Relative Surface Area Research Articles

Building Heating and Cooling Load Prediction Using Ensemble Machine Learning Model.

Building energy consumption prediction has become an important research problem within the context of sustainable homes and smart cities. Data-driven approaches have been regarded as the most suitable for integration into smart houses. With the wide deployment of IoT sensors, the data generated from these sensors can be used for modeling and forecasting energy consumption patterns. Existing studies lag in prediction accuracy and various attributes of buildings are not very well studied. This study follows a data-driven approach in this regard. The novelty of the paper lies in the fact that an ensemble model is proposed, which provides higher performance regarding cooling and heating load prediction. Moreover, the influence of different features on heating and cooling load is investigated. Experiments are performed by considering different features such as glazing area, orientation, height, relative compactness, roof area, surface area, and wall area. Results indicate that relative compactness, surface area, and wall area play a significant role in selecting the appropriate cooling and heating load for a building. The proposed model achieves 0.999 for heating load prediction and 0.997 for cooling load prediction, which is superior to existing state-of-the-art models. The precise prediction of heating and cooling load, can help engineers design energy-efficient buildings, especially in the context of future smart homes.

Trace Level Quantification of Lead in Michigan Lake Water Using Differential Pulse Stripping Voltammetry: A Comparative Study on the Usage of Mercury Based Electrodes Vs Solid State Gold Electrodes

The concentration of lead in fresh-water samples from the southern shoreline of Lake Michigan was analysed and compared using two different cell-stands: Controlled Growth Mercury Electrode (CGME) and voltammetry cell stand with disk type gold electrode. Clearly visible Lead (II) peaks at -395 mV and 130 mV were obtained with CGME and Au electrodes respectively using anodic stripping voltammetry (ASV) technique. Sensitivity, reproducibility, and ease of usage were differentiated for each method. While the measured lead concentration was 2.4 ppb using CGME set-up a closely similar concentration of 2.7 ppb was obtained with the gold disk electrode set-up and thereby confirms the availability of Hg-free detection of lead. The sensitivity obtained from the standard addition curve using the gold electrode was also over twice that of the CGME. The difference in background currents was attributed to the different electrode materials, bulk diffusion in electrolyte of lead ions, electrode-electrolyte interface and the relative surface areas of the electrode surface. Even after repeated polishing of gold electrodes in each run, its inherent sensitivity makes it an ideal candidate for lead determinations with no further requirement of handling the hazardous mercury wastes.

Prediction of Protein-Protein Interaction Sites by Multifeature Fusion and RF with mRMR and IFS.

Prediction of protein-protein interaction (PPI) sites is one of the most perplexing problems in drug discovery and computational biology. Although significant progress has been made by combining different machine learning techniques with a variety of distinct characteristics, the problem still remains unresolved. In this study, a technique for PPI sites is presented using a random forest (RF) algorithm followed by the minimum redundancy maximal relevance (mRMR) approach, and the method of incremental feature selection (IFS). Physicochemical properties of proteins and the features of the residual disorder, sequence conservation, secondary structure, and solvent accessibility are incorporated. Five 3D structural characteristics are also used to predict PPI sites. Analysis of features shows that 3D structural features such as relative solvent-accessible surface area (RASA) and surface curvature (SC) help in the prediction of PPI sites. Results show that the performance of the proposed predictor is superior to several other state-of-the-art predictors, whose average prediction accuracy is 81.44%, sensitivity is 82.17%, and specificity is 80.71%, respectively. The proposed predictor is expected to become a helpful tool for finding PPI sites, and the feature analysis presented in this study will give useful insights into protein interaction mechanisms.

Evaluation of the Effectiveness of Derived Features of AlphaFold2 on Single-Sequence Protein Binding Site Prediction.

