cssi/SciSciGPT-SciSciNet huggingface dataset:
Interferon-β Treatment of Metastatic Prostate Cancer

A limited clinical trial of Interferon-beta (Human Fibroblast Interferon) in the treatment of advanced, hormone-refractory prostate cancer was conducted by the National Prostate Cancer Project (NPCP Protocol 2100). Sixteen patients with metastatic prostate cancer who had failed prior hormone therapy were entered into the study. Treatment consisted of 6 X 10(6) units of Interferon-beta intravenously three times per week for 12 weeks. Chills and fever were seen in ten of the 16 patients (62.5%), and mild hematologic toxicity occurred in four patients. No complete or partial responses were observed. Three patients had stable disease by NPCP criteria for a mean duration of 6.3 months. Progression of disease was seen in 13 of the 16 patients, eight of whom progressed during therapy. The results of this study suggest that Interferon-beta has limited efficacy in the treatment of advanced, hormone-refractory prostate cancer.
METAL SENSITIVITY IN TOTAL KNEE ARTHROPLASTY: “DOC, AM I ALLERGIC TO MY IMPLANT?”

The role of metal sensitivity or allergy in causing persistent symptoms or failure and need for a revision of a total joint replacement has been the topic of debate and controversy for decades. There was renewed interest in this area with the rise of metal-on-metal hip arthroplasty and the advent of adverse local tissue reactions. This led to an increase in metal ion testing as well as metal sensitivity testing. With the decline of the use of metal-on-metal hip components, this is now mostly an issue in knee arthroplasty. It is well known that a substantial percentage of patients have persistent symptoms following knee replacement. What remains in question is whether allergy to metal or other materials such as PMMA may be a contributing factor. It is accepted that the incidence of positive skin patch tests is higher in symptomatic failed joint replacements. Nickel sensitivity is most common as a positive skin test with up to 15% of patients demonstrating this followed by chromium and cobalt. A recent review by Lachiewicz et al. concluded that there was insufficient evidence to recommend routine or widespread cutaneous or in vitro hypersensitivity testing before primary TKA, that there is no evidence-based rationale to recommend a routine metal allergy screening questionnaire, that there is only anecdotal support for Ni-free implants, and that local dermatitis should be treated with topical steroids. In another article, routine screening for metal allergy was not recommended, however, selective screening for history of sensitivity or unexplained pain or early loosening was suggested. Other experts have recommended a role for utilizing a commercially available alternative to components containing nickel or cobalt in patients thought to be hypersensitive. A recent study, however, concluded that there was no difference in complications, revisions, or reoperations among patients who tested positive with patch testing whether they were treated with standard components or nickel free components. Likewise, a consensus panel published results from the United Kingdom in which cobalt chrome implants were recommended regardless of the patients metal allergy status. Patient perception is important, however, and among patients who report multiple allergies of any kind, a higher percentage are likely to be dissatisfied with their knee replacement. Of more importance are those reporting a specific allergy to metal are substantially more likely to express some dissatisfaction with their components. Metal allergy as a cause of chronic pain and/or early failure of joint replacement is rare if it exists at all. It is always a diagnosis of exclusion. Patients who think they are allergic are probably more likely to be more symptomatic following joint replacement. Whether or not to use a nickel free or hypoallergenic component in such patients remains an area of controversy.
Modulation of the Seasonal Cycle of Antarctic Sea Ice Extent Related to the Southern Annular Mode

Through analysis of remotely sensed sea surface temperature (SST) and sea ice concentration data, we investigate the impact of winds related to the Southern Annular Mode (SAM) on sea ice extent around Antarctica. We show that positive SAM anomalies in the austral summer are associated with anomalously cold SSTs that persist and lead to anomalous ice growth in the following autumn, while negative SAM anomalies precede warm SSTs and a reduction in sea ice extent during autumn. The largest effect occurs in April, when a unit change in the detrended summertime SAM is followed by a 1.8±0.6 ×105 km2 change in detrended sea ice extent. We find no evidence that sea ice extent anomalies related to the summertime SAM affect the wintertime sea ice extent maximum. Our analysis shows that the wind anomalies related to the negative SAM during the 2016/2017 austral summer contributed to the record minimum Antarctic sea ice extent observed in March 2017.
Transport properties of the doped thermoelectric material K2Bi8-xSbxSe13

The synthesis, physicochemical, spectroscopic, and structural characterization of the compound β-K2Bi8Se13 has been previously reported. The results indicated that this material should be investigated further for possible thermoelectric applications. β-K2Bi8Se13 exhibits excellent electrical conductivity values at room temperature while maintaining high Seebeck coefficients. In this work, the optimization of the compound β-K2Bi8Se13 is continued by the introduction of varying concentrations of several different dopants. The value of x in K2Bi8- xSbxSe13 was varied in order to find the composition with minimum thermal conductivity. Where possible, transport measurements were carried out on both single crystal and polycrystalline ingot material. From these data, the trends in the key parameters were identified for optimizing the power factor and figure of merit.
Segmenting two-sided markets

