogenetic processes and highlights Wolffia’s potential to facilitate a paradigm shift in plant developmental biology while unlocking its applications in a second agricultural revolution. This work underscores Wolffia’s value in bridging fundamental research and innovative agricultural solutions.
Modification of Polyamide Resins by Addition of Polyvinylpyrrolidone
Authors: Ikemoto Yui , Yamaguchi Masayuki
Published: January 2025

The effect of the addition of polyvinylpyrrolidone (PVP) to polyamide resins was studied using polyamide 6 (PA6) and an amide copolymer with a low melting point (PA-L). For the PA6/PVP blends, the crosslinking reaction occurred during rheology measurements in the molten state. The blends did not show a phase-separated structure. Furthermore, the crystallization of PA6 was greatly inhibited by PVP addition. These results suggest that the PVP chains were dissolved in PA6 in the molten state, although the effect of the crosslinking reaction on the structure development is unknown. In the case of the PA-L/PVP blends, melt-mixing and the rheology measurements were performed at low temperature to avoid the crosslinking reaction. It was found that PVP was miscible with PA-L in the molten state when the PVP content was 10 and 15 wt%. The intermolecular interaction between the polyamide resins and PVP was detected from the peak shift of the infrared absorbance. PVP addition enhanced the moisture content in both polyamide resins and decreased the contact angle with water droplets. These results suggested that the surface properties and mechanical properties of polyamide resins, which are affected by the moisture content, are modified by PVP addition.
Simulation-Based Design of a Cam-Driven Hydraulic Prosthetic Ankle
Authors: Pace Anna , Gardiner James , Howard David
Published: January 2025

Background/Objectives: A cam-driven hydraulic prosthetic ankle was designed to overcome the weaknesses of commercial prostheses and research prototypes, which largely fail to mimic the energy-recycling behaviour of an intact ankle, resulting in poor walking performance for lower-limb prosthesis users. Methods: This novel device exploits miniature hydraulics to capture the negative work performed during stance, prior to push-off, in a hydraulic accumulator, and return positive work during push-off for forward body propulsion. Two cams are used to replicate intact ankle torque profiles based on experimental data. The design process for the new prosthesis used a design programme, implemented in MATLAB, based on a simulation of the main components of the prosthetic ankle. Results: In this paper, we present the design programme and explain how it is used to determine the cam profiles required to replicate intact ankle torque, as well as to size the cam follower return springs. Moreover, a constraint-based preliminary design investigation is described, which was conducted to size other key components affecting the device’s size, performance, and energy efficiency. Finally, the feasible design alternatives are compared in terms of their energy losses to determine the best design with regard to minimising both energy losses and device size. Conclusions: Such a design approach not only documents the design of a particular novel prosthetic ankle, but can also provide a systematic framework for decomposing complex design challenges into a series of sub-problems, providing a more effective alternative to heuristic approaches in prosthetic design.
A Grammatical Investigation of Miracles
Authors: Ellis David
Published: January 2025

Wittgenstein claims that religious belief does not stand on evidence, that only those with a religious point of view can see an event as a miracle, and that experiencing a miracle can influence a person towards religious belief. This has the unusual outcome that a miracle can lead a person to God, but a miracle cannot be evidence of God. This also faces two challenges. First, if miracles can only be seen from a religious point of view, then suggesting that a miracle can influence a person towards religion implies that a person can see a miracle before having a religious point of view. Second, if religious belief is not based on evidence, then those who report believing because of evidence are confused about their beliefs in a way we would not expect. I argue that these are not challenges to Wittgenstein’s account but symptoms of our misunderstanding of grammar and his distinction between relative and absolute miracles.
Concrete Mix Design of Recycled Concrete Aggregate (RCA): Analysis of Review Papers, Characteristics, Research Trends, and Underexplored Topics
Authors: Prasittisopin Lapyote , Tuvayanond Wiput , Kang Thomas H.-K. , Kaewunruen Sakdirat
Published: January 2025

