Invasive Plants Distribution Modeling: A Tool for Tropical Biodiversity Conservation With Special Reference to Sri Lanka

The potential threats and habitat preferences of noxious plants in tropical countries are poorly known. Species distribution modeling (SDM) is a robust tool that can be used in conservation planning for early detection of invasion risks. However, the use of SDM for the strategic management of increasing risks of such plant invasions in Sri Lanka has not been undertaken due to several underlying reasons including the long-lasting data gap, technical, technological, and financial issues. In addition, the literature relevant to SDM applications in the country is substantially poor, scattered, and unpublished. Therefore, in this article, we explore SDM applications relevant to invasive plants in Sri Lanka with implications similar to other countries in the tropics. We examine the challenges and potentials for utilization of SDM technology in conservation planning in Sri Lanka and discuss data gap as a major obstacle. We also identify the potential SDM interventions relevant to invasive plants control and management in Sri Lanka and recommend conservation planners to prioritize them and apply for the strategic management of invasive plants in Sri Lanka. Finally, we suggest some recommendations to make an enabling environment in relevant institutions for the utilization of SDM technology in ecosystem management planning in Sri Lanka

Implementation of a novel antimicrobial stewardship strategy for rural facilities utilising telehealth

A significant portion of healthcare takes place in small hospitals, and many are located in rural and regional areas. Facilities in these regions frequently do not have adequate resources to implement an onsite antimicrobial stewardship programme and there are limited data relating to their implementation and effectiveness. We present an innovative model of providing a specialist telehealth antimicrobial stewardship service utilising a centralised service (Queensland Statewide Antimicrobial Stewardship Program) to a rural Hospital and Health Service. Results of a 2-year post-implementation follow-up showed an improvement in adherence to guidelines [33.7% (95% CI 27.0–40.4%) vs. 54.1% (95% CI 48.7–59.5%)] and appropriateness of antimicrobial prescribing [49.0% (95% CI 42.2–55.9%) vs. 67.5% (95% CI 62.7–72.4%) (P < 0.001). This finding was sustained after adjustment for hospitals, with improvement occurring sequentially across the years for adherence to guidelines [adjusted odds ratio (aOR) = 2.44, 95% CI 1.70–3.51] and appropriateness of prescribing (aOR = 2.48, 95% CI 1.70–3.61). There was a decrease in mean total antibiotic use (DDDs/1000 patient-days) between the years 2016 (52.82, 95% CI 44.09–61.54) and 2018 (39.74, 95% CI 32.76–46.73), however this did not reach statistical significance. Additionally, there was a decrease in mean hospital length of stay (days) from 2016 (3.74, 95% CI 3.08–4.41) to 2018 (2.55, 95% CI 1.98–3.12), although this was not statistically significant. New telehealth-based models of antimicrobial stewardship can be effective in improving prescribing in rural areas. Programmes similar to ours should be considered for rural facilities

From Hours to Seconds: Towards 100x Faster Quantitative Phase Imaging via Differentiable Microscopy

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-learning-based inverse solvers, the throughput of QPM is currently limited by the speed of electronic hardware. Complementarily, to improve throughput further, here we propose to acquire images in a compressed form such that more information can be transferred beyond the existing electronic hardware bottleneck. To this end, we present a learnable optical compression-decompression framework that learns content-specific features. The proposed differentiable quantitative phase microscopy ($\partial \mu$) first uses learnable optical feature extractors as image compressors. The intensity representation produced by these networks is then captured by the imaging sensor. Finally, a reconstruction network running on electronic hardware decompresses the QPM images. In numerical experiments, the proposed system achieves compression of $\times$ 64 while maintaining the SSIM of $\sim 0.90$ and PSNR of $\sim 30$ dB on cells. The results demonstrated by our experiments open up a new pathway for achieving end-to-end optimized (i.e., optics and electronic) compact QPM systems that may provide unprecedented throughput improvements

Methodological overview of systematic reviews to establish the evidence base for emergency general surgery

BACKGROUND: The evidence for treatment decision‐making in emergency general surgery has not been summarized previously. The aim of this overview was to review the quantity and quality of systematic review evidence for the most common emergency surgical conditions. METHODS: Systematic reviews of the most common conditions requiring unplanned admission and treatment managed by general surgeons were eligible for inclusion. The Centre for Reviews and Dissemination databases were searched to April 2014. The number and type (randomized or non‐randomized) of included studies and patients were extracted and summarized. The total number of unique studies was recorded for each condition. The nature of the interventions (surgical, non‐surgical invasive or non‐invasive) was documented. The quality of reviews was assessed using the AMSTAR checklist. RESULTS: The 106 included reviews focused mainly on bowel conditions (42), appendicitis (40) and gallstone disease (17). Fifty‐one (48·1 per cent) included RCTs alone, 79 (74·5 per cent) included at least one RCT and 25 (23·6 per cent) summarized non‐randomized evidence alone. Reviews included 727 unique studies, of which 30·3 per cent were RCTs. Sixty‐five reviews compared different types of surgical intervention and 27 summarized trials of surgical versus non‐surgical interventions. Fifty‐seven reviews (53·8 per cent) were rated as low risk of bias. CONCLUSION: This overview of reviews highlights the need for more and better research in this field

