Distribution Of Sites Research Articles

Long-Term Settlement Dynamics in Ancient Macedonia: A New Multi-Disciplinary Survey from Grevena (NW Greece)

This paper discusses the evolution of human settlement in ancient Macedonia from the Neolithic to the Late Roman periods, based on the results of a new multi-disciplinary and multi-scale archaeological survey in northern Grevena (NW Greece). Building upon an unpublished (legacy) survey, we developed a GIS-structured workflow that integrates site-revisiting and surveying strategies (material collection and test pits) with multi-temporal remote-sensing analyses, offering analytical information about site distribution, characterisation, dating, and taphonomy. Notably, the new study led to a 64% increase in the number of known sites. The combined results indicate that prehistory is less represented in the surface record than historical periods, likely due to the impact of soil erosion episodes. The Late Bronze Age and Early Iron Age saw increased site numbers and the emergence of a settlement structure that characterised the area until the Hellenistic period. During the Roman period, the pattern shifted from a seemingly limited use of the landscape towards a model of more extensive habitation. This was driven by the appearance of new rural sites that introduced a land-use regime designed to support agricultural intensification by implementing anti-erosion measures, such as field terraces.

Implications for Paleontological Heritage Conservation: The Spatial Distribution and Potential Factors Controlling the Location of Fossil Sites of Shandong Province in China

Shandong Province in China is rich in paleontological fossils and has a long history of fossil research. However, research on the distribution characteristics and potential factors of discovered fossil sites in Shandong Province is limited and insufficient, making it difficult to comprehensively plan for the protection and utilization of fossil sites in Shandong Province. The study constructs a basic geographical information system (GIS) database with 133 discovered fossil sites and geological and socio-economic data of Shandong Province and studies fossil sites’ spatial distribution characteristics and the spatial relationship with potential factors at a regional scale. The results are as follows: (1) The fossil sites in Shandong Province are concentrated in the mountainous area of central Shandong and the hilly area of the Shandong Peninsula, with significant uneven distribution characteristics, including two agglomeration areas and seven sub-agglomeration areas. (2) Natural geographical conditions, such as topography, paleogeography, and stratigraphy, play a positive role in the distribution of fossil sites, and there are apparent concentrations in the following areas: at an altitude greater than 100 m; the Lower Paleozoic and Cretaceous sedimentary rocks; and the active areas of paleo-tectonics. (3) A certain degree of negative correlation exists between socio-economic conditions, such as roads and population density, and the number of fossil sites, and a positive correlation exists between disposable personal income and those fossil sites. The operational procedure presented here is a simple, objective, applicable method that can enhance our understanding of the spatial distribution patterns and influencing factors of the discovered fossil sites of Shandong Province and support more effective and appropriate planning for paleontological heritage conservation.

Dependence of Thermally Activated Relaxation of Crystalline Stems on the Molecular Topology at Crystalline/Amorphous Interfaces in Polyethylene.

We investigate the relaxation dynamics of crystalline stems in relation to the molecular topology of the crystalline/amorphous interface, employing coarse-grained molecular dynamics. To efficiently generate model semicrystalline systems of linear polyethylene with a realistic interphase morphology, we simplified the Monte Carlo method by introducing molecular dynamics for faster relaxation. The structural properties of the generated systems are validated against experimental measurements, theoretical predictions, and existing simulation data. The models suggest that the probability distribution of loop-entry sites on the lamellar surface can be described by a power law in terms of the distance between the entry sites. By considering realistic interphase morphology, we are able to improve the prediction of the overall activation energy for the relaxation of crystalline stems, aligning it closely with experimental measurements. The largest model predicts that crystalline stems connected via large loops, i.e., those that exceed the entanglement length, and long tails are associated with increased activation energy; whereas stems connected to shorter tails show the lowest activation energy. These predictions can guide the future development of tougher semicrystalline polymers by providing insights into how amorphous chain morphology contributes to the activation energy and the relaxation dynamics of crystalline chains.

