Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.

In addition to provide an extremely clean environment for primary loop of high-temperature gas-cooled reactor (HTR), the primary helium circulator (PHC) using electromagnetic levitation technology also provides an effective means for vibration control. Besides synchronous vibration produced by mass imbalance and sensor runout, double-frequency vibration produced by unbalanced magnetic pull (UMP) is serious in PHC engineering prototype (PHC-EP). In this paper, we firstly analyzed the mechanism of UMP and the multi-frequency vibration characteristics in combination with the PHC-EP. Then we put forward a distributed iterative learning control (ILC) algorithm and a parallel control scheme to suppress the periodic vibrations. Finally, we verified the methods by carrying out experimental researches on the active magnetic bearing (AMB) bench of PHC-EP. The results show that the methods put forward in this paper have significant control effect on the double-frequency vibration generated by UMP of the PHC-EP, and provide theoretical and practical references for the PHC safe operation in HTR.

The Ni-Co-Cr-W-Mo system is critical for the design of nickel-based super-alloys. This system stabilizes different topologically close packed (TCP) phases in many of the commercially super-alloys with high W and Mo contents. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), and thermodynamic calculations are applied to investigate the thermodynamics of the precipitates in two different W content Ni-Co-Cr-W-Mo super-alloys. Computational thermodynamics verified experimental observation of the f u phase formation as a function of temperature and alloy chemistry, but the kinetics for the precipitation of M6C phase do not agree with the experimental findings. The major precipitates of alloy 1 at temperatures 700 and 750 °C during long time exposure are M23C6, γ′ phase, and MC, and alloy 2 are M23C6, γ′ phase, MC, M6C and u phase. The W addition is found to promote the precipitation of M6C and u phase during exposure. The M6C has higher W and lower Ni content than that of u phase, meanwhile, M6C is an unstable phase would transform into M12C after 5000 h exposure at 750 °C. A great quantity of needle-like u phases precipitated after exposure at 750 °C for 5000h, which have no effect on the impact property of alloy 2.

Chitosan (CS) nanoparticles are under investigation for a wide range of applications in nanomedicine. The structural, molecular and physicochemical properties of chitosan nanoparticles have a direct bearing on their efficacy in drug conjugation and delivery, gene delivery, and tissue engineering. Herein we report on the structural, morphological and molecular properties of chitosan nanoparticles synthesized using the ionic gelation method with the intended purpose of being used for drug delivery. The chitosan nanoparticles (CS-NPs) were prepared in the 0.25 to 1.0% w/v concentration range, whereas separate samples of the 1.0% w/v CS-NPs were also functionalized with polyethylene oxide (PEO) alone and with a diblock copolymer of PEO and polypropylene glycol (PPG). The average size of the CS-NPs was determined from TEM imaging to be in the range of 11.3 to 14.8 nm. The XRD and TEM analyses show that the CS-NPs have semi-crystalline structure with the degree of crystallinity depending upon the nature of synthesis. Our results show that functionalizing the 1.0% w/v CS-NPs with PEO increases the degree of crystallinity whereas functionalizing with the diblock copolymer PEO - PPG results in a significant increase in their degree crystallinity. The CS/TPP concentration (CS:TPP fixed at 1:1 ratio) had no apparent effect on the degree of crystallinity of the CS-NPs. The results from the FTIR analysis confirm incorporation of TPP with CS in the CS-NPs. Additionally, FTIR analysis shows an enhancement of hydrogen bonding that is consistent with the increase in the degree of crystallinity of the CS-NPs.

Amyloid-beta plays an important role in the pathogenesis of Alzheimer’s disease. Aberrant amyloid-beta and tau accumulation induce neuroinflammation, cerebrovascular alterations, synaptic deficits, functional deficits, and neurodegeneration, leading to cognitive impairment. Animal models recapitulating the amyloid-beta pathology such as transgenic, knock-in mouse and rat models have facilitated the understanding of disease mechanisms and development of therapeutics targeting at amyloid-beta. There is a rapid advance in high-field MR in small animals. Versatile high-field magnetic resonance imaging (MRI) sequences such as diffusion tensor imaging, arterial spin labelling, resting-state functional MRI, anatomical MRI, MR spectroscopy as well as contrast agents have been developed for the applications in animal models. These tools have enabled high-resolution in vivo structural, functional, and molecular readouts with a whole brain field-of-view. MRI have been utilized to visualize non-invasively the amyloid-beta deposits, synaptic deficits, regional brain atrophy, impairment in white matter integrity, functional connectivity, cerebrovascular and glymphatic system in animal models of amyloidosis. Many of the readouts are translational in clinical MRI in the brain of patients with Alzheimer’s disease. In this review, we summarize the recent advance of using MRI for visualizing the pathophysiology in amyloidosis animal model. We discuss the outstanding challenges in brain imaging using MRI in small animal and propose future outlook in visualizing amyloid-beta-related alterations in brain of animal models.

Animal models of Alzheimer’s disease amyloidosis that recapitulate cerebral amyloid-beta pathology have been widely used in preclinical research, and have greatly enabled the mechanistic understanding of Alzheimer’s disease and the development of therapeutics. Comprehensive deep phenotyping of the pathophysiological and biochemical features in these animal models are essential. Recent advances in positron emission tomography have allowed the non-invasive visualization of the alterations in the brain of animal models as well as in patients with Alzheimer’s disease, These tools have facilitated our understanding of disease mechanisms, and provided longitudinal monitoring of treatment effect in animal models of Alzheimer’s disease amyloidosis. In this review, we focus on recent positron emission tomography studies of cerebral amyloid-beta accumulation, hypoglucose metabolism, synaptic and neurotransmitter receptor deficits (cholinergic and glutamatergic system), blood-brain barrier impairment and neuroinflammation (microgliosis and astrocytosis) in animal models of Alzheimer’s disease amyloidosis. We further propose the emerging targets and tracers for reflecting the pathophysiological changes, and discuss outstanding challenges in disease animal models and future outlook in on-chip characterization of imaging biomarkers towards clinical translation.

In recent years, cerium dioxide (CeO2) has attracted considerable attention owing to its remarkable performance in various applications, including photocatalysis, fuel cells, and catalysis. This study explores the effect of nickel (Ni) doping on the structural, thermal, and chemical properties of CeO2 nanorods, particularly focusing on oxygen vacancy-related phenomena. Utilizing X-ray powder diffraction (XRD), alterations in crystal structure and peak shifts were observed, indicating successful Ni doping and the formation of Ni2O3 at higher doping levels, likely due to non-equilibrium reactions. Thermal gravimetric analysis (TGA) revealed changes in oxygen release mechanisms, with increasing Ni doping resulting in the release of lattice oxygen at lower temperatures. Raman spectroscopy corroborated these findings by identifying characteristic peaks associated with oxygen vacancies, facilitating the assessment of Ni doping levels. Overall, this study underscores the substantial impact of Ni doping on CeO2 nanorods, shedding light on tailored catalytic applications through modulation of oxygen vacancies while preserving the nanorod morphology.

In this work, satellite data from the Clouds and Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments is analyzed to determine how the global absorbed sunlight and global entropy generation rate have changed during the time period from 2002 to 2023. The data is used to test hypotheses derived from the Maximum Power Principle (MPP) and Maximum Entropy Production Principle (MEP) about the evolution of earth’s surface and atmosphere. The results indicate that the amount of absorbed sunlight has increased over the last 20 years but rising surface temperatures have caused the entropy generation rate to remain approximately constant despite that decrease in albedo. The results are simpler to explain using the MPP but do not completely rule out the MEP. Given the acceptance of the MPP or MEP, some extensions and nuances are discussed.

Alzheimer’s disease (AD) poses a significant public health challenge due to its irreversible and progressive nature while lack of a cure. As a potential strategy to combat AD, its prevention becomes increasingly attractive. Mild Cognitive Impairment due to AD (MCI-AD) represents a critical transitional stage between normal age-related cognitive decline and more severe AD conditions, occurring just before dementia onset. Unfortunately, there is currently no established animal model that accurately recapitulates MCI-AD characteristics. While many laboratories have traditionally used normally aged wild-type animals as experimental models, this approach falls short in representing the inherently worse state of MCI-AD compared to normal aging. To address this gap, we introduce an animal model—a transgenic mouse line with genetic inactivation of G protein-coupled receptor kinase-5 (GRK5), commonly known as the GRK5 knockout (GRK5KO) mouse. These GRK5KO mice exhibit amnesia, cognitive deficits, increased β-amyloid levels, neurofibrillary tangle (NFT) immunopositive axonopathy, and hippocampal neurodegenerative changes. Importantly, these pathological alterations predominantly impact the entorhinal, transentorhinal, and hippocampal cortices, aligning with human MCI-AD criteria and Braak stage II of human AD progression. Notably, female GRK5KO mice show approximately 2.5 times more NFT-positive axonopathy than males, mirroring the higher prevalence of AD cases in women. Collectively, existing data strongly supports the GRK5KO mouse as a qualified animal model for studying MCI-AD.

In this research, catalytic steam reforming acetic acid derived from the aqueous portion of bio-oil for hydrogen production was investigated by using different Ni/ATC (Attapulgite Clay) catalysts prepared by precipitation, impregnation and mechanical blending methods. The fresh and reduced catalysts were characterized by XRD, N₂ adsorption-desorption, TEM and H₂-TPR. The comprehensive results demonstrated that the interaction between active metallic Ni and ATC carrier was significantly improved in Ni/ATC catalyst prepared by precipitation method, and in which the mean Ni particle size was the smallest (~13 nm) resulted in the highest metal dispersion (7.5%). The catalytic performance of the three catalysts was evaluated through the process of steam reforming of acetic acid in a fixed-bed reactor under atmospheric pressure at two different temperatures, such as 550 ℃ and 650 ℃. Results showed that the Ni/ATC (PM-N/ATC) prepared by precipitation method, achieved the highest H₂ yield of ~82% and little lower acetic acid conversion efficiency of ~85% than that (~95%) of Ni/ATC (IM-NATC) prepared by impregnation method. In addition, the deactivation catalysts after reaction for 4 h were analyzed by XRD, TGA-DTG and TEM, which demonstrated that the catalyst deactivation was not caused by the amount of carbon deposition, but owed to the significant agglomeration and sintering of Ni particles in the carrier.

In a global context, the story of the Jesuit compound in Shanghai, since its establishment by French Jesuits in 1847, reflected not only conflicts between rival powers in Europe but also the fight for their interests in the Eastern world. The Pope, who was stuck without legal status in the Vatican after 1861, was also seeking the chance to save the authority of the Church in the face of questions regarding the extent of his temporal power and the status of Rome in the context of Italian unification. As in the Reformation, a break-through in the east seemed to offer a solution for losses in Europe. However, the Jesuits to the East in the late 19th century were not only troops working and fighting on behalf of the Pope; their identities under the French Protectorate added complexity to an already complicated story involving not just the Church, but the course of world history.The female Catholic orders at the east bank of Zi-ka-wei compound became a unique window to approach the complexity.

