Platelet activation and antimicrobial activity of L-PRF: a preliminary study.

Leukocyte and platelet rich fibrin (L-PRF) is one of the platelet concentrates used to support regeneration and healing process. Many studies showed possible immunological and antibacterial properties of L-PRF. We perform an in vitro study to analyze the effect of L-PRF on platelet activation, platelet-leukocytes interactions and antimicrobial activity, important components in the healing process. Molecular biomarkers related with platelet activation and platelet-leukocyte interactions were analyzed by means of flow cytometry when L-PRF exudate was added to whole blood platelets. L-PRF membrane was used to evaluate antimicrobial activity using Enterococcus faecalis (ATCC 29212), Pseudomonas aeruginosa (ATCC 27853) and Candida albicans (ATCC 90028). Our experimental design allows to evaluate platelet activation and analyze molecular biomarkers of other immune cells and platelet-leukocyte interactions. From the results obtained we can conclude that L-PRF can be a valuable tool in healing process, efficient in activating platelets of whole blood and inhibiting microbial growth. In our opinion, the use of L-PRF exudate, in addition to L-PRF membrane, presents some advantages that have to be considered in clinical trials. Additional research on the characterization and quantification of cells and its products present in the L-PRF exudate, as well as on the temporal factor released. Also, further studies using strains isolated from clinical cases are needed.

Tropical tree size-frequency distributions from airborne lidar.

In tropical rainforests, tree size and number density are influenced by disturbance history, soil, topography, climate, and biological factors that are difficult to predict without detailed and widespread forest inventory data. Here, we quantify tree size-frequency distributions over an old-growth wet tropical forest at the La Selva Biological Station in Costa Rica by using an individual tree crown (ITC) algorithm on airborne lidar measurements. The ITC provided tree height, crown area, the number of trees >10 m height and, predicted tree diameter, and aboveground biomass from field allometry. The number density showed strong agreement with field observations at the plot- (97.4%; 3% bias) and tree-height-classes level (97.4%; 3% bias). The lidar trees size spectra of tree diameter and height closely follow the distributions measured on the ground but showed less agreement with crown area observations. The model to convert lidar-derived tree height and crown area to tree diameter produced unbiased (0.8%) estimates of plot-level basal area and with low uncertainty (6%). Predictions on basal area for tree height classes were also unbiased (1.3%) but with larger uncertainties (22%). The biomass estimates had no significant bias at the plot- and tree-height-classes level (-5.2% and 2.1%). Our ITC method provides a powerful tool for tree- to landscape-level tropical forest inventory and biomass estimation by overcoming the limitations of lidar area-based approaches that require local calibration using a large number of inventory plots.

Scaling left ventricular mass in adolescent boys aged 11-15 years.

BACKGROUND: Normalizing left ventricular mass (LVM) for inter-individual variation in body size is a central issue in human biology. During the adolescent growth spurt, variability in body size descriptors needs to be interpreted in combination with biological maturation. AIM: To examine the contribution of biological maturation, stature, sitting height, body mass, fat-free mass (FFM) and fat mass (FM) to inter-individual variability in LVM in boys, using proportional allometric modelling. SUBJECTS AND METHODS: The cross-sectional sample included 110 boys of 11-15 years (12.9-1.0 years). Stature, sitting height, body mass, cardiac chamber dimensions and LVM were measured. Age at peak height velocity (APHV) was predicted and used as an indicator of biological maturation. Percentage fat was estimated from triceps and subscapular skinfolds; FM and FFM were derived. RESULTS: Exponents for body size descriptors were k = 2.33 for stature, k = 2.18 for sitting height, k = 0.68 for body mass, k = 0.17 for FM and k = 0.80 for FFM (adjusted R(2 )= 19-62%). The combination of body descriptors and APHV increased the explained variance in LVM (adjusted R(2)( )= 56-69%). CONCLUSION: Stature, FM and FFM are the best combination for normalizing LVM in adolescent boys; when body composition is not available, an indicator of biological maturity should be included with stature.

Tracking devices and physical performance analysis in team sports: a comprehensive framework for research-trends and future directions.

