Development and assessment of an immobilized bacterial alliance that efficiently degrades tylosin in wastewater.

Microbial degradation of tylosin (TYL) is a safe and environmentally friendly technology for remediating environmental pollution. Kurthia gibsonii (TYL-A1) and Klebsiella pneumonia (TYL-B2) were isolated from wastewater; degradation efficiency of the two strains combined was significantly greater than either alone and resulted in degradation products that were less toxic than TYL. With Polyvinyl alcohol (PVA)-sodium alginate (SA)-activated carbon (AC) used to form a bacterial immobilization carrier, the immobilized bacterial alliance reached 95.9% degradation efficiency in 1 d and could be reused for four cycles, with > 93% degradation efficiency per cycle. In a wastewater application, the immobilized bacterial alliance degraded 67.0% TYL in 9 d. There were significant advantages for the immobilized bacterial alliance at pH 5 or 9, with 20 or 40 g/L NaCl, or with 10 or 50 mg/L doxycycline. In summary, in this study, a bacterial consortium with TYL degradation ability was constructed using PVA-SA-AC as an immobilized carrier, and the application effect was evaluated on farm wastewater with a view to providing application guidance in environmental remediation.

Ambient fine particulate matter chemical composition associated with in-hospital case fatality, hospital expenses, and length of hospital stay among patients with heart failure in China.

*Joint senior authorship. BACKGROUND: Previous studies have observed the adverse effects of ambient fine particulate matter pollution (PM2.5) on heart failure (HF). However, evidence regarding the impacts of specific PM2.5 components remains scarce. METHODS: We included 58 129 patients hospitalised for HF between 2013 and 2017 in 11 cities of Shanxi, China from inpatient discharge database. We evaluated exposure to PM2.5 and its components ((sulphate (SO42-), nitrate (NO3-), ammonium (NH4+), organic matter (OM) and black carbon (BC)), along with meteorological factors using bilinear interpolation at each patients' residential address. We used multivariable logistic and linear regression models to assess the associations of these components with in-hospital case fatality, hospital expenses, and length of hospital stay. RESULTS: Increase equivalents to the interquartile range (IQR) in OM (odds ratio (OR) = 1.13; 95% confidence interval (CI) = 1.02, 1.26) and BC (OR = 1.14; 95% CI = 1.02, 1.26) were linked to in-hospital case fatality. Per IQR increments in PM2.5, SO42-, NO3-, OM, and BC were associated with cost increases of 420.62 (95% CI = 285.75, 555.49), 221.83 (95% CI = 96.95, 346.71), 214.93 (95% CI = 68.66, 361.21), 300.06 (95% CI = 176.96, 423.16), and 303.09 (95% CI = 180.76, 425.42) CNY. Increases of 1 IQR in PM2.5, SO42-, OM, and BC were associated with increases in length of hospital stay of 0.10 (95% CI = 0.02, 0.19), 0.09 (95% CI = 0.02, 0.17), 0.10 (95% CI = 0.03, 0.17), and 0.16 (95% CI = 0.08, 0.23) days. CONCLUSIONS: Our findings suggest that ambient SO42-, OM, and BC might be significant risk factors for HF, emphasising the importance of formulating customised guidelines for the chemical constituents of PM and controlling the emissions of the most dangerous components.

Carbon price prediction based on decomposition technique and extreme gradient boosting optimized by the grey wolf optimizer algorithm.

It is essential to predict carbon prices precisely in order to reduce CO2 emissions and mitigate global warming. As a solution to the limitations of a single machine learning model that has insufficient forecasting capability in the carbon price prediction problem, a carbon price prediction model (GWO-XGBOOST-CEEMDAN) based on the combination of grey wolf optimizer (GWO), extreme gradient boosting (XGBOOST), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is put forward in this paper. First, a random forest (RF) method is employed to screen the primary carbon price indicators and determine the main influencing factors. Second, the GWO-XGBOOST model is established, and the GWO algorithm is utilized to optimize the XGBOOST model parameters. Finally, the residual series of the GWO-XGBOOST model are decomposed and corrected using the CEEMDAN method to produce the GWO-XGBOOST-CEEMDAN model. Three carbon emission trading markets, Guangdong, Hubei, and Fujian, were experimentally predicted to verify the model's validity. Based on the experimental results, it has been demonstrated that the proposed hybrid model has enhanced prediction precision compared to the comparison model, providing an effective experimental method for the prediction of future carbon prices.

