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Glass is a valuable physical evidence of our early trade exchanges, and ancient glass is susceptible to weathering by the burial environment, resulting in changes in its composition ratio. In this study, the surface weathering of glass artifacts was analyzed in relation to their glass type, decoration and color; the statistical patterns of the chemical composition content of artifact samples with and without weathering were analyzed in relation to the glass type and a Random forest (RF) model was developed to predict the chemical composition content of the artifacts before weathering based on the weathering point detection data.

In this work, we study the optimal design of two-armed clinical trials to maximize the accuracy of parameter estimation in a statistical model, where the interaction between patient covariates and treatment are explicitly incorporated to enable precision medication decisions. Such a modeling extension leads to significant complexities for the produced optimization problems because they include optimization over design and covariates concurrently. We take a min-max optimization model and minimize (over design) the maximum (over population) variance of the estimated interaction effect between treatment and patient covariates. This results in a min-max bilevel mixed integer nonlinear programming problem, which is notably challenging to solve. To address this challenge, we introduce a surrogate optimization model by approximating the objective function, for which we propose two solution approaches. The first approach provides an exact solution based on reformulation and decomposition techniques. In the second approach, we provide a lower bound for the inner optimization problem and solve the outer optimization problem over the lower bound. We test our proposed algorithms with synthetic and real-world data sets and compare them with standard (re)randomization methods. Our numerical analysis suggests that the proposed approaches provide higher-quality solutions in terms of the variance of estimators and probability of correct selection. We also show the value of covariate information in precision medicine clinical trials by comparing our proposed approaches to an alternative optimal design approach that does not consider the interaction terms between covariates and treatment. Summary of Contribution: Precision medicine is the future of healthcare where treatment is prescribed based on each patient information. Designing precision medicine clinical trials, which are the cornerstone of precision medicine, is extremely challenging because sample size is limited and patient information may be multidimensional. This work proposes a novel approach to optimally estimate the treatment effect for each patient type in a two-armed clinical trial by reducing the largest variance of personalized treatment effect. We use several statistical and optimization techniques to produce efficient solution methodologies. Results have the potential to save countless lives by transforming the design and implementation of future clinical trials to ensure the right treatments for the right patients. Doing so will reduce patient risks and reduce costs in the healthcare system.

Healthcare workers’ (HCWs) safety and availability to care for patients are critical during a pandemic such as the one caused by severe acute respiratory syndrome coronavirus 2. Among providers of different specialities, it is critical to protect those working in hospital settings with a high risk of infection. Using an agent-based simulation model, various staffing policies were developed and simulated for 90 days using data from the largest health systems in South Carolina. The model considers staffing policies that include geographic segregation, interpersonal contact limits, and a combination of factors, including the patient census, transmission rates, vaccination status of providers, hospital capacity, incubation time, quarantine period, and interactions between patients and providers. Comparing the existing practices to various risk-adjusted staffing policies, model predictions show that restricted teaming and rotating schedules significantly (p-value p-value = 0.09) benefits. Although these simulated outcomes are specific to one health system, our findings can be generalised to other health systems with multiple locations.

In this paper, we extend the adaptive partition-based approach for solving two-stage stochastic programs with fixed recourse matrix and fixed cost vector to the multistage stochastic programming setting where the stochastic process is assumed to be stage-wise independent. The proposed algorithms integrate the adaptive partition-based strategy with a popular approach for solving multistage stochastic programs, the stochastic dual dynamic programming (SDDP) algorithm, according to two main strategies. These two strategies are distinct from each other in the manner by which they refine the partitions during the solution process. In particular, we propose a refinement outside SDDP strategy whereby we iteratively solve a coarse scenario tree induced by the partitions, and refine the partitions in a separate step outside of SDDP, only when necessary. We also propose a refinement within SDDP strategy where the partitions are refined in conjunction with the machinery of the SDDP algorithm. We then use, within the two different refinement schemes, different tree-traversal strategies which allow us to have some control over the size of the partitions. We performed numerical experiments on a hydro-thermal power generation planning problem. Numerical results show the effectiveness of the proposed algorithms that use the refinement outside SDDP strategy in comparison to the standard SDDP algorithm and algorithms that use the refinement within SDDP strategy.

The Asian summer monsoon (ASM) affects more than one-third of the world’s population due to its close connection with floods, droughts thus water resources in densely populated Asian countries. The effects of aerosols emitted in remote regions on the ASM, in contrast to local emissions, remain largely unclear. Here we demonstrate through a hierarchy of climate models that aerosol emissions from the central African wildfires could strengthen the circulation of the ASM (South Asian Monsoon in particular), increase precipitation over South Asia and reduce precipitation immediately north and south of it. The enhanced latent heating over South Asia provides a critical positive feedback to the initial strengthening of monsoon westerlies associated with wildfire-driven anomalous Rossby wave source. The atmospheric dynamical bridge discovered here effectively connects African biomass burning with hydroclimate variability over East Asia in boreal summer and offers a new source of monsoon predictability across a range of timescales.

