Mixed Clusters Research Articles

Dynamics of paramagnetic permanent chains and self-assembled clusters under a rapidly rotating magnetic field.

We study experimentally and theoretically the dynamics of permanent paramagnetic chains and mixed clusters formed by permanent paramagnetic chains and paramagnetic particles under the influence of a time-varying magnetic field. First, we examine the dynamics of permanent chains at high frequencies (∼50 to 1000Hz). These permanent chains exhibit continuous rotational motion with a frequency several orders of magnitude lower than that of the magnetic field. We develop a theoretical model that accurately describes the dependence of the rotational dynamics of chains on their length, as well as the amplitude and frequency of the external magnetic field in this high frequency regime. Next, we examine how cluster dynamics are affected by the presence of permanent chains. We show that the rotation of clusters composed of a high proportion of permanent chains is slowed down but remains qualitatively well described by the theoretical model we developed for homogeneous clusters of isotropic particles. We propose that the decrease in angular velocity for mixed clusters is due to the hardening of the cluster's 2D elastic modulus caused by the increase of the steric interaction parameter stemming from the presence of chemical links between particles in the chains.

Remnant cholesterol, clinical characteristics and mortality in 41.767 patients from LIPIDOGRAM 2004-2015 studies - the factor analysis for mixed data cluster analysis

Abstract Introduction Remnant cholesterol (remnant-C) contributes to residual cardiovascular risk and is produced by metabolism of triglyceride rich proteins. Aim To assess association between clinical characteristics of patients with elevated remnant-C in a large cohort of patients under the care of primary care physicians. Methods The LIPIDOGRAM studies were carried out in the primary care in Poland in 2004, 2006 and 2015. Patients (n=47,398) recruited in all 16 administrative regions in Poland and physicians were proportionally distributed to the number of inhabitants in each administrative region. Each patient was asked to fill the questionnaire on risk factors, chronic diseases, treatment and lifestyle. In the present analysis we included patients with body mass index (BMI )>18.5 kg/m2 aged 18-75 years. We set the cut-off point of fasting remnant cholesterol at >30 mg/dL (>0.77 mmol/L) that differentiated subjects at high risk of cardiovascular events. We carried out Factor Analysis for Mixed Data (FAMD) cluster analysis to discern groups of patients with similar clinical profiles. Results 41,767 patients, for which we had all relevant data, were included in the analysis. Follow-up rate was 97.8%. Three FAMD-derived clinical characteristics patterns accounted for 47.8% of the total variance and were retained for further analysis. The first pattern was associated with higher prevalence of metabolic syndrome (MetS), higher waist circumference, higher levels of non-HDL-C and remnant-C levels. The second pattern was distinguished by lipid parameters, particularly higher HDL-C levels, and was not significantly associated with comorbid conditions. The third pattern was linked to male sex, previous myocardial infarction, smoking, age, lower remnant-C levels, and reduced prevalence of obesity. All patterns were associated with 5-year mortality. The hazard ratio (HR) for mortality per 1 standard deviation (SD) increase in the first pattern score was 1.18 (95% CI: 1.16-1.22, p<0.001). Patients with clinical characteristics corresponding to second pattern had more favorable outcome HR (per 1SD score increase) – 0.75, 95%CI (0.73-0.78, p<0.001). Patients in third cluster, similarly to patients in cluster 1 had increased mortality HR (per 1SD score) – 1.10, (95%CI:1.06-1.15, p <0.001). Higher (>0.77 mmol/l / 30 mg/dl) remnant-C cholesterol significantly contributed to classification of patients into first and third clusters. It was positively associated with first pattern (r=0.64, p<0.001), but negatively with the third pattern (r=0.39, p<0.001). Conclusions Elevated Remnant-C was associated with clinical pattern typical for metabolic syndrome. Interestingly, lower remnant-C levels in patients with comorbidities and more advanced age may not automatically be indicative of a better prognosis – this requires further investigation.Figure 1.Figure 2.

Composition Determination of Heterometallic Trinuclear Clusters via Anomalous X-ray and Neutron Diffraction.

