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In the present study, a series of laboratory experiments were conducted to examine the impact of pyrolysis temperature on the outcome yields of waste coconut shells in a fixed bed reactor under varying conditions of pyrolysis temperature, from 400 to 800 °C. The temperature was increased at a stable heating rate of about 10 °C/min, while keeping the sweeping gas (Ar) flow rate constant at about 100 mL/min. The bio-oil was described by Fourier transform infrared spectroscopy (FTIR) investigations and demonstrated to be an exceptionally oxygenated complex mixture. The resulting bio-chars were characterized by elemental analysis and scanning electron microscopy (SEM). The output of bio-char was diminished pointedly, from 33.6% to 28.6%, when the pyrolysis temperature ranged from 400 to 600 °C, respectively. In addition, the bio-chars were carbonized with the expansion of the pyrolysis temperature. Moreover, the remaining bio-char carbons were improved under a stable structure. Experimental results showed that the highest bio-oil yield was acquired at 600 °C, at about 48.7%. The production of gas increased from 15.4 to 18.3 wt.% as the temperature increased from 400 to 800 °C. Additionally, it was observed that temperature played a vital role on the product yield, as well as having a vital effect on the characteristics of waste coconut shell slow-pyrolysis.

Because of its slow rate of disintegration, plastic debris has steadily risen over time and contributed to a host of environmental issues. Recycling the world’s increasing debris has taken on critical importance. Pyrolysis is one of the most practical techniques for recycling plastic because of its intrinsic qualities and environmental friendliness. For scale-up and reactor design, an understanding of the degradation process is essential. Using one model-free kinetic approach (Friedman) and two model-fitting kinetic methods (Arrhenius and Coats-Redfern), the thermal degradation of Polyethylene Terephthalate (PET) microplastics at heating rates of 10, 20, and 30 °C/min was examined in this work. Additionally, a powerful artificial neural network (ANN) model was created to forecast the heat deterioration of PET MPs. At various heating rates, the TG and DTG thermograms from the PET MPs degradation revealed the same patterns and trends. This showed that the heating rates do not impact the decomposition processes. The Friedman model showed activation energy values ranging from 3.31 to 8.79 kJ/mol. The average activation energy value was 1278.88 kJ/mol from the Arrhenius model, while, from the Coats-Redfern model, the average was 1.05 × 104 kJ/mol. The thermodynamics of the degradation process of the PET MPs by thermal treatment were all non-spontaneous and endergonic, and energy was absorbed for the degradation. It was discovered that an ANN, with a two-layer hidden architecture, was the most effective network for predicting the output variable (mass loss%) with a regression coefficient value of (0.951–1.0).

Thermochemical process of biomass is being considered as a latest technique for the restoration of energy source and biochemical products. In this study, the influence of the different heating rates on pyrolysis behaviors and kinetic of jute stick were investigated to justify the waste jute stick biomass as a potential source of bioenergy. Pyrolysis experiments were carried out at four several heating rates of 10, 20, 30 and 40 °C/min, by utilizing the thermogravimetric analyzer (TG-DTA) and a fixed-bed pyrolysis reactor. Two different kinetic methods, Kissinger–Akahira–Sunose (KAS) and Ozawa–Flynn–Wall (OFW) were used to determine the distinct kinetic parameters. The experimental results showed that, the heating rates influenced significantly on the position of TG curve and maximum Tm peaks and highest decomposition rate of the jute stick biomass. Both the highest point of TG and the lowest point of Derivative thermogravimetry (DTG) curves were shifted towards the maximum temperature. However, the heating rates also influenced the products of pyrolysis yield, including bio-char, bio-oil and the non-condensable gases. The average values of activation energy were found to be 139.21 and 135.99 kJ/mol based on FWO and KAS models, respectively.

Cotton is planted on a large scale in China, especially in the Xinjiang Region. A large amount of agricultural waste from cotton plants is produced annually, and currently poses a disposal problem. In this study the product after liquefaction of cotton stalk powder was mixed with diphenylmethane diisocyanate to prepare polyurethane foams. The effects of the liquefaction conditions on the properties of the polyols and polyurethane foams produced using cotton stalk were investigated. The optimal processing conditions for the liquefied product, considering the quality of the polyurethane foams, were studied as a function of the residue fraction. Bio-polyols with promising material properties were produced using liquefaction conditions of 150 °C, reaction time of 90 min, catalyst content of 3 wt.%, and 20 w/w% cotton stalk loading. We investigated the optimal processing conditions for producing bio-foam materials with mechanical properties comparable to those of petroleum-based foam materials. This study demonstrated the potential of cotton stalk agricultural waste for use as a feedstock for producing polyols via liquefaction. It was shown that polyethylene glycol 400 (PEG400) and glycerin can be used as alternative solvents for liquefaction of lignocellulosic biomass, such as cotton stalk, to produce bio-polyol and polyurethane foams.

