Intensive Sampling Research Articles

Location-scale modeling as an integrative approach to symptom dynamics during psychotherapy: An illustration with depressive symptoms.

Depressive symptom dynamics, including change trajectories and symptom variability, have been related to therapy outcomes. However, such dynamics have often been examined separately and related to outcomes of interest using two-step analyses, which are characterized by several limitations. Here, we show how to overcome these limitations using location-scale models in a dynamic structural equation modeling framework. We introduce location-scale modeling in an accessible manner to pave the way for its use in research integrating within-person dynamics and intervention-related change in psychopathology, and we illustrate this modeling approach in a large-scale internet-based intervention for depression (N = 1,656). Using eight data points sampled across about 8 weeks, we predicted improvement across the intervention (50% symptom reduction) as a function of early change and symptom variability. Early symptom change was associated with a more likely improvement across therapy. Variability of symptoms beyond change trajectories during the intervention was associated with less likely improvement. Location-scale models, and dynamic structural equation modeling more generally, are well suited to modeling how patterns of symptom change during psychotherapy are related to important (e.g., therapy) outcomes. Our illustrative application of location-scale modeling showed that symptom variability was associated with less overall improvement in depressive symptoms. However, this finding requires replication with more intensive sampling of symptoms before final conclusions can be drawn on when and how to distinguish maladaptive from adaptive variability during psychotherapy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Population pharmacokinetics of ravidasvir in adults with chronic hepatitis C virus infection and impact of antiretroviral treatment.

Ravidasvir (RDV) is a novel NS5A inhibitor that exhibits potent pan-genotypic inhibition of hepatitis C virus (HCV) replication. Sofosbuvir (SOF) plus RDV was demonstrated to be efficacious and safe in adults with active HCV infection, including those living with HIV (LWHIV), in the STORM-C-1 trial. We assessed the population pharmacokinetics (PK) of RDV in a sub-study nested within STORM-C-1 conducted in Thailand and Malaysia. SOF (400 mg) plus RDV (200 mg) was administered orally once daily for 12 weeks to adults with chronic HCV infection, but without cirrhosis and for 24 weeks to those with compensated cirrhosis. Intensive and sparse PK samples were collected at 4, 8, and 12 weeks after treatment initiation. Population PK parameters of RDV and the impact of covariates were evaluated using nonlinear mixed-effects modeling. Five hundred ninety-four participants were included, 235 (40%) had compensated cirrhosis, and 189 (32%) were LWHIV. RDV plasma concentrations were best described by a two-compartment model with first-order elimination. Oral clearance (CL/F) and volume of distribution (Vd/F) parameters were allometrically scaled on fat-free mass. Concomitant antiretroviral treatment (ART) increased RDV CL/F by 30%-60%, with efavirenz-based ART having the largest impact. Females had 16% lower RDV CL/F than males, and higher albumin levels reduced RDV central volume of distribution. While several covariates impact RDV CL/F and Vd/F, the effect on RDV exposures was not clinically relevant based on the efficacy data reported in this diverse Asian adult population. There were no meaningful drug-drug interactions in adults LWHIV on ART.

Constrained Iterative Adaptive Algorithm for the Detection and Localization of RFI Sources Based on the SMAP L-Band Microwave Radiometer