Anomalous X-ray diffraction (AXD) and neutron diffraction can be used to crystallographically distinguish between metals of similar electron density. Despite the use of AXD for structural characterization in mixed metal clusters, there are no benchmark studies evaluating the accuracy of AXD toward assessing elemental occupancy in molecules with comparisons with what is determined via neutron diffraction. We collected resonant diffraction data on several homo and heterometallic clusters and refined their anomalous scattering components to determine metal site occupancies. Theoretical resonant scattering terms for Fe0, Co0, and Zn0 were compared against experimental values, revealing theoretical values are ill-suited to serve as references for occupancy determination. The cluster featuring distinct cation and anion metal compositions [CoCp2*][(tbsL)Fe3(μ3-NAr)] was used to assess the accuracy of different f' references for occupancy determination (f'theoretical ± 15-17%; f'experimental ± 10%). This methodology was applied toward calculating the occupancy of three different clusters: (tbsL)Fe2Zn(py) (6), (tbsL)Fe2Zn(μ3-NAr)(py) (7), and [CoCp*2][(tbsL)Fe2Zn(μ3-NAr)] (8). The first two clusters maintain 100% Fe/Zn site isolation, whereas 8 showed metal mixing within the sites. The large crystal size of 8 enabled collection of neutron diffraction data which was compared against the results found with AXD. The ability of AXD to replicate the metal occupancies as determined by neutron diffraction supports the AXD occupancy methodology developed herein. Furthermore, the advantages innate to AXD (e.g., smaller crystal sizes, shorter collection times, and greater availability of synchrotron resources) versus neutron diffraction further support the need for its development as a standard technique.

Mixed H2S and H2O Clusters─New Insights into Dispersion-Dominated Hydrogen Bonding.

Here, we report the results of an IR spectroscopy study on heteroclusters of H2S and H2O and several of their isotopomers using mass-selective IR spectroscopy in superfluid helium nanodroplets in the range of 2560-2800 cm-1. Based on DFT calculations on the B3LYP-D3/6-311++G(d,p) level of theory, we were able to assign the experimentally observed O-D stretching bands to heterodimer and heterotrimer clusters. Since no bands of the S-H-bound conformer HSH···OH2 could be observed, we were able to determine the O-H-bound conformer HOH···SH2 to be the global minimum structure. A trapping of the local minima in helium nanodroplets was not observed. This is in line with the weaker hydrogen bond expected for H2S complexes. In these clusters, the interaction energy is expected to be more dominated by dispersion and less dictated by highly directional electrostatic forces.

A Study on Oxygen Vacancy Resistance Mechanism of V2O5

Introduction: Due to its magnetic and semiconductor properties, V2O5 has shown tremendous potential in resistive switching memory. Method: Therefore, this paper investigates the resistive mechanism of oxygen vacancies in V2O5. The formation energies of different oxygen vacancies are calculated. Results: The results indicate that oxygen vacancies tend to form single-component conductive filaments. In mixed oxygen vacancies clusters, the charge transfer characteristics and density of states of the V2O5-VO 13 vacancies are the most significant, which is consistent with the analysis of formation energy data. Conclusions: Additionally, the charge transfer of cluster oxygen vacancies was calculated, showing that V atoms directly connected to oxygen vacancies tend to lose electrons, while adjacent oxygen atoms are more likely to gain electrons. In V2O5-VO 12 and V2O5-VO 13, the number of electrons obtained by O2 and O16 exceeds the average by 36.4% and 33.2%. Thus, the formation of oxygen vacancies effectively improves the resistance characteristics of the V2O5.

Geometric structures and adsorption energies of mixed methanol and C60 cationic clusters produced within helium nanodroplets

Mass spectrometry is a useful technique for studying molecular cluster sizes, their distributions, compositions, and stability. Methanol and fullerenes are among the species identified in the interstellar medium and, due to their high abundance, their interactions are an interesting investigation topic. A mass spectrometric study of mixed clusters of methanol and C60 inside helium nanodroplets is presented. Anomalies in the distribution intensities or magic numbers were observed for [CH3OH]4[C60]m+,1≤m≤7. Water molecules within clusters were also detected, arising as one of the products of intermolecular methanol dehydration. Optimized and supposedly stable geometrical structures of these molecules are presented along with corresponding HOMO–LUMO gaps and adsorption energies. A linear decrease in adsorption energy and saturation at a critical cluster size was noticed.