Recycled concrete aggregate (RCA) has been widely adopted in construction and emerged as a sustainable alternative to conventional natural aggregates in the construction industry. However, the study of holistic perspectives in recent literature is lacking. This review paper aims to provide a comprehensive analysis of RCA, highlighting its properties, applications, and overall sustainability benefits to facilitate the comprehensive points of view of technology, ecology, and economics. This paper explores the manufacturing process of RCA, examines its mechanical and durability characteristics, and investigates its environmental impacts. Furthermore, it delves into the various applications of RCA, such as road construction materials, pavement bases, and concrete materials, considering their life cycle performance and economic considerations. This review reveals that there is a need for systemic data collection that could enable automated concrete mix design. The findings concerning various mix concrete designs suggest that increasing the 1% replacement level reduces the compressive strength by 0.1913% for coarse RCA and 0.2418% for fine RCA. The current critical research gaps are the durability of RCA concrete, feasibility analyses, and the implementation of treatment methods for RCA improvement. An effective life cycle assessment tool and digitalization technologies can be applied to enhance the circular economy, aligning with the United Nations’ sustainable development goals (UN-SDGs). The equivalent mortar volume method used to calculate the RCA concrete mix design, which can contain chemical additives, metakaolin, and fibers, needs further assessment.
Tension-Aware Motion Planning for Tethered Robots
Authors: Lima Rogério R. , Pereira Guilherme A. S.
Published: January 2025

This paper presents a path-planning approach for tethered robots. The proposed planner finds paths that minimize the tether tension due to tether–obstacle and tether–floor interaction. The method assumes that the tether is managed externally by a tether management system and pulled by the robot. The planner is initially formulated for ground robots in a 2D environment and then extended for 3D scenarios, where it can be applied to tethered aerial and underwater vehicles. The proposed approach assumes a taut tether between two consecutive contact points and knowledge of the coefficient of friction of the obstacles present in the environment. The method first computes the visibility graph of the environment, in which each node represents a vertex of an obstacle. Then, a second graph, named the tension-aware graph, is built so that the tether–environment interaction, formulated in terms of tension, is computed and used as the cost of the edges. A graph search algorithm (e.g., Dijkstra) is then used to compute a path with minimum tension, which can help the tethered robot reach longer distances by minimizing the tension required to drag the tether along the way. This paper presents simulations and a real-world experiment that illustrate the characteristics of the method.
Local Influence of Surface Relative Humidity on Weather Radar Rainfall Observations over an Agricultural Semi-Arid Area
Authors: Polls Francesc , Bech Joan , Udina Mireia , Peinó Eric , Rigo Tomeu
Published: January 2025

Agricultural areas in semi-arid regions modify low-level atmospheric conditions through changes in heat and moisture surface fluxes and enhanced evapotranspiration. This study aims to investigate the influence of near-ground-level relative humidity (RH) on local precipitation characteristics in a relatively flat, mid-latitude, semi-arid agricultural region, divided into a rainfed and an irrigated area with high evapotranspiration contrast in summer. The region was selected for the Land Surface Interactions with the Atmosphere over the Iberian Semi-Arid Environment (LIAISE) international field campaign in 2021 and here is studied using Automatic Weather Station observations and C-band weather radar data covering six years. Summer RH records show clear contrasts between irrigated and non-irrigated areas, unlike rain gauge and radar-derived rainfall, which do not exhibit substantial differences. A closer analysis indicates that RH differences between irrigated and non-irrigated areas before rainfall tend to diminish for several hours after the rainfall onset. This suggests that the presence of rainfall is temporally more important than whether the terrain is irrigated or not. Examination of radar reflectivity (Z) profiles considered convective and non-convective cases averaged during the first 30 and 180 min from the precipitation onset. Results indicated a dependence on ground-level RH for convective cases, leading to higher Z values with higher RH, clearer for the first 30 min averaged profiles. Finally, a linear relation was found between the lowest 1 km radar Z value and collocated RH for the first 30 min period of convective precipitation, increasing Z with RH. These results point out that, despite no differences in precipitation amounts found over contiguous irrigated and non-irrigated areas, there is a local impact of low-level moisture on convective rainfall.
Investigating the Impact of Spatiotemporal Variations in Water Surface Optical Properties on Satellite-Derived Bathymetry Estimates in the Eastern Mediterranean
Authors: Muhammad Fickrie , Tsimpouxis Ioannis , Sternberg Harald
Published: January 2025