Recent years have witnessed the rise of many successful e-commerce marketplace platforms like the Amazon marketplace, AirBnB, Uber/Lyft, and Upwork, where a central platform mediates economic transactions between buyers and sellers. A common feature of many of these two-sided marketplaces is that the platform has full control over search and discovery, but prices are determined by the buyers and sellers. We summarize our results from [Banerjee et al. 2017] where, motivated by this application domain, we study the algorithmic aspects of market segmentation via directed discovery in two-sided markets with endogenous prices. We consider a model where an online platform knows each buyer/seller's characteristics, and associated demand/supply elasticities. Moreover, the platform can use discovery mechanisms (search, recommendation, etc.) to control which buyers/sellers are visible to each other. We develop efficient algorithms for throughput (i.e. volume of trade) and welfare maximization with provable guarantees under a variety of assumptions on the demand and supply functions.
Editorial: Note About Inaccurate Results Published in the American Journal of Epidemiology and the American Journal of Public Health.

Reviews are provided for the articles "The Impact of Obesity on U.S. Mortality Levels: The Importance of Age and Cohort Factors in Population Estimates" by R.K. Masters, E.N. Reither, D.A. Powers, Y.C. Yang, A.E. Burger, and B.G. Link which appears in a 2013 issue of this journal and "Obesity and U.S. Mortality Risk Over the Adult Life Course" by Masters, Powers,and Link which appears in a 2013 issue of the "American Journal of Epidemiology."
A Continuous-Time Model of Sovereign Debt

Abstract I construct a continuous-time model of strategic default and provide a numerical algorithm that solves it. I compare the results and computation times to standard discrete-time models of sovereign debt. The method proposed here is faster than discrete-time computation methods while obtaining similar quantitative results. The few differences between the models can all be attributed to a painful deleveraging feature. When debt issuance happens at a higher frequency, the sovereign faces higher interest rate spreads along the deleveraging process. So rolling over its debt becomes more costly. This feature leads to a coefficient of variation for interest rate spreads that is higher and closer to the data relative to its discrete-time sovereign debt model counterpart, calibrated to quarterly frequency. I solve three variants of the model. The first includes short-term maturity bonds only and a constant risk-free interest rate. The second allows for stochastic fluctuations in the risk-free rate. Finally, I extend the model to allow for long-term bonds.
An empirical analysis of corporate currency risk management policies and practices

Abstract Using a unique and extremely granular data set of complete currency spot and derivatives positions for 101 large non-financial corporations, we compare the stated currency risk management policies with the actual strategies executed by these companies. Our integrative analysis draws from the three principal sources of information that exist about firms: market prices, financial statements, and what firms say about themselves. We first identify a notable discord between the policies and their practices of firms. We next find that these companies engage in a high degree of currency speculation that seems to be driven by market movements with the results strongest for the heaviest derivatives users. Finally, we show that these companies attempt to time the market even when they are engaged in hedging. We find that the actions of companies differ from their words more often when they have a greater amount of debt, particularly foreign currency debt, and a lower level of managerial ownership. In general, we find that corporate risk management is highly speculative and more often than not disagrees with stated company policies.
Last Mile for Tuna (to a Safe Harbor): What is the TBT Agreement All About?

The WTO Agreement on TBT (Technical Barriers to Trade) aims at taming NTBs (nontariff barriers), the main instrument segmenting markets nowadays. Some of the terms used to flesh out the commitments undertaken are borrowed from the GATT, and some originate in the modern regulatory reality as expressed through SDOs (standard-development organizations). It does not share a copy-cat function with the GATT, though. Alas, the WTO Appellate Body, by understanding words as ‘invariances’, e.g., interpreting them out of context (without asking what is the purpose for the TBT?), has not only exported its GATT case law, but also misapplied it into the realm of TBT, and ended up with significant errors. In the most recent report of the tuna-saga, an ongoing dispute between Mexico and the United States, a panel corrected some of the pre-existing misunderstandings regarding the scope and function of TBT. Problems though, persist. Importantly, we cannot rely on instincts of isolated adjudicators to get it right. Only a coherent test for consistency with the TBT can serve this function. This is what we still miss. In what follows, we explain why the current approach is erroneous, and advance an alternative understanding, which could help implement the TBT in a manner faithful to its negotiating intent, and objective function.
Repetition and Language Models and Comparable Corpora.

I will discuss a couple of non-standard features that I believe could be useful for working with comparable corpora. Dotplots have been used in biology to find interesting DNA sequences. Biology is interested in ordered matches, which show up as (possibly broken) diagonals in dot-plots. Information Retrieval is more interested in unordered matches (e.g., cosine similarity), which show up as squares in dotplots. Parallel corpora have both squares and diagonals multiplexed together. The diagonals tell us what is a translation of what, and the squares tell us what is in the same language. I would expect dotplots of comparable corpora would contain lots of diagonals and squares, though the diagonals would be shorter and more subtle in comparable corpora than in parallel corpora.
Ancient genomic variation underlies repeated ecological adaptation in young stickleback populations.