Ambient particulates of Shanghai with 5-stage particle sizes were firstly determined in spring, 2017. The particles’ mass concentrations were mainly observed in fine particle matter (PM 1.1 ) and coarse particles (diameter > 7.0 μm). Water-soluble ionic contents were also more distributed in PM 1.1 with the great contents of secondary particles (NO 3 − , SO 4 2− , and NH 4 + ). Higher ratios of NO 2 /SO 2 and NO 3 − /SO 4 2− indicated that the vehicle emissions might be made more greater contribution rather than coal combustions to the fine particles. Crustal enrichment factors (EFcs) of trace elements (V, Cr, Ni, Zn, As, Se, Rb, Cd, Pb, and Bi) in PM 1.1 in that called slight air pollution events were always higher than those in that called severe air pollution events and EFcs of Se were up to 2.5 × 10 4 , while EFcs of Pb, Bi, and Cd were over 100. Based on kinds of elemental ratios in PM 1.1 and PM 1.1–2.0 , atmospheric pollutants in Shanghai might be mainly from coal and oil combustions, diesel, and gasoline vehicles. Air masses backward trajectories also showed that the air masses from the northern part of China were one important air pollutant origins, but other ones might be the local sources, such as traffic and industries. Based on carcinogenic risk analysis of PM 2.0 , it was considerable that 12–60 children and 37–87 adults among millions of people living in Shanghai might be attacked by cancer during their lifetime. Moreover, the great carcinogenic risk was also observed according to the high concentrations of elemental Cr and As in PM 1.1 .

The real-time monitoring of animal postures through computer vision techniques has become essential for modern precision livestock management. To overcome the limitations of current behavioral analysis systems in balancing computational efficiency and detection accuracy, this study develops an optimized deep learning framework named YOLOv8-BCD specifically designed for ovine posture recognition. The proposed architecture employs a multi-level lightweight design incorporating enhanced feature fusion mechanisms and spatial-channel attention modules, effectively improving detection performance in complex farm environments with occlusions and variable lighting. Our methodology introduces three technical innovations: (1) Adaptive multi-scale feature aggregation through bidirectional cross-layer connections. (2) Context-aware attention weighting for critical region emphasis. (3) Streamlined detection head optimization for resource-constrained devices. The experimental dataset comprises 1476 annotated images capturing three characteristic postures (standing, lying, and side lying) under practical farming conditions. Comparative evaluations demonstrate significant improvements over baseline models, achieving 91.7% recognition accuracy with 389 FPS processing speed while maintaining 19.2% parameter reduction and 32.1% lower computational load compared to standard YOLOv8. This efficient solution provides technical support for automated health monitoring in intensive livestock production systems, showing practical potential for large-scale agricultural applications requiring real-time behavioral analysis.

This study investigates the concentrations, health risks, and potential sources of heavy metal elements and polycyclic aromatic hydrocarbons (PAHs) in PM1.1 particles in Zhuji, a major copper-processing city in China. The ratios of heavy metals (summer: 0.906; winter: 0.619) and PAHs (>0.750 in both seasons) in PM1.1/PM2.0 suggest significant accumulation in ultrafine particles. In winter, heavy metal concentrations in PM1.1 reached up to 448 ng/m3, and PAH concentrations were 13.4 ng/m3—over ten times higher than in summer. Health risk assessments revealed that hazard index (HI) values exceeded 1.00 for five age groups (excluding infants) during winter, indicating chronic exposure risks. Incremental lifetime cancer risk (ILCR) values surpassed the upper acceptable limit (1.0 × 10⁻⁴) for four age groups, with Cr, As, Cd, and Pb as major contributors. PAH-related ILCRs were also elevated in winter, with benzo[a]pyrene (BaP) identified as the most potent carcinogen. Enrichment factor (EF) and principal component analysis (PCA) indicated that industrial activities and traffic emissions were the dominant anthropogenic sources of heavy metals. Diagnostic ratio analysis further showed that PAHs mainly originated from vehicle and coal combustion. These findings provide critical insights into pollution patterns in industrial cities and underscore the importance of targeted mitigation strategies.

