Miracle-dz/UniFAR-FTUs huggingface dataset:
A Behavioral Analysis of Learning Curve Strategy

Prior research on firm strategy in the presence of learning curves suggests that if learning is highly appropriable, early entrants can achieve sustained competitive advantage by rapidly building capacity and by pricing aggressively to preempt competition. However these studies all presume (1) rational actors and (2) equilibrium, implying markets clear at all points in time. We consider the robustness of the aggressive strategy in the presence of (1) boundedly rational agents and (2) a capacity acquisition lag. Agents are endowed with high local rationality but imperfect understanding of the feedback structure of the market; they use intendedly rational heuristics to forecast demand, acquire capacity, and set prices. These heuristics are grounded in empirical study and experimental test. Using a simulation of the duopoly case we show the aggressive learning curve strategy becomes suboptimal when the market is dynamically complex. When capacity cannot be adjusted instantaneously, forecasting errors leading to excess capacity can overwhelm the cost advantage conferred by the learning curve. We explore the sensitivity of the results to the feedback complexity of the market and the rationality of the agents’ decision making procedures. The results highlight the danger of extrapolating from equilibrium models of rational actors to the formulation of strategic prescriptions and demonstrate how disequilibrium behavior and bounded rationality can be incorporated into strategic analysis to form a ‘behavioral game theory’ amenable to rigorous analysis. * Sloan School of Management, Massachusetts Institute of Technology § McKinsey & Company Please direct correspondence to John Sterman at the MIT Sloan School of Management, 50 Memorial Drive, E53-351, Cambridge, MA 02142, or to <jsterman@mit.edu>.
Infinite-Label Learning with Semantic Output Codes

We develop a new statistical machine learning paradigm, named infinite-label learning, to annotate a data point with more than one relevant labels from a candidate set, which pools both the finite labels observed at training and a potentially infinite number of previously unseen labels. The infinite-label learning fundamentally expands the scope of conventional multi-label learning, and better models the practical requirements in various real-world applications, such as image tagging, ads-query association, and article categorization. However, how can we learn a labeling function that is capable of assigning to a data point the labels omitted from the training set? To answer the question, we seek some clues from the recent work on zero-shot learning, where the key is to represent a class/label by a vector of semantic codes, as opposed to treating them as atomic labels. We validate the infinite-label learning by a PAC bound in theory and some empirical studies on both synthetic and real data.
Combining Surface Analytical and Computational Techniques to Investigate Orientation Effects of Immobilized Proteins

Combining Surface Analytical and Computational Techniques to Investigate Orientation Effects of Immobilized Proteins Elisa Turla Harrison Chair of the Supervisory Committee: Professor David G. Castner Departments of Chemical Engineering and Bioengineering Controlling how proteins are immobilized (e.g. controlling their orientation and conformation) is essential for developing and optimizing the performance of in vitro protein-binding devices, such as enzyme-linked immunosorbent assays. The objective of this work is to develop new methodologies to study proteins and complex mixtures of proteins immobilized onto surfaces. The focus of this study was to control and characterize the orientation of protein G B1, an IgG antibody-binding domain of protein G, on well-defined surfaces as well as measure the effect of protein G B1 orientation on IgG antibody binding using a variety of surface analytical and computational techniques. The surface sensitivity of time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to distinguish between different proteins and their orientation by monitoring the changes in intensity of characteristic amino acid mass fragments. Amino acids distributed asymmetrically were used to calculate peak intensity ratios from ToF-SIMS data to determine the orientation of five different cysteine mutants of protein G B1 covalently attached to a maleimide surface. To study the effect of protein orientation on antibody binding, we formed multilayer protein films by binding IgG to protein G B1 films. Quartz crystal microbalance with dissipation monitoring (QCM-D) detected protein coverages of 69 – 130 ng/cm (theoretical mass of a monolayer of protein G B1 is 110 – 160 ng/cm). QCM-D and X-ray photoelectron spectroscopy analysis revealed that packing density along with orientation affected the antibody binding process. Spectra from ToF-SIMS using large Ar gas cluster ion sources distinguished between different proteins in multilayer protein systems. A Monte Carlo algorithm was developed to predict protein orientation on surfaces. Two distinct orientations of protein G B1 adsorbed onto a hydrophobic surface were found and characterized as two mutually exclusive sets of amino acids on the outermost β-sheets contacting the surface. This prediction was consistent with sum frequency generation (SFG) vibrational spectroscopy results. In fact, theoretical SFG spectra calculated from an equal combination of the two predicted orientations exhibited reasonable agreement with measured spectra of protein G B1 on polystyrene surfaces. These results show that computational methods to study proteins on surfaces can complement surface analytical data.
Symbolic execution of programs with strings