The public reporting of hospitals' quality of care is providing additional motivation for hospitals to deliver high-quality patient care. Hospital Compare, a consumer-oriented website by the Centers for Medicare and Medicaid Services (CMS), provides patients with detailed quality of care data on most US hospitals. Given that many quality metrics are the aggregate result of physicians' individual clinical decisions, the question arises if and how hospitals could influence their physicians so that their decisions positively contribute to hospitals' quality goals. In this paper, we develop a decision-theoretic model to explore how three different hospital interventions-incentivization, training, and nudging-may affect physicians' decisions. We focus our analysis on Outpatient Measure 14 (OP-14), which is an imaging quality metric that reports the percentage of outpatients with a brain computed tomography (CT) scan, who also received a same-day sinus CT scan. In most cases, same-day brain and sinus CT scans are considered unnecessary, and high utilizing hospitals aim to reduce their OP-14 metric. Our model captures the physicians' imaging decision process accounting for medical and behavioral factors, in particular the uncertainty in clinical assessment and a physician's diagnostic ability. Our analysis shows how hospital interventions of incentivization, training, and nudging affect physician decisions and consequently OP-14. This decision-theoretic model provides a foundation to develop insights for policy makers on the multi-level effects of their policy decisions.

SUMMARYThorough understanding of seismic signatures in cracked rocks is essential to estimate rock physical properties. Wave-induced fluid flow (or diffusion), scattering and Biot's global flow are three major mechanisms in controlling frequency-dependent attenuation and dispersion. To shed light on how those mechanisms and their interference affect the anisotropic features in cracked porous rocks, we develop an analytic model to estimate the angle-dependent attenuation and dispersion in such media. The most noteworthy feature of the model is that it is developed upon the exact solution of the problem of elastic wave scattered by a crack at oblique incidence. In particular, the poroelastic spring condition is applied to describe the influences of crack thickness and crack-filling fluid elasticity on wave scattering. Regardless of its complexity, we have showed that the model agrees with many benchmark theories under corresponding conditions, demonstrating its reasonability. It is found that the key factors that dominate anisotropic attenuation and dispersion are different in separating frequency regimes. At diffusion-dominated frequencies, the frequency-dependent anisotropic properties are mainly determined by the normal stress on the crack faces. In contrast, in Rayleigh scattering regime, they are greatly determined by the applied shear stress. At higher frequencies (Mie scattering regime), affected by the wave reflections between the crack edges, the frequency-dependent anisotropy becomes complex. The angle-dependent velocity can largely deviate from elliptic-shaped profile. As a result, the material properties cannot be described within the framework of the transversely isotropic medium model. Moreover, it is found that the attenuation is sensitive to the fluid compressibility and crack thickness, showing evidences that it is possible to invert fluid saturation and permeability from seismic attenuation. We also conclude that using a simple linear superposition of the attenuations due to wave-induced fluid flow and elastic scattering from their corresponding equivalent medium models will leads to an overestimation of the total attenuation. Our results demonstrate it is necessary to account for the mechanism interference to allow for an adequate estimation of the intrinsic attenuation of cracked porous rocks.

In the aftermath of a hurricane, humanitarian logistics plays a critical role in delivering relief items to the affected areas in a timely fashion. This paper proposes a novel stochastic look-ahead framework that implements a two-stage stochastic programming model in a rolling horizon approach to address the evolving uncertain logistics system state during the post-hurricane humanitarian logistics operations. The two-stage stochastic programming model that executes in this rolling horizon approach is formulated as a mixed-integer programming problem. The model aims to minimize the total cost incurred in the logistics operations, which consist of transportation cost and social cost. The social cost is measured as a function of deprivation for unsatisfied demand. Our extensive numerical results and sensitivity analysis demonstrate the effectiveness of the proposed approach in reducing the total cost incurred during the post-hurricane relief logistics operations compared to the two-stage stochastic programming model implemented in a static fashion.

Analytic solutions are derived for the problem of scattering of obliquely incident plane waves from a rectangular crack in a fluid-saturated porous solid. The propagation direction and polarization...

Wave-induced fluid flow (WIFF) between cracks and micropores is one of the major mechanisms causing attenuation and dispersion within seismic frequency ranges. Previous non-interaction-approximation (NIA) models often assume that the distribution of cracks is dilute, neglecting the influences of interacting cracks on dispersion and attenuation. To overcome this restriction, we have investigated the interaction between coplanar cracks and their influences on seismic dispersion and attenuation. First, a scattering problem for a longitudinal (P) wave normally impinging on a plane with equally distributed coplanar cracks in a porous medium is solved using an integral transform approach. Then, based on the solution, an effective wavenumber is derived for P-wave propagation in a porous material with coplanar cracks. It is found that the magnitude of dispersion and attenuation can significantly increase when the spacing between adjacent cracks decreases even if the crack density is unchanged. Moreover, frequency-dependent asymptotic behavior of inverse quality factor is also different from that of the NIA models at frequencies lower than the WIFF relaxation frequency. Specifically, the inverse quality factor scales with the square root of the frequency at low frequencies. When the spacing between adjacent cracks is large, an additional frequency-dependent scale occurs at relatively higher frequencies (but still lower than the WIFF relaxation frequency) with inverse quality factor scales with the first power of frequency. When the spacing becomes much larger so that the interaction between the adjacent cracks is negligible, the present model exactly reduces to an NIA model for the distribution of aligned slit cracks and the first power scale can maintain attenuation within low frequencies.

We present adaptive sequential SAA (sample average approximation) algorithms to solve large-scale two-stage stochastic linear programs. The iterative algorithm framework we propose is organized int...