Mechanism of Lactiplantibacillus plantarum regulating Ca2+ affecting the replication of PEDV in small intestinal epithelial cells.

Porcine epidemic diarrhea virus (PEDV) mainly invades the small intestine and promotes an inflammatory response, eventually leading to severe diarrhea, vomiting, dehydration, and even death of piglets, which seriously threatens the economic development of pig farming. In recent years, researchers have found that probiotics can improve the intestinal microenvironment and reduce diarrhea. At the same time, certain probiotics have been shown to have antiviral effects; however, their mechanisms are different. Herein, we aimed to investigate the inhibitory effect of Lactiplantibacillus plantarum supernatant (LP-1S) on PEDV and its mechanism. We used IPEC-J2 cells as a model to assess the inhibitory effect of LP-1S on PEDV and to further investigate the relationship between LP-1S, Ca2+, and PEDV. The results showed that a divalent cation chelating agent (EGTA) and calcium channel inhibitors (Bepridil hydrochloride and BAPTA-acetoxymethylate) could inhibit PEDV proliferation while effectively reducing the intracellular Ca2+ concentration. Furthermore, LP-1S could reduce PEDV-induced loss of calcium channel proteins (TRPV6 and PMCA1b), alleviate intracellular Ca2+ accumulation caused by PEDV infection, and promote the balance of intra- and extracellular Ca2+ concentrations, thereby inhibiting PEDV proliferation. In summary, we found that LP-1S has potential therapeutic value against PEDV, which is realized by modulating Ca2+. This provides a potential new drug to treat PEDV infection.

Building ecological civilization: the importance of promoting green investments by Chinese companies.

The study investigated "Building Ecological Civilization: the Importance of Promoting Green Investments by Chinese Companies" to examine the complex connections between the factors affecting Chinese businesses' ecological performance (EP). An autoregressive distributed lag (ARDL) model is used in the study to analyze the impact of green investments (GI), the policy environment (PE), government support (GS), public awareness and perception (PAP), and technological capability (TC) on companies' earnings per share (EPS). The results show a strong correlation between GI and EP, indicating that businesses' growing use of green initiatives is essential for raising environmental sustainability. The study also shows that PE, TC, and EP have an inverse relationship, indicating the need for more supportive governmental policies and regulations and the effective adoption and implementation of green technologies. The interaction of GS and PAP significantly reduces the ecological impact of green investments, highlighting the significance of citizen involvement and the role of government in advancing ecological civilization. The findings also demonstrated that green investments, policy environments, public perception, and technology influence the ecological performance of businesses. They also demonstrate statistical robustness with low p-values. This information is essential for developing policies that support an ecological civilization, which is necessary for China and globally in light of the current climate crisis.

Association of dementia comorbidities with caregivers' physical, psychological, social, and financial burden.

BACKGROUND: Informal caregivers of older adults with dementia may experience substantial burdens during their caregiving process, especially when caring for older adults with other comorbid conditions. This study evaluated whether and how comorbidity burden for persons with dementia (PWD) was associated with caregivers' physical, psychological, social, and financial burden as well as caregiving gain. METHODS: Data were from 1,065 community-dwelling older adults living with dementia and their primary caregivers in the National Health and Aging Trends Study and the National Study of Caregiving. PWD's comorbidity burden was measured by the count of chronic conditions and the pattern of comorbidity identified by the latent class analysis (LCA). We considered four domains of caregiving burden-physical, psychological, social, and financial burden. We used linear regressions to identify the unadjusted and adjusted associations between PWD's comorbidity burden and caregiving burden and gain. RESULTS: Of 1,065 PWD, 13.5% had 0-1 and 24.9% had 5 or more number of comorbid chronic conditions, respectively. After multivariable adjustment, an additional chronic condition is associated with an 0.11- and 0.36-point increase in caregivers' physical and psychological burden, respectively. Caregivers of PWD with 5 or more chronic conditions had a 0.64- and 2.22-point higher score of physical and psychological burden, respectively, than those caring for PWD with 0 or 1 comorbid condition. LCA divided PWD into two classes, a high comorbidity class (69.0%) and a low comorbidity class (31.0%). Caregivers of PWD in the high comorbidity burden class had a 0.46-point higher score of physical caregiving burden than those in the low comorbidity burden class. No significant association was found between care recipients' comorbidity burden and their caregivers' social and financial burden or caregiving gain. CONCLUSIONS: The comorbidity burden of PWD was associated with their caregivers' physical and psychological caregiving burden. Relevant interventions to manage the comorbid conditions of people living with dementia and support their caregivers are crucial to improving their physical health and psychological wellbeing.

