Controlling for Sustainability Strategies: Findings from Research and Directions for the Future

Over the past decade the focus of sustainability researchers has broadened to explore management controls for sustainable business practice. This paper contributes to the emerging area of interest on understanding the roles management controls play by presenting a review of the literature that specifically focuses on the relationship between management controls and sustainability strategies. The paper shows that the current literature predominantly focuses on exploring controls from a management control design perspective, mostly informed through the case study based approach while concentrating primarily on large firms. Nine key themes arising out of the review of the literature are presented. The limitations of current research are subsequently addressed and avenues for further research are presented and discussed

Tobacco abuse and its health effect

Tobacco smoking is still one of the most important risk factor for Respiratory and cardiovascular diseases and an estimated 90% of causes of lung cancer are attributable to Tobacco smocking and equally 90% of peripheral vascular disease in non-diabetic population is attributable to Tobacco smoking, despite the health effect there is disturbing figures of people who take up smoking habit daily and increase level of failed quit smoking attempts.Environment and genetics still plays major role, and various forms of tobacco is used worldwide and its health consequence has been highlighted. Monitoring tobacco use and prevention policies through effective tax laws is paramount to reduction of the tobacco health effects in our environments.Keywords: Tobacco abuse, cigarrete smoking, health effec

Einfluss von Phytophthora infestans auf den Kartoffelertrag in Abhängigkeit von der Nährstoffversorgung und optimierten Kupferapplikationen

Late blight, caused by Phytophthora infestans is commonly thought to be the factor most limiting yield in organic potato production. However, because there is no fully effective fungicide available to control late blight, there are virtually no yield loss data available for organic farming conditions. In large-scale experiments covering 2-6 ha from 2000-2002, late blight assessments were conducted throughout the season in small sections throughout the field. The same sections were harvested, resulting in between 400 and 700 data points per experiment and year. In a second set of experiments, from 2002-2004, the interactive effects of N-availability in the soil, climatic conditions and late blight were studied in the presence and absence of copper fungicides for the mid-early main-crop potato variety Nicola. Again, late blight and yield assessments were conducted within defined sections in the field resulting in about 100 data points per experiment. In 2005 and 2006, new copper products with minimal copper contents (157g Cu/ha and applica-tion) and optimised applications using the model Bio-PhytoPRE were integrated. Depending on year and variety, between 0 and 40% of the variation in yield could be explained through late blight severity. Copper fungicides in most cases did slow down epidemics somewhat adding an average of 3 days to the growth duration. However, only 26% of the variation in yield could be attributed to disease reductions. A multi-variate model including disease reduction, growth duration and temperature sum, and soil mineral N contents for the years 2002-2004 (FINCKH et al., 2006) could explain 61% of the observed variation in yield. However, the model failed when N-supply was extremely high. In 2005-2006, without the forecasting model, copper had no significant effect on dis-ease in plots with low nutrient availability while minimised applications combined with the forecasting model resulted in more reliable disease reductions even under low nutrient conditions. A reduction of the current maximally allowed Copper inputs from 3 kg to 1.5 kg per ha and year should thus be considered. Overall yield gains through copper applications were only 10% on average. The economic usefulness of copper applications needs to be scrutinised before recommending its use. The implications of the results on the management of organic potatoes will be discussed

Semi-Supervised End-to-End Learning for Integrated Sensing and Communications

Integrated sensing and communications (ISAC) is envisioned as one of the key enablers of next-generation wireless systems, offering improved hardware, spectral, and energy efficiencies. In this paper, we consider an ISAC transceiver with an impaired uniform linear array that performs single-target detection and position estimation, and multiple-input single-output communications. A differentiable model-based learning approach is considered, which optimizes both the transmitter and the sensing receiver in an end-to-end manner. An unsupervised loss function that enables impairment compensation without the need for labeled data is proposed. Semi-supervised learning strategies are also proposed, which use a combination of small amounts of labeled data and unlabeled data. Our results show that semi-supervised learning can achieve similar performance to supervised learning with 98.8% less required labeled data.Comment: 7 pages, 5 figures. Accepted to ICMLCN 202

Model-Driven End-to-End Learning for Integrated Sensing and Communication

Integrated sensing and communication (ISAC) is envisioned to be one of the pillars of 6G. However, 6G is also expected to be severely affected by hardware impairments. Under such impairments, standard model-based approaches might fail if they do not capture the underlying reality. To this end, data-driven methods are an alternative to deal with cases where imperfections cannot be easily modeled. In this paper, we propose a model-driven learning architecture for joint single- target multi-input multi-output (MIMO) sensing and multi-input single-output (MISO) communication. We compare it with a standard neural network approach under complexity constraints. Results show that under hardware impairments, both learning methods yield better results than the model-based standard baseline. If complexity constraints are further introduced, model- driven learning outperforms the neural-network-based approach. Model-driven learning also shows better generalization performance for new unseen testing scenario

Simple method for sub-diffraction resolution imaging of cellular structures on standard confocal microscopes by three-photon absorption of quantum dots