Symbolic execution has long been a popular technique for automated test generation and for error detection in complex code. Most of the focus has however been on programs manipulating integers, booleans, and references in object oriented programs. Recently researchers have started looking at programs that do lots of string processing; this is motivated by the popularity of the web and the risk that errors in such programs may lead to security violations. Attempts to extend symbolic execution to the domain of strings have mainly been divided into one of two camps: automata-based approaches and approaches based on efficient bitvector analysis. Here we investigate these two approaches in one setting: the symbolic execution framework of Java PathFinder. First we describe the implementations of both approaches and then do an extensive evaluation to show under what circumstances each approach performs well (or not so well). We also illustrate the usefulness of the symbolic execution of strings by finding errors in real-world examples.
Semi-purification procedures of prions from a prion-infected brain using sucrose has no influence on the nonenzymatic glycation of the disease-associated prion isoform

Abstract Previous studies have shown that the Nε-carboxymethyl group is linked to not only one or more N-terminal Lys residues but also to one or more Lys residues of the protease-resistant core region of the pathogenic prion isoform (PrPSc) in prion-infected brains. Using an anti-advanced glycation end product (AGE) antibody, we detected nonenzymatically glycated PrPSc (AGE-PrPSc) in prion-infected brains following concentration by a series of ultracentrifugation steps with a sucrose cushion. In the present study, the levels of in vitro nonenzymatic glycation of PrPSc using sucrose were investigated to determine whether sucrose cushion can artificially and nonenzymatically induce in vitro glycation during ultracentrifugation. The first insoluble pellet fraction following the first ultracentrifugation (PU1st) collected from 263K scrapie-infected brains was incubated with sucrose, glucose or colloidal silica coated with polyvinylpyrrolidone (percoll). None of the compounds in vitro resulted in AGE-PrPSc. Nonetheless, glucose and percoll produced AGEs in vitro from other proteins within PU1st of the infected brains. This reaction could lead to the AGE-modified polymer(s) of nonenzymatic glycation-prone protein(s). This study showed that PrPSc is not nonenzymatically glycated in vitro with sucrose, glucose or percoll and that AGE-modified PrPSc can be isolated and enriched from prion-infected brains.
Heterogeneity and Plasticity of Multiple Myeloma

Modern molecular and cytogenetic approaches have furthered progress in our understanding of MM biology and have led to the development of targeted therapy that has improved management of this incurable disease. Novel agents such as bortezomib, lenalidomide or thalidomide, have increased median survival rates and improved prospects for MM patients resistant to conventional therapy [1, 2]. Despite these therapeutic advances, MM remains a very difficult disease to treat still accompanied by the threat of repeated relapses with a fatal ending. These observations indicate that at least some of the MM cells are not targeted efficiently by current drug therapies. The existence of such persistent populations, called myeloma stem cells (MSC) or myeloma-initiating cells (MIC) has been suspected for more than two decades. However, the cells of origin remain elusive [3-9]. Timeline of growing knowledge about putative MSC is displayed in Figure 1. Discrepancies among myeloma stem cell concepts have arisen in parallel with the high phenotypic heterogeneity of clonal PCs that might be another factor contributing to the failure of therapies and identification of the population responsible for relapse. Myeloma PCs strongly depends on the supportive role of the bone marrow (BM) microenvironment (MEV) – it is a source of essential growth factors, supports survival and dissemination of pathological PCs [10-14]. Furthermore, hypoxic conditions of tumor microenvironments support tumor progression by inducing angiogenesis, maintaining the malignant phenotype and stimulating osteoclastogenesis [15-18]. There is growing evidence that signals from pathological microenvironments can (reversibly) alter the phenotype of PCs. Such plasticity of PCs might result in obvious heterogeneity of MM and generate inconsistencies among myeloma stem cell concepts.
Sports participation and humeral torsion.