Simple SummaryWith the development of artificial intelligence, researchers can roughly predict the crystal structure of a protein by computer without the need for biological experiments, which provides new ideas and solutions to problems, such as protein-protein interaction and drug-target predictions. In this study, we proposed strategies to combine predicted protein structures with deep learning networks and evaluated them on different protein binding site prediction tasks. Our computational experiment results showed that all proposed strategies could effectively encode structural information for deep learning models.Though AlphaFold2 has attained considerably high precision on protein structure prediction, it is reported that directly inputting coordinates into deep learning networks cannot achieve desirable results on downstream tasks. Thus, how to process and encode the predicted results into effective forms that deep learning models can understand to improve the performance of downstream tasks is worth exploring. In this study, we tested the effects of five processing strategies of coordinates on two single-sequence protein binding site prediction tasks. These five strategies are spatial filtering, the singular value decomposition of a distance map, calculating the secondary structure feature, and the relative accessible surface area feature of proteins. The computational experiment results showed that all strategies were suitable and effective methods to encode structural information for deep learning models. In addition, by performing a case study of a mutated protein, we showed that the spatial filtering strategy could introduce structural changes into HHblits profiles and deep learning networks when protein mutation happens. In sum, this work provides new insight into the downstream tasks of protein-molecule interaction prediction, such as predicting the binding residues of proteins and estimating the effects of mutations.

Use of the Kinect sensor measured three-dimensional reachable workspace to assess the upper extremity function in older adults.

We explored the utility of Kinect sensor-based upper extremity reachable workspace measure in healthy adults aged over 65years. Forty-three healthy older subjects (19 men and 24 women) aged over 65years and 22 healthy young subjects (11 men and 11 women) were included. All participants were ambulatory and perform the activities of daily living independently. Three-dimensional reachable workspace data were acquired for both arms using the Kinect sensor. We evaluated hand grip strength, manual muscle shoulder strength, and the active shoulder ranges of motion of the dominant and non-dominant sides. We assessed upper limb function using the Disabilities of Arm, Shoulder, and Hand (DASH) instrument and the health-related quality of life employing the descriptive EQ-5D-5L system. The quadrant 3 relative surface area in older adults was significantly smaller than that of young adults (both dominant and non-dominant sides), while the total and quadrants 1, 2, and 4 relative surface areas did not differ between older and young adults. However, the quadrant 3 relative surface area did not correlate with the DASH or EQ5D scores. The total and quadrant 1, 2, and 4 relative surface areas of the dominant side significantly correlated with the DASH score. The quadrant 4 relative surface area of the dominant side significantly correlated with the EQ5D score. Kinect sensor-based, three-dimensional, reachable workspace analysis may be useful to evaluate upper limb function in older adults.

Key Parameters Controlling the Photodesorption Yield in Interstellar CO Ice Analogs: The Influence of Ice Deposition Temperature and Thickness

The overabundance of gas molecules in the coldest regions of space points to a nonthermal desorption process. Laboratory simulations show the efficient desorption of CO ice that is exposed to ultraviolet radiation, known as photodesorption, which decreases with increasing ice deposition temperature. However, our understanding of this abnormal phenomenon still remains elusive. In this work, we show that the same phenomenon—and, in particular, a dramatic drop in the photodesorption yield—is observed when the deposition temperature is 19 K and higher. Also, the minimum ice thickness that accounts for a constant photodesorption yield of CO ice is dependent on the deposition temperature, an observation that is reported here for the first time. We propose that the key parameters dominating the absorbed photon energy transfer in CO ice, and contributing to the measured photodesorption yields, are the energy transfer length, the desorption yield contributed by a single ice layer, and the relative effective surface area. These parameters should be incorporated into astrophysical models that simulate the photodesorption of the top CO-rich ice layer in icy dust populations, with a size distribution that is related to the ice thickness.

Adsorption of Heavy Metals in Contaminated Water Using Zeolite Derived from Agro-Wastes and Clays: A Review

Due to climate change and anthropogenic activities such as agriculture, mining, and urbanization, water contamination has become a very real modern problem. Modern solutions such as activated carbon, reverse osmosis, and ultrafiltration, among others, have been employed in the decontamination of water. These methods are, however, expensive to set up and maintain and therefore have proved a challenge to implement in developing countries. Zeolite materials exhibit excellent structural properties, such as high ion exchange capacity, porosity, and relative surface area, which make them attractive to water decontamination processes. However, conventional zeolites are expensive, and recent research has focused on utilizing low-cost materials such as agro-wastes and clays as raw materials for the synthesis of zeolites. This review aims to discuss the role of low-cost zeolites in their removal of heavy metals and the feasibility of agro-wastes and natural clays in the synthesis of zeolites. Recent research studies based on the synthesis of zeolites from clays and agro-wastes and their application in heavy metal removal have been reviewed and discussed. Agro-wastes such as rice husk ash and sugarcane bagasse ash and layered silicate clays such as kaolinite and smectites are particularly of interest to zeolite synthesis due to their high silica to alumina ratio. Zeolites synthesized through various methods such as hydrothermal, molten salt, and microwave irradiation synthesis have been discussed with their effect on the adsorption of various heavy metals.

