Miracle-dz/UniFAR-FTUs huggingface dataset:
From simplistic to complex systems in economics

The applicability of complex systems theory in economics is evaluated and compared with standard approaches to economic theorising based upon constrained optimisation. A complex system is defined in the economic context and differentiated from complex systems in physio-chemical and biological settings. It is explained why it is necessary to approach economic analysis from a network, rather than a production and utility function perspective, when we are dealing with complex systems. It is argued that much of heterodox thought, particularly in neo-Schumpeterian and neo-Austrian evolutionary economics, can be placed within a complex systems perspective upon the economy. The challenge is to replace prevailing 'simplistic' theories, based in constrained optimisation, with 'simple' theories, derived from network representations in which value is created through the establishment of new connections between elements.
Interpolated Dirichlet Class Language Model for Speech Recognition Incorporating Long-distance N-grams

We propose a language modeling (LM) approach incorporating interpolated distancedn-grams in a Dirichlet class language model (DCLM) (Chien and Chueh, 2011) for speech recognition. The DCLM relaxes the bag-of-words assumption and documents topic extraction of latent Dirichlet allocation (LDA). The latent variable of DCLM reflects the class information of ann-gram event rather than the topic in LDA. The DCLM model uses default background n-grams where class information is extracted from the (n-1) history words through Dirichlet distribution in calculating n-gram probabilities. The model does not capture the long-range information from outside of the n-gram window that can improve the language modeling performance. In this paper, we present an interpolated DCLM (IDCLM) by using different distanced n-grams. Here, the class information is exploited from (n-1) history words through the Dirichlet distribution using interpolated distanced n-grams. A variational Bayesian procedure is introduced to estimate the IDCLM parameters. We carried out experiments on a continuous speech recognition (CSR) task using the Wall Street Journal (WSJ) corpus. The proposed approach shows significant perplexity and word error rate (WER) reductions over the other approach.
Localized delimited release: combining the what and where dimensions of information release

Information release (or declassification) policies are the key challenge for language-based information security. Although much progress has been made, different approaches to information release tend to address different aspects of information release. In a recent classification, these aspects are referred to as what, who, where, and when dimensions of declassification. In order to avoid information laundering, it is important to combine defense along the different dimensions. As a step in this direction, this paper presents a combination of what and where information release policies. Moreover, we show that a minor modification of a security type system from the literature (which was designed for treating the what dimension) in fact enforces the combination of what and where policies
Deep Kalman Filters

Kalman Filters are one of the most influential models of time-varying phenomena. They admit an intuitive probabilistic interpretation, have a simple functional form, and enjoy widespread adoption in a variety of disciplines. Motivated by recent variational methods for learning deep generative models, we introduce a unified algorithm to efficiently learn a broad spectrum of Kalman filters. Of particular interest is the use of temporal generative models for counterfactual inference. We investigate the efficacy of such models for counterfactual inference, and to that end we introduce the "Healing MNIST" dataset where long-term structure, noise and actions are applied to sequences of digits. We show the efficacy of our method for modeling this dataset. We further show how our model can be used for counterfactual inference for patients, based on electronic health record data of 8,000 patients over 4.5 years.
Genome-wide association analysis of anti-TNF drug response in patients with rheumatoid arthritis

Background Treatment strategies blocking tumour necrosis factor (anti-TNF) have proven very successful in patients with rheumatoid arthritis (RA). However, a significant subset of patients does not respond for unknown reasons. Currently, there are no means of identifying these patients before treatment. This study was aimed at identifying genetic factors predicting anti-TNF treatment outcome in patients with RA using a genome-wide association approach. Methods We conducted a multistage, genome-wide association study with a primary analysis of 2 557 253 single-nucleotide polymorphisms (SNPs) in 882 patients with RA receiving anti-TNF therapy included through the Dutch Rheumatoid Arthritis Monitoring (DREAM) registry and the database of Apotheekzorg. Linear regression analysis of changes in the Disease Activity Score in 28 joints after 14 weeks of treatment was performed using an additive model. Markers with p<10−3 were selected for replication in 1821 patients from three independent cohorts. Pathway analysis including all SNPs with p<10−3 was performed using Ingenuity. Results 772 markers showed evidence of association with treatment outcome in the initial stage. Eight genetic loci showed improved p value in the overall meta-analysis compared with the first stage, three of which (rs1568885, rs1813443 and rs4411591) showed directional consistency over all four cohorts studied. We were unable to replicate markers previously reported to be associated with anti-TNF outcome. Network analysis indicated strong involvement of biological processes underlying inflammatory response and cell morphology. Conclusions Using a multistage strategy, we have identified eight genetic loci associated with response to anti-TNF treatment. Further studies are required to validate these findings in additional patient collections.
Ribonucleases J1 and J2: two novel endoribonucleases in B.subtilis with functional homology to E.coli RNase E

