Predicting the number of COVID-19 cases in a geographical area is important for the management of health resources and decision making. Several methods have been proposed for COVID-19 case ...predictions but they have important limitations in terms of model interpretability, related to COVID-19’s incubation period and major trends of disease transmission. To be able to explain prediction results in terms of incubation period and transmission trends, this paper presents the Multivariate Shapelet Learning (MSL) model to learn shapelets from historical observations in multiple areas. An experimental evaluation was done to compare the prediction performance of eleven algorithms, using the data collected from 50 US provinces/states. Results show that the proposed method is effective and efficient. The learned shapelets explain increasing and decreasing trends of new confirmed cases, and reveal that the COVID-19 incubation period in the USA is around 28 days.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
In the last few years, organometal halide perovskites (OHPs) have emerged as a promising candidate for photovoltaic (PV) applications. A certified efficiency as high as 23.7% has been achieved, which ...is comparable with most of the well‐established PV technologies. Their good solubility due to the ionic nature enables versatile low‐temperature solution processes, including blade coating, slot‐die coating, etc., most of which are scalable and compatible with roll‐to‐roll large‐scale manufacturing processes. The low cost, high efficiency, and facile processable features make perovskite solar cells (PSCs) a very competitive PV technology. Despite the great progress, long‐term durability concerns, toxicity issues of both materials and manufacturing process, and lack of robust high‐throughput production technology for fabricating efficient large‐area modules are major obstacles toward commercialization. In this review, the recent progress of commercially available process of PSCs is surveyed, the underlying determinants for upscaling high‐quality PSCs from hydrodynamic characteristics and crystallization thermodynamic mechanism are identified, the influence of external stress factors on stability of PSCs and intrinsic instability mechanism in OHPs themselves is revealed, and the environmental impact and sustainable development of PSC technology are analyzed. Strategies and opportunities for large‐scale production of PSCs are suggested to promote the development of PSCs toward commercialization.
Perovskite solar cells (PSCs) have emerged as a promising candidate for photovoltaic applications. This review summarizes the recent progress and discusses the obstacles for PSCs toward industrial production, including upscaling of high‐quality perovskites for efficient PSC modules, stability issue of PSCs, Pb substitution, and greener manufacturing process, which can promote the development of PSCs toward commercialization.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Adsorption is one of the widely used processes in the chemical industry environmental application. As compared to mathematical models proposed to describe batch adsorption in terms of isotherm and ...kinetic behavior, insufficient models are available to describe and predict fixed-bed or column adsorption, though the latter one is the main option in practical application. The present review first provides a brief summary on basic concepts and mathematic models to describe the mass transfer and isotherm behavior of batch adsorption, which dominate the column adsorption behavior in nature. Afterwards, the widely used models developed to predict the breakthrough curve, i.e., the general rate models, linear driving force (LDF) model, wave propagation theory model, constant pattern model, Clark model, Thomas model, Bohart-Adams model, Yoon-Nelson model, Wang model, Wolborska model, and modified dose-response model, are briefly introduced from the mechanism and mathematical viewpoint. Their basic characteristics, including the advantages and inherit shortcomings, are also discussed. This review could help those interested in column adsorption to reasonably choose or develop an accurate and convenient model for their study and practical application.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Amplification of chromosome 7q21-7q31 is associated with tumor recurrence and multidrug resistance, and several genes in this region are powerful drivers of hepatocellular carcinoma (HCC). We aimed ...to investigate the key circular RNAs (circRNAs) in this region that regulate the initiation and development of HCC.
We used qRT-PCR to assess the expression of 43 putative circRNAs in this chromosomal region in human HCC and matched nontumor tissues. In addition, we used cultured HCC cells to modify circRNA expression and assessed the effects in several cell-based assays as well as gene expression analyses via RNA-seq. Modified cells were implanted into immunocompetent mice to assess the effects on tumor development. We performed additional experiments to determine the mechanism of action of these effects.
circMET (hsa_circ_0082002) was overexpressed in HCC tumors, and circMET expression was associated with survival and recurrence in HCC patients. By modifying the expression of circMET in HCC cells in vitro, we found that circMET overexpression promoted HCC development by inducing an epithelial to mesenchymal transition and enhancing the immunosuppressive tumor microenvironment. Mechanistically, circMET induced this microenvironment through the miR-30-5p/Snail/ dipeptidyl peptidase 4(DPP4)/CXCL10 axis. In addition, the combination of the DPP4 inhibitor sitagliptin and anti-PD1 antibody improved antitumor immunity in immunocompetent mice. Clinically, HCC tissues from diabetic patients receiving sitagliptin showed higher CD8
T cell infiltration than those from HCC patients with diabetes without sitagliptin treatment.
