In the present study, a magnetic adsorbent, rhein-coated magnetic Fe₃O₄ nanoparticle (RMNP), for Pb²⁺ and Mg²⁺ had been developed, and adsorption mechanism was studied via low-field NMR. RMNP was characterized by TEM, FTIR, and XRD. RMNP could adsorb and remove Pb²⁺ and Mg²⁺ from water and was successfully applied to remove Pb²⁺ and Mg²⁺ from wastewater, with satisfactory recovery rates and high adsorption capacities. The calculated maximum adsorption capacity for Mg²⁺ and Pb²⁺ was approximately 69.3 and 64.9 mg g⁻¹ of RMNP, respectively, which was better than some results reported. Low-field NMR results showed that Pb²⁺ or Mg²⁺ enhanced the T₂ relaxation time of RMNP, which suggested that RMNP selectively coordinated with Pb²⁺ or Mg²⁺ and led to the aggregation of RMNP, furthermore removal of Pb²⁺ or Mg²⁺ from water. The standard curves for △T₂-cation concentration exhibited good line correlation. The linear ranges were from 4.2 × 10⁻⁶ to 2.0 × 10⁻⁴ mol L⁻¹ for Pb²⁺ and from 5.0 × 10⁻⁶ mol L⁻¹ to 1.0 × 10⁻⁴ mol L⁻¹ for Mg²⁺, respectively. The limits of detection were 1.4 × 10⁻⁶ mol L⁻¹ for Pb²⁺ and 2.1 × 10⁻⁶ mol L⁻¹ for Mg²⁺, respectively. In short, low-field NMR could clearly display the interaction between RMNP and Pb²⁺ or Mg²⁺, even be used to detect Pb²⁺ or Mg²⁺ in suitable condition. Besides, this method could be expanded to study the interaction between other magnetic adsorbents and analytes.

Trinexapac-ethyl (TE) was more widely used in golf course worldwide. As a plant growth regulator, it inhibited grass development and delayed grass cutting date. Direct contact with TE by workers that handle and apply these agents can lead to harmful effects depending on the exposure dosage and duration. Many studies have focused on the growth regulation of TE in plants, while its health risks to human beings were rarely reported. Here, we investigated the risk assessment of workers directly dermal exposed to TE by using some absorbent paper patches. The exposure intensity (EI) and potential dermal exposure (PDE) of worker body sections were obtained, and different exposure patterns were compared. The EI of each body section among mixing/loading, hand-held power sprayer, and manual sprayer workers was ranging from 7.22 to 73.0 pg cm⁻². The maximum EI of TE was found on hands of manual sprayers, while the minimum EI of TE was recorded on upper arms of mixing and loading workers. The maximum contribution sections was 29% for the chest and back from mixing/loading workers, 40% for the chest and back from hand-held power sprayers, and 32% for the thigh from manual sprayers. The unit weight potential dermal exposure (UWPDE) of hand-held power sprayers was 60% lower than that of manual sprayers, indicating that hand-held power sprayers were safer than those of manual sprayers. These findings revealed that trinexapac-ethyl posed relatively higher exposure risks to manual sprayer workers than other operator workers in golf course, mainly responsible for body sections of the chest and back and thigh.

In the last few decades, wind energy has become a significant source of the renewable energy system, and it is essential to use wind energy for generating power and run the wind turbine system (WTs) at a higher level. With the rapid penetration of wind energy in the distributed generation system (DGS) and isolated micro-grid (MG), the WT runs at its optimal energy conversion output. For this, WT has to track or drive at the optimal power point tracking algorithm. However, various publications are available on MPPT algorithms for wind energy system (WES) applications, making a choice on exact trackers for a particular algorithm because each tracker has its advantages and disadvantages. Therefore, our primary goal is to review and evaluate the exact tracking algorithm for WES applications in this manuscript. To introduce the power controller, it is essential to track maximum power despite wind energy results. Besides, many algorithms have been evaluated, and their maximum output is achieved compared to their performance. This research paper will help researchers provide an accurate reference for future recommendations by selecting the best tracking algorithms in WES.