Mesh topology-based spurious pressure stabilization in 3D finite elasticity using Voronoi tessellations

AbstractIn this paper, we present a mesh topology-based stabilization approach to suppress spurious pressure modes in 3D nearly-incompressible finite elasticity. The focus lies on a mixed formulation with lowest-order approximation for the displacement and pressure fields. Motivated by the fact that the popular H1/P0 element does not fulfill the inf-sup condition, all possible local spurious pressure modes are derived on a patch of elements. The nullspace method is used to determine all spurious pressure solutions. From this, the topological requirements of the finite element mesh are established. We conclude that no more than four elements are allowed to intersect in the same vertex to overcome local checkerboarding. To fulfill this requirement, we employ non-degenerate 3D Voronoi diagrams with several different site distributions. These result in random, centroidal, and honeycomb Voronoi meshes. The resulting convex polyhedral elements are discretized by a polyhedral mixed finite element based on the lowest possible interpolation pair. The numerical examples illustrate that spurious pressure modes do not occur for any degree of mesh refinement as long as the topological mesh requirements are met. Furthermore, it is shown that the numerical inf-sup test is passed. By violating the topological requirements, it is shown that a stable pressure field cannot be guaranteed and the checkerboard phenomenon is provoked.

Epidemiological analysis of 2106 geriatric trauma patients in a level I trauma center in Lanzhou City, Gansu Province, China.

As the global population ages, geriatric trauma gains attention. Limited studies on geriatric trauma in developing countries necessitate comprehensive investigation. This study aims to delineate the epidemiological characteristics of geriatric trauma, providing insights for prevention and enhanced elderly trauma care. Clinical data of 2106 geriatric trauma patients (age ≥ 60) treated from November 1, 2020, to October 31, 2023, at the trauma center of the First Hospital of Lanzhou University were retrospectively analyzed. Descriptive statistics covered temporal and monthly distribution, trauma sites, causes, and length of stay. Inclusive were 2106 geriatric patients (941 males, 1165 females; male-to-female ratio 1:1.24). Trauma incidence was higher in summer and autumn (May-October) than winter (November-December). Peak incidents occurred between 14:00-16:00, with concentrations at 12:00-16:00 and 20:00-22:00. Falls (59.35%), road traffic accidents (16.62%), other traumas (14.10%), cutting/stabbing (4.56%), violence (3.42%), mechanical injuries (1.61%), winter sports injuries (0.14%), burns (0.14%), and animal bites (0.06%) were major causes. Extremity and skin injuries prevailed, with significant site distribution differences (P < .001). Average length of stay at the trauma center was 78.35 ± 48.32 minutes. The gender distribution, timing, causes, and sites of trauma in the elderly differ significantly from other age groups. Unlike the higher occurrence of trauma in young men compared to women, among the elderly, it is more prevalent in women than men, mainly attributed to falls. It is crucial to implement specific measures to prevent trauma in the elderly, and the advancement of information technology in the trauma care system could additionally improve the quality of care.

Infection risk factor measurement based on spatial and temporal distribution of COVID-19 nucleic acid test sites: an example from Shenzhen

COVID-19 has profoundly impacted global daily life, emphasizing the need for effective virus suppression strategies. In response, China has established numerous nucleic acid testing sites to facilitate rapid testing and curb outbreaks. However, these sites often experience congestion, increasing transmission risks and reducing testing efficiency. This study focuses on the spatial–temporal analysis of testing site distribution and associated infection risks in Shenzhen, China. Data from all Shenzhen testing sites were analyzed for the week of October 24–30, 2022, noting the percentage of busy hours per site and incorporating a population size factor by district to assess regional infection risks. Findings indicate three daily peak testing times—primarily in the evening—with the highest risk of transmission in Longgang District, followed by Yantian and Luohu, and the lowest in Futian. The risk coefficient varied from 0.040 to 0.349, with most areas showing stable risk levels between 0.06 and 0.20. This research underlines the necessity for policymakers to alleviate congestion at testing sites and suggests increasing site availability in Longgang District to mitigate COVID-19 spread, offering methodological guidance for managing infection risks in other major Chinese cities.

