Efficient Strategy Research Articles

2D Self-Assembly of Large-Sized Inorganic Nanosheets Leading to Enhanced Power Factors in Earth-Abundant Cu3SbSe4-Based Flexible Hybrid Films.

Fabrication of large-sized inorganic nanosheets is an efficient strategy to promote carrier transportation in flexible thermoelectric (TE) films. Herein, we report the self-assembly of large-sized Cu3SbSe4 nanosheets by using a Se nanowire template via wet chemical synthesis and then vacuum-assisted filter these plate-like microcrystals on nylon to prepare Cu3SbSe4 flexible thermoelectric (TE) hybrid films. SEM reveals that the as-synthesized Cu3SbSe4 powders by using Se nanowires as selenium sources presented 2D plate-like micron structures uniformly and tightly self-assembled by acute triangle-like nanoparticles. Furthermore, XPS evidences that extra Sb vacancies are generated in the unit cell of Cu3SbSe4 crystals synthesized by using the Se NW template, resulting in the shrinkage of the unit cell and the narrowing interplanar spacing, which are characterized by XRD and TEM. As a result, both carrier concentration and carrier mobility have been significantly improved. The high carrier concentration is proved to originate from the extra carriers induced by Sb vacancies, and the high carrier mobility of the film is mainly ascribed to its continuous grain boundaries in the plate-like microcrystal morphology. The large-sized nanosheet Cu3SbSe4/nylon hybrid film (CSS MPs) exhibits a high power factor (PF) of 235.45 μW m-1 K-2 at 400 K, which is 4.23 times higher than that of the Cu3SbSe4/nylon hybrid film (CSS NPs) where Cu3SbSe4 crystals are synthesized by using raw Se particles. This work reveals a novel approach to prepare plate-like Se-based semiconductors, which requires both high carrier concentration and high carrier mobility.

Inhibition of Chk1 stimulates cytotoxic action of platinum-based drugs and TRAIL combination in human prostate cancer cells.

Checkpoint kinase 1 (Chk1) plays an important role in regulation of the cell cycle, DNA damage response and cell death, and represents an attractive target in anticancer therapy. Small-molecule inhibitors of Chk1 have been intensively investigated either as single agents or in combination with various chemotherapeutic drugs and they can enhance the chemosensitivity of numerous tumor types. Here we newly demonstrate that pharmacological inhibition of Chk1 using potent and selective inhibitor SCH900776, currently profiled in phase II clinical trials, significantly enhances cytotoxic effects of the combination of platinum-based drugs (cisplatin or LA-12) and TRAIL (tumor necrosis factor-related apoptosis inducing ligand) in human prostate cancer cells. The specific role of Chk1 in the drug combination-induced cytotoxicity was confirmed by siRNA-mediated silencing of this kinase. Using RNAi-based methods we also showed the importance of Bak-dependent mitochondrial apoptotic pathway in the combined anticancer action of SCH900776, cisplatin and TRAIL. The triple drug combination-induced cytotoxicity was partially enhanced by siRNA-mediated Mcl-1 silencing. Our findings suggest that targeting Chk1 may be used as an efficient strategy for sensitization of prostate cancer cells to killing action of platinum-based chemotherapeutic drugs and TRAIL.

Effectiveness of Endoscopic Screening on Esophageal Cancer Incidence and Mortality: A 9-Year Report of the Endoscopic Screening for Esophageal Cancer in China (ESECC) Randomized Trial.

