Reference Data Research Articles

Validity of IMU sensors for assessing features of walking in laboratory and outdoor environments among older adults

IntroductionIMU sensors (three-dimensional accelerometer, gyroscope and magnetometer) enable assessment of walking in older adults outside the laboratory. We studied whether IMUs are valid for detecting walking parameters (step events, time, length, and cadence) in a laboratory and outdoors on a level surface in older adults. MethodsThis validation study is part of a larger cross-sectional study. Twenty-six participants (mean age 76 years, 65 % female) walked on a treadmill indoors and on a sport track outdoors at self-selected speed. IMUs were attached laterally on the shanks and on the lower back at the level of L3-L4. Initial contact (IC) and step lengths were also estimated using acceleration signals (vertical, antero-posterior) from the pelvic IMU. Terminal contact (TC) was determined from the shank IMU sagittal angular velocity. For step length, inverted pendulum model and participant’s leg length (0.53 x height) was used. Step duration was calculated from IC to the opposite leg IC and stride duration from IC to next ipsilateral IC. Cadence was calculated as steps/min. As reference data, 3D motion capture was used in the laboratory and a high-speed video camera outdoors. Intraclass correlation coefficients (ICC), root mean squared errors (RMSE), typical errors and Bland-Altman plots were calculated and drawn. ResultsWhen comparing IC timing between IMU and reference data, mean bias was 0.031 s in the laboratory and −0.004 s outdoors, and for TC −0.057 s and −0.070 s respectively. Step and stride duration and cadence showed ICC values >0.80 and mean bias was <0.005 s for step and stride durations and <0.05 steps/min for cadence in both environments. Step length ICC values were <0.40 in the laboratory and outdoors. SignificanceIMUs can be used to monitor temporal walking variables in older adults and may be useful for rehabilitation interventions and functional capacity assessment.

A low-cost alternative to LiDAR for site index models: applying repeated digital aerial photogrammetry data in the modelling of forest top height growth

Abstract Environmental and forest structural information derived from remote sensing data has been found suitable for modelling forest height growth and site index and therefore forest productivity assessment, with the advances in airborne laser scanning (ALS) playing a major role in this development. While there is growing interest in the use of ALS-derived point clouds, point clouds from high-resolution digital aerial photography (DAP) are also often used for mapping and estimating forest ecosystem properties due to their lower acquisition costs. In this study, we document the applicability of bi-temporal DAP data for developing top height (TH) growth models for Scots pine stands. Our results indicate that DAP data can function as an alternative to traditional TH measurements used in growth modelling when corrected based on a limited sample of field-measured reference TH values. As the correction cannot be constant for each DAP dataset due to the different parameters during data acquisition, we propose a straightforward method for the bias correction of DAP-derived TH estimates. By undertaking iterative random sampling, we were able to find the minimum number of reference measurements needed to calculate the TH correction in order to achieve the desired accuracy of the TH estimations based on DAP. Here, we used ALS data as the reference data; however, the ALS measurements can be replaced by any other reliable source of TH values. The presented method for determining TH can be used not only for site index and forest growth modelling but also in forest inventories.

Experimental study of flame morphology in slope buildings under the influence of aspect ratio and ambient wind

Slope structures are commonly used in buildings, but such slope structures can exacerbate the rate of fire spread, complicate building fire safety and suppression, and lead to injuries, deaths, and property damage. Particularly, the thermal hazards posed by ambient wind on sloped fires remain unquantified. In this study, a propane burner was used to simulate the flame morphology behavior of a sloped building fire. 480 tests were conducted with varying aspect ratios (1∼8) of the fire source, different ambient winds (0 m/s∼3.5 m/s), and slope inclination angles (0°∼40°). Results demonstrate that the flame length initially increases and then decreases with an increment in ambient wind velocity. Moreover, with an increased aspect ratio of the fire source (length-to-width ratio), the turning point at which the flame length peaks shift to occur at a lower wind velocity threshold. The tilt angle and height of the flame change (respectively increases and decreases) significantly at lower ambient wind speeds and they tend to asymptotically approach respective constant values. As the ambient wind is further promoted. Existing physical models of flame morphology do not consider the combined effects of fire source aspect ratio, slope inclination angle, and ambient wind. A new slope entrainment restriction factor (EF) was proposed based on an analysis of the upward and leeward entrainment volumes. Using this factor, new models for flame morphology (including flame length, flame tilt angle, and flame height) were established. The accuracy and generalizability of the new flame models have been validated using reference data.