GbtXyl43A, a β-xylosidase that is isolated from Geobacillus thermoleovorans IT-08 and grouped in GH43 family. The substitution of 121Asp residue with Asn in GbtXyl43A caused decrease the enzyme activity. The aim of this study, determine the kinetic characteristics of wild-type GbtXyl43A and D121N variant using Vmax, KM, kcat, and kcat/KM. These parameters indicated catalytic mechanism of GbtXyl43A and its derivative. All of them were produced in Escherichia coli BL21 star. The purification of wild-type GbtXyl43A using affinity chromatography, but D121N variant also required anion-exchange chromatography. The specific activity of wild-type GbtXyl43A and D121N variant were 0.471 U mg-1 in purity level 55,44 and 0.012 U mg-1 in purity level 2,407, respectively. Both enzymes had same molecular weight, ~58 kDa. The kinetic parameters of wild-type GbtXyl43A were KM: 2.845 mM, kcat: 0.033 s-1, Vmax: 0.0033 mM min-1and kcat/KM: 0.0115 s-1mM-1. Furthermore, the KM, kcat, Vmax, and kcat/KM values of D121N variant were 4.565 mM, 1.01 × 10-4 mM min-1, 0.140 × 10-4 s-1, and 0.0307 s-1mM-1, respectively. The KM value of the D121N variant was higher than its wild type and showed the affinity of D121N variant was lower than GbtXyl43A

Recently, research on ultra-high-performance concrete (UHPC) with the characteristics of ultra-high strength, high toughness, and high durability has been actively conducted from materials to actual structural applications. However, research on experimental methods that reflect the unique characteristics of UHPC, which are different from those of normal concrete, is insufficient. To solve the difficulties in applying the compressive creep test method for normal concrete to UHPC and to verify the validity of the recently proposed ASTM C 1856 standard test method, this study performed compressive creep tests on UHPC with variables of specimen size, sustained load intensity, fiber length, and strain measuring method. Two types of cylindrical specimens of ϕ100 × 200 mm and ϕ75 × 150 mm were used for a specimen size variable. The sustained load intensities of 10% to 40% based on the specified compressive strength of 150 MPa were applied. Two types of steel fiber lengths of 13 mm and 19.5 mm in the UHPC mix were used as a variable, and three strain measuring methods of the embedded strain gauge method, the attached strain gauge method, and the strain meter with stud measured the change in length of the UHPC specimens. The experimental results showed that the strain meter method using the standard rod had limitations due to the error in the verification process using the standard rod and the observation error of the measurer, and the sustained load intensity is preferable to 15% to 40% of the actual compressive strength. It was found that it is possible to perform a compressive creep test for UHPC using a specimen with a size of ϕ75 mm or more, and the fiber length did not affect the creep behavior of UHPC up to 19.5 mm. As a result of comparing the UHPC creep test results with the creep prediction model, the B3 model was found to most accurately predict the UHPC creep behavior. The creep coefficient pattern of the B3 model was very similar to the measured results, and well reflected the effects of the mixing ratio and compressive strength of UHPC.

The article focuses on the galvanic replacement synthesis of Ti-Ni and Zr-Ni metal systems with the "core-shell" structure which are potential precursors for intermetallics. The authors defined the effective synthesis parameters and the formation features of polymetallic systems character-ized by granulometric, phase and elemental composition. The X-ray fluorescence and X-ray phase analysis methods showed that the deposition of nickel on dispersed titanium and zirconium leads to the production of test samples with phase composition representing a mechanical mixture of Ni and Ti, Ni and Zr. The method of X-ray fluorescence analysis showed that the presence of hy-drofluoric acid with a 0.5-1.5 M concentration results in the formation of fixed quantitative ratios of elements in the precipitate, which allows the quantitative composition of dispersed systems "titanium - nickel", "zirconium - nickel" to be regulated within a relatively wide range. Scanning electron microscopy proved that all synthesized systems are characterized by a highly porous structure that follows the titanium and zirconium particle surface contour and the presence of spherical nanoscale subunits on the formed particle surface.

The paper provides a discussion on the results of studies of the effect exerted by combined degradation factors typical of four types of wear: abrasion, impact-abrasion, tribocorrosion, and impact-abrasion-corrosion, conducted for chain wheels made of Ni-Cu alloyed Austempered Ductile Iron. The studies consisted in determining the content of retained austenite in the structure of the cast irons in question, establishing the measures of wear following wear testing, and identifying basic surface degradation mechanisms observed in the chain wheels tested following multifactorial wear processes. The chain wheels made of ADI were found to have sustained the greatest damage under the impact-abrasion-corrosion (three-factor) wear scenario, while the wear was least advanced in the abrasion (one-factor) wear case. Another observation derived from the studies is that the combined effect of dynamic forces, corrosion, and quartz sand-based abrasives causes increased surface degradation in the cast iron grades taken into consideration compared to processes characterised by a reduced number of degradation factors (i.e. one- or two-factor wear processes). Additional hardness tests and XRD analyses have revealed a distinctive effect attributable to combined degradation factors on the surface hardness increase value and implied that bench testing was followed by phase transition.

Two interesting compounds such as quaternary ammonium lignin(QAL) and 2-ethylhexyl phosphoric acid mono-2-ethylhexyl ester (P507) were synthesized as ionic liquids(QP-ILs) for the extraction of metal ions. The extraction behavior of Co(II) and Ni(II) from chloride solution was compared between QP-ILs and P507. The results showed that the extraction rates of Co(II) and Ni(II) in the two solutions varied with the extraction conditions, but QP-ILs has stronger extractability for cobalt than P507, while Ni is on the contrary. Under the same conditions, the Co/Ni separation performance(βCo/Ni) in QP-ILs is superior to that in p507. At pH4.0, 55℃, concentration of 20%, extraction time of 10 minutes, the βCo/Ni of QP-ILs reached to 2703, while that of P507 was only 164. In conclusion, QP-ILs was more efficient than P507 for separating Co from mixed solutions.

The effect of current density of electrodeposition on the morphology, hardness, and corrosion resistance of the Ni coatings and Ni-Al2O3 coatings on Q345 steels were investigated. The surface of Ni coatings exhibited the cellular structure, while the surface of Ni-Al2O3 composite coatings showed the finer protrusions structure. The thickness of all coatings increased as the current density of electrodeposition increased from 1.5 A/dm2 to 3.0 A/dm2. After coating, the hardness and corrosion resistance of the Q345 steels were significantly enhanced. Furthermore, for the Ni coatings and Ni-Al2O3 coatings, the highest hardness and best anticorrosion property were obtained at 2.5 A/dm2 of electrodeposition current density. Compared with the Ni coatings, the co-deposition of Al2O3 nanoparticles improved the hardness of Ni-Al2O3 coating due to the second phase strengthen, but reduced the thickness and corrosion resistance due to more defects caused by the coelectrodeposition of the Al2O3 particles.

The disparity between software design and implementation, especially concerning IoT security and forensics, often lacks clarity and precision. Formal languages, rooted in mathematical rules, logic, and symbols, have proven priceless for expressing specifications and verifying system designs. Various semi-formal and formal languages, such as JSON, XML, predicate logic, and regular expressions, along with formal models like Turing machines, cater to specific domains. This paper introduces a novel formal language, named ObTFL (Object Transaction Formal Language), initially developed for IoT forensics and authentication purposes but later extended to encompass general distributed systems. The paper elucidates the syntax and semantics of ObTFL and presents several case studies showcasing its versatility and effectiveness.

A derivative series of 3,4-dimethoxy-β-nitrostyrene were synthesized and identified including new compound 6. The effect of antimicrobial activity of 3,4-alkyloxy modification of β-nitrostyrene was investigated. A molecular docking was also performed to obtain information about their interactions with Protein Tyrosine Phosphatase 1B (PTP1B). PTP1B containing cysteine 215 and arginine 221 as essential active residues plays a key role in signaling pathways that regulate various cell functions of microorganisms, which also act as negative regulator in signaling pathways of insulin that are involved in type 2 diabetes and other metabolic diseases. Compound 5 and 6 were the most potent as fragment of PTP1B inhibitor based on molecular docking, but compound 5 was more effective against Candida albicans. These compounds interact with serine 216 and arginine 221 residues. However, further research is needed to investigate their potential medicinal use.

Cohesion in the refractory metals Cr, Mo, and W is phenomenologically described in this work via a n-body energy functional with a set of physically motivated parameters that were optimized to reproduce selected experimental properties characteristic of perfect and defective crystals. The functional contains four terms accounting for the hard-core repulsion, the Thomas-Fermi kinetic energy repulsion and for contributions to the binding energy of s and d valence electrons. Lattice dynamics, molecular statics, and molecular dynamics calculations show that this model describes satisfactorily thermodynamic properties of the studied metals whereas, unlike other empirical approaches from the literature, predictions of phonon dispersion relations and of surface and point defect energetics reveal in fair good agreement with experiments. These results suggest that the present model is well adapted to large-scale simulations and whenever total energy calculations of thermodynamic properties are unfeasible

When developing bone implants Young's modulus is one of the primary characteristics of the material that should be considered. The study focuses on the possibility of regulating the modulus of the alloy Ti-50.8 at % Ni by varying its initial structure as well as aging-induced microstructure in a wide range. Microstructure observations were performed using TEM and SEM observations. The calorimetric studies of martensitic transformations were carried out using "Mettler Toledo 822e". Tensile tests were performed in a test temperature range of ‒196≤T≤+100°C using an «IN-STRON 5966». The grain/subgrain size of B2-austenite strongly affects the modulus magnitude. This effect is ambiguous for a material with a grain size of 0.13–3 µm and depends on the test temperature. The effectiveness of aging on the modulus reduction depends on the initial structure: it is most pronounced in an alloy with a relatively coarse grain size of 9 µm and brings a decrease by 3.8 times at a temperature of 37°C. Bone-like elastic modulus (10–30 GPa) at a human body temperature of 37°C is realized in an aged fine-grained NiTi alloy. An ultrafine-grained sub-structure exhibits he same values of Young's modulus in the temperature range from -100°С to 25°С.

In the paper, the authors survey integral representations of the Catalan numbers and the Catalan–Qi function, discuss equivalent relations between these integral representations, supply alternative and new proofs of several integral representations, collect applications of some integral representations, and present sums of several power series whose coefficients involve the Catalan numbers.

The bipartite entanglement is comprehensively investigated in the mononuclear molecular complex (Et3NH)[Ni(hfac)2L], where HL denotes 2-(2-hydroxy-3-methoxy-5-nitrophenyl)-4,4,5,5-tetramethyl-4,5-dihydro-1H-imidazol-3-oxide-1-oxyl and hfacH stands for hexafluoroacetylacetone. From the magnetic point of view, the molecular compound (Et3NH)[Ni(hfac)2L] consists of an exchange-coupled spin-1 Ni2+ magnetic ion and a spin-12 nitronyl-nitroxide radical substituted nitrophenol. The nickel-radical molecular complex affords an experimental realization of a mixed spin-(12, 1) Heisenberg dimer with a strong antiferromagnetic exchange coupling J/kB= 505 K and two distinct g-factors gRad=2.005 and gNi=2.275. By adopting this set of magnetic parameters we demonstrate that the Zeeman splitting of a quantum ferrimagnetic ground-state doublet due to a weak magnetic field may substantially reinforce the strength of bipartite entanglement at low temperatures. The molecular compound (Et3NH)[Ni(hfac)2L] maintains sufficiently strong thermal entanglement even at room temperature, vanishing only above 546 K. Specifically, the thermal entanglement in the nickel-radical molecular complex retains approximately 40% of the maximum value corresponding to perfectly entangled Bell states at room temperature, which implies that this magnetic compound provides suitable platform of a molecular qubit with potential implications for room-temperature quantum computation and quantum information processing.

Multi-level direct networks fueled by the evolving technology of active optical cables and increasing pin-bandwidth achieve reduced diameters and cost, with high-radix switches. These networks, like Dragonfly, are becoming the preferred aspirants for extreme high-performance parallel machines such as exa-scale computing. In this paper, we introduce a Hyper Z-Tree topology, which deploys the Z-Tree, a variant of fat-tree, as a computing node of a Generalized Hypercube (GHC) configuration. The resulting configuration provides higher bisection bandwidth, lower latency for some applications and higher throughput. Furthermore, the levels of the fat tree offer several path diversities across the GHC dimensions, hence conceding a more fault tolerant architecture. To profit from these path diversities, we propose two adaptive routing algorithms, which are extensions to the routing algorithm suggested in HyperX topology. These two algorithms exhibit better latencies and throughput than the HyperX.

We consider the second order differential equation y'' + ω^(2)ρ(x)y = 0 where ω is a positive parameter. The principal concern here is to find conditions on the function ρ^(−1/2)(x), which ensure that the consecutive differences of sequences constructed from the zeros of a nontrivial solution of the equation are regular in sign for ω sufficiently large. In particular, if c_(νk)(α) denotes the k-th positive zero of the general Bessel (cylinder) function C_(ν)(x; α) = J_(ν)(x) cos α−Y_(ν)(x) sin α of order ν, and if |ν| < 1/2, we prove that (−1)^(m)∆^(m+2)c_(νk)(α) > 0 (m = 0, 1, 2, ...; k = 1, 2, ...), where ∆a_(k) = a_(k+1) − a_(k). This type of inequalities was conjectured by Lorch and Szego in 1963. We also show that the differences of the zeros of various orthogonal polynomials with higher degrees possess the sign-regularity.

In the paper, the authors find two explicit formulas and recover a recursive formula for the generalized Motzkin numbers. Consequently, the authors deduce two explicit formulas and a recursive formula for the Motzkin numbers, the Catalan numbers, and the restricted hexagonal numbers respectively.