Adaptation in the wild often involves standing genetic variation (SGV), which allows rapid responses to selection on ecological timescales. However, we still know little about how the evolutionary histories and genomic distributions of SGV influence local adaptation in natural populations. Here, we address this knowledge gap using the threespine stickleback fish (Gasterosteus aculeatus) as a model. We extend restriction site-associated DNA sequencing (RAD-seq) to produce phased haplotypes approaching 700 base pairs (bp) in length at each of over 50,000 loci across the stickleback genome. Parallel adaptation in two geographically isolated freshwater pond populations consistently involved fixation of haplotypes that are identical-by-descent. In these same genomic regions, sequence divergence between marine and freshwater stickleback, as measured by dXY , reaches tenfold higher than background levels and genomic variation is structured into distinct marine and freshwater haplogroups. By combining this dataset with a de novo genome assembly of a related species, the ninespine stickleback (Pungitius pungitius), we find that this habitat-associated divergent variation averages six million years old, nearly twice the genome-wide average. The genomic variation that is involved in recent and rapid local adaptation in stickleback has therefore been evolving throughout the 15-million-year history since the two species lineages split. This long history of genomic divergence has maintained large genomic regions of ancient ancestry that include multiple chromosomal inversions and extensive linked variation. These discoveries of ancient genetic variation spread broadly across the genome in stickleback demonstrate how selection on ecological timescales is a result of genome evolution over geological timescales, and vice versa.
On Preferring A to B, While Also Preferring B to A

In important contexts, people prefer option A to option B when they evaluate the two separately, but prefer option B to option A when they evaluate the two jointly. In consumer behavior, politics, ...
ShapeCodes: Self-Supervised Feature Learning by Lifting Views to Viewgrids

We introduce an unsupervised feature learning approach that embeds 3D shape information into a single-view image representation. The main idea is a self-supervised training objective that, given only a single 2D image, requires all unseen views of the object to be predictable from learned features. We implement this idea as an encoder-decoder convolutional neural network. The network maps an input image of an unknown category and unknown viewpoint to a latent space, from which a deconvolutional decoder can best “lift” the image to its complete viewgrid showing the object from all viewing angles. Our class-agnostic training procedure encourages the representation to capture fundamental shape primitives and semantic regularities in a data-driven manner—without manual semantic labels. Our results on two widely-used shape datasets show (1) our approach successfully learns to perform “mental rotation” even for objects unseen during training, and (2) the learned latent space is a powerful representation for object recognition, outperforming several existing unsupervised feature learning methods.
Kinome Expansion in the Fusarium oxysporum Species Complex Driven by Accessory Chromosomes

ABSTRACT The Fusarium oxysporum species complex (FOSC) is a group of soilborne pathogens causing severe disease in more than 100 plant hosts, while individual strains exhibit strong host specificity. Both chromosome transfer and comparative genomics experiments have demonstrated that lineage-specific (LS) chromosomes contribute to the host-specific pathogenicity. However, little is known about the functional importance of genes encoded in these LS chromosomes. Focusing on signaling transduction, this study compared the kinomes of 12 F. oxysporum isolates, including both plant and human pathogens and 1 nonpathogenic biocontrol strain, with 7 additional publicly available ascomycete genomes. Overall, F. oxysporum kinomes are the largest, facilitated in part by the acquisitions of the LS chromosomes. The comparative study identified 99 kinases that are present in almost all examined fungal genomes, forming the core signaling network of ascomycete fungi. Compared to the conserved ascomycete kinome, the expansion of the F. oxysporum kinome occurs in several kinase families such as histidine kinases that are involved in environmental signal sensing and target of rapamycin (TOR) kinase that mediates cellular responses. Comparative kinome analysis suggests a convergent evolution that shapes individual F. oxysporum isolates with an enhanced and unique capacity for environmental perception and associated downstream responses. IMPORTANCE Isolates of Fusarium oxysporum are adapted to survive a wide range of host and nonhost conditions. In addition, F. oxysporum was recently recognized as the top emerging opportunistic fungal pathogen infecting immunocompromised humans. The sensory and response networks of these fungi undoubtedly play a fundamental role in establishing the adaptability of this group. We have examined the kinomes of 12 F. oxysporum isolates and highlighted kinase families that distinguish F. oxysporum from other fungi, as well as different isolates from one another. The amplification of kinases involved in environmental signal relay and regulating downstream cellular responses clearly sets Fusarium apart from other Ascomycetes . Although the functions of many of these kinases are still unclear, their specific proliferation highlights them as a result of the evolutionary forces that have shaped this species complex and clearly marks them as targets for exploitation in order to combat disease.
Why we need to look beyond the glass transition temperature to characterize the dynamics of thin supported polymer films.