Due to the COVID-19 pandemic, Bangladesh government took the measure like partial lockdown (PL) and complete lockdown (CL) to curb the spread. These measures gave a chance for environmental restoration. In this study, street dust samples were collected during PL and CL from four main urban land use categories in Dhaka city, such as industrial area (IA), commercial area (CA), public facilities area (PFA), and residential area (RA). Ten potentially toxic elements (Cr, Mn, Zn, Fe, Pb, Cu, Co, Ni, As, and Cd) in fine street dust particles (diameter < 20 μm) were determined following aqua-regia digestion and measured by inductively coupled plasma mass spectrometry (ICP-MS) to evaluate distribution, pollution sources, and potential risks to ecological systems and human health. Results showed that during PL, the concentrations of toxic elements in the dust were higher than that of CL. Cd and Fe were lowest and highest in concentration with 1.56 to 41,970 µg/g and 0.82 to 39,330 µg/g in partial and complete lockdown period respectively. All toxic elements were detected at high levels above background values where Fe with the highest and Cd with lowest concentrations, respectively. By land use, the levels of toxic elements pollution followed IA > PFA > RA > CA. Correlation analysis (CA), principal component analysis (PCA), and hierarchal cluster analysis (HCA) revealed that the sources of these analyzed toxic elements were mainly from anthropogenic which are related to industrial and vehicular or traffic emissions. Enrichment factor (EF), geoaccumulation index ( I geo ), contamination factor (CF), and pollution load index (PLI) also suggested that the dust was more polluted during PL. Exposure of toxic elements to human was mainly via skin contact followed by ingestion and inhalation. Hazard quotient (HQ) values were < 1 except for Mn through dermal contact at all sites during partial and complete lockdown, similar to hazard index (HI), while Cr further showed high non-carcinogenic risks to children. Generally, children HI values were about 5–6 times higher than those of adults, suggesting a greater vulnerability of children to the health concerns caused by toxic elements in street dust. Carcinogenic risk (CR) values via ingestion pathway indicated all elements (except Pb) had significant health effect, while CR value by inhalation results showed no significant health effect. Cumulative carcinogenic risk (CCR) value had significant health effect except Pb in all land use categories. CCR values decreased during CL and reached at acceptable limit for most of the cases. This research provides a message to the local governments and environmental authorities to have a complete assessment of toxic elements in the street dust of Dhaka megacity in order to assuring public health safety and ecological sustainability.

Unmanned aerial vehicles (UAVs), or Drones, have recently begun to appear frequently in the television, newspapers and social media for their applicability in various fields of science. Although UAVs have been used in a wide range of atmospheric science, there are few reports of using UAVs for lower layer atmospheric observation available. In my laboratory, harmful black carbon (BC) in ambient particulates was determined based on the observation results of harmful chemicals in the lower boundary layer and atmospheric conditions using UAVs. The ambient particulates in the lower layer atmosphere based on heights can be measured by UAVs at the optional location. In this paper, I want to report the lower layer atmospheric observation of ambient particulates with their chemical species for the first time in Japan. The data transfer devices were loaded into UAVs for the transformation of the results measured at different heights during 2018 in order to develop real-time observations of PM2.5 and PM10 in the lower layer atmosphere of the suburban and urban areas of Saitama city, Japan. Air pollutants transported from the urban areas of metropolitan Tokyo were determined from the real-time results of measurements in the vanity in the morning, noon and afternoon. High concentrations of PM2.5 and PM10 were observed around noon in the rural area of Yorii-machi, Saitama prefecture on December 5, 2017 which might be influenced by the polluted air mass from the urban atmosphere. It is clear that different air pollution phenomena can be observed easily by using UAVs real-time atmospheric monitoring.

Background: Chronic atrophic gastritis precancerous lesions (PL-CAG) are characterized by the atrophy of gastric mucosal glands, often accompanied by intestinal metaplasia or dysplasia. Timely intervention and treatment can effectively reverse its malignant progression and prevent the onset of gastric cancer. Bombyx Batryticatus (BB) exhibits a range of pharmacological effects, including anticoagulation, antiepileptic properties, anticancer activity, and antibacterial effects. However, the pharmacological basis and mechanisms underlying BB’s efficacy in treating PL-CAG remain unclear. Methods: A three-factor modeling approach was implemented to develop a rat PL-CAG model, while the MNNG-induced PLGC (precancerous lesions of gastric cancer) cell model was served as a cell PL-CAG model. UPLC-QE-Orbitrap-MS/MS (Ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry) was utilized to perform an in-depth analysis of the components in the plasma extract of BB. Leveraging network pharmacology, molecular docking analyses, and experimental validation, we initially elucidated the potential mechanisms through which BB mediates its therapeutic effects on PL-CAG at both in vivo and in vitro levels. Results: Prototype compounds of 42 blood-entering components were identified by UPLC-QE-Orbitrap-MS/MS analysis. Network pharmacology analysis and molecular docking studies indicate that the core targets are primarily enriched in the PI3K-Akt signaling pathway, and the key components, including Nepitrin, Quercetin 3-O-neohesperidoside, Rutin, and others, exhibited stable docking conformations with the first eleven pivotal targets. Both in vivo and in vitro experiments validated that BB may effectively treat PL-CAG via modulation of the PI3K-Akt signaling pathway. Conclusions: The therapeutic efficacy of BB in the management of PL-CAG may be achieved through the synergistic interaction of multiple components and targets, which may be more closely related to the inhibition of the PI3K/AKT signaling pathway. This approach will establish a solid experimental foundation and provide essential data for the clinical application of BB in treating PL-CAG, while also facilitating further research initiatives.