bluuebunny/crossref_metadata_2025 huggingface dataset:
Leveraging Community Pharmacies to Address Social Needs: A Promising Practice to Improve Healthcare Quality
Authors: Kuo Tony , Barragan Noel C. , Chen Steven
Published: September 2024

Emerging research suggests that chronic conditions such as cardiovascular disease, diabetes, and asthma are often mediated by adverse social conditions that complicate their management. These conditions include circumstances such as lack of affordable housing, food insecurity, barriers to safe and reliable transportation, structural racism, and unequal access to healthcare or higher education. Although health systems cannot independently solve these problems, their infrastructure, funding resources, and well-trained workforce can be realigned to better address social needs created by them. For example, community pharmacies and the professionals they employ can be utilized and are well-positioned to deliver balanced, individualized clinical services, with a focus on the whole person. Because they have deep roots and presence in the community, especially in under-resourced neighborhoods, community pharmacies (independent and chain) represent local entities that community members recognize and trust. In this article, we provide case examples from California, United States, to illustrate and explore how community pharmacies can be leveraged to address patient social needs as part of their core responsibilities and overall strategy to improve healthcare quality.
Temperature Dependence and the Effects of Ultraviolet Radiation on the Ultrastructure and Photosynthetic Activity of Carpospores in Sub-Antarctic Red Alga Iridaea cordata (Turner) Bory 1826
Authors: Navarro Nelso P. , Huovinen Pirjo , Jofre Jocelyn , Gómez Iván
Published: September 2024

The short-term effects of UV radiation and low temperature on ultrastructure, photosynthetic activity (measured as the maximal photochemical quantum yield of photosystem II: Fv/Fm), chlorophyll-a (Chl-a) contents, and UV-absorbing compounds on the carpospores of Iridaea cordata from a sub-Antarctic population were investigated. Exposure to both photosynthetically active radiation (PAR) and PAR + UV for 4 h caused ultrastructural modifications in all treatments. Under PAR + UV at 2 °C, a disruption of the chloroplast’s internal organization was observed. Plastoglobuli were often found in carpospores exposed to 2 °C. ‘Electron dense particles’, resembling physodes of brown algae, were detected for the first time in cells exposed to PAR and PAR + UV at 8 °C. Fv/Fm decreased following 4 h exposure at 2 °C under PAR + UV (64%) and PAR (25%). At 8 °C, Fv/Fm declined by 21% only under PAR + UV. The photosynthesis of carpospores previously treated with UV partially recovered after a 4 h exposure under dim light. UV-absorbing compounds were degraded in all radiation and temperature treatments without recovery after a 4 h dim light period. Chl-a did not change, whereas total carotenoids increased under PAR at 8 °C The study indicates that although carpospores of I. cordata exhibit photoprotective mechanisms, UV radiation strongly damages their ultrastructure and physiology, which were exacerbated under low temperatures.
Challenges of Salinity Intrusion and Drought Stress on Olive Tree Cultivation on Mljet Island
Authors: Tadić Josip , Dumičić Gvozden , Veršić Bratinčević Maja , Vitko Sandra , Radić Brkanac Sandra
Published: September 2024

Understanding genotype-specific responses to environmental stressors is vital for developing resilience strategies that ensure sustainable olive cultivation and productivity. In this work, cultivar ‘Oblica’ and several olive genotypes from the island of Mljet (Croatia) were exposed to short-term (21 days) salinity and drought treatments. In contrast to other olive genotypes, genotype M29 as well as cultivar ‘Oblica’ managed to maintain growth and chlorophyll a levels under salinity stress to the same level as the control. Drought, however, significantly reduced the growth parameters in all olive trees. Cultivar ‘Oblica’ accumulated the greatest amount of Na+ ions in the leaves compared to olive genotypes from the island of Mljet, demonstrating superior resistance by translocating Na+ to leaf vacuoles. The observed reduction in K+ content in the roots of olive trees under all treatments suggests a generalized stress response. On the other hand, effective Ca2+ uptake has been identified as a crucial energy-saving strategy that olive trees use to cope with brief periods of salinity and drought. The proline content and activities of superoxide dismutase (SOD) and guaiacol peroxidase (GPOX) varied among the olive trees, highlighting the importance of antioxidative capacities and stress adaptation mechanisms. According to the obtained results, stress-resistant olive genotypes like ‘Oblica’ and M29 show potential for breeding resilient varieties.
Defense Responses Induced by Viral Movement Protein and Its Nuclear Localization Modulate Virus Cell-to-Cell Transport
Authors: Atabekova Anastasia K. , Lazareva Ekaterina A. , Lezzhov Alexander A. , Golyshev Sergei A. , Skulachev Boris I. , Morozov Sergey Y. , Solovyev Andrey G.
Published: September 2024