There is significant variation in the reported magnitude and even the sign of [Formula: see text] shifts in thin polymer films with nominally the same chemistry, film thickness, and supporting substrate. The implicit assumption is that methods used to estimate [Formula: see text] in bulk materials are relevant for inferring dynamic changes in thin films. To test the validity of this assumption, we perform molecular simulations of a coarse-grained polymer melt supported on an attractive substrate. As observed in many experiments, we find that [Formula: see text] based on thermodynamic criteria (temperature dependence of film height or enthalpy) decreases with decreasing film thickness, regardless of the polymer-substrate interaction strength e. In contrast, we find that [Formula: see text] based on a dynamic criterion (relaxation of the dynamic structure factor) also decreases with decreasing thickness when e is relatively weak, but [Formula: see text] increases when e exceeds the polymer-polymer interaction strength. We show that these qualitatively different trends in [Formula: see text] reflect differing sensitivities to the mobility gradient across the film. Apparently, the slowly relaxing polymer segments in the substrate region make the largest contribution to the shift of [Formula: see text] in the dynamic measurement, but this part of the film contributes less to the thermodynamic estimate of [Formula: see text] Our results emphasize the limitations of using [Formula: see text] to infer changes in the dynamics of polymer thin films. However, we show that the thermodynamic and dynamic estimates of [Formula: see text] can be combined to predict local changes in [Formula: see text] near the substrate, providing a simple method to infer information about the mobility gradient.
Electrical synapses between inhibitory neurons shape the responses of principal neurons to transient inputs in the thalamus: a modeling study

As multimodal sensory information proceeds to the cortex, it is intercepted and processed by the nuclei of the thalamus. The main source of inhibition within thalamus is the reticular nucleus (TRN), which collects signals both from thalamocortical relay neurons and from thalamocortical feedback. Within the reticular nucleus, neurons are densely interconnected by connexin36-based gap junctions, known as electrical synapses. Electrical synapses have been shown to coordinate neuronal rhythms, including thalamocortical spindle rhythms, but their role in shaping or modulating transient activity is less understood. We constructed a four-cell model of thalamic relay and TRN neurons, and used it to investigate the impact of electrical synapses on closely timed inputs delivered to thalamic relay cells. We show that the electrical synapses of the TRN assist cortical discrimination of these inputs through effects of truncation, delay or inhibition of thalamic spike trains. We expect that these are principles whereby electrical synapses play similar roles in regulating the processing of transient activity in excitatory neurons across the brain.
Quantum information processing using quasiclassical electromagnetic interactions between qubits and electrical resonators

Electrical resonators are widely used in quantum information processing, by engineering an electromagnetic interaction with qubits based on real or virtual exchange of microwave photons. This interaction relies on strong coupling between the qubits' transition dipole moments and the vacuum fluctuations of the resonator in the same manner as cavity quantum electrodynamics (QED), and has consequently come to be called 'circuit QED' (cQED). Great strides in the control of quantum information have already been made experimentally using this idea. However, the central role played by photon exchange induced by quantum fluctuations in cQED does result in some characteristic limitations. In this paper, we discuss an alternative method for coupling qubits electromagnetically via a resonator, in which no photons are exchanged, and where the resonator need not have strong quantum fluctuations. Instead, the interaction can be viewed in terms of classical, effective 'forces' exerted by the qubits on the resonator, and the resulting resonator dynamics used to produce qubit entanglement are purely classical in nature. We show how this type of interaction is similar to that encountered in the manipulation of atomic ion qubits, and we exploit this analogy to construct two-qubit entangling operations that are largely insensitive to thermal or other noise in the resonator, and to its quality factor. These operations are also extensible to larger numbers of qubits, allowing interactions to be selectively generated among any desired
Predicting Budgetary Change: The Effect of Performance Gaps

Literature on punctuated equilibrium theory (PET) explains the reasons organizations undergo incremental and punctuated policy changes. This study examines PET within the budgeting process. Alongside disproportionate information processing and institutional friction, recent innovations in PET have incorporated organizational history and theories from public administration to explain budgetary fluctuations. Part of the work merging PET with public administration has demonstrated how policy feedback (measured as the absolute level of performance) influences budgetary changes. Building upon this work, this study adds to the literature by examining another measure of policy feedback–organization performance gaps. This is a theoretically interesting question in how managers respond to performance growth and decline over time. It addresses performance budgeting and evidence based policymaking. Results show that while incremental budgetary changes are the most prevalent no matter the performance change, the probability of negative and positive budgetary changes differ across the spectrum of positive and negative performance gaps.
Altering lipid droplet homeostasis affects Coxiella burnetii intracellular growth

