Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating the Technology of Cognitive and Noncognitive Skill Formation

This paper formulates and estimates multistage production functions for child cognitive and noncognitive skills. Output is determined by parental environments and investments at different stages of childhood. We estimate the elasticity of substitution between investments in one period and stocks of skills in that period to assess the benefits of early investment in children compared to later remediation. We establish nonparametric identification of a general class of nonlinear factor models. A by-product of our approach is a framework for evaluating childhood interventions that does not rely on arbitrarily scaled test scores as outputs and recognizes the differential effects of skills in different tasks. Using the estimated technology, we determine optimal targeting of interventions to children with different parental and personal birth endowments. Substitutability decreases in later stages of the life cycle for the production of cognitive skills. It increases in later stages of the life cycle for the production of noncognitive skills. This finding has important implications for the design of policies that target the disadvantaged. For some configurations of disadvantage and outcomes, it is optimal to invest relatively more in the later stages of childhood.
Surface energy of fusion bonded silicon nitride to silicon

Transfer of silicon nitride (nitride) membranes to silicon has been performed using hydrophilic fusion bonding. Dry and wet oxidation of the nitride was compared to unoxidized nitride, and silicon-silicon references. Measurements of the surface energies by Ihe blade test indicated that both dry and wet oxidation of the nitride was beneficial to the bond strength increasing the surface energy from 8 mJ/m 2 to more than 50 mJ/m 2 . Voids, probably caused by trapped gas, were observed at the bonded interface after bond annealing. The dry oxidized nitride wafers showed less voids than the wet oxidized nitride wafers. The nitride film was successfully transferred to a second silicon wafer by KOH etching. After etching, one wafer was diced into 8×8mm 2 squares without signs of film delamination. This indicates high bond strength.
In silico generation of novel, drug-like chemical matter using the LSTM neural network

The exploration of novel chemical spaces is one of the most important tasks of cheminformatics when supporting the drug discovery process. Properly designed and trained deep neural networks can provide a viable alternative to brute-force de novo approaches or various other machine-learning techniques for generating novel drug-like molecules. In this article we present a method to generate molecules using a long short-term memory (LSTM) neural network and provide an analysis of the results, including a virtual screening test. Using the network one million drug-like molecules were generated in 2 hours. The molecules are novel, diverse (contain numerous novel chemotypes), have good physicochemical properties and have good synthetic accessibility, even though these qualities were not specific constraints. Although novel, their structural features and functional groups remain closely within the drug-like space defined by the bioactive molecules from ChEMBL. Virtual screening using the profile QSAR approach confirms that the potential of these novel molecules to show bioactivity is comparable to the ChEMBL set from which they were derived. The molecule generator written in Python used in this study is available on request.
Data retention fault in SRAM memories: analysis and detection procedures

In this paper, we present a novel study on data retention faults (DRFs) in SRAM memories. We analyze in detail the electrical origins of these faults, starting from the most common till those that lead to what we have called hard to detect DRFs. In general, DRFs are supposed to be produced by very high resistive-open defects that affect the refreshment loop of the core-cell. We demonstrate that lower values of resistance may produce hard to detect DRFs. Moreover, each resistive-open defect produces a particular faulty behavior of the core-cell that changes for different ranges of the resistive value. We analyze different cases and we propose for each one an efficient test procedure based on March tests. In particular, we propose to stimulate the defective cells in some cases by indirect accesses and in some other cases by emphasizing natural noise phenomenon of SRAM memories (such as the ground bounce).
Decentralised particle filtering for multiple target tracking in wireless sensor networks

This paper presents algorithms for consistent joint localisation and tracking of multiple targets in wireless sensor networks under the decentralised data fusion (DDF) paradigm where particle representations of the state posteriors are communicated. This work differs from previous work as more generalised methods have been developed to account for correlated estimation errors that arise due to common past information between two discrete particle sets. The particle sets are converted to continuous distributions for communication and inter-nodal fusion. Common past information is then removed by a division operation of two estimates so that only new information is updated at the node. In previous work, the continuous distribution used was limited to a Gaussian kernel function. This new method is compared to the optimal centralised solution where each node sends all observation information to a central fusion node when received. Results presented include a real-time application of the DDF operation of division on data logged from field trials.
Block-quantized kernel matrix for fast spectral embedding

Eigendecomposition of kernel matrix is an indispensable procedure in many learning and vision tasks. However, the cubic complexity O(N3) is impractical for large problem, where N is the data size. In this paper, we propose an efficient approach to solve the eigendecomposition of the kernel matrix W. The idea is to approximate W with W that is composed of m2 constant blocks. The eigenvectors of W, which can be solved in O(m3) time, is then used to recover the eigenvectors of the original kernel matrix. The complexity of our method is only O(mN + m3), which scales more favorably than state-of-the-art low rank approximation and sampling based approaches (O(m2N + m3)), and the approximation quality can be controlled conveniently. Our method demonstrates encouraging scaling behaviors in experiments of image segmentation (by spectral clustering) and kernel principal component analysis.
Does Organizational Support Promote Citizenship in Service Settings? The Moderating Role of Service Climate