What does it take to stabilize a naphthalene anion?

We investigate attachment of slow electrons (0-10eV) to naphthalene (Np) clusters in a crossed beam experiment. Supersonic expansions under different conditions using different buffer gases generate the clusters: in He, Ne, and low pressure Ar, neat (Np)N clusters are formed, while we also observe mixed clusters of naphthalene with rare-gas atoms in co-expansion with Ar above 0.5bar and with Kr. Negatively charged (Np)n- and Rgm(Np)n- (Rg = Ar, Kr) clusters are analyzed by mass spectrometry, and electron energy dependent ion yields are measured. We show that the smallest stable naphthalene complex with an excess electron, the dimer (Np)2- anion, cannot be formed in a binary collision of a free electron with (Np)2 dimer, nor with (Np)3 trimer. Evaporation of a weakly bound Ar atom(s) from a mixed ArM(Np)2 cluster following electron attachment leads to the dimer (Np)2- anion. Larger (Np)n-, n > 3, transient cluster anions decay via evaporation of an Np unit on a timescale of tens of microseconds. The self-scavenging process opens around 6eV, where a naphthalene unit is electronically excited by the incoming electron, which is slowed down and trapped. However, the transient negative ion is efficiently stabilized only in the mixed clusters, from which Ar atom(s) can be evaporated.

Modulation of p-Block Electron Orbits in Metal-Organic Frameworks for CO2 Capture and Electrochemical Reduction.

Developing catalysts with excellent CO2 capture capability and electrochemical CO2 reduction reaction (CO2RR) at a wide potential range simultaneously is significant but remains a formidable challenge. Here, two novel InMg defective trinuclear cluster-based MOFs (SNNU-41 and SNNU-42) with abundant p-block unsaturated coordinated sites were reported and exhibited good CO2 capture and CO2RR performance simultaneously. Due to the suitable micropores, SNNU-41 showed higher CO2 capture ability at different adsorption pressure conditions. On account of the rigid framework and the closer p band center to Fermi level, SNNU-42 accelerated the conversion of CO2 molecule to C1 efficiency. Notably, via adjusting the ratio of p-block metal (In) in the SNNU-42 framework, the performance of the CO2RR was promoted drastically. SNNU-42 with the InMg (1:1.8) mixed cluster delivered an excellent Faradaic efficiency of 91.3% for C1 products and high selectivity of 72.0% for HCOOH at -2.5 V (vs Ag/Ag+) with a total current density of 77.2 mA cm-2. This work provides a possibility for efficient CO2 capture and CO2RR electrocatalysts through the modulation of electronic structures and composition in MOFs.

Beyond the Spectrum: Subtype-Specific Molecular Insights into Autism Spectrum Disorder Via Multimodal Data Integration.

Some toddlers with autism spectrum disorder (ASD) have mild social symptoms and developmental improvement in skills, but for others, symptoms and abilities are moderately or even severely affected. Those with profound autism have the most severe social, language, and cognitive symptoms and are at the greatest risk of having a poor developmental outcome. The little that is known about the underlying biology of this important profound autism subtype, points clearly to embryonic dysregulation of proliferation, differentiation and neurogenesis. Because it is essential to gain foundational knowledge of the molecular biology associated with profound, moderate, and mild autism clinical subtypes, we used well-validated, data-driven patient subtyping methods to integrate clinical and molecular data at 1 to 3 years of age in a cohort of 363 ASD and controls representative of the general pediatric population in San Diego County. Clinical data were diagnostic, language, cognitive and adaptive ability scores. Molecular measures were 50 MSigDB Hallmark gene pathway activity scores derived from RNAseq gene expression. Subtyping identified four ASD, typical and mixed diagnostic clusters. 93% of subjects in one cluster were profound autism and 93% in a different cluster were control toddlers; a third cluster was 76% moderate ability ASD; and the last cluster was a mix of mild ASD and control toddlers. Among the four clusters, the profound autism subtype had the most severe social symptoms, language, cognitive, adaptive, social attention eye tracking, social fMRI activation, and age-related decline in abilities, while mild autism toddlers mixed within typical and delayed clusters had mild social symptoms, and neurotypical language, cognitive and adaptive scores that improved with age compared with profound and moderate autism toddlers in other clusters. In profound autism, 7 subtype-specific dysregulated gene pathways were found; they control embryonic proliferation, differentiation, neurogenesis, and DNA repair. To find subtype-common dysregulated pathways, we compared all ASD vs TD and found 17 ASD subtype-common dysregulated pathways. These common pathways showed a severity gradient with the greatest dysregulation in profound and least in mild. Collectively, results raise the new hypothesis that the continuum of ASD heterogeneity is moderated by subtype-common pathways and the distinctive nature of profound autism is driven by the differentially added profound subtype-specific embryonic pathways.

