Task Scheduling in Networks

Scheduling a set of tasks on a set of machines so as to yield an efficient schedule is a basic problem in computer science and operations research. Most of the research on this problem incorporates the potentially unrealistic assumption that communication between the different machines is instantaneous. In this paper we remove this assumption and study the problem of network scheduling, where each job originates at some node of a network, and in order to be processed at another node must take the time to travel through the network to that node. Our main contribution is to give approximation algorithms and hardness proofs for fully general forms of the fundamental problems in network scheduling. We consider two basic scheduling objectives: minimizing the makespan and minimizing the average completion time. For the makespan, we prove small constant factor hardness-to-approximate and approximation results. For the average completion time, we give a log-squared approximation algorithm for the most general form of the problem. The techniques used in this approximation are fairly general and have several other applications. For example, we give the first nontrivial approximation algorithm to minimize the average weighted completion time of a set of jobs on related or unrelated machines, with or without a network

A Simulation-Based Approach for Evaluating Cost and Performance of a Sediment Removal and Processing System for the Lower Susquehanna River Dams

A series of three major dams and reservoirs located along the Lower Susquehanna River have historically acted as a system of sediment and nutrient pollution traps.  However, episodic pulses of these pollution loads are released following short-term extreme storm events, affecting subaquatic vegetation, benthic organisms, and the overall water quality in the Upper Chesapeake Bay.  In addition, all three reservoirs have reached a state of near maximum storage capacity termed as dynamic equilibrium.  Based on prior research, this study seeks to reduce the sediment buildup behind the dams through a sediment removal and processing operation, and thereby reduce the ecological impact of major storms.  A set of scour performance curves derived from a regression analysis, and a stochastic lifecycle cost model were used to evaluate the sediment scouring reduction and economic feasibility of three processing alternatives:  Plasma Vitrification, Cement-Lock, and Quarry/Landfill, and three removal amount cases:  Nominal, Moderate, and Maximum.  Since the scour performance curves treat the dams as static, a fluid system dynamics model was used to determine if the dynamic interaction between the capacitance of the dams during major scouring events is negligible or considerable.  A utility vs. cost analysis factoring in time, performance, and suitability of the alternatives indicates that a Cement-Lock processing plant at moderate dredging for the Safe Harbor and Conowingo Dams is the most cost-performance effective solution

Human Robot Interface for Assistive Grasping

This work describes a new human-in-the-loop (HitL) assistive grasping system for individuals with varying levels of physical capabilities. We investigated the feasibility of using four potential input devices with our assistive grasping system interface, using able-bodied individuals to define a set of quantitative metrics that could be used to assess an assistive grasping system. We then took these measurements and created a generalized benchmark for evaluating the effectiveness of any arbitrary input device into a HitL grasping system. The four input devices were a mouse, a speech recognition device, an assistive switch, and a novel sEMG device developed by our group that was connected either to the forearm or behind the ear of the subject. These preliminary results provide insight into how different interface devices perform for generalized assistive grasping tasks and also highlight the potential of sEMG based control for severely disabled individuals.Comment: 8 pages, 21 figure

Analysis of High-Speed Rail Implementation Alternatives in the Northeast Corridor: the Role of Institutional and Technological Flexibility

In this paper, an engineering systems framework using the CLIOS Process, scenario analysis, and flexibility analysis is used to study the implementation of a high-speed rail corridor in the Northeast Corridor of the United States. Given the tremendous uncertainty that characterizes high-speed rail projects, the implementation of the alternatives proposed, which are very similar to other commonly accepted ways to implement high-speed rail in the corridor, are analyzed under different scenarios. The results motivate incorporation of flexibility into the alternatives to allow decision makers to adapt as situations evolve. While designing-in this flexibility has a cost, it may facilitate the implementation of the alternatives by enabling adaptation to uncertain outcomes, thereby improving performance

Selection of Post-Acute Care for Stroke Patients

Background: Significant variation exists in post-acute care for stroke survivors. This study examines referral practices of occupational and physical therapists for patients after acute stroke. Method: Occupational therapists (OTs) and physical therapists (PTs) were surveyed either electronically or in person at a national conference. The respondents selected the most appropriate referral for each of five case vignettes. The referral choices included Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility (SNF), Long-Term Acute Care Hospital (LTACH), home with home services, or home with outpatient services. Demographic data included practice location, setting, and duration. The respondents were also asked to rate how strongly 15 clinical factors influence their referral decisions. Results: The 33 OTs and 41 PTs favored similar referrals. Consensus was observed in four of the five cases. No differences were observed among the respondents based on practice location, practice setting, or number of years in practice and the referrals. Prognosis for functional improvement and pre-stroke functional status were identified as the most important factors influencing referral decisions. Conclusion: Further studies are needed to define areas of broad consensus as well as areas of disagreement, with subsequent efforts to clarify optimal treatment algorithms for patients who currently receive variable rehabilitative care

Stem Cells in the Nervous System

Given their capacity to regenerate cells lost through injury or disease, stem cells offer new vistas into possible treatments for degenerative diseases and their underlying causes. As such, stem cell biology is emerging as a driving force behind many studies in regenerative medicine. This review focuses on the current understanding of the applications of stem cells in treating ailments of the human brain, with an emphasis on neurodegenerative diseases. Two types of neural stem cells are discussed: endogenous neural stem cells residing within the adult brain and pluripotent stem cells capable of forming neural cells in culture. Endogenous neural stem cells give rise to neurons throughout life, but they are restricted to specialized regions in the brain. Elucidating the molecular mechanisms regulating these cells is key in determining their therapeutic potential as well as finding mechanisms to activate dormant stem cells outside these specialized microdomains. In parallel, patient-derived stem cells can be used to generate neural cells in culture, providing new tools for disease modeling, drug testing, and cell-based therapies. Turning these technologies into viable treatments will require the integration of basic science with clinical skills in rehabilitation