STUDY DESIGN Cross-sectional study. OBJECTIVE To examine differences between arms in humeral torsion in adult and adolescent throwing and nonthrowing athletes, and nonathletic adults. BACKGROUND It is hypothesized that humeral retrotorsion develops by, and is beneficial for, throwing. Thus throwers should demonstrate greater retrotorsion in their dominant arm relative to their nondominant arm and have more side-to-side retrotorsion difference than nonthrowing groups. In addition, adult throwers should have a greater side-to-side retrotorsion difference than adolescent throwers, and swimmers should not demonstrate a retrotorsion difference. METHODS AND MEASURES Using ultrasound to standardize the location of the bicipital groove, the amount of humeral torsion was measured in both arms of male baseball players (85 adult, 35 adolescent), female softball players (16 adult, 37 adolescent), 29 elite adolescent swimmers (19 female), and 16 nonathletic adults (8 female). RESULTS More retrotorsion was found in the dominant arm of almost all throwing athletes, irrespective of their gender or whether they were adults or adolescents (mean+/-SD side-to-side difference, 11.9 degrees+/-10.5 degrees). This difference was less for swimmers (6.4 degrees+/-9.9 degrees) and nonathletic adults (1.3 degrees+/-8.9 degrees). CONCLUSION Greater dominant armhumeral retrotorsion is observed contingent with participation in throwing sports.
A Hierarchical Classification Ant Colony Algorithm for Predicting Gene Ontology Terms

This paper proposes a novel Ant Colony Optimisation algorithm for the hierarchical problem of predicting protein functions using the Gene Ontology (GO). The GO structure represents a challenging case of hierarchical classification, since its terms are organised in a direct acyclic graph fashion where a term can have more than one parent — in contrast to only one parent in tree structures. The proposed method discovers an ordered list of classification rules which is able to predict all GO terms independently of their level. We have compared the proposed method against a baseline method, which consists of training classifiers for each GO terms individually, in five different ion-channel data sets and the results obtained are promising.
Biomechanical changes in the pharynx and upper esophageal sphincter after modified balloon dilatation in brainstem stroke patients with dysphagia

Few studies have investigated the biomechanical changes in the upper esophageal sphincter (UES) and pharyngeal function after successful dilatation therapy for dysphagia. Using high‐resolution manometry (HRM), we examined the biomechanical properties of swallowing in brainstem stroke patients with dysphagia following modified balloon dilation therapy.
Comparison of field methods to estimate fat mass in children

Background: Reliable field methods to measure fat mass (FM) in children may contribute to primary prevention of childhood obesity. Aim: The objective was to compare the accuracy of existing field methods (skinfold thickness (SF), leg-to-leg bioelectrical impedance analysis (BIA), anthropometrics for FM measurement in prepubertal European children. Subjects and methods: Reference FM was measured in 55 French children (30 boys, 25 girls; mean age 8.7 years) using a three-compartment model: body volume (BV) was assessed by air displacement plethysmography (ADP) and total body water (TBW) was assessed by deuterium dilution. Agreement between field methods and the reference method was assessed using Bland–Altman analyses. Since field methods for FM measurement are reported to be population-dependent, adjustment to the study population was performed using stepwise multiple linear regressions modelling. Results: Even after adjustment, field methods exhibited a high correlation (R2 = 0.71–0.84) but a moderate agreement (±3.32 to ±4.47 kg for fat mass) with the reference model. Methods based on BIA or SF performed slightly better than those based on anthropometry. Conclusions: Field methods for FM measurement may be recommended for epidemiological applications, but not for individual follow-up. New field equipment is required to improve accuracy of FM measurement in children and make individual follow-up possible.
Steganalysis with mismatched covers: do simple classifiers help?