Size-dependent Scaling of Stingless Bee Flight Metabolism Reveals an Energetic Benefit to Small Body Size.

Understanding the effect of body size on flight costs is critical for development of models of aerodynamics and animal energetics. Prior scaling studies that have shown that flight costs scale hypometrically have focused primarily on larger (> 100 mg) insects and birds, but most flying species are smaller. We studied the flight physiology of thirteen stingless bee species over a large range of body sizes (1-115 mg). Metabolic rate during hovering scaled hypermetrically (scaling slope=2.11). Larger bees had warm thoraxes while small bees were nearly ecothermic; however, even controlling for body temperature variation, flight metabolic rate scaled hypermetrically across this clade. Despite having a lower mass-specific metabolic rate during flight, smaller bees could carry the same proportional load. Wingbeat frequency did not vary with body size, in contrast to most studies that find wingbeat frequency increases as body size decreases. Smaller stingless bees have greater relative forewing surface area which may help them reduce the energy requirements needed to fly. Further, we hypothesize that the relatively larger heads of smaller species may change their body pitch in flight. Synthesizing across all flying insects, we demonstrate that the scaling of flight metabolic rate changes from hypermetric to hypometric at approximately 58 mg body mass with hypermetic scaling below (slope=1.2) and hypometric scaling (slope=0.67) above 58 mg in body mass. The reduced cost of flight likely provides selective advantages for the evolution of small body size in insects. The biphasic scaling of flight metabolic rates and wingbeat frequencies in insects supports the hypothesis that the scaling of metabolic rate is closely related to the power requirements of locomotion and cycle frequencies.

‘Blue’ coasts: Unravelling the perceived restorativeness of coastal environments and the influence of their components

Outdoor environments benefit health by providing psychological restoration, but the degree of psychological restoration may vary considerably within heterogenous areas. This study focused on the Belgian coast to quantify the inter- and intra-environment variation in psychological restoration and the influence of natural and urban components and people.Students (N = 102, 18-30y, 83 % female) rated 52 pictures of ten coastal environments and of five beach-specific locations on a five-item perceived restorativeness scale (PRS) in random order. General linear mixed modelling standardized for individual and study design-related covariates and random effects.Generally, the average PRS-scores varied according to the scenes’ ‘naturalness’. The PRS was up to 30% higher for beaches, dunes, and salt marshes (PRS ≈ 8/10) than for dikes, docks, recreational harbors, and towns (PRS ≈ 5/10). Green parks, piers, and historical sites scored intermediate. At the beach specifically, pictures taken ‘on a breakwater’ (PRS ≈ 8.5/10) scored up to 20% higher than those taken ‘in a beach bar’ and ‘between beach cabins’ (PRS ≈ 6.5/10). The PRS was also associated with the relative surface area of the picture components. Associations were positive for natural components (i.e. vegetation, sky, and natural underground, not water), negative for urban components (i.e. buildings, vehicles and hardened underground), and unclear for people.This study confirmed the hypothesized inter- and intra-environment variation in the psychological restoration along the Belgian coast, and highlighted the importance of coastal nature for mental health. The generated insights can lead to better informed policy decisions to maximize the health benefits offered by coastal environments.

Phytovid19: a compilation of phytochemicals research in coronavirus.