Mammalian reproduction is a highly regulated process that can be distorted following exposure to synthetic antimicrobial preservatives like butylparaben (BP). Besides, studies have not investigated the potential antioxidant effects of turmeric on BP-provoked reprotoxicity. The present research was planned on prepubertal mice, orally treated with BP (150 μg/g body weight/day) with and without Curcuma longa (turmeric) (400 μg/mice/day) from postnatal day 35 to 65 routinely. Results showed an insignificant reduction in body weight of both sexes but contrary to these, gonadal weight increased significantly in PB-exposed mice. Additionally, elevated levels of follicle-stimulating hormone and luteinizing hormone while decreased estrogen levels were observed in BP-treated females against control. Sperm count and motility were disturbed, coupled with abnormal sperm morphology in BP-intoxicated group. These findings were synchronized with a decreased testosterone levels in the same group as compared with control. The follicular count revealed reduction in the number of antral follicles while an increase in empty follicles. The BP also significantly increased lipid peroxidation and decreased glutathione content, superoxide dismutase, and catalase activities, while the morphometric, biochemical, and histological deviations were less pronounced in the group, which was co-administered with BP and turmeric. Results indicated that turmeric has antioxidant potential to protect BP-induced oxidative stress and reprotoxicity in mice.

Reliable and accurate prediction model capturing the changes in solar radiation is essential in the power generation and renewable carbon-free energy industry. Malaysia has immense potential to develop such an industry due to its location in the equatorial zone and its climatic characteristics with high solar energy resources. However, solar energy accounts for only 2–4.6% of total energy utilization. Recently, in developed countries, various prediction models based on artificial intelligence (AI) techniques have been applied to predict solar radiation. In this study, one of the most recent AI algorithms, namely, boosted decision tree regression (BDTR) model, was applied to predict the changes in solar radiation based on collected data in Malaysia. The proposed model then compared with other conventional regression algorithms, such as linear regression and neural network. Two different normalization techniques (Gaussian normalizer binning normalizer), splitting size, and different input parameters were investigated to enhance the accuracy of the models. Sensitivity analysis and uncertainty analysis were introduced to validate the accuracy of the proposed model. The results revealed that BDTR outperformed other algorithms with a high level of accuracy. The funding of this study could be used as a reliable tool by engineers to improve the renewable energy sector in Malaysia and provide alternative sustainable energy resources.

With the rapid development of economies, the problem of water resources availability particularly in sub-Sahara Africa (SSA) has increased significantly. Specifically, in recent times, addressing the challenge of access to water resources has become a global issue of which countries in SSA are not exceptional since the adequate supply of potable water is as relevant as economic development. Consequently, this current paper seeks to estimate the determinants of water resources availability in sub-Sahara Africa. For this purpose, a panel-based regression model, which represents the availability of water resources, is specified based on the period 2000 to 2016 to examine a panel of 41 SSA countries sub-sectioned into low, lower-middle, and upper-middle-income nations. Considering the existence of residual cross-sectional reliance, outcomes based on the CIP and CADF unit root tests showed that the variables were not integrated at the same order. This thus leads to the employment of the PMG/ARDL estimation approach which unveiled that (i) agriculture production has a significant negative influence on H₂O in the lower-middle and low-income panel of SSA countries whereas in the upper-middle-income panel, an insignificant impact is witnessed; (ii) CO₂ emissions affect H₂O palpably in the upper-middle-income SSA panel while for lower-middle and low-income panels, an adverse effect is identified; (iii) economic growth adversely influenced H₂O resources in the lower-middle-income panel whereas in the case of the low-income panel, a significant positive liaison is evidenced; (iv) excluding low-income panel, industrial development concerning H₂O has a significant negative influence in upper-middle and lower-middle-income panels; (v) urbanization homogeneously showed a positive relationship with H₂O resources across all panels. The results are reconfirmed by the CCEPMG/CS-ARDL and MG employed as robust methods. Causality checks by Dumitrescu-Hurlin test finally revealed a mixture of results regarding the causal paths amid variables among the country panels. Policy recommendations have therefore been proposed based on the study findings.