The Soil Moisture Active Passive (SMAP) satellite carries an L-band microwave radiometer. This sensor can be used to observe global soil moisture (SM) and sea surface salinity (SSS) within the protected L-band spectrum (1400–1427 MHz). Owing to the complex effects of radio frequency interference (RFI), the SM and SSS data are missing or have low accuracy. In this paper, a constrained iterative adaptive algorithm for the detection, identification, and localization of RFI sources is designed, named MICA-BEID. The algorithm synthesizes antenna temperatures for the third and fourth Stokes parameters before RFI filtering, creating a new polarization parameter called WSPDA, designed to approximate the level of RFI interference on the L-band microwave radiometer. The algorithm then utilizes the WSPDA intensity and distribution density of RFI detection samples to enhance the identification and classification of RFI sources across various intensity levels. By utilizing statistical methods such as the probability density function (PDF) and the cumulative distribution function (CDF), the algorithm dynamically adjusts adaptive parameters, including the RFI detection threshold and the maximum effective radius of RFI sources. Through the application of multiple iterative clustering methods, the algorithm can adaptively detect and identify RFI sources at various satellite orbits and intensity levels. Through extensive comparative analysis with other localization results and known RFI sources, the MICA-BEID algorithm can achieve optimal localization accuracy of approximately 1.2 km. The localization of RFI sources provides important guidance for identifying and turning off illegal RFI sources. Moreover, the localization and long-time-series characteristic analysis of RFI sources that cannot be turned off is of significant value for simulating the spatial distribution characteristics of localized RFI source intensity in local areas.

Model-Informed Clinical Development of Once-Every-6-Month Injection of Paliperidone Palmitate in Patients with Schizophrenia: A Pharmacometric Bridging Approach (Part I).

A model-informed drug development (MIDD) approach was implemented for paliperidone palmitate (PP) 6-month (PP6M) clinical development, using pharmacokinetics and pharmacokinetic/pharmacodynamic model-based simulations. PP6M pharmacokinetics were simulated by extending the PP 3-month (PP3M) pharmacokinetic model to account for increased injection volume, and hence dose. Contribution of the MIDD approach to the design of the pivotal PP6M phase-3 study (PP6M/PP3M noninferiority study, NCT03345342) investigating schizophrenia relapse rates was twofold: (1) PP6M dose selection, and (2) hypothesis generation that lower trough concentrations (Ctrough) associated with PP6M, relative to PP3M, were not associated with lower efficacy, which was to be evaluated in the phase-3 study. Moreover, accompanied by an intense sampling scheme to adequately characterize paliperidone pharmacokinetics and to elucidate the potential relationship between concentration and safety/efficacy, the bridging strategy eliminated the need for additional phase-1/phase-2 clinical studies. Using a MIDD bridging strategy, PP6M doses were selected that, compared with PP3M, were expected to have a similar range of exposures and a noninferior relapse rate and safety profile. Clinical data from PP6M/PP3M noninferiority study confirmed that PP6M, compared with PP3M, had a similar range of exposures (T'jollyn etal. in Eur J Drug Metab Pharmacokinet 2024), as well as a noninferior relapse rate and safety profile (this manuscript). Consistency of the MIDD approach with observed clinical outcomes confirmed the hypothesis that lower Ctrough did not lead to increased relapse rates at the doses administered. Although higher paliperidone peak concentrations are achieved with corresponding doses of PP6M relative to PP3M in the phase-3 clinical study, types and incidences of treatment-related adverse events were comparable between PP6M and PP3M groups and no new safety concerns emerged for PP6M (Najarian etal. in Int J Neuropsychopharmacol 25(3):238-251, 2022).

Estimation of adaptability parameters of grain sorghum variety range in the conditions of Donbass

The purpose of the current study was to conduct an environmental testing and give a comprehensive estimation of the adaptability parameters of modern grain sorghum varieties developed by the FSBSI “ARC “Donskoy”. Weather conditions during the years of study were different, which made it possible to estimate varieties under contrasting cultivation conditions. The year’s conditions index was the highest in 2019 and 2023 (+0.76 and +1.03), and the lowest (-1.21) in the acutely arid year of 2020. The main effect on the productivity formation of the grain sorghum varieties was made by the conditions of the year (49.8 %) and the minor effect was made by the genotype of the variety (31.0 %). The varieties ‘Ataman’, ‘Zernogradskoe 88’, ‘Luchistoe’, ‘Zernogradskoe 53’ were found to be more productive (> 4.6 t/ha) and have a higher adaptability coefficient (108.8–117.2 %). Intensive samples (bi > 1) were ‘Zernogradskoe 53’, ‘Ataman’, ‘Luchistoe’, ‘Zernogradskoe 88’. Extensive varieties (bi < 1) were ‘Orlovskoe’, ‘Velikan’ and ‘Krymbel’ (st.). The varieties ‘Luchistoe’, ‘Ataman’,’ Zernogradskoe 88’ (S2d = 0.02–0.04) had high stability indicators, and the varieties ‘Ataman’, ‘Luchistoe’, ‘Zernogradskoe 88’, ‘Zernogradskoe 53’ had high overall adaptive capacity (TAC). The maximum indicators (115–131 %) of the stability level were established in the varieties ‘Ataman’, ‘Luchistoe’, ‘Zernogradskoe 88’. The rating estimation of adaptability parameters has shown that the early ripening intensive varieties ‘Ataman’ (68 points), ‘Luchistoe’ (67 points) and ‘Zernogradskoye 88’ (61 points) are the best and the most suitable ones for cultivation in the Donbass.