Background: Tracking devices, such as global (GPS) and local (LPS) positioning systems, combined with physiological measurements, have become reliable tools to characterize movement patterns, assessing the external load (EL), internal load (IL), fatigue, and performance of athletes in team sports. This scoping review aims to provide a comprehensive understanding of the applicability of tracking systems in physical performance analysis within team sports and the wellbeing of athletes based on research strategies and combined variables. Methods: A systematic search was conducted in PubMed, Web of Knowledge, and Scopus databases according to PRISMA guidelines. The 79 studies that were reviewed met the following criteria: (1) contained relevant data regarding elite athletes' performance; (2) athletes' EL and IL; (3) were written in the English language; (4) were related only to team sports. Results: The findings indicate that tracking technology has been engaged in several research areas, including performance analysis, training vs. match load management, injuries, and nutrition, through characterization and correlational studies. Metrics, primarily focused on kinematic and mechanical EL aspects, have been employed in combination with IL data to analyze the performance of athletes. However, the lack of an integrative model for the analysis and integration of EL and IL metrics within each team sport suggests an interesting direction for further research. Conclusion: There is a need for coherence between the methods and the research goals on performance analysis. The development of a framework that guides experimental studies is highly recommended, particularly on manipulating metrics analyzed between training and match sessions, injury prevention, and nutrition. This will lead to the development of the most applied sports science research to improve the preparation and decision-making of athletes based on reliable data. Systematic Review Registration: https://inplasy.com/?s=2022120039, identifier 2022120039.

Interpreting match performance in elite futsal: considerations for normalizing variables using effective time.

Introduction: This study aimed to investigate the physical and individual technical-tactical performance of elite futsal players. Methods: Thirteen National Team futsal players (27.4 ± 4.7 years, 70.3 ± 7.6 kg, 176.3 ± 5.5 cm) competed in 15 official matches in three distinct competitions. Session rate of perceived exertion (sRPE) and player load (PL) were measured for assessing physical internal and external load, respectively. Individual tactical actions were analyzed using Instat Scout®, considering variables such as fouls, shots, shots on target, goals, successful dribbles, passes, successful passes, ball losses, ball recoveries, and challenges won. Results: The cluster analysis classified the players into two groups: "high-involvement" (HIGH) and "low-involvement" (LOW), based on their average effective playing time, sRPE, and PL. A linear mixed model was used to examine the differences in external and internal load and technical-tactical variables between the two groups, accounting for individual repeated measures. Considering absolute values, HIGH players presented higher sRPE, RPE, total PL, shots, goals, passes, successful passes, ball losses and recoveries, and challenges won (p = 0.001-0.039; ES = 0.43-2.48), when compared to their LOW counterparts. However, when analyzed relative to effective time, LOW players reached higher total PL and shots per minute (p = 0.001-0.012; ES = 0.39-0.93) when compared to HIGH players. Non-significant differences were found for the rest of the variables. Discussion: In summary, these results emphasize the importance of normalizing internal and external load variables and technical-tactical performance variables per effective playing time in futsal. The current findings indicate that players with lower involvement can present the same or even higher physical and technical-tactical performance compared to teammates with more playing time.

Levetiracetam-induced drug reaction with eosinophilia and systemic symptoms syndrome.