Movement proteins (MPs) encoded by plant viruses are essential for cell-to-cell transport of viral genomes through plasmodesmata. The genome of hibiscus green spot virus contains a module of two MP genes termed ‘binary movement block’ (BMB), encoding the proteins BMB1 and BMB2. Here, BMB1 is shown to induce a defense response in Nicotiana benthamiana plants that inhibits BMB-dependent virus transport. This response is characterized by the accumulation of reactive oxygen species, callose deposition in the cell wall, and upregulation of 9-LOX expression. However, the BMB1-induced response is inhibited by coexpression with BMB2. Furthermore, BMB1 is found to localize to subnuclear structures, in particular to Cajal bodies, in addition to the cytoplasm. As shown in experiments with a BMB1 mutant, the localization of BMB1 to nuclear substructures enhances BMB-dependent virus transport. Thus, the virus transport mediated by BMB proteins is modulated by (i) a BMB1-induced defense response that inhibits transport, (ii) suppression of the BMB1-induced response by BMB2, and (iii) the nuclear localization of BMB1 that promotes virus transport. Collectively, the data presented demonstrate multiple levels of interactions between viral pathogens and their plant hosts during virus cell-to-cell transport.
The Potential of Helichsryum splendidum (Thunb.) Less. for the Restoration of Sites Polluted with Coal Fly Ash
Authors: Munyengabe Alexis , Kamogelo Ledwaba Samuel , Ngmenzuma Titus Yeliku-ang , Banda Maria Fezile
Published: September 2024

The disposal of coal fly ash (CFA) generated from coal-fired power stations has serious impact on the ecosystem, by converting large pieces of land to barren ash dams with the potential to contaminate groundwater, surface water, air and soil. The aim of this study was to clarify the potential of phytoremediation using Helichrysum splendidum (Thunb.) Less. in areas polluted by CFA through conduction of pot trial experiments for 14 weeks. Plants of the same age were cultivated in CFA to assess their growth, photosynthetic rate and tolerance towards metal toxicity. This study revealed that the CFA was moderately polluted with heavy metals, and a lower photosynthetic rate was recorded for the CFA plants in comparison to the controls (plants grown in soil). Although the CO2 assimilation rate was lower for the CFA plants, increased growth was recorded for all the plants tested. Inductively coupled plasma mass spectrometry (ICP-MS) was used to quantify the amount of trace elements in samples and parameters including translocation factor (TF) and bioconcentration factor (BCF) were used to evaluate the phytoremediation potential of H. splendidum (Thunb.) Less. The results revealed that higher concentrations of Cd, Co, Cr, Cu, Mn and Pb were accumulated in the roots, while As, Ni and Zn were found in the shoots. Elements including As, Cr and Zn reported TF values above 1, indicating the plants’ phytoextraction potential. The BCF values for As, Cu and Zn were 1.22, 1.19 and 1.03, indicating effectiveness in the phytostabilization processes. A removal rate efficiency ranging from 18.0 to 56.7% was recorded confirming that, H. splendidum (Thunb.) Less. can be employed for restoration of CFA dams.
CaZingipain2 Acts Positively in Pepper (Capsicum annuum L.) Immunity against R. solanacearum
Authors: Wu Ruijie , Wu Zhen , Qing Yalin , Duan Chenfeng , Guo Yiling , Zhang Xujing , Huang Ronghua , He Shuilin , Qiu Ailian
Published: September 2024

Bacterial wilt caused by Ralstonia solanacearum is one of the most important diseases in solanaceous plants, including peppers. It generally tends to be more serious under warm−temperature and moist (WM) conditions than at moist room−temperature (RM) conditions. Although immunity mechanisms at room temperature have been intensively studied, the mechanisms underlying WM conditions remain poorly understood. Herein, the pepper cysteine protease CaZingipain2 was expressed and functionally characterized in pepper immunity against R. solanacearum at WM conditions and at room temperature. The results showed that CaZingipain2 localized to the nucleus and was upregulated at the transcript level in pepper plants upon R. solanacearum infection under WM conditions (RSWM). Virus−induced gene silencing of CaZingipain2 significantly increased the susceptibility of pepper plants to RSWM, and was coupled with the downregulation of CaPRP1 and CaMgst3, which are specifically related to pepper immunity against RSWM, according to our previous studies, while its overexpression significantly reduced the susceptibility of N. benethamiana plants to RSWM compared to that of wild−type plants. In addition, our data showed that CaZingipain2 also acts positively in pepper immunity against R. solanacearum infection at room temperature by upregulating the SA− and JA−responsive PR genes, including CaNPR1 and CaDEF1. All these results indicate that CaZingipain2 improves pepper immunity against R. solanacearum under WM conditions and at room temperature by regulating different PR genes.
A Plant Strategy: Irrigation, Nitrogen Fertilization, and Climatic Conditions Regulated the Carbon Allocation and Yield of Oilseed Flax in Semi-Arid Area
Authors: Wang Haidi , Zhao Bangqing , Gao Yuhong , Yan Bin , Wu Bing , Cui Zhengjun , Wang Yifan , Wen Ming , Ma Xingkang
Published: September 2024

