First Set Of Models Research Articles

Predictors of concerned others' mental health and quality of life over 12 months following adults' entry into treatment for an alcohol use disorder

IntroductionPeople in treatment for alcohol use disorders (AUDs) can negatively impact their Concerned Others (COs). This longitudinal study examined patient and CO characteristics associated with CO outcomes. MethodParticipants were 279 dyads of patients entering residential treatment and their CO. Outcomes were COs' mental health and quality of life. The study collected patient and CO predictors and CO outcomes at baseline and 3-, 6-, and 12-month follow-ups as part of a randomized controlled trial. In the first set of models, the analytic approach identified baseline patient predictors associated with COs' outcomes measured at baseline and follow-ups. In the second set of models, we examined whether those effects remained after adding baseline CO characteristics. ResultsIn the first set of models, COs of older age and whose patient reported less CO-patient relationship stress had better mental health. Also, married COs and those with higher income and whose patient reported no violence in the CO-patient relationship had better quality of life. In the second set of models, COs whose patient entered treatment due to criminal justice involvement, with more social support, less reported stigma, and less use of avoidance coping had better mental health. Also, married COs, those with higher income, and less reported discrimination stigma had better quality of life. ConclusionsUnderstanding patient and CO characteristics that are associated with COs' outcomes may inform AUD treatment programs' efforts to help COs. Identifying modifiable determinants of CO outcomes is important to clinical practice regardless of whether the patient chooses to obtain treatment.

Assessing the Accuracy of 2‐D Planetary Evolution Models Against the 3‐D Sphere

AbstractRegardless of the steady increase of computing power during the last decades, numerical models in a 3D spherical shell are only used in specific setups to investigate the thermochemical convection in planetary interiors, while 2D geometries are typically favored in most exploratory studies involving a broad range of parameters. The 2D cylindrical and the more recent 2D spherical annulus geometries are predominantly used in this context, but the extent to how well they reproduce the 3D spherical shell results in comparison to each other and in which setup has not yet been extensively investigated. Here we performed a thorough and systematic study in order to assess which 2D geometry reproduces best the 3D spherical shell. In a first set of models, we investigated the effects of the geometry on thermal convection in steady‐state setups while varying a broad range of parameters. Additional thermal evolution models of three terrestrial bodies, namely Mercury, the Moon, and Mars, which have different interior structures, were used to compare the 2D and 3D geometries. Our investigations show that the 2D spherical annulus geometry provides results closer to models in a 3D spherical shell compared to the 2D cylindrical geometry. Our study indicates where acceptable differences can be expected when using a 2D instead of a 3D geometry and where to be cautious when interpreting the results.

Coastal forecast through coupling of Artificial Intelligence and hydro-morphodynamical modelling

ABSTRACT As climate-driven risks for the world’s coastlines increase, understanding and predicting morphological changes as well as developing efficient systems for coastal forecast has become of the foremost importance for adaptation to climate change. Artificial Intelligence is a powerful technology that has been rapidly evolving recently and can offer new means of analysis for the coastal science field. Yet, the potential of these technologies for coastal geomorphology remains relatively unexplored with respect to other scientific fields. This article investigates the use of Artificial Neural Networks and Bayesian Networks in combination with fully coupled hydrodynamics and morphological models (Delft3D) for predicting morphological changes and sediment transport along coastal systems. Two sets of Artificial Intelligence models were tested, one set relying on localized modeling outputs or localized data sources and another set having reduced dependency from modeling outputs and, once trained, solely relying on boundary conditions and coastline geometry. The first set of models provides regression values greater than 0.95 and 0.86 for training and testing, respectively. The second set of reduced dependency models provides regression values greater than 0.84 and 0.76 for training and testing, respectively. Our results highlight the potential of AI and statistical models for coastal applications.

Evaluation of the accuracy of the IDvet serological test for Mycoplasma bovis infection in cattle using latent class analysis of paired serum ELISA and quantitative real-time PCR on tonsillar swabs sampled at slaughter.