Forests are critical in regulating the world’s climate and they maintain overall Earth’s energy balance. The variability in forest canopy structure, topography and underneath vegetation background condition creates uncertainty in the estimation and modelling of Earth’s surface radiation particularly for boreal regions in high latitude. We studied seasonal variation in surface reflectance with respect to land cover classes, canopy structures, and topography in a boreal region of Alaska by fusing together Landsat 8 surface reflectance and LiDAR-derived canopy matrices. Our study shows that canopy structure and topography interplay and influence surface reflectance in a complex way particularly during the snow season. Topographic aspect and elevation control vegetation growth, type and structure. The southern slope is featured with more deciduous and taller trees having greater rugosity than the northern slope. Higher elevation is associated with taller trees for both vegetation types, particularly in the southern slope. In general, surface reflectance shows similar relationships with canopy cover, height and rugosity, mainly due to close relationships between these parameters. Surface reflectance decreases with canopy cover, tree height, and rugosity especially for evergreen forest. Deciduous forest shows larger variability of surface reflectance, particularly in March, mainly due to the mixing effect of snow and vegetation. The relationship between vegetation structure and surface reflectance is greatly impacted by topography. The negative relationship between elevation and surface reflectance may be due to taller and denser vegetation distribution in higher elevation. Surface reflectance in the southern slope is slightly larger than the northern slope for both deciduous and evergreen forest. The shadow effect from topography and tree crowns on surface reflectance play a different role for deciduous and evergreen forests. For deciduous forest, topographic shadow effect on surface reflectance is stronger than from tree shadowing in all seasons. For evergreen forest, shadow effects from topography and tree crowns on surface reflectance are both equally dominant, however tree shadow effect is more significant in March than in May and August. The generalized additive models (GAM) based on non-linear relationships between response (surface reflectance) and predictor (canopy structures and topography) variables confirms such observations. Our study not only provides accurate quantification of surface radiation budget but also helps in parametrization of climate change models.

The retinoblastoma (RB) transcriptional corepressor 1 (RB1) is a critical tumor suppressor gene, governing diverse cellular processes implicated in cancer biology. Dysregulation or deletion in RB1 contributes to the development and progression of various cancers, making it a prime target for therapeutic intervention. RB1's canonical function in cell cycle control and DNA repair mechanisms underscores its significance in restraining aberrant cell growth and maintaining genomic stability. Understanding the complex interplay between RB1 and cellular pathways is beneficial to fully elucidate its tumor-suppressive role across different cancer types and for therapeutic development. As a result, investigating vulnerabilities arising from RB1 deletion-associated mechanisms offers promising avenues for targeted therapy. Recently, several findings highlighted multiple methods as a promising strategy for combating tumor growth driven by RB1 loss, offering potential clinical benefits in various cancer types. This review summarizes the multifaceted role of RB1 in cancer biology and its implications for targeted therapy.

DNA polymerases replicate cell genomes and/or participate in the maintenance of genome integrity. DNA polymerases sharing high sequence homology with E. coli DNA polymerase I (pol I), have been grouped in Family A. Pol I participates in Okazaki fragment maturation and in bacterial genome repair. Since its discovery in 1956, pol I has been extensively studied, primarily to get deeper insights into the mechanism of DNA replication. As research on DNA polymerases advances, many novel functions of this group of polymerases are uncovered. For example, human DNA polymerase θ (a Family A DNA pol) has been shown to synthesize DNA using RNA as a template, a function typically attributed to retroviral reverse transcriptase. A heightened interest in drug discovery against pol θ has emerged due to its roles in cancer. Likewise, Pol I family enzymes also appear attractive drug-development targets against microbial infections. Development of antimalarial compounds targeting apicoplast apPOL, an ortholog of Pol I, further extends the druggability of this family of enzymes. Here, we summarize reported drug-development efforts against Family A polymerases, and future perspective regarding these enzymes as antibiotic targets. Current techniques such artificial intelligence can be used to facilitate the goal of new drugs.

In the paper, the authors establish two identities to express the generating function of the Chebyshev polynomials of the second kind and its higher order derivatives in terms of the generating function and its derivatives each other, deduce an explicit formula and an identities for the Chebyshev polynomials of the second kind, derive the inverse of an integer, unit, and lower triangular matrix, present several identities of the Catalan numbers, and give some remarks on the closely related results including connections of the Catalan numbers respectively with the Chebyshev polynomials, the central Delannoy numbers, and the Fibonacci polynomials.

Herein, we report about the monometallic Ni and bimetallic Pd-Ni catalysts supported on CeO2-Al2O3 binary oxide, which were investigated in oxy-steam reforming of methanol (OSRM). Monometallic and bimetallic supported catalysts were prepared by wet aqueous impregnation and subsequent impregnation method, respectively. The physicochemical properties of the catalytic systems were investigated using various methods such as: BET, XRD, TPR-H2, TPD-NH3, XPS and SEM-EDS techniques. It has been proven that the addition of palladium to the nickel catalyst facilitates its reduction. The activity tests performed for all catalysts confirmed the promotion effect of palladium on catalytic activity of nickel catalyst and selectivity towards hydrogen production. Both nickel and bimetallic palladium-nickel supported catalysts showed excellent stability during the reaction. Such catalytic systems are valuable for the advance of the field of fuel cell technology.

Density Functional Theory (DFT) full potential linearized augmented plane wave (FP-LAPW) method with the Modified Becke-Johnson (mBJ) approximation is used to perform spin polarised calculations of the transition metal perovskites MoScO₃ and WScO₃. Both depict half metallic behaviour with semiconducting and metallic in the minority and majority spins respectively. MoScO₃ and WScO₃ have indirect R− Γ band gaps in the minority spin channels of 3.61 and 3.82eV respectively. Moreover, they both show substantial magnetic moments of 2.99μ_B. In addition, we calculate the dielectric function, optical conductivity and the optical constants, namely, the refractive index, the reflectivity, the extinction and absorption coefficients.

In the present work, a predictive modelling and optimization with the adaptive network based fuzzy inference system(ANFIS) modelling of mechanical properties of laser-coated NB/SiC/Ni welds was studied based on Taguchi design by laser cladding. An ANFIS model based on a Sugeno type fuzzy inference system was developed for predicting the hardness properties of SiC/BN/Ni welds by laser cladding with experimental data required for network training and prediction. Based on analysis of variance, three important factors were taken as inputs for the fuzzy logic inferences, while the hardness properties was taken as the output of the ANFIS. The microstructure of welds were analysed using scanning electron microscopy with an energy dispersive X-Ray spectrometer. Highly developed leaf-like dendrites and eutectic crystals were found in some areas of the melting zone for the BN/SiC/Ni weld, which was significantly hardened. The ANFIS model based on Taguchi's design provides a better pattern of response because the predicted and experimental values were highly similar. As a result, a satisfactory result was achieved between the predicted and experimental values of hardness in laser-coated NB/SiC/Ni welds, whereby the success and validity of the method was verified.

Concerns about China’s air quality, and its impact on the important tourism industry have been on the debate in recent years. This article aims to investigate the potential effect of air pollution on direct economic impact of tourism, using the case of Beijing and Shanghai. The results indicate that air pollution negatively affects China's inbound tourism, resulting in huge loss of tourist arrivals and receipts, and Beijing suffers a greater loss in comparison with Shanghai, its loss in tourist number amounts to 1569,700 persons, equal to CNY 10264.268 million in tourism receipts, and the GDP losses ranges from CNY 20528.536 to 41057.072 across major source countries. This study provides a quantification of the impact helpful to generate a social awareness of air pollution detrimental impacts on inbound tourism and hence the economy.

Background: Coronavirus disease (COVID-19) related pneumonia is leaded by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which infects host cells through receptors named Angiotensin-converting enzyme 2 (ACE2). Smoking is thought to be related to poor disease prognosis, as a large amount of evidence highlights the negative effects of smoking on lung health and its causal relationship with various respiratory diseases. Methods: We first evaluated the role of ACE2 expression level with tobacco effect. And correlation analyses were used to identify the related genes of ACE2 both in smoker trait and human normal multi-tissues. After intersections, hub genes were later used to further GSEA and co-regulated mechanisms were explored by GeneMANIA. We used UALCAN to perform survival curves of pan-cancers included 33 types of cancers. New clinical model of top co-occurrence cancer type was constructed and validated. Results: Effected by cigarette smoking, the expression level of ACE2 expressed statistically upwards in current smokers compared with never smokers, upwards in groups after acute smoke exposed compared with normal control. But no strong evidence detected in third-hand smoke, as poor amounts of samples, only 4. A little trend of expressing upwards became in groups after third-hand smoke compared with groups after clean air exposing. 4 genes included PIR, ADH7, AKR1C2 and AKR1C3 were identified as ACE2 related genes in smoker trait and human normal multi-tissues. Then, we made the survival curves of pan-cancers in 4 genes. Brain lower grade glioma was the co-occurrence type as both ACE2, PIR and AKR1C3 had the significantly prognostic situation. Later, we made the new clinical prediction model as the C-index was 0.827 and the Area Under Curves (AUCs) of 1-year survival, 2-year survival and 3-year survival were 0.921(95%CI, 0.882-0.961), 0.911(95%CI, 0.860-0.962) and 0.878(95%CI, 0.818-0.939). In inner validation, the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.777(95%CI, 0.640-0.914), 0.916(95%CI, 0.842-0.990) and 0.888(95%CI, 0.768-1.000). In outer validation one, the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.764(95%CI, 0.672-0.856), 0.848(95%CI, 0.783-0.913) and 0.748(95%CI, 0.656-0.841). And in outer validation two the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.740(95%CI, 0.654-0.826), 0.766(95%CI, 0.688-0.843) and 0.794(95%CI, 0.721-0.866). Conclusions: In our study, we compared the ACE2 expression level between smokers and non-smokers crowds and identified associated hub genes. Then we explored the further role of hub genes in tumor fields to identify the correlation and influence between the avoidable host factors such as smoking on COVID-19 contamination and tumor. ACE2 and AKR1C3 are potential prognostic genes for brain lower grade glioma, and we created the web dynamic nomogram and encapsulation app through validations.

In this work, Al-Mo-B(CN) thin coatings were deposited by magnetron sputtering using composite metal-ceramic Al-Mo-B4C target. A metal-ceramic composite target for magnetron sputtering was fabricated by a robotic complex for detonation spraying of coatings equipped with a multi-chamber detonation accelerator. The powder composition (30Mo-30Al-40B4C) was sprayed onto the copper plate base of the composite target-cathode. The obtained cathode target with Al-Mo-B4C coating (thickness 280-300 μm) was used to deposit the Al-Mo-B(CN) coating (DC mode) on flat specimens of AISI 316 steels and silicon using equipment for magnetron sputtering UNICOAT 200. The Al-Mo-B4C coating has a lamella-type structure with inclusions of boron car-bide particles the elemental composition is evenly distributed in the material. The structure and morphology of coatings were studied using methods of optical, scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray analysis (XRD), and X-ray photoelectron spectros-copy (XPS). Mechanical and tribological properties of the Al-Mo-B(CN) thin coatings were determined using methods of nanoindentation, scratch testing, and tribological testing under fluid-free friction regime at room temperature. The Al-Mo-B(CN) coating (thickness ~ 1 μm) exhibited a dense uniform fine-grained structure with no columnar elements and were well-adherent to the substrates after deposition. Al-Mo-B(CN) coating has a amorphous structure. XPS analysis confirmed the formation of the MoB2 and AlN phase with an admixture of oxygen in the form of aluminum oxide, molybdenum oxide and boron oxide. Al-Mo-B(CN) coating possess hardness of 13 GPa, elasticity modulus of 114 GPa, elastic recovery of 45%, and friction coefficient of 0.8 against steel 100 Cr6 ball. The failure mode occurring in the tested coatings was fatigue and abrasive. The adhesion strength of Al-Mo-B(CN) coating amounted to about 11 N, and the failure mode was cohesive associated with plastic deformation and formation of fatigue cracks in the coating material.

Monometallic (Ni, Co, Cu) and bimetallic (Ni-Co, Ni-Cu) 10-20 wt. % metal containing catalysts supported on fly ash zeolite were prepared by post-synthesis impregnation method. The catalysts were characterized by X-ray powder diffraction, N2 physisorption, XPS and H2-TPR methods. Finely dispersed metal oxides and mixed oxides were detected after the decomposition of impregnating salt on the relevant zeolite support. By reduction intermetallic, NiCo and NiCu phases were identified in the bimetallic catalysts. Hydrogeoxygenation of lignocellulosic biomass-derived levulinic acid to γ-valerolactone (GVL) was studied. Bimetallic, 10 wt. % Ni, 10 wt. % Cu or Co containing fly ash zeolite catalyst showed higher catalytic activity than monometallic ones. Their selectivity to GVL reached 70-85 % at 100 % conversion. The reaction proceeds through formation of 4-hydroxy pentanoic acid, as the only intermediate compound.