To evaluate the effectiveness of endoscopic screening against incidence of and mortality from esophageal squamous cell carcinoma (ESCC). From January 2012 to September 2016, we conducted a community-based cluster randomized controlled trial involving permanent residents age 45-69 years in a high-risk region for ESCC in northern China. A total of 668 targeted villages were randomly assigned in a 1:1 ratio to the screening group (offered Lugol's chromoendoscopy) or control group (no screening). Intention-to-treat and per-protocol analyses were performed to compare esophageal cancer (EC) incidence and mortality between the two groups. The per-protocol analysis adjusted for nonadherence to the screening procedure. A total of 33,847 participants were included in the analysis: 17,104 in the screening group, 15,165 (88.7%) of whom underwent screening, and 16,743 in the control group. During a maximum follow-up of 9 years, EC incidence in the screening and control groups were 60.9 and 72.5 per 100,000 person-years, respectively; mortality in the screening and control groups were 29.7 and 32.4 per 100,000 person-years, respectively. Compared with the control group, the incidence and mortality of the screening group reduced by 19% (adjusted hazard ratio [aHR], 0.81 [95% CI, 0.60 to 1.09]) and 18% (aHR, 0.82 [95% CI, 0.53 to 1.26]), respectively, in the intention-to-treat analysis; and by 22% (aHR, 0.78 [95% CI, 0.56 to 1.10]) and 21% (aHR, 0.79 [95% CI, 0.49 to 1.30]), respectively, in the per-protocol analysis. With a 9-year follow-up, our trial suggests that chromoendoscopic screening induces modest reductions in EC incidence and mortality. A more efficient strategy for EC screening and subsequent patient management should be established to guarantee the effectiveness of endoscopic screening.

Genetic determinants of thermal resistance in foodborne bacterial pathogens

AbstractThermal food processing stands as the conventional and prevalent intervention utilized by food industries to uphold food safety standards. Some bacteria are known to withstand thermal treatments up to definite extents. This ability primarily stems from genetically determined traits that can be influenced by environmental conditions. This review focuses on the genetic determinants of thermal resistance in foodborne pathogens including the locus of heat resistance (LHR). Genes contributing to the expression of proteins that might indirectly contribute to thermal resistance have also been covered. The emergence of thermal tolerance in these pathogens raises significant food safety concerns, given global worries about bacterial resistance. The review consolidates existing research on genetic components and loci of heat resistance and highlights potential areas of gaps that warrant further research. Furthermore, acquired cross‐protection leading to resistance across multiple interventions has also been highlighted as an emerging concern. Acquiring insights into the environmental conditions that promote the selection of the LHR will empower the adoption of more efficient strategies to obstruct the pathways by which these pathogens persist within processing chains.

An Efficient Checkpoint Strategy for Federated Learning on Heterogeneous Fault-Prone Nodes

Federated learning (FL) is a distributed machine learning method in which client nodes train deep neural network models locally using their own training data and then send that trained model to a server, which then aggregates all of the trained models into a globally trained model. This protects personal information while enabling machine learning with vast amounts of data through parallel learning. Nodes that train local models are typically mobile or edge devices from which data can be easily obtained. These devices typically run on batteries and use wireless communication, which limits their power, making their computing performance and reliability significantly lower than that of high-performance computing servers. Therefore, training takes a long time, and if something goes wrong, the client may have to start training again from the beginning. If this happens frequently, the training of the global model may slow down and the final performance may deteriorate. In a general computing system, a checkpointing method can be used to solve this problem, but applying an existing checkpointing method to FL may result in excessive overheads. This paper proposes a new FL method for situations with many fault-prone nodes that efficiently utilizes checkpoints.

Data model-based toolpath generation techniques for CNC milling machines

Introduction: With the development of computer technology and data modeling, the use of point cloud models to generate tool paths is particularly important for improving productivity and accuracy.Methods: This study proposes a new method that first preprocesses the point cloud data using four-point denoising and octree methods to improve processing efficiency. Subsequently, roughing tool paths were analyzed using the layer slicing method and finishing paths using the residual height method.Results and Discussion: The experimental results show that the layer slicing method has a minimum error close to 10% on the roughing path generation and the computation time is reduced to 35 s, while the residual height method has an error rate of 10.17% on the finishing path and the computation time is only 11.82 s, which reflects a high trajectory smoothness and accuracy. The above results show that the study not only optimizes the tool path generation process and improves the machining efficiency and accuracy, but also demonstrates the potential application of point cloud models in the machining of complex parts.Conclusion: The novel tool roughing and finishing methods provide more reliable path planning for actual machining operations, and future research will be devoted to further improving the performance of the data processing algorithms and exploring more efficient path planning strategies to facilitate automated production.