Favorable formation of needle-shaped NiAl2O4 phase over macroporous Ni/CexZr1-xO2–Al2O3 catalysts in one-pot preparation and coke-resistant catalytic performance in dry reforming of methane

In this study, we report the formation of needle-shaped NiAl2O4 via favorable interactions between Ni and Al species over macroporous Ni/CexZr1-xO2–Al2O3 catalysts for dry reforming of methane (DRM) and its remarkable improvement in the catalytic performance. The macroporous catalysts prepared by a one-pot (OP) method promote a favorable interaction between Ni and Al species that results in the formation of unique needle-shaped NiAl2O4 due to easy access to each other compared with that by incipient wetness impregnation. The NiAl2O4 phase in the calcined catalysts transforms into highly dispersed Ni and defective Al2O3 via the Ni exsolution in the reduction step. The presence of oxygen vacancies near Ni0 species facilitates the CO2 activation and enhances the catalyst stability over DRM. The optimized distribution of active sites with abundant defects over macroporous Ni/CexZr1-xO2-Al2O3 catalysts (OP) result in high conversions of CH4 and CO2 and a low coking rate in DRM.

Foraging distance distributions reveal how honeybee waggle dance recruitment varies with landscape

Honeybee (Apis mellifera) colonies use a unique collective foraging system, the waggle dance, to communicate and process the location of resources. Here, we present a means to quantify the effect of recruitment on colony forager allocation across the landscape by simply observing the waggle dance on the dancefloor. We show first, through a theoretical model, that recruitment leaves a characteristic imprint on the distance distribution of foraging sites that a colony visits, which varies according to the proportion of trips driven by individual search. Next, we fit this model to the real-world empirical distance distribution of forage sites visited by 20 honeybee colonies in urban and rural landscapes across South East England, obtained via dance decoding. We show that there is considerable variation in the use of dancing information in colony foraging, particularly in agri-rural landscapes. In our dataset, reliance on dancing increases as arable land gives way to built-up areas, suggesting that dancing may have the greatest impact on colony foraging in the complex and heterogeneous landscapes of forage-rich urban areas. Our model provides a tool to assess the relevance of this extraordinary behaviour across modern anthropogenic landscape types.

Are Ameloblastic Fibroma-related Lesions True Tumors?: Evidence Through CNA and BRAF Mutation Analysis.

Ameloblastic fibroma (AF) and related lesions, namely ameloblastic fibrodentinoma (AFD) and ameloblastic fibro-odontoma (AFO), span a spectrum from true neoplasms to hamartomas. The 2017 World Health Organization classification proposes that AFD and AFO are precursors to odontomas, yet their precise nature remains uncertain. This study examined 19 AF cases, 4 AFD, 15 AFO, 19 odontomas (OD, 14 complex, 5 compound), and 2 ameloblastic fibrosarcomas (AFS), focusing on clinical characteristics, recurrence, and molecular profiles. AF primarily affected individuals under 20 years (60.0% of cases), mainly in the mandible (68.4%), with a recurrence rate of 21.1% in the followed cases. AFD and AFO appeared in younger patients (average age 15.7y) without any recurrence observed. Notable differences in site and size distribution were observed between AF, its related lesions, and odontomas. Copy number alterations (CNAs) were detected in the mesenchymal component in 9 of 19 AF (47.4%), 2 of 4 AFD (50.0%), 6 of 14 AFO (42.9%), and 2 of 2 AFS (100%). In contrast, all odontomas exhibited normal CNAs, highlighting the specificity of CNAs in mesenchymal elements of AF and related lesions. BRAF p.V600E mutation was identified in the mesenchymal component in 13 of 19 AF (68.4%), 2 of 4 AFD (50.0%), 8 of 15 AFO (53.3%), and 2 of 2 AFS (100%), whereas all 19 odontomas were BRAF wild type. No mutations were found in the epithelial component. Our analysis reveals that AF and its related lesions present a spectrum of biological behaviors, from true neoplasms to hamartomas. The presence of BRAF p.V600E mutations and CNAs in their mesenchymal components, as opposed to odontomas, indicates potential neoplastic characteristics. Profiling copy number alterations in AF and related lesions emerge as a valuable tool for enhancing their differential diagnosis and facilitating the anticipation of disease progression. Our findings underscore the efficacy of copy number alteration analysis in determining the nature of lesions within AF and related lesions.