ABSTRACT Background Ubiquitination plays an important role in protein post-translational processes and has been found to be involved in a number of regulatory functions including proteasome degradation, DNA repair, transcription, signal transduction, endocytosis, and sorting. As the identification of ubiquitination site is critical to furthering our understanding of the mechanism of ubiquitination, various experimental and machine learning methods have been used to conduct this task. It has been an important but challenging task to improve the accuracy of ubiquitination site prediction. In this research, we explore the possibility of improving the prediction performance of machine learning by incorporating grid search in the training process. Method We developed grid search procedures for each of six widely used machine learning methods including NB, LR, DT, SVM, LASSO, and KNN, and applied them to ubiquitination site prediction using the six PCP datasets that were previously developed. For each of the ML methods, we developed a set of values for each of the tunable hyperparameters available to the method. These sets of values then can be combined to form a large grid of hyperparameter settings, and each of these settings is used in the grid search. We integrated 5-fold cross-validation in grid search to train and test ML models and applied an additional independent validation procedure by conducting a pre-training 80-20 sample split. We evaluated the performance of the six methods by comparing them side by side for each of the six datasets. We also compared the grid search results with the results that were previously published without doing grid search. To optimize the prediction performance, we trained 1.1 million ML models in total through grid search. Results We compared the overall prediction performance of these six methods, as well as their prediction performance when working with balanced vs. imbalanced data, and large-scale vs. small-scale data. From the perspective of dataset, we find that the overall performance of every PCP dataset has been significantly improved in this study compared to the previous study, with the percentage increase of the average AUC of all six datasets ranging from 7.9% (PCP-4) up to 17.0% (PCP-1). From the perspective of method, we find that three out of four methods significantly benefit from grid search comparing to their previously published non-grid search results, with the maximum AUC improvement as high as 47% (LASSO on PCP-5), 43.3% (NB on PCP-1), and 33.7% (SVM on PCP-6). SVM overall ranks number one, followed by KNN as the number two performer based on their average AUCs on all datasets. But these two also ranked the top two (KNN 76 days and SVM 15 days) in terms of the total running time that they need to do grid search. We also find that SVM, KNN, and DT tend to handle small-scale and imbalanced datasets better, while LR, and LASSO are doing well with large-scale and balanced datasets. NB is more sensitive to data imbalance while less sensitive to the size of a dataset. Conclusions Our results show that using grid search has improved the performance of ubiquitination prediction significantly. We find that the performance of a method is closely related to its hyperparameter setting and the type of data it handles. Even though SVM is on average an outperformer, none of the methods can provide the best performance for all datasets. When sufficient computing resources are well accessible, grid search is an effective way to identify both a top performing model for a machine learning method and a suitable machine learning method for a particular dataset.

Ecological ternary cements (ECP) were perpared with powders of phosphogypsum (PG), fly ash (FA) and portland cement (PC). The evolution mechanism of the hydration product structure was characterized through macro and micro experiments.The thermodynamic characteristics of solid phase, solid solution phase and aqueous solution in process of hydration about phosphogypsum-fly ash-cement ternary cementitious system were studied based on the Gibbs-free-energy C-S-H thermodynamic model and GEM-Selektor software, and compared with experimental results. The results show that in the hydration reaction the thermodynamic interaction between mineral single-phase and hydration products plays an important role in the spatio-temporal distribution of ions in the cementitious system. The values of CaO、SiO2Hand H2Ohyd gradually increased with the increase of Ca/Si ratio, while the values of CaOext and H2OOH showed a positive proportional relationship, and the values of SiO2H and SiO2 showed an inverse proportional relationship. GEM-Selektor is accurate in the simulation calculation of the total amount of AFt and AFm mineral phases which quantitatively analysis the correlation between C-S-H gels formation and C3S with complex decomposition ion groups.

In the paper, the authors establish two identities, which can be regarded as nonlinear differential equations, for the generating function of Eulerian polynomials, find two identities for the Stirling numbers of the second kind, and present two identities for Eulerian polynomials and higher order Eulerian polynomials, pose two open problems about summability of two finite sums involving the Stirling numbers of the second kind. Some of these conclusions meaningfully and significantly simplify several known results.

Rice is consumed as a staple food by majority of the people in the world and failure in rice crop, due to any reason, poses a severe threat of starvation. Rice blast, caused by a fungus blast has been ranked among the most important plant diseases. It is by far the most threatening disease of ric crop and it is found wherever rice is grown. All of the rice blast disease management strategies that have been employed have limited success and rice blast has never been eliminated from a region in which rice is grown. Hence there is need to look for the best remedy in terms of effectiveness and organic nature of the method etc. This study was aimed to determine the plant growth promoting and biopesticidal effects of bioactive components present in a mixture of Piper caninum and Piper betle var. Nigra leaf extracts. . The extracts were applied in the field to determine their inhibition effects against blast disease, growth and yield improvement.. Extract of both the plants promoted plant growth and exhibited antifungal activity against rice blast fungus, Pyricularia oryzae. However the synergistic effect of the mixture of the two extracts exhibited greater effects than an effect of a single extract. . All treatments reduced the intensity of blast disease on week 15 with disease intensity by 7.90%. The extracts could increase plant height, the numbers of tillers, number of leaves, number of grains per panicle number of heads per panicle, and the full-grain weight hill.. The highest potential yield (t/ha) was observed in the 2% extract treatment, and all treatment results significantly differed from that of the control. The potential grain yield was 3.23 t/ha in the control, while that in the treatment ranged from 3.81 t/ha to 5.61 t/ha. The high grain yield observed with the treatment was caused by the low intensity of blast disease.

The microstructural evolution, thermodynamics and kinetics of Mo-21%Tm₂O₃ (mass fraction, %) powder mixtures during ball milling were investigated using X-ray diffraction and transmission electron microscopy. Ball milling induced Tm₂O₃ to be decomposed and then dissolved into Mo crystal. The supersaturated nanocrystalline solid solution of Mo (Tm, O) was obtained after 96 h of ball milling. The elements of Mo, Tm and O were distributed uniformly in the ball-milled particles. Based on the semi-experimental theory of Miedema, a thermodynamic model was developed to calculate the driving force of phase evolution. There was no chemical driving force to form a crystal solid solution of Tm atoms in Mo crystal or an amorphous phase because the Gibbs free energy for both processes was higher than zero. For Mo-21%Tm₂O₃, it was mechanical work, not negative heat of mixing, that provided the driving force to form supersaturated nanocrystalline Mo (Tm, O) solid solution.

Aqueous Zinc ion batteries (ZIBs) possess significant potential in large energy storage systems due to their cost-effectiveness and environmental protection. However, the limited voltage window and poor reaction kinetics of the cathode material are still bottlenecks, restricting the further development of ZIBs. In this work, we rationally design Ni-doped V2O5@3D Ni core/shell composite on carbon cloth electrode (Ni-V2O5@3D Ni@CC) by growing Ni-V2O5 on the free-standing 3D Ni metal nanonets for high-voltage and high-capacity ZIBs. Impressively, the embedded Ni doping increases the interlayer spacing of V2O5, extending the working voltage and improving the Zn2+ kinetics reaction of the cathode materials, at the same time the 3D structure with high specific surface area and superior electronic conductivity benefits to fast Zn2+ transport. Consequently, the as-designed Ni-V2O5@3D Ni@CC cathodes can operate within a wide voltage window from 0.3 to 1.8 V vs. Zn/Zn2+ and deliver a high capacity of 270 mAh g-1 at a high current density of 0.8 A g-1. In addition, the reversible Zn2+ (de)-incorporation reaction mechanisms in the Ni-V2O5@3D Ni@CC cathodes are investigated by multiple characterization methods. As a result, we achieve a big step toward the practical applications of commercial ZIBs.

This study determines the threshold for the computational rate of actuator motor controllers for unmanned underwater vehicles necessary to accurately follow discontinuous square wave commands. Motors must track challenging square-wave inputs, and identification of key computational rates permit application of deterministic artificial intelligence (D.A.I.) to achieve tracking to a machine-precision degree of accuracy in direct comparison to other state-of-art approaches. All modeling approaches are validated in MATLAB simulations where the motor process is discretized at varying step-sizes (inversely proportional to computational rate). At a large step-size (fast computational rate), discrete D.A.I. shows a mean error more than three times larger than that of a ubiquitous model-following approach. Yet, at a smaller step size (slower computational rate), the mean error decreases by a factor of 10, only three percent larger than that of continuous D.A.I. Hence, the performance of discrete D.A.I. is critically affected by the sampling period for discretization of the system equations and computational rate. Discrete D.A.I. should be avoided when small step-size discretization is unavailable. In fact, continuous D.A.I. has surpassed all modeling approaches which makes it the safest and most viable solution to future commercial applications in unmanned underwater vehicles.

By planting LEDs on the surfaces of orifice baffles, a novel batch oscillatory baffled photoreactor (OBPR) together with polymer-supported Rose Bengal (Ps-RB) beads are used to investigate reaction kinetics of a photo-oxidation reaction between α-terpinene and singlet oxygen (1O2). In the widely used NMR data analysis for this reaction, α-terpinene and ascaridole are treated as a reaction pair, assuming kinetically singlet oxygen is in excess or constant. We have, for the first time, examined the validity of the method, discovered that increasing α-terpinene initially leads to an increase of ascaridole, indicating that the supply of singlet oxygen is in excess. Applying kinetic analysis, a pseudo first order reaction kinetics is confirmed, supporting this assumption. We have subsequently initiated a methodology of estimating the 1O2 concentrations based on the proportionality of ascaridole concentrations with respect to its maximum under these conditions. With the help of the estimated singlet oxygen data, the efficiency of 1O2 utilization and the photo efficiency of converting molecular oxygen to 1O2 are further proposed and evaluated. We have also identified conditions where further increase of α-terpinene has caused decreases in ascaridole, implying kinetically that 1O2 has now become a limiting reagent, the method of treating α-terpinene and ascaridole as a reaction pair in the data analysis would no longer be valid under those conditions.

Optical power splitters play a crucial role as the fundamental building blocks for many integrated optical devices. They should have low losses, broad bandwidth, and a high tolerance to fabrication errors. Adiabatic optical power splitters inherently possess these qualities while being compatible with foundry processes well-suited for mass-production. The long device lengths of adiabatic power splitters, however, are a limiting factor to achieve compact device sizes, which must be reduced. Here, we use a polynomial taper profile optimization algorithm to design 1×2 and 2×2 adiabatic power splitters with significantly shorter lengths than their adiabatic counterparts. The best performing 1×2 and 2×2 power splitters have 20 μm and 16 μm coupling lengths, respectively. Our designs have minimum feature sizes ranging from 140 nm to 200 nm, and our measurements averaged across 9 different chips show excellent consistency in performance for devices with 180 nm and 200 nm minimum features. Both the 1×2 and 2×2 adiabatic optical power splitters have excess losses less than 0.7 dB over a 100 nm bandwidth, with a standard deviation lower than 0.3 dB. Furthermore, our measurements show greater than 20 dB extinction ratios over 130 nm bandwidth. We also demonstrate the design of 1×2 power splitters with arbitrary splitting ratios, where splitting ratios ranging from 50:50 to 94:6 were achieved with standard deviations between 2% and 6%.

University course scheduling (UCS) is one of the most important and time-consuming issues that all educational institutions face yearly. Most of the existing techniques to model and solve UCS problems have applied approximate methods, which are different in terms of efficiency, performance, and optimization speed. Accordingly, this research aims to apply an exact optimization method to provide an optimal solution to the course scheduling problem. In other words, in this research, an integer programming model is presented to solve the USC problem. In this model, hard and soft constraints include the facilities of classrooms, courses of different levels and compression of students' curriculum, courses outside the faculty and planning for them, and the limited time allocated to the professors. The objective is to maximize the weighted sum of allocating available times to professors based on their preferences in all periods. To evaluate the presented model's feasibility, it is implemented using the GAMS software. Finally, the presented model is solved in a larger dimension using a real data set from a college in China and compared with the current program in the same college. The obtained results show that considering the mathematical model's constraints and objective function, the faculty courses' timetable is reduced from 4 days a week to 3 working days. Moreover, master courses are planned in two days, and the courses in the educational groups do not interfere with each other. Furthermore, by implementing the proposed model for the real case study, the maximum teaching hours of the professors are significantly reduced. The results demonstrate the efficiency of the proposed model and solution method in terms of optimization speed and solution accuracy.

