Acceptable Time Constraints Research Articles

Kidney utility and futility.

Changes in kidney allocation coupled with the COVID-19 pandemic have placed tremendous strain on current systems of organ distribution and logistics. Although the number of deceased donors continues to rise annually in the United States, the proportion of marginal deceased donors (MDDs) is disproportionately growing. Cold ischemia times and kidney discard rates are rising in part related to inadequate planning, resources, and shortages. Complexity in kidney allocation and distribution has contributed to this dilemma. Logistical issues and the ability to reperfuse the kidney within acceptable time constraints increasingly determine clinical decision-making for organ acceptance. We have a good understanding of the phenotype of "hard to place" MDD kidneys, yet continue to promote a "one size fits all" approach to organ allocation. Allocation and transportation systems need to be agile, mobile, and flexible in order to accommodate the expanding numbers of MDD organs. By identifying "hard to place" MDD kidneys early and implementing a "fast-track" or open offer policy to expedite placement, the utilization rate of MDDs would improve dramatically. Organ allocation and distribution based on location, motivation, and innovation must lead the way. In the absence of change, we are sacrificing utility for futility and discard rates will continue to escalate.

A Systematic Literature Review on Metaheuristic Optimization Techniques in WSNs

Metaheuristic algorithms are recognized for developing new algorithms and optimizing various aspects in Wireless Sensor Networks (WSNs). Evaluating a multitude of possible modes is required, in most complicated problems, to obtain an exact solution. Metaheuristic algorithms can obtain solutions in acceptable time constraints. These algorithms play an operational role in solving such problems by optimizing the different metrics such as coverage rate and energy consumption of the networks. These metrics have valuable impact on network lifetime as well. This systematic review focuses on the published work from 2010 to 2020 in metaheuristic optimization in WSN. Furthermore, the systematic review will answer multiple questions that will be discussed in the methodology section.

Isolating Lymphocytes from the Mouse Small Intestinal Immune System

The intestinal immune system plays an essential role in maintaining the barrier function of the gastrointestinal tract by generating tolerant responses to dietary antigens and commensal bacteria while mounting effective immune responses to enteropathogenic microbes. In addition, it has become clear that local intestinal immunity has a profound impact on distant and systemic immunity. Therefore, it is important to study how an intestinal immune response is induced and what the immunologic outcome of the response is. Here, a detailed protocol is described for the isolation of lymphocytes from small intestine inductive sites like the gut-associated lymphoid tissue Peyer's patches and the draining mesenteric lymph nodes and effector sites like the lamina propria and the intestinal epithelium. This technique ensures isolation of a large numbers of lymphocytes from small intestinal tissues with optimal purity and viability and minimal cross compartmental contamination within acceptable time constraints. The technical capability to isolate lymphocytes and other immune cells from intestinal tissues enables the understanding of immune responses to gastrointestinal infections, cancers, and inflammatory diseases.

HSCA: a novel harmony search based efficient clustering in heterogeneous WSNs

Clustering objective reasons scalability, fault tolerance, data aggregation or fusion, load balancing of cluster heads, stabilized network topology, maximal network lifetime, increased connectivity, reduced routing delay, collision avoidance and utilizing sleeping schemes in wireless sensor networks. Load balanced clustering effectively organize the network into a connected hierarchy. Clustering is a discrete problem that can have more than one solution under different operating constraints. In this scenario, meta-heuristic algorithms are found suitable because they give set of solutions in acceptable time constraints. In the literature, several analytical and meta-heuristic approaches have been developed for load balanced clustering. In this paper, a novel harmony search based energy efficient load balanced clustering algorithm is presented and it is tested on a large sample network. Results demonstrated that the proposed approach has faster convergence and gives reliable and efficient load balanced clustering as compared to conventional harmony search algorithm (HSA) and several other methods in the literature. Moreover, the robustness of the proposed approach is also verified for different cases of fixed and variable parameters of HSA.