Climate change caused by carbon emissions has a strong influence on the economy and human society. Though numerous previous studies have emphasized the importance of low-carbon innovation on curbing or mitigating carbon emissions, not much attention has been given to the reverse effect. We used a panel of 285 Chinese prefecture-level cities from 2005 to 2016 and Cooperative Patent Classification (CPC)-Y02 patents as low-carbon innovation indicators. The results show that the increasing carbon emissions accelerate cities’ low-carbon innovation in China, and the predicted effect varies across low-carbon innovation types. As carbon emissions rise, more low-carbon innovation will occur in activities with higher carbon emissions. Besides, we explore environmental awareness as the mediation channel for carbon emissions to impact low-carbon innovation. With the help of media, government, and enterprises, the growing carbon emissions promote public environmental awareness and change consumers’ behaviors, motivating companies to speed up low-carbon innovation.

Oxoanions are a class of contaminants that are easily released into the aquatic systems either through natural or anthropogenic activities. Depending on their oxidation states, they are highly mobile, resulting in the contamination of underground water. Above the permissible level in groundwater, they pose as threats to mammals when the contaminated water is consumed. Some of the health challenges caused are cancer, neurological, cardiac, gastrointestinal, and skin disorders. Several treatment technologies have been adopted over the years for the management of these oxoanions present in the aquatic systems. However interesting these treatment technologies might be, they also have their limitations such as cost-effectiveness, the complexity of the process, and generation of secondary pollutants. This work focused on some of the water treatment technologies applied for the removal of oxoanions. Some of the advantages and disadvantages of these treatment technologies are also highlighted. Amongst all the treatment technologies, adsorption is the most applied method for the removal of oxoanions. However, photocatalysis has a higher prospect since it is non-selective and secondary pollutants are not generated after the treatment process. Also, photocatalysis can simultaneously reduce and oxidise oxoanions as well as organic pollutants respectively.

Water and wastewater physicochemical treatments often rely on coagulation and flocculation to generate aggregates adequate for separation. Floc development may be assessed by particle size distribution (PSD) using dynamic light scattering techniques (DLS) available in commercial equipment. The DLS output data, however, often presents high variability, which may hinder comparisons of the aggregation time series for different conditions. The Visibility Graph (VG), a novel approach to be applied within the sanitation context, may be an alternative to disclose properties of these highly oscillatory monitoring results. In this study, after defining ideal shear rates and mixing times for the treatability of high-turbidity test water, we monitored PSD after coagulation using metallic salts (ferric chloride and ferric sulfate) and a natural coagulant (Opuntia cochenillifera). PSD data was converted to visibility networks and measurements were obtained to describe these time series by the VG technique. Although no series patterns were found, the VG approach shed some light onto the PSD through time, but no inferences were scaled to the treatability aspect. The limitations for the VG method in this study are mainly due to the small time series; thus, we endorse that visibility network analysis may be a promising technique within the environmental and sanitation context.

The health of family farmers is at risk due to occupational exposure to pesticides. The aims of the current study were to investigate the level of farmers’ perception of risks associated with pesticide use and to assess their health condition based on biochemical and immunological tests. Family farmers living in a vegetable-producing region in Southern Brazil were selected to participate in the study. More than 70% of the family farmers were often exposed to more than one type of pesticides; 41.2% were intensively using several pesticides for more than one decade and 74.4% were not using personal protective equipment (PPE) at the time of pesticide handling due to low perception of the risks posed by these chemicals. Enzymatic analysis performed in participants’ blood samples showed changes in catalase (CAT) and glutathione reductase (GR) activity, in lipid peroxidation (TBARS) and carbonylated protein levels, as well as in chemoattractant (IL-8) and anti-inflammatory (IL-10) interleukin expression. Low perception of health-related risks posed by pesticides can be attributed to factors such as low schooling and lack of information, which put farmers’ health at risk, as evidenced by blood biochemical and immunological changes.