Despite many existing research on data forwarding in low-duty-cycle wireless sensor networks (WSNs), relatively little work has been done on energy-efficient data forwarding with probabilistic delay bounds. Probabilistic delay guarantees ( i.e. , delay bounded data delivery with reliability constraints) are of increasing importance for many delay-constrained applications, since deterministic delay bounds are prohibitively expensive to guarantee in WSNs. However, radio duty-cycling and unreliable wireless links pose challenges for achieving the probabilistic delay guarantee in WSNs. In this paper, we propose EEAF, a novel energy-efficient adaptive forwarding technique tailored for low-duty-cycle WSNs with unreliable wireless links. We show the existence of path diversity in low-duty-cycle WSNs, where delay-optimal routing and energy-optimal routing are likely following different paths. The key idea of EEAF is to exploit the intrinsic path diversity to provide probabilistic delay guarantees while minimizing transmission cost. In EEAF, an early arriving packet will be adaptively switched to the energy-optimal path for energy conservation. Delay quantiles are derived at each node in a distributed manner and are used as the guidelines in the adaptive forwarding decision making. Extensive testbed experiment and large-scale simulation show that EEAF effectively reduces the transmission cost by 12%~25% with probabilistic delay guarantees under various network settings. In addition, we extend the EEAF technique with data aggregation for event-based traffic scenarios. Evaluation using publicly available WSN event traffic traces yields very encouraging results with up to 40% energy saving in probabilistic delay bounded data delivery.

In this paper, we consider service applications where drivers serve subscription customers at their homes on a regular basis and at known times. To build trust with customers, the company requires that subscription customers are consistently served by the same driver. In addition to subscription customers, on-demand customers request delivery on a daily basis. For the company, the challenge is to consistently serve the subscription customers while simultaneously maximizing the daily profit from the on-demand customers. We model the problem as a two-stage stochastic decision problem. The first stage determines the assignment of drivers to subscription customers. The second stage is a team-orienteering problem with time windows and mandatory visits by fixed drivers. We present an anticipatory consistent customer assignment policy (ACCA) based on the multiple scenario approach framework. Our computational study shows that ACCA significantly outperforms consistency concepts from the literature, while increasing costs less than 5%.

SUMMARYUnderstanding the wave propagation in fluid-saturated cracked rocks is important for detecting and characterizing cracked reservoirs and fault zones with applications in geomechanics, hydrogeology, exploration geophysics and reservoir engineering. In sedimentary rocks, microscopic-scale pores are usually filled with fluid. One logical means of modelling the essential features of such rocks is to use poroelasticity theory. But previous models of wave propagation in cracked porous medium are either restricted to low frequencies at which effects of the elastic scattering (scattering into fast-P and S waves via mode conversion at the crack faces) are negligible or to the case that the crack-filling fluid is assumed to be incompressible. To overcome these restrictions, we consider the effects of crack fluid compressibility by extending spring condition into poroelasticity and derive exact solutions of the scattering problem of an incident P wave by a circular crack containing compressible fluid in a porous medium. Based on the solutions, we develop two different effective medium models to estimate frequency-dependent effective velocity and attenuation in a fluid-saturated porous rock with a set of aligned cracks. The mixed-boundary value problem reveals that both the wave-induced fluid flow (WIFF) and elastic wave scattering can cause important velocity dispersion and attenuation. The diffusion-type WIFF dominates the velocity change and attenuation for the low frequency range, while the elastic scattering dominates them for the relatively higher frequency range. The dependences of the P-wave velocity on the crack fluid compressibility are different at different frequencies. For the WIFF-dominated frequency range and Rayleigh-scattering frequency range, the P-wave velocity decreases with the crack fluid compressibility. In contrast, for the Mie scattering frequency range, the opposite occurs (the P-wave velocity increases with the crack fluid compressibility).

Two critical yet frequently conflicting objectives for logistics and transportation service companies are improving customer satisfaction and reducing transportation cost. In particular, given a network of customer requests with preferred service times, it is very challenging to find vehicle routes and service schedules simultaneously that respect all operating constraints and minimize the total transportation and customers’ inconvenience costs. In this paper, we introduce the vehicle routing problem with time windows and convex node costs (VRPTW-CNC), in which we model each customer’s inconvenience cost as a convex function of the service start time at that customer. The VRPTW-CNC combines and extends both the standard vehicle routing problem with time windows and some previous results on the optimal service scheduling problem over a fixed route. We propose a branch-and-cut-and-price algorithm to solve the VRPTW-CNC with general convex inconvenience cost functions. To solve the pricing problem, our labeling algorithm only generates labels that possibly lead to optimal schedule times over a route, which significantly improves the effectiveness of pricing. Extensive computational results demonstrate the effectiveness of our approach.

Hydraulic fractures and preexisting cracks in natural aquifers and hydrocarbon reservoirs are often saturated with fluids. Understanding the elastic wave properties in such a cracked fluid-saturated medium is of importance for many physical and engineering applications such as hydrology, petroleum engineering, oil exploration, induced seismicity, and nuclear waste disposal. In this paper, the scattering of a normally incident longitudinal (P-) wave by a fluid-saturated circular crack in an infinite elastic non-porous matrix is studied. In particular, the mechanism of hydraulic conduction (including the effects of the crack permeability and fluid inertia) inside the crack is incorporated. A semi-analytic solution for this scattering problem is derived. Based on the solution and multiple scattering theorem, an effective medium model is developed to determine the velocity dispersion and attenuation due to wave scattering in an elastic matrix with sparse distribution of aligned cracks. It is shown that the effective P-wave velocity is consistent with Gassmann's theory in the low-frequency limit. The effect of crack permeability on scattering is negligible, but the effect of fluid inertia is important. Specifically, it is found that resonance phenomena can take place inside the cracks at frequencies much lower than the scattering characteristic frequency so that rapid velocity variation can occur at relatively low frequencies. The fluid viscosity plays a damping role in weakening the resonance. The effects of crack thickness and fluid compressibility on scattering dispersion are similar to those in the case of plane-strain (two-dimensional) slit crack.