Coxiella burnetii is an obligate intracellular bacterial pathogen and a causative agent of culture-negative endocarditis. While C. burnetii initially infects alveolar macrophages, it has also been found in lipid droplet (LD)-containing foamy macrophages in the cardiac valves of endocarditis patients. In addition, transcriptional studies of C. burnetii-infected macrophages reported differential regulation of the LD coat protein-encoding gene perilipin 2 (plin-2). To further investigate the relationship between LDs and C. burnetii, we compared LD numbers using fluorescence microscopy in mock-infected and C. burnetii-infected alveolar macrophages. On average, C. burnetii-infected macrophages contained twice as many LDs as mock-infected macrophages. LD numbers increased as early as 24 hours post-infection, an effect reversed by blocking C. burnetii protein synthesis. The observed LD accumulation was dependent on the C. burnetii Type 4B Secretion System (T4BSS), a major virulence factor that manipulates host cellular processes by secreting bacterial effector proteins into the host cell cytoplasm. To determine the importance of LDs during C. burnetii infection, we manipulated LD homeostasis and assessed C. burnetii intracellular growth. Surprisingly, blocking LD formation with the pharmacological inhibitors triacsin C or T863, or knocking out acyl-CoA transferase-1 (acat-1) in alveolar macrophages, increased C. burnetii growth at least 2-fold. Conversely, preventing LD lipolysis by inhibiting adipose triglyceride lipase (ATGL) with atglistatin almost completely blocked bacterial growth, suggesting LD breakdown is essential for C. burnetii. Together these data suggest that maintenance of LD homeostasis, possibly via the C. burnetii T4BSS, is critical for bacterial growth.
"Ghost tablet" husks excreted in feces in large bupropion XL overdose.

Background: Extended-release medications are widely prescribed across the spectrum of medical specialties; however, there is heterogeneity in how they are formulated. Commonly, they consist of an i...
HyLine: a Simple and Practical Flow Scheduling for Commodity Datacenters

Today’s datacenter networks (DCNs) have been built upon multipath topologies where each path contains multiple links. However, flow scheduling schemes proposed to minimize flow completion times (FCT) in DCNs are based on algorithms which are optimum or close-to-optimum only over single link. Moreover, most of these scheduling schemes seek either fully centralized approaches having overhead of communicating to a central entity or fully distributed approaches requiring changes in the fabric.Motivated by these shortcomings, we present HyLine a simple scheduling design for commodity DCNs which is equipped with a joint load-balancing and flow scheduling (path-aware) design exploiting the multipath nature of DCNs. HyLine takes a hybrid approach and uses the global-awareness of centralized and agility of distributed techniques without requiring any changes in the fabric. To that end, it determines a threshold margin identifying flows for which using centralized approach is beneficial.We have shown through extensive ns2 simulations that despite HyLine’s simplicity, it significantly outperforms existing schemes and achieves lower average and 99th percentile FCTs. For instance, compared to Qjump–state-of-the-art practical scheme– and pFabric–one of the best performing flow scheduling schemes– HyLine reduces average FCT up to 68% and 31%, respectively, under a production datacenter workload.
Statistics students’ identification of inferential model elements within contexts of their own invention

Statistical thinking partially depends upon an iterative process by which essential features of a problem setting are identified and mapped onto an abstract model or archetype, and then translated back into the context of the original problem setting (Wild and Pfannkuch, Int Stat Rev 67(3):223–248, 1999). Assessment in introductory statistics often relies on tasks that present students with data in context and expects them to choose and describe an appropriate model. This study explores post-secondary student responses to an alternative task that prompts students to clearly identify a sample, population, statistic, and parameter using a context of their own invention. The data include free-text narrative responses of a random sample of 500 students from a sample of more than 1600 introductory statistics students. Results suggest that students’ responses often portrayed sample and population accurately. Portrayals of statistic and parameter were less reliable and were associated with descriptions of a wide variety of other concepts. Responses frequently attributed a variable of some kind to the statistic, or a study design detail to the parameter. Implications for instruction and research are discussed, including a call for emphasis on a modeling paradigm in introductory statistics.
Labor Markets and the Choice of Technology in an Open Developing Economy

This article highlights economic factors determining the choice of technology and openness in an intertemporal context in the presence of institutional constraints in the labour market. It considers the case in which a ‘more aggressive’ development strategy involves an investment in a modern technology. This technology raises the degree to which real wages and productivity depend on external factors while at the same time it also raises the expected value of real income. In the absence of such investment, production takes place in a traditional sector, using a technology that limits exposure to external shocks. The analysis evaluates the dependence of the choice of technology on the volatility of the shocks affecting the economy, the expected productivity gains, the investment cost associated with the modern technology, and the attitude towards risk. The dependence of openness, investment, and real wages on the attitude towards risk is derived for such an economy. The analysis also discusses the interacti...
ANALYZING THE EFFECTS OF INSURING HEALTH RISKS: ON THE TRADE-OFF BETWEEN SHORT RUN INSURANCE BENEFITS VS. LONG RUN INCENTIVE COSTS

