Comparative analysis of multiple machine learning models: identifying impact factors in biochar heavy metal adsorption mechanisms.

The contribution analysis of influencing factors governing biochar-mediated heavy metal adsorption in aqueous systems holds significant implications for cost-effective water remediation. Current studies predominantly rely on single-model approaches to identify critical variables, which may introduce bias due to inherent model assumptions, thereby impeding systematic elucidation of impact mechanisms and variable interactions. To address this gap, we integrated twelve machine learning models with SHAP (Shapley Additive exPlanations) interpretation to holistically investigate determinants and key variables.

Terminations Determine Energy-Level Alignment of Perovskite Buried Interfaces.

The "substrate-effect", where the semiconduction type of perovskite changes according to that of the substrate is a widely-reported, but so far not fully understood phenomenon in the field of perovskite. The main challenge lies in the difficulty of probing and comprehending the electronic properties of perovskite buried interfaces. Here, through broadly investigating 20 buried interfaces formed between different perovskites and organic hole or electron transport materials (HTMs or ETMs), it is revealed that the substrate-effect originates from the distinct energy-level alignments at HTM or ETM substrates.

Multi-factor interaction perspective: machine learning-based analysis of Ni⁺ adsorption onto soil.

With the rapid development of industry and agriculture, the ecological and health impacts of nickel (Ni) have gained increasing attention. While previous experimental studies have identified factors influencing Ni adsorption behavior in soils, their nonlinear relationships and interactive effects remain underexplored. Through combining machine learning (CatBoost/XGBoost) models with SHapley Additive exPlanations (SHAP), this study analyzed 662 experimental datasets to reveal these nonlinear interactions between factors that affect the adsorption behavior of Ni in soil.

Supramolecular force-driven non-fullerene acceptors as an electron-transporting layer for efficient inverted perovskite solar cells.

Fullerene derivatives are widely employed as efficient electron-transporting layers (ETLs) in p-i-n perovskite photovoltaics but face challenges in mitigating interfacial recombination losses and ensuring stable film morphology. Non-fullerene acceptors (NFAs), commonly utilized in organic photovoltaics, present a promising alternative to fullerene-based ETLs. Nevertheless, the suboptimal performance of NFA-based devices underscores the need for molecular engineering to tailor their properties.

An Intermediate-Aided Perovskite Phase Purification for High-Performance Solar Cells.

In recent years, perovskite solar cells (PSCs) have garnered considerable attention as a prime candidate for next-generation photovoltaic technology. Ensuring the structural stability of perovskites is crucial to the operational reliability of these devices. However, the nonphotoactive yellow phase (δ-FAPbI) of formamidine (FA)-based perovskites is more favorable in thermodynamics, making it challenging to achieve pure α phase in crystallization.

Migration of total petroleum hydrocarbon and heavy metal contaminants in the soil-groundwater interface of a petrochemical site using machine learning: impacts of convection and diffusion.

Convection and diffusion are key pathways for the migration of total petroleum hydrocarbons (TPH) and heavy metals (HMs) from soil to groundwater. However, the extent of their influence on pollutant migration, as well as the nonlinear relationships between these processes and pollutants, remains unclear. This study investigates the spatial distribution of TPH and HMs at a petrochemical site with complex hydrogeological conditions in southwestern China.

Dimensional Regulation from 1D/3D to 2D/3D of Perovskite Interfaces for Stable Inverted Perovskite Solar Cells.

Constructing low-dimensional/three-dimensional (LD/3D) perovskite solar cells can improve efficiency and stability. However, the design and selection of LD perovskite capping materials are incredibly scarce for inverted perovskite solar cells (PSCs) because LD perovskite capping layers often favor hole extraction and impede electron extraction. Here, we develop a facile and effective strategy to modify the perovskite surface by passivating the surface defects and modulating surface electrical properties by incorporating morpholine hydriodide (MORI) and thiomorpholine hydriodide (SMORI) on the perovskite surface.

Common pathogenic bacteria-induced reprogramming of the host proteinogenic amino acids metabolism.

Apart from cancer, metabolic reprogramming is also prevalent in other diseases, such as bacterial infections. Bacterial infections can affect a variety of cells, tissues, organs, and bodies, leading to a series of clinical diseases. Common Pathogenic bacteria include Helicobacter pylori, Salmonella enterica, Mycobacterium tuberculosis, Staphylococcus aureus, and so on.

On the Ion Coordination and Crystallization of Metal Halide Perovskites by In Situ Dynamic Optical Probing.

Controlling the crystallization to achieve high-quality homogeneous perovskite film is the key strategy in developing perovskite electronic devices. Here, an in situ dynamic optical probing technique is demonstrated that can monitor the fast crystallization of perovskites and effectively minimize the influence of laser excitation during the measurement. This study finds that the typical static probing technique would damage and induce phase segregation in the perovskite films during the excitation.

Unlocking the Ambient Temperature Effect on FA-Based Perovskites Crystallization by In Situ Optical Method.

Multiple cation-composited perovskites are demonstrated as a promising approach to improving the performance and stability of perovskite solar cells (PSCs). However, recipes developed for fabricating high-performance perovskites in laboratories are always not transferable in large-scale production, as perovskite crystallization is highly sensitive to processing conditions. Here, using an in situ optical method, the ambient temperature effect on the crystallization process in multiple cation-composited perovskites is investigated.

Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is the most common renal malignancy, although newly developing targeted therapy and immunotherapy have been showing promising effects in clinical treatment, the effective biomarkers for immune response prediction are still lacking. The study is to construct a gene signature according to ccRCC immune cells infiltration landscape, thus aiding clinical prediction of patients response to immunotherapy.

Methods: Firstly, ccRCC transcriptome expression profiles from Gene Expression Omnibus (GEO) database as well as immune related genes information from IMMPORT database were combine applied to identify the differently expressed meanwhile immune related candidate genes in ccRCC comparing to normal control samples.

Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression.

Background: Osteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking, partly due to the comprehensive and highly heterogeneous nature of osteosarcoma. The study is to identify more potential responsible genes during the development of osteosarcoma, thus identifying promising gene indicators and aiding more precise interpretation of the disease.

Spatial Control of the Hole Accumulation Zone for Hole-Dominated Perovskite Light-Emitting Diodes by Inserting a CsAc Layer.

Perovskites show efficient electroluminescence and are expected to have wide applications in light-emitting diodes (LEDs). However, owing to the unbalanced electron-hole transport properties of some highly luminescent perovskites, a fundamental challenge is that the exciton recombination zone of perovskite LEDs (PeLEDs) typically overlaps with an accumulation of the major carrier. It is known to reduce the performances of PeLEDs, leading to a reduction of efficiency and operation stability due to Auger recombination.

Heat Transfer Enhancement of n-Type Organic Semiconductors by an Insulator Blend Approach.

The transfer of heat energy in organic semiconductors (OSCs) plays an important role in advancing the applications of organic electronics, especially for lifetime issues. However, compared with crystalline inorganic semiconductors, the thermal transport of OSCs is less efficient and a relevant understanding is very limited. In this contribution, we show that the heat conduction of OSCs can be enhanced by blending with a "commodity" insulator (both thermal and electrical).

Enhancing the Performance of Perovskite Light-Emitting Diodes by Humidity Treatment.

While humidity treatment has been employed for enhancing the performance of perovskite solar cells and light-emitting diodes (LEDs), only very limited success has been achieved in quasi-two-dimensional (2D) perovskite LEDs (PeLEDs). Here, for the first time, we demonstrate more than one order of magnitude enhancement of the external quantum efficiency (EQE) and electroluminescence (EL) intensity in blue CsPb(Cl/Br) PeLEDs with an organic cation of 2,2-(ethylenedioxy)bis(ethylammonium) (EDBE). Upon humidity treatment, the crystallinity of the three-dimensional (3D) perovskite phase in the EDBE-based perovskite is improved, contributing to an enhancement of photoluminescence quantum yield (PLQY).

Molecular profiling of gene fusions in soft tissue sarcomas by Ion AmpliSeq: a study of 35 cases.

Background: The accurate diagnosis of sarcoma can be difficult as there are over 70 different subtypes. While molecular profiling in soft tissue sarcoma (STS) has gradually been incorporated into routine diagnostics, conventional methods such as fluorescence in situ hybridization (FISH), reverse transcriptase-PCR (RT-PCR), and Sanger sequencing have several drawbacks. By allowing simultaneous analysis of multiple targets and increasing sequencing depth to achieve ultra-sensitivity, next-generation sequencing (NGS) can not only detect common genetic abnormalities without prior assumptions but also identify uncommon or even new variants.

IMUP and GPRC5A: two newly identified risk score indicators in pancreatic ductal adenocarcinoma.

Background: Pancreatic cancer has been a threateningly lethal malignant tumor worldwide. Despite the promising survival improvement in other cancer types attributing to the fast development of molecular precise medicine, the current treatment situation of pancreatic cancer is still woefully challenging since its limited response to neither traditional radiotherapy and chemotherapy nor emerging immunotherapy. The study is to explore potential responsible genes during the development of pancreatic cancer, thus identifying promising gene indicators and probable drug targets.

Efficient Perovskite White Light-Emitting Diode Based on an Interfacial Charge-Confinement Structure.

Perovskite light-emitting diodes (LEDs) show great potential for next-generation lighting and display technology. Despite intensive studies on single-color devices, there are few reports on perovskite-based white LEDs (Pe-WLEDs). Here, an efficient Pe-WLED based on a blue perovskite and an orange phosphorescent emitter is reported for the first time.

Bioinformatic analysis identifying FGF1 gene as a new prognostic indicator in clear cell Renal Cell Carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) has been the commonest renal cell carcinoma (RCC). Although the disease classification, diagnosis and targeted therapy of RCC has been increasingly evolving attributing to the rapid development of current molecular pathology, the current clinical treatment situation is still challenging considering the comprehensive and progressively developing nature of malignant cancer. The study is to identify more potential responsible genes during the development of ccRCC using bioinformatic analysis, thus aiding more precise interpretation of the disease METHODS: Firstly, different cDNA expression profiles from Gene Expression Omnibus (GEO) online database were used to screen the abnormal differently expressed genes (DEGs) between ccRCC and normal renal tissues.