Pharmacokinetics of standard versus high-dose rifampin for tuberculosis preventive treatment: A sub-study of the 2R2 randomized controlled trial

BackgroundPharmacokinetic data of rifampin, when used for tuberculosis preventive treatment (TPT) are not available. We aimed to describe the pharmacokinetics of rifampin used for TPT, at standard and higher doses, and to assess predictors of rifampin exposure. MethodsA pharmacokinetic sub-study was performed in Bandung, Indonesia among participants in the 2R2 randomized trial, which compared TPT regimens of 2 months of high-dose rifampin at 20 mg/kg/day (2R20) and 30 mg/kg/day (2R30), with 4 months of standard-dose rifampin at 10 mg/kg/day (4R10) in adolescents and adults. Intensive pharmacokinetic sampling was performed after 2–8 weeks of treatment. Pharmacokinetic parameters were assessed non-compartmentally. Total exposure (AUC0-24) and peak concentration (Cmax) between arms were compared using one-way ANOVA and Tukey's post-hoc tests. Multivariable linear regression analyses were used to assess predictors of AUC0-24 and Cmax. ResultsWe enrolled 51 participants in this study. In the 4R10, 2R20, and 2R30 arms, the geometric mean AUC0-24 was 68.0, 186.8, and 289.9 h⋅mg/L, and Cmax was 18.4, 36.7, and 54.4 mg/L, respectively; high interindividual variabilities were observed. Compared with the 4R10 arm, AUC0-24 and Cmax were significantly higher in the 2R20 and 2R30 arms (P < 0.001). Drug doses, body weight, and female sex were predictors of higher rifampin AUC0-24 and Cmax (P < 0.05). AUC0-24 and Cmax values were much higher than those previously reported in persons with TB disease. ConclusionsDoubling and tripling the rifampin dose led to three- and four-fold higher exposure compared to standard dose. Pharmacokinetic/pharmacodynamic modelling and simulations are warranted to support trials of shortening the duration of TPT regimens with high-dose rifampin.

Comparative review of novel model-assisted designs for phase I/II clinical trials.

In recent years, both model-based and model-assisted designs have emerged to efficiently determine the optimal biological dose (OBD) in phase I/II trials for immunotherapy and targeted cellular agents. Model-based designs necessitate repeated model fitting and computationally intensive posterior sampling for each dose-assignment decision, limiting their practical application in real trials. On the other hand, model-assisted designs employ simple statistical models and facilitate the precalculation of a decision table for use throughout the trial, eliminating the need for repeated model fitting. Due to their simplicity and transparency, model-assisted designs are often preferred in phase I/II trials. In this paper, we systematically evaluate and compare the operating characteristics of several recent model-assisted phase I/II designs, including TEPI, PRINTE, Joint i3+3, BOIN-ET, STEIN, uTPI, and BOIN12, in addition to the well-known model-based EffTox design, using comprehensive numerical simulations. To ensure an unbiased comparison, we generated 10,000 dosing scenarios using a random scenario generation algorithm for each predetermined OBD location. We thoroughly assess various performance metrics, such as the selection percentages, average patient allocation to OBD, and overdose percentages across the eight designs. Based on these assessments, we offer design recommendations tailored to different objectives, sample sizes, and starting doselocations.