The COVID-19 pandemic has immensely impacted global health causing colossal damage. The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has increased the quest to explore phytochemicals as treatment options. We summarize phytochemicals with activity against various coronaviruses including SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). We compiled 705 phytochemical compounds through text mining of 893 PubMed articles. The physicochemical properties including molecular weight, lipophilicity, and the number of hydrogen bond donors and acceptors were determined from the structures of these compounds. A structure-based evaluation of these properties with respect to drug likeness showed that most compounds have a positive score of drug likeness. QSAR analysis showed that 5 descriptors, namely polar surface area, relative polar surface area, number of hydrogen bond donors, solubility, and lipophilicity, are significantly related to IC50. We envisage that these phytochemicals could be further explored for developing new potential therapeutic molecules for COVID-19.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11224-022-02035-6.

Influence of luminescent powder type and characteristic on the glow light performance of architectural glass mortar

The effect of luminescent powder (LP) type and characteristics on the properties of architectural luminescent glass-mortars (ALM) was investigated. Four LPs including ZnS:Cu (LP1) and SrAl2O4:Eu2+,Dy2+ (LP2-4) with different particle sizes and surface conditions (with or without a protective layer) were coated on the surface of glass particles using an adhesive paint for producing luminescent glass (LG). LG was then used to replace coarse aggregate in conventional glass mortar for the production of ALM. The results showed that all ALMs obtained good fresh properties and mechanical strength (>40 MPa) with proper excitation and emission wavelengths ranging from 250 to 450 nm and 500–560 nm, respectively, demonstrating the feasibility of fabricating decorative concrete. Regarding the glow light performance, SrAl2O4:Eu2+,Dy2+ outweighed ZnS:Cu in all luminescent indexes including initial brightness (luminescent intensity), decay rate, and afterglow time. Coarser LP attained lower luminescent intensity but a better decay rate due to the its relative lower specific surface area. A protective layer on the LP surface (surface condition) inhibited its light absorption and emission capacity, leading to poor luminescent performance. The adhesive paint used for producing LG, having poor UV aging resistance, was susceptible to sunlight degradation, reflected by colour turning into brown. The darker colour reduced its light transmitting efficiency, inducing a decrease in glow light performance of ALM. The excellent water and wearing resistance of ALM allowed maintaining their luminescent performance under extreme environment conditions.

Sensor acquired reachable workspace in the elderly population: A cross-sectional observational study.

The elderly population experiences a decline in upper extremity range of motion (ROM), impairing activities of daily living. The primary mode of quantification is by goniometer measurement. In this cross-sectional observation study, we investigate a sensor-acquired reachable workspace for assessing shoulder ROM decline in an elderly population in comparison to traditional measurements.Sixty-one healthy subjects aged ≥ 65 years were included and compared to a cohort of 39 younger subjects, aged 20 to 64. A sensor acquired reachable workspace using a Kinect motion capture camera measured the maximum reaching ability of both arms while in a seated position, measured in m2 and normalized to arm length to calculate a novel score defined as a relative surface area. This score approximates range of motion in the upper extremity. This measurement was compared to goniometer measurements, including active ROM in shoulder flexion and abduction.Total RSA shows moderate to strong correlation between goniometer in flexion and abduction in the dominant arm (R = 0.790 and R = 0.650, P < .001, respectively) and moderate correlations for the nondominant arm (R = 0.622 and R = 0.615, P < .001). Compared to the younger cohort, the elderly population demonstrated significantly reduced total RSA in the dominant arm (meanelderly = 0.774, SD = 0.09; meanyounger = 0.830, SD = 0.07, P < .001), with significant reductions in the upper lateral quadrant in both arms (dominant: meanelderly = 0.225, SD = 0.04; meanyounger = 0.241, SD = 0.01; P < .001; nondominant: meanelderly = 0.213, SD = 0.03; meanyounger = 0.228, SD = 0.01; P = .004). The test-retest reliability was strong for both dominant and nondominant total RSA (ICC > 0.762).The reachable workspace demonstrates promise as a simple and quick tool for clinicians to assess detailed and quantitative active shoulder ROM decline in the elderly population.