Mycoplasma bovis (Mbovis) was first detected in cattle in New Zealand (NZ) in July 2017. To prevent further spread, NZ launched a world-first National Eradication Programme in May 2018. Existing diagnostic tests for Mbovis have been applied in countries where Mbovis is endemic, for detecting infection following outbreaks of clinical disease. Diagnostic test evaluation (DTE) under NZ conditions was thus required to inform the Programme. We used Bayesian Latent Class Analysis on paired serum ELISA (ID Screen Mycoplasma bovis Indirect from IDvet) and tonsillar swabs (qPCR) for DTE in the absence of a gold standard. Tested samples were collected at slaughter between June 2018 and November 2019, from infected herds depopulated by the Programme. A first set of models evaluated the detection of active infection, i.e. the presence of Mbovis in the host. At a modified serology positivity threshold of SP%> = 90, estimates of animal-level ELISA sensitivity was 72.8% (95% credible interval 68.5%-77.4%), respectively 97.7% (95% credible interval 97.3%-98.1%) for specificity, while the qPCR sensitivity was 45.2% (95% credible interval 41.0%-49.8%), respectively 99.6% (95% credible interval 99.4%-99.8%) for specificity. In a second set of models, prior information about ELISA specificity was obtained from the National Beef Cattle Surveillance Programme, a population theoretically free-or very low prevalence-of Mbovis. These analyses aimed to evaluate the accuracy of the ELISA test targeting prior exposure to Mbovis, rather than active infection. The specificity of the ELISA for detecting exposure to Mbovis was 99.9% (95% credible interval 99.7%-100.0%), hence near perfect at the threshold SP%=90. This specificity estimate, considerably higher than in the first set of models, was equivalent to the manufacturer's estimate. The corresponding ELISA sensitivity estimate was 66.0% (95% credible interval 62.7%-70.7%). These results confirm that the IDvet ELISA test is an appropriate tool for determining exposure and infection status of herds, both to delimit and confirm the absence of Mbovis.

Contribution of gut bacteria to arsenic metabolism in the first year of life in a prospective birth cohort

Gut bacteria are at the interface of environmental exposures and their impact on human systems, and may alter host absorption, metabolism, and excretion of toxic chemicals. We investigated whether arsenic-metabolizing bacterial gene pathways related to urinary arsenic concentrations. In the New Hampshire Birth Cohort Study, urine and stool samples were obtained at six weeks (n = 186) and one year (n = 190) of age. Inorganic arsenic (iAs), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), and arsenobetaine (AsB) were quantified in infant urine samples using high-performance liquid chromatography with inductively coupled plasma mass spectrometry. Total arsenic exposure (tAs) was summarized as Σ(iAs, MMA, DMA) and log2-transformed. Fecal microbial DNA underwent metagenomic sequencing and the relative abundance of bacterial gene pathways were grouped as KEGG Orthologies (KOs) using BioBakery algorithms. Arsenic metabolism KOs with >80% prevalence were log2-transformed and modeled continuously using linear regression, those with <10% were not evaluated and those with 10–80% prevalence were analyzed dichotomously (detect/non-detect) using logistic regression. In the first set of models, tAs was regressed against KO relative abundance or detection adjusting for age at sample collection and child's sex. Effect modification by delivery mode was assessed in stratified models. In the second set of models, the association between the relative abundance/detection of the KOs and arsenic speciation (%iAs, %MMA, %DMA) was quantified with linear regression. Urinary tAs was associated with the increased relative abundance/detection odds of several arsenic-related KOs, including K16509, an arsenate reductase transcriptional regulator, with stronger associations among six-week-olds than one-year-olds. K16509 was also associated with decreased %MMA and increased %DMA at six weeks and one year. Notably, many associations were stronger among operatively-delivered than vaginally-delivered infants. Our findings suggest associations between arsenic-metabolizing bacteria in the infant gut microbiome and urinary arsenic excretion.

ENERGY DISSIPATION AND DUCTILITY OF STEEL PLATE SHEAR WALL WITH PERFORATION

Steel plate shear wall (SPSW) is known as an effective structural system in high rise building that provides lateral resistance against wind or earthquake. SPSW sometimes, needs to be perforated to provide access for human which may reduce the capability of SPSW in resisting the lateral load. This study investigated the effect of size and location of perforation to the lateral resistance of SPSW. This study was done numerically by varying the sizes and locations of perforation in the SPSW, while monitoring the horizontal displacement of the top side of SPSW. The first set of models had perforation of 1.2 m wide and 2 m high being placed at different location in the SPSW models, while the second set of models had varying sizes of perforation at the centre of the SPSWs. Both sets of the SPSWs were 4 m high with two different widths, which were 4 m and 6 m. Cyclic loadings were applied laterally for each SPSW model as according to ATC24 and the displacements at the top side of the SPSW model was obtained from the analysis. Hysteretic curves of all models were plotted to obtain the energy dissipation, lateral load capacity and ductility. It is found that perforation that is located nearest to the edge of the SPSW lowers the energy dissipation, ductility and lateral load capacity the most. Larger size of perforation of the SPSW caused larger reduction of the energy dissipation, ductility and lateral load capacity, while wider SPSW have larger values of energy dissipation, ductility and lateral load capacity.