Mapping surface sediment characteristics in enclosed shallow‐marine environments using spatially balanced designs and the random forest algorithm

AbstractMapping the sedimentary character of the seafloor in large water‐filled basins is fundamental for understanding landform dynamics to inform research, management, intervention and conservation actions. Seabed mapping methods have undergone considerable development in the last two decades, including the uptake of machine learning approaches for sediment size prediction and classification. However, predictions of surficial sediment characteristics are often hindered by the availability of ground truthing data, their arrangement in space and the modelling approach chosen. Spatially informed sampling designs provide an opportunity to significantly improve the accuracy and uncertainty of predicted sediment distributions. In this study, we apply a machine learning algorithm to predict sediment distributions across Port Phillip Bay, a large (1930 km2) structurally controlled estuary on the southeast coast of Victoria, Australia. Surface sediment samples (n = 252) were collected using a spatially balanced design, ensuring that sampling effort was spread evenly within the embayment with increased sampling intensity placed in more heterogeneous areas. Surficial textural metrics were modelled using the random forest algorithm with bathymetric and hydrodynamic predictor variables. Models highlighted trends in sediment grain size, sorting and composition consistent with predicted wave‐ and current‐induced sediment mobilisation. Model predictions were accurate (normalised‐root mean squared error [NRMSE]: 0.14–0.16); however, standard error was not homogeneous across the study area. Uncertainty maps highlighted areas where additional sampling effort may be needed, including areas where transitional bathymetry impacted surficial sediment character and areas of anthropogenic modifications to the seabed. This study shows the benefits of undertaking spatially informed sample design, block cross‐validation during model fitting and quantifying spatial uncertainty in predictive maps to accurately quantify the fundamental boundary conditions of sediment size. The results of this study are intended to inform local coastal management, including beach renourishment activities. However, approaches outlined are applicable to any study where the seafloor grain size is a fundamental variable in understanding landscape change.

Effect of ZnO on Luminescence Performance of Terbium-Activated Zinc Borosilicate Glasses.

In this study, terbium-doped ZnO-SiO2-B2O3-Na2O glasses were fabricated with the conventional melt-quenching method. The effect of altering the concentration of the host matrix on luminescence performance was investigated in terms of different ZnO/B2O3 and ZnO/SiO2 ratios. FT-IR results indicate that bridging oxygens (Bos) were converted to non-bridging oxygens (NBOs) with increments of ZnO. Furthermore, the emission intensity and luminescence lifetime of samples were influenced by the amount of ZnO; this was proven with photoluminescence spectra results. The maximum emission intensity was observed at a 1.1 ZnO/B2O3 ratio and a 0.8 ZnO/SiO2 ratio; however, the highest luminescence lifetime was observed at a 1.1 ZnO/SiO2 ratio. The emission intensity and luminescence lifetime of glass samples were improved by heat treatment as a result of the formation of willemite and zinc oxide phases. An increase in the ZnO/SiO2 ratio facilitated the formation of willemite and zinc oxide phases; therefore, crystallinity was directly related to the luminescence behavior of glass samples.

The low diversity of vegetation seedling and sapling threatening the tree existence at the university green space of Universitas Sumatera Utara, Indonesia