Bathymetric data are crucial for benthic monitoring in coastal areas but are traditionally obtained through costly and geographically limited acoustic methods. This study uses satellite-derived bathymetry (SDB) in the Eastern Mediterranean, focusing on the Cretan Sea in Greece. It explores how variations in water surface optical properties affect SDB models over four years (2019–2022), using Sentinel-2 satellite data. The research covers two areas with contrasting features: the Chania Gulf and the open waters around Chrissi Island. Three methodologies were tested: the band-ratio method, the linear-logarithmic method, and an inherent optical properties linear model. Significant spatiotemporal variations in the SDB models were found, due to seasonal changes in water surface properties, such as temperature and suspended organic materials. Linear optical properties-based methods performed best, achieving a mean RMSE close to 1 m, slightly outperforming the ratio-based method. The logarithmic method was less effective, with RMSE values ranging from 1.3 to 1.5 m. A preliminary Kalman filter (KF) analysis increased RMSE to the decimeter level. This study demonstrates the impact of water surface optical properties on SDB models. It highlights the value of SDB for cost-effective, high-resolution coastal mapping in complex coastlines like those in Greece.
Forest Stem Extraction and Modeling (FoSEM): A LiDAR-Based Framework for Accurate Tree Stem Extraction and Modeling in Radiata Pine Plantations
Authors: Ibrahim Muhammad , Wang Haitian , A. Iqbal Irfan , Miao Yumeng , Albaqami Hezam , Blom Hans , Mian Ajmal
Published: January 2025

Accurate characterization of tree stems is critical for assessing commercial forest health, estimating merchantable timber volume, and informing sustainable value management strategies. Conventional ground-based manual measurements, although precise, are labor-intensive and impractical at large scales, while remote sensing approaches using satellite or UAV imagery often lack the spatial resolution needed to capture individual tree attributes in complex forest environments. To address these challenges, this study provides a significant contribution by introducing a large-scale dataset encompassing 40 plots in Western Australia (WA) with varying tree densities, derived from Hovermap LiDAR acquisitions and destructive sampling. The dataset includes parameters such as plot and tree identifiers, DBH, tree height, stem length, section lengths, and detailed diameter measurements (e.g., DiaMin, DiaMax, DiaMean) across various heights, enabling precise ground-truth calibration and validation. Based on this dataset, we present the Forest Stem Extraction and Modeling (FoSEM) framework, a LiDAR-driven methodology that efficiently and reliably models individual tree stems from dense 3D point clouds. FoSEM integrates ground segmentation, height normalization, and K-means clustering at a predefined elevation to isolate stem cores. It then applies circle fitting to capture cross-sectional geometry and employs MLESAC-based cylinder fitting for robust stem delineation. Experimental evaluations conducted across various radiata pine plots of varying complexity demonstrate that FoSEM consistently achieves high accuracy, with a DBH RMSE of 1.19 cm (rRMSE = 4.67%) and a height RMSE of 1.00 m (rRMSE = 4.24%). These results surpass those of existing methods and highlight FoSEM’s adaptability to heterogeneous stand conditions. By providing both a robust method and an extensive dataset, this work advances the state of the art in LiDAR-based forest inventory, enabling more efficient and accurate tree-level assessments in support of sustainable forest management.
A Top-Down Method for Estimating Regional Fossil Fuel Carbon Emissions Based on Satellite XCO2 Retrievals
Authors: Zhang Lingyu , Jiang Fei , Mao Yu , Lv Guoyuan , Wang Hengmao , Feng Shuzhuang , Ju Weimin
Published: January 2025

Satellite XCO2 retrievals have been widely used in estimating fossil fuel carbon (FFC) emissions at point and urban scales. However, at the regional scale, it remains a significant challenge. Furthermore, current global and regional atmospheric inversions often overlook the uncertainties associated with FFC emissions. To meet the needs of the global carbon stocktake, we developed an inversion method based on Bayesian statistical theory and OCO-2 satellite XCO2 observations to optimize FFC emissions alongside terrestrial ecosystem carbon fluxes (NEE). The methodology’s core is to distinguish the contributions of NEE and FFC to the observed concentrations using their different spatial distributions. We designed an observing system simulation experiment to invert the 2016 FFC emissions. The results showed that posterior FFC emissions were significantly optimized during the non-growing seasons in the regions with high emissions, with the optimization effect diminishing as emissions shrank. Average FFC emissions uncertainty reductions are in the range of 13–82% in the non-growing season for the eight largest emitting regions globally. By assuming the same uncertainty reduction for FFC emissions in both the growing and non-growing seasons, we can optimize annual emissions for high-emission areas. We believe this study provides a new idea for the inversion of FFC emissions at the regional scale, which is important for achieving the goal of carbon neutrality.
Metasensor: A Proposal for Sensor Evolution in Robotics
Authors: Braccini Michele
Published: January 2025