Minimal conceptual models for tropical cyclone intensification

We examine a hierarchy of minimal conceptual models for tropical cyclone intensification. These models are framed mostly in terms of axisymmetric balance dynamics. In the first set of models, the heating rate is prescribed in such a way to mimic a deep overturning circulation with convergence in the lower troposphere and divergence in the upper troposphere, characteristic of a region of deep moist convection. In the second set, the heating rate is related explicitly to the latent heat release of ascending air parcels. The release of latent heat markedly reduces the local static stability of ascending air, raising two possibilities in the balance framework. The first possibility is that the effective static stability and the related discriminant in the Eliassen equation for the overturning circulation in saturated air, although small, remains positive so the Eliassen equation is globally elliptic. The second possibility, the more likely one during vortex intensification, is that the effective static stability in saturated air is negative and the Eliassen equation becomes locally hyperbolic. These models help to understand the differences between the early Ooyama models of 1968 and 1969, the Emanuel, 1989 model, and the later Emanuel models of 1995, 1997 and 2012. They provide insight also into the popular explanation of the WISHE feedback mechanism for tropical cyclone intensification. Some implications for recent work are discussed.

Development of nonlinear Reynolds average turbulent [formula omitted] models

Reynolds Average Navier Stokes (RANS) models are among the most employed models to solve turbulent flows, due to their low computational cost. The majority of RANS models use the Boussinesq approximation, based on a linear relation between the deviatoric part of Reynolds stress tensor and the rate of strain tensor, with the turbulent viscosity as the positive proportionality parameter. However, these models fail in several situations, and a great deal of effort has been made by the scientific community aiming to improve models prediction through the development of nonlinear models. Analysis of higher-order models employing objective orthogonal tensors has shown to be very promising to improve the prediction of the normal components of the Reynolds stress. In this work, nonlinear models based on combinations of the square of the rate-strain tensor and non-persistence tensor are examined for a range of friction Reynolds number from 395 to 5200. Two sets of models employing different tensor basis are proposed, both employing the turbulent kinetic energy as the turbulent characteristic velocity. With respect to the turbulent characteristic length, the first set of models employs the dissipation rate of the turbulent kinetic energy, while the second set employs the intensity of the rate of strain tensor. The models prediction for a channel flow are compared with DNS data. As expected, the nonlinear models present a better adherence to the DNS data. In addition, the new approach with the norm of the deformation replacing the dissipation of turbulent kinetic energy lead to more accurate predictions with respect to the DNS.

Thermal Effects on the Bearing and Ductility of Tubular Reduced Beam Section Connection: Numerical Investigation

In the present paper, an innovative fire-earthquake resistant joint called high-performance tube (HP-T) connection is presented and numerically validated. This HP-T connection improves the axial and rotational ductility as well as prevents brittle failure. Two series of models were simulated in ABAQUS software. In the first set of models, which was designed for heat simulation, a sequentially coupled thermal-stress analysis was performed to investigate the effects of different parameters such as web and flange tube thickness and the ratio of the applied load. To simulate the fire damage, two probable scenarios were considered: bottom flange tube damage and beam web damage when exposed to combined initial loading and fire. In the second set of models for seismic simulation, the failure mode, hysteretic curves, and strain distribution were analyzed. According to the results, HP-T robust connection not only provides appropriate ductility enhancement in force-variable fire conditions but also withstands at least 8% inter-story drift without considerable strength reduction.