Transmissible Gastroenteritis Virus Nucleocapsid Protein Interacts with Na+/H+ Exchanger 3 To Reduce Na+/H+ Exchanger Activity and Promote Piglet Diarrhea.

Transmissible gastroenteritis virus (TGEV) is member of the family Coronaviridae and mainly causes acute diarrhea. TGEV infection is characterized by vomiting, watery diarrhea, and severe dehydration, resulting in high mortality rates in neonatal piglets. TGEV infection symptoms are related to an imbalance of sodium absorption in small intestinal epithelial cells; however, the etiology of sodium imbalance diarrhea caused by TGEV remains unclear. In this study, we performed transcriptomic analysis of intestinal tissues from infected and healthy piglets and observed that the expression of NHE3, encoding Na+/H+ exchanger 3 (NHE3), the main exchanger of electroneutral sodium in intestinal epithelial cells, was significantly reduced upon TGEV infection. We also showed that specific inhibition of intestinal NHE3 activity could lead to the development of diarrhea in piglets. Furthermore, we revealed an interaction between TGEV N protein and NHE3 near the nucleus. The binding of TGEV N to NHE3 directly affected the expression and activity of NHE3 on the cell surface and affected cellular electrolyte absorption, leading to diarrhea. Molecular docking and computer-aided screening techniques were used to screen for the blocker of the interaction between TGEV N and NHE3, which identified irinotecan. We then demonstrated that irinotecan was effective in relieving TGEV-induced diarrhea in piglets. These findings provide new insights into the mechanism of TGEV-induced sodium imbalance diarrhea and could lead to the design of novel antiviral strategies against TGEV. IMPORTANCE A variety of coronaviruses have been found to cause severe diarrhea in hosts, including TGEV; however, the pathogenic mechanism is not clear. Therefore, prompt determination of the mechanism and identification of efficient therapeutic agents are required, both for public health reasons and for economic development. In this study, we demonstrated that NHE3 is the major expressed protein of NHEs in the intestine, and its expression decreased by nearly 70% after TGEV infection. Also, specific inhibition of intestinal NHE3 resulted in severe diarrhea in piglets. This demonstrated that NHE3 plays an important role in TGEV-induced diarrhea. In addition, we found that TGEV N directly regulates NHE3 expression and activity through protein-protein interaction, which is essential to promote diarrhea. Molecular docking and other techniques demonstrated that irinotecan could block the interaction and diarrhea caused by TGEV. Thus, our results provide a basis for the development of novel therapeutic agents against TGEV and guidance for the development of drugs for other diarrhea-causing coronaviruses.

Spatiotemporal variation in the blood lead levels of Chinese children with the environmental Kuznets curve trend.

The environmental Kuznets curve (EKC) is often used to analyze the relationship between environmental pollution health indicators and economic development level in different regions. In developed countries, the blood lead levels (BLLs) of children have been declining fitting the EKC since the 1970s. However, such figures in China have remained at relatively high levels, without any obvious decline, since 2010. We explored spatial variations and graded countermeasures using reported data on BLLs including the lead poisoning rates (LPRs) of children. We found that there were prefectures where either the mean BLLs of the children had reached 100.00 µg/L or the LPRs of more than 40% of the children had reached 100 µg/L. When we reduced the average BLLs to 50 µg/L or lowered the proportion of children with a lead poisoning rate (LPR) above 100 µg/L to 10.00%, the EKC trend decreased, and the linear slope after 2010 became -0.202. If the areas where children's BLLs exceeded 50.00 µg/L or the proportion of children with an LPR above 100 µg/L was more than 10.00% will be controlled, the linear slope of the EKC decrease trend after 2010 will became -0.989, and the national average of children's BLLs would decline by 22.17%. The study concluded that children's BLLs in different regions of China are situated at different EKC stages, and urgent prevention and control strategies must be put in place for undeveloped areas.