ABSTRACT The present study integrates social exchange, role theory, and climate research to suggest that employees who have contact with customers (“contact employees”) will reciprocate felt obligations of high-quality employment relationships (i.e., perceived organizational support [POS]). They do this by expanding their role in ways that are consistent with contextual behavioral expectations. A longitudinal survey of 1,387 contact employees and 666 supervisors in a large supermarket chain in Taiwan demonstrated that the positive relationship between POS and service-oriented organizational citizenship behavior (SOCB) role definitions was strengthened by service climate. In summary, organizational support resulted in expanded SOCB role definitions within a strong service climate, while this relationship was much weaker and not significant in weak service climate. I discuss theoretical and managerial implications through this empirical examination.
Development of cytochrome b and an active oxidase system in association with maturation of a human promyelocytic (HL-60) cell line

The human HL-60 myeloid leukaemia cell line developed, during maturational changes induced by dimethyl sulphoxide, an enhanced capacity for phorbol myristate acetate- stimulated oxidative activity and acquired a cytochrome b. Titration of the absorbance at 559 nm at potentials of-190 to -370 mV indicated that this cytochrome had a very low potential, differentiating it from mitochondrial and endoplasmic reticulum cytochromes and identifying it as the cytochrome b(-245) that has been recently found in other phagocytic cells. Subcellular fractionation studies of mature HL-60 cells showed that cytochrome b had a dual distribution within the cell. The lighter peak of activity was associated with the plasma membrane markers, adenylate cyclase and receptors for the N- formal-L-methionyl-L-leucyl-L-phenylalanine (f-Met-Leu-Phe) peptide. The denser components localized with the mitochondria but were distinct from mitochondrial cytochromes because whereas the activity of cytochrome c oxidase fell during HL-60 cell maturation, that of this cytochrome b was markedly increased. Concentrations of myeloperoxidase were unrelated to activity of the oxidase system and decreased as the cell matured. The increase in the concentrations of cytochrome b with cellular maturation parallelled the increase in the stimulated nonmitochondrial respiratory activity of these cells. The turnover of the hexose monophosphate shunt of immature cells was increased by the oxidising agents, methylene blue and tert-butylhydroperoxide, indicating that these immature cells have stimulated nonmitochondrial respiratory activity by maturing HL-60 cells is associated with, and is probably dependent upon, the acquisition by these cells of the cytochrome b(-245) oxidase system.
Development and Intratumoral Distribution of Block Copolymer Micelles as Nanomedicines for the Targeted Delivery of Chemotherapy to Solid Tumors

Recent advancements in pharmaceutical technology based on principles of nanotechnology, polymer chemistry, and biomedical engineering have resulted in the creation of novel drug delivery systems with the potential to revolutionize current strategies in cancer chemotherapy. In oncology, realization of significant improvements in therapeutic efficacy requires minimization of drug exposure to healthy tissues and concentration of the drug within the tumor. As such, encapsulation of chemotherapeutic agents inside nanoparticles capable of enhancing tumor-targeted drug delivery is a particularly promising innovation. Yet, initial investigations into the intratumoral fate of nanomedicines have suggested that they may be heterogeneously distributed and achieve limited access to cancer cells located distant from the tumor vasculature. As such, uncovering the determinants of nanoparticle transport at the intratumoral level is
The role of folate receptor α in cancer development, progression and treatment: Cause, consequence or innocent bystander?

Folate receptor α (FRα) is a membrane‐bound protein with high affinity for binding and transporting physiologic levels of folate into cells. Folate is a basic component of cell metabolism and DNA synthesis and repair, and rapidly dividing cancer cells have an increased requirement for folate to maintain DNA synthesis, an observation supported by the widespread use of antifolates in cancer chemotherapy. FRα levels are high in specific malignant tumors of epithelial origin compared to normal cells, and are positively associated with tumor stage and grade, raising questions of its role in tumor etiology and progression. It has been suggested that FRα might confer a growth advantage to the tumor by modulating folate uptake from serum or by generating regulatory signals. Indeed, cell culture studies show that expression of the FRα gene, FOLR1, is regulated by extracellular folate depletion, increased homocysteine accumulation, steroid hormone concentrations, interaction with specific transcription factors and cytosolic proteins, and possibly genetic mutations. Whether FRα in tumors decreases in vivo among individuals who are folate sufficient, or whether the tumor's machinery sustains FRα levels to meet the increased folate demands of the tumor, has not been studied. Consequently, the significance of carrying a FRα‐positive tumor in the era of folic acid fortification and widespread vitamin supplement use in countries such as Canada and the United States is unknown. Epidemiologic and clinical studies using human tumor specimens are lacking and increasingly needed to understand the role of environmental and genetic influences on FOLR1 expression in tumor etiology and progression. This review summarizes the literature on the complex nature of FOLR1 gene regulation and expression, and suggests future research directions. © 2006 Wiley‐Liss, Inc.
Cluster-Based Cooperative Spectrum Sensing in Cognitive Radio Systems