Enhanced activation of peroxymonosulfate by introducing Co/Fe atoms in LaCoO3-biochar derived catalysts for the degradation of sulfamethoxazole

In this study, a novel perovskite-biochar composite, LaCoMO3-C (LaCoM-C, M = Cu, Fe), was designed using a co-precipitation-calcination strategy and employed activation of peroxymonosulfate (PMS) for efficiently degrade sulfamethoxazole (SMX). The degradation results indicated that the LaCoCu-C/PMS system could effectively degrade 95 % of SMX within 7 min with a kinetics rate constant of 0.33 min−1, which was about 2.21, 6.64 and 3.7 times that of LaCoFe-C, LaCoCu and LaCo-C, respectively. The biochar skeleton greatly increased the specific surface area and uniform distribution of surface active sites of the composites, leading to the optimization of its catalytic performance. Density Functional Theory (DFT) calculations demonstrated that the adsorption capacity of the composites with PMS could be improved by introducing Cu/Fe elements into the interfacial structure of the composites, while Co was identified as the dominant active site. Combined with quenching test, electron paramagnetic resonance(EPR) and X-ray photoelectron spectroscopy (XPS) analyses, we demonstrated the generation of reactive oxygen species including 1O2, •OH, SO4•- and O2•-, and revealed that the oxidation process of Cu+/Cu2+ and Co2+/Co3+ on the LaCoCu-C surface contributes to PMS activation. This work constitutes an insightful reference for the development of catalysts based on perovskite B-site for efficient activation of PMS.

Highly Efficient Separation of Intermediate-Size m-Xylene from Xylenes via a Length-Matched Metal-Organic Framework with Optimal Oxygen Sites Distribution.

Xylene separation is crucial but challenging, especially for the preferential separation of the intermediate-size m-xylene from xylene mixtures. Herein, exploiting the differences in molecular length and alkyl distribution among xylenes, we present a length-matched metal-organic framework, formulated as Al(OH)[O2C-C4H2O-CO2], featuring an effective pore size corresponding to m-xylene molecular length combined with multiple negative O hydrogen bond donors distribution, can serve as a molecular trap for efficient preferential separation of the intermediate-size m-xylene. Benchmark separation performance was achieved for separating m-xylene from a ternary mixture of m-xylene/o-xylene/p-xylene, with simultaneous record-high m-xylene uptake (1.3 mmol g-1) and m-xylene/p-xylene selectivity (5.3) in the liquid-phase competitive adsorption. Both vapor- and liquid-phase fixed-bed tests confirmed its practical separation capability with benchmark dynamic m-xylene/p-xylene and m-xylene/o-xylene selectivities, as well as excellent regenerability. The selective and strong m-xylene binding affinity among xylene molecules was further elucidated by simulations, validating the effectiveness of such a pore environment for the separation of intermediate-size molecules.