Resource budget model with Duffing oscillator for dynamics of synchronized biennial-bearing olives in the Levant

We develop and analyze a temporally continuous spatially lumped resource budget model to explain the dynamics of synchronized biennial-bearing olives in the Levant, specifically focusing on Syria, the region’s foremost olive-producing country. The model is a time-continuous counterpart of the celebrated resource budget model. It consists of a Duffing oscillator coupled with a dynamical model of pollination with an external force propelling olive growth by photosynthesis. The reference data are obtained from statistical databases of international organizations and our own observation systems in Jordan, a country neighboring Syria, providing a wealth of information to refine the model structure. An intensive review of Syria’s modern history involving significant shifts in agricultural policy and social stability leads to a conclusion that the model should comprehend the anomaly of olive yield interacting with socio-political factors as an autonomous behavior. The conventional mathematical methodology analyzes the model’s characteristics, such as solutions’ non-negativity, boundedness, and stability. The system is stable during pollination off-season but may become unstable and unbounded during pollination on-season, which is a property that the time-discrete resource budget model cannot reproduce. A significant finding is that coupling individual fruit trees by anemophily is not essential in synchronization, overturning earlier studies in the literature. The values of model parameters that best fit the historical data of olive yield in Syria result in bounded chaos. With alternative parameter values, the model could exhibit periodic oscillation, instability, or blowing up, as clearly shown in bifurcation diagrams.

Normative In-Game Data for Collegiate Baseball Pitchers Using Markerless Tracking Technology.

The current standard for motion capture data collection in baseball biomechanics is marker-based optical motion capture. Recent advancement in markerless motion capture capabilities has greatly improved accessibility to in-game, high-precision motion capture data, but specific values may differ from markered systems, necessitating separate normative values. For future data comparison, reference data are needed. To describe common kinematic variables in baseball pitching using an in-game markerless motion capture system. Descriptive laboratory study. Kinematic data were collected in 2 collegiate stadiums in the National Collegiate Athletic Association Division I Southeastern Conference using 8 synchronized 300-Hz KinaTrax cameras placed around the playing field. The in-game biomechanics data of 51 pitchers from 5 different teams during the 2023 season were collected; only pitchers with >3 outings during the season were included. After averaging all available fastballs thrown in the first inning of a game, we analyzed triaxial trunk (rotation, flexion, and lean) and pelvic rotation angles in the global reference frame, as well as shoulder rotation, shoulder horizontal abduction, shoulder abduction, elbow flexion, stride knee flexion, and hip-shoulder separation. A total of 509 fastballs were analyzed. Mean fastball velocity was 40.98 m/s (91.5 mph), with a vertical break of 42.0 ± 10.6 cm (16.5 ± 4.2 inches) and a horizontal break of 28.0 ± 11.1 cm (11.0 ± 4.4 inches). Mean stride length was 1.41 ± 0.08 m. The mean arm slot was 59.4°± 9.3°, and the mean upper arm slot was 72.9°± 9.3° at ball release. Additional normative time-series data are presented for commonly analyzed variables, and discrete metrics are provided at distinct time points in the pitching cycle. These data fill a need for separate norms for in-game, markerless motion capture performance metrics, and biomechanics for collegiate baseball pitchers to be used as reference values for researchers, coaches, and clinicians. Clinicians should use these results as reference values to contextualize injury mechanisms and the injury-performance trade-off. These data will also educate clinicians on what athletes' bodies must do to perform when constructing plans of care and return-to-play timelines.

Effect of low degree succinylation on properties of enzyme-induced casein hydrogel

This study examines the impact of succinic anhydride (SA) modification (0–9 %) on the gel properties of casein. Upon succinylation, the surface hydrophobicity (H0) of casein initially increased before decreasing, achieving its peak at a degree of succinylation of 5.22 ± 0.16 %. The α-helix content rose to 14.13 ± 2.60 %, and the -OH peak shifted towards lower wavenumbers, suggesting enhanced hydrogen bonding within intra/intermolecular structures. The storage modulus in the rheological test escalated from 2160.11 Pa to 5047.60 Pa, and SEM analysis revealed that the optimally succinylated casein gel formed a denser and more stable gel network structure. Moreover, succinylated casein hydrogels demonstrated superior texture properties, swelling ability, and thermal stability. Molecular dynamics simulation (MD) results suggest that SA preferentially binds to LYS27 and LYS28 of β-casein via hydrogen bonds and amide bonds, respectively. The interaction between modified proteins is primarily governed by hydrogen bonds, aligning with FT-IR findings. PCA analysis identified a positive correlation between the ordered structure and gel performance. This research offers theoretical insights and reference data for modulating casein hydrogel properties through succinylation.