The injudicious use of water and fertilizer to maximize crop yield not only leads to environmental pollution, but also causes enormous economic losses. For this reason, we investigated the effect of nitrogen (N) (N0 (0), N60 (60 kg ha−1), and N120 (120 kg ha−1)) at different irrigation levels (I0 (0), I1200 (budding 600 m3 ha−1 + kernel 600 m3 ha−1), and I1800 (budding 900 m3 ha−1 + kernel 900 m3 ha−1)) on oilseed flax in the Loess Plateau of China in 2019 and 2020. The objective was to establish appropriate irrigation and fertilizer management strategies that enhance the grain yield (GY) of oilseed flax and maximize water and N productivity. The results demonstrated that irrigation and N application and their coupling effects promoted dry matter accumulation (DMA) and non-structural carbohydrate (NSC) synthesis, and increased the GY of oilseed flax. The contents of NSC in various organs of flax were closely related to grain yield and yield components. Higher NSC in stems was conducive to increased sink capacity (effective capsule number per plant (EC) and thousand kernel weight (TKW)), and the coupling of irrigation and N affected GY by promoting NSC synthesis. Higher GY was obtained by the interaction of irrigation and N fertilizer, with the increase rate ranging from 15.84% to 35.40%. Additionally, in the increased yield of oilseed flax, 39.70–78.06%, 14.49–54.11%, and −10.6–24.93% were contributed by the application of irrigation and nitrogen and the interaction of irrigation and nitrogen (I × N), respectively. Irrigation was the main factor for increasing the GY of oilseed flax. In addition, different climatic conditions changed the contribution of irrigation and N and their interaction to yield increase in oilseed flax. Drought and low temperature induced soluble sugar (SS) and starch (ST) synthesis to resist an unfavorable environment, respectively. The structural equation model showed that the key factors to increasing the GY of oilseed flax by irrigation and nitrogen fertilization were the differential increases in DMA, EC, and TKW. The increases in EC and TKW were attributed to the promotion of DMA and NSC synthesis in oilseed flax organs by irrigation, nitrogen fertilization, and their coupling effects. The I1200N60 treatment obtained higher water use efficiency (WUE) and N partial factor productivity (NPFP) due to lower actual evapotranspiration (ETa) and lower N application rate. Therefore, the strategy of 1200 m3 ha−1 irrigation and 60 kg ha−1 N application is recommended for oilseed flax in semi-arid and similar areas to achieve high grain yield and efficient use of resources.
Diverging Elevational Patterns of Tree vs. Epiphyte Species Density, Beta Diversity, and Biomass in a Tropical Dry Forest
Authors: Werner Florian A. , Homeier Jürgen
Published: September 2024

There is evidence to suggest that vascular epiphytes experience low competition for resources (light, water, and nutrients) compared to terrestrial plants. We tested the hypothesis that low resource competition may lead to higher nestedness among vascular epiphyte assemblages compared to trees. We studied the species composition and biomass of epiphytes and trees along an elevation gradient in a tropical dry forest in SW Ecuador. Both life-forms were inventoried on 25 plots of 400 m2 across five elevation levels (550–1250 m). Tree species density and total species richness increased with elevation, whereas basal area and biomass did not show significant trends. Epiphyte species density and richness both increased strongly with elevation, in parallel to biomass. Plot-level compositional changes were similarly strong for both life-forms. We attribute elevational increases in the species richness of trees and epiphytes to increasing humidity, i.e., more mesic growth conditions. We attribute the more pronounced elevational increase in epiphyte biomass, species density, and richness—the latter coupled with a higher degree of nestedness—to the greater moisture dependency of epiphytes and relatively low direct competition for resources. Our study provides a first comparison of elevational trends in epiphyte and tree diversity and biomass for a tropical dry forest.
Automatic Disease Detection from Strawberry Leaf Based on Improved YOLOv8
Authors: He Yuelong , Peng Yunfeng , Wei Chuyong , Zheng Yuda , Yang Changcai , Zou Tengyue
Published: September 2024

Strawberries are susceptible to various diseases during their growth, and leaves may show signs of diseases as a response. Given that these diseases generate yield loss and compromise the quality of strawberries, timely detection is imperative. To automatically identify diseases in strawberry leaves, a KTD-YOLOv8 model is introduced to enhance both accuracy and speed. The KernelWarehouse convolution is employed to replace the traditional component in the backbone of the YOLOv8 to reduce the computational complexity. In addition, the Triplet Attention mechanism is added to fully extract and fuse multi-scale features. Furthermore, a parameter-sharing diverse branch block (DBB) sharing head is constructed to improve the model’s target processing ability at different spatial scales and increase its accuracy without adding too much calculation. The experimental results show that, compared with the original YOLOv8, the proposed KTD-YOLOv8 increases the average accuracy by 2.8% and reduces the floating-point calculation by 38.5%. It provides a new option to guide the intelligent plant monitoring system and precision pesticide spraying system during the growth of strawberry plants.
Efficacy and Safety of Poly-l-Lactic Acid in Facial Aesthetics: A Systematic Review
Authors: Signori Roberta , Barbosa Antony de Paula , Cezar-dos-Santos Fernando , Carbone Ana Claudia , Ventura Silvio , Nobre Bryanne Brissian de Souza , Neves Maria Luiza Boechat Borges , Câmara-Souza Mariana Barbosa , Poluha Rodrigo Lorenzi , De la Torre Canales Giancarlo
Published: September 2024

The primary objective of this systematic review study was to investigate the effectiveness, durability, and adverse events of PLLA treatment for aesthetic indications. The search strategy was performed in MEDLINE (Ovid). The electronic literature search of five databases was performed, from the inception of the databases until the 12th of February 2024. This was to identify randomized clinical trials that assessed PLLA treatment in adult individuals exhibiting facial aging and/or facial lipoatrophy. Risk of bias was assessed using the Cochrane Risk-of-Bias Tool for Randomized Trials (RoB 2). Eleven RCTs out of 1467 identified citations were included. Four studies showed increased dermal thickness, significant improvement in facial lipoatrophy severity and aesthetic clinical scores, after PLLA treatment with its effects sustained for at least 25 months. Two studies demonstrated the superiority of PLLA over injectable human collagen. Also, three studies showed positive results favoring PLLA when compared with PH gel in lipoatrophy severity, transepidermal water loss, skin quality, elasticity, and patient satisfaction. All adverse events were mild-to-moderate in intensity, and the main ones worth noting were bruising, hematoma, tenderness, nodules, and edema. Five out of eleven studies were considered having high risk of bias. The evidence on the effectiveness and safety of PLLA for facial rejuvenation is of low quality; thus, the reported high effectiveness, safety, and long-lasting effects for this purpose should be further investigated.
An Additive Manufacturing MicroFactory: Overcoming Brittle Material Failure and Improving Product Performance through Tablet Micro-Structure Control for an Immediate Release Dose Form
Authors: Prasad Elke , Robertson John , Halbert Gavin W.
Published: September 2024