Cell‐free DNA‐associated multi‐feature applications in cancer diagnosis and treatment

AbstractMalignant tumours pose significant challenges in terms of high morbidity and mortality rates, primarily due to the lack of large‐scale applicable screening methods and efficient treatment strategies. However, the development of liquid biopsies, particularly circulating cell‐free DNA (cfDNA), offers promising solutions characterised by their non‐invasiveness and cost‐effectiveness, providing comprehensive tumour information on a global scale. The release of cfDNA is predominantly associated with cell death and turnover, while its elimination occurs through nuclease digestion, renal excretion into the urine and uptake by the liver and spleen. Extensive research into the biological properties of cfDNA has led to the identification of novel applications, including non‐invasive cancer screening, cancer subtype classification, tissue‐of‐origin detection and monitoring of treatment efficacy. Additionally, emerging fields such as methylation‐omics, fragment‐omics and nucleosome‐omics show immense potential as tissue‐ and disease‐specific markers. Therefore, this review aims to comprehensively introduce the latest detection techniques of cfDNA, along with detailed information on its characteristics and applications, providing valuable insights for cancer diagnosis and monitoring, which will assist us in purposefully enhancing relevant features for a more comprehensive application in clinical practice.

Structure of the Bacterial Cell Envelope and Interactions with Antimicrobials: Insights from Molecular Dynamics Simulations.

Bacteria have evolved over 3 billion years, shaping our intrinsic and symbiotic coexistence with these single-celled organisms. With rising populations of drug-resistant strains, the search for novel antimicrobials is an ongoing area of research. Advances in high-performance computing platforms have led to a variety of molecular dynamics simulation strategies to study the interactions of antimicrobial molecules with different compartments of the bacterial cell envelope of both Gram-positive and Gram-negative species. In this review, we begin with a detailed description of the structural aspects of the bacterial cell envelope. Simulations concerned with the transport and associated free energy of small molecules and ions through the outer membrane, peptidoglycan, inner membrane and outer membrane porins are discussed. Since surfactants are widely used as antimicrobials, a section is devoted to the interactions of surfactants with the cell wall and inner membranes. The review ends with a discussion on antimicrobial peptides and the insights gained from the molecular simulations on the free energy of translocation. Challenges involved in developing accurate molecular models and coarse-grained strategies that provide a trade-off between atomic details with a gain in sampling time are highlighted. The need for efficient sampling strategies to obtain accurate free energies of translocation is also discussed. Molecular dynamics simulations have evolved as a powerful tool that can potentially be used to design and develop novel antimicrobials and strategies to effectively treat bacterial infections.

Organophotoredox Catalysis: Switchable Radical Generation from Alkyl Sodium Sulfinates for Sulfonylation and Alkylative Activation of C-C Bonds of Cyclopropenes.

Generating alkyl radicals from the sulfonyl radicals remains challenging in synthetic chemistry. Here, we report an efficient photocatalyzed strategy using alkyl sodium sulfinates as both sulfonylating and alkylating reagents by controlling the reaction temperature. This methodology provides a versatile protocol for synthesizing diastereoselective sulfonylated cyclopropanes and poly-substituted styrene derivatives. This methodology is successfully demonstrated with a wide variety of cyclopropenes and alkyl sulfinates, showcasing its broad substrate scope, high diastereo- and E/Z selectivity, and yielding good to excellent yields.

A non-residue surface modification strategy for active-targeting fluorescent silica nanoparticles to cellular organelles.

