bluuebunny/crossref_metadata_2025 huggingface dataset:
Nanotechnology-Based Approaches for the Management of Diabetes Mellitus: An Innovative Solution to Long-Lasting Challenges in Antidiabetic Drug Delivery
Authors: Sarkhel Shounak , Shuvo Saikat Mollick , Ansari Md Ahesan , Mondal Sourav , Kapat Pritam , Ghosh Arindam , Sarkar Tanima , Biswas Ranu , Atanase Leonard Ionut , Carauleanu Alexandru
Published: December 2024

Diabetes is a widespread metabolic illness. Mismanagement of diabetes can lead to severe complications that tremendously impact patients’ quality of life. The assimilation of nanotechnology in diabetes care holds the potential to revolutionize treatment paradigms, improve patient outcomes, and reduce the economic burden associated with this pervasive disease. This manuscript explores the multifaceted utilization of nanomaterials in diabetes care, emphasizing the unique features of nano-based medication delivery methods and smart drug delivery mechanisms. Additionally, this paper talks about research on nanocarrier-integrated oral, transdermal, and inhalable insulin delivery; dendrimer- and nanocarrier-coupled antisense oligonucleotide-driven gene therapy; the implementation of gold nanoparticles and quantum dots for glucose surveillance; and nucleic acid therapies. There are certain restrictions when using medication delivery methods that are commonly available to handle diabetes. In order to increase efficacy and safety, the rapidly developing science of nanotechnology is also being explored and employed in medical biology. Nanomaterials like liposomes, dendrimers, niosomes, polymeric and metallic nanocarriers, and solid lipid nanoparticles are among the nanocarriers that have been developed for better delivery of various oral hypoglycemic agents in comparison to conventional therapies. These nanocarriers provide great control over elevated blood glucose levels, making them one of the most intriguing and promising technologies available today. Furthermore, adding additional ligands to nanocarriers allows for more focused distribution while protecting the encapsulated hypoglycemic drugs.
Pharmacokinetic Interaction Between Olaparib and Regorafenib in an Animal Model
Authors: Szkutnik-Fiedler Danuta , Karbownik Agnieszka , Otto Filip , Maciejewska Julia , Kuźnik Alicja , Grabowski Tomasz , Wolc Anna , Grześkowiak Edmund , Stanisławiak-Rudowicz Joanna , Szałek Edyta
Published: December 2024

Background: Olaparib (OLA) and regorafenib (REG) are metabolized by the CYP3A4 isoenzyme of cytochrome P450. Both drugs are also substrates and inhibitors of the membrane transporters P-glycoprotein and BCRP. Therefore, the potential concomitant use of OLA and REG may result in clinically relevant drug–drug interactions. Knowledge of the influence of membrane transporters and cytochrome P450 enzymes on the pharmacokinetics of drugs makes it possible to assess their impact on the efficacy and safety of therapy. Purpose: The study aimed to evaluate the bilateral pharmacokinetic interactions of OLA and REG and its active metabolites after a single administration in healthy rats. Methods: The study was performed in male Wistar rats (n = 24) randomly divided into three groups: one study group, IREG+OLA (n = 8), received REG with OLA, and two control groups, IIREG (n = 8) and IIIOLA (n = 8), received REG and OLA, respectively. The concentrations of OLA, REG, REG-N-oxide (M-2), and N-desmethyl-REG-N-oxide (M-5) were determined by ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). The values of the pharmacokinetic parameters of OLA, REG, M-2, and M-5 were determined by non-compartmental analysis with linear interpolation. Results: After OLA administration, the pharmacokinetic parameters of REG (AUC0–∞, tmax, and t0.5) increased significantly by 3.38-, 2.66-, and 1.82-fold, respectively. On the other hand, REG elimination parameters, i.e., kel and Cl/F, were significantly reduced in the study group by 1.77- and 1.70-fold, respectively. In the study group, Cmax and AUC0–t values were also 7.22- and 8.86-fold higher for M-2 and 16.32- and 17.83-fold higher for M-5, respectively. The Metabolite M-2/Parent and Metabolite M-5/Parent ratios for Cmax and AUC0–t increased by 6.52-, 10.74-, 28-, and 13-fold, respectively. After administration of OLA with REG, the Cmax, AUC0–t, and AUC0–∞ of OLA increased by 2.0-, 3.4-, and 3.4-fold, respectively, compared to the control group. Meanwhile, Cl/F and Vd/F of OLA were significantly decreased in the presence of REG. Conclusions: OLA was shown to significantly affect the pharmacokinetics of REG and its active metabolites M-2 and M-5 in rats after co-administration of both drugs. There was also a significant effect of REG on the pharmacokinetics of OLA, which may have clinical relevance. The AUC ratios (study group/control group) were 3.41 and 3.39 for REG and OLA, respectively, indicating that REG and OLA were moderate inhibitors in this preclinical study. The results obtained need to be confirmed in clinical studies. This study may provide guidance on the safety of using both drugs in clinical practice.
Vegetal Delights: The Phytopoetics of Ross Gay
Authors: Jacobs Joela
Published: December 2024