MRI markers of accelerated brain aging and misappraisal of sleep depth

AbstractBackgroundSlow‐wave sleep (SWS) is the deepest sleep stage, and has been linked to many important physiological functions, including the cerebral metabolic clearance of toxins associated with Alzheimer’s disease. SWS loss might correlate with accelerated brain aging. However, older individuals and people with cognitive impairment have an impaired ability to appraise their sleep, suggesting that accelerated brain aging might affect how sleep depth is perceived. The purpose of this study was to evaluate whether misappraisal of sleep depth was associated with MRI markers of accelerated brain aging.MethodWe studied 242 participants (mean: 62.0±8.7 years) participants in the Framingham Heart Study Offspring Cohort that were evaluated with an overnight in‐home polysomnography and an MRI 3.4 years later on average. Self‐reported sleep depth (whether sleep was light or deep) on the night of the polysomnography was compared to objective SWS (percent of total sleep spent in SWS, separated by the median). Four groups were created: 36% of the sample had consistent appraisal of deep sleep; 12% of the sample had consistent appraisal of light sleep; 36% misappraised their light sleep as deep; and 16% misappraised their deep sleep as light. We evaluated total brain volume, cortical gray matter volume, and subcortical gray matter volume on MRI. A first set of models were adjusted for age, sex, time between MRI and neuropsychology; a second set of models were additionally adjusted for APOE4 allele status, body mass index, sleeping pills, depression, and stroke risk.ResultParticipants who misappraised light sleep, i.e., reported deep sleep but had lower SWS, had lower cortical gray matter volume (model 1: β±SE=‐0.62±0.26, p=0.018; model 2: ‐0.56±0.27, p=0.036) compared to those that reported deep sleep with higher SWS. We also observed a trend for lower subcortical gray matter volume in the same group (model 1:β±SE=‐0.09±0.05, p=0.084). No other between‐group differences were observed.ConclusionParticipants with lower SWS that reported their sleep as deep displayed lower cortical volume. Accelerated brain aging might affect the ability to appropriately perceived sleep depth, which could be occurring in preclinical stages of dementia. Relying on self‐report sleep depth may introduce systematic misclassification.

Numerical modelling of blast-induced crack propagation in pre-fractured rock

This paper presents a series of numerical simulations to investigate blast-induced crack propagation in rock specimens embedded with a pre-existing fracture. The simulation is conducted using the particle-based discrete element method, which can effectively capture many important geomechanical processes such as solid vibration, crack growth and fracture sliding. Particles are assembled based on the grain size distribution of Beishan granite using a Voronoi tessellation algorithm, with the parameters of particle contacts calibrated against to the laboratory testing results. The pre-existing fracture is represented using the model of smooth-joint contacts. In this study, three sets of models are established to explore the effects of stress state, fracture length and fracture orientation on the damage evolution in the rock specimen subject to a blast load. In the first set of models, we observe that when the horizontal stress σx is not equal to the vertical stress σy , the maximum slip of the pre-existing fracture is positively correlated with the differential stress, i.e. Δσ= σx − σy, which further leads to the generation of different numbers of secondary cracks. The second set of models shows that the number of secondary fractures grows as a quadratic power function with the increased length of the pre-existing fracture. Furthermore, extensive tensile stress regions emerge around the tips of secondary fractures. The third set of models focuses on the sensitivity analysis of fracture orientation, showing that with the clockwise rotation of the pre-existing fracture from the vertical direction, the number of secondary fractures decreases significantly but they are still concentrated locally at the tips of the pre-existing fracture. The research findings of our paper have important implications for the assessment of excavation damaged zone properties around nuclear waste repositories built using the drilling and blasting method.

Does tree canopy moderate the association between neighborhood walkability and street crime?

Creating walkable places and increasing urban vegetation in neighborhoods have emerged as important planning strategies to promote health, social, and environmental benefits. Although past studies have found that walkability and tree canopy are associated with crime, little research has comprehensively examined how neighborhood walkability and tree canopy are associated with street crime. The current study fills this gap by analyzing the relationship among walkable access to amenities measured by Walk Score, urban tree canopy, and the five-year violent and property street crime rates (2014–2018) across an entire city. This study used the case of Austin, Texas to investigate the association exists between 1) neighborhood walkability and street crime and 2) tree canopy and street crime. We also assessed whether the association between neighborhood walkability and street crime was moderated by tree canopy. The first set of models based on a negative binomial regression showed that neighborhood walkability was positively associated with both violent and property street crime rates while tree canopy was inversely associated with violent and property street crime rates. The second set of models revealed a nonlinear relationship between neighborhood walkability and the street crime rate. The final set of models showed that tree canopy cover can moderate the relationship between street crime and neighborhood walkability, suggesting that tree canopy can somewhat offset the negative influence of walkable neighborhoods, such as crowdedness and noise, in relation to street crime. The findings have implications for developing evidence-based planning, design, and policy strategies to create livable streets and prevent street crime by planting more trees in walking-friendly environments.