This study describes a simple technique that improves a recently developed 3D sub-diffraction imaging method based on three-photon absorption of commercially available quantum dots. The method combines imaging of biological samples via tri-exciton generation in quantum dots with deconvolution and spectral multiplexing, resulting in a novel approach for multi-color imaging of even thick biological samples at a 1.4 to 1.9-fold better spatial resolution. This approach is realized on a conventional confocal microscope equipped with standard continuous-wave lasers. We demonstrate the potential of multi-color tri-exciton imaging of quantum dots combined with deconvolution on viral vesicles in lentivirally transduced cells as well as intermediate filaments in three-dimensional clusters of mouse-derived neural stem cells (neurospheres) and dense microtubuli arrays in myotubes formed by stacks of differentiated C2C12 myoblasts

Biochar and Its Potential Application for the Improvement of the Anaerobic Digestion Process: A Critical Review

Poor management of organic waste is a key environmental and public health issue as it contributes to environmental contamination and the spread of diseases. Anaerobic digestion (AD) presents an efficient method for organic waste management while generating energy and nutrient-rich digestate. However, the AD process is limited by key factors, which include process inefficiencies from substrate-induced instability, poor quality digestate, and poor management of effluent and emissions. Lately, there has been more interest in the use of biochar for improving anaerobic digestion. Biochar can improve methane production by speeding up the methanogenesis stage, protecting microorganisms from toxic shocks, and reducing inhibition from ammonia and volatile fatty acids. It can be applied for in situ cleanup of biogas to remove carbon dioxide. Applying biochar in AD is undergoing intensive research and development; however, there are still unresolved factors and challenges, such as the influence of feedstock source and pyrolysis on the performance of biochar when it is added to the AD process. In light of these considerations, this review sheds more light on various potential uses of biochar to complement or improve the AD process. This review also considers the mechanisms through which biochar enhances methane production rate, biochar’s influence on the resulting digestate, and areas for future research

Cardiovascular risk and stroke mortality in persons living with HIV: a longitudinal study in a hospital in Yaounde

Introduction: HIV infection is a well-known risk factor for stroke, especially in young adults. In Cameroon, there is a death of data on the outcome of stroke among persons living with HIV (PLWH). This study aimed to assess the cardiovascular risk profile and mortality in PLWH who had a stroke. Methods: this was a retrospective cohort study of all PLWH aged ≥18 years admitted for stroke between January 2010 and December 2019 to the Cardiology Unit of the Yaoundé Central Hospital, Cameroon. Cardiovascular risk was estimated using the modified Framingham score, with subsequent dichotomization into low and intermediate/high risk. Mortality was assessed on day 7 during hospitalization (medical records), at one month, and one year by telephone call to a relative. Results: a total of 43 PLWH who had a stroke were enrolled. Their mean age was 52.1 (standard deviation 12.9) years, most of them were female (69.8%, n = 30). There were 25 (58.1%) patients on concomitant antiretroviral therapy. The Framingham cardiovascular risk score at admission was low in 29 patients (67.4%) and intermediate to high in 14 patients (32.6%). Ischemic stroke was the most common type of stroke in 36 persons (83.7%). The length of hospital stay was 11.4 (interquartile range 9.2-13.7) days. Mortality at 1 year was 46.5% (n = 20). Conclusion: stroke mortality was high in this population of PLWH. Most patients had a low Framingham score, suggesting that this risk estimation tool underestimates cardiovascular risk in PLWH

Integrative clinical transcriptome analysis reveals TMPRSS2‐ERG dependency of prognostic biomarkers in prostate adenocarcinoma

In prostate adenocarcinoma (PCa), distinction between indolent and aggressive disease is challenging. Around 50% of PCa are characterized by TMPRSS2‐ERG (T2E)‐fusion oncoproteins defining two molecular subtypes (T2E‐positive/negative). However, current prognostic tests do not differ between both molecular subtypes, which might affect outcome prediction. To investigate gene‐signatures associated with metastasis in T2E‐positive and T2E‐negative PCa independently, we integrated tumor transcriptomes and clinicopathological data of two cohorts (total n = 783), and analyzed metastasis‐associated gene‐signatures regarding the T2E‐status. Here, we show that the prognostic value of biomarkers in PCa critically depends on the T2E‐status. Using gene‐set enrichment analyses, we uncovered that metastatic T2E‐positive and T2E‐negative PCa are characterized by distinct gene‐signatures. In addition, by testing genes shared by several functional gene‐signatures for their association with event‐free survival in a validation cohort (n = 272), we identified five genes (ASPN, BGN, COL1A1, RRM2 and TYMS)—three of which are included in commercially available prognostic tests—whose high expression was significantly associated with worse outcome exclusively in T2E‐negative PCa. Among these genes, RRM2 and TYMS were validated by immunohistochemistry in another validation cohort (n = 135), and several of them proved to add prognostic information to current clinicopathological predictors, such as Gleason score, exclusively for T2E‐negative patients. No prognostic biomarkers were identified exclusively for T2E‐positive tumors. Collectively, our study discovers that the T2E‐status, which is per se not a strong prognostic biomarker, crucially determines the prognostic value of other biomarkers. Our data suggest that the molecular subtype needs to be considered when applying prognostic biomarkers for outcome prediction in PCa