How community forest management performs when REDD+ payments fail

The Reduced Emissions in Deforestation and Degradation (REDD+) initiative uses payments for ecosystem services as incentives for developing countries to manage and protect their forests. REDD+ initiatives also prioritize social (and environmental) co-benefits aimed at improving the livelihoods of communities that are dependent on forests. Despite the incorporation of co-benefits into REDD+ goals, carbon sequestration remains the primary metric for which countries can receive payments from REDD+, but after more than ten years of REDD+, many site-specific programs have failed to complete the carbon verification process. Here, we examine whether the REDD+ social co-benefits alone are sufficient to have slowed deforestation in the absence of carbon payments on Pemba, Tanzania. Using satellite imagery (Landsat archive), we quantified forest cover change for the period before (2001-2010) and after (2010-2018) the launch in 2010-11 of Pemba island’s REDD+ Readiness project. We then compared rates of forest cover change between shehia (administrative units) that were part of REDD+ Readiness intervention and those that were not, adjusting for confounding variables and the non-random selection of REDD+ shehia with a statistical matching procedure. Despite considerable variation in forest outcomes among shehia, the associated co-benefits with the Pemba REDD+ project had no discernible effect on forest cover change. Likewise, we did not detect an effect of socioecological covariates on forest cover change across all shehia, though island-wide human population growth since 2012 may have played a role. These findings are unsurprising given the failure to secure carbon payments on Pemba and indicate that co-benefits alone are insufficient to reduce deforestation. We conclude that better oversight of all-involved parties is needed to ensure that REDD+ interventions satisfactorily conclude the process of securing a mechanism for carbon payments, if slowing deforestation is to be achieved.

Testing the Green Bond Premium in COVID-19 Pandemia

The purpose of this chapter is testing the existence of the green bond premium in the secondary market by using a most update data set involving the market developments in the pandemia times. The variables such as rating, sector, amount of the issue, maturity, and external review are balanced by using a matching procedure of a green bond with conventional bond issued by the same issuer. The ask-bid spread differential is regressed by using a panel regression method under fixed and random effects. The results of the analysis revealed that there exists negative premium of 39 basis points, and the green bond premium is more profound for USD denominated twins than for Euro ones as there exist a negative premium of 59 basis points for USD-denominated green bonds whereas it is -26 basis points for Euro-denominated bonds.

Hough Transform for Distinctive Edge Detection to Images in Fingerprint Recognition Matching Transformation

Biometric Identification is a globally renowned procedure, which has been utilised to achieve a successful and accurate level of identification. In the sea of biometrics, fingerprints are deemed more popular when it comes to verification. This results from the presence of the ridges on the fingerprints that are completely exclusive to each individual. Besides that, fingerprints are expansively employed to ascertain and authenticate people individually. Therefore, this study had proposed to employ distinctive Edge Detection techniques together with the Hough Transform to match the images of the fingerprints in a fingerprint matching system. The Hough Transform is a superior procedure carried out to get an accurate series of finer points or lines. The finer points or lines would then distinguish the fingerprints. Nevertheless, it was still a challenge to extract finer points or lines from the fingerprints under uninhibited conditions. Therefore, this paper was organised based on four distinctive steps. First, different Edge Detection operators were employed to perform the fingerprint matching algorithm. Next, the fingerprint matching algorithm was applied twice to the same Edge Detection operators. Thirdly, the Edge Detection operators had been substituted with the Transformation Method for the same matching procedure. For example, the proposed fingerprint matching algorithm comprised of the Hough Transform and same Edge Detection operators. Finally, distinct Edge Detection operators based on the decision making algorithm were used to calculate and determine the percentage of matching. Therefore, this study proved that the prints obtained via the Prewitt Edge Detection together with Hough Transform were in an agreement.

Phosphorous Determination in Biochar-Based Fertilizers by Spark Discharge-Laser-Induced Breakdown Spectroscopy

Biochar-based fertilizers are a new attractive alternative to P supplementation for crops, as they can gradually release the nutrient, avoiding losses and improving soil quality. In this regard, the evaluation of the P amount in biochar-based fertilizers is extremely important for their quality control. Analytical techniques that require sample solubilization are not very efficient for this task, as biochar is difficult to solubilize. Laser-induced breakdown spectroscopy (LIBS) is a promising technique to respond to this demand, as it enables a direct analysis of solid samples, avoiding the complicated process of sample solubilization. In this work, a novel method based on spark discharge (SD) coupled to LIBS was evaluated for P determination in biochar-based fertilizers prepared from three different biomasses. To overcome calibration problems in LIBS analysis, a matrix-matching procedure accomplished by the addition of eucalyptus biochar to calibration standards was used in experiments. This procedure minimized matrix effects and allowed us to achieve a satisfactory accuracy even when applied to similar but different matrices. Furthermore, the developed method is simple, fast, direct, does not generate post-analysis residues and appears appropriate for the quality control of sustainable biochar-based fertilizers and other biochar products.