OBJECTIVE: To describe a case of levetiracetam-induced drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome. CASE SUMMARY: A 31-year-old white male with a low-grade astrocytoma presenting with tonic-clonic seizures was treated with levetiracetam 1 g twice daily and dexamethasone (initial dosage 12 mg/day, tapered down to 2 mg/day). On day 45 after levetiracetam initiation, dexamethasone was discontinued and levetiracetam continued. The patient developed fever and dyspnea on day 46 and was admitted to the hospital on day 49. A chest X-ray showed bilateral pulmonary interstitial infiltrates, and laboratory tests showed elevated lactate dehydrogenase (LDH; 288 U/L [reference range <204]), ferritin (223 ng/mL [13-178]), and C-reactive protein (CRP; 3.1 mg/dL [<0.5]). Neurologic fever was suspected and the reinitiation of dexamethasone at 6 mg/day was followed by improvement of all symptoms; the patient was discharged on day 55 with dexamethasone 4 mg/day for 2 more days. On day 59, 2 days after the withdrawal of dexamethasone for the second time, the patient presented with a pruritic erythematous maculopapular rash along with recurrence of fever and dyspnea, and was admitted to the hospital. A chest X-ray showed reappearance of the bilateral pulmonary interstitial infiltrates, and laboratory tests showed impaired liver function (alanine aminotransferase 60 U/L [reference range <56], aspartate aminotransferase 53 U/L [<30], LDH 516 U/L, ferritin 419 ng/mL, and CRP 2.6). A diagnosis of DRESS syndrome was suspected and levetiracetam was discontinued. Upon levetiracetam withdrawal, the patient's symptoms resolved by day 66, and radiological images showed resolution of the interstitial infiltrate by day 68. The patient was discharged on day 68. Low-grade fever persisted until day 71, with no other symptoms. During a 2-month follow-up period, liver function test results returned to normal. DISCUSSION: DRESS is a hypersensitivity reaction to several drugs, mainly antiepileptic drugs (AEDs), characterized by cutaneous, hematologic, and visceral involvement. Levetiracetam is structurally and pharmacologically unrelated to other AEDs. Previously, only one case of levetiracetam-induced DRESS syndrome had been reported, which required corticosteroids to control symptoms. We describe a case of levetiracetam-induced DRESS syndrome presenting with pneumonitis and hepatitis that resolved with levetiracetam withdrawal. Our patient was classified as a definitive DRESS case according to the RegiSCAR scoring system, which grades DRESS cases. According to the Naranjo probability scale, the adverse drug reaction was considered probable. CONCLUSIONS: Although levetiracetam is usually well tolerated, clinicians should be aware of the potential for it to cause DRESS syndrome.

Body composition and grip strength constraints in elite male rink-hockey players of contrasting ethnicity.

Rink hockey is a highly specialized and physiological demanding sport with sparse research regarding the game and athletes' characteristics. A cross-sectional study was developed to characterize the body composition and grip strength of elite male rink hockey players and to establish the relationship between ethnicity on body composition and grip strength. A sample of 100 elite rink-hockey athletes aged 26.59 ± 6.02 participated in the study, comprised of 69 Caucasian male adults aged 27.58 ± 6.44 years and 31 Black African male adults aged 24.39 ± 4.27. Body composition was assessed by anthropometric measurements. Static grip strength was assessed with an adjustable dynamometer. Multiple regression analysis was applied to understand which variables constraints body fat percentage (BF) and grip strength. Body mass showed an average of 76.36 ± 9.18 kg for 175.80 ± 5.87 cm of height and BF% of 10.82 ± 5.07%. Maximal right grip strength was 50.91 ± 6.26 kg and 50.27 ± 6.23 kg for left grip strength. Four predictors accounted for 70.01% of the variance of BF%: abdominal circumference (p < 0.001), right thigh circumference (p < 0.001), right calf circumference (p = 0.001) and ethnicity (p = 0.016). Three predictors accounted for 13.1% of the variance of right grip strength: ethnicity (p = 0.013), chronological age (p = 0.024) and right distal thigh circumference (p = 0.014). Results suggest that elite rink hockey athletes have a specific anthropometric identity, which at the elite level may lead to reduced body fat and greater handgrip strength. Ethnicity seems to predict body fat and grip strength in elite rink hockey athletes.

Classification of impacted blueberries during storage using an electronic nose.

BACKGROUND: An electronic nose (EN) was used to determine the effect of repeated impacts on changes in volatile characteristics of fresh blueberries during storage. Hand-harvested 'Misty' blueberries (Vaccinium corymbosum) were treated either as (1) undropped (control) fruits, (2) fruits poured six times from a picking bucket 200 mm into a plastic field lug or (3) fruits dropped as above ten times onto a steel surface. Fruits from all treatments were stored in vented polystyrene clamshell containers at 2 °C and 95% relative humidity. RESULTS: Repeated impacts caused no skin rupture or leakage after treatment or during storage. EN data were subjected to discriminant function analysis to classify samples by treatment at days 0, 2, 10, 17 and 24 (n=5 per treatment). Correct classification rates (CCRs) for days 0, 2, 10, 17 and 24 were 0, 100, 100, 100 and 100% respectively. On day 0 there was no significant difference in sample volatiles, and CCRs for all treatments and storage times ranged from 80 to 100%. Cross-validation rates for different treatments and storage times ranged from 75 to 100%. CONCLUSION: The EN could be a useful tool to estimate the effect of impacts incurred during blueberry handling on quality based on changes in volatile characteristics.