Dissociation of HBr in Water Clusters Based on a Hybrid Density Functional Approach.

The dissociation of acidic molecules within a microscopic water environment is crucial for understanding intermolecular interactions such as hydrogen bonding. This study explores the optimal configurations of HBr(H2O)n=1-7 using hybrid density functional theory. According to the different mixed cluster structures, the corresponding HBr bond lengths, single-point energies, and introduced proton-transfer parameters are computed and analyzed. The findings indicate that a minimum of three water molecules is necessary for the dissociation of HBr. Subsequently, this conclusion is reinforced through the decomposition of energy components between the acid molecule and water clusters, calculation of hydrogen bonding energies, and analysis of vibrational infrared spectroscopy.

Effectiveness of a minecraft education intervention for improving spatial thinking in primary school children: A mixed methods two-level cluster randomised trial

BackgroundSpatial thinking plays a crucial role in STEM success. Minecraft Education, a digital game-based learning platform, provides opportunities for developing students’ spatial thinking while supporting curricular content. AimThis study evaluated the effectiveness of a Minecraft Education intervention, integrated into the curriculum, in improving spatial thinking and creativity. SampleFifth and sixth year primary school students (Mage = 11.53, SDage = 0.58) and their teachers. MethodsThe study used a mixed-methods, two-level cluster randomised-controlled trial design. Thirty-two classes (N = 885 students) were randomly assigned to the intervention or education-as-usual control group. Assessments of spatial thinking and creativity were completed at pre-test, post-test and 6-week follow up. Teacher interviews were conducted to understand their experiences of the intervention. ResultsWhile no overall intervention-related improvements in spatial thinking were found, subgroup analyses revealed that 5th year demonstrated improved spatial thinking compared to 6th year at post-test. This may be attributable to 5th year students’ higher levels of engagement in the intervention. Unexpectedly, creativity scores were higher in the control group at post-test. Qualitative interviews identified four themes: 1) Improving spatial thinking, 2) Improving creativity, 3) Engagement, and 4) Difficulties implementing the programme. ConclusionThis study highlights the importance of increasing student engagement in spatial interventions to improve their spatial skills. Finally, the study suggests that sustained practice is required to maintain the benefits of spatial instruction/training.

Local Coordination Environment of Lanthanides Adsorbed onto Cr- and Zr-based Metal-Organic Frameworks.

Separating individual lanthanide (Ln) elements in aqueous mixtures is challenging. Ion-selective capture by porous materials, such as metal-organic frameworks (MOFs), is a promising approach. To design ion-selective MOFs, molecular details of the Ln adsorption complexes within the MOFs must be understood. We determine the local coordination environment of lanthanides Nd(III), Gd(III), and Lu(III) adsorbed onto Cr(III)-based terephthalate MOF (Cr-MIL-101) and Zr(IV)-based Universitet in Oslo MOFs (UiO-66 and UiO-68) and their derivatives. In the Cr(III)- and Zr(IV)-based MOFs, Ln adsorb as inner-sphere complexes at the metal oxo clusters, regardless of whether the organic linkers are decorated with amino groups. Missing linkers result in favorable Ln binding sites at oxo clusters; however, Ln can coordinate to metal sites even with linkers in place. MOF functionalization with phosphonate groups led to Ln chemisorption onto these groups, which out-compete metal cluster sites. Ln form monodentate and bidentate and mononuclear and binuclear surface complexes. We conclude that MOFs for ion-selective Ln capture can be designed by a combination of (1) maximizing metal-lanthanide interactions via shared O atoms at the metal oxo cluster sites, where mixed oxo clusters can lead to ion-selective Ln adsorption, and (2) functionalizing MOFs with Ln-selective groups capable of out-completing the metal oxo cluster sites.