Modern steganalysis can be incredibly sensitive and accurate, but only in an artificial setting in which the training data is from the exact same image source as the data being tested. When faced with mismatched training data, performance degrades, often substantially. Some recent publications have advocated the use of very simple classifiers for steganalysis. It is folklore from the machine learning literature that simple classifiers may be more robust to variations between training and testing data, and this paper investigates whether this is true for steganalysis also. Simple classifiers are compared with the classic complex Kernel Support Vector Machine, faced with training data which is mismatched with the testing data. A real-world source of images is used.
The accuracy of guided surgery via mucosa-supported stereolithographic surgical templates in the hands of surgeons with little experience.

OBJECTIVES This prospective study analyzed the accuracy of implant placement with mucosa-supported stereolithographic guides, executed by inexperienced surgeons supervised by an experienced colleague. MATERIAL AND METHODS For the accuracy analysis, 75 OsseoSpeed implants™, placed in 17 fully edentulous jaws (16 patients) using a mucosa-supported stereolithographic guide (IMPLANT SAFE Guide, DENTSPLY Implants) and the Facilitate™ protocol, were included. DICOM images of the pre-surgical planning and the post-surgical CBCT were matched using the Mimics(®) software (Materialise Dental). These data were compared with the data (12 jaws, 52 implants) of an experienced surgeon (Vercruyssen et al. Journal of Clinical Periodontology 2014; doi:10.1111/jcpe.12231). RESULTS The global deviation at the coronal and apical point was 0.9 mm (SD 0.5) and 1.1 mm (SD 0.5), respectively. Depth deviations were 0.5 mm (SD 0.5) and 1.1 mm (SD 0.5), respectively, and the angular deviation was 2.8° (SD 1.5°). These deviations were statistically not inferior to the deviations of the experienced surgeon and also within the range of deviations reported by several systematic reviews. CONCLUSION Within the limitations of this study and for the above-mentioned surgical protocol, inexperience of the surgeon had no influence on the accuracy of implant placement in fully edentulous jaws, when all steps needed for the procedure are supervised by experienced dentists.
Strong pinning of triple junction migration for robust high strain nanostructures

ABSTRACT The universality of a key recovery mechanism: triple junction migration in high strain nanostructures is revealed herein. This migration is the only means to uniformly coarsen deformed lamellar microstructures. Migration of medium to high angle geometrically necessary boundaries at triple junctions is resisted by strong pinning phenomena. Pinning by low angle dislocation boundaries is the novel mechanism that greatly adds to the solute drag of these higher angle boundaries during migration at triple junctions. Solutes furthermore cause a significant increase in the dislocation density of the low angle boundaries formed during deformation and thus greatly enhance the observed pinning. Boundary pinning by dislocation boundaries and solute drag is analysed for deformed Ni of different purities via in and ex situ electron microscopy. A kinetic model is utilised to obtain activation energies that quantitatively demonstrate the strength of this pinning. A new strategy for achieving robust nanostructured metals is developed based on solute and dislocation pinning of triple junction migration – a universal recovery mechanism in deformed lamellar microstructures.
Exenatide improves both hepatic and adipose tissue insulin resistance: A dynamic positron emission tomography study