This article explores the poetics at work in Black American poet Ross Gay’s contemporary two-volume Book of Delights (2019 and 2023). I argue that his delights are phytopoetic, which describes moments when plants impact the human imagination and, by extension, shape human culture and aesthetic production, such as literary texts. Such phytopoetic processes are moments of co-creation, involving plants both as engaged in poietic making and in the shaping of the poetics of a given text. By examining patterns of form in Gay’s prose and close reading some of his delights that center on plants, this article unfolds Gay’s specific phytopoetics and shows that the delights are a genre that operates on plant time: seasonal, cyclical, and rooted in growth. As such, the genre slows down the reader and draws attention to the delight found in small, everyday encounters with plants and the world around us, even in the midst of overwhelming crises.
Determination of the XUV Frequency Chirp at the Free-Electron Laser FLASH via THz Streaking and Electron Beam Diagnostics
Authors: Bidhendi Mahdi M. , Goetzke Gesa , Bermudez Macias Ivette J. , Ivanov Rosen , Schneidmiller Evgeny A. , Mirian Najmeh , Düsterer Stefan
Published: December 2024

Free-electron lasers (FELs) operating in the extreme ultraviolet (XUV) and X-ray regions deliver ultrashort pulses with unprecedented intensity, enabling groundbreaking research across various scientific disciplines. A potential chirp (frequency change within the pulse) of these pulses influences their spectral properties, directly impacting the experimental outcomes and FEL performance. The accurate characterization of the chirp is, therefore, important for optimizing FEL operation and interpreting experimental results. This study presents a comprehensive comparison of two techniques determining the chirp of the XUV pulses at FLASH by directly measuring the XUV pulses with THz streaking and by detecting the chirp of the electron bunches by a Transverse Deflection Structure (PolariX TDS) to infer the XUV chirp. We conducted simultaneous measurements using both techniques at FLASH2 while tuning the FEL to produce various energy chirps on the electron bunch.
Multidisciplinary Laser Facility Driven by New-Generation High-Repetition Laser
Authors: Vaz Gonçalo , Alves Joana , Hariton Victor , João Celso P. , Marques João , Cristino David , Gomes Hugo , Priebe Cara , Pokorny Petr , Santos Maria P. , Pires Hugo , Figueira Gonçalo
Published: December 2024

For many years, high-power laser technology has been divided between industrial applications, which prioritize higher average powers and repetition rates, and academic research, which focuses on achieving higher peak powers and ultrashort pulse durations. The introduction of Yb-doped crystals in laser technology has paved the way for a new generation of laser sources that bridge the gap between industrial and academic requirements, combining high average power with ultrashort pulse capabilities. These advancements enable the integration of compact, adaptable front-end stages, making such lasers versatile for scientific applications. In Lisbon, the Laboratory of Intense Lasers leverages this technology with a system that combines commercial and custom-built front-end stages to enhance operational flexibility. In this paper, we present the current status of this facility and outline upcoming upgrades. We also showcase applications enabled by these high-power laser sources, including semiconductor studies, bi-photonics, and time-resolved spectroscopy.
Low-Molecular-Weight Organic Acid as an Alternative to Promote the Rooting of Persimmon Rootstock Shoot Cuttings
Authors: Geng Jingjing , Zhang Chi , Deng Shaoning , Liu Bowei , Cheng Mengye , An Xiuhong , Wang Hongxia , Wang Wenjiang
Published: December 2024

Organic acids are naturally present in plants and exert a positive influence on plant development, which justifies surveying their potential effect on adventitious root (AR) formation. In this study, 0.0298 mol/L (4000 mg/L) of malic acid and 0.0267 mol/L (4000 mg/L) of tartaric acid were used to explore the effects of low-molecular-weight organic acid on the rooting of persimmon rootstock Diospyros lotus L. during cutting propagation. After organic acid treatment, the rooting percentage and the survival rate significantly increased, accompanied by a greater development of lateral roots. Anatomical analysis revealed that Diospyros lotus L. exhibits characteristics that induce root primordia, and organic acid treatment can enhance the differentiation of root primordia. Furthermore, treatment with organic acid led to a substantial decrease in soluble sugar and starch contents, along with a slight increase in soluble protein content during early cutting stages. Additionally, the indole-3-acetic acid (IAA) content peaked in the early stages of AR formation and was significantly higher than that of the control, while abscisic acid (ABA) levels exhibited the opposite trend. Comparatively, gibberellic acid (GA3) remained at extremely low levels throughout the rooting process in the organic acid groups compared to the control. In conclusion, the current study uncovers the anatomical structure over time during AR formation, revealing the dynamic changes in the related main nutrients and hormones and providing new ideas and a new practical approach for improving root regeneration in persimmon rootstock cuttings.
Adaptive Strategy of the Perennial Halophyte Grass Puccinellia tenuiflora to Long-Term Salinity Stress
Authors: Han Lei , Gao Zhanwu , Li Luhao , Li Changyou , Yan Houxing , Xiao Binbin , Ma Yimeng , Wang Huan , Yang Chunwu , Xun Hongwei
Published: December 2024