Highly Efficient Separation of Intermediate‐Size m‐Xylene from Xylenes via a Length‐Matched Metal–Organic Framework with Optimal Oxygen Sites Distribution

AbstractXylene separation is crucial but challenging, especially for the preferential separation of the intermediate‐size m‐xylene from xylene mixtures. Herein, exploiting the differences in molecular length and alkyl distribution among xylenes, we present a length‐matched metal–organic framework, formulated as Al(OH)[O2C−C4H2O−CO2], featuring an effective pore size corresponding to m‐xylene molecular length combined with multiple negative O hydrogen bond donors distribution, can serve as a molecular trap for efficient preferential separation of the intermediate‐size m‐xylene. Benchmark separation performance was achieved for separating m‐xylene from a ternary mixture of m‐xylene/o‐xylene/p‐xylene, with simultaneous record‐high m‐xylene uptake (1.3 mmol g−1) and m‐xylene/p‐xylene selectivity (5.3) in the liquid‐phase competitive adsorption. Both vapor‐ and liquid‐phase fixed‐bed tests confirmed its practical separation capability with benchmark dynamic m‐xylene/p‐xylene and m‐xylene/o‐xylene selectivities, as well as excellent regenerability. The selective and strong m‐xylene binding affinity among xylene molecules was further elucidated by simulations, validating the effectiveness of such a pore environment for the separation of intermediate‐size molecules.

Deciphering the Link between Zeolite Crystal Size, Brønsted Acid Site Distribution, and Dual-Cycle Selectivity in Methanol-to-Olefins over Zeolite

Deciphering the Link between Zeolite Crystal Size, Brønsted Acid Site Distribution, and Dual-Cycle Selectivity in Methanol-to-Olefins over Zeolite

Determining the chemical ordering in nanoalloys by considering atomic coordination types.

The energetically most favorable chemical ordering of bimetallic nanoparticles can be characterized by combining global optimization algorithms and surrogate energy models. The latter approximate the energy of nanoalloys relying on structural descriptors, training models, and data. Here, we systematically evaluate the performance of highly data-efficient topological descriptors [Kozlov et al., Chem. Sci. 6, 3868 (2015)] for predicting the energies of metal nanoalloys with different chemical orderings. We also introduce a new descriptor based on atomic coordination types, which results in a less data-efficient and interpretable approach, but improves the general accuracy and the quantification of orderings in the inner parts of nanoparticles. The capacity of both the original and new approaches in combination with a basin hopping algorithm is illustrated by generating convex hulls of PdZn nanoalloys and predicting the resulting active surface site distribution as a function of particle composition. Finally, we show how these approaches can be combined with machine-learning adsorption models in electrocatalysis studies for a fast evaluation of the reactivity landscape of targeted nanoalloys.

Trends in incidence, treatment modalities and prognosis of esophageal adenocarcinoma in the US population

BackgroundEsophageal adenocarcinoma (EAC) was the predominant subtype of esophageal cancer in the Western population. However, an updated and comprehensive analysis of epidemiologic, clinical, and prognostic characteristics of esophageal adenocarcinoma is lacking. Materials and methodsThis was a population-based cohort study using the Surveillance Epidemiology and End-Results (SEER) Database. Patients diagnosed with EAC between 1988 and 2020 were included. Incidence trends, clinical characteristics, treatment patterns, and relative survival were systematically analyzed. ResultsThe overall age-standardized incidence rate of EAC significantly increased from 1.7 per 100000 persons in 1988 to 3.6 per 100000 persons in 2020. There were no significant changes in the distribution of age group, sex, and primary site of EAC over time. However, the proportion of EAC clinically staged as I or II decreased from 35.1 % to 27.9 %. Over time, palliative chemotherapy in metastatic EAC increased from 26.7 % to 41.3 %, combination therapy was still the main treatment strategy for nonmetastatic EAC. Despite the 5-year survival rate was less than 20 %, 1-year survival has experienced a moderate increase from 46.7 % to 53.7 %. Specifically, 1-year survival rate for nonmetastatic EAC undergoing surgery only experienced a significant increase from 80.2 % in 2004–2006 to 94.7 % in 2019–2020. For metastatic EAC, obvious improvement in 1-year survival rate was observed in those treated with systematic therapy (from 26.6 % in 2004–2006 to 41.2 % in 2019–2020). In the multivariable analysis, older age, male sex, lower household income, living without a partner, advanced TNM stage, and receiving no cancer treatment were significantly associated with poor survival. ConclusionIn summary, this population-based study of EAC patients in the US showed an increase in incidence, a shift in treatment modalities for metastatic EAC, and moderately improved 1-year survival. The search for more effective surveillance and treatment strategies should be continued in the future.