Autonomy of Nations and Indigenous Peoples and the Environmental Release of Genetically Engineered Animals with Gene Drives

This article contends that the environmental release of genetically engineered (GE) animals with heritable traits that are patented will present a challenge to the efforts of nations and indigenous peoples to engage in self‐determination. The environmental release of such animals has been proposed on the grounds that they could function as public health tools or as solutions to the problem of agricultural insect pests. This article brings into focus two political‐economic‐legal problems that would arise with the environmental release of such organisms. To address those challenges, it is proposed that nations considering the environmental release of GE animals must take into account the underlying circumstances and policy failures that motivate arguments for the use of the modified animals. Moreover, countries must recognize that the UN International Covenant on Civil and Political Rights and the UN International Covenant on Economic, Social and Cultural Rights place on them an obligation to ensure that GE animals with patented heritable traits are not released without the substantive consent of the nations or indigenous peoples that could be affected

FitFlame – Health and Fitness Coaching Application to Mitigate the Issues in the Current Applications

Online fitness coaches help people achieve a healthy lifestyle by offering customized solutions. The demand for professional coaching is expected to grow in the coming years. Nevertheless, no applications in the market address the problems in the coaching process. Today, coaches and clients had to use many third-party apps. The reason for this is that no single fitness coaching app offers communication and exercise-tracking features. Even though some apps meet some of these requirements, they are out of reach for most people's budgets. This paper aims to suggest a robust and full-fledged app to mitigate those issues. FitFlame is the name of the proposed app. Both coaches and clients can benefit from this app. Also, FitFlame is a fitness coaching system available on mobile and the web. It helps clients locate and contact coaches, subscribe to coaching plans, and track their progress. It does away with third-party programs and gives users a better experience

ESTIMATION OF FARM LEVEL TECHNICAL EFFICIENCY AND ITS SOCIO-ECONOMIC DETERMINANTS IN VANILLA PRODUCTION IN KANDY DISTRICT, SRI LANKA

Vanilla is one of the economically important crops in Sri Lanka although it is mainly confined as a home garden crop grown in mid and low country wet zone. Farmer productivity is one of the most important concerns in vanilla cultivation. Thus, the productivity of Vanilla farmers can be raised by improvement in efficiency in the short run. As a result of the near absence of empirical information on farm-level technical efficiency in small scale Vanilla Production in the country generally and Kandy District in particular, a Stochastic Frontier function which incorporated inefficiency factors was estimated using a Maximum Likelihood technique to provide estimates of technical efficiency and its determinants using data obtained from 80 Vanilla farmers in Ganga Ihala Korale Divisional Secretariat division since it has one of the largest numbers of small-holder vanilla producers in the country. The results reveal that Vanilla farmers are not fully technically efficient and the mean technical efficiency estimated is 37.32%. Estimated results of the inefficiency model show that experience and educational level of the vanilla farmers significantly influence the farmers ‘efficiency positively whereas age of the farmers contributes to increase the inefficiency. The findings imply that policies that would encourage youth to engage in vanilla farming and improvement in human capital should be made and implemented.Keywords: Kandy District, Maximum Like hood estimation, Stochastic frontier model, Technical efficiency, Vanilla farmer

Activin-A induces regulatory T cells that suppress T helper cell immune responses and protect from allergic airway disease

Activin-A is a pleiotropic cytokine that participates in developmental, inflammatory, and tissue repair processes. Still, its effects on T helper (Th) cell–mediated immunity, critical for allergic and autoimmune diseases, are elusive. We provide evidence that endogenously produced activin-A suppresses antigen-specific Th2 responses and protects against airway hyperresponsiveness and allergic airway disease in mice. Importantly, we reveal that activin-A exerts suppressive function through induction of antigen-specific regulatory T cells that suppress Th2 responses in vitro and upon transfer in vivo. In fact, activin-A also suppresses Th1-driven responses, pointing to a broader immunoregulatory function. Blockade of interleukin 10 and transforming growth factor β1 reverses activin-A–induced suppression. Remarkably, transfer of activin-A–induced antigen-specific regulatory T cells confers protection against allergic airway disease. This beneficial effect is associated with dramatically decreased maturation of draining lymph node dendritic cells. Therapeutic administration of recombinant activin-A during pulmonary allergen challenge suppresses Th2 responses and protects from allergic disease. Finally, we demonstrate that immune cells infiltrating the lungs from individuals with active allergic asthma, and thus nonregulated inflammatory response, exhibit significantly decreased expression of activin-A's responsive elements. Our results uncover activin-A as a novel suppressive factor for Th immunity and a critical controller of allergic airway disease