Salinity stress influences plants throughout their entire life cycle. However, little is known about the response of plants to long-term salinity stress (LSS). In this study, Puccinellia tenuiflora, a perennial halophyte grass, was exposed to 300 mM NaCl for two years (completely randomized experiment design with three biological replicates). We measured the photosynthetic parameters and plant hormones and employed a widely targeted metabolomics approach to quantify metabolites. Our results revealed that LSS induced significant metabolic changes in P. tenuiflora, inhibiting the accumulation of 11 organic acids in the leaves and 24 organic acids in the roots and enhancing the accumulation of 15 flavonoids in the leaves and 11 phenolamides in the roots. The elevated accumulation of the flavonoids and phenolamides increased the ability of P. tenuiflora to scavenge reactive oxygen species. A comparative analysis with short-term salinity stress revealed that the specific responses to long-term salinity stress (LSS) included enhanced flavonoid accumulation and reduced amino acid accumulation, which contributed to the adaptation of P. tenuiflora to LSS. LSS upregulated the levels of abscisic acid in the leaves and ACC (a direct precursor of ethylene) in the roots, while it downregulated the levels of cytokinins and jasmonic acids in both the organs. These tolerance-associated changes in plant hormones would be expected to reprogram the energy allocation among growth, pathogen defense, and salinity stress response. We propose that abscisic acid, ethylene, cytokinins, and jasmonic acids may interact with each other to construct a salinity stress response network during the adaptation of P. tenuiflora to LSS, which mediates salinity stress response and significant metabolic changes. Our results provided novel insights into the plant hormone-regulated metabolic response of the plants under LSS, which can enhance our understanding of plant salinity tolerance.
Physiological and Biochemical Responses of Pseudocereals with C3 and C4 Photosynthetic Metabolism in an Environment with Elevated CO2
Authors: Silva Bruna Evelyn Paschoal , Pires Stefânia Nunes , Teixeira Sheila Bigolin , Lucho Simone Ribeiro , Fagundes Natan da Silva , Centeno Larissa Herter , Carlos Filipe Selau , de Souza Fernanda Reolon , Avila Luis Antonio de , Deuner Sidnei
Published: December 2024

The present work aimed to investigate the effect of increasing CO2 concentration on the growth, productivity, grain quality, and biochemical changes in quinoa and amaranth plants. An experiment was conducted in open chambers (OTCs) to evaluate the responses of these species to different levels of CO2 {a[CO2] = 400 ± 50 μmol mol−1 CO2 for ambient CO2 concentration, e[CO2] = 700 ± 50 μmol mol−1 CO2 for the elevated CO2 concentration}. Growth parameters and photosynthetic pigments reflected changes in gas exchange, saccharolytic enzymes, and carbohydrate metabolism when plants were grown under e[CO2]. Furthermore, both species maintained most of the parameters related to gas exchange, demonstrating that the antioxidant system was efficient in supporting the primary metabolism of plants under e[CO2] conditions. Both species were taller and had longer roots and a greater dry weight of roots and shoots when under e[CO2]. On the other hand, the panicle was shorter under the same situation, indicating that the plants invested energy, nutrients, and all mechanisms in their growth to mitigate stress in expense of yield. This led to a reduction on panicle size and, ultimately, reducing quinoa grain yield. Although e[CO2] altered the plant’s metabolic parameters for amaranth, the plants managed to maintain their development without affecting grain yield. Protein levels in grains were reduced in both species under e[CO2] in the average of two harvests. Therefore, for amaranth, the increase in CO2 mainly contributes to lowering the protein content of the grains. As for quinoa, its yield performance is also affected, in addition to its protein content. These findings provide new insights into how plants C3 (amaranth) and C4 (quinoa) respond to e[CO2], significantly increasing photosynthesis and its growth but ultimately reducing yield for quinoa and protein content in both species. This result ultimately underscore the critical need to breed plants that can adapt to e[CO2] as means to mitigate its negative effects and to ensure sustainable and nutritious crop production in future environmental conditions.
Comparative Study on Polyelectrolyte Complex Formation of Chitosan and Pectin or PEMA: Effects of Molecular Weight and Mixing Speed
Authors: Boughanmi Rahma , Oelmann Marina , Steinbach Christine , Schwarz Simona
Published: December 2024

Polyelectrolyte complexes (PECs) have gained increasing attention in recent decades due to their importance in various applications, such as water treatment and paper processing. These complexes are formed by mixtures of polycations (n+) and polyanions (n−), known as polyelectrolytes (PEs). In this study, a series of PECs were prepared with different molar charge ratios (n−/n+) using biopolymers such as chitosan (lch) and pectin (p) at pH 5, in addition to the synthetic polymer poly(ethylene alt maleic acid) (PEMA) at the same pH. Two types of chitosan—low molecular weight chitosan (lch) and high molecular weight chitosan (hch)—were used as polycations, and these were mixed with two types of pectin with either a high esterification degree (hp) or a low esterification degree (lp), as well as PEMA as polyanions. These components interacted via electrostatic forces to form the following PEC combinations: (lch&lp), (lch&hp), (hch&hp), and (lch&PEMA). The charge density, turbidity, and particle size of the formed PECs were examined to evaluate the influence of molecular weight and mixing speed on the formation process.
Bacterial Cellulose Purification with Non-Conventional, Biodegradable Surfactants
Authors: Nikbakht Alireza , van Zyl Elizabeth M. , Larson Stephen , Fenlon Sawyer , Coburn Jeannine M.
Published: December 2024