Additive manufacturing of pharmaceutical formulations offers advanced micro-structure control of oral solid dose (OSD) forms targeting not only customised dosing of an active pharmaceutical ingredient (API) but also custom-made drug release profiles. Traditionally, material extrusion 3D printing manufacturing was performed in a two-step manufacturing process via an intermediate feedstock filament. This process was often limited in the material space due to unsuitable (brittle) material properties, which required additional time to develop complex formulations to overcome. The objective of this study was to develop an additive manufacturing MicroFactory process to produce an immediate release (IR) OSD form containing 250 mg of mefenamic acid (MFA) with consistent drug release. In this study, we present a single-step additive manufacturing process employing a novel, filament-free melt extrusion 3D printer, the MicroFactory, to successfully print a previously ‘non-printable’ brittle Soluplus®-based formulation of MFA, resulting in targeted IR dissolution profiles. The physico-chemical properties of 3D printed MFA-Soluplus®-D-sorbitol formulation was characterised by thermal analysis, Fourier Transform Infrared spectroscopy (FTIR), and X-ray Diffraction Powder (XRPD) analysis, confirming the crystalline state of mefenamic acid as polymorphic form I. Oscillatory temperature and frequency rheology sweeps were related to the processability of the formulation in the MicroFactory. 3D printed, micro-structure controlled, OSDs showed good uniformity of mass and content and exhibited an IR profile with good consistency. Fitting a mathematical model to the dissolution data correlated rate parameters and release exponents with tablet porosity. This study illustrates how additive manufacturing via melt extrusion using this MicroFactory not only streamlines the manufacturing process (one-step vs. two-step) but also enables the processing of (brittle) pharmaceutical immediate-release polymers/polymer formulations, improving and facilitating targeted in vitro drug dissolution profiles.
Monolithic Polyepoxide Membranes for Nanofiltration Applications and Sustainable Membrane Manufacture
Authors: Anderson Mackenzie Babetta , Danna Riley A. , French Clayton , Wu Jishan , Thiel Markus N. , Yang Zhiyin , Hoek Eric M. V. , Kaner Richard B.
Published: September 2024

The present work details the development of carbon fiber-reinforced epoxy membranes with excellent rejection of small-molecule dyes. It is a proof-of-concept for a more sustainable membrane design incorporating carbon fibers, and their recycling and reuse. 4,4′-methylenebis(cyclohexylamine) (MBCHA) polymerized with either bisphenol-A-diglycidyl ether (BADGE) or tetraphenolethane tetraglycidylether (EPON Resin 1031) in polyethylene glycol (PEG) were used to make monolithic membranes reinforced by nonwoven carbon fibers. Membrane pore sizes were tuned by adjusting the molecular weight of the PEG used in the initial polymerization. Membranes made of BADGE-MBCHA showed rejection of Rose Bengal approaching 100%, while tuning the pore sizes substantially increased the rejection of Methylene Blue from ~65% to nearly 100%. The membrane with the best permselectivity was made of EPON-MBCHA polymerized in PEG 300. It has an average DI flux of 4.48 LMH/bar and an average rejection of 99.6% and 99.8% for Rose Bengal and Methylene Blue dyes, respectively. Degradation in 1.1 M sodium hypochlorite enabled the retrieval of the carbon fiber from the epoxy matrix, suggesting that the monolithic membranes could be recycled to retrieve high-value products rather than downcycled for incineration or used as a lower selectivity membrane. The mechanism for epoxy degradation is hypothesized to be part chemical and part physical due to intense swelling stress leading to erosion that leaves behind undamaged carbon fibers. The retrieved fibers were successfully used to make another membrane exhibiting similar performance to those made with pristine fibers.
Exploring Alloy Composition Dynamics: Thermodynamic Analysis of Fe-Al-Si-Cr System in Homogeneous Liquid State
Authors: Shabanov Yerbol , Zhumagaliyev Yerlan , Nurgali Nurzhan , Dossekenov Murat , Almuratova Karlyga , Orynbassar Raigul , Kainenova Tursyngul , Bakirova Botagoz , Kanapiyeva Fatima , Zhunussova Elvira
Published: September 2024

This study employs thermodynamic-diagram analysis to investigate component ratios within the Fe-Al-Si-Cr system, focusing on the behavior of homogeneous liquid states. Through comprehensive modeling, a phase diagram is constructed, elucidating the interplay of iron, aluminum, silicon, and chromium components. This study identifies stable elementary tetrahedra within the system, providing insights into phase compositions and distribution. Key findings reveal the significance of tetrahedral geometry in understanding and optimizing alloy compositions, particularly in the context of complex chromium alloys. This research underscores the utility of thermodynamic analysis in advancing our understanding of alloy systems and facilitating the optimization of production processes.
Model-Free Adaptive Sliding Mode Control Scheme Based on DESO and Its Automation Application
Authors: Wei Xiaohua , Sui Zhen , Peng Hanzhou , Xu Feng , Xu Jianliang , Wang Yulong
Published: September 2024