The Effect of Green Finance on the Ecological and Environmental Quality of the Yangtze River Economic Belt.

Since China's reform and opening up, the speed of economic development has increased significantly. However, at the same time, there are also serious environmental pollution problems. To resolve the deep-seated contradiction between economic growth and environmental protection, green finance has gradually gained attention in China's development. Based on this, the paper explores the impact of green finance on the quality of the ecological environment in the Yangtze River Economic Belt. The main part of the paper is based on panel data of eleven provinces and cities in China's 2011-2020 Yangtze River Economic Belt. Seven indicators, including chemical oxygen demand COD, harmless treatment rate of domestic waste, and green coverage rate of built-up, were used to construct an ecological and environmental quality evaluation index system. The entropy method is used to measure the ecological environment quality level and green finance development level of various provinces and cities in the Yangtze River Economic Belt. The impact of green finance development on ecological environment quality is analyzed using a panel data model. The research results show that: (1) The development level of green finance and the quality of the ecological environment in the Yangtze River Economic Belt have improved between 2011 and 2020. (2) The development of green finance has a significant positive impact on the quality of the ecological environment in the Yangtze River Economic Belt. In addition, related research has focused on the impact of green finance on a certain branch of ecological and environmental quality and lacks an analysis of the overall impact. Therefore, this paper constructs a comprehensive evaluation system for ecological environment quality and analyzes the overall impact of green finance on ecological environment quality in the region.

Reinforced MCTS for non-intrusive online load identification based on cognitive green computing in smart grid.

Cognitive green computing (CGC) is widely used in the Internet of Things (IoT) for the smart city. As the power system of the smart city, the smart grid has benefited from CGC, which can achieve the dynamic regulation of the electric energy and resource integration optimization. However, it is still challenging for improving the identification accuracy and the performance of the load model in the smart grid. In this paper, we present a novel algorithm framework based on reinforcement learning (RL) to improve the performance of non-invasive load monitoring and identification (NILMI). In this model, a knowledge base of load power facilities (LPF-KB) architecture is designed to facilitate the load data-shared collection and storage; utilizing deep convolutional neural networks (DNNs) structure based on the attentional mechanism to enhance the representations learning of load features; using RL-based Monte-Carlo tree search (MCTS) method to construct an optimal strategy network, and to realize the online combined load prediction without relying on the prior knowledge. We use the massive experiment on the real-world datasets of household appliances to evaluate the performance of our method. The experimental results show that our approach has remarkable performance in reducing the load online identification error rate. Our model is a generic model, and it can be widely used in practical load monitoring identification and the power prediction system.

Low-cost pentagonal NiX2 (X = S, Se, and Te) monolayers with strong anisotropy as potential thermoelectric materials.

Pentagonal compounds, as a new family of 2D materials, have recently been extensively studied in the fields of electrocatalysis, photovoltaics, and thermoelectrics. Encouraged by the successful synthesis of pentagonal PdSe2, the thermoelectric properties of low-cost pentagonal NiX2 (X = S, Se, and Te) monolayers are theoretically predicted with the help of first-principles calculations and the semiclassical Boltzmann transport theory. The high dynamic and thermal stabilities of pentagonal NiX2 (X = S, Se, and Te) monolayers are confirmed according to the phonon dispersion spectrums and ab initio molecular dynamics (AIMD) simulations. Indirect semiconductor features with wide bandgaps of 2.44, 2.31, and 1.88 eV at the Heyd-Scuseria-Ernzerhof (HSE06) level are discovered for pentagonal NiS2, NiSe2, and NiTe2 monolayers. Combining the Boltzmann transport equation and deformation potential theory, the Seebeck coefficient, power factor, and thermoelectric figure of merit (ZT) of NiX2 (X = S, Se, and Te) monolayers are evaluated from 300 to 600 K. The strongly anisotropic ZT values are discovered, which are attributed to the significant differences in electrical and thermal transport along the x and y directions. In addition, low lattice thermal conductivities are observed at 600 K for the pentagonal NiTe2 monolayer, accompanying higher ZT values of 1.81 and 1.58 along the x and y directions. The predicted thermoelectric properties indicate that the low-cost pentagonal NiSe2 and NiTe2 monolayers are potential anisotropic thermoelectric materials with high performance.