Trace Analysis of Lead in Michigan Lake Water Using Differential Pulse Stripping Voltammetry: A Comparative Study on the Usage of Controlled Growth Mercury Electrodes Vs Solid State Gold Electrodes

The concentration of lead in fresh-water samples from the southern shoreline of Lake Michigan was analyzed and compared using two different cell-stands: Controlled Growth Mercury Electrode (CGME) and voltammetry cell stand with disk type gold electrode. Clearly visible Lead (II) peaks at -395 mV and 130 mV were obtained with CGME and Au electrodes respectively using anodic stripping voltammetry (ASV) technique [1-4]. Sensitivity, reproducibility, and ease of usage are compared and reported for each method. While the measured lead concentration was 2.4 ppb using CGME set-up a closely similar concentration of 2.7 ppb was obtained with the gold disk electrode set-up. The sensitivity obtained from the standard addition curve using the gold electrode was over twice that of the CGME. The difference in background currents was attributed to the different electrode materials, bulk diffusion in electrolyte of lead ions, electrode-electrolyte interface and the relative surface areas of the electrode surface. The main convenience associated with the CGME was the fresh electrode surface provided by each new drop, so no further electrochemical cleaning was needed. However, even after repeated polishing of gold electrodes in each run, its inherent sensitivity makes it an ideal candidate for lead determinations with no further requirement of handling the hazardous mercury wastes. Figure 1

Ultrasensitive and multiplex detection of four pathogenic bacteria on a bi-channel lateral flow immunoassay strip with three-dimensional membrane-like SERS nanostickers

A lateral flow immunoassay (LFA) technique for sensitive and multiplexed on-site detection of bacteria remains a challenge. Here, we develop a bi-channel surface-enhanced Raman scattering (SERS)-based LFA by using three-dimensional membrane-like SERS tags as nanostickers (named GO@Au/Ag) for direct and ultrasensitive analysis of multiple pathogens in a single test. The grafting of numerous Ag satellites onto nanosticker significantly increased the relative surface area for bacteria binding and generated efficient SERS hotspots over large area to improve the sensing sensitivity. Antibody-labeled GO@Au/Ag nanostickers can rapidly stick onto the target bacteria and generate superior SERS signals and fluidity on the paper strip, thus conquering the adverse effect of bacteria size and improving the multiplex analysis ability of LFA. The integration of two different Raman reporter molecules into nanostickers allows simultaneous detection of four pathogens on two test lines, which significantly simplifies the reading process of SERS signals. The proposed biosensor can quantitatively detect four different bacteria in real clinical samples with low detection limit (9 cells mL−1 level), short assay time (20 min), high accuracy and excellent stability, indicating its great application potential for on-site detection of pathogens.

Reachable workspace analysis is a potential measurement for impairment of the upper extremity in neuralgic amyotrophy.

Introduction/AimsNeuralgic amyotrophy (NA) is a multifocal neuropathy involving the nerves of the upper extremity, limiting functional capability and reducing range of motion. The reachable workspace (RWS) is a computerized three‐dimensinal analysis system that evaluates the relative surface area (RSA) of an individual's arm reachability and has shown utility in several neuromuscular disorders. The aims of this study were to examine the ability of the RWS to quantitatively detect limitations in upper extremity active range of motion in patients with NA, and correlate these with other upper extremity functional outcome measures.MethodsForty‐seven patients with NA and 25 healthy age‐ and sex‐matched controls were measured with the RWS. Study participants’ RSAs were correlated with scores on the Shoulder Rating Questionnaire (SRQ), the Disabilities of Arm Shoulder and Hand (DASH) questionnaire, and upper extremity strength measurements using hand‐held dynamometry.ResultsPatients with NA showed significantly lower values in the affected arm for all quadrants (except for the ipsilateral lower quadrant) and total RSA compared with controls (P < 0.001). We found moderate correlations between the reachable workspace, the DASH questionnaire result (r = −0.415), and serratus anterior muscle strength (r = 0.414).DiscussionRWS is able to detect limitations in active range of motion of the affected arm in patients with NA, and is moderately correlated with upper extremity functional measures. RWS can demonstrate impairment of the affected upper extremity in NA and it has potential as a clinical outcome measure.