Cystic fibrosis pathogens persist in the upper respiratory tract following initiation of elexacaftor/tezacaftor/ivacaftor therapy.

Elexacaftor/tezacaftor/ivacaftor (ETI) therapy has revolutionized the treatment of cystic fibrosis (CF) for most affected individuals but the effects of treatment on sinus microbiota are still unknown. Changes to the airway microbiota in CF are associated with disease state and alterations to the bacterial community after ETI initiation may require changes to clinical management regimens. We collected sinus swab samples from the middle meatus in an observational study of 38 adults with CF and chronic rhinosinusitis (CRS) from 2017 to 2021 and captured the initiation of ETI therapy. We performed 16S and custom amplicon sequencing to characterize the sinus microbiota pre- and post-ETI. Real-time quantitative PCR (RT-qPCR) was performed to estimate total bacterial abundance. Sinus samples from people with CF (pwCF) clustered into three community types, dependent on the dominant bacterial organism: a Pseudomonas-dominant, Staphylococcus-dominant, and mixed dominance cluster. Shannon's diversity index was low and not significantly altered post-ETI. Total bacterial load was not significantly lowered post-ETI. Pseudomonas spp. abundance was significantly reduced post-ETI, but eradication was not observed. Staphylococcus spp. became the dominant organism in most individuals post-ETI and we showed the presence of methicillin-resistant Staphylococcus aureus (MRSA) in the sinus both pre- and post-ETI. We also demonstrated that the sinus microbiome is predictive of the presence of Pseudomonas spp., Staphylococcus spp., and Serratia spp. in the sputum. Pseudomonas spp. and Staphylococcus spp., including MRSA, persist in the sinuses of pwCF after ETI therapy, indicating that these pathogens will continue to be important in CF airway disease management in the era of highly effective modulator therapies (HEMT).IMPORTANCEHighly effective modulator therapies (HEMT), such as elexacaftor/tezacaftor/ivacaftor (ETI), for cystic fibrosis (CF) have revolutionized patient care and quality of life for most affected individuals. The effects of these therapies on the microbiota of the airways are still unclear, though work has already been published on changes to microbiota in the sputum. Our study presents evidence for reduced relative abundance of Pseudomonas spp. in the sinuses following ETI therapy. We also show that Staphylococcus spp. becomes the dominant organism in the sinus communities of most individuals in this cohort after ETI therapy. We identified methicillin-resistant Staphylococcus aureus (MRSA) in the sinus microbiota both pre- and post-therapy. These findings demonstrate that pathogen monitoring and treatment will remain a vital part of airway disease management for people with cystic fibrosis (pwCF) in the era of HEMT.

A regional examination of the footprint of agriculture and urban cover on stream water quality

Freshwater systems in cold regions, including the Laurentian Great Lakes, are threatened by both eutrophication and salinization, due to excess nitrogen (N), phosphorus (P) and chloride (Cl−) delivered in agricultural and urban runoff. However, identifying the relative contribution of urban vs. agricultural development to water quality impairment is challenging in watersheds with mixed land cover, which typify most developed regions. In this study, a self-organizing map (SOM) analysis was used to evaluate the contributions of various forms of land cover to water quality impairment in southern Ontario, a population-dense, yet highly agricultural region in the Laurentian Great Lakes basin where urban expansion and agricultural intensification have been associated with continued water quality impairment. Watersheds were classified into eight spatial clusters, representing four categories of agriculture, one urban, one natural, and two mixed land use clusters. All four agricultural clusters had high nitrate-N concentrations, but levels were especially high in watersheds with extensive corn and soybean cultivation, where exceedances of the 3 mg L−1 water quality objective dramatically increased above a threshold of ‍∼30 % watershed row crop cover. Maximum P concentrations also occurred in the most heavily tile-drained cash crop watersheds, but associations between P and land use were not as clear as for N. The most urbanized watersheds had the highest Cl− concentrations and expansions in urban area were mostly at the expense of surrounding agricultural land cover, which may drive intensification of remaining agricultural lands. Expansions in tile-drained corn and soybean area, often at the expense of mixed, lower intensity agriculture are not unique to this area and suggest that river nitrate-N levels will continue to increase in the future. The SOM approach provides a powerful means of simplifying heterogeneous land cover characteristics that can be associated with water quality patterns and identify problem areas to target management.

