A Regularised Total Least Squares Approach for 1D Inverse Scattering

We study the inverse scattering problem for a Schrödinger operator related to a static wave operator with variable velocity, using the GLM (Gelfand–Levitan–Marchenko) integral equation. We assume to have noisy scattering data, and we derive a stability estimate for the error of the solution of the GLM integral equation by showing the invertibility of the GLM operator between suitable function spaces. To regularise the problem, we formulate a variational total least squares problem, and we show that, under certain regularity assumptions, the optimisation problem admits minimisers. Finally, we compute numerically the regularised solution of the GLM equation using the total least squares method in a discrete sense.

The determinants of environmental performance and its effect on the financial performance of European-listed companies

This study seeks to identify the factors that can simultaneously improve the environmental and financial performance of a company and determine if an improvement in the environmental performance of a company is accompanied by an improvement in its financial performance. We estimate a system of structural equations using the partial least squares approach applied to data on 351 large European-registered companies extracted from the ASSET4-Environmental, Social, and Governance database for the 2007–2015 period. The results show that the engagement of a company in environmental protection is significantly affected by the system of governance of the company and the availability of financial resources at the 1 and 5% levels, respectively. The results also show that engaging in environmental protection increases the accounting and stock exchange performance of companies. These results thus suggest that the protection of the ecosystem by companies leads to a paradigm, which can form the basis of a model of responsible governance whose goal is to create value while respecting environmental factors.

Factors Affecting Pandemic Biosecurity Behaviors of International Travelers: Moderating Roles of Gender, Age, and Travel Frequency

Research undertaken during the COVID-19 pandemic has identified a number of significant factors that affect international travelers’ biosecurity behavior. Tourists’ age and gender as well as travel frequency have been found to have significant impacts on consumers’ non-pharmaceutical intervention practices. However, despite the importance of age, gender, and travel frequency, such studies have overlooked international tourists’ values, attitudes, interventions, and behaviors relevant to biosecurity during a pandemic. In order to bridge this gap, the purposes of this study are to build and test a conceptually comprehensive framework on the relationships between values, attitudes, interventions, and behaviors, along with the moderating effects of age, gender, and travel frequency. To meet the study objectives, a digital survey was administered during 1–5 September 2020, which generated n = 386 total useable responses. Data were analyzed using the partial least squares approach. The results revealed that tourists’ values have the greatest effect on their attitudes toward COVID-19 biosecurity for travel, which in turn positively influences interventions and behaviors. Interventions also have a significant impact on travelers’ COVID-19 biosecurity behavior. This study expands the theoretical understanding of biosecurity and pandemic behavior. The findings of this research also provide significant insights to the literature as well as stakeholders, such as governments, health organizations, international health and tourism agencies, and destinations, with respect to managing international travel biosecurity measures.

Proposed Method for Statistical Analysis of On-Farm Single Strip Treatment Trials

On-farm experimentation (OFE) allows farmers to improve crop management over time. The randomized complete blocks design (RCBD) with field-length strips as individual plots is commonly used, but it requires advanced planning and has limited statistical power when only three to four replications are implemented. Harvester-mounted yield monitor systems generate high resolution data (1-s intervals), allowing for development of more meaningful, easily implementable OFE designs. Here we explored statistical frameworks to quantify the effect of a single treatment strip using georeferenced yield monitor data and yield stability-based management zones. Nitrogen-rich single treatment strips per field were implemented in 2018 and 2019 on three fields each on two farms in central New York. Least squares and generalized least squares approaches were evaluated for estimating treatment effects (assuming independence) versus spatial covariance for estimating standard errors. The analysis showed that estimates of treatment effects using the generalized least squares approach are unstable due to over-emphasis on certain data points, while assuming independence leads to underestimation of standard errors. We concluded that the least squares approach should be used to estimate treatment effects, while spatial covariance should be assumed when estimating standard errors for evaluation of zone-based treatment effects using the single-strip spatial evaluation approach.

The halal label Morocco and the commitment of the Moroccan consumer on the national market

The objective of this paper is to study the influence of the cognitive perception of the Moroccan halal label LHM on the commitment of the Moroccan consumer towards the products labeled by the LHM. For this purpose, a questionnaire survey was conducted with a sample of 84 Moroccan consumers. A structural equation analysis using the Partial Least Squares approach by SmartPLS was performed. The results achieved indicate, on the one hand, that knowledge and trust have no influence on consumer commitment to the products labeled by the LHM. On the other hand, the consumer's sustained involvement has a positive influence on his commitment to the products labeled by the LHM.