Bacterial cellulose (BC) is a versatile biopolymer with significant potential across biomedical, food, and industrial applications. To remove bacterial contaminants, such as protein and DNA, BC pellicles undergo purification, which traditionally relies on harsh alkali treatments, such as sodium hydroxide or strong surfactants, which present environmental concerns. In response, this study evaluates the efficacy of various non-conventional surfactants—both non-biodegradable and biodegradable—as alternatives for BC purification. Among the surfactants tested, sodium cocoyl isethionate (SCI), a mild anionic and biodegradable surfactant, emerged as particularly effective, achieving an 80.7% reduction in protein content and a 65.19% reduction in double-stranded DNA (dsDNA) content relative to untreated samples. However, these advantages were not without additional challenges, such as the appearance of residual surfactants. Given SCI’s promising performance and biodegradability, it was further examined in two-step treatment protocols; additionally, sodium dodecyl sulfate (SDS) was also examined as a more traditional anionic surfactant as well as NaOH. For the two-step treatment protocol, BC pellicles were treated with one reagent for 3 h, followed by a second reagent for an additional 3 h. Notably, by using NaOH as the final step in the two-step treatment protocol, residual surfactant was not detected in the FTIR analysis. Overall, this work demonstrates that SCI, in addition to subsequent NaOH treatment, can be used as a surfactant-based approach for BC purification, representing a potential environmentally friendly alternative to traditional surfactant-based approaches for BC purification.
Multi-Target Irregular Behavior Recognition of Chemical Laboratory Personnel Based on Improved DeepSORT Method
Authors: Duan Yunhuai , Li Zhenhua , Shi Bin
Published: December 2024

The lack of safety awareness and the irregular behavior of chemical laboratory personnel are major contributors to laboratory accidents which pose significant risks to both the safety of laboratory environments and the efficiency of laboratory work. These issues can lead to accidents, equipment damage, and jeopardize personnel health. To address this challenge, this study proposes a method for recognizing irregular behavior in laboratory personnel by utilizing an improved DeepSORT algorithm tailored to the specific characteristics of a chemical laboratory setting. The method first extracts skeletal keypoints from laboratory personnel using the Lightweight OpenPose algorithm to locate individuals. The enhanced DeepSORT algorithm tracks human targets and detects the positions of the relevant objects. Finally, an SKPT-LSTM network was employed to integrate tracking data for behavior recognition. This approach was designed to enhance the detection and prevention of unsafe behaviors in chemical laboratories. The experimental results on a self-constructed dataset demonstrate that the proposed method accurately identifies irregular behaviors, thereby contributing to the reduction in safety risks in laboratory environments.
Optimal Air Flow Modeling in Real Healthcare Facilities for Quick Removal of Contaminated Air
Authors: Altwijri Omar , Javed Ravish , Algabri Yousif A. , Fakhouri Abdulaziz , Alqarni Khaled , Altamimi Reema , Alqahtani Sarah , Almijalli Mohammed , Saad Ali
Published: December 2024

Background: Contaminated air can have a negative impact on patient recovery, leading to longer hospital stays, higher healthcare costs, and even death. Objective: Our study focuses on improving indoor air quality for patient recovery in healthcare facilities. Methods: We conducted computational analysis using the finite element modeling (FEM) technique to investigate the flow of contaminated air exhaled by a patient. Distinct models were examined: a neonatal intensive care unit (NICU) with two-beds and a coronavirus isolation room (CIR). Using ANSYS, we designed models using actual and real specifications of both NICUs and IRs from local hospitals. We determined the optimal dimensions and locations of outlet vents in NICUs and CIRs using simulations with ANSYS software drawing on our designed modeling of air flow. Outlet vent dimensions and locations were modified to achieve optimal air flow for quickly venting out contaminated air from a patient in a room. Results: The results show a substantial improvement in directly venting out the contaminated air from the patient. Conclusions: It can be concluded that the optimal design of outlet vent locations and dimensions using ANSYS simulation results in finding the optimal path for the quick removal of contaminated air flow from the patient in an NICU and CIR.
Annealing Temperature Effect on the Properties of CoCe Thin Films Prepared by Magnetron Sputtering at Si(100) and Glass Substrates
Authors: Lin Shih-Hung , Chang Yung-Huang , Huang Yu-Jie , Chen Yuan-Tsung , Dong Shu-Huan
Published: December 2024

This study explores cobalt–cerium (Co90Ce10) thin films deposited on silicon (Si) (100) and glass substrates via direct current (DC) magnetron sputtering, with thicknesses from 10 nanometer (nm) to 50 nm. Post-deposition annealing treatments, conducted from 100 °C to 300 °C, resulted in significant changes in surface roughness, surface energy, and magnetic domain size, demonstrating the potential to tune magnetic properties via thermal processing. The films exhibited hydrophilic behavior, with thinner films showing a stronger substrate effect, crucial for surface engineering in device fabrication. Increased film thickness reduced transmittance due to photon signal inhibition and light scattering, important for optimizing optical devices. Furthermore, the reduction in sheet resistance and resistivity with increasing thickness and heat treatment highlights the significance of these parameters in optimizing the electrical properties for practical applications.
Electron-Beam-Evaporated Nickel Oxide Thin Films for Application as a Hole Transport Layer in Photovoltaics
Authors: Hossain Mohammad Istiaque , Aissa Brahim
Published: December 2024