Silica nanoparticles (SiNPs) with a chemically modified surface typically have a complicated chemical composition, which can significantly differ from their intended design. In this study, we systematically studied the effects of two surface modification methods on active-targeting of intracellular organelles of SiNPs: (1) the widely used step-by-step approach, which involves modifying SiNPs in two steps, i.e., the outer surface of SiNPs was firstly modified with amino groups and then these amino groups were linkedwith targeting groups, and (2) a newly developed one-step approach in which the ligand-silane complex is initially synthesized, followed by chemically immobilizing the complex on the surface of SiNPs. In the one-step approach, the molar ratio of reactants was precisely tuned so that there are no reactive groups left on the outer surface of SiNPs. Two essential organelles, mitochondria and the nucleus, were selected to compare the targeting performances of SiNPs synthesized via these two approaches. By characterizing physicochemical properties, including structural properties, the number of amino groups, surface charge, polydispersity, and cell colocalization, we demonstrated that SiNPs synthesized via the one-step approach with no residual linkage groups on their surface showed significantly improved mitochondria- and nucleus-targeting performances. This precise control of surface properties allows for optimized biological behavior and active-targeting efficiency of SiNPs. We anticipate that such simple and efficient synthetic strategies will enable the synthesis of effective SiNPs for active-targeting organelles in various biological applications.

Comparative evolutionary analyses of peste des petits ruminants virus genetic lineages.

Peste des petits ruminants virus (PPRV) causes a highly infectious disease affecting mainly goats and sheep in large parts of Africa, Asia, and the Middle East and has an important impact on the global economy and food security. Full genome sequencing of PPRV strains has proved to be critical to increasing our understanding of PPR epidemiology and to inform the ongoing global efforts for its eradication. However, the number of full PPRV genomes published is still limited and with a heavy bias towards recent samples and genetic Lineage IV (LIV), which is only one of the four existing PPRV lineages. Here, we generated genome sequences for twenty-five recent (2010-6) and seven historical (1972-99) PPRV samples, focusing mainly on Lineage II (LII) in West Africa. This provided the first opportunity to compare the evolutionary pressures and history between the globally dominant PPRV genetic LIV and LII, which is endemic in West Africa. Phylogenomic analysis showed that the relationship between PPRV LII strains was complex and supported the extensive transboundary circulation of the virus within West Africa. In contrast, LIV sequences were clearly separated per region, with strains from West and Central Africa branched as a sister clade to all other LIV sequences, suggesting that this lineage also has an African origin. Estimates of the time to the most recent common ancestor place the divergence of modern LII and LIV strains in the 1960s-80s, suggesting that this period was particularly important for the diversification and spread of PPRV globally. Phylogenetic relationships among historical samples from LI, LII, and LIII and with more recent samples point towards a high genetic diversity for all these lineages in Africa until the 1970s-80s and possible bottleneck events shaping PPRV's evolution during this period. Molecular evolution analyses show that strains belonging to LII and LIV have evolved under different selection pressures. Differences in codon usage and adaptative selection pressures were observed in all viral genes between the two lineages. Our results confirm that comparative genomic analyses can provide new insights into PPRV's evolutionary history and molecular epidemiology. However, PPRV genome sequencing efforts must be ramped up to increase the resolution of such studies for their use in the development of efficient PPR control and surveillance strategies.

Novel SNP markers for flowering and seed quality traits in faba bean (Vicia faba L.): characterization and GWAS of a diversity panel.