Short- and medium-term cost effects of non-indicated thyroid diagnostics: empirical evidence from German claims data

This paper contributes to the discussion of whether non-indicated ultrasound examinations of the thyroid gland contribute to overtreatment and excess health care expenditures. Using two sources of claims data from Germany, we analyzed data from patients who underwent a TSH blood test which is the initial diagnostic measure to check for possible presence of thyroid dysfunction. In a matching analysis, we compared health costs of two groups of patients. One consisted of patients who underwent an early thyroid ultrasound that according to medical guidelines—at this point—was probably not indicated. The other group consisted of patients, who underwent no ultrasound examination at all or later in the course of the disease, making probable a correct indication. Both groups were made comparable by the means of a matching procedure. Average thyroid-specific health costs were substantially higher for the first group in the quarter in which the ultrasound examination took place. Some deviation in these specific costs persisted over a substantial period of time, with drug expenditures exhibiting the biggest difference. If, however, total health costs were considered, difference in costs was only found in the initial quarter. We conclude that non-indicated ultrasound examination of the thyroid gland may have some moderate effects on thyroid-specific costs. Yet the data do not suggest that long-lasting overtreatment and excess health expenditures are initiated by non-indicated ultrasound in Germany.

Oversampling and replacement strategies in propensity score matching: a critical review focused on small sample size in clinical settings

Background Propensity score matching is a statistical method that is often used to make inferences on the treatment effects in observational studies. In recent years, there has been widespread use of the technique in the cardiothoracic surgery literature to evaluate to potential benefits of new surgical therapies or procedures. However, the small sample size and the strong dependence of the treatment assignment on the baseline covariates that often characterize these studies make such an evaluation challenging from a statistical point of view. In such settings, the use of propensity score matching in combination with oversampling and replacement may provide a solution to these issues by increasing the initial sample size of the study and thus improving the statistical power that is needed to detect the effect of interest. In this study, we review the use of propensity score matching in combination with oversampling and replacement in small sample size settings. Methods We performed a series of Monte Carlo simulations to evaluate how the sample size, the proportion of treated, and the assignment mechanism affect the performances of the proposed approaches. We assessed the performances with overall balance, relative bias, root mean squared error and nominal coverage. Moreover, we illustrate the methods using a real case study from the cardiac surgery literature. Results Matching without replacement produced estimates with lower bias and better nominal coverage than matching with replacement when 1:1 matching was considered. In contrast to that, matching with replacement showed better balance, relative bias, and root mean squared error than matching without replacement for increasing levels of oversampling. The best nominal coverage was obtained by using the estimator that accounts for uncertainty in the matching procedure on sets of units obtained after matching with replacement. Conclusions The use of replacement provides the most reliable treatment effect estimates and that no more than 1 or 2 units from the control group should be matched to each treated observation. Moreover, the variance estimator that accounts for the uncertainty in the matching procedure should be used to estimate the treatment effect.

Scattering amplitudes for binary systems beyond GR

Amplitude methods have proven to be a promising technique to perform Post-Minkowskian calculations used as inputs to construct gravitational waveforms. In this paper, we show how these methods can be extended beyond the standard calculations in General Relativity with a minimal coupling to matter. As proof of principle, we consider spinless particles conformally coupled to a gravitational helicity-0 mode. We clarify the subtleties in the matching procedure that lead to the potential for conformally coupled matter. We show that in the probe particle limit, we can reproduce well known results for the field profile. With the scattering amplitudes at hand, we compute the conservative potential and scattering angle for the binary system. We find that the result is a non trivial expansion that involves not only the coupling strengths, but also a non trivial dependence on the energy/momentum of the scattered particles.

How Character-Centric Game Icon Design Affects the Perception of Gameplay

Mobile games are developing rapidly as an important part of the national economy. Gameplay is an important attribute, and a game’s icon sometimes determines the user’s initial impression. Whether the user can accurately perceive gameplay and affective quality through the icon is particularly critical. In this article, a two-stage perceptual matching procedure is used to evaluate the perceptual quality of six categories of games whose icons include characters as elements. First, 60 highly visual matching icons were selected as second-stage objects through classification tasks. Second, through the semantic differential method and correlation analysis, highly visual matching icons’ affective matching quality was measured. Finally, a series of icon samples were determined, and element analysis was carried out. Several methods were proposed for improving the perceptual quality of game icons. Studying the perceptual matching relationship can better enhance the interaction between designers, developers, and users.

Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy

With a dataset of testing and case counts from over 1,400 institutions of higher education (IHEs) in the United States, we analyze the number of infections and deaths from SARS-CoV-2 in the counties surrounding these IHEs during the Fall 2020 semester (August to December, 2020). We used a matching procedure designed to create groups of counties that are aligned along age, race, income, population, and urban/rural categories---socio-demographic variables that have been shown to be correlated with COVID-19 outcomes. We find that counties with IHEs that remained primarily online experienced fewer cases and deaths during the Fall 2020 semester; whereas before and after the semester, these two groups had almost identical COVID-19 incidence. Additionally, we see fewer deaths in counties with IHEs that reported conducting any on-campus testing compared to those that reported none. We complement the statistical analysis with a case study of IHEs in Massachusetts---a rich data state in our dataset---which further highlights the importance of IHE-affiliated testing for the broader community. The results in this work suggest that campus testing can itself be thought of as a mitigation policy and that allocating additional resources to IHEs to support efforts to regularly test students and staff would be beneficial to mitigating the spread of COVID-19 in the general population.