University of Sumatera Utara (USU) located in the densely populated urban area and committed to maintain the vegetations of green space which are fundamental to the key indicator in green campus ranking. Green open spaces are a vital element in urban areas providing the comfortable-healthy spaces for urban communities and numerous of environmental services. Specifically, the quality of environmental services depends on the extensive of green spaces, climate characteristic, and existing vegetation as the natural element at the area. Vegetation analysis is the method to study the composition, structure, and form of plant communities that is a prerequisite for describing diverse ecological processes and dynamics of species community in a forest. This study aims to analyze the important value, diversity, evenness, and richness index of USU green space vegetation based on the growth levels from seedlings to trees. The sampling plot was quantified using 2% sampling intensity and positioned with a simple random method. Species name, individual and species number, diameter at breast height (DBH), and stand height were recorded in the designated plots and subplots for each life stage. This research documented 21 species belonging to 12 families at USU green space. Swietenia mahagoni was the dominant species at all growth level with the IVI of 141.07 % (trees), 144.21 % (poles), 133.33 % (saplings), and 135.37 % (seedlings). The species diversity of trees and poles was moderate (H’= 1.6 – 1.7), whereas of saplings and seedlings was low (H’= 0.6 – 0.7). Vegetation evenness at all growth levels was high (E= 0.6 – 1.0). The species richness of trees was identified as moderate (R= 3.5) and of seedlings, saplings, and poles was low (R= 0.2 – 2.5). The seedlings and saplings were inadequate indicating the poor regeneration threatening the tree existence at USU green space.

The potential biomass, carbon stock and CO2 sequestration of forest litters at Sibolangit nature park

Several factors generated CO2 releasing into the atmosphere in large quantities and persist. The CO2 concentration is continuously increase (exceeding 400 ppm in 2019) leading to more negative impact of global warming and climate change. Biomass is a key parameter in estimating and predicting ecosystem productivity, carbon storage, nutrient sharing, and fuel accumulation in assessing an ecosystem. This study aims to analyze the biomass, carbon stock and carbon sequestration of forest litters at Sibolangit nature park. The research data was recorded at Sibolangit Tourism Park, located in Sibolangit, Deli Serdang, North Sumatera. 0.5 m x 0.5 m plot was placed based on the simple random sampling method to collect the litters. The 5% sampling intensity was applied resulting in total of 30 sampling plots. All litter in the sample plots was collected and weighed to determine the wet weight. 100 grams of sample was then placed in a sample plastic and labelled. The litter biomass was calculated using the formula according to SNI7724-2011. This research calculated the biomass, carbon stock, and carbon sequestration of litter at Sibolangit nature park, i.e., 86.92 ton ha−1, 40.85 ton ha−1, and 149.94 ton ha−1. The results support the role of Sibolangit nature park in climate change mitigation by reduction of carbon emission.

Structural, Optical, and Magnetic Properties of Mn Doped Zn3P2 Diluted Magnetic Semiconductor Nanoparticles

Mn-doped Zn3P2-diluted magnetic semiconducting nanoparticles (Zn0.98Mn0.02P2, Zn0.96Mn0.04P2, Zn0.94Mn0.06P2, and Zn0.92Mn0.08P2) were synthesized by a conventional solid-state reaction followed by a subsequent vacuum annealing process. The formation of a tetragonal structure of pure and Mn-doped Zn3P2 was confirmed by X-ray diffraction studies, with no evidence of any further phases. Lattice parameters dicrease from a = b = 8.133 Å, c = 11.459 Å to a = b = 8.041 Å, c = 11.410 Å with increasing dopant concentration. Scanning electron microscpy analysis indicated that all samples that underwent doping exhibited agglomeration in the scanned range of 500 nm. Energy-dispersive X-ray analysis confirmed the presence of Zn, P, and Mn in the samples, and all of the synthesized samples achieved a nearly atomic ratio. In the diffused reflectance spectra, the optical band gap increases from 1.398 to 1.418 eV with increasing dopant concentration. PL has provided evidence indicating that the emission intensity of all doped samples remains constant with increasing dopant content from x = 0.02 to 0.08, with different excitation wavelengths (215 and 290 nm). Vibrating sample magnetometer tests confirmed the presence of ferromagnetic behavior at room temperature, and a positive correlation between saturation magnetization and Mn content, with the magnetic moment increasing from 0.0640 to 0.1181 emu g−1 with an increase in dopant content.