Simplified inverse distance weighting-immersed boundary method for simulation of fluid-structure interaction

When simulating fluid-structure interaction (FSI) problems involving moving objects, the implicit inverse distance weighting-immersed boundary method (IDW-IBM) developed by Du et al. [1] has to construct a large square correlation matrix and solve its inversion at each time step. In this work, a simplified inverse distance weighting-immersed boundary method (SIDW-IBM) is proposed to eliminate the intrinsic limitations in the original implicit IDW-IBM. Through error analysis using Taylor series expansion, a second order approximation can be derived, which allows us to approximate the large square correlation matrix into a diagonal matrix; thereby, we proposed the SIDW-IBM based on this second order approximation to explicitly evaluate the velocity corrections, where the needs to assemble the large correlation matrix and inverse it are circumvented. Owing to the fact that the inverse distance weighting interpolation removes the limitations in the Dirac delta function, the proposed SIDW-IBM has been successfully implemented on the non-uniform meshes to further improve the computational efficiency. The proposed SIDW-IBM is integrated with the reconstructed lattice Boltzmann flux solver (RLBFS) [2] to simulate some classic incompressible viscous flows, including flow past an in-line oscillating cylinder, flow past a heaving airfoil, and flow past a three-dimensional flexible plate. The good agreement between the present results and reference data demonstrates the capability and feasibility of the SIDW-IBM for simulating FSI problems with moving boundaries and large deformations.

Efficiency of the decision support system for determining the severity of scoliotic spinal deformity by the analysis of radiographs

BACKGROUND: In 2020, a decision support system was developed at expense of grant from Innovation Promotion Fund and integrated into medical base of prosthetic and orthopedic center “Sсoliologic.ru.” It is the first computer program for determining severity of scoliotic spinal deformity in analysis of radiographs. AIM: To evaluate performance of a computer program for determining Cobb angle by comparing obtained automated data with manual measurement data by various specialists. MATERIALS AND METHODS: From medical base of prosthetic and orthopedic center “Sсoliologic.ru,” 411 digital radiographs of spine of children and adolescents were selected, which were drawn by a radiologist (BP-etalon), an orthopedic traumatologist with 5 years of experience and experience in vertebrology (OO), and an orthopedic traumatologist with less than 1 year of experience and no experience in vertebrology (OB) and computer program (KP). The number and proportion of exact matches and mean absolute percentage error (MAPE) of results of measuring the Cobb angle of reference data were compared with indicators obtained by OO, OB, and KP in, for various types of scoliosis according to the classification of Rigо, as well as in determining the main arc. Bland–Altman graphs were used. The mean absolute deviation (MAD) and MAPE for the main arc with magnitude ranging from 20° to 50° were calculated. RESULTS: The exact matches of KP with standard were 21%. Hence, every fifth measurement of the Cobb angle on X-ray, calculated automatically, was identical to standard. The highest proportion of matches with standard was noted in OO (33%), and the lowest in OB (16%). The highest accuracy of KP was found at types E1 and E2, and the arc of 3 was 30% and 24%, respectively. The proportion of KP matches with standard increased to 61%, with an error of 3°, and to 75%, with an error of 5°; with an error of 7°, the proportion of matches reached 84%. Moreover, the proportion of coincidences of a non-experienced researcher increased from 34% to 58%. When determining magnitude of the main arc of scoliosis, OO increased his/her accuracy by almost 2,6 times, KP by 2,1 times, and OB by 1,5 times. The MAD of KP for all major arcs was 3.8°. Good reliability of the obtained KP indicators compared to the reference (ICC = 0.9) was noted. CONCLUSIONS: The use of a computer program may be recommended for automated determination of Cobb angle, because current algorithm of computer program has been found to be accurate compared to reference measurement. Its accuracy was significantly higher than that of novice orthopedic traumatologists with no experience in vertebrology.