We consider well-known decomposition techniques for multistage stochastic programming and a new scheme based on normal solutions for stabilizing iterates during the solution process. The given algorithms combine ideas from finite perturbation of convex programs and level bundle methods to regularize the so-called forward step of these decomposition methods. Numerical experiments on a hydrothermal scheduling problem indicate that our algorithms are competitive with the state-of-the-art approaches such as multistage regularized decomposition, nested decomposition and stochastic dual dynamic programming.

Golgi Membrane Protein 1 (GOLM1) has been identified as a prime target for cancer therapy because it overexpresses in many solid tumors, increases tumor growth and metastasis and leads to unfavorable survival. Though various approaches including siRNA interference and antibody targeting have been attempted, GOLM1 has remained an un-targetable molecule because of its mainly intracellular location and the lack of domains that could possibly be interfered with by small molecules. Numerous natural anti-tumoral plant substances have been identified, while their possible function on GOLM1 has never been revealed. This is the first report to study the relationship between GOLM1 downregulation and natural anti-tumoral plant substances and the possible mechanism. Among three tested possible migration-inhibiting natural substances (Epigallocatechin gallate (EGCG), Betulinic acid (BA) and Lupeol), EGCG showed the most potent inhibition effect on GOLM1 expression and MDA-MB-231 cell migration. Knocking down GOLM1 expression further increased the EGCG treatment effect. Molecular docking prediction and following experiments suggested that EGCG may inhibit GOLM1 expression and MDA-MB-231 cells migration through HGF/HGFR/AKT/GSK-3/β-catenin/c-Myc signaling pathway. In all, EGCG is the first identified GOLM1 downregulation natural product. Silencing GOLM1 may be a novel mechanism of potentiated anti-cancer migration effects and cytotoxic effect of EGCG. In addition, this study shed a new way for cancer therapy by combination of GOLM1 silencing and EGCG treatment in the future.

Food insecurity affects approximately 8% of older adults in the U.S. and may be connected to social isolation. This study aimed to understand how loneliness and social support associated with food ...

Surgery scheduling is of critical importance, because an operating room (OR) is the major cost generating unit in the hospital. However, schedulers face tremendous challenges brought by case cancellation, which have been observed in most departments. On the other hand, the randomness of surgery duration also has a significant impact on an OR schedule. In this paper, we develop a stochastic integer programming model for multiple ORs that simultaneously considers the uncertainties of case cancellation and surgery duration. We aim at minimizing the costs from the perspectives of both health care providers and patients. The Benders decomposition is used to address the computational complexity. A series of experiments is conducted to show the effectiveness of the proposed model and solution approaches. A case study based on two departments at West China Hospital is carried out, where the total cost can be reduced by approximately 27%. A sensitivity analysis is conducted in the case study, from which we gain managerial insights. Note to Practitioners —The effectiveness and efficiency of operating room (OR) scheduling are highly valued by hospital practitioners, as the OR department is one of the most resource-intensive units in a hospital. The uncertainty of surgery duration and patient cancellation in OR scheduling brings a tremendous challenges to the decision makers. We propose a stochastic integer programming model by taking these uncertain factors into consideration. The proposed model significantly outperforms the current practice according to our case study. We also conduct a sensitivity analysis to obtain managerial insights. The value of stochastic solutions is calculated to show the importance of considering both the uncertain factors.

Humana, a large health care company, has set a goal of 20% improvement in health in the communities it serves by 2020. The metric chosen for the Bold Goal initiative was the HRQOL-4 version of the Centers for Disease Control and Prevention (CDC) Healthy Days survey. This paper presents the methods for measuring progress, reports results for the first year of tracking, and describes Humana's community-based interventions. Across 7 specially designated “Bold Goal” communities, mean unhealthy days declined from 10.98 in 2015 to 10.64 in 2016, which represented a 3.1% relative, or 0.34 absolute, decline. This compares with a 0.17 absolute unhealthy days decline in Humana's national population overall. The paper also describes how additional work identifying associations between social determinants of health (SDOH) and Healthy Days is influencing Humana's strategy. Lastly, a strategy of community engagement is illustrated through 2 case examples: San Antonio and Knoxville. In the San Antonio area, the community in which Humana has been involved the longest, unhealthy days dropped by 9.0% (−0.95 absolute) from a mean 10.52 to 9.57 unhealthy days. In Knoxville, one of the newer areas of engagement, mean unhealthy days declined by 4.8% (−0.61 absolute), representing declines in both physically and mentally unhealthy days. Overall, results are encouraging, and Humana expects declines to accelerate over time as initiatives are launched and scaled in Bold Goal communities.

We consider a generic maximum flow interdiction problem that involves a leader and a follower who take actions in sequence. Given an interdiction budget, the leader destroys a subset of arcs to minimize the follower’s maximum flows from a source to a sink node. The effect from an interdiction action taken on each arc is random, following a given success rate of decreasing the arc’s capacity to zero. The follower can add additional arc capacities for mitigating flow losses, after knowing the leader’s interdiction plan but before realizing the uncertainty. We consider risk-neutral and risk-averse behaviors of the two players and investigate five bi-level/tri-level programming models for different risk-preference combinations. The models incorporate the expectation, left-tail, and right-tail Conditional Value-at-Risk (CVaR) as commonly used convex risk measures for evaluating random maximum flows in the leader’s and follower’s objectives. We reformulate each model as an equivalent mixed-integer linear program and test them on real-world network instances to demonstrate interactions between the leader and the follower under various risk-preference settings.