Износостойкость теплостойких сталей ВКС-7 и ВКС-10 после ионно-плазменного азотирования, вакуумной цементации и вакуумной нитроцементации

Tribotechnical characteristics of martensitic grade steels HSM-7 (16Cr2Ni3MoVNbNAl) and HSM-10 (13Cr3Ni3Mo2VNbNAl) were analyzed. Steels underwent ion plasma nitriding, low-pressure carburizing and low-pressure carbonitriding. The concept of a two-stage hardening technology has been implemented: the creation of a thermally stable finely dispersed state of steel at the first stage and the use of such a state for accelerated and qualitative saturation of the surface layer with nitrogen or carbon at the second stage. To create an ultra-finely divided state in the samples of steels under investigation, the method of intensive plastic deformation (IPD) was used. The method is based on the grinding of the microstructure due to large shear deformations. IPD was performed by the method of warm precipitation in a die with a degree of deformation of 80 % at a temperature of 700 ℃. The wear resistance tests of the samples were carried out on a special stand with reciprocating motion in the medium of a plastic lubricant material of mating samples having flat friction surfaces at a pressure of 10 MPa and an average velocity of 0,19 m/s. It is shown that HSM-7 and HSM-10 steels after ion-plasma nitriding and vacuum cementation have high wear resistance (wear intensity I  10-10). After low-pressure carbonitriding, the values of the wear intensity of the friction pair samples are almost the same and amount to 0,3·10-10, which is ~3,0 times less than after low-pressure carburizing. As a result of ion-plasma nitriding and low-pressure carbonitriding, a nanostructured surface layer is formed on steel surfaces contributing to wear resistance increase. The ideas concerning nitrided steel score resistance increase are given.

Detection of Virulence Genes in Pseudomonas aeruginosa Isolates by Polymerase Chain Reaction and Investigation of High-Risk Clones by Matrix Assisted Laser Desorption/ Ionization Time-of-Flight Mass Spectrometer Method

Pseudomonas aeruginosa is a non-fermentative gram-negative bacillus. Many virulence factors play a role in the pathogenesis of P.aeruginosa. The aim of this study was to early detection of ST111, ST175, ST235, ST253, ST395 which are named high-risk clones with increased epidemic potential due to multidrug resistance in P.aeruginosa isolates by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) method and to evaluate the relationship between high-risk clones and the presence of P.aeruginosa virulence factors and carbapenemase production genes.P.aeruginosa isolates (n= 100) found to be resistant to at least imipenem or meropenem antibiotics isolated from the various clinical samples in the medical microbiology laboratory between 01.01.2021 and 07.06.2022 were included in the study. For the detection of virulence genes uniplex polymerase chain reaction (PCR) for toxA and multiplex PCR for algD, plcN, lasB, plcH were performed in P.aeruginosa isolates. In the detection of carbapenemase genes, two separate multiplex PCRs used for blaKPC , blaNDM , blaVIM , blaOXA-48 and for blaIMP , blaSPM , blaSIM , blaGIM , blaGES . Investigation of the peaks specific to high-risk clones was performed by using VITEK®-MS (bioMérieux, France) system. P.aeruginosa isolates were mostly isolated from intensive care units (45%) and respiratory tract samples (46%). The antibiotic to which the isolates were found to be most susceptible was amikacin, while highest resistance was detected for piperacillin. In PCR results, toxA, lasB, plcH, plcN and algD were detected as 89%, 99%, 98%, 100%, 100%, respectively. When the presence of characteristic peaks belonging to high-risk clones was evaluated with MALDI-TOF MS, ST253 (7%) and ST175 (2%) were detected. The peaks specific to ST235 and ST395 clones were not detected in our study. blaVIM was detected in two isolates and blaGES-5 carbapenemase was detected in two isolates. Virulence factors were detected at high rates in both high-risk clones and other strains and no significant relationship was found between high-risk clones and virulence factors. Early detection of high-risk clones, identification of antimicrobial resistance mechanisms will help to develop strategic treatment options and prevent their worldwide spread.

Assessment of the Conformation Stability and Glycosylation Heterogeneity of Lactoferrin by Native Mass Spectrometry.