We present the growth of nickel oxide (NiO) thin films as a hole transport material in photovoltaic devices using the e-beam evaporation technique. The metal oxide layers were reactively deposited at a substrate temperature of 200 °C using an electron beam evaporator under an oxygen atmosphere. The oxide films reactively grown through electron-beam evaporation were optimized for carrier transport layers. Optical and structural characterizations were performed using ultraviolet–visible (UV–Vis) spectrometry, X-ray diffraction, contact angle measurements, scanning electron microscopy, and Hall effect measurements. The study of these films confirmed that the NiO layer is a suitable candidate for use as a hole transport layer based on Hall effect measurements. A morphological study using field-emission scanning electron microscopy confirmed the growth of compact, uniform, and defect-free metal oxide layers. Contact angle measurements revealed that the films possessed semi-hydrophilic properties, contributing to improved stability by repelling water from their surfaces. The stoichiometry of the films was influenced by the oxygen pressure during deposition, which affected both their morphological and optical features. The NiO films exhibited a transmittance exceeding 80% in the visible spectrum. These findings highlight the potential applications of such nickel oxide films as hole transport material layers.
Implementation of an Improved 100 CMM Regenerative Thermal Oxidizer to Reduce VOCs Gas
Authors: Park Hoon-Min , Jung Hyun-Min , Lee Dae-Hee , Park Hei-Na , Lim Tae-Young , Yoon Jong-Hwa , Yoon Dal-Hwan
Published: December 2024

In this paper, an improved 100 CMM regenerative thermal oxidizer (RTO) is implemented for low-emission combustion. The existing RTO system is a cylindrical drum structure that cyclically introduces and discharges VOC gas into and from the rotating disk, and which achieves excellent energy efficiency with a heat recovery rate of more than 95%. However, the drive shaft designed under the RTO combustion chamber increases wear around the rotating shaft due to the load of the combustion chamber and there is a problem that the untreated gas is simultaneously released through the outlet due to the channeling phenomenon of the combustion chamber and the drive shaft. In addition, the combustion chamber, used at a high temperature of 800 °C, may cause serious problems such as rotation stop or explosion due to pollutants, dust accumulation, and thermal expansion in the chamber. Particularly when treating VOCs harmful gasses, RTO performance may be degraded due to the burner’s non-uniform temperature control and unstable combustion function. To solve this problem, first, the design of the combustion chamber rotating plate driving device is improved. Second, when treating high concentration VOC gas, the design of combustion chamber considers a temperature increase of up to 920 °C or more. For this, the diameter of the gas burner is 125 mm and the outlet dimension is set to 650 mm × 650 mm to effectively discharge high-temperature waste heat. Third, the heat storage material in the combustion chamber is composed of a ceramic block with a thickness of 250 mm, and the outer diameter and height of the combustion chamber are set to, 2530 mm and 1875 mm, respectively, to optimize gas residence time and heat insulation thickness. Fourth, we supplement safe operation by applying the trip control algorithm of the programmable logic controller (PLC) panel for failure prediction of RTO and the Edge-IoT-based intelligent algorithm for this. Finally, we evaluate the economic performance of 100 CMM RTO by conducting empirical experiments to analyze changes in VOCs removal efficiency, nitrogen oxide emission concentration, and total hydrocarbon (THC) concentration through 10 CMM design and implementation.
Study on Soil Freeze–Thaw and Surface Deformation Patterns in the Qilian Mountains Alpine Permafrost Region Using SBAS-InSAR Technique
Authors: Xue Zelong , Zhao Shangmin , Zhang Bin
Published: December 2024

The Qilian Mountains, located on the northeastern edge of the Qinghai–Tibet Plateau, are characterized by unique high-altitude and cold-climate terrain, where permafrost and seasonally frozen ground are extensively distributed. In recent years, with global warming and increasing precipitation on the Qinghai–Tibet Plateau, permafrost degradation has become severe, further exacerbating the fragility of the ecological environment. Therefore, timely research on surface deformation and the freeze–thaw patterns of alpine permafrost in the Qilian Mountains is imperative. This study employs Sentinel-1A SAR data and the SBAS-InSAR technique to monitor surface deformation in the alpine permafrost regions of the Qilian Mountains from 2017 to 2023. A method for spatiotemporal interpolation of ascending and descending orbit results is proposed to calculate two-dimensional surface deformation fields further. Moreover, by constructing a dynamic periodic deformation model, the study more accurately summarizes the regular changes in permafrost freeze–thaw and the trends in seasonal deformation amplitudes. The results indicate that the surface deformation time series in both vertical and east–west directions obtained using this method show significant improvements in accuracy over the initial data, allowing for a more precise reflection of the dynamic processes of surface deformation in the study area. Subsidence is predominant in permafrost areas, while uplift mainly occurs in seasonally frozen ground areas near lakes and streams. The average vertical deformation rate is 1.56 mm/a, with seasonal amplitudes reaching 35 mm. Topographical (elevation; slope gradient; aspect) and climatic factors (temperature; soil moisture; precipitation) play key roles in deformation patterns. The deformation of permafrost follows five distinct phases: summer thawing; warm-season stability; frost heave; winter cooling; and spring thawing. This study enhances our understanding of permafrost deformation characteristics in high-latitude and high-altitude regions, providing a reference for preventing geological disasters in the Qinghai–Tibet Plateau area and offering theoretical guidance for regional ecological environmental protection and infrastructure safety.
Evaluation of Soil Moisture Retrievals from a Portable L-Band Microwave Radiometer
Authors: Zhang Runze , Nayak Abhi , Houtz Derek , Watts Adam , Soltanaghai Elahe , Alipour Mohamad
Published: December 2024