We present a computational study of several strategies to solve two-stage stochastic linear programs by integrating the adaptive partition-based approach with level decomposition. A partition-based formulation is a relaxation of the original stochastic program, obtained by aggregating variables and constraints according to a scenario partition. Partition refinements are guided by the optimal second-stage dual vectors computed at certain first-stage solutions. The proposed approaches rely on the level decomposition with on-demand accuracy to dynamically adjust partitions until an optimal solution is found. Numerical experiments on a large set of test problems including instances with up to one hundred thousand scenarios show the effectiveness of the proposed approaches. The online supplement is available at https://doi.org/10.1287/ijoc.2017.0765 .

In this paper, we propose partition-based decomposition algorithms for solving two-stage stochastic integer program with continuous recourse. The partition-based decomposition method enhance the classical decomposition methods (such as Benders decomposition) by utilizing the inexact cuts (coarse cuts) induced by a scenario partition. Coarse cut generation can be much less expensive than the standard Benders cuts, when the partition size is relatively small compared to the total number of scenarios. We conduct an extensive computational study to illustrate the advantage of the proposed partition-based decomposition algorithms compared with the state-of-the-art approaches.

Atmospheric transport of black carbon (BC) from surrounding areas has been shown to impact the Tibetan environment, and clarifying the geographical source and receptor regions is crucial for providing guidance for mitigation actions. In this study, 10 trace volatile organic compounds (VOCs) sampled across Tibet are chosen as proxies to diagnose source regions and related transport of pollutants to Tibet. The levels of these VOCs in Tibet are higher than those in the Arctic and Antarctic regions but much lower than those observed at many remote and background sites in Asia. The highest VOC level is observed in the eastern region, followed by the southern region and the northern region. A positive matrix factorization (PMF) model found that three factors—industry, biomass burning, and traffic—present different spatial distributions, which indicates that different zones of Tibet are influenced by different VOC sources. The average age of the air masses in the northern and eastern regions is estimated to be 3.5 and 2.8 days using the ratio of toluene to benzene, respectively, which indicates the foreign transport of VOC species to those regions. Back-trajectory analyses show that the Afghanistan-Pakistan-Tajikistan region, Indo-Gangetic Plain (IGP), and Meghalaya-Myanmar region could transport industrial VOCs to different zones of Tibet from west to east. The agricultural bases in northern India could transport biomass burning-related VOCs to the middle-northern and eastern zones of Tibet. High traffic along the unique national roads in Tibet is associated with emissions from local sources and neighboring areas. Our study proposes international joint-control efforts and targeted actions to mitigate the climatic changes and effects associated with VOCs in Tibet, which is a climate sensitive region and an important source of global water.

A mathematical formulation is presented for the dynamic stress intensity factor (mode I) of a permeable penny-shaped crack subjected to a time-harmonic propagating longitudinal wave in an infinite poroelastic solid. In particular, the effect of the wave-induced fluid flow on the dynamic stress intensity factor is analyzed. The Hankel integral transform technique in conjunction with Helmholtz potential theory is used to formulate the mixed boundary-value problem as dual integral equations in the frequency domain. Using appropriate transforms, the dual integral equations can be reduced to a Fredholm integral equation of the second kind. The phenomenon of fluid flow along the crack surface has significant influences upon the frequency-dependent behavior of the dynamic stress intensity factor. The stress intensity factor monotonically decreases with increasing frequency, declining the fastest when the crack radius and the slow wave wavelength are of the same order. Such near-field information is of particular importance in predicting the crack strength subjected to oscillating loads. The characteristic frequency at which the stress intensity factor decays the fastest shifts to higher frequency values when the crack radius decreases.

Carbonaceous aerosols significantly affect global radiative forcing and climate through absorption and scattering of sunlight. Black carbon (BC) and brown carbon (BrC) are light-absorbing carbonaceous aerosols. The direct radiative effect (DRE) of BrC is uncertain. A recent study suggests that BrC absorption is comparable to BC in the upper troposphere over biomass burning regions and that the resulting radiative heating tends to stabilize the atmosphere. Yet current climate models do not include proper physical and chemical treatments of BrC. In this study, we derived a BrC global biomass burning emission inventory on the basis of the Global Fire Emissions Database 4 (GFED4), developed a BrC module in the Community Atmosphere Model version 5 (CAM5) of Community Earth System Model (CESM) model, and investigated the photo-bleaching effect and convective transport of BrC on the basis of Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry Project (DC-3) measurements. The model simulations of BC were also evaluated using HIAPER (High-Performance Instrumented Airborne Platform for Environmental Research) Pole-to-Pole Observations (HIPPO) measurements. We found that globally BrC is a significant absorber, the DRE of which is 0.10 W/m2, more than 25 % of BC DRE (+0.39 W/m2). Most significantly, model results indicated that BrC atmospheric heating in the tropical mid and upper troposphere is larger than that of BC. The source of tropical BrC is mainly from wildfires, which are more prevalent in the tropical regions than higher latitudes and release much more BrC relative to BC than industrial sources. While BC atmospheric heating is skewed towards northern mid-latitude lower atmosphere, BrC heating is more centered in the tropical free troposphere. The contribution of BrC heating to the Hadley circulation and latitudinal expansion of the tropics is comparable to BC heating.