Lactoferrin (LTF) has diverse biological activities and is widely used in functional foods and active additives. Nevertheless, evaluating the proteoform heterogeneity, conformational stability, and activity of LTF remains challenging during its production and storage processes. In this study, we describe the implementation of native mass spectrometry (nMS), glycoproteomics, and an antimicrobial activity assay to assess the quality of LTF. We systematically characterize the purity, glycosylation heterogeneity, conformation, and thermal stability of LTF samples from different sources and transient high-temperature treatments by using nMS and glycoproteomics. Meanwhile, the nMS peak intensity and antimicrobial activity of LTF samples after heat treatment decreased significantly, and the two values were positively correlated. The nMS results provide essential molecular insights into the conformational stability and glycosylation heterogeneity of different LTF samples. Our results underscore the great potential of nMS for LTF quality control and activity evaluation in industrial production.

Assessing water diversion impacts on the fish community size structure in headwater stream stretches

Water diversion for hydropower plants is one of the leading causes of habitat alteration and biotic homogenization. The impacts of small hydropower plants on fish communities are usually assessed using taxonomic composition and structure indicators. Size-based indicators are useful tools to evaluate the effects of environmental factors and anthropogenic perturbations on riverine ecosystems. In this study, we investigated the impact of water diversion on fish community body size structure in 16 small hydropower plants in the upper Ter River basin (NE Iberian Peninsula). We tested the use of multiple size-based metrics under different sampling intensities (one- vs. four-pass electrofishing) and compared control vs. diverted stream stretches. Results revealed that water diversion had a negative effect on fish community average and median length, while size spectrum and size diversity metrics showed no responses to the impact. Altitude was positively related with body size metrics and was the strongest natural driver affecting them. Moreover, we found that all the size-based metrics exhibited consistent values under different sampling efforts. Our findings suggest that size-based metrics could be useful indicators for bioassessment of river flow alteration and that one-pass electrofishing was robust enough to characterize the stream fish community size structure in our study.

Adaptive Ghost Imaging Based on 2D-Haar Wavelets

To improve the imaging speed of ghost imaging and ensure the accuracy of the images, an adaptive ghost imaging scheme based on 2D-Haar wavelets has been proposed. This scheme is capable of significantly retaining image information even under under-sampling conditions. By comparing the differences in light intensity distribution and sampling characteristics between Hadamard and 2D-Haar wavelet illumination patterns, we discovered that the lateral and longitudinal information detected by the high-frequency 2D-Haar wavelet measurement basis could be used to predictively adjust the diagonal measurement basis, thereby reducing the number of measurements required. Simulation and experimental results indicate that this scheme can still achieve high-quality imaging results with about a 25% reduction in the number of measurements. This approach provides a new perspective for enhancing the efficiency of computational ghost imaging.

Ghost roads and the destruction of Asia-Pacific tropical forests.

Roads are expanding at the fastest pace in human history. This is the case especially in biodiversity-rich tropical nations, where roads can result in forest loss and fragmentation, wildfires, illicit land invasions and negative societal effects1-5. Many roads are being constructed illegally or informally and do not appear on any existing road map6-10; the toll of such 'ghost roads' on ecosystems is poorly understood. Here we use around 7,000 h of effort by trained volunteers to map ghost roads across the tropical Asia-Pacific region, sampling 1.42 million plots, each 1 km2 in area. Our intensive sampling revealed a total of 1.37 million km of roads in our plots-from 3.0 to 6.6 times more roads than were found in leading datasets of roads globally. Across our study area, road building almost always preceded local forest loss, and road density was by far the strongest correlate11 of deforestation out of 38 potential biophysical and socioeconomic covariates. The relationship between road density and forest loss was nonlinear, with deforestation peaking soon after roads penetrate a landscape and then declining as roads multiply and remaining accessible forests largely disappear. Notably, after controlling for lower road density inside protected areas, we found that protected areas had only modest additional effects on preventing forest loss, implying that their most vital conservation function is limiting roads and road-related environmental disruption. Collectively, our findings suggest that burgeoning, poorly studied ghost roads are among the gravest of all direct threats to tropical forests.