In cognitive radio systems, secondary users can be coordinated to perform cooperative spectrum sensing so as to detect the primary user more accurately. However, when the sensing observations are forwarded to a common receiver through fading channels, the sensing performance can be severely degraded. In this paper, we propose a cluster-based cooperative spectrum sensing method to improve the sensing performance. By separating all the secondary users into a few clusters and selecting the most favorable user in each cluster to report to the common receiver, the proposed method can exploit the user selection diversity so that the sensing performance can be enhanced. Furthermore, decision fusion and energy fusion are both studied and the analytical performance results are given. Numerical results show that the sensing performance is improved significantly as opposed to conventional spectrum sensing.
Role of the Transcriptional Regulator RamB (Rv0465c) in the Control of the Glyoxylate Cycle in Mycobacterium tuberculosis

ABSTRACT Mycobacterium tuberculosis generally is assumed to depend on lipids as a major carbon and energy source when persisting within the host. The utilization of fatty acids requires a functional glyoxylate cycle with the key enzymes isocitrate lyase (Icl) and malate synthase. The open reading frame Rv0465c of M. tuberculosis H37Rv encodes a protein with significant sequence similarity to the transcriptional regulator RamB, which in Corynebacterium glutamicum controls the expression of several genes involved in acetate metabolism, i.e., those encoding enzymes of acetate activation and the glyoxylate cycle. We show here that the M. tuberculosis Rv0465c protein can functionally complement RamB in C. glutamicum and that it binds to the promoter regions of M. tuberculosis icl1 and Rv0465c. Construction and subsequent transcriptional and enzymatic analysis of a defined Rv0465c deletion mutant in M. tuberculosis revealed that the Rv0465c protein, now designated RamB, represses icl1 expression during growth with glucose and negatively autoregulates the expression of its own operon. Whole-genome microarray analysis of the M. tuberculosis ramB (ramBMT ) mutant and the wild type furthermore showed that apart from icl1 and the ramBMT operon, the expression of all other M. tuberculosis genes involved in acetate metabolism remain unchanged in the mutant. Thus, RamBMT has a more specific regulatory function as RamB from C. glutamicum and is confined to expression control of icl1 and the ramBMT operon.
A Segmentation Matrix Method for Chinese Segmentation Ambiguity Analysis

Chinese Segmentation Ambiguity (CSA) is a fundamental problem confronted when processing Chinese language, where a sentence can generate more than one segmentation paths. Two techniques are commonly used to identify CSA: Omni-segmentation and Bi-directional Maximum Matching (BiMM). Due to the high computational complexity, Omni-segmentation is difficult to be applied for big data. BiMM is easier to be implemented and has a higher speed. However, recall of BiMM is much lower. In this paper, a Segmentation Matrix (SM) method is presented, which encodes each sentence as a matrix, then maps string operation into set operations. To identify CSA, instead of scanning a whole sentence, only specific areas of the matrix are checked. SM has a computational complexity close to BiMM with recall the same as Omni-segmentation. In addition to CSA identification, SM also supports lexicon-based Chinese word segmentation. In our experiments, based on SM, several issues about CSA are explored. The result shows that SM is useful for CSA analysis.
Middle Cerebral Artery Bifurcation Aneurysms: An Anatomic Classification Scheme for Planning Optimal Surgical Strategies