A mathematical formulation is presented for the dynamic stress intensity factor (mode I) of a finite permeable crack subjected to a time-harmonic propagating longitudinal wave in an infinite poroelastic solid. In particular, the effect of the wave-induced fluid flow due to the presence of a liquid-saturated crack on the dynamic stress intensity factor is analyzed. Fourier sine and cosine integral transforms in conjunction with Helmholtz potential theory are used to formulate the mixed boundary-value problem as dual integral equations in the frequency domain. The dual integral equations are reduced to a Fredholm integral equation of the second kind. It is found that the stress intensity factor monotonically decreases with increasing frequency, decreasing the fastest when the crack width and the slow wave wavelength are of the same order. The characteristic frequency at which the stress intensity factor decays the fastest shifts to higher frequency values when the crack width decreases.

The pollution-routing problem (PRP) aims to determine a set of routes and speed over each leg of the routes simultaneously to minimize the total operational and environmental costs. A common approach to solve the PRP exactly is through speed discretization, i.e., assuming that speed over each arc is chosen from a prescribed set of values. In this paper, we keep speed as a continuous decision variable within an interval and propose new formulations for the PRP. In particular, we build two mixed-integer convex optimization models for the PRP, by employing tools from disjunctive convex programming. These are the first arc-based formulations for the PRP with continuous speed. We also derive several families of valid inequalities to further strengthen both models. We test the proposed formulations on benchmark instances. Some instances are solved to optimality for the first time.

The quasi-static theory of poroelasticity presented by Biot and Gassmann provides a relationship between the drained and undrained elastic constants of an isotropic fluid-saturated porous material in terms of the porosity of the material, bulk modulus of the solid grains, and bulk modulus of the pore fluid. We have developed an alternative approach to derive the Biot-Gassmann (BG) relationship while including the effects of the pore microstructure. First, the Eshelby transformation is used to express the local inclusion/pore strain tensor in terms of the applied strain tensor and reference material elastic properties by the superposition of a void strain and a perturbation term due to induced inclusion stress. Second, the inclusion strain expression and Hill’s average principles are combined with the Mori-Tanaka/Kuster-Toksöz scheme to obtain inclusion-stress-dependent effective elastic moduli of porous materials. For an isolated pore system, the effective modulus tensor corresponds to the original Mori-Tanaka/Kuster-Toksöz’s expression. Although for communicating pore system, it is proven to satisfy the BG relation. In the second case, the deformation is assumed to occur so slowly that the infiltrating fluid mass has sufficient time to diffuse between material elements and, consequently, the pore fluid pressure is equilibrated within the whole pore system. It is noteworthy that we arrive at a BG relationship without applying reciprocity theorem and that the porous material effective strain is defined from Hill’s principles instead of solid phase average strain. A potential application of the stress-independent effective modulus is to help develop a dynamical modulus model of rock physics for a specific pore microstructure.

We consider a Stackelberg game in a network where a leader minimizes the cost of interdicting arcs and a follower seeks the shortest distance between given origin and destination nodes under uncertain arc traveling cost. In particular, we consider a risk-averse leader, who aims to keep high probability that the follower’s traveling distance is longer than a given threshold, interpreted by a chance constraint. Under the assumption of a wait-and-see follower—i.e., the follower selects a shortest path after seeing realizations of the random arc cost—we propose a branch-and-cut algorithm and apply lifting techniques to exploit the combinatorial structure of the risk-averse leader’s interdiction problem. We demonstrate the computational efficacy of our approaches, risk-averse interdiction solution patterns, and result sensitivity, by testing instances of randomly generated grid networks and real-world transportation networks.

Grain-scale local fluid flow is an important loss mechanism for attenuating waves in cracked fluid-saturated poroelastic rocks. In this study, a dynamic elastic modulus model is developed to quantify local flow effect on wave attenuation and velocity dispersion in porous isotropic rocks. The Eshelby transform technique, inclusion-based effective medium model (the Mori–Tanaka scheme), fluid dynamics and mass conservation principle are combined to analyze pore-fluid pressure relaxation and its influences on overall elastic properties. The derivation gives fully analytic, frequency-dependent effective bulk and shear moduli of a fluid-saturated porous rock. It is shown that the derived bulk and shear moduli rigorously satisfy the Biot-Gassmann relationship of poroelasticity in the low-frequency limit, while they are consistent with isolated-pore effective medium theory in the high-frequency limit. In particular, a simplified model is proposed to quantify the squirt-flow dispersion for frequencies lower than stiff-pore relaxation frequency. The main advantage of the proposed model over previous models is its ability to predict the dispersion due to squirt flow between pores and cracks with distributed aspect ratio instead of flow in a simply conceptual double-porosity structure. Independent input parameters include pore aspect ratio distribution, fluid bulk modulus and viscosity, and bulk and shear moduli of the solid grain. Physical assumptions made in this model include (1) pores are inter-connected and (2) crack thickness is smaller than the viscous skin depth. This study is restricted to linear elastic, well-consolidated granular rocks.