Gain-scheduled autopilots have emerged as a dominant strategy to achieve adaptive control of coupled, non-linear engineering complexities, owing to an ability to adapt to changing operational conditions and uncertainties. This study focuses on utilizing bilinear interpolation of gain-scheduled autopilots, emphasizing enhanced system performance and robustness. Through a comprehensive investigation and comparative analysis using three disparate cases, advantages over conventional methods are revealed. Strengths and weaknesses of both simple and specialized variants (such as linear, and real-time gain-scheduling) are introduced. Three missile guidance case–studies utilize simulation time and miss distance figures of merit. Potential to achieve precise control across various mission scenarios, while ensuring reduced computational complexity is revealed by nearly two–hundred percent improved missile miss distances with comparable distances traveled and slightly improved computational burden.

The present study conducts the phase analysis, microstructural characteristics, and mechanical property evaluation on the as-cast and quenched Ti-15Mo-xFe alloys with high iron content ranging from 4 to 12 weight percent. All the four alloys were produced in a button-arc melting furnace. Heat treatment in the form of solution treatment was performed in a muffle furnace at a temperature of 1100°C, with a 1-hour holding time. The samples were rapidly quenched in ice-brine. Various characterization techniques were used to analyze samples both in the as cast and quenched conditions. X-ray diffractometer (XRD) was used to analyses the phases present in each alloy whereas the optical microscope (OM) was employed to track the microstructural evolution. The mechanical properties of the alloys were evaluated using a tensile test method while the micro-Vickers hardness measurements were conducted to evaluate hardness of the alloys. OM micrographs revealed equiaxed β grains and substructures in as-cast TMF0, dendritic structure, and equiaxed β grains with pores forming around the grain boundaries in TMF1, and micrograph full of dendrites and pores was observed in the as-cast TMF2 and TMF3 alloys. The quenched TMF0 showed only β equiaxed grains whereas TMF1, TMF2, and TMF3 revealed micrographs full of equiaxed grains of β phase with pores throughout the grain boundaries. The XRD patterns of cast TMF0 showed peaks belonging to the β and orthorhombic α″ martensitic phases and the quenched sample showed the bcc β phase only. The TMF1, TMF2, and TMF3 alloys in as-cast condition indicated peaks belonging to β , α″ and intermetallic B2 TiFe phases, however, their quenched samples showed the presence of β and Fe·Ti·O2 phases in TMF2 and TMF3 alloys. The tensile properties such as ultimate tensile strength (UTS) and elastic modulus (E) of as-cast TMF0 were 264 MPa and 79 GPa and these properties changed upon quenching to 411 MPa and 66 GPa respectively. The elastic modulus of TMF1 in as-cast condition was 74 GPa. The UTS and E of TMF1, TMF2, and TMF3 in as cast and quenched conditions were not recorded due to the fragility of the samples that failed prior to yielding any useful data. The micro-Vickers hardness in as cast and quenched conditions showed a similar trend with hardness increasing slightly upon quenching for TMF0, TMF1, and TMF3 alloys but slightly decreased in the case of TMF2. 6). The fracture surfaces of TMF0 exhibited both ductile and brittle fracture in as cast and quenched conditions whereas the only brittle fracture mode was observed in the TMF1, TMF2 and TMF3 alloys in both conditions.

Automatic recognition methods for non-stationary EEG data collected from EEG sensors play an essential role in neurological detection. The integrative approaches proposed in this study consists of Symlet wavelet processing, a gradient boosting machine, and a grid search optimizer for a three-level classification scheme for normal subjects, intermittent epilepsy, and continuous epilepsy. Fourth-order Symlet wavelets were adopted to decompose the EEG data into five time-frequency sub-bands, whose statistical features were computed and used as classification features. The grid search optimizer was used to automatically find the optimal parameters for training the classifier. The classification accuracy of the gradient boosting machine was compared with that of a support vector machine and a random forest classifier constructed according to previous descriptions. Multiple-index were used to evaluate the Symlet wavelet transform-gradient boosting machine-grid search optimizer classification scheme, which provided better classification accuracy and detection effectiveness than has recently reported in other work on three-level classification of EEG data.

Although the dockless bike-sharing system, which can be regarded as a typical example of the resource-sharing system, has been increasingly popular for years with people especially in China, the imbalanced distribution of shared bikes gradually becomes a major problem for both bike-sharing companies and their customers. To solve the imbalance problem, we aim to investigate the long-term performance of a system under the influence of some key factors (with an emphasis on the unequal demand between different nodes), which can guide us to discover the causes of the problem and offer several valuable suggestions to the operators. According to the fundamental principle of a dockless bike-sharing system, we propose a model reduction method to reduce the complexity of the theoretical network models, which are developed based on the Markovian queueing theory with the consideration of higher-demand nodes and lower-demand nodes. The theoretical network models provide us with steady-state probabilities of having a certain number of bikes at one node, which are used as an important part of the optimization model for solving the imbalance problem by carrying out an operator-based relocation strategy. The objective of the optimization model is to maximize the total profit and determine the optimal relocation frequency. It is found that most of the shared bikes are possible to gather at one low-demand node eventually in the long run under the influence of the different arrival rates at different nodes, but the decrease of the number of bikes at the high-demand nodes is more sensitive to the unequal demands and may cause a great loss for operators, which should be payed attention to especially when solving the relocation problems.

As construction costs continue to rise and adequate amounts of funding continues to be a challenge, the allocation of resources is of critical importance when it comes to the maintenance and rehabilitation (M&R) of highway infrastructure. A Life Cycle Assessment (LCA) methodology is presented here that integrates realistic traffic conditions in the operational phase to compare M&R scenarios over the analysis period of a 26-km stretch of Interstate-495. Pavement International Roughness Index (IRI) were determined using AASHTO’s PavementME System. Meanwhile, vehicle fuel consumption and emission factors were calculated using a combination of Google Maps®, the U.S. EPA’s Motor Vehicle Emission Simulator, the SHRP2 Naturalistic Driving Study, and MassDOT’s Transportation Data Management System. The evaluation of pavement performance with realistic traffic conditions, varying M&R strategies and material characteristics was quantified in terms of Life Cycle Cost (LCC), Global Warming Potential (GWP) and Cumulative Energy Demand (CED) for both agencies and users. The inclusion of realistic traffic conditions into the use phase of the LCA resulted in a 6.4% increase in CED and GWP when compared to baseline conditions simulated for a week long operation duration. Results from this study show that optimization of M&R type, material selection and timing may lead to a 2.72% decrease in operations cost and 47.6% decrease in construction/maintenance costs.

This study presents the algorithm ACTION, defined as Automatic Center detection of Tropical cyclone (TC) using Image processing based on the Operational radar Network. Based on the high visibility of weather radar imagery, the TC’s motion vector is calculated from the continuous image change using optical flow, producing its rotation center as the TC’s center. The algorithm’s performance was verified for typhoons (TCs in the Northwestern Pacific) affecting the Korean Peninsula from 2018–2021 and showed a high detection rate of 80.8% within an error distance of 40 km compared to the best track of the Korea Meteorological Administration (KMA). The detection rate was 100% for typhoons with temporally consistent morphological characteristics. ACTION automatically generates TC center information upon the TC’s initial entry inside the observation radius even in the absence of uniform radar data. ACTION easily calculates using Open Source Computer Vision, performs in real time, and can be directly applied to rapidly generated weather radar images; hence, it is currently being utilized by the KMA. The high-temporal-resolution TC center information calculated through ACTION is expected to improve the efficiency of TC forecasting.

We prove general stability theorems for $n$-dimensional quartic-cubic-quadratic-additive type functional equations of the form \begin{eqnarray*} \sum_{i=1}^\ell c_i f \big( a_{i1}x_1 + a_{i2}x_2 + \cdots + a_{in}x_n \big) = 0 \end{eqnarray*} by applying the direct method. These stability theorems can save us much trouble of proving the stability of relevant solutions repeatedly appearing in the stability problems for various functional equations.

Using a theorem of Ulam and Hyers, we will prove the Hyers-Ulam stability of two-dimensional Lagrange's mean value points $(\eta, \xi)$ which satisfy the equation, $f(u, v) - f(p, q) = (u-p) f_x(\eta, \xi) + (v-q) f_y(\eta, \xi)$, where $(p, q)$ and $(u, v)$ are distinct points in the plane. Moreover, we introduce an efficient algorithm for applying our main result in practical use.

Alumina dispersion-strengthened copper, Glidcop, is used widely in high-heat-load ultra-high-vacuum components for synchrotron light sources (absorbers), accelerator components (beam intercepting devices) and in nuclear power plants. Glidcop has similar thermal and electrical properties to OFE (oxygen free electrical) copper, but has superior mechanical properties, thus making it a feasible structural material; its yield and ultimate strength are equivalent to those of mild-carbon steel. The purpose of this work has been to develop a brazing technique to join Glidcop to Mo, using a commercial Cu-based alloy. The effects of the excessive diffusion of the braze along the grain boundaries on the interfacial chemistry and joint microstructure, as well as on the mechanical performance of the brazed joints, has been investigated. In order to prevent the diffusion of the braze into the Glidcop alloy, a copper barrier layer has been deposited on Glidcop by means of RF-sputtering.

Objectives: Essential thrombocythemia (ET) is a chronic myeloproliferative neoplasm characterized by elevated platelet counts and an increased risk of thrombotic events, including ischemic strokes. Methods: We conducted a retrospective analysis of data from consecutive ischemic stroke patients with ET between March 2014 and February 2023. Results: This case series describes the clinical presentation, radiological features, and management of five patients with ET-associated ischemic strokes, all harboring the JAK2 mutation. The diverse radiological findings suggest that both large and small vessel diseases may be influenced by the prothrombotic state induced by ET. A significant elevation in platelet count was observed to correlate with the emergence of new acute infarctions in some cases. Conclusions: The study highlights combined use of antiplatelet and cytoreductive therapy in preventing secondary stroke events in patients with ET and JAK2 mutations. The heterogeneity of stroke patterns in this population necessitates a comprehensive understanding of the underlying pathophysiological mechanisms and tailored therapeutic approaches.

Bimetallic Ni/Cu core-shell and Cu-Ni heterostructural micro- and nanoparticles were prepared using two simple successive reduction procedures. Monometallic Ni and Cu particles were synthesized for comparison. The phase constitutions and morphological features of the particles were studied by means of X-ray diffraction, energy-dispersive X-ray spectroscopy and scanning electron microscopy methods. All the obtained mono- and bimetallic particles were applied as electrocatalysts in the electrohydrogenation of p-nitrophenol (p-NPh). An additional electrochemical reduction of copper cations during the hydrogen saturation of Cu-containing particles was established. Some of the prepared particles exhibited high catalytic activity with an increase in the hydrogenation rate of p-NPh by more than 3 times compared to its electrochemical reduction on the non-activated cathode, and p-NPh conversion yielded the maximum values. The main product of p-NPh electrocatalytic hydrogenation over Ni-Cu particles is p-aminophenol, which is an intermediate in the synthesis of many drugs. p-Aminophenol formation is confirmed by UV-Vis spectra.

Brain is the most complex organ in the human body and it is divided into two hemispheres - left and right hemispheres. Left hemisphere is responsible for control of right side of our body whereas right hemisphere is responsible for control of left side of our body. Brain image segmentation from different neuroimaging modalities is one of the important parts in clinical diagnostic tools. Neuroimaging based digital imagery generally contain noise, inhomogeneity, aliasing artifacts, and orientational deviations. Therefore, accurate segmentation of brain images is a very difficult task. However, the development of accurate segmentation of brain images is very important and crucial for a correct diagnosis of any brain related diseases. One of the fundamental segmentation tasks is to identify and segment inter-hemispheric fissure/mid-sagittal plane, which separate the two hemispheres of the brain. Moreover, the symmetric/asymmetric analyses of left and right hemispheres of brain structures are important for radiologists to analyze diseases such as Alzheimer's, Autism, Schizophrenia, Lesions and Epilepsy. Therefore, in this paper we have analyzed the existing computational techniques used to find brain symmetric/asymmetric analysis in various neuroimaging techniques (MRI/CT/PET/SPECT), which are utilized for detecting various brain related disorders.