BACKGROUND: Changing landscapes in neurosurgical training and increasing use of endovascular therapy have led to decreasing exposure in open cerebrovascular neurosurgery. To ensure the effective transition of medical students into competent practitioners, new training paradigms must be developed. OBJECTIVE: Using principles of pattern recognition, we created a classification scheme for middle cerebral artery (MCA) bifurcation aneurysms that allows their categorization into a small number of shape pattern groups. METHODS: Angiographic data from patients with MCA aneurysms between 1995 and 2012 were used to construct 3-dimensional models. Models were then analyzed and compared objectively by assessing the relationship between the aneurysm sac, parent vessel, and branch vessels. Aneurysms were then grouped on the basis of the similarity of their shape patterns in such a way that the in-class similarities were maximized while the total number of categories was minimized. For each category, a proposed clip strategy was developed. RESULTS: From the analysis of 61 MCA bifurcation aneurysms, 4 shape pattern categories were created that allowed the classification of 56 aneurysms (91.8%). The number of aneurysms allotted to each shape cluster was 10 (16.4%) in category 1, 24 (39.3%) in category 2, 7 (11.5%) in category 3, and 15 (24.6%) in category 4. CONCLUSION: This study demonstrates that through the use of anatomic visual cues, MCA bifurcation aneurysms can be grouped into a small number of shape patterns with an associated clip solution. Implementing these principles within current neurosurgery training paradigms can provide a tool that allows more efficient transition from novice to cerebrovascular expert. ABBREVIATIONS: DSA, digital subtraction angiography MCA, middle cerebral artery
The Importance of Estimating Implied Volatility Functions Using the Relevant Loss Function

We investigate the importance of appropriately de ̄ning the loss function used for the estimation of parameters in option pricing models. The implementation of the models is (implicitly or explicitly) always part of a two-step procedure. In a ̄rst step, one estimates the parameters and in a second step, one uses the parameters for model evaluation (pricing out-of-sample). The paper argues that the loss functions used in the in-sample and out-of-sample exercises should be identical to obtain the lowest possible out-of-sample loss. To illustrate the quantitative importance of this methodological issue, we investigate various Mean-Squared-Errors (MSE) for the practitioner BlackScholes model proposed by Dumas, Fleming and Whaley (1997). We demonstrate that when we use the appropriate loss functions to estimate the out-of-sample MSE of the model can be dramatically reduced. Because this model is used as a benchmark in the option pricing literature, these ̄ndings have important implications for the evaluation of existing and future option pricing models. JEL Classi ̄cation: G12
An alternating treatment comparison of minimal and maximal opposition sound selection in Turkish phonological disorders

A single-subject alternating treatment design in combination with a staggered multiple baseline model across subjects was implemented with two 6:0 year-old girls, monozygotic twins, who were referred to a university clinic for evaluation and treatment. The treatment programme was structured according to variants of minimal pair contrast treatment in which the target sounds and their oppositions were selected according to either minimal or maximal opposition (including major-class differences) contrast treatments to evaluate which of the sound selection strategy would result in better learning. Independent variables were the minimal and maximal opposition conditions; dependent variables were the target phonemes treated. Consistent with the literature, maximal opposition treatment resulted in significantly greater changes in the sound systems of the twins than minimal opposition treatment.
One dimensional photonic crystal for label-free and fluorescence sensing application

The development of more sensitive and more reliable sensors aids medical applications in many fields as diseases detection or therapy progress. This thesis threats the development of an optical biosensor based on electromagnetic modes propagating at the interface between a finite one-dimensional photonic crystal (1DPC) and a homogeneous external medium, also named Bloch Surface Waves (BSW). BSW have emerged as an attractive approach for label-free sensing in plasmon-like sensor configurations. Besides label-free operation, the large field enhancement and the absence of quenching allow the use of BSW to excite fluorescent labels that are in proximity of the 1DPC surface. This approach was adapted to the case of angularly resolved resonance detection, thus giving rise to a combined label-free/labelled biosensor platform. BSW present many degrees of design freedomthat enable tuning of resonance properties. In order to obtain a figure of merit for an optimization, I investigated the measurement uncertainty depending on resonance width and depth with different numericalmodels. This has led to a limit of detection that can assist the choice of the best design to use. Two tumor biomarkers, such as vascular endothelial growth factor (VEGF) and Angiopoietin-2 (Ang2), have been considered to be detected with the BSW biosensing platform. For this purpose the specific antibodies for the two tumor biomarkers were immobilized on the 1DPC biochip surface. The conclusive experiments reported in this work demonstrated the successful detection of the VEGF biomarker in complex matrices, such as cell culture supernatants and human plasma samples. Moreover, the platformwas used to determinate Ang2 concentration in untreated human plasma samples using low volumes, 300 μL, and with short turnaround times, 30 minutes. This is the first BSW based biosensor assay for the determination of tumor biomarker in human plasma samples at clinically relevant concentrations.
Some Impossibility Results for Budgeted Learning

We prove two impossibility results for budgeted learning with linear predictors. The first result shows that no budgeted learning algorithm can in general learn an -accurate d-dimensional linear predictor while observing less than d/ attributes at training time. Our second result deals with the setting studied by Greiner et al. (2002), where the learner has all the information at training time and at test time he has to form a prediction after observing a fixed amount of attributes per each instance. We formally prove that while it is possible to learn a consistent predictor accessing at most two attributes of each example at training time, it is not possible (even with an infinite amount of training examples) to build an active classifier that uses at most two attributes of each example at test time, and whose error will be smaller than a constant.