A novel Portable L-band radiometer (PoLRa), compatible with tower-, vehicle- and drone-based platforms, can provide gridded soil moisture estimations from a few meters to several hundred meters yet its retrieval accuracy has rarely been examined. This study aims to provide an initial assessment of the performance of PoLRa-derived soil moisture at a spatial resolution of approximately 0.7 m × 0.7 m at a set of sampling pixels in central Illinois, USA. This preliminary evaluation focuses on (1) the consistency of PoLRa-measured brightness temperatures from different viewing directions over the same area and (2) whether PoLRa-derived soil moisture retrievals are within an acceptable accuracy range. As PoLRa shares many aspects of the L-band radiometer onboard NASA’s Soil Moisture Active Passive (SMAP) mission, two SMAP operational algorithms and the conventional dual-channel algorithm (DCA) were applied to calculate volumetric soil moisture from the measured brightness temperatures. The vertically polarized brightness temperatures from the PoLRa are typically more stable than their horizontally polarized counterparts across all four directions. In each test period, the standard deviations of observed dual-polarization brightness temperatures are generally less than 5 K. By comparing PoLRa-based soil moisture retrievals against the simultaneous moisture values obtained by a handheld capacitance probe, the unbiased root mean square error (ubRMSE) and the Pearson correlation coefficient (R) are mostly below 0.05 m3/m3 and above 0.7 for various algorithms adopted here. While SMAP models and the DCA algorithm can derive soil moisture from PoLRa observations, no single algorithm consistently outperforms the others. These findings highlight the significant potential of ground- or drone-based PoLRa measurements as a standalone reference for the calibration and validation of spaceborne L-band synthetic aperture radars and radiometers. The accuracy of PoLRa-yielded high-resolution soil moisture can be further improved via standardized operational procedures and appropriate tau-omega parameters.
Evolution Characteristics and Risk Assessment on Nonpoint Source Pollution in the Weihe River Basin, China
Authors: Lyu Jiqiang , Zhang Haihao , Huang Yuanjia , Bai Chunyu , Yang Yuhao , Shi Junlin , Yang Zhizhou , Wang Yan , Zhou Zhaohui , Luo Pingping , Jiao Meng , Huo Aidi
Published: December 2024

Temporal and spatial changes in non-point source pollution, driven by significant alterations in land use due to increased human activity, have considerably affected the quality of groundwater, surface water, and soil environments in the region. This study examines the Weihe River basin in greater detail, an area heavily impacted by human activity. The study developed the River Section Potential Pollution Index (R-PPI) model using the Potential Non-Point Source Pollution Index (PNPI) model in order to investigate the dynamic changes in River Section Potential Pollution (R-PP) over a 31-year period and its associated risks, especially those related to land use and land cover change (LUCC). The predominant land uses in the Weihe River Basin are cropland, grassland, and forest, making up around 97% of the basin’s total area. The Weihe River Basin underwent a number of soil and water conservation initiatives between 1990 and 2020, which significantly decreased the potential pollution risk in the river segment. The research separated the R-PP risk values in the area into five different categories using a quantile classification technique. According to the data, there is a polarization of R-PP risk in the area, with downstream parts especially having an increased risk of pollution in river segments impacted by human activity. On the other hand, river segments in the middle and upper reaches of the basin showed a discernible decline in possible pollution risk throughout the study period. The Weihe River Basin’s rapid urbanization and land degradation are to blame for the current increase in R-PP risk. The substantial influence of LUCC on the dynamic variations in R-PP risk in the Weihe River Basin is highlighted by this study. Additionally, it offers crucial information for upcoming conservation initiatives and urban planning guidelines meant to enhance the area’s ecological well-being and environmental standards.
Comparison Between Thermal-Image-Based and Model-Based Indices to Detect the Impact of Soil Drought on Tree Canopy Temperature in Urban Environments
Authors: Asawa Takashi , Oshio Haruki , Yoshino Yumiko
Published: December 2024

This study aimed to determine whether canopy and air temperature difference (ΔT) as an existing simple normalizing index can be used to detect an increase in canopy temperature induced by soil drought in urban parks, regardless of the unique energy balance and three-dimensional (3D) structure of urban trees. Specifically, we used a thermal infrared camera to measure the canopy temperature of Zelkova serrata trees and compared the temporal variation of ΔT to that of environmental factors, including solar radiation, wind speed, vapor pressure deficit, and soil water content. Normalization based on a 3D energy-balance model was also performed and used for comparison with ΔT. To represent the 3D structure, a terrestrial light detection and ranging-derived 3D tree model was used as the input spatial data. The temporal variation in ΔT was similar to that of the index derived using the energy-balance model, which considered the 3D structure of trees and 3D radiative transfer, with a correlation coefficient of 0.85. In conclusion, the thermal-image-based ΔT performed comparably to an index based on the 3D energy-balance model and detected the increase in canopy temperature because of the reduction in soil water content for Z. serrata trees in an urban environment.
Multitemporal Monitoring for Cliff Failure Potential Using Close-Range Remote Sensing Techniques at Navagio Beach, Greece
Authors: Konsolaki Aliki , Karantanellis Efstratios , Vassilakis Emmanuel , Kotsi Evelina , Lekkas Efthymios
Published: December 2024