Faba bean (Vicia faba L.) is a legume crop grown in diverse climates worldwide. It has a high potential for increased cultivation to meet the need for more plant-based proteins in human diets, a prerequisite for a more sustainable food production system. Characterization of diversity panels of crops can identify variation in and genetic markers for target traits of interest for plant breeding. In this work, we collected a diversity panel of 220 accessions of faba bean from around the world consisting of gene bank material and commercially available cultivars. The aims of this study were to quantify the phenotypic diversity in target traits to analyze the impact of breeding on these traits, and to identify genetic markers associated with traits through a genome-wide association study (GWAS). Characterization under field conditions at Nordic latitude across two years revealed a large genotypic variation and high broad-sense heritability for eleven agronomic and seed quality traits. Pairwise correlations showed that seed yield was positively correlated to plant height, number of seeds per plant, and days to maturity. Further, susceptibility to bean weevil damage was significantly higher for early flowering accessions and accessions with larger seeds. In this study, no yield penalty was found for higher seed protein content, but protein content was negatively correlated to starch content. Our results showed that while breeding advances in faba bean germplasm have resulted in increased yields and number of seeds per plant, they have also led to a selection pressure towards delayed onset of flowering and maturity. DArTseq genotyping identified 6,606 single nucleotide polymorphisms (SNPs) by alignment to the faba bean reference genome. These SNPs were used in a GWAS, revealing 51 novel SNP markers significantly associated with ten of the assessed traits. Three markers for days to flowering were found in predicted genes encoding proteins for which homologs in other plant species regulate flowering. Altogether, this work enriches the growing pool of phenotypic and genotypic data on faba bean as a valuable resource for developing efficient breeding strategies to expand crop cultivation.

Ultra-Wideband Ranging Error Mitigation with Novel Channel Impulse Response Feature Parameters and Two-Step Non-Line-of-Sight Identification.

The effective identification and mitigation of non-line-of-sight (NLOS) ranging errors are essential for achieving high-precision positioning and navigation with ultra-wideband (UWB) technology in harsh indoor environments. In this paper, an efficient UWB ranging-error mitigation strategy that uses novel channel impulse response parameters based on the results of a two-step NLOS identification, composed of a decision tree and feedforward neural network, is proposed to realize indoor locations. NLOS ranging errors are classified into three types, and corresponding mitigation strategies and recall mechanisms are developed, which are also extended to partial line-of-sight (LOS) errors. Extensive experiments involving three obstacles (humans, walls, and glass) and two sites show an average NLOS identification accuracy of 95.05%, with LOS/NLOS recall rates of 95.72%/94.15%. The mitigated LOS errors are reduced by 50.4%, while the average improvement in the accuracy of the three types of NLOS ranging errors is 61.8%, reaching up to 76.84%. Overall, this method achieves a reduction in LOS and NLOS ranging errors of 25.19% and 69.85%, respectively, resulting in a 54.46% enhancement in positioning accuracy. This performance surpasses that of state-of-the-art techniques, such as the convolutional neural network (CNN), long short-term memory-extended Kalman filter (LSTM-EKF), least-squares-support vector machine (LS-SVM), and k-nearest neighbor (K-NN) algorithms.

Performance evaluation and optimization of a multigeneration hybrid system for power, hydrogen, cooling, and freshwater production from renewable sources

Designing a hybrid system emerges as a highly efficient strategy for augmenting the performance of renewable-based power plants, owing to their adaptability in integrating diverse subsystems. In this study, a new multigeneration system is introduced, showcasing its capability to concurrently generate power, hydrogen, cooling, and freshwater through a synergy of methanol-steam reforming, modified absorption refrigeration cycles, humidification-dehumidification, and multi-effect desalination. The operational foundation of the system is rooted in the harmonious integration of solar and geothermal energy sources. To comprehensively evaluate the proposed system's performance, a combination of exergy and economic analyses is employed. This research studies the impacts of varying key parameters on the system's operation. Notably, the water-to-methanol ratio is identified as the most influential variable affecting reformer performance, underscoring the pivotal role of reforming pressure. The estimated total fixed cost of the system stands at $4.039 million, with a calculated payback period of 6 years and a net present value of $3.454 million. Furthermore, in its optimized state, the system achieves an impressive exergy efficiency of 49.80 % and a unit product cost of $32.38/GJ. These findings unequivocally validate the feasibility and economic viability of the proposed hybrid renewable-based power generation system. In conclusion, the amalgamation of solar and geothermal energy, coupled with meticulous parameter optimization, substantiates the potential of this innovative system to serve as a sustainable and economically viable solution for power generation.