MP16-06 A NOVEL NOMOGRAM TO PREDICT BCG RESPONSE IN PATIENTS WITH HIGH-GRADE NON-MUSCLE INVASIVE BLADDER CANCER

You have accessJournal of UrologyBladder Cancer: Non-invasive II (MP16)1 Sep 2021MP16-06 A NOVEL NOMOGRAM TO PREDICT BCG RESPONSE IN PATIENTS WITH HIGH-GRADE NON-MUSCLE INVASIVE BLADDER CANCER Kelly Bree, Patrick Hensley, Nathan Brooks, Lianchun Xiao, Yu Shen, Neema Navai, H. Barton Grossman, Colin Dinney, and Ashish Kamat Kelly BreeKelly Bree More articles by this author , Patrick HensleyPatrick Hensley More articles by this author , Nathan BrooksNathan Brooks More articles by this author , Lianchun XiaoLianchun Xiao More articles by this author , Yu ShenYu Shen More articles by this author , Neema NavaiNeema Navai More articles by this author , H. Barton GrossmanH. Barton Grossman More articles by this author , Colin DinneyColin Dinney More articles by this author , and Ashish KamatAshish Kamat More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002001.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Current risk tables for outcome prediction in patients with non-muscle invasive bladder cancer (NMIBC) are based upon studies comprised primarily of low-grade tumors. We developed nomograms that predict disease recurrence and progression in patients with high-grade NMIBC using a large institutional dataset. METHODS: The log rank test, univariate and multivariate Cox proportional hazards regression models were used to identify risk factors of histologically confirmed disease recurrence and progression using data on 519 patients treated with adequate induction bacillus Calmette-Guerin (BCG) at our institution from 2000 to 2018. The first set of models predicted bladder cancer recurrence free survival (RFS), and the second set predicted tumor progression (any upstaging) free survival (PFS). RESULTS: At an estimated median follow-up time was 60.4 months (95% CI: 54-66.2), recurrence or death, whichever occurred first was recorded in 248 patients (47.8%) with a median RFS time of 73 months (95% CI, 52.6-91.2). Recurrent tumors (HR 1.78, 95% CI 1.33-2.33, p<0.0001), larger tumor size (HR 1.07, 95% CI 1.00-1.15, p=0.0487), and diabetes mellitus (HR 1.57, 95% CI 1.14-2.15, p=0.0055) were significantly associated with a higher risk of recurrence or death. Conversely, the receipt of maintenance BCG (mBCG) (HR 0.46, 95% CI 0.29-0.73, p=0.0008) and number of doses of mBCG (HR 0.92, 95% CI 0.89-0.94, p<0.0001) were associated with lower risk of events. Progression or death occurred in 128 patients (24.7%) with a median PFS time of 151 months (95% CI, 121.32-NA). Prior BCG (HR 2.19, 95% CI 1.23-3.88, p=0.0075) and older age (HR 1.041, 95% CI 1.02-1.06, p<0.001) were associated with higher risk of progression or death, while BMI≥25 (HR 0.519, 95% CI 0.35-0.78, p=0.0015) and number of doses of mBCG (HR 0.88, 95% CI 0.86-0.91, p<0.0001) were associated with lower risk of progression or death. These prognostic factors were integrated to construct nomograms for prediction of PFS and RFS. CONCLUSIONS: These nomograms provide personalized prediction of recurrence and progression in patients with high-grade NMIBC treated with BCG, and may help identify patients who may benefit most from early radical cystectomy. Source of Funding: This research was supported by the Wayne B. Duddlesten Professorship in Cancer Research, the Raymond and Maria Floyd Bladder Cancer Research Foundation Grant to AMK, and NIH/NCI UTMD Anderson SPORE in Genitourinary Cancer (Bladder) (P50CA091846) to CPND © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e298-e298 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kelly Bree More articles by this author Patrick Hensley More articles by this author Nathan Brooks More articles by this author Lianchun Xiao More articles by this author Yu Shen More articles by this author Neema Navai More articles by this author H. Barton Grossman More articles by this author Colin Dinney More articles by this author Ashish Kamat More articles by this author Expand All Advertisement Loading ...