Hunting for Sulfur-containing Molecules in Space: A Spectroscopic Characterization of Cyclopropenethione Based on High-level Ab Initio Calculations

Cyclopropenethione falls into the class of complex organic molecules but has not yet been observed in the interstellar medium or any circumstellar disks. However, its existence is very likely, and thus this study provides high-level ab initio predictions, which may serve as reference data for future observations or experimental work. Rovibrational configuration interaction theory based on multidimensional potential energy surfaces being obtained from explicitly correlated coupled-cluster calculations has been used to predict the fundamental vibrational modes, the microwave spectrum, and low-lying rovibrational transitions. Rotational constants as well as quartic and sextic centrifugal distortion constants were obtained from vibrational perturbation theory.

Large eddy simulation of highly underexpanded sonic jets from elliptical nozzles

The injection of high-pressure jets into quiescent air poses significant challenges in fluid dynamics, pertinent to various industrial engineering applications. This study used large eddy simulations on a massively parallel computational framework, employing a grid of over 600 million nodes, to investigate the behavior of highly underexpanded sonic jets from elliptical nozzles at a nozzle pressure ratio of 15. Three elliptical nozzles, with aspect ratios of 1.5, 2.2, and 3.0, each having a sectional area equivalent to that of a circular jet with a diameter of D=1 mm, were analyzed. The aim was to clarify the gasdynamic and mixing characteristics of these jets to guide the design of next-generation injectors. A detailed analysis of the flow provided insights into the mechanisms of turbulence generation and Reynolds stress anisotropy. This was achieved using the componentality contour approach and a modified barycentric color mapping scheme, offering valuable reference data for developing lower-order models. The results indicate a non-axisymmetric radial expansion of the jet boundary in all elliptical injectors, leading to an axis switch phenomenon. The use of elliptical orifices was found to reduce jet penetration, mitigating issues such as fuel impingement in small engine combustion chambers and promoting improved air–fuel mixing quality.

Enhancing Sensitivity in Detecting Severe Fever With Thrombocytopenia Syndrome Virus: Development of a Reverse Transcription-Droplet Digital Polymerase Chain Reaction.

Severe fever with thrombocytopenia syndrome (SFTS) is a highly fatal disease. Droplet digital polymerase chain reaction (ddPCR) presents unparalleled sensitivity and enables absolute quantification of viral load. In this prospective study, we enrolled 111 patients with SFTS and collected 259 continuous samples. Our findings unveil a robust reverse transcription (RT)-ddPCR method for SFTS with a limit of detection of 2.46 copies/µL (95% CI, 1.50-11.05), surpassing the sensitivity of RT-quantitative polymerase chain reaction at 103.29 copies/µL (95% CI, 79.69-216.35). Longitudinal cohort analysis revealed significantly higher RT-ddPCR detection rates at days 10 to 11, 13 to 14, and ≥15 of the disease course as compared with RT-quantitative polymerase chain reaction (P < .05). Positive RT-ddPCR results were associated with declined platelet and elevated aspartate aminotransferase and lactate dehydrogenase on the same day vs negative RT-ddPCR samples. RT-ddPCR exhibits commendable diagnostic efficacy in SFTS, and it remains detectable in blood samples from patients with an extended disease course. Furthermore, RT-ddPCR correlates with clinical laboratory tests, furnishing valuable reference data for clinical diagnosis.

Optimization of field asymmetric ion mobility spectrometry-based assessment of Aphanomyces root rot in pea