This paper addresses a class of uncertain nonlinear systems with disturbances that are challenging to model by proposing a novel model-free adaptive sliding mode control (MFASMC) scheme based on a discrete-time extended state observer (DESO). Initially, leveraging the pseudo partial derivative (PPD) concept in the model-free adaptive control (MFAC) framework, the discrete-time nonlinear model is converted into a full-form dynamic linearization (FFDL) model. Secondly, using the FFDL data model, a discrete sliding mode controller is designed. A discrete integral sliding mode surface is chosen to mitigate chattering during the reaching phase, and a hyperbolic tangent function with minimal slope variation is selected for smoother switching control. Furthermore, a DESO is designed to estimate uncertainties in the discrete system, enabling real-time compensation for the controller. Finally, a genetic optimization algorithm is employed for parameter tuning to minimize the time cost associated with selecting control parameters. The design process of this scheme relies solely on the data of the controlled system, without depending on a mathematical model. The proposed DESO-MFASMC scheme is tested through simulations using a typical numerical equation and the existing EFG-BC/320 electric heavy-duty forklift from the Quzhou Special Equipment Inspection Center. Simulation results show that the proposed method is significantly superior to the traditional MFAC and PID control methods in tracking accuracy and robustness when dealing with nonlinear disturbance of the system. The DESO-MFASMC scheme proposed in this paper not only shows its advantages in theory but also verifies its effectiveness and practicability in engineering through practical application.
Enhanced Bearing Fault Diagnosis in NC Machine Tools Using Dual-Stream CNN with Vibration Signal Analysis
Authors: Ni Zhen , Tong Yifei , Song Yixuan , Wang Ruikang
Published: September 2024

Numerically controlled (NC) machine tools, as vital production equipment in manufacturing, have been widely applied across various sectors and have become a core competitive advantage for enterprises in the global market. Therefore, ensuring the normal and efficient operation of NC machine tool groups and promptly diagnosing faults have become critical concerns for many enterprises and scholars today. This paper focuses on bearing fault diagnosis, utilizing the vibration signals from the Case Western Reserve University Bearing Data Center as the input dataset. This study constructed a dual-stream convolutional neural network (CNN) fault diagnosis model, where the first stream processes one-dimensional vibration signal spectra and the second stream handles two-dimensional time-frequency maps derived from the same signals. The model uniquely integrates convolutional attention mechanisms to enhance feature extraction along with dropout algorithms and batch normalization to prevent overfitting and improve training stability. The proposed approach enables a comprehensive learning of both temporal and spatial features, effectively identifying bearing faults with high accuracy. The model’s performance was validated against this widely recognized dataset, demonstrating superior accuracy compared to traditional methods.
The Influence of the Structure of Organochlorine Compounds on Their Decomposition Process in a Dielectric Barrier Discharge
Authors: Ulejczyk Bogdan
Published: September 2024

The decomposition efficiency of C2HCl3 and CHCl3 in a barrier discharge is very different, even though these compounds differ little in chemical composition. In both compounds, there are three chlorine atoms and one hydrogen atom. The difference between them is the presence of one carbon atom in CHCl3 and two carbon atoms connected by a double bond in C2HCl3 and the higher polarizability of C2HCl3. The polarizability of C2HCl3 is 10.21 Å3 and that of CHCl3 is 8.39 Å3. As a result of these differences, the C2HCl3 conversion was two to three times higher than the CHCl3 conversion. The main product of CHCl3 decomposition containing chlorine was ClO2, while Cl2, COCl2, HCl, CCl4, and Cl− were formed in smaller amounts. The main products of C2HCl3 decomposition, which contain chlorine, were COCl2, HCl, and Cl−. CCl4 was not formed. Cl2 and ClO2 were formed in smaller amounts. Pathways of C2HCl3 and CHCl3 decomposition are shown in this paper. The process was carried out at low power (0.2–0.8 W) in air. The gas flow was 10 L/h, and the concentration of the decomposed compound was 0.4%. The volume of the gas space of the reactor (plasma zone) was 27 cm3.
The Adventure of a Book That Migrated from Shirwān to Istanbul: A Study of Ḥadīth Terminology Presented to Sultan Mehmet the Conqueror
Authors: Akbaş Mustafa Yasin
Published: September 2024