Epigenetic regulation at LRP1 risk locus for cardiovascular diseases and assessment of cellular function in hiPSC derived smooth muscle cells

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Research Council (ERC) Background/Introduction Spontaneous coronary artery dissection (SCAD) is an increasingly recognized cause of myocardial infarction in young and middle-aged women. A common genetic variant, rs11172113, located in LRP1 (low density lipoprotein receptor-related protein 1) first intron, was associated with several vascular diseases, including SCAD, coronary artery disease and migraine. However, the biological mechanisms through which rs11172113 influence LRP1 function in the context of non-atherosclerotic arterial lesions is not fully understood. Purpose We aim at defining the specific mechanisms of rs11172113 genotype affecting LRP1 expression in contractile smooth muscle cells (SMCs), leading to alterations of their physiological function. Methods We applied in silico functional annotation to select variants and measured their enhancer activity using luciferase reporter assay in rat primary SMCs (A7r5). We performed siRNA knockdown of LRP1 and 4 transcription factors (TFs) predicted to interact with rs11172113 in human induced pluripotent stem cells (iPSCs) derived SMCs, harboring either synthetic or contractile phenotype. We edited iPSCs prior to differentiation using CRISPR-Cas9 to generate 100 bp deletion of the enhancer region containing rs11172113. We also created frame-shift indels in exons 2 or 5 of LRP1 in iPSCs to create SMCs knockouts and differentiated into SMCs. We then performed a proteomic and transcriptomic characterization of LRP1 knockout effect in these iPSC derived SMCs. We used a computational method of cell tracking and relative cell surface area change to characterize the contractility of LRP1 knockout effect in these iPSC derived SMCs. We performed the assessment of fluo-4 labeled Ca2+ mobilization to characterize the ability of calcium release in iPSC derived SMCs after LPR1 knockout. Results Seven variants in LRP1 locus co-located with enhancer (histone marks) and open chromatin regions (ATAC-Seq peaks) in SMCs and arterial tissues. Reporter assay in rat SMCs confirmed that rs11172113 belongs to a genomic region showing enhancer activity in vitro. iPSCs with homozygous deletion of rs11172113 enhancer region presented the same pluripotency compared with wild type, and iPSC derived SMCs showed positive expression of specific markers for each phenotype (ACTA2, TAGLN for both, MYH11 for contractile SMCs and CALM2 for synthetic SMCs). We found that the deletion of rs11172113 enhancer region decreased the expression of LRP1 while LRP1 knockdown increased cell migration capacity in SMCs. Preliminary results in LRP1-knockout iPSC-derived SMCs suggest LRP1 to enhance the expression of cell contraction markers and decrease capacity of cell proliferation. Conclusions We confirmed rs11172113 to regulate LRP1 expression in iPSCs derived synthetic and contractile SMCs. Our results support LRP1 effect on SMCs cellular function alteration as a potential mechanism in genetic susceptibility for vascular disease.

Effect of Milling Time and PCA on Electrode Properties of Cu2O-ZnO/C Catalyst Alloy used on Electrochemical Reduction Method of CO2

Carbon dioxide is one of the greenhouse gases that cause climate change, thus the effort for reducing the concentration of CO2 necessary, for example through the conversion of CO2. The conversion of CO2 into methanol plays important role, because in addition to reducing greenhouse gas, it is also creating a future energy carrier needed in fuel cell technology. One of the CO2 conversion methods is the electrolysis method using MEA. The electrochemical CO2 conversion in this study used a Cu2O-ZnO/C composite catalyst made by milling methods at various milling times, as well as the effect of PCA utilization. The catalysts were characterized using Particle Size Analyzer (PSA), Brunauer-Emmett-Teller (BET), Cyclic Voltammetry (CV), Electrochemical Impedance Spectroscopy (EIS) and SEM-EDX analysis. The results of PSA and BET characterization showed that the longer the milling time, the smaller the particle size and the higher the relative surface area. The use of PCA increased the unoxidized Cu content as indicated by the SEM-EDX results. Based on the results of CV analysis, the catalyst that has the largest ECSA (Electrochemical surface area) value is the catalyst milled using PCA and the milling time is three hours.

How to estimate R50% for cranial SRS/SRT cases with overlapping 50% isodose volumes: A proposed system.