This study demonstrates the successful synthesis of Ni/Y2O3 nanocomposite particles through the application of ultrasound-assisted precipitation using the Ultrasonic Spray Pyrolysis technique. The particle size was predicted accurately using a modified equation, and they were collected in a water suspension with Polyvinylpyrrolidone (PVP) as the stabiliser. The presence of the Y2O3 core and Ni shell was confirmed with Transmission Electron Microscopy (TEM) and with electron diffraction. The TEM observations revealed the formation of round particles with an average diameter of 466 nm, while the lattice parameter on the Ni particle’s surface was measured to be 0.343 nm. The Ni/Y2O3 nanocomposite particle suspensions were lyophilized, to obtain a dried material that was suitable for embedding into a Polylactic acid (PLA) matrix. The resulting PLA/Ni/Y2O3 composite material was successfully extruded successfully, so that a 3D printed technology Fused Filament Fabrication could be used further for the production of tensile test tubes. The tensile tests showed that the addition of lyophilised Ni/Y2O3 into the PLA matrix decreased the tensile strength by 21.8 %, while the tensile modulus was not influenced. Dynamic Mechanical Analysis (DMA) showed that the addition of the Ni/Y2O3 particles increased the glass transition temperature by 5 °C, and increased the storage modulus in the glass transition range significantly. These findings demonstrate the potential for utilising Ni/Y2O3 nanocomposite particles in 3D printing applications, and warrant further exploration of their mechanical properties and potential applications in various fields.

This study aims to provide an updated overview of the systematic evaluation and management of Post-Traumatic trigeminal neuropathic pain (PTTN) resulting from dental procedures or trauma. PTTN arises following an injury to the trigeminal nerve, which is responsible for sensory and motor functions in the maxillofacial region. The etiology encompasses various dental procedures and craniofacial trauma, leading to a spectrum of symptoms, from tingling to severe pain. Diagnostic challenges stem from the absence of standardized criteria and the overlap with focal neuralgia, necessitating comprehensive evaluation. Misdiagnosis can result in prolonged suffering and unnecessary procedures. Successful management hinges on prompt diagnosis and interdisciplinary collaboration, with early intervention crucial in mitigating chronicity. While nerve recovery post-trauma is challenging, preventive measures through accurate evaluation and treatment are paramount.  Management for PTTN includes non-invasive and surgical interventions. Non-invasive intervention includes systematic and local pharmacological management. This review enhances uniformity in PTTN evaluation and treatment approaches despite standardized study limitations.

Hashimoto’s thyroiditis (HT) is a common autoimmune disease, with its prevalence rapidly increasing. Both genetic and environmental risk factors contribute to the development of HT. Recently, viral infection has been suggested to act as a trigger of HT by eliciting the host immune response and subsequent autoreactivity. We analyzed features of HT through bioinformatics analysis so as to identify markers of HT development. We accessed public microarray data of HT patients from the Gene Expression Omnibus (GEO) and obtained differentially expressed genes (DEGs) under HT. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed for functional clustering of our protein-protein interaction (PPI) network. Utilizing ranked gene lists, we performed Gene Set Enrichment Analysis (GSEA) using the clusterprofiler R package. By comparing the expression signatures of the huge perturbation database with the queried rank-ordered gene list, connectivity map (CMap) analysis was performed to screen potential therapeutic targets and agents. The gene expression profile of the HT group was in line with general characteristics of HT. Biological processes related to the immune response and viral infection pathways were obtained for the upregulated DEGs. GSEA results revealed activation of autoimmune disease-related pathways and several viral infection pathways. Autoimmune disease and viral infection pathways were highly interconnected by common genes, while the HLA genes which are shared by both were significantly upregulated. CMap analysis suggested that perturbagens, including SRRM1, NLK, and CCDC92, have the potential to reverse the HT expression profile. Several lines of evidence suggested that viral infection and the host immune response are activated during HT. Viral infection is suspected to act as a key trigger of HT by causing autoimmunity. SRRM1, an alternative splicing factor, which responds to viral activity, might serve as potential marker of HT.

Muscle mass, strength and physical function are known to decline with age. This is associated with the development of geriatric syndromes including sarcopenia and frailty. These conditions are associated with disability, falls, longer hospital stay, higher readmission rates, institutionalisation, osteoporosis, and death. Moreover, they are associated with reduced quality of life, as well as substantial costs to health services around the world. Dietary protein is essential for skeletal muscle function. Older adults have shown evidence of anabolic resistance, where greater amounts of protein are required to stimulate muscle protein synthesis and therefore require higher daily amounts of dietary protein. Research shows that resistance exercise has the most beneficial effect on preserving skeletal muscle. A synergistic effect has been noted when this is combined with dietary protein, yet studies in this area lack consistency. This is due, in part, to the variation that exists within dietary protein, in terms of dose, quality, source, amino acid composition and timing. Research has targeted participants that are replete in dietary protein with negative results. Inconsistent measures of muscle mass, muscle function, physical activity and diet are used. This review attempts to summarise these issues, as well as introduce the possible role of the gut microbiome and its metabolome in this area.

This paper uses the spatial analysis software GeoDa as a tool, takes GRP (Gross regional product) of Sichuan Province in 2012 and 2018 as the dependent variable, and takes the city (autonomous prefecture) factor-driven, investment-driven and innovation-driven indicators as the dependent variable to explore the impact of innovation activities on regional economic development and the spatial distribution characteristics of regional economy. Through the comparison of the global correlation and local correlation, this paper explores the crux of the regional economic polarization and unbalanced development, and puts forward some measures to solve the existing economic development problems, such as cultivating and improving the regional industrial dependence, accelerating the regional transportation accessibility and convenience, and constructing the regional collaborative innovation system, So as to achieve the strategic goal of the construction of innovative Province in Sichuan Province.

In the paper, the authors present unified generalizations for the Bell numbers and polynomials, establish explicit formulas and inversion formulas for these generalizations in terms of the Stirling numbers of the first and second kinds with the help of the Faà di Bruno formula, properties of the Bell polynomials of the second kind, and the inversion theorem connected with the Stirling numbers of the first and second kinds, construct determinantal and product inequalities for these generalizations with aid of properties of the completely monotonic functions, and derive the logarithmic convexity for the sequence of these generalizations.

Background Tuberculosis is a type of infectious disease that can cause death if treatment is not completed. the duration of tuberculosis treatment can reach 6 to 8 months so it really requires discipline when doing treatment. This makes tuberculosis patients in dire need of health information and social support which is very helpful in providing motivation, health information, and monitoring treatment from nurses. Aim of this literature review is to provide an overview of the The Role Of Nurses In Providing Social Support In Tuberculosis Treatment: Literature Review. Method is a literature review research, this study uses electronic database searches using keywords according to research questions from the online library PubMed, Content Science, and Science Direct. Result it was found that the role of nurses in the aspect of social support, namely in providing motivation, supervision, comfort, empathy, and information. this is very necessary for patients with tuberculosis at the time of treatment. Conclution social support is needed by tuberculosis patients who are currently undergoing treatment to provide motivation, health information, and as a nurse's supervision of patient adherence to tuberculosis treatment.

This study proposed the combination system consisting of biogas dry reforming reactor and solid oxide fuel cell (SOFC). Since a biogas dry reforming is an endothermic reaction, this study adopted a membrane reactor operated due to the non-equilibrium state with H2 separation from the reaction space. This study aimed to clarify the characteristics of Ni/Cr/Ru catalyst using for a biogas dry reforming membrane reactor. Additionally, this study also investigated the comparison of the characteristics of Ni/Cr/Ru catalyst with that of Ni/Cr catalyst. The impact of operation temperature, the molar ratio of CH4 : CO2, the differential pressure between the reaction chamber and the sweep chamber and the introduction of sweep gas on the characteristics of the biogas dry reforming membrane reactor using Pd/Cu membrane and Ni/Cr/Ru catalyst was examined. The concentration of H2 using Ni/Cr/Ru catalyst was larger than that using Ni/Cr catalyst by 2871 ppmV for the molar ratio of CH4 : CO2 = 1.5 : 1 at the reaction temperature of 600 ℃ and the differential pressure of 0 MPa without a sweep gas, especially. Under this condition, CH4 conversion, H2 yield and thermal efficiency were 67.4 %, 1.77×10-2 % and 0.241 %, respectively.

The movement of liquid droplets on the energy gradient surface has attracted extensive attention. Inspired by biological features in nature, such as the periodic spindle-shaped nodes in spider silks and conical-like barbs of cacti, the structure-property-function relationship of multifunctional gradient surfaces. In this study, a series of specific patterns are fabricated by 3D printing technology, followed by modification via the atmospheric pressure plasma treatment and liquid phase chemical deposition, resulting in enhancing the ability of water droplets of 5μL to travel 18.47mm on a horizontal plane and 22.75mm against gravity up to 20° tilting angle. Additionally, analysis techniques have been employed including contact angle analyzer, ESCA and laser confocal microscope to evaluate the sample performance. This work could further be applied to many applications related to microfluidic devices, drug delivery and water/fog collection.

The influence of pore size on the toughness of Fe-Mo-Cu-C sintered and carburized components was investigated. The charpy impact value of the component made from Fe-0.4%Mo diffusion-alloyed steel powder mixed with 2%Cu powder and 0.3% graphite powder significantly increased with a decrease in pore size. The highest impact value of 17 J/cm2 was obtained at the average pore size of 12 µm. This value was 25% higher than that of the sintered and carburized component made from conventional Fe- 4%Ni-1.5%Cu-0.5%Mo alloyed steel powder called 4Ni even though the component was made from a Ni-free alloyed steel powder. The mechanism of the improvement of the impact value by pore size refinement and the influence of microstructural difference between the components made from Fe- 0.4%Mo diffusion-alloyed steel powder and 4Ni on toughness is discussed based on optical microstructural observation and crystal orientation analysis data.

This research investigated high-temperature corrosion (500 °C) of Cr-Mo steel processed using water jet peening or multifunction cavitation (MFC), and the suitability of such steel for high-temperature boilers and reaction vessels. High-temperature corrosion was induced using an embedment test and a coating test using sulfide-type K2SO4-Na2SO4 powder. To measure the relaxation of the residual stress due to the decrease in work hardening caused by an increase in specimen temperature and the difference in thermal shrinkage between the surface and interior of the specimen, a thermal cycling test was conducted. For the MFC-processed specimen, the oxide film that formed on the surface suppressed mass loss, prevented crack formation, and reduced the compressive residual stress caused by high-temperature corrosion. MFC-processed Cr-Mo steel is thus suitable for a high-temperature corrosion environment.

Objective: The purpose of this study is to compare the effects of stretching methods for flexibility, muscle activation, and pressure pain threshold in ballet dancers, and to suggest an effective stretching method. Methods: Thirty-three ballet dancers were randomized to a static stretching group (n=11), muscle energy technique stretching group (n=11), and vibration-assisted stretching group (n=11). The angle of hip joint extension in arabesque, the activation of rectus femoris in Devéloppé, and the pressure pain threshold on rectus femoris in sitting position were measured to compare the effects of different stretching methods. Results: Hip joint extension angles increased in all stretching methods (p<0.05), however, vibration-assisted stretching and muscle energy technique stretching were more effective than static stretching (p<0.05). The activation of the rectus femoris decreased in all groups (p<0.05), but the muscle energy technique stretching group and the vibration-assisted stretching group showed a significant decrease compared to the static stretching group (p<0.05). The pressure pain threshold showed significant improvement only in the static stretching group (p<0.05), and the vibration-assisted stretching group (p<0.05). Conclusion: Vibration-assisted stretching compared to static stretching and muscle energy technique stretching is a beneficial method for flexibility, muscle activation, and pressure pain threshold in ballet dancers.