This paper constructs a dynamic model of health insurance to evaluate the short- and long run effects of policies that prevent firms from conditioning wages on health conditions of their workers, and that prevent health insurance companies from charging individuals with adverse health conditions higher insurance premia. Our study is motivated by recent US legislation that has tightened regulations on wage discrimination against workers with poorer health status (Americans with Disability Act of 2009, ADA, and ADA Amendments Act of 2008, ADAAA) and that will prohibit health insurance companies from charging different premiums for workers of different health status starting in 2014 (Patient Protection and Affordable Care Act, PPACA). In the model, a trade-off arises between the static gains from better insurance against poor health induced by these policies and their adverse dynamic incentive effects on household efforts to lead a healthy life. Using household panel data from the PSID we estimate and calibrate the model and then use it to evaluate the static and dynamic consequences of no-wage discrimination and no-prior conditions laws for the evolution of the cross-sectional health and consumption distribution of a cohort of households, as well as ex-ante lifetime utility of a typical member of this cohort. In our quantitative analysis we find that although a combination of both policies is effective in providing full consumption insurance period by period, it is suboptimal to introduce both policies jointly since such policy innovation induces a more rapid deterioration of the cohort health distribution over time. This is due to the fact that combination of both laws severely undermines the incentives to lead healthier lives. The resulting negative effects on health outcomes in society more than offset the static gains from better consumption insurance so that expected discounted lifetime utility is lower under both policies, relative to only implementing wage nondiscrimination legislation.
Two-Layer Model Predictive Battery Thermal and Energy Management Optimization for Connected and Automated Electric Vehicles

Future vehicles are expected to be able to exploit increasingly the connected driving environment for efficient, comfortable, and safe driving. Given relatively slow dynamics associated with the state of charge and temperature response in electrified vehicles with large batteries, a long prediction/planning horizon is needed to achieve improved energy efficiency benefits. In this paper, we develop a two-layer Model Predictive Control (MPC) strategy for battery thermal and energy management of electric vehicle (EV), aiming at improving fuel economy through real-time prediction and optimization. In the first layer, the long-term traffic flow information and an approximate model reflective of the relatively slow battery temperature dynamics are leveraged to minimize energy consumption required for battery cooling while maintaining the battery temperature within the desired operating range. In the second layer, the scheduled battery thermal and state of charge (SOC) trajectories planned to achieve long-term battery energyoptimal thermal behavior are used as the reference over a short horizon to regulate the battery temperature. Additionally, an intelligent online constraint handling (IOCH) algorithm is developed to compensate for the mismatch between the actual and predicted driving conditions and reduce the chance for battery temperature constraint violation. The simulation results show that, depending on the driving cycle, the proposed two-layer MPC is able to save 2.8 - 7.9% of the battery energy compared to the traditional rule-based controller in connected and automated vehicle (CAV) operation scenario. Moreover, as compared to a single layer MPC with a long horizon, the two-layer structure of the proposed MPC solution reduces significantly the computing effort without compromising the performance.
Valence and core excitons in solids from velocity-gauge real-time TDDFT with range-separated hybrid functionals: An LCAO approach

Abstract An atomic-orbital basis set framework is presented for carrying out velocity-gauge real-time time-dependent density functional theory (TDDFT) simulations in periodic systems employing range-separated hybrid functionals. Linear optical response obtained from real-time propagation of the time-dependent Kohn-Sham equations including nonlocal exchange is considered in prototypical solid-state materials such as bulk Si, LiF and monolayer hexagonal-BN. Additionally core excitations in monolayer hexagonal-BN at the B and N K-edges are investigated and the role of long-range and short-range nonlocal exchange in capturing valence and core excitonic effects is discussed. Results obtained using this time-domain atomic orbital basis set framework are shown to be consistent with equivalent frequency-domain planewave results in the literature. The developments discussed lead to a time-domain generalized Kohn-Sham TDDFT implementation for the treatment of core and valence electron dynamics and light-matter interaction in periodic solid-state systems.
How instructors frame students' interactions with educational technologies can enhance or reduce learning with multiple representations

Abstract Instructors in STEM classrooms often frame students' interactions with technologies to help them learn content. For instance, in many STEM domains, instructors commonly help students translate physical 3D models into 2D drawings by prompting them to focus on (a) orienting physical 3D models and (b) generating 2D drawings. We investigate whether framing prompts that target either of these practices enhance the effectiveness of an educational technology that supports collaborative translation among multiple representations. To this end, we conducted a quasi-experiment with 565 undergraduate chemistry students. All students collaboratively built physical 3D models of molecules and translated them into 2D drawings. In a business-as-usual control condition, students drew on paper, without support from an educational technology. In two experimental conditions, students drew in an educational technology that provided feedback and prompted collaboration. One condition received framing prompts to focus on physical models (model condition); another received prompts to generate intermediary drawings on paper (draw condition). Compared to the control condition, the model condition showed higher learning gains, but the draw condition showed lower learning gains. Analyses of log data showed that students made more model-based errors, and the prompts in the model condition reduced these model-based errors. However, interviews with instructors showed that they prefer drawing-focused prompts, in contrast to our results. These findings offer theoretical insights into how students learn to translate among representations. Furthermore, they yield practical recommendations for the use of educational technologies that support learning with multiple representations.
Imaging of demineralized enamel in intact tooth by epidetected stimulated Raman scattering microscopy