Assessment of racial differences in the incidence of thrombocytopenia induced by trastuzumab emtansine: a systematic review and meta-analysis.

BACKGROUND: Trastuzumab emtansine (T-DM1) has been proved to have value and efficacy in the treatment of advanced metastatic cancer, including in the adjuvant setting. However, there is increasing concern about T-DM1-induced thrombocytopenia (TCP), which shows racial differences in incidence. This meta-analysis aimed to evaluate differences in the incidence of T-DM1-related TCP between Asian and non-Asian patients by combining accessible information from all single-agent T-DM1 clinical trials published to date. METHODS: We conducted systematic searches of the PubMed, Embase, and the Cochrane Library databases to identify relevant clinical studies of T-DM1 that reported on safety, including the incidence of TCP, which were published between January 1980 and March 2020. Two reviewers were responsible for the screening and extraction of data. The pooled-effect estimate calculated with a fixed-effects or random-effects model was represented as incidence with 95% confidence intervals (CIs). RESULTS: A total of 29 studies involving 6,188 patients were included. The incidence of all-grade TCP in Asian patients and non-Asian patients was 0.39 (95% CI: 0.11-0.67) and 0.29 (95% CI: 0.23-0.35), respectively. The incidence of TCP of grade 3 or higher in Asians was 0.20 (95% CI: 0.10-0.29), compared with 0.02 (95% CI: 0.01-0.03) in non-Asians. Gastrointestinal cancer type and a T-DM1 treatment dose of 2.4 mg/kg Q3W were related to grade 3 or higher TCP events. DISCUSSION: Asian patients have a higher risk of developing TCP after receiving T-DM1 than non-Asian patients. Clinicians should be aware of the importance of careful observation of platelet count in patients receiving T-DM1 therapy.

The Analysis of Occurrences Associated with Air Traffic Volume and Air Traffic Controllers' Alertness for Fatigue Risk Management.

Fatigue is an inevitable hazard in the provision of air traffic services and it has the potential to degrade human performance leading to occurrences. The International Civil Aviation Organization (ICAO) requires air navigation services which providers establish fatigue risk management systems (FRMS) based on scientific principles for the purpose of managing fatigue. To develop effective FRMSs, it is important to investigate the relationship between traffic volume, air traffic management occurrences, and fatigue. Fifty-seven qualified ATCOs from a European Air Navigation Services provider participated in this research by providing data indicating their alertness levels over the course of a 24-hour period. ATCOs' fatigue data were compared against the total of 153 occurrences and 962,328 air traffic volumes from the Eurocontrol TOKAI incident database in 2019. The result demonstrated that ATCO fatigue levels are not the main contributory factor associated with air traffic management occurrences, although fatigue did impact ATCOs' performance. High traffic volume increases ATCO cognitive task load that can surpass available attention resources leading to occurrences. Furthermore, human resilience drives ATCOs to maintain operational safety though they suffer from circadian fatigue. Consequently, FRMS appropriately implemented can be used to mitigate the effects of fatigue. First-line countermeasure strategies should focus on enough rest breaks and roster schedule optimization; secondary strategies should focus on monitoring ATCOs' task loads that may induce fatigue. It is vital to consider traffic volume and ATCOs' alertness levels when implementing effective fatigue risk management protocols.

A new procedure, free from human assessment that automatically grades some facial skin structural signs. Comparison with assessments by experts, using referential atlases of skin ageing.

OBJECTIVE: To develop an automatic system that grades the severity of facial signs through 'selfies' pictures taken by women of different ages and ethnics. METHODS: 1140 women from three ethnics (African-American, Asian, Caucasian), of different ages (18-80 years old), took 'selfies' by high resolution smartphones cameras under different conditions of lighting or facial expressions. A dedicated software, was developed, based on a Convolutional Neural Network (CNN) that integrates training data from referential Skin Aging Atlases. The latter allows to an immediate quantification of the severity of nine facial signs according to the ethnicity declared by the subject. These automatic grading were confronted to those assessed by 12 trained experts and dermatologists either on 'selfies' pictures or in live conditions on a smaller cohort of women. RESULTS: The system appears weakly influenced by lighting conditions or facial expressions (coefficients of variations ranging 10-13% for most signs) and leads to global agreements with experts' assessments, even showing a better reproducibility on some facial signs. CONCLUSION: This automatic scoring system, still in development, seems offering a new quantitative approach in the quantified description of facial signs, independent from human vision, in many applications, being individual, cosmetic oriented or dermatological with regard to the follow-up of medical anti-ageing corrective strategies.