Modelling foraging strategies of honey bees as agents in a dynamic landscape representation

Introduction: Both intrinsic colony mechanisms and external environmental variables affect the honey bee colony development rates and response and a key aspect of this is the use of resources within the landscape by honey bees. Although several models have been developed to explore the foraging behaviour of bees, none fully considered the spatial and temporal dynamics of landscape resources and the role of the colony in the process. Methodology: Here, we introduce a new honey bee foraging model being developed as a part of the ApisRAM honey bee colony model. Based on agent-based modelling, we used a dynamic ALMaSS landscape model enhanced with floral resource modelling to assess the impacts of weather conditions and resource availability on the possible foraging behaviour of honey bees. Several possible mechanisms (defined, based on honey bee traits) for scouting and foraging were investigated, separately for nectar and pollen collection, including prioritising foraging polygons for nectar foraging according to their distance to the colony, the quality or the energetic efficiency and, for pollen foraging, according to their distance to the colony and pollen quantity. Results: If model foraging bees prioritised the polygons, based on their distance from the colony, the number of unsuccessful flights increased compared to other tested strategies and the total amount of sugar collected showed a high variability. Contrary to expectations, the energetic efficiency strategy did not provide the colony with the highest amount of sugar. Overall, the tested strategies provide different outcomes on the collection of resources, the number of performed flights and their success rate, evidencing that the model's outcome at the colony level arises from the individual types of behaviour. Conclusions and Relevance: Variability in the mass of collected nectar and pollen was found mostly when scout bees applied the distance strategy. This higher variability in sugar collection means that model bees were not able to find the most profitable foraging sites at the landscape level, but only at the local level. Other strategies showed less dependence on the surrounding landscape (i.e. quality or random), but it comes at a cost (i.e. lower production for both nectar and pollen collection). These outputs help us evaluate which strategies could be used for future model development and confirm the models' ability to create dynamic responses. These responses at the colony level were only possible thanks to the implementation of a dynamic landscape model and dynamic spatiotemporal resource model, as well as implementing a social communication mechanism for bees to share information about the resources. Plant nectar production and quality information is essential to predict honey bee foraging distribution. In future model development, the implementation of pollen quality should also be explored to evaluate if it influences the overall pollen collection.

Theoretical Design of Strengthened Nanotwinned γ*-Boron.

The distinctive electron deficiency and unusual multicenter bonding situations of boron give rise to fascinating chemical complexity and imaginative structural polymorphism. Herein, we employ an independently developed method to construct the new twinned γ*-boron based on the well-known hardest elemental boron, γ-B28. Notably, the newly propounded γ*-boron phases exhibit considerably close energy levels with γ-B28 under ambient conditions. The simulated X-ray diffraction patterns of stable twinned structure present excellent agreement with experimental data. First-principles calculations reveal a 7.5% increase in the ideal Vickers shear strength of γ*-boron compared to γ-B28, attributed to diverse bond responses within the twinned slabs. The evaluated hardness of nanotwinned γ*-B reaches 59 GPa in consideration of the size hardening effect. Our research presents an efficient strategy for constructing new polymorphs of boron with improved mechanical properties and expands the knowledge about twinning structures of boron.

Nanostructured Lipid Carriers of Donepezil Hydrochloride for the Treatment of Alzheimer's Disease.