A Review of Players' Characterization and Game Performance on Male Rink-Hockey.

The aim of this study was to review the evolutionary tendencies of research regarding to the study of male Rink-Hockey players´ and game performance. A systematic search was conducted in PubMed, Web of Knowledge and Scopus databases according to PRISMA method. The initial search identified 815 titles, resulting in 19 articles being included within the review. Original papers (English language) contained relevant data regarding rink hockey players' performance or morphological/physiological demands, anthropometry/body composition characteristics were eligible. Studies were classified into categories: (1) Physiological Demands, (2) Anthropometry and Body Composition, (3) Game Characterization/Patterns, (4) Injuries. Results indicated that Rink hockey requires high intensity effort which demands both short and long duration efforts requirements from players. Body composition analysis shows to be an important monitoring tool which complements the understanding of the athlete's cardiac adaptation. Game patterns shows a combination of specific game momentums with different outcomes according to the game zone. The intense short-term movements, collision and contact between players, in addition to the weight and speed of the hard ball and the stick, can considerably increase the risk of moderate and severe injuries. Lack of literature in Rink-Hockey is remarkable, and research is mainly focused on children and adolescents' players. Furthermore, the existing research with adult elite athletes was assessed with a small sample size.

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests.

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high-resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED-2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED-2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

Forest degradation and biomass loss along the Chocó region of Colombia.

BACKGROUND: Wet tropical forests of Chocó, along the Pacific Coast of Colombia, are known for their high plant diversity and endemic species. With increasing pressure of degradation and deforestation, these forests have been prioritized for conservation and carbon offset through Reducing Emissions from Deforestation and forest Degradation (REDD+) mechanisms. We provide the first regional assessment of forest structure and aboveground biomass using measurements from a combination of ground tree inventories and airborne Light Detection and Ranging (Lidar). More than 80,000 ha of lidar samples were collected based on a stratified random sampling to provide a regionally unbiased quantification of forest structure of Chocó across gradients of vegetation structure, disturbance and elevation. We developed a model to convert measurements of vertical structure of forests into aboveground biomass (AGB) for terra firme, wetlands, and mangrove forests. We used the Random Forest machine learning model and a formal uncertainty analysis to map forest height and AGB at 1-ha spatial resolution for the entire pacific coastal region using spaceborne data, extending from the coast to higher elevation of Andean forests. RESULTS: Upland Chocó forests have a mean canopy height of 21.8 m and AGB of 233.0 Mg/ha, while wetland forests are characterized by a lower height and AGB (13.5 m and 117.5 Mg/a). Mangroves have a lower mean height than upland forests (16.5 m), but have a similar AGB as upland forests (229.9 Mg/ha) due to their high wood density. Within the terra firme forest class, intact forests have the highest AGB (244.3 ± 34.8 Mg/ha) followed by degraded and secondary forests with 212.57 ± 62.40 Mg/ha of biomass. Forest degradation varies in biomass loss from small-scale selective logging and firewood harvesting to large-scale tree removals for gold mining, settlements, and illegal logging. Our findings suggest that the forest degradation has already caused the loss of more than 115 million tons of dry biomass, or 58 million tons of carbon. CONCLUSIONS: Our assessment of carbon stocks and forest degradation can be used as a reference for reporting on the state of the Chocó forests to REDD+ projects and to encourage restoration efforts through conservation and climate mitigation policies.

Diversity, distribution and dynamics of large trees across an old-growth lowland tropical rain forest landscape.