Stimulated Raman scattering microscopy (SRS) was deployed to quantify enamel demineralization in intact teeth. The surfaces of 15 bovine-enamel blocks were divided into four equal-areas, and chemically demineralized for 0, 8, 16, or 24 h, respectively. SRS images (spectral coverage from ∼850 to 1150 cm − 1) were obtained at 10-μm increments up to 90 μm from the surface to the dentin–enamel junction. SRS intensities of phosphate (peak: 959 cm − 1), carbonate (1070 cm − 1), and water (3250 cm − 1) were measured. The phosphate peak height was divided by the carbonate peak height to calculate the SRS-P/C-ratio, which was normalized relative to 90 μm (SRS-P/C-ratio-normalized). The water intensity against depth decay curve was fitted with exponential decay. A decay constant (SRS-water-content) was obtained. Knoop-hardness values were obtained before (SMHS) and after demineralization (SMHD). Surface microhardness-change (SMH-change) [ ( SMHD − SMHS ) / SMHS] was calculated. Depth and integrated mineral loss (ΔZ) were determined by transverse microradiography. Comparisons were made using repeated-measures of analysis of variance. For SRS-P/C-ratio-normalized, at 0-μm (surface), sound (0-h demineralization) was significantly higher than 8-h demineralization and 24-h demineralization; 16-h demineralization was significantly higher than 24-h demineralization. For SRS-water-content, 24-h demineralization was significantly higher than all other demineralization-groups; 8-h demineralization and 16-h demineralization were significantly higher than 0-h demineralization. SRS-water-content presented moderate-to-strong correlation with SMH-change and weak-to-moderate correlation with depth. These results collectively demonstrate the potential of using SRS microscopy for in-situ chemical analysis of dental caries.
The Dual Kaczmarz Algorithm

The Kaczmarz algorithm is an iterative method for solving a system of linear equations. It can be extended so as to reconstruct a vector $x$ in a (separable) Hilbert space from the inner-products $\{\langle x, \phi _{n} \rangle \}$. The Kaczmarz algorithm defines a sequence of approximations from the sequence $\{\langle x, \phi _{n} \rangle \}$; these approximations only converge to $x$ when $\{\phi _{n}\}$ is effective. We dualize the Kaczmarz algorithm so that $x$ can be obtained from $\{\langle x, \phi _{n} \rangle \}$ by using a second sequence $\{\psi _{n}\}$ in the reconstruction. This allows for the recovery of $x$ even when the sequence $\{\phi _{n}\}$ is not effective; in particular, our dualization yields a reconstruction when the sequence $\{\phi _{n}\}$ is almost effective. We also obtain some partial results characterizing when the sequence of approximations from $\{\langle x, \phi _{n} \rangle \}$ using $\{\psi _{n}\}$ converges to $x$, in which case $\{(\phi _{n}, \psi _{n})\}$ is called an effective pair.
Relay node placement under budget constraint

Abstract The relay node placement problem in the wireless sensor network domain has been studied extensively. But under a fixed budget, it may be impossible to procure the minimum number of relay nodes needed to design a connected network of sensor and relay nodes. Nevertheless, one would still like to design a network with high level of connectedness, or low disconnectedness. In this paper, we introduce the notion of a measure of the “connectedness” of a disconnected graph. We study a family of problems whose goal is to design a network with “maximal connectedness” subject to a fixed budget constraint.
The creation and evolution of entrepreneurial public markets

Abstract This paper explores the creation and evolution of new stock exchanges around the world geared toward entrepreneurial companies, known as second-tier exchanges. Using hand-collected novel data, we show the proliferation of these exchanges in many countries, their significant volume of Initial Public Offerings (IPOs), and lower listing requirements. Shareholder protection strongly predicted exchange success, even in countries with high levels of venture capital activity, patenting, and financial market development. Better shareholder protection allowed younger, less-profitable, but faster-growing, companies to raise more capital. These results highlight the importance of institutions in enabling the provision of entrepreneurial capital to young companies.
Decentralized Privacy-Preserving Timed Execution in Blockchain-Based Smart Contract Platforms