Alzheimer's Disease (AD) is a long-term brain disorder that worsens over time. A cholinesterase inhibitor called Donepezil HCl (DNZ) is used to treat and control AD. Due to its failure to reach the appropriate concentration in the brain cells, its efficacy upon oral administration is limited, and thus investigation of alternative administration route is necessary. The objective of this study was to develop donepezil HCl-loaded Nanostructured Lipid Carriers (NLCs) that can bypass the blood-brain barrier and thus be directly delivered to the brain through the nasal route. This method improves availability at the site of action, reduces the negative effects of oral medication, and ensures an expedited commencement of action. High-pressure homogenization and ultrasonication were used to formulate NLCs. Glyceryl Monostearate (GMS) as a solid lipid, Tween 80 as a surfactant, and Poloxamer 407 as a co-- surfactant were used. In this study, argan oil was employed as a liquid lipid as well as a penetration enhancer. The chosen NLCs displayed a particle size of 137.34 ± 0.79 nm, a PDI of 0.365 ± 0.03, and a zeta potential of -10.4 mV. The selected formulation showed an entrapment efficiency of 84.05 ± 1.30% and a drug content of 77.02 ± 0.23%. The concentration of the drug in the brain after intravenous and intranasal administration of DNZ NLCs at 1 h was found to be 0.490 ± 0.007 and 4.287 ± 0.115, respectively. Thus, the concentration of DNZ achieved in the brain after intranasal administration of DNZ NLCs was approximately 9 times more than the concentration when administered by intravenous route. The DNZ-loaded NLCs, when administered via nasal route, showed markedly improved drug availability in the brain, suggesting an efficient drug delivery strategy to treat Alzheimer's disease.

Access to 2,4-Disubstituted Pyrrole-Based Polymer with Long-Wavelength and Stimuli-Responsive Properties via Copper-Catalyzed [3+2] Polycycloaddition.

Pyrrole-based polymers (PBPs), a type of fascinating functional polymers, play a crucial role in materials science. However, efficient synthetic strategies of PBPs with diverse structures are mainly focused on conjugated polypyrroles and still remain challenging. Herein, an atom and step economy protocol is described to access various 2,4-disubstituted PBPs by in situ formation of pyrrole core structure via copper-catalyzed [3+2] polycycloaddition of dialkynones and diisocyanoacetates. A series of PBPs is prepared with high molecular weight (Mw up to 18 200 Da) and moderate to good yield (up to 87%), which possesses a fluorescent emission located in the green to yellow light region. Blending the PBPs with polyvinyl alcohol, the stretchable composite films exhibit a significant strengthening of the mechanical properties (tensile stress up to 59 MPa, elongation at break >400%) and an unprecedented stress-responsive luminescence enhancement that over fourfold fluorescent emission intensity is maintained upon stretching up to 100%. On the basis of computational studies, the unique photophysical and mechanical properties are attributed to the substitution of carbonyl chromophores on the pyrrole unit.

Iron-Catalyzed Csp2-Csp3 Cross-Coupling via Double Decarboxylation: One Step Synthesis of Remote Polar Alkenes.

Herein, we report an efficient photoinduced iron-catalyzed strategy for cross-couplings of alkyl carboxylic and acrylic acids, which provides a powerful tool for the synthesis of a variety of alkenes with polar functional groups. This novel synthetic methodology can also be applied to the preparation of ketones by using α-keto acids. Mechanistic experiments revealed preliminary mechanistic details. Diverse functionalization could be achieved, which may help streamline the synthesis of complex analogues for drug discovery.

CUQIpy: I. Computational uncertainty quantification for inverse problems in Python

This paper introduces CUQIpy, a versatile open-source Python package for computational uncertainty quantification (UQ) in inverse problems, presented as Part I of a two-part series. CUQIpy employs a Bayesian framework, integrating prior knowledge with observed data to produce posterior probability distributions that characterize the uncertainty in computed solutions to inverse problems. The package offers a high-level modeling framework with concise syntax, allowing users to easily specify their inverse problems, prior information, and statistical assumptions. CUQIpy supports a range of efficient sampling strategies and is designed to handle large-scale problems. Notably, the automatic sampler selection feature analyzes the problem structure and chooses a suitable sampler without user intervention, streamlining the process. With a selection of probability distributions, test problems, computational methods, and visualization tools, CUQIpy serves as a powerful, flexible, and adaptable tool for UQ in a wide selection of inverse problems. Part II of the series focuses on the use of CUQIpy for UQ in inverse problems with partial differential equations.