Developing simple indicators of nitrogen and phosphorus removal in constructed stormwater wetlands

Quantifying pollutant removal by stormwater wetlands requires intensive sampling which is cost-prohibitive for authorities responsible for a large number of wetlands. Wetland managers require simple indicators that provide a practical means of estimating performance and prioritising maintenance works across their asset base. We therefore aimed to develop vegetation cover and metrics derived from monitoring water level, as simple indicators of likely nutrient pollutant removal from stormwater wetlands. Over a two-year period, we measured vegetation cover and water levels at 17 wetlands and used both to predict nitrogen (N) and phosphorus (P) removal. Vegetation cover explained 48 % of variation in total nitrogen (TN) removal; with a linear relationship suggesting an approximate 9 % loss in TN removal per 10 % decrease in vegetation cover. Vegetation cover is therefore a useful indicator of TN removal. Further development of remotely-sensed data on vegetation configuration, species and condition will likely improve the accuracy of TN removal estimates. Total phosphorus (TP) removal was not predicted by vegetation cover, but was weakly related to the median water level which explained 25 % of variation TP removal. Despite weak prediction of TP removal, metrics derived from water level sensors identified faults such as excessive inflow and inefficient outflow, which in combination explained 50 % of the variation in the median water level. Monitoring water levels therefore has the potential to detect faults prior to loss of vegetation cover and therefore TN removal, as well as inform the corrective action required.

A multitaxa approach to biodiversity inventory in Matela protected area (Terceira, Azores, Portugal).

This manuscript is the first contribution of the project, "Matela - uma ilha de biodiversidade" ("Matela - an island of biodiversity"), that aims to restore the native vegetation within the Azorean Protected Area of the Terceira Island Nature Park known as the "Protected Area for the Management of Habitats or Species of Matela" (TER08), situated on Terceira Island, the Azores Archipelago, Portugal. This small fragment of native forest, positioned at a low-medium altitude (300-400 m a.s.l.), is facing some conservation impacts as a consequence of the spread of different invasive exotic plant species, mainly Pittosporumundulatum, Rubusulmifolius and Hedychiumgardnerianum. The database we present encompasses diverse taxonomic groups, including bryophytes, vascular plants, arthropods, birds and mammals. It is derived from intensive sampling campaigns conducted in 2022, but some data from a previous vascular plant survey in 2015 were also included. The objective of this study was to provide an updated inventory of bryophytes, vascular plants, arthropods, birds and mammals within this protected area. In this way we are providing the reference conditions necessary for the monitoring of the impacts of the current ongoing restoration efforts within the project "Matela - an island of biodiversity". Whenever feasible, the present inventory is juxtaposed with historical data from previous surveys conducted in Matela. In the realm of bryophytes, our analysis revealed the presence of 75 taxa, comprising 44 mosses and 32 liverworts. Amongst these, 71 were indigenous, while three remained indeterminate and one, Campylopusintroflexus, was identified as invasive. A comparison with previous historical data revealed a decrease in species richness, which was partially counterbalanced by the discovery of 23 new recorded species in the area.Regarding vascular plants, we distinguished 54 species, comprising 28 indigenous and 26 introduced taxa. Almost 80% of the inventoried species (n = 43) were newly documented in Matela.The study of arthropods encompassed a total of 103 taxa. Within the realm of soil arthropods, we documented eight indigenous and 25 introduced taxa, witnessing the disappearance of endemic species alongside a substantial increase in introduced ones between 2002 and 2022. Canopy arthropods, totalling 36 indigenous and 18 introduced taxa, exhibited few changes when compared with data from 2002. SLAM traps captured 24 indigenous and 15 introduced arthropod taxa and no historical data are available for comparison.As for avian species, we noted 12 indigenous birds and one introduced species, confirming the presence of most of the historical recorded native species.The mammalian census revealed eight introduced species, setting new precedents for Matela, alongside the identification of one endemic species: the Azorean endemic bat Nyctalusazoreum.