Optimal Control of Brownian Inventory Models with Convex Inventory Cost: Discounted Cost Case

We consider an inventory system in which inventory level fluctuates as a Brownian motion in the absence of control. The inventory continuously accumulates cost at a rate that is a general convex function of the inventory level, which can be negative when there is a backlog. At any time, the inventory level can be adjusted by a positive or negative amount, which incurs a fixed positive cost and a proportional cost. The challenge is to find an adjustment policy that balances the inventory cost and adjustment cost to minimize the expected total discounted cost. We provide a tutorial on using a three-step lower-bound approach to solving the optimal control problem under a discounted cost criterion. In addition, we prove that a four-parameter control band policy is optimal among all feasible policies. A key step is the constructive proof of the existence of a unique solution to the free boundary problem. The proof leads naturally to an algorithm to compute the four parameters of the optimal control band policy

Sprinklers: A Randomized Variable-Size Striping Approach to Reordering-Free Load-Balanced Switching

Internet traffic continues to grow exponentially, calling for switches that can scale well in both size and speed. While load-balanced switches can achieve such scalability, they suffer from a fundamental packet reordering problem. Existing proposals either suffer from poor worst-case packet delays or require sophisticated matching mechanisms. In this paper, we propose a new family of stable load-balanced switches called "Sprinklers" that has comparable implementation cost and performance as the baseline load-balanced switch, but yet can guarantee packet ordering. The main idea is to force all packets within the same virtual output queue (VOQ) to traverse the same "fat path" through the switch, so that packet reordering cannot occur. At the core of Sprinklers are two key innovations: a randomized way to determine the "fat path" for each VOQ, and a way to determine its "fatness" roughly in proportion to the rate of the VOQ. These innovations enable Sprinklers to achieve near-perfect load-balancing under arbitrary admissible traffic. Proving this property rigorously using novel worst-case large deviation techniques is another key contribution of this work

On Optimizing PSA Berth Planning System

Competition among container ports continues to increase as the differentiation of hub ports and feeder ports progresses. Managers in many container terminals are trying to attract carriers by automating handling equipment, providing and speeding up various services, and furnishing the most current information on the flow of containers. At the same time, however, they are trying to reduce costs by utilizing resources efficiently, including human resources, berths, container yards, quay cranes, and various yard equipment. When planning berth usage, the berthing time and the exact position of each vessel at the wharf, as well as various quay side resources are usually determined in the process. Several variables must be considered, including the length overall (LOA) and arrival time of each vessel, the number of containers for discharging and loading, and the storage location of outbound/inbound containers to be loaded onto/discharged from the corresponding vessel. Furthermore, we aim to propose berthing plan that will be "robust", since the actual arrival time of each vessel can vary substantially from forecast. This is particular important for vessels from priority customers (called priority vessels hereon), who have been promised berth-on-arrival (i.e. within two hours of arriving) service guarantee in their contract with PSA. A robust plan will also helps to minimize the frequent updates (changes) to berthing plan that have repercussion in resource and sta deployment within the terminal. Thus, the problem reduces to one of finding a berthing plan, so that priority vessels can be berthed-on-arrival with high probability, and the vessels can be berthed as close to their preferred locations as possible, to reduce the cost of transporting the containers within the terminal. In this paper, we described an approach to address this problem.Singapore-MIT Alliance (SMA

Magnetization Transfer Prepared Gradient Echo MRI for CEST Imaging

Chemical exchange saturation transfer (CEST) is an emerging MRI contrast mechanism that is capable of noninvasively imaging dilute CEST agents and local properties such as pH and temperature, augmenting the routine MRI methods. However, the routine CEST MRI includes a long RF saturation pulse followed by fast image readout, which is associated with high specific absorption rate and limited spatial resolution. In addition, echo planar imaging (EPI)-based fast image readout is prone to image distortion, particularly severe at high field. To address these limitations, we evaluated magnetization transfer (MT) prepared gradient echo (GRE) MRI for CEST imaging. We proved the feasibility using numerical simulations and experiments in vitro and in vivo. Then we optimized the sequence by serially evaluating the effects of the number of saturation steps, MT saturation power (B1), GRE readout flip angle (FA), and repetition time (TR) upon the CEST MRI, and further demonstrated the endogenous amide proton CEST imaging in rats brains (n = 5) that underwent permanent middle cerebral artery occlusion. The CEST images can identify ischemic lesions in the first 3 hours after occlusion. In summary, our study demonstrated that the readily available MT-prepared GRE MRI, if optimized, is CEST-sensitive and remains promising for translational CEST imaging

PPARα siRNA–Treated Expression Profiles Uncover the Causal Sufficiency Network for Compound-Induced Liver Hypertrophy

Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor α (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARα-induced liver hypertrophy is supported by their ability to predict non-PPARα–induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events

Moment capacity of cold-formed steel channel beams with edge-stiffened holes by machine learning

A novel machine learning model, eXtreme Gradient Boosting (XGBoost), was used for the purpose of predicting the moment capacity of cold-formed steel (CFS) channel beams with edge-stiffened web holes subject to bending. A total of 1,620 data points were generated for training the XGBoost model, using an elasto-plastic finite element model which was validated against 12 sets of test data taken from the literature. The R2 score of XGBoost predictions for the moment capacity was around 99%. The performance of current design equations was evaluated through the comparison of their results against those obtained from the XGBoost model. The moment capacities obtained from the XGBoost testing dataset were also compared with that obtained from the existing design equations for un-stiffened holes (USH) and edge-stiffened holes (ESH). The moment capacities determined from the current design equations for USH and ESH were found to be excessively conservative by 38.3%, and unconservative by 36.2% on average, respectively. Therefore, new design equations were proposed based on the results of parametric study using the XGBoost model. From the results of XGBoost outputs, the absolute percentage error of new design equations for that based on the strengths of plain CFSCB was 8.78%, and for that based on the strengths of CFSCB with USH, the absolute percentage error was 13.7%. Additionally, a reliability analysis was performed to evaluate the accuracy of the proposed equations in predicting the moment capacity of CFS channel beams with ESH subject to bending. The reliability indices of all the proposed equations were greater than 2.5 which can be reliable as per the guidelines of AISI

Target-Based Identification of Whole-Cell Active Inhibitors of Biotin Biosynthesis in Mycobacterium tuberculosis

SummaryBiotin biosynthesis is essential for survival and persistence of Mycobacterium tuberculosis (Mtb) in vivo. The aminotransferase BioA, which catalyzes the antepenultimate step in the biotin pathway, has been established as a promising target due to its vulnerability to chemical inhibition. We performed high-throughput screening (HTS) employing a fluorescence displacement assay and identified a diverse set of potent inhibitors including many diversity-oriented synthesis (DOS) scaffolds. To efficiently select only hits targeting biotin biosynthesis, we then deployed a whole-cell counterscreen in biotin-free and biotin-containing medium against wild-type Mtb and in parallel with isogenic bioA Mtb strains that possess differential levels of BioA expression. This counterscreen proved crucial to filter out compounds whose whole-cell activity was off target as well as identify hits with weak, but measurable whole-cell activity in BioA-depleted strains. Several of the most promising hits were cocrystallized with BioA to provide a framework for future structure-based drug design efforts