Solvent effects and Raman enhancement during the adsorption of atrazine on pristine Ag, Au, Cu and mixed clusters

Investigation of the adsorption properties of a herbicide, atrazine (6-chloro-4-N-ethyl-2-N-propan-2-yl-1,3,5-triazine-2,4-diamine) (CPD) with Ag, Au, Cu and their mixed clusters are presented using density functional theory (DFT) analysis. With metal clusters, it is found that CPD forms stable clusters, the drug-cluster complexation energy is maximum in CPD-Au2Cu (−38.69 and −45.79 kcal/mol) in vacuum and aqueous phase in comparison with other clusters. Dipole moment of the CPD-metal systems is higher than that of CPD. Clustering of CPD with metal cages enhances the Raman signals due to surface enhanced Raman scattering (SERS) activity. The exothermic processes and fluctuations in entropy during the processes were altered for all clusters as a result of CPD adsorption to the cages, indicating a change to a more ordered structure. Wavefunction based analysis indicated that there are significant non-covalent interactions (NCIs) between the system and the metal clusters.

Chemical Relationship among Genetically Authenticated Medicinal Species of Genus Angelica.

The genus Angelica comprises various species utilized for diverse medicinal purposes, with differences attributed to the varying levels or types of inherent chemical components in each species. This study employed DNA barcode analysis and HPLC analysis to genetically authenticate and chemically classify eight medicinal Angelica species (n = 106) as well as two non-medicinal species (n = 14) that have been misused. Nucleotide sequence analysis of the nuclear internal transcribed spacer (ITS) region revealed differences ranging from 11 to 117 bp, while psbA-trnH showed variances of 3 to 95 bp, respectively. Phylogenetic analysis grouped all samples except Angelica sinensis into the same cluster, with some counterfeits forming separate clusters. Verification using the NCBI database confirmed the feasibility of species identification. For chemical identification, a robust quantitative HPLC analysis method was developed for 46 marker compounds. Subsequently, two A. reflexa-specific and seven A. biserrata-specific marker compounds were identified, alongside non-specific markers. Moreover, chemometric clustering analysis reflecting differences in chemical content between species revealed that most samples formed distinct clusters according to the plant species. However, some samples formed mixed clusters containing different species. These findings offer crucial insights for the standardization and quality control of medicinal Angelica species.

Cluster size distributions, electronic characteristics and geometric structures of mixed cationic clusters of cesium and sulfur hexafluoride doped in helium

Mass Spectrometry has emerged as a valuable technique for investigating molecular cluster characteristics, including size distributions, compositions, stabilities and reactivity. In this study, we present a mass spectrometric analysis of cesium Cs mixed with sulfur hexafluoride S F 6 clusters, denoted as [ Cs ] n [ S F 6 ] m + , encapsulated within helium nanodroplets HNDs. Our analysis involved precise evaluation of mass spectra and calculating ion abundances taking into account the isotope patterns of ions. Additionally, we examined geometrical structures and stabilities of these molecules along with their corresponding highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) energy gaps. This finding sheds light on the fundamental properties and behaviour of mixed molecular clusters, offering insights into their potential applications and interactions.