OBJECTIF: De développer un système automatique qui quantifie la sévérité de certains signes du visage à partir de photographies de type 'selfies' pris par des femmes d'origine ethnique et d'âge différents. MÉTHODES: 1140 femmes de trois ethnies différentes (Afro-Américaines, Asiatiques, Caucasiennes), d'âges différents (18-80 ans) ont pris des selfies sous différentes conditions d'éclairage et d'expressions faciales. Un logiciel dédié a été développé, basé sur un réseau de convolution neuronal et intégrant les données d'annotations utilisant les Atlas de Vieillissement Cutané. Ce système quantifie immédiatement la sévérité de 9 signes faciaux selon l'ethnie déclarée par le sujet. Ces scores ont été confrontés à ceux de 12 experts et dermatologistes soit à partir des 'selfies' ou en conditions réelles sur un groupe plus restreint de femmes. RÉSULTATS: Le système apparaît faiblement influencé par les conditions d'éclairage et les expressions faciales (coefficients de variation de l'ordre de 10-13%) et conduit à des valeurs comparables de celles des experts, voire même de meilleure reproductibilité dans certains cas. CONCLUSION: Ce système de scorage automatique, encore en développement, semble offrir une nouvelle approche dans la description quantitative de signes du visage, indépendante de l'œil humain, dans de nombreuses applications, comme la personnalisation, à visée cosmétique ou dermatologique, dans le suivi de certaines stratégies médicales de l'antivieillissement cutané.

Rheological, biocompatibility and osteogenesis assessment of fish collagen scaffold for bone tissue engineering.

In the present investigation, an attempt was made to find an alternative to mammalian collagen with better osteogenesis ability. Three types of collagen scaffolds - collagen, collagen-chitosan (CCH), and collagen-hydroxyapatite (CHA) - were prepared from the cartilage of Blue shark and investigated for their physico-functional and mechanical properties in relation to biocompatibility and osteogenesis. CCH scaffold was superior with pH 4.5-4.9 and viscosity 9.7-10.9cP. Notably, addition of chitosan and HA (hydroxyapatite) improved the stiffness (11-23MPa) and degradation rate but lowered the water binding capacity and porosity of the scaffold. Interestingly, CCH scaffolds remained for 3days before complete in-vitro biodegradation. The decreased amount of viable T-cells and higher level of FAS/APO-1 were substantiated the biocompatibility properties of prepared collagen scaffolds. Osteogenesis study revealed that the addition of CH and HA in both fish and mammalian collagen scaffolds could efficiently promote osteoblast cell formation. The ALP activity was significantly high in CHA scaffold-treated osteoblast cells, which suggests an enhanced bone-healing process. Therefore, the present study concludes that the composite scaffolds prepared from fish collagen with higher stiffness, lower biodegradation rate, better biocompatible, and osteogenesis properties were suitable biomaterial for a bone tissue engineering application as an alternative to mammalian collagen scaffolds.

Life Cycle Assessment of Titania Perovskite Solar Cell Technology for Sustainable Design and Manufacturing.

Perovskite solar cells have attracted enormous attention in recent years due to their low cost and superior technical performance. However, the use of toxic metals, such as lead, in the perovskite dye and toxic chemicals in perovskite solar cell manufacturing causes grave concerns for its environmental performance. To understand and facilitate the sustainable development of perovskite solar cell technology from its design to manufacturing, a comprehensive environmental impact assessment has been conducted on titanium dioxide nanotube based perovskite solar cells by using an attributional life cycle assessment approach, from cradle to gate, with manufacturing data from our laboratory-scale experiments and upstream data collected from professional databases and the literature. The results indicate that the perovskite dye is the primary source of environmental impact, associated with 64.77% total embodied energy and 31.38% embodied materials consumption, contributing to more than 50% of the life cycle impact in almost all impact categories, although lead used in the perovskite dye only contributes to about 1.14% of the human toxicity potential. A comparison of perovskite solar cells with commercial silicon and cadmium-tellurium solar cells reveals that perovskite solar cells could be a promising alternative technology for future large-scale industrial applications.