We propose two new Lagrangian dual problems for chance-constrained stochastic programs based on relaxing nonanticipativity constraints. We compare the strength of the proposed dual bounds and demonstrate that they are superior to the bound obtained from the continuous relaxation of a standard mixed-integer programming (MIP) formulation. For a given dual solution, the associated Lagrangian relaxation bounds can be calculated by solving a set of single scenario subproblems and then solving a single knapsack problem. We also derive two new primal MIP formulations and demonstrate that for chance-constrained linear programs, the continuous relaxations of these formulations yield bounds equal to the proposed dual bounds. We propose a new heuristic method and two new exact algorithms based on these duals and formulations. The first exact algorithm applies to chance-constrained binary programs, and uses either of the proposed dual bounds in concert with cuts that eliminate solutions found by the subproblems. The second exact method is a branch-and-cut algorithm for solving either of the primal formulations. Our computational results indicate that the proposed dual bounds and heuristic solutions can be obtained efficiently, and the gaps between the best dual bounds and the heuristic solutions are small.

An exact analytical solution is presented for the effective dynamic shear modulus in a heterogeneous fluid-filled poroelastic medium containing spherical inclusions. The complex and frequency-dependent properties of the derived shear modulus are solely caused by the physical mechanism of mesoscopic-scale wave-induced fluid flow whose scale is assumed to be smaller than wavelength but larger than the size of pores. Our model consists of three phases: a spherical inclusion, a shell of matrix material with different mechanical and/or hydraulic properties and an outer region of effective homogeneous medium of infinite extent. This three-phase model represents a self-consistent model or an approximate model of composite having periodically distributed inclusions. The behaviors of both the inclusion and the matrix are described by Biot's equations (1941) with standard conditions of Deresiewicz and Skalak (1963) at the inclusion-matrix interface. The effective medium is regarded as an equivalent elastic or viscoelastic material with complex and frequency-dependent moduli to be determined. The derived effective shear modulus is used to quantify the shear-wave attenuation and velocity dispersion. For the problem of fluid patchy saturation (inclusions with the same solid frame as the matrix but with a different pore fluid from that in the matrix), the gas pocket does not affect the shear attenuation and dispersion characteristic of the water-filled matrix medium at all. For the problem of double porosity structure (inclusions having a different solid frame than the matrix but the same pore fluid as the matrix), with the increase of frequency the heterogeneous medium transitions from a low-frequency state having drained inclusions and drained matrix with no pore pressure difference to a higher-frequency state having undrained inclusions and undrained matrix with no fluid communication at the inclusion's surface. The relaxation frequency at which the maximum value of inverse quality factor occurs moves to frequencies by two orders of magnitude lower if the size of a unit cell increases by one order of magnitude. Stiff inclusions imbedded in a relatively soft matrix can cause significant and observable attenuation at seismic frequency bands, but softer inclusions imbedded in a relatively stiff matrix cause very weak attenuation. The mixed heterogeneity in both the solid frame and pore fluid also has important influences on the frequency-dependent shear wave attenuation.

Faced with a sentence like Every horse didn't jump over the fence as a description of a scenario in which one out of two horses jumped, adults readily endorse the utterance as a good description, while children overwhelmingly reject it. However, systematic changes to the task setup lead to marked increases in chil dren's endorsement rates (Musolino & Lidz 2006; Viau et al. 2010). Savinelli et al. (2017) use a computational cognitive model of utterance endorsement in truth- value judgment tasks to analytically demonstrate that both children and adults' interpretation behavior is affected by pragmatic manipulations. We test a clear pre diction of these models: manipulating the conversational goal (or Question Under Discussion) should lead to clear effects on utterance endorsement. In addition to investigating the predictions for English, we also investigate Spanish and Mandarin, where the status of the relevant ambiguity may be less clear.

It is well known that mesoscopic-scale wave-induced fluid flow (WIFF) between cracks and surrounding porous matrix is one of significant mechanisms in causing seismic dispersion and attenuation. Previous theoretical models that were used to interpret the interaction between cracks and passing waves assumed the cracks to be circular or slit-like. However, in many actual cases, the cracks can have a shape more close to a rectangle. In this paper, we develop an effective medium model to estimate the P-wave attenuation and velocity dispersion in a saturated porous rock containing a random distribution of permeable, aligned, rectangular cracks of infinitesimal thickness. This is done by combining the far-field displacement representation of the solution of a normally incident P wave scattered by a single crack and Foldy's scattering theorem. The effective low-frequency P-wave velocity predicted by the present model is asymptotically consistent with the Gassmann's theory. It is shown that thorough knowledge of the crack shape is important for understanding seismic signatures. Specifically, the WIFF relaxation frequency is mainly determined by the crack intermediate dimension, while it is insensitive to the crack largest dimension. Moreover, P-wave velocity of the rectangular crack model can be quite different from those of the circular crack model and the slit crack model, although the overall frequency-dependent trends of the velocities for different models are very similar. Analogously to the circular crack model and the slit crack model, at the normal incidence of a fast-P wave, the WIFF is found to dominate the wave attenuation and velocity dispersion. These results are helpful to estimate formation parameters from different frequency components of observed seismic data.

