Probable Donor-Derived Human Adenovirus Type 34 Infection in 2 Kidney Transplant Recipients From the Same Donor.

Human adenovirus type 34 (HAdV-34) infection is a recognized cause of transplant-associated hemorrhagic cystitis and, in rare cases, tubulointerstitial nephritis. The source of such infections is often difficult to assess, that is, whether acquired as a primary infection, exposure to a pathogen in the transplanted organ, or reactivation of an endogenous latent infection. We present here 2 cases of likely transplant-acquired HAdV-34 infection from the same organ donor, manifesting as tubulointerstitial nephritis in 1

A qualitative stakeholder analysis of avian influenza policy in Bangladesh

Avian influenza is a major animal and public health concern in Bangladesh. A decade after development and implementation of the first national avian influenza and human pandemic influenza preparedness and response plan in Bangladesh, a two-stage qualitative stakeholder analysis was performed in relation to the policy development process and the actual policy. This study specifically aimed to identify the future policy options to prevent and control avian influenza and other poultry-related zoonotic diseases in Bangladesh. It was recommended that the policy should be based on the One Health concept, be evidence-based, sustainable, reviewed and updated as necessary. The future policy environment that is suitable for developing and implementing these policies should take into account the following points: the need to formally engage multiple sectors, the need for clear and acceptable leadership, roles and responsibilities, and the need for a common pool of resources and provision for transferring resources. Most of these recommendations are directed towards the Government of Bangladesh. However, other sectors, including research and poultry production stakeholders, also have a major role to play to inform policy-making and actively participate in the multi-sectoral approach

Simple Systematic Synthesis of Periodic Mesoporous Organosilica Nanoparticles with Adjustable Aspect Ratios

One-dimensional periodic mesoporous organosilica (PMO) nanoparticles with tunable aspect ratios are obtained from a chain-type molecular precursor octaethoxy-1,3,5-trisilapentane. The aspect ratio can be tuned from 2:1 to >20:1 simply by variation in the precursor concentration in acidic aqueous solutions containing constant amounts of triblock copolymer Pluronic P123. The mesochannels are highly ordered and are oriented parallel to the longitudinal axis of the PMO particles. No significant Si–C bond cleavage occurs during the synthesis according to29Si MAS NMR. The materials exhibit surface areas between 181 and 936 m2 g−1

DMLR: Data-centric Machine Learning Research -- Past, Present and Future

Drawing from discussions at the inaugural DMLR workshop at ICML 2023 and meetings prior, in this report we outline the relevance of community engagement and infrastructure development for the creation of next-generation public datasets that will advance machine learning science. We chart a path forward as a collective effort to sustain the creation and maintenance of these datasets and methods towards positive scientific, societal and business impact.Comment: This editorial report accompanies the inaugural Data-centric Machine Learning Research (DMLR) Workshop that took place at ICML 2023 https://dmlr.ai

A multi-criteria sustainability assessment framework: development and application in comparing two food waste management options using a UK region as a case study

This is a post-peer-review, pre-copyedit version of an article published in Environmental Science and Pollution Research. The final authenticated version is available online at: https://doi.org/10.1007/s11356-018-2479-

A utility-based adaptive sensing and multi-hop communication protocol for wireless sensor networks

This article reports on the development of a utility-based mechanism for managing sensing and communication in cooperative multisensor networks. The specific application on which we illustrate our mechanism is that of GlacsWeb. This is a deployed system that uses battery-powered sensors to collect environmental data related to glaciers which it transmits back to a base station so that it can be made available world-wide to researchers. In this context, we first develop a sensing protocol in which each sensor locally adjusts its sensing rate based on the value of the data it believes it will observe. The sensors employ a Bayesian linear model to decide their sampling rate and exploit the properties of the Kullback-Leibler divergence to place an appropriate value on the data. Then, we detail a communication protocol that finds optimal routes for relaying this data back to the base station based on the cost of communicating it (derived from the opportunity cost of using the battery power for relaying data). Finally, we empirically evaluate our protocol by examining the impact on efficiency of a static network topology, a dynamic network topology, the size of the network, the degree of dynamism of the environment, and the mobility of the nodes. In so doing, we demonstrate that the efficiency gains of our new protocol, over the currently implemented method over a 6 month period, are 78%, 133%, 100%, and 93%, respectively. Furthermore, we show that our system performs at 65%, 70%, 63%, and 70% of the theoretical optimal, respectively, despite being a distributed protocol that operates with incomplete knowledge of the environment

Active case detection in national visceral leishmaniasis elimination programs in Bangladesh, India, and Nepal: feasibility, performance and costs

Background Active case detection (ACD) significantly contributes to early detection and treatment of visceral leishmaniasis (VL) and post kala-azar dermal leishmaniasis (PKDL) cases and is cost effective. This paper evaluates the performance and feasibility of adapting ACD strategies into national programs for VL elimination in Bangladesh, India and Nepal. Methods The camp search and index case search strategies were piloted in 2010-11 by national programs in high and moderate endemic districts / sub-districts respectively. Researchers independently assessed the performance and feasibility of these strategies through direct observation of activities and review of records. Program costs were estimated using an ingredients costing method. Results Altogether 48 camps (Bangladesh-27, India-19, Nepal-2) and 81 index case searches (India-36, Nepal-45) were conducted by the health services across 50 health center areas (Bangladesh-4 Upazillas, India-9 PHCs, Nepal-37 VDCs). The mean number of new case detected per camp was 1.3 and it varied from 0.32 in India to 2.0 in Bangladesh. The cost (excluding training costs) of detecting one new VL case per camp varied from USD 22 in Bangladesh, USD 199 in Nepal to USD 320 in India. The camp search strategy detected a substantive number of new PKDL cases. The major challenges faced by the programs were inadequate preparation, time and resources spent on promoting camp awareness through IEC activities in the community. Incorrectly diagnosed splenic enlargement at camps probably due to poor clinical examination skills resulted in a high proportion of patients being subjected to rK39 testing. Conclusion National programs can adapt ACD strategies for detection of new VL/PKDL cases. However adequate time and resources are required for training, planning and strengthening referral services to overcome challenges faced by the programs in conducting ACD

Managing Crowdsourced Human Computation

The proposed tutorial covers an emerging topic of wide interest: Crowdsourcing. Specifically, we cover areas of crowdsourcing related to managing structured and unstructured data in a web-related content. Many researchers and practitioners today see the great opportunity that becomes available through easily-available crowdsourcing platforms. However, most newcomers face the same questions: How can we manage the (noisy) crowds to generate high quality output? How to estimate the quality of the contributors? How can we best structure the tasks? How can we get results in small amounts of time and minimizing the necessary resources? How to setup the incentives? How should such crowdsourcing markets be setup? Their presented material will cover topics from a variety of fields, including computer science, statistics, economics, and psychology. Furthermore, the material will include real-life examples and case studies from years of experience in running and managing crowdsourcing applications in business settings. The tutorial presenters have an extensive academic and systems building experience and will provide the audience with data sets that can be used for hands-on tasks. Keywords crowdsourcing mechanical turk workflow control quality assurance incentives reputation market design human computation 1