Sensors play a fundamental role in achieving the complex behaviors typically found in biological organisms. However, their potential role in the design of artificial agents is often overlooked. This often results in the design of robots that are poorly adapted to the environment, compared to their biological counterparts. This paper proposes a formalization of a novel architectural component, called a metasensor, which enables a process of sensor evolution reminiscent of what occurs in living organisms. The metasensor layer searches for the optimal interpretation of its input signals and then feeds them to the robotic agent to accomplish the assigned task. Also, the metasensor enables a robot to adapt to new tasks and dynamic, unknown environments without requiring the redesign of its hardware and software. To validate this concept, a proof of concept is presented where the metasensor changes the robot’s behavior from a light avoidance task to an area avoidance task. This is achieved through two different implementations: one hand-coded and the other based on a neural network substrate, in which the network weights are evolved using an evolutionary algorithm. The results demonstrate the potential of the metasensor to modify the behavior of a robot through sensor evolution. These promising results pave the way for novel applications of the metasensor in real-world robotic scenarios, including those requiring online adaptation.
Dynamic Stability Analysis and Optimization of Multi-Vehicle Systems in Heterogeneous Connected Traffic
Authors: Wang Tao , Qu Dayi
Published: January 2025

This study investigates the stability and performance of mixed-traffic flows consisting of human-driven vehicles (HDVs), connected autonomous vehicles (CAVs), autonomous vehicles (AVs), and connected human-driven vehicles (CHVs). Recognizing the complexity introduced by multi-vehicle interactions in such heterogeneous traffic, a refined CAV car-following model that integrates multi-vehicle state information, including headway, weighted velocity differences, weighted acceleration, and optimal velocity memory effects from both front and rear vehicles, is introduced. Through theoretical analysis of the model’s linear and nonlinear stability, the key parameters that enhance flow stability in mixed environments are determined. Numerical simulations across braking, start-up, and ring road scenarios validate the proposed model’s efficacy, demonstrating that it can effectively suppress traffic congestion and reduce oscillations, thereby improving traffic flow stability. This work offers valuable insights into the behavior of connected vehicles within mixed traffic and highlights the potential for CAV-based strategies to enhance both safety and efficiency in future transportation systems.
Experimental Assessment of OSNMA-Enabled GNSS Positioning in Interference-Affected RF Environments
Authors: Rusu-Casandra Alexandru , Lohan Elena Simona
Published: January 2025

This article investigates the performance of the Galileo Open Service Navigation Message Authentication (OSNMA) system in real-life environments prone to RF interference (RFI), jamming, and/or spoofing attacks. Considering the existing data that indicate a relatively high number of RFI- and spoofing-related incidents reported in Eastern Europe, this study details a data-collection campaign along various roads through urban, suburban, and rural settings, mostly in three border counties in East and South-East of Romania, and presents the results based on the data analysis. The key performance indicators are determined from the perspective of an end user relying only on Galileo OSNMA authenticated signals. The Galileo OSNMA signals were captured using one of the few commercially available GNSS receivers that can perform this OSNMA authentication algorithm incorporating the satellite signals. This work includes a presentation of the receiver’s operation and of the authentication results obtained during test runs that experienced an unusually high number of RFI-related incidents, followed by a detailed analysis of instances when such RFI impaired or fully prevented obtaining an authenticated position, velocity, and time (PVT) solution. The results indicate that Galileo OSNMA demonstrates significant robustness against interference in real-life RF-degraded environments, dealing with both accidental and intentional interference.
Parallax-Tolerant Weakly-Supervised Pixel-Wise Deep Color Correction for Image Stitching of Pinhole Camera Arrays
Authors: Zhang Yanzheng , Gao Kun , Yang Zhijia , Li Chenrui , Cai Mingfeng , Tian Yuexin , Cheng Haobo , Zhu Zhenyu
Published: January 2025