Large trees, here defined as ≥60 cm trunk diameter, are the most massive organisms in tropical rain forest, and are important in forest structure, dynamics and carbon cycling. The status of large trees in tropical forest is unclear, with both increasing and decreasing trends reported. We sampled across an old-growth tropical rain forest landscape at the La Selva Biological Station in Costa Rica to study the distribution and performance of large trees and their contribution to forest structure and dynamics. We censused all large trees in 238 0.50 ha plots, and also identified and measured all stems ≥10 cm diameter in 18 0.50 ha plots annually for 20 years (1997-2017). We assessed abundance, species diversity, and crown conditions of large trees in relation to soil type and topography, measured the contribution of large trees to stand structure, productivity, and dynamics, and analyzed the decadal population trends of large trees. Large trees accounted for 2.5% of stems and ~25% of mean basal area and Estimated Above-Ground Biomass, and produced ~10% of the estimated wood production. Crown exposure increased with stem diameter but predictability was low. Large tree density was about twice as high on more-fertile flat sites compared to less fertile sites on slopes and plateaus. Density of large trees increased 27% over the study interval, but the increase was restricted to the flat more-fertile sites. Mortality and recruitment differed between large trees and smaller stems, and strongly suggested that large tree density was affected by past climatic disturbances such as large El Niño events. Our results generally do not support the hypothesis of increasing biomass and turnover rates in tropical forest. We suggest that additional landscape-scale studies of large trees are needed to determine the generality of disturbance legacies in tropical forest study sites.

Observational study of post-operative pain control before and after the implementation of a clinical practice guideline for postoperative pain management. / Estudio observacional del control del dolor postoperatorio antes y después de la implementación de una guía del manejo del dolor postoperatorio.

BACKGROUND AND OBJECTIVES: Postoperative pain is common in hospitals. Clinical practice guidelines for the control of postoperative pain (CPGPP) have been developed to improve its treatment. The objective of this study was to evaluate the prevalence and intensity of postoperative pain and analgesic norms, before and after the implementation of a CPGPP. MATERIAL AND METHOD: An observational study was carried out that included 2cross-sectional studies in 2separate periods, before and after implementation of the CPGPP. Adult patients postoperated on the first day of admission in the surgery plants were included. Demographic, clinical and pharmacological variables were collected from clinical histories. The intensity of the pain was collected through individual interviews with patients. RESULTS: We included 306 patients in the first period and 317 in the second. There were no differences between patients' demographic and clinical variables and the 2periods. The prevalence of pain was 92% (IC 95%: 87%-95%) in the first period and 77% (IC 95%: 72%-82%) in the second (P <0.05). The most frequent pain in the last 24hours was moderate or intense in 53% (IC 95%: 48%-59%) of patients in the first period and in 33% (IC 95%: 28%-38%) of the patients in the second (P <0.05). CONCLUSIONS: After the implementation of the CPGPP, a decrease in the prevalence and intensity of pain in patients was observed, but without reaching an optimal level. Continued pain training and assessment measures are therefore necessary for proper pain treatment over time.

Mental health and quality of life outcomes in family members of patients with chronic critical illness admitted to the intensive care units of two Brazilian hospitals serving the extremes of the socioeconomic spectrum.

Chronic critical illness (CCI) is a relevant clinical, social and financial health issue. The aim of this study was to compare the mental outcomes (symptoms of anxiety and depression) and quality of life outcomes of the family members of patients with CCI from different socioeconomic backgrounds who were admitted to one of the intensive care units (ICUs) in two Brazilian hospitals, one private and one public. It is a prospective study involving a public hospital that serves a low-income population and a tertiary private hospital that serves a high-income population. Family members of patients with CCI answered the Hospital Anxiety and Depression Scale (HADS) and The World Health Organization Quality of Life-WHOQOL-bref questionnaires. They responded to the European Quality of life Five Dimension three Level (EuroQol-5D-3L) and the Activities of Daily Living (ADL) questionnaires on behalf of the patients at three time points: during the ICU stay, 30 and 90 days after the patient was discharged. We used logistic regression models to evaluate the main predictors of a binary outcome regarding symptoms of anxiety and depression. We enrolled 186 patients with CCI. Many patients from public hospitals who were independent became dependent for their ADLs at 90 days (41.7% versus 14.3%, p = 0.03). At 30 days, family members from public hospital had worse impact on all domains of WHOQOL-bref compared with families from private hospital. At 90-days, the difference persists in the physical domain, worse for families from public hospital (p = 0.006). The symptoms of depression at 30-days (p = 0.008) and at 90-days (p = 0.013) were worse in the public hospital. CCIs affected quality of life and the emotional condition of family members, especially in families with fewer resources when the patients became more dependent. Family members with higher education were more likely to experience depression, while depression was associated with cohabiting with the patient in low-income families.