779 Effects of lifetime trauma exposure on the association between neighborhood safety and sleep

Abstract Introduction Greater perceived neighborhood safety (PNS) has been linked to better sleep quality and longer sleep duration. There is also evidence that past exposure to traumatic events may be associated with lower perceived personal safety and poor mental health. Yet, the moderating effects of lifetime trauma exposure on the association between PNS and sleep (duration &amp; latency), has not been assessed. Methods We used cross-sectional data from 190 healthy NYC Latino adults. Lifetime trauma exposure was measured using the Life Events Checklist [LEC] (a count of traumatic events that happened to or were witnessed). In the first set of models, we regressed self-reported sleep duration in minutes (continuous), on PNS (safe vs. not safe), a single item scale, with three covariates (i.e. age, gender, education). In the second set, self-reported sleep latency in minutes, replaced sleep duration. To test for moderation, interaction terms—LEC x PNS—were added to covariate-adjusted models. In sensitivity analyses, regression models were re-run with adjustment for PTSD symptoms, and with short sleep duration (&amp;lt;7hours) as the outcome. Results On average, participants were 37.9 years old (SE= 1.02), 65.8% female, 59.5% foreign-born, and 33.2% completed &amp;lt; Bachelor’s degree. Overall, 43.68% slept &amp;lt;7 hours and 83.68% were exposed to &amp;gt;1 traumatic event in their lifetime. In adjusted models, each traumatic event (b= -2.95, SE = 1.34, p=0.03) was negatively associated with sleep duration. When PTSD symptoms was added, trauma was no longer statistically significant (b=-1.08, SE=1.02, p=0.18). However, each traumatic event exposure was associated with a 10% higher odds of short sleep duration (OR= 1.10, CI=1.02, 1.15), and this association remained significant with adjustment for PTSD symptoms. No interaction terms were significant. In models for sleep latency, there were no statistically significant main effects for LEC or interaction terms. Conclusion We found a dose response in the negative association between lifetime exposure to trauma and sleep duration, but not sleep latency. Trauma history did not moderate the association between PNS and sleep. These results suggest that short sleep duration may be particularly sensitive to lifetime exposure to trauma independent of neighborhood safety. Future studies should replicate these results in population-based samples. Support (if any):

An investigation of the causal effect of educational expectations on school performance. Behavioral consequences, time-stable confounding, or reciprocal causality?

Educational expectations are core concepts in the sociology of education. In this study, we are interested in the potential behavioral consequences of expectations on school performance in early secondary education. The existing literature leads to contradictory hypotheses regarding the causal effect of expectations on achievement. On the one hand, expectations could act as cognitions steering individual behavior towards the attainment of a certain educational degree via preparatory commitment and effort. Such behavioral consequences should affect achievement in school. On the other hand, expectations could merely reflect students’ perceptions of opportunities without exerting an effect on future achievement. This paper studies these claims by relying on German panel data of students in lower secondary education. In the first set of models, we find that after adjusting for student fixed effects, expectations are only marginally related to grades and competences. In further models, we assess the role of stable high and low aspirations in explaining educational achievement trajectories. After adjusting for past grades via inverse probability weighting, achievement at the end of lower secondary education is similar between students with stable high expectations and those with stable low expectations. Taking together the results of these different modelling approaches, our study suggests that expectations are not drivers of achievement-related behavior.

Identifying underpricing in index options

This study analyses the occurrence and extent of underpricing of index options on the National Stock Exchange (NSE) of India. The study uses discriminant analysis to explain the incidence of underpricing, and regression analysis to explain the extent of underpricing. Further, the study proposes three sets of models to explain underpricing of options. The first set of models considers only the impact of moneyness on underpricing. The second set of models considers the impact of both moneyness and time to expiration on underpricing. The third set of models considers the impact of moneyness, time to expiration, and changes in returns and volatility of the underlying asset on underpricing. The results of the study would enable speculators to identify arbitrage opportunities by predicting the occurrence and magnitude of underpricing in index options, vis-à-vis trading costs, in terms of moneyness, time to expiration, returns of the underlying index, and the volatility of the underlying index. The results also identify the inefficiencies of options in the price discovery mechanism, which the exchange can try to rectify by provision of sufficient market demand and liquidity.