Clusters of 24-hour movement behavior and diet and their relationship with health indicators among youth: a systematic review

Movement-related behaviors (physical activity [PA], sedentary behavior [SB], and sleep) and diet interact with each other and play important roles in health indicators in youth. This systematic review aimed to investigate how PA, SB, sleep, and diet cluster in youth by biological sex; and to examine which cluster are associated with health indicators. This study was registered in PROSPERO (number: CRD42018094826). Five electronic databases were assessed. Eligibility criteria allowed studies that included youth (aged 19 years and younger), and only the four behaviors {PA, SB, sleep, and diet (ultra-processed foods [UPF]; fruits and vegetables [FV])} analyzed by applying data-based cluster procedures. From 12,719 articles screened; 23 were included. Of these, four investigated children, and ten identified clusters by biological sex. Sixty-six mixed cluster were identified including, 34 in mixed-sex samples, 10 in boys and 11 in girls. The most frequent clusters in mixed-sex samples were “High SB UPF Low Sleep”, “Low PA High SB Satisfactory Sleep”, and “High PA”. The main difference in profiles according to sex was that girls’ clusters were characterized by high sleep duration, whereas boys’ clusters by high PA. There were a few associations found between cluster types and health indicators, highlighting that youth assigned to cluster types with low PA exhibited higher adiposity. In conclusion, the youth presented a range of clusters of behaviors, typically exhibiting at least one unhealthy behavior. Similar patterns were observed in both sexes with the biggest difference in time of sleep for girls and PA for boys. These findings underscore the importance of intervention strategies targeting multiple behaviors simultaneously to enhance health risk profiles and indicators in children and adolescents.

SERS-Based Sensor Using Subnanometric Copper-Silver Mixed Clusters Ag(8-n)Cun (n = 0-8) for Pyridine: A DFT Study.

Surface-enhanced Raman spectroscopy (SERS) is a powerful Raman technique that provides high selectivity and sensitivity in analyzing the intermolecular interaction of a target compound adsorbed on the surface of a noble nanomaterial, i.e., silver, gold, or copper. Although copper presents a better SERS enhancement than gold and silver, its oxidation in the air is much easier than that of gold and silver. A mixed material between these metals may potentially improve the SERS signal enhancement in this context. In this work, we evaluated the SERS spectra of pyridine (Py) adsorbed on the copper-silver mixed clusters Ag(8-n)Cun (n = 0-8) using density functional theory (DFT) at the PBE functional. The cc-pVDZ-PP basis set was chosen for Ag and Cu, while the cc-pVDZ basis set was used for C, N, and H atoms. Geometrical and electronic structures of the mixed clusters and the Py adsorption configuration on these clusters were computed. The calculated SERS spectra then revealed the influence of the Ag/Cu mixing ratio on the SERS enhancement. As a result, the substituted copper atoms on the silver cluster turned out to be favorable adsorption sites for Py. Interestingly, when the number of Cu atoms increased from n = 0 (pure Ag8 cluster) to n = 5 (Ag3Cu5 cluster), the ring stretching peak (1590 cm-1) of Py significantly increased from 20 to 120 au and then saturated around this value despite increasing the Cu atom number to 8 (pure Cu8 cluster). This observation was extended for other ligands such as pyrazine and 3H-pyrrole. TD-DFT was then employed to clarify the chemical enhancement mechanism. The results obtained hopefully provide helpful information for the design of analytical sensors with lower costs.

Faster or Cheaper: A Q-learning based cost-effective mixed cluster scaling method for achieving low tail latencies

The cloud elasticity allows users to acquire resources and release useless resources as needed. This feature has attracted more and more web service providers to deploy their latency-crucial, user-oriented applications on cloud platforms. For web service providers, in the case of fluctuating workloads, scaling their server clusters over time could save system expenditures without service quality violations. Therefore, a lot of cloud platforms begin to offer automatic scaling strategies based on threshold-based rules for helping web service providers to save system expenditures. However, building threshold-based rules requires expertise, and such reactive scaling strategies cannot guarantee low and consistent tail latencies. For those proactive scaling strategies depending on predictions, random user behaviors lead to declines in prediction accuracy. In this paper, we propose a reinforcement learning based proactive strategy for scaling a mixed cluster, which is composed of a variety of cloud instances. Ensuring the availability and quality of reward signals is the main problem to be solved for algorithms based on standard RL. We design a reward function which could balance service cost, service quality and other parameters which can affect decision-making. We assign different weights to parameters based on their effects on decision-making. In order to avoid the explosion of the state space caused by fluctuating workloads and various server status, we discretize the continuous state space of our model. Experimental results based on TailBench show that our Q-learning based scaling method can maintain low and consistent tail latencies while achieving fewer costs than three common baselines.