Camera arrays typically use image-stitching algorithms to generate wide field-of-view panoramas, but parallax and color differences caused by varying viewing angles often result in noticeable artifacts in the stitching result. However, existing solutions can only address specific color difference issues and are ineffective for pinhole images with parallax. To overcome these limitations, we propose a parallax-tolerant weakly supervised pixel-wise deep color correction framework for the image stitching of pinhole camera arrays. The total framework consists of two stages. In the first stage, based on the differences between high-dimensional feature vectors extracted by a convolutional module, a parallax-tolerant color correction network with dynamic loss weights is utilized to adaptively compensate for color differences in overlapping regions. In the second stage, we introduce a gradient-based Markov Random Field inference strategy for correction coefficients of non-overlapping regions to harmonize non-overlapping regions with overlapping regions. Additionally, we innovatively propose an evaluation metric called Color Differences Across the Seam to quantitatively measure the naturalness of transitions across the composition seam. Comparative experiments conducted on popular datasets and authentic images demonstrate that our approach outperforms existing solutions in both qualitative and quantitative evaluations, effectively eliminating visible artifacts and producing natural-looking composite images.
Estimation of the Measurement Accuracy of Wireless Passive Resonance Sensors
Authors: Reindl Leonhard M. , Aftab Taimur , Schaechtle Thomas , Ostertag Thomas , Luo Wei , Rupitsch Stefan Johann
Published: January 2025

Resonators are passive devices that respond to an excitation signal by oscillating at their natural frequency with exponentially decreasing amplitudes. Physical, chemical and electrical variables can modify the natural frequencies of resonators. If resonators are connected to antennas or other transducers that couple into a communication channel, they enable purely passive sensors that can be read wirelessly. In this manuscript, we use maximum likelihood estimation to analyze the measurement accuracy that can be achieved by the wireless readout of passive resonant sensors as a function of the read signal, the stimulation power and noise figure of the reader, the distance and transducer gain of the transmission channel, and the natural frequency and quality factor of the resonant passive sensor. The Crámer–Rao lower bound characterizes the minimum variance of the natural frequency and decay constant of the resonator. We show the derivation of the Crámer–Rao lower bounds from the Fisher information matrix based on a maximum likelihood estimation of discrete-time samples of an exponentially decaying phasor. This theoretical lower limit of accuracy is almost achieved by an iterative algorithm that approximates the maximum of the measured resonator spectrum with a Lorentz curve.
Polymer-Based Contactless Conductivity Detector for Europan Salts (PolyCoDES)
Authors: Govinda Raj Chinmayee , Salyards Peyton , McCoy Catherine , Stockton Amanda
Published: January 2025

This study presents the development of an innovative drop-stain-coat fabrication technique for creating high-quality PEDOT:PSS films, optimized for use in polymer-based electrodes within contactless conductivity detection (C4D) sensors. We detail the fabrication and thorough characterization of PEDOT films produced via the drop-stain-coat method, emphasizing its efficiency and reliability in electrode manufacturing. The resulting polymer electrodes were integrated into C4D sensors, which were rigorously characterized to assess their performance in detecting multiple salt types within real-world samples. This approach highlights the potential of drop-stain-coat fabrication to advance sensor applications in diverse analytical environments, offering a practical solution for accurate and adaptable conductivity detection.
Real-Time Classification of Ochratoxin a Contamination in Grapes Using AI-Enhanced IoT
Authors: Sebti Mohamed Riad , Dakhia Zohra , Carabetta Sonia , Di Sanzo Rosa , Russo Mariateresa , Merenda Massimo
Published: January 2025

Ochratoxin A (OTA) contamination presents significant risks in viticulture, affecting the safety and quality of wine and grape-derived products. This study introduces a groundbreaking method for early detection and management of OTA, leveraging environmental data such as temperature and humidity. A function derived from chemical analysis was developed to estimate OTA concentrations and used to label a synthetic dataset, establishing safe thresholds. Two AI models were trained: one for the detecting of OTA presence and the other for classifying the concentration range. These models were deployed on a M5Stick C+, a microcontroller designed for real-time data processing. The inference process is optimized for rapid response, requiring minimal time to deliver results. Additionally, the low power consumption of the M5Stick C+ ensures that the device can operate throughout the harvest period on a single charge. The system is able to transmit inference data via MQTT for real-time analysis. This comprehensive approach offers a scalable, cost-effective, on-site solution that is autonomous, eliminating the need for domain experts and extensive resources. The robustness of the system was demonstrated through its consistent performance across multiple test sets, providing an effective enhancement to food safety in grape and wine production. The study also details the system architecture, describes the function used for data labeling, outlines the training and deployment processes of the models, and finally, assesses the testing of the overall system.
Spatio-Temporal Agnostic Sampling for Imbalanced Multivariate Seasonal Time Series Data: A Study on Forest Fires
Authors: Mutakabbir Abdul , Lung Chung-Horng , Naik Kshirasagar , Zaman Marzia , Ajila Samuel A. , Ravichandran Thambirajah , Purcell Richard , Sampalli Srinivas
Published: January 2025