This study aims to address the challenges associated with rockfall assessment and monitoring, focusing on the coastal cliffs of “Navagio Shipwreck Beach” in Zakynthos. A complete time-series analysis was conducted using state-of-the-art methodologies including a 2020 survey using unmanned aerial systems (UASs) and two subsequent surveys, incorporating terrestrial laser scanning (TLS) and UAS survey techniques in 2023. Achieving high precision and accuracy in georeferencing involving direct georeferencing, the utilization of pseudo ground control points (pGCPs), and integrating post-processing kinematics (PPK) with global navigation satellite system (GNSS) permanent stations’ RINEX data is necessary for co-registering the multitemporal models effectively. For the change detection analysis, UAS surveys were utilized, employing the multiscale model-to-model cloud comparison (M3C2) algorithm, while TLS data were used in a validation methodology due to their very high-resolution model. The synergy of these advanced technologies and methodologies offers a comprehensive understanding of rockfall dynamics, aiding in effective assessment and monitoring strategies for coastal cliffs prone to rockfall risk.
An Ultrasensitive Ethanol Gas Sensor Based on a Dual-Nanoparticle In2O3/SnO2 Composite
Authors: Zhang Cheng , Zhang Ze , Tian Yao , Yu Lingmin , Wang Hairong
Published: December 2024

As a VOC, ethanol can be found in human exhaled breath, and its concentration can be used as a biomarker of human liver disease. To detect trace-level concentrations of ethanol, an ultrasensitive ethanol sensor was developed based on a dual-nanoparticle In2O3/SnO2 composite that was prepared by hydrothermal synthesis, and its suspension was dipped on a flat electrode to form a gas sensor. The nanocomposite was characterized by an SEM (scanning electron microscope), XRD (X-ray diffraction), and a TEM (transmission electron microscope), and the nanoparticle structure was observed. The experimental results showed that gas sensors based on the In2O3/SnO2 nanocomposite had higher responses compared to sensors based on pure In2O3. Among the nanocomposites, the one with a In2O3-to-SnO2 mol ratio of 1:8 was used in the sensor with the highest response of 1.41 to 100 ppb ethanol at 150 °C, which also exhibited good repeatability. The ultrasensitive response to ethanol can be attributed to the faster electron migration rate and the increase in oxygen-absorbing sites caused by the n-n heterojunction in the nanocomposite. Due to its low detection limit, good repeatability, and relatively high responses in high humidity, this sensor has a potential application in exhaled breath detection.
Type-2 Neutrosophic Markov Chain Model for Subject-Independent Sign Language Recognition: A New Uncertainty–Aware Soft Sensor Paradigm
Authors: Al-Saidi Muslem , Ballagi Áron , Hassen Oday Ali , Saad Saad
Published: December 2024

Uncertainty-aware soft sensors in sign language recognition (SLR) integrate methods to quantify and manage the uncertainty in their predictions. This is particularly crucial in SLR due to the variability in sign language gestures and differences in individual signing styles. Managing uncertainty allows the system to handle variations in signing styles, lighting conditions, and occlusions more effectively. While current techniques for handling uncertainty in SLR systems offer significant benefits in terms of improved accuracy and robustness, they also come with notable disadvantages. High computational complexity, data dependency, scalability issues, sensor and environmental limitations, and real-time constraints all pose significant hurdles. The aim of the work is to develop and evaluate a Type-2 Neutrosophic Hidden Markov Model (HMM) for SLR that leverages the advanced uncertainty handling capabilities of Type-2 neutrosophic sets. In the suggested soft sensor model, the Foot of Uncertainty (FOU) allows Type-2 Neutrosophic HMMs to represent uncertainty as intervals, capturing the range of possible values for truth, falsity, and indeterminacy. This is especially useful in SLR, where gestures can be ambiguous or imprecise. This enhances the model’s ability to manage complex uncertainties in sign language gestures and mitigate issues related to model drift. The FOU provides a measure of confidence for each recognition result by indicating the range of uncertainty. By effectively addressing uncertainty and enhancing subject independence, the model can be integrated into real-life applications, improving interactions, learning, and accessibility for the hearing-impaired. Examples such as assistive devices, educational tools, and customer service automation highlight its transformative potential. The experimental evaluation demonstrates the superiority of the Type-2 Neutrosophic HMM over the Type-1 Neutrosophic HMM in terms of accuracy for SLR. Specifically, the Type-2 Neutrosophic HMM consistently outperforms its Type-1 counterpart across various test scenarios, achieving an average accuracy improvement of 10%.
A One-Dimensional Depthwise Separable Convolutional Neural Network for Bearing Fault Diagnosis Implemented on FPGA
Authors: Liang Yu-Pei , Chen Hao , Chung Ching-Che
Published: December 2024

This paper presents a hardware implementation of a one-dimensional convolutional neural network using depthwise separable convolution (DSC) on the VC707 FPGA development board. The design processes the one-dimensional rolling bearing current signal dataset provided by Paderborn University (PU), employing minimal preprocessing to maximize the comprehensiveness of feature extraction. To address the high parameter demands commonly associated with convolutional neural networks (CNNs), the model incorporates DSC, significantly reducing computational complexity and parameter load. Additionally, the DoReFa-Net quantization method is applied to compress network parameters and activation function outputs, thereby minimizing memory usage. The quantized DSC model requires approximately 22 KB of storage and performs 1,203,128 floating-point operations in total. The implementation achieves a power consumption of 527 mW at a clock frequency of 50 MHz, while delivering a fault diagnosis accuracy of 96.12%.
An Efficient Acoustic Camera Simulator for Robotic Applications: Design, Implementation, and Validation
Authors: Park Jisung
Published: December 2024