The present study investigates the relationship between the local structure, photocatalytic ability, and cathode performances in sodium-ion batteries (SIBs) and lithium-ion batteries (LIBs) using Ni-substituted goethite nanoparticles (Ni_xFe_1-xOOH NPs) with a range of 'x' values from 0 to 0.5. The structural characterization was performed applying various techniques, including X-ray diffractometry (XRD), Thermogravimetry differential thermal analysis (TG-DTA), Fourier Transform Infrared Spectroscopy (FT-IR), X-ray absorption spectroscopy (XANES/EXAFS), both measured at room temperature (RT), and ⁵⁷Fe Mössbauer spectroscopy recorded at RT and at low temperatures (LT) from 20 K to 300 K, Brunauer-Emmett-Teller surface area measurement (BET), and diffuse reflectance spectroscopy (DRS). In addition, the electrical properties of Ni_xFe_1-xOOH NPs were evaluated by impedance spectroscopy. XRD showed the presence of goethite as the only crystalline phase in prepared samples with x ≤ 0.20, and goethite and α-Ni(OH)₂ in the samples with x > 0.20. Sample with x = 0.10 (Ni10) showed the highest photo-Fenton ability with a first-order rate constant value (k) of 15.8×10^-3 min^-1. The ⁵⁷Fe Mössbauer spectrum of Ni0, measured at RT, displayed a sextet corresponding to goethite, with an isomer shift (δ) of 0.36 mm s^-1 and a hyperfine magnetic distribution (B_hf) of 32.95 T. Moreover, the DC conductivity decreased from 5.52×10^-10 to 5.30×10^-12 (Ω.cm)^–1 with 'x' increasing from 0.10 to 0.50. Ni20 showed the highest initial discharge capacity of 223 mAh g^-1, attributed to its largest specific surface area of 174.0 m² g^-1. In conclusion, Ni_xFe_1-xOOH NPs can be effectively utilized as visible-light-activated catalysts and active cathode materials in secondary batteries.

Plant Cysteine Oxidase (PCO) is a plant O2-sensing enzyme of catalyzing oxidation of cysteine to Cys-sulfinic acid at the N-termini of target proteins. To better understand the Brassica napus PCO gene family, PCO genes in B. napus and related species were analyzed. In this study, 20, 7 and 8 PCO genes were identified in Brassica napus, Brassica rapa and Brassica oleracea, respectively. According to phylogenetic analysis, the PCOs were divided into five groups: PCO1, PCO2, PCO3, PCO4 and PCO5. Gene organization and motif distribution analysis suggested that PCO gene family was relatively conserved during evolution. Expression analysis showed that PCO genes were expressed in different tissues at different developmental stages. Interestingly, most of the Bna/Br/BoPCO5 members were expressed in leaves, roots, flowers, buds and siliques, suggesting an important role in both vegetative and reproductive development. Expression of BnaPCO was induced by various abiotic stress, especially waterlogging stress, which was consistent with the result of cis-element analysis. In this study, the PCO gene family of Brassicaceae was analyzed for the first time, which contributes to a comprehensive understanding of the origin and evolution of PCO genes in Brassicaceae and the function of BnaPCO in regulating plant responses to abiotic stresses.

Mesoporous silica nanoparticles (MSNs) can be used as carrier materials for the controlled release of pesticides while reducing their negative environmental impact. In this study, we screened an active ingredient, p-cymene (PC), with an excellent inhibitory effect on rice bacterial blight. Subsequently, the PC was successfully loaded onto MSNs via physisorption(PC@MSNs). PC@MSNs, characterized by a regular spherical shape, smooth surface, and an MSN average size of 262.9 nm, achieved an 8.6 % drug loading capacity. The release kinetics of the PC from the PC@MSNs demonstrated a sustained release (288 h) pattern influenced by drug diffusion. The efficacy of the PC@MSNs against Xanthomonas oryzae pv. Oryzae paralleled those of PC. Acute toxicity assays re-vealed that the PC@MSNs were less toxic to aquatic life (LC50=257.867 mg/L) and that the formu-lation showed no adverse effects on rice seedling growth. In summary, these results suggest that PC@MSNs can broaden PC's application scope in managing rice diseases.

Pathogens, especially invasive species, have caused significant global ecological, economic, and social losses in forests. Plant disease research has traditionally focused on direct interactions between plants and pathogens in an appropriate environment. However, recent research indicates that the microbiome can interact with the plant host and pathogens to modulate plant resistance or pathogen pathogenicity, thereby altering the outcome of plant–pathogen interactions. Thus, this presents new opportunities for studying the microbial management of forest diseases. Compared to parallel studies on human and crop microbiomes, research into the forest tree microbiome and its critical role in forest disease progression has lagged. The rapid development of microbiome sequencing and analysis technologies has resulted in the rapid accumulation of a large body of evidence regarding the association between forest microbiomes and diseases. These data will aid the development of innovative, effective, and environmentally sustainable methods for the microbial management of forest diseases. Herein, we summarize the most recent findings on the dynamic structure and composition of forest tree microbiomes in belowground and aboveground plant tissues (i.e., rhizosphere, endosphere, and phyllosphere), as well as their pleiotropic impact on plant immunity and pathogen pathogenicity, highlighting representative examples of biological control agents used to modulate relevant tree microbiomes. Lastly, we discuss the potential application of forest tree microbiomes in disease control as well as their future prospects and challenges.

：Sleep stage on the whole night is not steady. Sleepers generally pass through three to five cycles. In each cycle, there are occur four typical sleep stages, such as wake stage (WS), light stage (LS), deep sleep (DS), rapid eye movement sleep stage (REM). According to the natural routine, in this paper, we investigate the stage transition and analyze the feature of stage transition using the local cluster Algorithm (LCA). Two-cycle sleep model (TCSM) is proposed to automatically classify sleep stages using over-night continuous heart rate variability (HRV) data. The generated model is based on the characteristics of the nested cycle's sleep stage distribution and the transition probabilities of sleep stages. Experiments were conducted using a public data set including 400 healthy subjects (female 239, male 161) and the model’s classification accuracy was evaluated for four sleep stages: WS, LS, DS, REM. The experimental results showed that based on the TCSM model, the segmentation classification of pure sleep is 5.2% higher than that of the traditional method, and the accuracy of segmentation classification is 11.2% higher than the traditional sleep staging accuracy. The experimental performance is promising in terms of the accuracy, sensitivity, and specificity rates compared with the ones of the state-of-the-art methods. The study contributes to improve the quality of sleep monitoring in daily life using easy-to-wear HRV sensors.

This study introduces a new discrete distribution which is a weighted version of Poisson-Lindley distribution. The weighted distribution is obtained using the negative binomial weight function and can be fitted to count data with over-dispersion. The p.m.f., p.g.f. and simulation procedure of the new weighted distribution, namely weighted negative binomial Poisson-Lindley (WNBPL), are provided. The maximum likelihood method for parameter estimation is also presented. The WNBPL distribution is fitted to several insurance datasets, and is compared to the Poisson and negative binomial distributions in terms of several statistical tests.

The plethora of bio-functional compounds present in fermented alcoholic beverages like wine, as well as the valorization of bioactives from their wineries/breweries by-products like grape pomace and grape seed, has gained significant interest in the functional foods sector. Wine has always accompanied humanity, for religion or for health. For example, Christians are using wine in the “Holy Communion”, following what Jesus Christ himself did and said during the Last Supper, while the benefits of the wine consumption in moderation was embedded in all Mediterranean civilizations, as it is mentioned by the wise King-Prophet David in his psalms, but also by Hip-pocrates and other wise men, in a Greek-based philosophy of “All things in Moderation” (Cleobulus of Lindos; 6th century BC). In modern times, and after the outbreak of research on wine benefits since the 90’s, when the term “French Paradox” was introduced in the US public during a CBS show, recent evidence has outlined that these benefits are derived by the synergisms of its bio-functional compounds and their digestion-derived metabolites. Within this article, the proposed health benefits of moderate wine consumption, as a functional component of a balanced diet (i.e. the Mediterra-nean Diet), against inflammation-related chronic disorders, is thoroughly reviewed. The various bio-functional compounds of both wine and wineries’ by-products, such as their bioactive phe-nolics, unsaturated fatty acids, polar lipids, and dietary fibers, and their functional antioxidant, anti-inflammatory and antithrombotic health promoting properties are also thoroughly evaluated. The mechanisms of actions and synergism, by which the health benefits are elicited, are also ex-plored. Functional properties of non-alcoholic wine products are also introduced. Emphasis is also given to applications of wineries’ by-products bioactives, as ingredients of bio-functional foods, supplements and nutraceuticals. Limitations and future perspectives for this popular functional alcoholic beverage (wine) ant its rich in bioactives by-products are also addressed. .

To obtain a cost-effective and high-performance composite material of polybutylene adipate-terephthalate (PBAT), for this study we selected microcrystalline cellulose, which is inexpensive and easily available, as the reinforcing medium. Hexadecyl trimethoxysilane (HDTMS) containing a long carbon chain was chosen to silanize the microcrystalline cellulose (MCC) to obtain silanized cellulose (SG). Three types of SGs with different degrees of silanization were obtained by controlling the reaction ratio. Characterization of these three types of SGs was conducted using FTIR, TEM, and water absorption analysis. Subsequently, PBAT/SG composites were prepared through a sol-gel method, and the effects of these three types of SGs on the thermal stability, compatibility, mechanical properties, and dynamic thermomechanical properties of PBAT were evaluated. Furthermore, the mechanism behind enhancing the mechanical properties of the composite was analyzed. The results demonstrated successful synthesis of SG. As the reaction ratio between HDTMS and MCC increased, the nanoparticle size increased, while the water absorption decreased significantly. After SG was added to the PBAT composites, the yield stress increased while maintaining good thermal stability. Both the SEM and DMA results indicated good compatibility of the PBAT/SG composites. Analysis of the mechanical properties revealed that the tensile strength initially increased and then decreased with increasing blending ratio for all three composites tested; among them, the PBAT/SG2 composites exhibit superior performance, with a maximum tensile strength reaching 22 MPa at an 85/15 blending ratio—nearly 30% higher than that of pure PBAT alone. The addition of SG significantly improved the strength of the PBAT, and we speculated as to the underlying mechanism involved. This study provides a new idea for the industrial-scale development of degradable polyesters with low cost and good mechanical properties.

In the article, the results of research on a NiTi alloy with a high nickel content (51.7 at.%), produced using the additive technology SLM method and subjected to isothermal aging after so-lution annealing, are presented. The study involved the determination of the sequence of phase transformations occurring using differential scanning calorimetry (DSC), and the determination of the temperature range of these transformations. In parallel, the phase composition was determined using the XRD method; hardness and the Young’s modulus were also determined. The analysis of the DSC results obtained indicates the following characteristic features of the NiTi alloy, which change with ageing time: (1) during cooling (from +1500C to -500C), the type of transformation changes from a one-step transformation after solution annealing to a two-step transformation after the ageing process over 1, 20 and 100 hours at 500°C; (2) during heating (from -500C to +1500C) for all the samples, regardless of the ageing time, only a one-step transformation from martensite M(B19’) to austenite A(B2) is observed; (3) the temperature at which the transformation starts increases with the ageing time, (4) the width of the total temperature range of the transformation M(B19’)  A(B2) during heating changes from large (∆T=49,7°C), after solution annealing, to narrow (∆T=19.3°C and ∆T=17.9°C after 20 h and 100 h of ageing) and, most importantly, (5) a comparison with literature data shows that, irrespective of the composition of the NiTi alloy and the manufacturing technology of the alloy samples (regardless of the fact whether this was traditional or additive technology), a sufficiently long ageing process period leads to the occurrence of the martensite  austenite transformation in the same temperature range.

The digital economy promotes economic development, industrial upgrading, and environmental protection. This article calculates the green total factor productivity (GTFP) based on the SBM-DDF model and uses the entropy method and principal component analysis to calculate the digital economy index. We use panel data from 282 Chinese cities to test the driving effect of the digital economy on green total factor productivity. The study results show that the digital economy significantly increases GTFP, and the heterogeneity of this impact is further explored. We also explored the mechanism of the digital economy in promoting green. The digital economy can indirectly increase industrial production efficiency by promoting innovation in green technologies.

Aim at a better understanding of the flow field around a fully appended Joubert BB2 submarine model and complementing the experimental investigations of the wake of the hydroplanes and sail, the Large eddy simulation (LES) with the dynamic Smagorinsky model is conducted. Three sets of grids with a maximum grid number of up to 228 million are designed, to perform the LES simulation for the Joubert BB2 at 10° yaw conditions, with a freestream Reynolds (Re) number based on the local freestream velocity and the hull length of ReL=2.2×107. And comparison of the wake of the cruciform appendage is made with experiments, to verify the computational accuracy and examine the influence of the spatial resolution. A satisfactory result shows more favorable agreement with experimental measurements as the improvement of spatial resolution, with the relative error of the vortice centers well within 7.2% in the most refined grid arrangement. And under this grid arrangement, the evolution characteristics of three co-rotating vortices originating from the cruciform appendage are further described in detail at straight ahead and 10° yaw conditions.