Correction: Mental health and quality of life outcomes in family members of patients with chronic critical illness admitted to the intensive care units of two Brazilian hospitals serving the extremes of the socioeconomic spectrum.

[This corrects the article DOI: 10.1371/journal.pone.0221218.].

Temporal dynamics and metabolic correlation between lactate-producing and hydrogen-producing bacteria in sugarcane vinasse dark fermentation: The key role of lactate.

This study aimed to better understand the role of different microbial groups and the determining fermentation pathways in a biohydrogen (bioH2)-producing reactor fed with sugarcane vinasse by using next-generation sequencing and principal component analysis (PCA). Both microbial structure and dynamics were characterized. The highest bioH2 production levels were associated with the Thermoanaerobacterium genus, whilst lactate-producing bacteria comprised the dominant genera (e.g. Lactobacillus and Leuconostoc) within the reactor at both stable and unstable bioH2-producing periods. PCA further revealed that the fermentation of lactate played a dual role in the reactor, as both bioH2-producing (acetate+lactate→butyrate+bioH2) and non-bioH2-producing (lactate→propionate+acetate) routes could be observed. Overall, the results suggested that lactate is the primary alternative carbon source in vinasse-fed systems subjected to carbohydrate-shortage conditions.

454-Pyrosequencing analysis of highly adapted azo dye-degrading microbial communities in a two-stage anaerobic-aerobic bioreactor treating textile effluent.

Azo dyes, which are widely used in the textile industry, exhibit significant toxic characteristics for the environment and the human population. Sequential anaerobic-aerobic reactor systems are efficient for the degradation of dyes and the mineralization of intermediate compounds; however, little is known about the composition of the microbial communities responsible for dye degradation in these systems. 454-Pyrosequencing of the 16S rRNA gene was employed to assess the bacterial biodiversity and composition of a two-stage (anaerobic-aerobic) pilot-scale reactor that treats effluent from a denim factory. The anaerobic reactor was inoculated with anaerobic sludge from a domestic sewage treatment plant. Due to the selective composition of the textile wastewater, after 210 days of operation, the anaerobic reactor was dominated by the single genus Clostridium, affiliated with the Firmicutes phylum. The aerobic biofilter harbored a diverse bacterial community. The most abundant phylum in the aerobic biofilter was Proteobacteria, which was primarily represented by the Gamma, Delta and Epsilon classes followed by Firmicutes and other phyla. Several bacterial genera were identified that most likely played an essential role in azo dye degradation in the investigated system.

Impact of data model and point density on aboveground forest biomass estimation from airborne LiDAR.