When plants are infected with pathogens, disease response can result in changes in the profiles of volatile organic compounds (VOC). These changes in volatile organic compounds (VOC) profiles can be utilized for disease detection and quantification. In this study, field asymmetric ion mobility spectrometry (FAIMS) was used to evaluate the VOC profile variability in a pea near isogenic line (Pisum sativum L.) inoculated with zoospores of Aphanomyces euteiches Drechs, which causes Aphanomyces root rot disease. Pots were filled with silica sand and six plants per pot were grown under controlled conditions in a randomized complete block design with four replications. Four treatments, namely non-inoculated, 1 x 105, 1 x 106, and 2.79 x 106 zoospores ml−1 were applied to plants at 5 and 7 days after emergence. FAIMS was used to collect volatile profiles at 2, 4, 7 and 9 days after inoculation. Specific regions of interest – extracted from the 3D ion current intensity from the FAIMS spectra – were analyzed using ANOVA, Similarly, multiple regions of interest were evaluated using principal component analysis and k-means clustering. Ion current profiles and curvature profiles were incorporated into the analysis using k-means clustering. Other ground reference data such as root rot index and physiological parameters were also recorded. The results showed a biomarker in a specific region of interest demonstrating ample ability to quantify and differentiate treatment effects during non-destructive sampling at 14 DAE (7 DAI). Data from this region could be used for early and non-destructive quantification and differentiation of treatment effects based on zoospore inoculation levels. The k-means clustering of ion current and curvature profiles showed patterns based on the treatments. These findings demonstrated that FAIMS could be used as a tool to assess plant-pathogen interactions using volatile biomarkers to evaluate disease responses and severity under controlled conditions.

Assimilation of Sentinel‐1 Backscatter to Update AquaCrop Estimates of Soil Moisture and Crop Biomass

AbstractThis study assesses the potential of regional microwave backscatter data assimilation (DA) in AquaCrop for the first time, using NASA's Land Information System. The objective is to assess whether the assimilation setup can improve surface soil moisture (SSM) and crop biomass estimates. SSM and crop biomass simulations from AquaCrop were updated using Sentinel‐1 synthetic aperture radar observations, over three regions in Europe in two separate DA experiments. The first experiment concerned updating SSM using VV‐polarized backscatter and the corrections were propagated via the model to the biomass. In the second experiment, the DA setup was extended by also updating the biomass with VH‐polarized backscatter. SSM was evaluated with local in situ data and with downscaled Soil Moisture Active Passive (SMAP) retrievals for all cropland grid cells, whereas crop biomass was compared to SMAP vegetation optical depth and the Copernicus dry matter productivity. The assimilation showed mixed results for root mean square error and Pearson's correlation, with slight overall improvements in the (anomaly) correlations of updated SSM relative to independent in situ and satellite data. By contrast, the biomass estimates obtained with backscatter DA did not agree better with reference data sets. Overall, the SSM evaluation showed that there is potential in using Sentinel‐1 backscatter for assimilation in AquaCrop, but the present setup was not able to improve crop biomass estimates. Our study reveals how the complex interaction between SSM, crop biomass and backscatter affect the impact and performance of DA, offering insight into ways to optimize DA for crop growth estimation.

Bacterial community succession and its correlation with the dynamics of flavor compound during processing of Enshi bacon

Enshi bacon, a famous specialty in Enshi Prefecture, Hu Bei, China, is renowned among customers for the nutritious content and distinct smoky flavor. This study explored the flavor and bacterial flora changes of Enshi bacon during processing and investigated the effect of bacteria on flavor formation. The results showed that the main genera in the pre-processing stage were Brochothrix, Lactococcus and Psychrobacter, which originated from raw meat. Salt-tolerant Staphylococcus and Cobetia were the dominant genera in the late stage of processing. Five free amino acids (aspartic acid, glutamic, alanine, valine, and lysine) were recognized as the flavor substances promoting taste, while aldehydes and phenols were the volatiles that contributed the most to odor. Particularly, compared to the smoking phase, phenolic content increased 2.25-fold at the end of fermentation through microbial action and tyrosine catabolism. The correlation study showed Staphylococcus and Lactococcus as fundamental functional genera that are essential for the formation of bacon flavor. This study provided reference data for the changes in flavor indicators and flora during the processing of Enshi Bacon, revealed the potential mechanism of core functional flora and characteristic flavor formation, and provided a theoretical basis for quality control of the manufacturing process.

Korean-specific internal dosimetry data for radioiodine bioassay and evaluation of the dosimetric impact

Our earlier works focused on exploring the Korean iodine biokinetic model and calculating Korean-specific S values and dose coefficients. Building on this foundation, this study extended our efforts to establish an extensive dosimetry dataset for Korean-specific iodine bioassay. We calculated bioassay functions (e.g., thyroid retention and urinary excretion functions), dose-per-content-functions, and content for the specified doses based on the Korean biokinetic model and dose coefficients previously developed. Also, this study provides a comprehensive understanding of the practical impact of using Korean-specific dosimetry data. Compared to the ICRP reference data, the thyroid retention functions for Koreans were significantly lower (for I-131, peaks at 18% vs. 27%). The physical half-lives of radioiodine played a significant role in the differences of dose-per-content-function. For long-lived iodine isotopes such as I-125, the dose-per-content-functions were comparable to ICRP data, whereas for short-lived iodine isotopes such as I-131, the higher values were observed in the Korean data, indicating a greater dose estimation for a given iodine activity measured in the thyroid. Although we revealed the differences between Korean and ICRP reference data, the comprehensive understanding of Korean data suggests that using the Korean-specific data should be considered only when high doses are predicted.