Inevitably in clinical stereotactic cranial single isocenter multiple target cases treated with linac‐based multi‐leaf collimated (MLC) delivery, one encounters planning target volumes (PTVs) in close proximity with overlapping 50% isodose clouds (IDC50%). In such cases, it is very difficult to separate the IDC50% attributable to each individual target and, thus, assess the intermediate dose conformality or R50%. Such scenarios happen regardless of what metric is used to measure intermediate dose spill. Now that universal standards for intermediate dose spill have been proposed, it is important to have a consistent method for apportioning these overlapping IDC50% volumes to allow comparison with the proposed standards when multiple PTVs have overlapping IDC50%. We propose a systematic method for apportioning the IDC50% of multiple targets with overlapping IDC50% based on the relative surface area of each target volume; we call this the fair value estimate (FVE). This FVE system of apportionment is tested for reasonableness by comparing the apportionment of multiple target single isocenter stereotactic treatment with widely spaced targets where the IDC50% can be obviously assigned to demonstrate that the FVE results are very similar to the actual R50% results. We then demonstrate how the FVE system would be applied to cases with overlapping IDC50%. We propose this FVE system for consideration by the cranial stereotactic community for apportioning the intermediate dose spill when that intermediate dose spill overlaps among multiple targets.

Molybdenum active sites implanted defective UiO-66(Zr) for cyclohexene epoxidation: Activity and kinetics investigation

Defect engineering is a versatile method to modulate structure and performance of crystalline materials yet remain sophisticated. Herein, Zr-based metal organic frameworks (i.e., UiO-66) featuring controlled structural defects and single Mo active sites, namely Mo@UiO-66-xy (x represented molar equivalents and y denoted the modulator, acetic acid or formic acid, with respect to the linker), were synthesized to systematically conduct activity and kinetics investigation on microscopic level. It was determined that the predominant defects, missing-cluster defects, could be tuned to a large extent via altering molar equivalents of formic acid not acetic acid. Further, it was established that intrinsic Lewis acid acidity was positively correlated with formic acid concentration. All Mo@UiO-66-xy exhibited catalytic activity in cyclohexene epoxidation and Mo@UiO-66-100for showed the highest catalytic performance due to its relative strong Lewis acid acidity and suitable specific surface area / porosity-derived attractive high Mo sites-dispersion and mass-transfer property. Additionally, for the first time, a kinetic measurement that considered two reaction pathways and all products was performed as a function of reaction temperature to evaluate activation barrier for cyclohexene epoxidation. That was, cyclohexene epoxidation to epoxide activation energies determined for direct and radical routes were 46.12 and 102.46 kJ mol−1, respectively, and Mo@UiO-66-100for was inclined to act along direct pathway to stimulate cyclohexene epoxidation.

Flexible ligand for Metal-Organic frameworks with simultaneous Large-Pore and antenna effect emission

Polycyclic aromatic ligands improve the pore size of metal–organic frameworks (MOFs), but their big π-conjugation structure forbids energy transfer for antenna effect emission. Thus, large-pore and antenna effect are a dilemma even their combination could improve the efficiency of MOFs. Herein, we construct a flexible ligand, 1,3,5-tris(5-methoxy-1,3-benzene dicarboxylic acid)benzene (L1) by attaching three isophthalic acids (L2) to a benzene ring through flexible –CH2-O- bonds. L1 retains the optical properties of L2 for antenna effect and expands the molecular size for MOFs with large pore. Single-crystal result of the MOFs obtained with L1 and Eu3+, Tb3+, or Gd3+ reveals the aperture of 18 Å and the density of 1.2 g/mL. L1 excites Eu3+ and Tb3+ ions for their antenna effect emission. The –CH2-O- group tunes the energy transfer for dual-emission at 360 and 623 nm from L1-Eu MOF under single excitation of 290 nm. The dual-emission is used for ratiometric fluorescence detection of phosphate (PO43-) and adenosine-5′-triphosphate (ATP). We reveal the effect of porous structure of MOFs on the response speed and range. The pore size affects the target entrance as L1-Eu MOF shows faster response to PO43- and ATP than L2-Eu MOF. Moreover, fast diffusion dynamics of a target is observed in large-pore MOFs for good linear response. The relative specific surface area affects the linear range as a narrower range was observed for ATP than PO43-. Thus, flexible ligand is effective to expand the aperture, improve optical properties, and study the response mechanism for the extensive applications of MOFs.