Glucagon‐like peptide 1 (GLP‐1) receptor agonists (GLP‐1‐RAs) act on multiple tissues, in addition to the pancreas. Recent studies suggest that GLP‐1‐RAs act on liver and adipose tissue to reduce insulin resistance (IR). Thus, we evaluated the acute effects of exenatide (EX) on hepatic (Hep‐IR) and adipose (Adipo‐IR) insulin resistance and glucose uptake. Fifteen male subjects (age = 56 ± 8 years; body mass index = 29 ± 1 kg/m2; A1c = 5.7 ± 0.1%) were studied on two occasions, with a double‐blind subcutaneous injection of EX (5 μg) or placebo (PLC) 30 minutes before a 75‐g oral glucose tolerance test (OGTT). During OGTT, we measured hepatic (HGU) and adipose tissue (ATGU) glucose uptake with [18F]2‐fluoro‐2‐deoxy‐D‐glucose/positron emission tomography, lipolysis (RaGly) with [U‐2H5]‐glycerol, oral glucose absorption (RaO) with [U‐13C6]‐glucose, and hepatic glucose production (EGP) with [6,6‐2H2]‐glucose. Adipo‐IR and Hep‐IR were calculated as (FFA0‐120min) × (Ins0‐120min) and (EGP0‐120min) × (Ins0‐120min), respectively. EX reduced RaO, resulting in reduced plasma glucose and insulin concentration from 0 to 120 minutes postglucose ingestion. EX decreased Hep‐IR (197 ± 28 to 130 ± 37; P = 0.02) and increased HGU of orally administered glucose (23 ± 4 to 232 ± 89 [μmol/min/L]/[μmol/min/kg]; P = 0.003) despite lower insulin (23 ± 5 vs. 41 ± 5 mU/L; P < 0.02). EX enhanced insulin suppression of RaGly by decreasing Adipo‐IR (23 ± 4 to 13 ± 3; P = 0.009). No significant effect of insulin was observed on ATGU (EX = 1.16 ± 0.15 vs. PLC = 1.36 ± 0.13 [μmol/min/L]/[μmol/min/kg]). Conclusion: Acute EX administration (1) improves Hep‐IR, decreases EGP, and enhances HGU and (2) reduces Adipo‐IR, improves the antilipolytic effect of insulin, and reduces plasma free fatty acid levels during OGTT. (Hepatology 2016;64:2028‐2037).
Role of CTCF Binding Sites in the Igf2/H19 Imprinting Control Region

ABSTRACT A ∼2.4-kb imprinting control region (ICR) regulates somatic monoallelic expression of the Igf2 and H19 genes. This is achieved through DNA methylation-dependent chromatin insulator and promoter silencing activities on the maternal and paternal chromosomes, respectively. In somatic cells, the hypomethylated maternally inherited ICR binds the insulator protein CTCF at four sites and blocks activity of the proximal Igf2 promoter by insulating it from its distal enhancers. CTCF binding is thought to play a direct role in inhibiting methylation of the ICR in female germ cells and in somatic cells and, therefore, in establishing and maintaining imprinting of the Igf2/H19 region. Here, we report on the effects of eliminating ICR CTCF binding by severely mutating all four sites in mice. We found that in the female and male germ lines, the mutant ICR remained hypomethylated and hypermethylated, respectively, showing that the CTCF binding sites are dispensable for imprinting establishment. Postfertilization, the maternal mutant ICR acquired methylation, which could be explained by loss of methylation inhibition, which is normally provided by CTCF binding. Adjacent regions in cis—the H19 promoter and gene—also acquired methylation, accompanied by downregulation of H19. This could be the result of a silencing effect of the methylated maternal ICR.
Boolean satisfiability in electronic design automation

Boolean Satisfiability (SAT) is often used as the underlying model for a significant and increasing number of applications in Electronic Design Automation (EDA) as well as in many other fields of Computer Science and Engineering. In recent years, new and efficient algorithms for SAT have been developed, allowing much larger problem instances to be solved. SAT “packages” are currently expected to have an impact on EDA applications similar to that of BDD packages since their introduction more than a decade ago. This tutorial paper is aimed at introducing the EDA professional to the Boolean satisfiability problem. Specifically, we highlight the use of SAT models to formulate a number of EDA problems in such diverse areas as test pattern generation, circuit delay computation, logic optimization, combinational equivalence checking, bounded model checking and functional test vector generation, among others. In addition, we provide an overview of the algorithmic techniques commonly used for solving SAT, including those that have seen widespread use in specific EDA applications. We categorize these algorithmic techniques, indicating which have been shown to be best suited for which tasks.