The Application of Meta-Heuristic based Clustering Techniques in Wireless Sensor Networks

Wireless sensor networks are normally utilized for monitoring and controlling of specific environments. They are made out of a large number of low-cost sensor nodes which are densely separated in distributed environments. The information collected by sensors should be transmitted to a base station. Recent developments indicate that the interest in applications of wireless sensor networks has increased and expanded on a large scale. One of the most important issues in this type of networks is limited energy. Clustering is a suitable method for increasing network lifetime that protects the limited sensor resources by energy saving. Meta-heuristic algorithms have been widely used for clustering of wireless sensor networks. In most complicated problems, it is required to evaluate a multitude of possible modes, to determine an accurate answer. Meta-heuristic algorithms can provide an answer in acceptable time constraints. They play an effective role in solving such problems by optimizing the energy consumption of the networks that has a significant impact on the network lifetime. In this paper, the application of clustering algorithms in wireless sensor networks has been investigated. The selected clustering methods are based on the meta-heuristic algorithms.

Min-heap-based scheduling algorithm: an approximation algorithm for homogeneous and heterogeneous distributed systems

One of the most important issues in the design of distributed systems is process scheduling, which maps applications to resources in an attempt to reduce the application execution time or maximise resource utilisation. The complexity involved in finding good scheduling solutions has motivated the design of several heuristics and approximation algorithms. Although heuristics aim at finding good solutions within acceptable time constraints, they do not guarantee solution quality. On the other hand, approximation-based algorithms provide optimal solution bounds, but they are usually designed to address simple scenarios. In an attempt to combine the best of both algorithmic approaches, this paper proposes the min-heap-based scheduling algorithm (MHSA), which finds solutions for homogeneous and heterogeneous distributed environments within acceptable time constraints and optimal solution bounds. MHSA considers applications that can be bag-of-tasks or which communicate among each other. Such solutions minimise the application execution time and maximise resource utilisation; therefore, MHSA is a system-oriented scheduling algorithm. Results confirm that MHSA provides better solutions than schedulers such as Random, Round-Robin, Workload-Queue and List-Scheduling. In addition, MHSA provides an -approximation ratio for reaching optimal solution bounds.

Isolation of mouse lymphocytes from small intestine tissues.

The isolation of lymphocytes and other hematopoietic-derived cells from small intestinal tissues has become increasingly relevant to immunology over the last decade. It is also becoming increasingly clear that the impact of local immunity at the mucosal barrier of the intestine has a profound impact on immune responses at distant sites, bringing a new cadre of immunologists to the mucosal frontier. Furthermore, the ability to experimentally manipulate smaller and smaller populations of immune cells has become technologically feasible and in some cases routine. The expanding importance of mucosal immunology coupled with increased technical capabilities requires a standard for experimentally obtaining uniform and consistent cells from the intestinal mucosa. Therefore, it is important to isolate immune cells that are highly viable and minimally manipulated to maximize cellular yields while maintaining acceptable time constraints.

Developing a biomarker-stratified trial design in advanced colorectal cancer: The MRC FOCUS 3 feasibility study.

TPS165 Background: It is likely that future trials for many solid tumours will be stratified by predictive/prognostic biomarkers in order to a) derive more homogeneous patient cohorts; b) “personalize” treatment interventions in relation to tumour (or host) phenotype; and c) improve the likelihood of discovering a beneficial effect, in at least a subset of patients with the disease. In some settings there are likely to be multiple relevant biomarkers and treatments to be tested. For logistical reasons it would be efficient to combine these into single trials. Moreover, the inclusion of overlapping or common treatment arms could serve to further validate the use of a given biomarker for selection and support retrospective testing of other biomarker selection algorithms that may arise during the course of a trial’s enrolment period. These requirements present significant challenges both for creating efficient designs and for making these comprehensible for prospective subjects. Methods: FOCUS 3 is a feasibility study designed to address these issues and test a novel design for examining the predictive role of biomarkers (KRAS/BRAF mutations and topo-1 expression) for 1st-line therapy of aCRC. It employs an unusual design in which the two biomarkers defined four possible cohorts. Specific treatment questions were relevant to each marker and, because each cohort was defined by 2 markers, there were 2 relevant experimental arms for each cohort, plus 1 common control arm for all cohorts (FOLFIRI). The study thus incorporates 5 treatment regimens, but only 3 possibilities for each patient, defined by marker phenotype. We will complete recruitment of 240 patients by April 2011. Paraffin blocks from 24 sites were obtained for central biomarker analysis and aim to feedback results within 10 working days. A 4 stage suite of patient information sheets (PIS) was designed to avoid patient overload and we are assessing patients’ comprehension in a qualitative study. Conclusion: Patient samples can be collected and analysed centrally within acceptable time constraints. Complex, stratified, multi arm designs can be made acceptable to patients through good PIS design, ensured by patient and carer input into their design.