Timed transaction execution is critical for various decentralized privacy-preserving applications powered by blockchain-based smart contract platforms. Such privacy-preserving smart contract applications need to be able to securely maintain users' sensitive inputs off the blockchain until a prescribed execution time and then automatically make the inputs available to enable on-chain execution of the target function at the execution time, even if the user goes offline. While straight-forward centralized approaches provide a basic solution to the problem, unfortunately they are limited to a single point of trust. This paper presents a new decentralized privacy-preserving transaction scheduling approach that allows users of Ethereum-based decentralized applications to schedule transactions without revealing sensitive inputs before an execution time window selected by the users. The proposed approach involves no centralized party and allows users to go offline at their discretion after scheduling a transaction. The sensitive inputs are privately maintained by a set of trustees randomly selected from the network enabling the inputs to be revealed only at the execution time. The proposed protocol employs secret key sharing and layered encryption techniques and economic deterrence models to securely protect the sensitive information against possible attacks including some trustees destroying the sensitive information or secretly releasing the sensitive information prior to the execution time. We demonstrate the attack-resilience of the proposed approach through rigorous analysis. Our implementation and experimental evaluation on the Ethereum official test network demonstrates that the proposed approach is effective and has a low gas cost and time overhead associated with it.
Gibbs posterior inference on value-at-risk

ABSTRACTAccurate estimation of value-at-risk (VaR) and assessment of associated uncertainty is crucial for both insurers and regulators, particularly in Europe. Existing approaches link data and Va...
A Diffusion-Reaction Model for Predicting Enzyme-Mediated Dynamic Hydrogel Stiffening.

Hydrogels with spatiotemporally tunable mechanical properties have been increasingly employed for studying the impact of tissue mechanics on cell fate processes. These dynamic hydrogels are particularly suitable for recapitulating the temporal stiffening of a tumor microenvironment. To this end, we have reported an enzyme-mediated stiffening hydrogel system where tyrosinase (Tyrase) was used to stiffen orthogonally crosslinked cell-laden hydrogels. Herein, a mathematical model was proposed to describe enzyme diffusion and reaction within a highly swollen gel network, and to elucidate the critical factors affecting the degree of gel stiffening. Briefly, Fick's second law of diffusion was used to predict enzyme diffusion in a swollen poly(ethylene glycol) (PEG)-peptide hydrogel, whereas the Michaelis⁻Menten model was employed for estimating the extent of enzyme-mediated secondary crosslinking. To experimentally validate model predictions, we designed a hydrogel system composed of 8-arm PEG-norbornene (PEG8NB) and bis-cysteine containing peptide crosslinker. Hydrogel was crosslinked in a channel slide that permitted one-dimensional diffusion of Tyrase. Model predictions and experimental results suggested that an increasing network crosslinking during stiffening process did not significantly affect enzyme diffusion. Rather, diffusion path length and the time of enzyme incubation were more critical in determining the distribution of Tyrase and the formation of additional crosslinks in the hydrogel network. Finally, we demonstrated that the enzyme-stiffened hydrogels exhibited elastic properties similar to other chemically crosslinked hydrogels. This study provides a better mechanistic understanding regarding the process of enzyme-mediated dynamic stiffening of hydrogels.
Making a Choice

It is our responsibility as educators to see that our students receive training to meet the present-day challenges facing our clients. The graduate programs in social work are especially suited for...
The impact of skew on performance and bias: How skew distorts short term performance, triggers bias, and changes drawdowns

Abstract In this paper, we explore the relationship between the statistic skew and known behavioral biases. We investigate the impact that skew has on the perception of performance as a function of time, and we show that negative skew artificially improves performance over the short term, while positive skew has the opposite effect. We quantify the relationship between skew and drawdown depth and length, and we show that negative skew increases drawdown depth and length, and that again positive skew does the opposite. Finally, we explore the relationship between skew, volatility, and drawdown, and we show that negative skew amplifies the increase that volatility causes in drawdown depth and length, while positive skew has a corresponding dampening effect.
Nanomechanical Analysis of Extracellular Matrix and Cells in Multicellular Spheroids

Over the last decade, atomic force microscopy (AFM) has played an important role in understanding nanomechanical properties of various cancer cell lines. This study is focused on Lewis lung carcinoma cell tumours as 3D multicellular spheroid (MS). Not much is know about the mechanical properties of the cells and the surrounding extracellular matrix (ECM) in rapidly growing tumours. Depth-dependent indentation measurements were conducted with the AFM. Force-vs.-indentation curves were used to create stiffness profiles as a function of depth. Here studies were focused on the outer most layer, i.e., proliferation zone of the spheroid. Both surface and sub-surface stiffness profiles of MS were created. This study revealed three nanomechanical topographies, Type A-high modulus due to collagen fibers, Type B-high stiffness at cell membrane and ECM interface and Type C-increased modulus due to cell lying deep inside matrix at a depth of 1.35 μm. Both Type and Type-B topographies result from collagen-based structures in ECM. This study has first time revealed mechanical constitution of an MS. Depth-dependent indentation studies have the revealed role of various molecular and cellular components responsible for providing mechanical stability to MS. Nanomechanical heterogeneities revealed in this investigation can shed new light in developing correct dosage regime for collagenase treatment of tumours and designing better controlled artificial extracellular matrix systems for replicating tissue growth in-vitro.