Assessing the value of electrical resistivity derived soil water content: Insights from a case study in the Critical Zone of the Chinese Loess Plateau

Acquiring data for the soil water content (θ) is important for assessing vegetation growth, drought, and climate change. However, it is a time-consuming and labor-intensive task that is especially challenging in deep soils. Therefore, we introduce the noninvasive technique of electrical resistivity tomography (ERT) for indirectly determining θ through the development of prediction models for loessial regions under different site conditions (i.e., soil texture, land use, soil depth, and dry/wet conditions). We obtained 2769 pairs of electrical resistivity (ρ) and θ datasets using ERT (53 sites) and a neutron probe (69 access tubes) on the Chinese Loess Plateau. We built linear and nonlinear models correlating ρ and θ and selected the best model according to the coefficient of determination (R2) and root-mean-square error (RMSE). The uncertainty and sensitivity of ERT-derived θ were further evaluated and acceptable results were obtained. The new models correlating ρ and θ under different site conditions are the first set of models based on field data from a loessial region, and their acceptable performance makes them applicable for measuring different soil parameters in the Loess Plateau and possibly other loessial regions around the world.

Coordination of Purchasing and Bidding Activities Across Markets

In both consumer purchasing and industrial procurement, combinatorial interdependencies among the items to be purchased are commonplace. E-commerce compounds the problem by providing more opportunities for switching suppliers at low costs, but also potentially eases the problem by enabling automated market decision-making systems, commonly referred to as trading agents, to make purchasing decisions in an integrated manner across markets. Most of the existing research related to trading agents assumes that there exists a combinatorial market mechanism in which buyers (or sellers) can bid (or sell) service or merchant bundles. Today's prevailing e-commerce practice, however, does not support this assumption in general and thus limits the practical applicability of these approaches. We are investigating a new approach to deal with the combinatorial interdependency challenges for online markets. This approach relies on existing commercial online market institutions such as posted-price markets and various online auctions that sell single items. It uses trading agents to coordinate a buyer's purchasing and bidding activities across multiple online markets simultaneously to achieve the best overall procurement effectiveness. This paper presents two sets of models related to this approach. The first set of models formalizes optimal purchasing decisions across posted-price markets with fixed transaction costs. Flat shipping costs, a common e-tailing practice, are captured in these models. We observe that making optimal purchasing decisions in this context is NP-hard in the strong sense and suggest several efficient computational methods based on discrete location theory. The second set of models is concerned with the coordination of bidding activities across multiple online auctions. We study the underlying coordination problem for a collection of first or second-price sealed-bid auctions and derive the optimal coordination and bidding policies.

Empirical Models for the Realistic Generation of Cooperative Awareness Messages in Vehicular Networks

Most V2X (Vehicle-to-Everything) applications rely on broadcasting awareness messages known as CAM (Cooperative Awareness Messages) in ETSI or BSM (Basic Safety Message) in SAE standards. A large number of studies have been devoted to guarantee their reliable transmission. However, to date, the studies are generally based on simplified data traffic models that generate awareness messages at periodic intervals or with a constant message size. These models do not accurately represent the real generation of CAM messages that follow specific mobility-based rules. Using simplified and unrealistic traffic models can significantly impact the results and validity of the studies, and hence accurate models for the generation of awareness messages are necessary. This paper proposes the first set of models that can realistically generate CAM messages. The models have been created from real traces collected by two car manufacturers in urban, sub-urban and highway test drives. The models are based on mth order Markov sources, and model the size of CAMs and the time interval between CAMs. The models are openly provided to the community and can be easily integrated into any simulator.

CFD Simulation of an Industrial Spiral Refrigeration System

In the food industry, heating and cooling are key processes where CFD can play an important role in improving quality, productivity and reducing energy costs. Cooling products after baking is crucial for storage and transportation; the product has to be cooled efficiently to a specified temperature (often to fulfill regulatory requirements) whilst preserving its quality. This study involves the analysis of spiral cooling refrigerators used in cooling food products, in this case, Cornish Pasties. Three separate sets of CFD models were developed and validated against experimental data taken in the laboratory and measurements taken in use in industry. In the first set of models a full CFD model was developed of a refrigeration spiral including the pasties, and used to study the heat transfer from the products to the air. Further simulations were carried out on individual pasties to explore the pasty cooling and heat transfer to the air in more detail, with the pasty geometry being determined from MRI scans. In the final set of simulations, Image Based Meshing (IBM) was used to determine the interior structure of the pasty and develop a full heat conduction model of the interior, which was compared with separate laboratory experiments using jets of cold air to cool the pasty. In all cases, good agreement was obtained between the CFD results and experimental data, whilst the CFD simulations provide valuable information about the air flows and cooling in the industrial system.