Polyoxometalate-embedded copper-organic network as dual-site synergetic catalyst for the selective oxidation of benzylic C−H bond

Selective activation and oxidization of inert C−H bonds into value-added chemicals affords attractively economic and ecological benefits, as well as central challenge in modern synthetic chemistry. Herein, by integrating the redox polyoxometalate (POM) centers and multinuclear copper sites in one system, four compounds were constructed with formulas of [Cu2(μ2-Cl)(H2O)2L3][PM12O40]·4H2O (M = Mo for 1, W for 2), and [Cu4(μ2-OH)4L2] [H3PM11CuO40]·12H2O (M = Mo for 3, W for 4, L = 1,4-di[4H-1,2,4-triazol-4-yl]-benzene). Both compounds 1–2 exhibited 3-D POM-embedded supramolecular networks constructed by discrete [PM12O40]3− clusters and binuclear {Cu2(μ2-Cl)(N–N)2} unit-based metal-organic sheets. While compounds 3–4 displayed 3-D POM-supported supramolecular networks composed of monosubstituted Keggin-type anions [H3PM11CuO40]4− and {Cu2(μ2-OH)(N–N)2} chain-based metal-organic layers. Four crystalline structures with distinct dual-active site distribution showed significant peroxidase-like activities owing to the collaborative catalysis of multinuclear copper units and polyanionic clusters, which can smoothly catalyze the C−H bond oxidation of diphenylmethane to benzophenone with ca. 97 % conversion and >98 % selectivity within 24 h. Notably, the monosubstituted [H3PM11CuO40]4−-based compounds 3−4 showed higher catalytic activities than [PM12O40]3−-based compounds 1−2 (88 % conversion and >97 % selectivity within 12 h). This kind of crystalline structures also showed good recoverability. The synergetic reaction mechanism was also explored. This work provides a new strategy to design robust heterogeneous POM-based synergetic catalysts for C−H bond functionalization.

Is naloxone where it needs to be? Using spatial analytics to examine equitable distribution of community-based naloxone sites

BackgroundOne of the most effective harm reduction services for preventing opioid overdose deaths is naloxone. Given the ongoing opioid crisis, which has led to a surge in overdose deaths across the country, expanding access to naloxone is critical. Community-based naloxone distributions sites in Palm Beach County can increase access to naloxone. However, several rural and disadvantaged regions rarely have any type of access to naloxone. The purpose of this descriptive paper is to examine the spatial distribution of and evaluate equitable accessibility to community-based naloxone sites in Palm Beach County. MethodsWe examined health equity in the distribution of community-based naloxone sites using a mixed-methods approach with ArcGIS Pro version 3.0, which is a geographic information system (GIS) software used for mapping, spatial analysis, and data visualization. ResultsThe Belle Glade region was identified as the location most adversely affected with health inequities and limited accessibility to naloxone distribution sites, as it ranked in the 100 % percentile for all social vulnerability index (SVI) themes. The 30-minute drive-time area calculated a county service area of 1885.3 km2 (km2), which covers about 34 % of the 478.0 km2 land area of census tracts. Drive-time areas did not account for periods of heavier traffic such as during rush hour. Maximum distances during heavier traffic may be smaller, thus decreasing accessibility to naloxone distribution sites. ConclusionThere is a need for effective policy-led strategies tailored to expanding our understanding of the challenges that are experienced by the individuals in need of naloxone and encountered by the distribution sites themselves, as accessible naloxone is crucial for preventing nonfatal and fatal overdoses and ensuring timely emergency responses in vulnerable communities.