The science and religion policies of the states affected the types of scholars, the understanding of science, the centres of science and the styles of teaching in the regions they dominated. While Timur made Samarkand and his grandson Ulugh Beg made Herat centres of knowledge, they tried to attract scholars to these cities. This was done by forcing the ulema to emigrate or by increasing the opportunities available to them. The Ottoman Empire, which was a candidate for the role of the central Muslim state, invited scholars to the cities under its rule, especially Istanbul. During the reign of Sultan Mehmet the Conqueror (1451–1481), one of the pioneers of this activity, many scholars came to Istanbul. As a result, renowned scholars in medicine, astronomy, mathematics and religious sciences; books in these fields; and their understanding of knowledge were transferred to the Ottoman Empire. This article analyses the still extant manuscript of the ḥadīth methodology book Qawāʻid al-usūl fī ‘ilm ḥādīth al-Rasūl, which Ibrāhīm b. ʿAlī al-Shirwānī brought to Istanbul during the reign of Fatih and presented to the Sultan. The analysis examines the method and content of the work, whether it is an original book or not and the comparison of the information contained in it with similar books, taking into account the status of the science of ḥadīth in Istanbul and the Ottoman Empire. In particular, it questions the Ottoman political approach to the reception of religious sciences and the impact of this book on Ottoman ḥadīth scholarship, as the Ottoman Empire patronised knowledge and scholars from other regions through migration.
The Reconstruction of FY-4A and FY-4B Cloudless Top-of-Atmosphere Radiation and Full-Coverage Particulate Matter Products Reveals the Influence of Meteorological Factors in Pollution Events
Authors: Song Zhihao , Zhao Lin , Ye Qia , Ren Yuxiang , Chen Ruming , Chen Bin
Published: September 2024

By utilizing top-of-atmosphere radiation (TOAR) data from China’s new generation of geostationary satellites (FY-4A and FY-4B) along with interpretable machine learning models, near-surface particulate matter concentrations in China were estimated, achieving hourly temporal resolution, 4 km spatial resolution, and 100% spatial coverage. First, the cloudless TOAR data were matched and modeled with the solar radiation products from the ERA5 dataset to construct and estimate a fully covered TOAR dataset under assumed clear-sky conditions, which increased coverage from 20–30% to 100%. Subsequently, this dataset was applied to estimate particulate matter. The analysis demonstrated that the fully covered TOAR dataset (R2 = 0.83) performed better than the original cloudless dataset (R2 = 0.76). Additionally, using feature importance scores and SHAP values, the impact of meteorological factors and air mass trajectories on the increase in PM10 and PM2.5 during dust events were investigated. The analysis of haze events indicated that the main meteorological factors driving changes in particulate matter included air pressure, temperature, and boundary layer height. The particulate matter concentration products obtained using fully covered TOAR data exhibit high coverage and high spatiotemporal resolution. Combined with data-driven interpretable machine learning, they can effectively reveal the influencing factors of particulate matter in China.
A Space Non-Cooperative Target Recognition Method for Multi-Satellite Cooperative Observation Systems
Authors: Zhang Yue , Wang Jianyuan , Chen Jinbao , Shi Donghao , Chen Xiaotong
Published: September 2024

Space non-cooperative target recognition is crucial for on-orbit servicing. Multi-satellite cooperation has great potential for broadening the observation scope and enhancing identification efficiency. However, there is currently a lack of research on recognition methods tailored for multi-satellite cooperative observation. In this paper, we propose a novel space non-cooperative target recognition method to identify satellites and debris in images from multi-satellite observations. Firstly, we design an image-stitching algorithm to generate space-wide-area images. Secondly, we propose a two-stage multi-target detection model, a lighter CNN model with distance merge threshold (LCNN-DMT). Specifically, in the first stage, we propose a novel foreground extraction model based on a minimum bounding rectangle with the threshold for distance merging (MBRT-D) to address redundant detection box extraction for satellite components. Then, in the second stage, we propose an improved SqueezeNet model by introducing separable convolution and attention mechanisms for target classification. Moreover, due to the absence of a public multi-target detection dataset containing satellites and debris, we construct two space datasets by introducing a randomized data augmentation strategy. Further experiments demonstrate that our method can achieve high-precision image stitching and superior recognition performance. Our LCNN-DMT model outperforms mainstream algorithms in target localization accuracy with only 0.928 M parameters and 0.464 GFLOPs, making it ideal for on-orbit deployment.
Research on Multiscale Atmospheric Chaos Based on Infrared Remote-Sensing and Reanalysis Data
Authors: Wang Zhong , Sun Shengli , Xu Wenjun , Chen Rui , Ma Yijun , Liu Gaorui
Published: September 2024

The atmosphere is a complex nonlinear system, with the information of its temperature, water vapor, pressure, and cloud being crucial aspects of remote-sensing data analysis. There exist intricate interactions among these internal components, such as convection, radiation, and humidity exchange. Atmospheric phenomena span multiple spatial and temporal scales, from small-scale thunderstorms to large-scale events like El Niño. The dynamic interactions across different scales, along with external disturbances to the atmospheric system, such as variations in solar radiation and Earth surface conditions, contribute to the chaotic nature of the atmosphere, making long-term predictions challenging. Grasping the intrinsic chaotic dynamics is essential for advancing atmospheric analysis, which holds profound implications for enhancing meteorological forecasts, mitigating disaster risks, and safeguarding ecological systems. To validate the chaotic nature of the atmosphere, this paper reviewed the definitions and main features of chaotic systems, elucidated the method of phase space reconstruction centered on Takens’ theorem, and categorized the qualitative and quantitative methods for determining the chaotic nature of time series data. Among quantitative methods, the Wolf method is used to calculate the Largest Lyapunov Exponents, while the G–P method is used to calculate the correlation dimensions. A new method named Improved Saturated Correlation Dimension method was proposed to address the subjectivity and noise sensitivity inherent in the traditional G–P method. Subsequently, the Largest Lyapunov Exponents and saturated correlation dimensions were utilized to conduct a quantitative analysis of FY-4A and Himawari-8 remote-sensing infrared observation data, and ERA5 reanalysis data. For both short-term remote-sensing data and long-term reanalysis data, the results showed that more than 99.91% of the regional points have corresponding sequences with positive Largest Lyapunov exponents and all the regional points have correlation dimensions that tended to saturate at values greater than 1 with increasing embedding dimensions, thereby proving that the atmospheric system exhibits chaotic properties on both short and long temporal scales, with extreme sensitivity to initial conditions. This conclusion provided a theoretical foundation for the short-term prediction of atmospheric infrared radiation field variables and the detection of weak, time-sensitive signals in complex atmospheric environments.
Himawari-8 Sea Surface Temperature Products from the Australian Bureau of Meteorology
Authors: Govekar Pallavi , Griffin Christopher , Embury Owen , Mittaz Jonathan , Beggs Helen Mary , Merchant Christopher J.
Published: September 2024