The development of Al-Ni alloys with a controlled microstructure has had a great impact on the field of study of aluminum-based alloys. In the present research, the influence of thermal parameters on the grain structures resulting from the directional solidification process of Al-Ni alloys with different alloy content has been studied. It has also been evaluated how different structures and the distribution of second phases influence the corrosion behavior and microhardness of alloys. The columnar-to-equiaxed transition (CET) was observed to occur when the temperature gradient in the melt decreased to values between 1.3 to 2.9 ° C/cm. In addition, a small increase in the microhardness values was observed as a function of the Ni-content. When the Ni-content increase, the resistance to polarization decreases for samples with equiaxed grain structure, throughout the range of compositions studied. Furthermore, the equiaxed grain structure presents higher resistance to polarization values than the columnar grain zone, for alloys with a composition equal to or lower than the eutectic composition.

Employing numerical methods to simulate manufacturing processes and study their influential factors is increasing. The development of computers and engineering software has increased the ability and accuracy of numerical methods in simulating various aspects of different processes. One of the manufacturing processes that has been considered by many industries in recent years to join metals in solid-state with unique properties is called friction stir welding. It is challenging and, in some cases, impossible to experimentally study the various aspects of this process, such as temperature distribution, stress distribution, and material flow, due to severe plastic deformation in the weld zone. In this case, numerical methods are used to investigate these parameters and better understand the process. This study first investigates various numerical methods researchers use to simulate the process. The ability, pros, and cons of these methods to simulate the process are also examined. Then, the applications of numerical models in simulating the temperature distribution during the process as well as the effects of input parameters on the temperature history of the process, are deeply considered. Next, the application of numerical methods in material flow modeling during the process is investigated. Finally, the modeling of the microstructure of the welding zone is investigated using numerical methods that help significantly in predicting the weld microstructure.

Urban areas have very complex spatial structures. These spatial structures are primarily composed of a complex network of built environments, which evolve rapidly as the cities expand to meet the growing population’s demand and economic development. Therefore, studying the impact of spatial structures on urban heat patterns is extremely important for sustainable urban planning and growth. We investigated the relationship between surface temperature obtained by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER, at 90 m spatial resolution) on the current EOS-Terra platform and different urban components based on the classification of high-resolution QuickBird imagery. We further investigated the relationships between surface temperature and building footprint and land use information acquired from the New York City (NYC) Department of City Planning. The ASTER image reveals fine-scale urban heat patterns in the NYC metropolitan region. The dark and medium-dark impervious surfaces, along with bright surfaces, generate higher surface temperatures. Even with highly reflective urban materials, the presence of impervious materials leads to an increased surface temperature. At the same time, trees and shadows are effective in reducing urban heat. The data aggregated to the census tract reveals high-temperature clusters in Queens, Brooklyn, and the Bronx region of NYC. These clusters are associated with industrial and manufacturing areas and multi-family walk-up buildings as dominant land use. The census tracts with more trees and higher building height variability generate lower surface temperatures, consistent with shadow cast by high-rise buildings and trees. The results of this study can be valuable for urban heat island modeling on the effects of building heights variability and tree shadows on small-scale surface temperature patterns. It can also help identify the risk areas during extreme heat events to protect public health.

In the paper, using two inversion theorems for the Stirling numbers and binomial coecients, employing properties of the Bell polynomials of the second kind, and utilizing a higher order derivative formula for the ratio of two dierentiable functions, the authors present two explicit formulas, a determinantal expression, and a recursive relation for a sequence of unnamed polynomials, derive two identities connecting the sequence of unnamed polynomials with the Bell polynomials, and recover a known identity connecting the sequence of unnamed polynomials with the Bell polynomials.

In the paper, by virtue of the Faà di Bruno formula, some properties of the Bell polynomials of the second kind, and an inversion formula for the Stirling numbers of the first and second kinds, the authors establish meaningfully and significantly two identities which simplify coefficients in a family of ordinary differential equations associated with higher order Bernoulli numbers of the second kind.

In the paper, by virtue of the Fa`a di Bruno formula, some properties of the Bell polynomials of the second kind, and the inversion formulas of binomial numbers and the Stirling numbers of the first and second kinds, the authors simplify meaningfully and significantly coefficients in two families of ordinary differential equations associated with higher order Frobenius–Euler numbers.

The impacts of inflation on international finance are generally reflected in the decline of buying power, risks of investment and deposit loss from currency devaluation. For the purpose of optimized allocation and management of asset values, i.e., annual income or research grants, a framework of a three-level model for static financial management is presented to maximize banking interests, bonuses, and the remaining balance after spending necessary expenditures. Meanwhile, in retrospect to higher-level financial inflation, strategies of dynamic investment, i.e., posing regular tests of flipping coins, exploiting variations of the currency exchange rate, as well as applying the theory of broad money, are presented to increase the appreciation rate of net assets in and post the era of COVID-19. Quantitative evaluations in case studies verify the feasibility of improving the financial situation, indicating broader applications for budgeting and investing when US inflation rate is below 3.0%. Besides, combining approaches of static and dynamic strategies, the expected annual growth rate of individual zero-risk asset investment is predicted as within the range of 8.30~9.62% according to budgeted appreciation on net assets in 12 months, which is capable of overcoming negative impacts from higher level annual inflation, i.e., those as highest as 8.01% in the Year 2022.

In this paper, we consider the generalized sextic functional equation \begin{align*} \sum_{i=0}^{7}{}_7 C_{i} (-1)^{7-i}f(x+iy) = 0. \end{align*} And by applying the fixed point theory in the sense of L. C\u adariu and V. Radu, we will discuss the stability of the solutions for this functional equation.

Phototherapy is an efficient strategy to respond to oxidative stress and has been in the spotlight in various therapeutic fields through its biological effect, but the exact molecular mechanism has not yet been established. As a result of irradiating RAW264.7 cells with a 630 nm or 850 nm LED with an energy intensity of 0.01J/cm2, cell viability was increased depend on the irradiation time. After H2O2 was added, 630 nm or 850 nm LEDs were irradiated for 10 min or 40 min to increase cell viability by about 1.7- or 1.6-fold, respectively. In addition, 630nm or 850nm LED irradiation showed a significant ROS scavenging effect and significantly reduced TUNEL-positive cells by 45.7% and 37.8%, respectively, compared to cells treated only with H2O2. In the result of flow cytometry, the number of cells in the late apoptosis stage was about 2.3- and 1.8-fold lower than that of the cells treated with H2O2 only, but there was no significance. The Bax/Bcl-2 ratio of cells irradiated with 630 nm or 850 nm LED was significantly lower than that of cells treated with H2O2 only, and the expression of procaspase-3 and cleaved PARP was also significantly expressed in the direction of suppressing cell death. In conclusion, the ROS scavenging activity by 630 nm or 850 nm LED irradiation, leading the expression of cell death pathway proteins in the direction of inhibiting cell death.

In this study, we examine the relationship of bank level lending and borrowing decisions and the risk preferences on the dynamics of the interbank lending We develop an agent-based model that incorporates individual bank decisions using the temporal difference reinforcement learning algorithm with empirical data of 6600 S. banks. The model can successfully replicate the key characteristics of interbank lending and borrowing relationships documented in the recent literatur A key finding of this study is that risk preferences at individual bank level can lead to unique interbank market structures which are suggestive of the capacity that the market responds to surprising

The KID (Koopmans in DFT) procedure usually applies in organic molecules of the closed–shell type. We used the KID procedure in an open–shell system for the first time to choose the most suitable density functional to compute global and local reactivity descriptors coming from the Conceptual Density–Functional Theory. From a set of 18 density functionals spread from the second until the fourth rung of the Jacob’s ladder: BP86, B97-D, BLYP, CAM-B3LYP, M06-L, M11-L, MN12-L, B3LYP, PBE0, N12-SX, M06-2X, M11, MN12-SX, CAM-B3LYP, LC-ωHPBE, ωB97X-D, APFD, MN15 and MN15-L, we concluded that CAM-B3LYP provides the best outcome.

K417G Ni-based superalloy is widely used in aeroengine turbine blade for its excellent properties. However, the aeroengine rotor blade zigzag crown appears early failure frequently, which is because of the wear problems occurring in the working process. Laser forming repairing (LFR) is a promising technique to repair these damaged blades. Unfortunately, the laser formed Ni-based superalloys with high content of (Al + Ti) have a high cracking sensitivity. In this paper, the crack characterization of the LFRed K417G, the microstructure, microhardness and tribological properties of the coating before and after laser remelting are presented. The results show that the microstructure of as-deposited K417G consists of γ phase, γ′ precipitated phase, γ + γ′ eutectic and carbide. Cracking mechanisms including solidification cracking, liquation cracking and ductility dip cracking are proposed based on the composition of K417G and processing characteristics to explain the cracking behavior of the K417G superalloy during LFR. After laser remelting, the microstructure of the coating has been refined, and the microhardness and tribological properties has been improved. Laser remelting can decrease the size of the cracks in the LFRed K417G but not the number. Therefore, laser remelting can be applied as an effective method for strengthening coating and as an auxiliary method for controlling cracking.

The special affine Fourier transform (SAFT) is a useful and powerful analyzing tool in signal processing, optics and communications. In this paper, we mainly discuss the randomized nonuniform sampling and reconstruction for random signals bandlimited in the SAFT domain. First, we show that the nonuniform sampling is identical to the uniform sampling after a pre-filter in the sense of second order statistic characters. Then, we propose an approximate reconstruction based on sinc interpolation for the nonuniform sampling of random signals bandlimited in the SAFT domain. Finally, we give the mean square error estimate for the proposed approximate recovery approach.

In the note, the authors find several simple and explicit forms for a family of inhomogeneous linear ordinary differential equations studied in "D. Lim, Differential equations for Daehee polynomials and their applications, J. Nonlinear Sci. Appl. 10 (2017), no. 4, 1303-1315; Available online at http://dx.doi.org/10.22436/jnsa.010.04.02".

In the paper, the authors nd a new closed expression for the Fibonacci polynomials and, consequently, for the Fibonacci numbers, in terms of a tridiagonal determinant.

In the paper, by virtue of techniques in combinatorial analysis, the authors simplify two families of nonlinear ordinary differential equations in terms of the Stirling numbers of the first kind.

This work investigated the influence of current density, plating solution flow rate, and nozzle outlet-cathode distance on the properties of Ni-diamond composite coatings. A multi-physics field simulation is employed to analyze the interplay between current density, plating solution flow rate, and nozzle outlet-cathode distance on the flow field and electric field distribution. Additionally, particle tracing simulations were incorporated into the model to evaluate the incorporation efficiency of diamond particles during composite electrodeposition. Experimental validation of the findings shows a significant increase in the diamond particle content of the coating. This combined approach provides valuable insights for optimizing the jet electrodeposition process for Ni-diamond composite coatings with superior properties.

Heat-treated aluminum-silicon (Al-Si)-based alloys have dominated the cast lightweight alloy industry for several decades. However, in the last decade, Al-Ce-based alloys have shown promise in replacing Al-Si alloys due to their ability to remove the need for costly heat treatments. Since the properties of Al-Ce alloys depend on the as-cast microstructure, it is important to characterize the solidification kinetics of these alloys. Therefore, this study focused on characterizing the solidification of a near eutectic Al-Ce alloy with additions of Ni and Mn. The alloy was cast in a wedge mold configuration, resulting in cooling rates between 0.18 and 14.27 °C/s. SEM coupled with EDS and DSC techniques characterized the evolution rate of solid phases. The SEM/EDS data revealed that an Al10CeMn2 phase is present at higher cooling rates. At lower cooling rates, near the center of the casting, a proeutectic Al23Ce4Ni6 phase was more present. It was observed that up to 2.6 at. % of Mn was dissolved in this proeutectic Al23Ce4Ni6 phase, thereby removing a large portion of the available Mn for forming the Al10CeMn2 phase. DSC analysis showed differences in the samples' liquidus temperatures which is indicative of compositional variations. Inductively coupled plasma atomic emission spectroscopy (ICP-OES) and Scheil solidification simulations correlated the compositional differences to phase formation, which agreed with the SEM and DSC results. This experimentation provides insight into novel Al-Ce-Ni-Mn alloys and where their potential lies in industrial applications.