As forward-looking imaging sonar, also called an acoustic camera, has emerged as an important sensor for marine robotics applications, its simulators have attracted considerable research attention within the field. This paper presents an acoustic camera simulator that efficiently generates acoustic images using only the depth information of the scene. The simulator approximates the acoustic beam of a real acoustic camera as a set of acoustic rays originating from the center of the acoustic camera. A simplified active sonar model and error models for the acoustic rays are incorporated to account for the environmental factors which can affect the rays. The simulator is implemented in the Gazebo simulator, a robotic simulator, and does not rely on any other components except depth rendering. To evaluate the performance of the developed simulator, qualitative and quantitative comparisons were conducted between simulated images and actual acoustic images obtained in a test tank.
Spatiotemporal Multivariate Weather Prediction Network Based on CNN-Transformer
Authors: Wu Ruowu , Liang Yandan , Lin Lianlei , Zhang Zongwei
Published: December 2024

Weather prediction is of great significance for human daily production activities, global extreme climate prediction, and environmental protection of the Earth. However, the existing data-based weather prediction methods cannot adequately capture the spatial and temporal evolution characteristics of the target region, which makes it difficult for the existing methods to meet practical application requirements in terms of efficiency and accuracy. Changes in weather involve both strongly correlated spatial and temporal continuation relationships, and at the same time, the variables interact with each other, so capturing the dynamic correlations among space, time, and variables is particularly important for accurate weather prediction. Therefore, we designed a spatiotemporal coupled prediction network based on convolution and Transformer for weather prediction from the perspective of multivariate spatiotemporal fields. First, we designed a spatial attention encoder-decoder to comprehensively explore spatial representations for extracting and reconstructing spatial features. Then, we designed a multi-scale spatiotemporal evolution module to obtain the spatiotemporal evolution patterns of weather using inter- and intra-frame computations. After that, in order to ensure that the model has better prediction ability for global and local hotspot areas, we designed a composite loss function based on MSE and SSIM to focus on the global and structural distribution of weather to achieve more accurate multivariate weather prediction. Finally, we demonstrated the excellent effect of STWPM in multivariate spatiotemporal field weather prediction by comprehensively evaluating the proposed algorithm with classical algorithms on the ERA5 dataset in a global region.
A Weather-Adaptive Convolutional Neural Network Framework for Better License Plate Detection
Authors: Saha Utsha , Saha Binita , Imran Md Ashique
Published: December 2024

Automatic License Plate Recognition (ALPR) systems are essential for Intelligent Transport Systems (ITS), effective transportation management, security, law enforcement, etc. However, the performance of ALPR systems can be significantly affected by environmental conditions such as heavy rain, fog, and pollution. This paper introduces a weather-adaptive Convolutional Neural Network (CNN) framework that leverages the YOLOv10 model that is designed to enhance license plate detection in adverse weather conditions. By incorporating weather-specific data augmentation techniques, our framework improves the robustness of ALPR systems under diverse environmental scenarios. We evaluate the effectiveness of this approach using metrics such as precision, recall, F1, mAP50, and mAP50-95 score across various model configurations and augmentation strategies. The results demonstrate a significant improvement in overall detection performance, particularly in challenging weather conditions. This study provides a promising solution for deploying resilient ALPR systems in regions with similar environmental complexities.
An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival
Authors: Kanwal Saima , Abdullah Muhammad , Kumar Sahil , Arshad Saqib , Shahroz Muhammad , Zhang Dawei , Kumar Dileep
Published: December 2024

Smart fish farming faces critical challenges in achieving comprehensive automation, real-time decision-making, and adaptability to diverse environmental conditions and multi-species aquaculture. This study presents a novel Internet of Things (IoT)-driven intelligent decision-making system that dynamically monitors and optimizes water quality parameters to enhance fish survival rates across various regions and species setups. The system integrates advanced sensors connected to an ESP32 microcontroller, continuously monitoring key water parameters such as pH, temperature, and turbidity which are increasingly affected by climate-induced variability. A custom-built dataset comprising 43,459 records, covering ten distinct fish species across diverse pond environments, was meticulously curated. The data were stored as a comma-separated values (CSV) file on the IoT cloud platform ThingSpeak and synchronized with Firebase, enabling seamless remote access, control, and real-time updates. Advanced machine learning techniques, with feature transformation and balancing, were applied to preprocess the dataset, which includes water quality metrics and species-specific parameters. Multiple algorithms were trained and evaluated, with the Decision Tree classifier emerging as the optimal model, achieving remarkable performance metrics: 99.8% accuracy, precision, recall, and F1-score, a 99.6% Matthews Correlation Coefficient (MCC), and the highest Area Under the Curve (AUC) score for multi-class classification. Our framework’s capability to manage complex, multi-species fishpond environments was validated across diverse setups, showcasing its potential to transform fish farming practices by ensuring sustainable climate-adaptive management through real-time water quality optimization. This study marks a significant step forward in climate-smart aquaculture, contributing to enhanced fish health, survival, and yield while mitigating the risks posed by climate change on aquatic ecosystems.