Natural disasters are mostly seasonal and caused by anthropological, climatic, and geological factors that impact human life, economy, ecology, and natural resources. This paper focuses on increasingly widespread forest fires, causing greater destruction in recent years. Data obtained from sensors for predicting forest fires and assessing fire severity, i.e., area burned, are multivariate, seasonal, and highly imbalanced with a ratio of 100,000+ non-fire events to 1 fire event. This paper presents Spatio-Temporal Agnostic Sampling (STAS) to overcome the challenge of highly imbalanced data. This paper first presents a mathematical understanding of fire and non-fire events and then a thorough complexity analysis of the proposed STAS framework and two existing methods, NearMiss and SMOTE. Further, to investigate the applicability of STAS, binary classification models (to determine the probability of forest fire) and regression models (to assess the severity of forest fire) were built on the data generated from STAS. A total of 432 experiments were conducted to validate the robustness of the STAS parameters. Additional experiments with a temporal data split were conducted to further validate the results. The results show that 180 of the 216 binary classification models had an F1score>0.9 and 150 of the 216 regression models had an R2score>0.75. These results indicate the applicability of STAS for fire prediction with highly imbalanced multivariate seasonal time series data.
Exploring AI Amid the Hype: A Critical Reflection Around the Applications and Implications of AI in Journalism
Authors: Spyridou Paschalia (Lia) , Ioannou Maria
Published: January 2025

Over the last decade, AI has increasingly been adopted by newsrooms in the form of different tools aiming to support journalists and augment the capabilities of the profession. The main idea behind the adoption of AI is that it can make journalists’ work more efficient, freeing them up from some repetitive or routine tasks while enhancing their research and storytelling techniques. Against this idea, and drawing on the concept of “hype”, we employ a critical reflection on the lens often used to talk about journalism and AI. We suggest that the severe sustainability crisis of journalism, rooted in growing pressure from platforms and major corporate competitors, changing news consumption habits and rituals and the growing technologization of news media, leads to the obsessive pursuit of technology in the absence of clear and research-informed strategies which cater to journalism’s civic role. As AI is changing and (re)shaping norms and practices associated with news making, many questions and debates are raised pertaining to the quality and plurality of outputs created by AI. Given the disproportionate attention paid to technological innovation with little interpretation, the present article explores how AI is impacting journalism. Additionally, using the political economy framework, we analyze the fundamental issues and challenges journalism is faced with in terms of both practices and professional sustainability. In the process, we untangle the AI hype and attempt to shed light on how AI can help journalism regain its civic role. We argue that despite the advantages AI provides to journalism, we should avoid the “shiny things perspective”, which tends to emphasize productivity and profitability, and rather focus on the constructive synergy of humans and machines to achieve the six or seven things journalism can do for democracy. Otherwise, we are heading toward “alien intelligence” which is agnostic to the core normative values of journalism.
Dead in Life: Narratives About Circumstances Prior to Suicide in Rural Western Spain
Authors: López-Lago Ortiz Luis , Mariano Juárez Lorenzo , López García Julián
Published: January 2025

Background: In rural contexts, meanings of suicide are part of the intimate heritage of those closest to the suicidal person. They are also constructed through a social process. Over time, the community creates meanings, shares notions, and experiences common emotions. In this process, the boundaries between the life and death of the suicidal person are blurred. Methods: An ethnographic study was carried out with more than six months of fieldwork in a rural locality of Extremadura, Spain. This research included narratives that delved into the historical memory of suicides from 1922 to 2023. Results: In the narratives, the following categories emerged in the consideration of the suicidal person at the moment of death: trance as a transition/connection towards death, the appearance of being detached from life, the possibility of resurrection, and the premonitory appearance. These categories were interrelated and shared close symbolic meanings. Conclusions: The nature of the results and their contrast with diverse theories and experiences show that the earthly and otherworldly planes are intertwined. This allows us to affirm that, in the narratives about suicides, individuals perceive themselves as simultaneously alive and dead at the moment of taking their own lives.