The dynamic (frequency-dependent) mode-I stress intensity factor (SIF) is obtained for a porous medium containing an array of equally distributed collinear cracks. Unlike previous work in which the cracks are assumed to be dry and impermeable, this paper studies the case that the crack is fluid-saturated and permeable. The cracks are under the action of a normal incidence of a time-harmonic plane longitudinal (P) wave. The interaction between the collinear cracks and the mechanism of wave-induced fluid flow (scattered slow P wave) can significantly affect the magnitude and frequency-dependent trend of the SIF, in particular at low frequencies. At low frequencies, the magnitude of the SIF increases monotonously with the decreasing distance between the adjacent cracks and can be much larger than that of a single crack, implying that the material strength can be greatly lowered by the interaction of cracks. However, at higher frequencies, the impacts of interacting cracks are negligible. The comparison with the counterpart of dry impermeable cracks reveals that the magnitude of SIF is lower than that of dry impermeable cracks owing to effective normal stress effect. Moreover, unlike the SIF of dry impermeable cracks for which a peak value is observed around elastic wave resonance frequency, the corresponding SIF of fluid-saturated permeable cracks monotonously decreases with the increasing frequency. This frequency-dependent trend is attributed to the conversion of incident energy into the slow P wave. The obtained results reveal significant influences of the presence of pore fluid and interaction of collinear cracks upon the SIF, both magnitudes and frequency-dependent trends. Such information is useful in predicting the fracture strength of saturated porous materials subjected to oscillating loads.

The multi-vehicle covering tour problem with time windows (MCTPTW) aims to construct a set of maximal coverage routes for a fleet of vehicles that serve (observe) a secondary set of sites given a fixed time schedule, coverage requirements, and energy restrictions. The problem is formulated as a mixed-integer second-order cone programming (MISOCP) model and is an extension of both the multi-covering tour problem and the vehicle routing problem with time windows under energy constraints. Further, we study a special case of the proposed model and develop a labeling algorithm to solve its Lagrangian relaxation problem, which exploits the combinatorial structure exhibited by an optimal solution to the Lagrangian relaxation., Comment: 37 pages, 7 figures, 6 tables

Crustal rocks are commonly permeated by aligned fractures which may control the wave anisotropy and permeability pattern. In the presence of pore fluid the mechanical and hydraulic features of such rocks become more complex. Understanding the dynamic anisotropy in fluid-saturated fractured rocks is important for detecting and characterizing fractured reservoirs and fault zones with applications in geomechanics, hydrogeology, exploration geophysics and reservoir engineering. For waves propagating normal to the fractures, the effects of wave-induced fluid flow (WIFF) due to the presence of permeable fractures on seismic dispersion and attenuation are significant and have been quantified in earlier studies. But previous literatures are restricted to low frequency range within which the fracture size is much smaller than the incident wavelength. In this paper, we extend low-frequency normal incidence results to full-frequency oblique incidence. We first derive exact solutions of the scattering problem of obliquely incident plane waves by a single slit fracture in a poroelastic solid. Based on previous analysis, for ideal fractures with infinitesimal thickness, the fracture fluid can be modelled as an incompressible one. Then, based on the solutions and Foldy's scattering theorem we develop a dynamic-effective-medium model to estimate frequency-dependent anisotropy of wave propagation in a fluid-saturated poroelastic rock with a sparse set of aligned fractures. We find that for the oblique incidence problem apart from WIFF there exist another two important attenuation mechanisms, i.e., the elastic scattering (scattering into fast P and S waves via mode conversion at the fracture faces) and Biot's global flow, in causing velocity dispersion and attenuation. The mixed-boundary problem reveals that the WIFF is controlled by the normal displacement discontinuity that is determined by effective normal stress applied on the fracture faces, while the scattering effects by the tangential displacement discontinuity that is determined by effective shear stress. Because the effective normal and shear stresses depends on incident angles and frequency, the dispersion and attenuation of both P and S waves are anisotropic and frequency-dependent. In contrast, Biot's global flow is an intrinsic energy loss mechanism that can play a role in causing velocity dispersion and attenuation at higher frequency range but it is independent of the presence of fractures or incident angle.

We study a variant of the capacitated vehicle routing problem where the cost over each arc is defined as the product of the arc length and the weight of the vehicle when it traverses that arc. We propose two new mixed-integer linear programming formulations for the problem: an arc-load formulation and a set partitioning formulation based on q-routes with additional constraints. A family of cycle elimination constraints are derived for the arc-load formulation. We then compare the linear programming (LP) relaxations of these formulations with the two-index one-commodity flow formulation proposed in the literature. In particular, we show that the arc-load formulation with the new cycle elimination constraints gives the same LP bound as the set partitioning formulation based on 2-cycle-free q-routes, which is stronger than the LP bound given by the two-index one-commodity flow formulation. We propose a branch-and-cut algorithm for the arc-load formulation, and a branch-cut-and-price algorithm for the set partitioning formulation strengthened by additional constraints. Computational results on instances from the literature demonstrate that a significant improvement can be achieved by the branch-cut-and-price algorithm over other methods.

We consider a reliable network design problem under uncertain edge failures. Our goal is to select a minimum-cost subset of edges in the network to connect multiple terminals together with high probability. This problem can be seen as a stochastic variant of the Steiner tree problem. We propose two scenario-based Steiner cut formulations, study the strength of the proposed valid inequalities, and develop a branch-and-cut solution method. We also propose an LP-based separation for the scenario-based directed Steiner cut inequalities using Benders feasibility cuts, leveraging the success of the directed Steiner cuts for the deterministic Steiner tree problem. In our computational study, we test our branch-and-cut method on instances adapted from graphs in SteinLib Testdata Library with up to 100 nodes, 200 edges, and 17 terminals. The performance of our branch-and-cut method demonstrates the strength of the scenario-based formulations and the benefit from adding the additional valid inequalities that we propose. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 321–334, 2015