As a contribution to the Integrated Marine Observing System (IMOS), the Bureau of Meteorology introduces new reprocessed Himawari-8 satellite-derived Sea Surface Temperature (SST) products. The Radiative Transfer Model and a Bayesian cloud clearing method is used to retrieve SSTs every 10 min from the geostationary satellite Himawari-8. An empirical Sensor Specific Error Statistics (SSES) model, introduced herein, is applied to calculate bias and standard deviation for the retrieved SSTs. The SST retrieval and compositing method, along with validation results, are discussed. The monthly statistics for comparisons of Himawari-8 Level 2 Product (L2P) skin SST against in situ SST quality monitoring (iQuam) in situ SST datasets, adjusted for thermal stratification, showed a mean bias of −0.2/−0.1 K and a standard deviation of 0.4–0.7 K for daytime/night-time after bias correction, where satellite zenith angles were less than 60° and the quality level was greater than 2. For ease of use, these native resolution SST data have been composited using a method introduced herein that retains retrieved measurements, to hourly, 4-hourly and daily SST products, and projected onto the rectangular IMOS 0.02 degree grid. On average, 4-hourly products cover ≈10% more of the IMOS domain, while one-night composites cover ≈25% more of the IMOS domain than a typical 1 h composite. All available Himawari-8 data have been reprocessed for the September 2015–December 2022 period. The 10 min temporal resolution of the newly developed Himawari-8 SST data enables a daily composite with enhanced spatial coverage, effectively filling in SST gaps caused by transient clouds occlusion. Anticipated benefits of the new Himawari-8 products include enhanced data quality for applications like IMOS OceanCurrent and investigations into marine thermal stress, marine heatwaves, and ocean upwelling in near-coastal regions.
Assessment of Low-Cost and Higher-End Soil Moisture Sensors across Various Moisture Ranges and Soil Textures
Authors: Nandi Rajesh , Shrestha Dev
Published: September 2024

The accuracy and unit cost of sensors are important factors for a continuous soil moisture monitoring system. This study compares the accuracy of four soil moisture sensors differing in unit costs in coarse-, fine-, and medium-textured soils. The sensor outputs were recorded for the VWC, ranging from 0% to 50%. Low-cost capacitive and resistive sensors were evaluated with and without the external 16-bit analog-to-digital converter ADS1115 to improve their performances without adding much cost. Without ADS1115, using only Arduino’s built-in analog-to-digital converter, the low-cost sensors had a maximum RMSE of 4.79% (v/v) for resistive sensors and 3.78% for capacitive sensors in medium-textured soil. The addition of ADS1115 showed improved performance of the low-cost sensors, with a maximum RMSE of 2.64% for resistive sensors and 1.87% for capacitive sensors. The higher-end sensors had an RMSE of up to 1.8% for VH400 and up to 0.95% for the 5TM sensor. The RMSE differences between higher-end and low-cost sensors with the use of ADS1115 were not statistically significant.
Applications of Artificial Intelligence for Heat Stress Management in Ruminant Livestock
Authors: Rebez Ebenezer , Sejian Veerasamy , Silpa Mullakkalparambil , Kalaignazhal Gajendirane , Thirunavukkarasu Duraisamy , Devaraj Chinnasamy , Nikhil Kumar , Ninan Jacob , Sahoo Artabandhu , Lacetera Nicola , Dunshea Frank
Published: September 2024

Heat stress impacts ruminant livestock production on varied levels in this alarming climate breakdown scenario. The drastic effects of the global climate change-associated heat stress in ruminant livestock demands constructive evaluation of animal performance bordering on effective monitoring systems. In this climate-smart digital age, adoption of advanced and developing Artificial Intelligence (AI) technologies is gaining traction for efficient heat stress management. AI has widely penetrated the climate sensitive ruminant livestock sector due to its promising and plausible scope in assessing production risks and the climate resilience of ruminant livestock. Significant improvement has been achieved alongside the adoption of novel AI algorithms to evaluate the performance of ruminant livestock. These AI-powered tools have the robustness and competence to expand the evaluation of animal performance and help in minimising the production losses associated with heat stress in ruminant livestock. Advanced heat stress management through automated monitoring of heat stress in ruminant livestock based on behaviour, physiology and animal health responses have been widely accepted due to the evolution of technologies like machine learning (ML), neural networks and deep learning (DL). The AI-enabled tools involving automated data collection, pre-processing, data wrangling, development of appropriate algorithms, and deployment of models assist the livestock producers in decision-making based on real-time monitoring and act as early-stage warning systems to forecast disease dynamics based on prediction models. Due to the convincing performance, precision, and accuracy of AI models, the climate-smart livestock production imbibes AI technologies for scaled use in the successful reducing of heat stress in ruminant livestock, thereby ensuring sustainable livestock production and safeguarding the global economy.
Design and Analysis of a Hand-Held Surgical Forceps with a Force-Holding Function
Authors: Bai Yang , Yu Yang , Xu Zhenbang
Published: September 2024