BACKGROUND: Accurate estimation of aboveground forest biomass (AGB) and its dynamics is of paramount importance in understanding the role of forest in the carbon cycle and the effective implementation of climate change mitigation policies. LiDAR is currently the most accurate technology for AGB estimation. LiDAR metrics can be derived from the 3D point cloud (echo-based) or from the canopy height model (CHM). Different sensors and survey configurations can affect the metrics derived from the LiDAR data. We evaluate the ability of the metrics derived from the echo-based and CHM data models to estimate AGB in three different biomes, as well as the impact of point density on the metrics derived from them. RESULTS: Our results show that differences among metrics derived at different point densities were significantly different from zero, with a larger impact on CHM-based than echo-based metrics, particularly when the point density was reduced to 1 point m-2. Both data models-echo-based and CHM-performed similarly well in estimating AGB at the three study sites. For the temperate forest in the Sierra Nevada Mountains, California, USA, R2 ranged from 0.79 to 0.8 and RMSE (relRMSE) from 69.69 (35.59%) to 70.71 (36.12%) Mg ha-1 for the echo-based model and from 0.76 to 0.78 and 73.84 (37.72%) to 128.20 (65.49%) Mg ha-1 for the CHM-based model. For the moist tropical forest on Barro Colorado Island, Panama, the models gave R2 ranging between 0.70 and 0.71 and RMSE between 30.08 (12.36%) and 30.32 (12.46) Mg ha-1 [between 0.69-0.70 and 30.42 (12.50%) and 61.30 (25.19%) Mg ha-1] for the echo-based [CHM-based] models. Finally, for the Atlantic forest in the Sierra do Mar, Brazil, R2 was between 0.58-0.69 and RMSE between 37.73 (8.67%) and 39.77 (9.14%) Mg ha-1 for the echo-based model, whereas for the CHM R2 was between 0.37-0.45 and RMSE between 45.43 (10.44%) and 67.23 (15.45%) Mg ha-1. CONCLUSIONS: Metrics derived from the CHM show a higher dependence on point density than metrics derived from the echo-based data model. Despite the median of the differences between metrics derived at different point densities differing significantly from zero, the mean change was close to zero and smaller than the standard deviation except for very low point densities (1 point m-2). The application of calibrated models to estimate AGB on metrics derived from thinned datasets resulted in less than 5% error when metrics were derived from the echo-based model. For CHM-based metrics, the same level of error was obtained for point densities higher than 5 points m-2. The fact that reducing point density does not introduce significant errors in AGB estimates is important for biomass monitoring and for an effective implementation of climate change mitigation policies such as REDD + due to its implications for the costs of data acquisition. Both data models showed similar capability to estimate AGB when point density was greater than or equal to 5 point m-2.

Spatial Distribution of Carbon Stored in Forests of the Democratic Republic of Congo.

National forest inventories in tropical regions are sparse and have large uncertainty in capturing the physiographical variations of forest carbon across landscapes. Here, we produce for the first time the spatial patterns of carbon stored in forests of Democratic Republic of Congo (DRC) by using airborne LiDAR inventory of more than 432,000 ha of forests based on a designed probability sampling methodology. The LiDAR mean top canopy height measurements were trained to develop an unbiased carbon estimator by using 92 1-ha ground plots distributed across key forest types in DRC. LiDAR samples provided estimates of mean and uncertainty of aboveground carbon density at provincial scales and were combined with optical and radar satellite imagery in a machine learning algorithm to map forest height and carbon density over the entire country. By using the forest definition of DRC, we found a total of 23.3 ± 1.6 GtC carbon with a mean carbon density of 140 ± 9 MgC ha-1 in the aboveground and belowground live trees. The probability based LiDAR samples capture variations of structure and carbon across edaphic and climate conditions, and provide an alternative approach to national ground inventory for efficient and precise assessment of forest carbon resources for emission reduction (ER) programs.

Traffic fatality indicators in Brazil: State diagnosis based on data envelopment analysis research.

The intense economic growth experienced by Brazil in recent decades and its consequent explosive motorization process have evidenced an undesirable impact: the increasing and unbroken trend in traffic fatality numbers. In order to contribute to road safety diagnosis on a national level, this study presents a research into two main indicators available in Brazil: mortality rate (represented by fatalities per capita) and fatality rate (represented by two sub-indicators, i.e., fatalities per vehicle and fatalities per vehicle kilometer traveled). These indicators were aggregated into a composite indicator or index through a multiple layer data envelopment analysis (DEA) composite indicator model, which looks for the optimum combination of indicators' weights for each decision-making unit, in this case 27 Brazilian states. The index score represents the road safety performance, based on which a ranking of states can be made. Since such a model has never been applied for road safety evaluation in Brazil, its parameters were calibrated based on the experience of more consolidated European Union research in ranking its member countries using DEA techniques. Secondly, cluster analysis was conducted aiming to provide more realistic performance comparisons and, finally, the sensitivity of the results was measured through a bootstrapping method application. It can be concluded that by combining fatality indicators, defining clusters and applying bootstrapping procedures a trustworthy ranking can be created, which is valuable for nationwide road safety planning.