Microwave-assisted Synthesis of Benzimidazole Derivatives: A Green and Effective Approach

Benzimidazole derivatives are pivotal in medicinal chemistry due to their diverse therapeutic applications. Traditional synthesis methods often require catalysts and long reaction times, which can be inefficient and environmentally unfriendly. Hence, there is a growing need for more efficient and eco-friendly synthetic methodologies. A newly devised and efficacious synthetic methodology has been established for the synthesis of benzimidazole derivatives, employing microwave assistance without the requirement for a catalyst. This method facilitated the synthesis of fifteen derivatives with notable efficiency, characterized by significantly reduced reaction times ranging from 5 to 10 minutes and impressive yields ranging from 94% to 98%. The identity and purity of the synthesized benzimidazole derivatives were meticulously verified through a comprehensive analysis, encompassing a comparison of their physicochemical properties and spectral characteristics with authenticated reference data. This method represents a significant advancement in the synthesis of benzimidazole derivatives, offering a rapid and high-yielding alternative to traditional synthetic routes.

Optimization of a DNA extraction protocol for improving bacterial and fungal classification based on Nanopore sequencing.

Ribosomal RNA gene amplicon sequencing is commonly used to evaluate microbiome profiles in health and disease and document the impact of interventional treatments. Nanopore sequencing is attractive since it can provide greater classification at the species level. However, optimized protocols to target marker genes for bacterial and fungal profiling are needed. To achieve an increased taxonomic resolution, we developed extraction and full-length amplicon PCR-based approaches using Nanopore sequencing. Three lysis conditions were applied to a mock microbial community, including known bacterial and fungal species: ZymoBIOMICS lysis buffer (ML) alone, incorporating bead-beating (MLB) or bead-beating plus MetaPolyzyme enzymatic treatment (MLBE). In profiling of bacteria in comparison to reference data, MLB had more statistically different bacterial phyla and genera than the other two conditions. In fungal profiling, MLB had a significant increase of Ascomycota and a decline of Basidiomycota, subsequently failing to detect Malassezia and Cryptococcus. Also, a principal coordinates analysis plot by the Bray-Curtis metric showed a significant difference among groups for bacterial (P=0.033) and fungal (P=0.012) profiles, highlighting the importance of understanding the biases present in pretreatment. Overall, microbial profiling and diversity analysis revealed that ML and MLBE are more similar than MLB for both bacteria and fungi; therefore, using this specific pipeline, bead-beating is not recommended for whole gene amplicon sequencing. However, ML alone was suggested as an optimal approach considering DNA yield, taxonomic classification, reagent cost and hands-on time. This could be an initial proof-of-concept study for simultaneous human bacterial and fungal microbiome studies.

Synthesis, structure, and biological activity of sodium, zinc, and magnesium mono- and bis-1-alkoxy-4-(2′-naphthyl)-1,4-dioxo-2-buten-2-olates