circMET is an onco-circRNA that induces HCC development and immune tolerance via the Snail/DPP4/CXCL10 axis. Furthermore, sitagliptin may enhance the efficacy of anti-PD1 therapy in a subgroup of patients with HCC.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Developing effective catalysts to degrade chemical warfare agents is of great significance. Herein, a mesoporous MIL-101(Cr) composite material dangled with porphyrin molecules (denote as ...TCPP@MIL-101(Cr), TCPP = tetra(4-carboxyphenyl)porphyrin) is reported, which can be used as a heterogeneous photocatalyst for detoxification of mustard gas simulants 2-chloroethyl ethyl sulfide (CEES) to 2-chloroethyl ethyl sulfoxide (CEESO) with a half-life of 1 min. The catalytic performance of TCPP@MIL-101(Cr) is comparable to that of homogeneous molecular porphyrin. Mechanistic studies reveal that both
O
and O
are efficiently generated and play vital roles in the oxidation reaction. Gold nanoparticles (AuNPs) are attached to the TCPP@MIL-101(Cr) to further enhance the catalytic activity with a benchmark half-life of 45 s, which is the fastest record so far. A medical mask loaded TCPP@MIL-101(Cr) is fabricated for practical applications, which can selectively photoxidize CEES to CEESO under sunlight and air atmosphere, exhibiting the best degradation performance among the reported fabric-like composite materials.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Adsorption is one of the most widely applied techniques for environmental remediation. Its kinetics are of great significance to evaluate the performance of a given adsorbent and gain insight into ...the underlying mechanisms. There are lots of references available concerning adsorption kinetics, and several mathematic models have been developed to describe adsorption reaction and diffusion processes. However, these models were frequently employed to fit the kinetic data in an unsuitable or improper manner. This is mainly because the boundary conditions of the associated models were, to a considerable extent, ignored for data modeling. Here we reviewed several widely-used adsorption kinetic models and paid more attention to their boundary conditions. We believe that the review is of certain significance and improvement for adsorption kinetic modeling.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Planar perovskite solar cells (PSCs) have attracted extensive research attention owing to their simple architecture and manufacturing process. Improving the charge extraction ability of electron ...transport materials (ETMs) is imperative to enhance their power conversion efficiencies (PCEs). Herein, we report low-temperature solution-processed SnO2 nanocrystals (SnO2 NCs) enveloped by amorphous NbOx (SnO2/NbOx) as efficient ETMs for planar PSCs, achieving an impressive PCE of 24.01% with negligible hysteresis, which is significantly superior to that of PSCs made from commercial SnO2 (with PCEs up to 21.96%) and self-developed SnO2 NCs (with PCEs up to 23.01%). The NbOx layer can simultaneously passivate defects at the ETMs/perovskite interface, promote charge extraction from perovskites, and improve the crystallinity of perovskite films. The unencapsulated PSC retains over 85% of its initial efficiency after 1000 h of light soaking (one sun), showing remarkable device stability. Furthermore, the low-temperature processed SnO2/NbOx ETMs are compatible with flexible substrates and present a maximum PCE of 20.00%. This work offers a facile approach to low-temperature processed ETMs with boosted carrier extraction ability, affording excellent device efficiency and stability for planar PSCs.
Big data values data processing to ensure effective value-added data. With the rapid development of the cloud era, the coverage of big data has gradually expanded, and it has received wide attention ...from all walks of life. In the process of modern social development, big data analysis is gradually applied to the future development planning, risk evaluation and integration of market development status. With the rapid development of many fields of society, the flow of information has gradually expanded, and the Internet has developed more rapidly, prompting the application of big data in various fields. Machine learning is a multidisciplinary study of how computers use data or past experience. With the ability to independently improve specific algorithms, the computer acquires knowledge through learning and achieves the goal of artificial intelligence. Big data and machine learning are the major technological changes in the modern computer world, and these technologies have had a huge impact on all walks of life. At present, with the rapid development of the Internet, mobile communications, social networks and the Internet of Things, these networks generate large amounts of data every day, and data become the most important information resource of today. Some studies have shown that in many cases, the larger the amount of data, the better the data will be for machine learning. On this basis, this paper proposes an online client algorithm based on machine learning algorithm for IoT unstructured big data analysis and uses it in other big data analysis scenarios. Use the online data entered by the customer to implement background data mining, the parallel way to verify its efficiency through machine learning algorithms such as K-nearest neighbor algorithm.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, ODKLJ, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Two novel and eco-friendly redox mediators (RMs), magnetic oxidative vanillin (MOV) and magnetic oxidative syringaldehyde (MOS), both derived from lignin, were prepared to improve the decolorization ...of the methyl orange (MO) dye. The Decolorization Efficiency (DE) of MO in the batch experiments with MOV and MOS were increased by more than 60% and 22%, respectively, when compared to the control experiment without magnetic RMs. Moreover, the two magnetic RMs could maintain stable DE of MO in sequenced batch reactors (SBRs), and negligible leaching of the oxidized lignin monomers was observed under various environmental conditions. Density Function Theory (DFT) calculations were used to propose three potential biodegradation mechanisms for azo dyes, and the key intermediates were confirmed using high-performance liquid chromatography. This study proposed a feasible strategy for functional utilization of lignin resource, as well as a practical method for effectively treating azo dye-containing wastewater.
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•A kind of novel and eco-friendly redox mediators (RMs) derived from lignin were prepared.•The induction of RMs accelerated the decolorization of methyl orange (MO).•Magnetic immobilized in sequenced batch reactors, RMs maintained stable removal of MO.•Three stimulative mechanisms of the RMs for azo dyes were proposed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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