Physiological hand tremors, twitching, and the nonlinear characteristics of the relationship between surgical forceps clamping force and operating force seriously affect the clamping accuracy of surgical instruments. To address this problem, a new type of surgical forceps with a force-holding function was developed to replace traditional forceps, which was studied in terms of structural design, statics, and dynamics. The overall structure of the surgical forceps was designed based on the lever principle, the kinematic model of the clamping part of the surgical forceps was established by the geometrical method, and the correctness of the kinematic model was verified by ADAMS. To address the clamping accuracy of the surgical forceps, a stress analysis was performed, its dynamics model was established, a finite element simulation was performed, the modal of the forceps was optimized using the Box–Behnken method, and, finally, an experimental platform was built to perform the accuracy test. The results demonstrate that the designed surgical forceps exhibit high clamping accuracy and fulfill the design specifications for surgical operations.
Remotely Powered Two-Wire Cooperative Sensors for Bioimpedance Imaging Wearables
Authors: Chételat Olivier , Rapin Michaël , Bonnal Benjamin , Fivaz André , Sporrer Benjamin , Rosenthal James , Wacker Josias
Published: September 2024

Bioimpedance imaging aims to generate a 3D map of the resistivity and permittivity of biological tissue from multiple impedance channels measured with electrodes applied to the skin. When the electrodes are distributed around the body (for example, by delineating a cross section of the chest or a limb), bioimpedance imaging is called electrical impedance tomography (EIT) and results in functional 2D images. Conventional EIT systems rely on individually cabling each electrode to master electronics in a star configuration. This approach works well for rack-mounted equipment; however, the bulkiness of the cabling is unsuitable for a wearable system. Previously presented cooperative sensors solve this cabling problem using active (dry) electrodes connected via a two-wire parallel bus. The bus can be implemented with two unshielded wires or even two conductive textile layers, thus replacing the cumbersome wiring of the conventional star arrangement. Prior research demonstrated cooperative sensors for measuring bioimpedances, successfully realizing a measurement reference signal, sensor synchronization, and data transfer though still relying on individual batteries to power the sensors. Subsequent research using cooperative sensors for biopotential measurements proposed a method to remove batteries from the sensors and have the central unit supply power over the two-wire bus. Building from our previous research, this paper presents the application of this method to the measurement of bioimpedances. Two different approaches are discussed, one using discrete, commercially available components, and the other with an application-specific integrated circuit (ASIC). The initial experimental results reveal that both approaches are feasible, but the ASIC approach offers advantages for medical safety, as well as lower power consumption and a smaller size.
Hybrid Optimization Path Planning Method for AGV Based on KGWO
Authors: Guo Zhengjiang , Xia Yingkai , Li Jiawei , Liu Jiajun , Xu Kan
Published: September 2024

To address the path planning problem for automated guided vehicles (AGVs) in challenging and complex industrial environments, a hybrid optimization approach is proposed, integrating a Kalman filter with grey wolf optimization (GWO), as well as incorporating partially matched crossover (PMX) mutation operations and roulette wheel selection. Paths are first optimized using GWO, then refined with Kalman filter corrections every ten iterations. Moreover, roulette wheel selection guides robust parent path selection, while an elite strategy and partially matched crossover (PMX) with mutation generate diverse offspring. Extensive simulations and experiments were carried out under a densely packed goods scenario and complex indoor layout scenario, within a fully automated warehouse environment. The results showed that this hybrid method not only enhanced the various optimization metrics but also ensured more predictable and collision-free navigation paths, particularly in environments with complex obstacles. These improvements lead to increased operational efficiency and safety, highlighting the method’s potential in real-world applications.
Experimental Validation of Realistic Measurement Setup for Quantitative UWB-Guided Hyperthermia Temperature Monitoring
Authors: Prokhorova Alexandra , Helbig Marko
Published: September 2024

Hyperthermia induces slight temperature increase of 4–8 °C inside the tumor, making it more responsive to radiation and drugs, thereby improving the outcome of the oncological treatment. To verify the level of heat in the tumor and to avoid damage of the healthy tissue, methods for non-invasive temperature monitoring are needed. Temperature estimation by means of microwave imaging is of great interest among the scientific community. In this paper, we present the results of experiments based on ultra-wideband (UWB) M-sequence technology. Our temperature estimation approach uses temperature dependency of tissue dielectric properties and relation of UWB images to the reflection coefficient on the boundary between tissue types. The realistic measurement setup for neck cancer hyperthermia considers three antenna arrangements. Data are processed with Delay and Sum beamforming and Truncated Singular Value Decomposition. Two types of experiments are presented in this paper. In the first experiment, relative permittivity of subsequently replaced tumor mimicking material is estimated, and in the second experiment, real temperature change in the tumor imitate is monitored. The results showed that the presented approach allows for qualitative as well as quantitative permittivity and temperature estimation. The frequency range for temperature estimation, preferable antenna configurations, and limitations of the method are indicated.