The search for new biologically active compounds is a key area of chemical science. Therefore, the synthesis of compounds with a potentially bactericidal effect seems relevant. In order to extend the range of biologically active substances, the synthesis of sodium 4-(2’-naphthyl)-1,4-dioxo-1-ethoxy-2-buten-2-olate and sodium 1-butoxy-4-(2´-naphthyl)-1,4-dioxo-2-buten-2-olate was carried out by Claisen condensation of equimolar amounts of 2-acetonaphtone and dialkyloxalates in a non-polar medium in the presence of sodium as a condensing agent. Bidentate mononuclear metal chelates were obtained by the metal exchange reaction of sodium oxoenolates with Zn(II) and Mg(II) salts. The structure of the synthesized compounds was confirmed by infrared spectroscopy, (1Н, 13С) nuclear magnetic resonance spectroscopy, and mass spectrometry. The infrared spectra of solid samples of sodium oxoenolates and metal complexes contain bands of stretching vibrations of ester carbonyl groups, skeletal vibrations of aromatic rings, as well as “ether” bands due to vibrations of C–O–C bonds. The 1Н and 13С nuclear magnetic resonance spectra recorded in CDCl3 and Dimethyl sulfoxide-d6 are characterized by a complete set of all expected signals with chemical shift values that are well comparable with the reference data. In the mass spectra of the analyzed compounds, recorded in an acetonitrile solution in the electrospray mode, signals of [M+H]+ and [M+Na]+ protonated and cationized molecules are observed. The bactericidal action of the synthesized preparations was assessed using the agar well diffusion method in combination with the serial dilution method. The biological activity of sodium 4-(2’-naphthyl)-1,4-dioxo-1-ethoxy-2-buten-2-olate against Pseudomonas Aeruginosa and Staphylococcus Aureus, as well as sodium 1-butoxy-4-(2’-naphthyl)-1,4-dioxo-2-buten-2-olate against Pseudomonas Aeruginosa, was revealed. Pronounced resistance of Salmonella spp. to the studied compounds was established.

Design and performance of the Climate Change Initiative Biomass global retrieval algorithm

The increase in Earth observations from space in recent years supports improved quantification of carbon storage by terrestrial vegetation and fosters studies that relate satellite measurements to biomass retrieval algorithms. However, satellite observations are only indirectly related to the carbon stored by vegetation. While ground surveys provide biomass stock measurements to act as reference for training the models, they are sparsely distributed. Here, we addressed this problem by designing an algorithm that harnesses the interplay of satellite observations, modeling frameworks and field measurements, and generated global estimates of above-ground biomass (AGB) density that meet the requirements of the scientific community in terms of accuracy, spatial and temporal resolution. The design was adapted to the amount, type and spatial distribution of satellite data available around the year 2020. The retrieval algorithm estimated AGB annually by merging estimates derived from C- and L-band Synthetic Aperture Radar (SAR) backscatter observations with a Water Cloud type of model and does not rely on AGB reference data at the same spatial scale as the SAR data. This model is integrated with functions relating to forest structural variables that were trained on spaceborne LiDAR observations and sub-national AGB statistics. The yearly estimates of AGB were successively harmonized using a cost function that minimizes spurious fluctuations arising from the moderate-to-weak sensitivity of the SAR backscatter to AGB. The spatial distribution of the AGB estimates was correctly reproduced when the retrieval model was correctly set. Over-predictions occasionally occurred in the low AGB range (<50 Mg ha−1) and under-predictions in the high AGB range (>300 Mg ha−1). These errors were a consequence of sometimes too strong generalizations made within the modeling framework to allow reliable retrieval worldwide at the expense of accuracy. The precision of the estimates was mostly between 30% and 80% relative to the estimated value. While the framework is well founded, it could be improved by incorporating additional satellite observations that capture structural properties of vegetation (e.g., from SAR interferometry, low-frequency SAR, or high-resolution observations), a dense network of regularly monitored high-quality forest biomass reference sites, and spatially more detailed characterization of all model parameters estimates to better reflect regional differences.

ScCrab: A Reference-Guided Cancer Cell Identification Method based on Bayesian Neural Networks.

Cancer is a significant global public health concern, where early detection can greatly enhance curative outcomes. Therefore, the identification of cancer cells holds significant importance as the primary method for cancer diagnosis. The advancement of single-cell RNA sequencing (scRNA-seq) technology has made it possible to address the problem of cancer cell identification at the single-cell level more efficiently with computational methods, as opposed to the time-consuming and less reproducible manual identification methods. However, existing computational methods have shown suboptimal identification performance and a lack of capability to incorporate external reference data as prior information. Here, we propose scCrab, a reference-guided automatic cancer cell identification method, which performs ensemble learning based on a Bayesian neural network (BNN) with multi-head self-attention mechanisms and a linear regression model. Through a series of experiments on various datasets, we systematically validated the superior performance of scCrab in both intra- and inter-dataset predictions. Besides, we demonstrated the robustness of scCrab to dropout rate and sample size, and conducted ablation experiments to investigate the contributions of each component in scCrab. Furthermore, as a dedicated model for cancer cell identification, scCrab effectively captures cancer-related biological significance during the identification process.