Boosting oxygen storage capacity of Fe-Cu bimetallic catalysts through sulfide modification for efficient and selective molecular oxygen activation

Molecular oxygen (O2), a reactive oxygen species precursor, has great potential for water purification, but its spin-forbidden resistance hinders its direct involvement in the redox reactions of organic compounds under mild ambient conditions. In this study, a facile strategy was employed to synthesize sulfide-modified Fe-Cu bimetallic catalysts (FeCu-S) to enhance the activation efficiency of O2. The results showed that the FeCu-S material exhibited a tenfold increase in O2 activation compared to that of the control group, primarily attributed to the increased specific surface area of the catalysts with an optimized Fe/Cu site distribution and promoted generation of Cu-containing crystalline phases (e. g., CuFeS2 and CuO) to significantly enhanced the oxygen storage capacity. Moreover, such Cu-containing crystalline phases strengthened surface electron transfer, thus remarkably promoting the selective generation of singlet oxygen (1O2) for sulfamethoxazole (SMX) degradation. The FeCu-S/O2 system maintained high activity after the fifth recycle with stable reaction pH and negligible leaching of Cu and Fe ions, also exhibited great performance in the advanced treatment of the real biological effluent and ultrafiltration effluent from landfill leachate, confirming its great potential for practical water purification applications.

Is there a bias in the codon frequency corresponding to homo-repeats found in human proteins?

It is well known that there is a codon usage bias in genomes, that is, some codons are observed more often than others. Codons implicated in the homo-repeats regions in human proteins are no exception. In this work, we analyzed the codon usage bias for all amino acid residues in homo-repeats larger than 4 in 3753 human proteins from 20447 protein sequences from the canonically reviewed human proteome. We have discovered that almost all homo-repeats in the human proteome, most of which encode Ala, Glu, Gly, Leu, Pro, and Ser (∼80% of all homo-repeats), have a codon usage bias, i.e. are mainly encoded by one codon. Moreover, there is a strong shift in homo-repeats in favor of the content of GC rich codons. Homo-repeats with Ala, Glu, Gly, Leu, Pro, and Ser predominate in the PDB, which has both ordered and disordered status. Examining the distribution of splicing sites, we found that about 15% of homo-repeats either contain or are located within 10 nucleotides of the splicing site, and Glu and Leu predominate in these homo-repeats. Our data is important for future study of the functions of homo-repeats, protein-protein interactions, and evolutionary fitness.

A data-driven model for the field emission from broad-area electrodes

Electron emission from cathodes in high field gradients is a quantum tunneling effect. The 1928 Fowler–Nordheim field emission (FE) equation and the 1956 Murphy–Good FE equation have traditionally been key in describing cold field emissions, offering estimates for emitters for almost a century. Nevertheless, applying FE theory in practice is often constrained by the lack of data on the distribution and geometry of the emission sites. Predictions become more challenging with an uneven electric field distribution at the cathode surface. Consequently, FE formulations are frequently calibrated using current–voltage data after test, limiting their efficacy as true predictive models.This study develops an alternative model for field emission using a data-driven predictive approach based on (1) vast experimental data, (2) electrostatic simulations of the cathode surface, and (3) detailed material and geometry properties, which together overcome these limitations. The objective of this work is to develop and harness this comprehensive dataset to train a machine learning model capable of providing precise predictions of the cathode current in order to further the understanding and application of field emission phenomena. More than 259 h of experimental data have been processed to train and benchmark some of the well-known machine learning models. After two stages of optimization, a coefficient of determination >98% is achieved in the prediction total field emission current using ensemble models.