Many prokaryotic organisms lack an equivalent of RNase E, which plays a key role in mRNA degradation in Escherichia coli. In this paper, we report the purification and identification by mass spectrometry in Bacillus subtilis of two paralogous endoribonucleases, here named RNases J1 and J2, which share functional homologies with RNase E but no sequence similarity. Both enzymes are able to cleave the B.subtilis thrS leader at a site that can also be cleaved by E.coli RNase E. We have previously shown that cleavage at this site increases the stability of the downstream messenger. Moreover, RNases J1/J2 are sensitive to the 5′ phosphorylation state of the substrate in a site-specific manner. Orthologues of RNases J1/J2, which belong to the metallo-β-lactamase family, are evolutionarily conserved in many prokaryotic organisms, representing a new family of endoribonucleases. RNases J1/J2 appear to be implicated in regulatory processing/maturation of specific mRNAs, such as the T-box family members thrS and thrZ, but may also contribute to global mRNA degradation.
Changing Sibling Relationships After Parents' Death: The Role of Solidarity and Kinkeeping

Background The solidarity hypothesis predicts a short‐term strengthening of sibling relationships after parental death, whereas the kinkeeping hypothesis predicts a long‐term weakening of sibling relationships after parental death. Method Hypotheses were tested with fixed effects regression models using four waves of the Netherlands Kinship Panel Study (2003–2015; N = 3,812 respondents), a nationally representative sample of individuals in the Netherlands. This survey combined data on sibling ties with data on intergenerational ties to (surviving) parents. Results Consistent with the solidarity hypothesis, results showed that sibling contact intensified after parental death. The increase lasted longer after losing the first parent and was partially explained by changes in contact with and support to the surviving parent. After the death of the second parent, contact and conflict between siblings increased, but these effects were short‐lived. In line with the kinkeeping hypothesis, sibling relations among adult orphans faded in the long run. Conclusion Changes in horizontal ties between siblings followed to a large extent from changes in vertical ties between siblings and their parents. Implications Sibling ties can be understood better when they are studied in the context of the larger family network.
BulkCommit: Scalable and fast commit of atomic blocks in a lazy multiprocessor environment

To help improve the programmability and performance of shared-memory multiprocessors, there are proposals of architectures that continuously execute atomic blocks of instructions — also called Chunks. To be competitive, these architectures must support chunk operations very efficiently. In particular, in a large manycore with lazy conflict detection, they must support efficient chunk commit. This paper addresses the challenge of providing scalable and fast chunk commit for a large manycore in a lazy environment. To understand the problem, we first present a model of chunk commit in a distributed directory protocol. Then, to attain scalable and fast commit, we propose two general techniques: (1) Serialization of the write sets of output-dependent chunks to avoid squashes and (2) Full parallelization of directory module ownership by the committing chunks. Our simulation results with 64-threaded codes show that our combined scheme, called BulkCommit, eliminates most of the squash and commit stall times, speeding-up the codes by an av­erage of 40% and 18% compared to previously-proposed schemes.
Reducing test data volume using LFSR reseeding with seed compression

A new lossless test vector compression scheme is presented which combines linear feedback shift register (LFSR) reseeding and statistical coding in a powerful way. Test vectors can be encoded as LFSR seeds by solving a system of linear equations. The solution space of the linear equations can be quite large. The proposed method takes advantage of this large solution space to find seeds that can be efficiently encoded using a statistical code. Two architectures for implementing LFSR reseeding with seed compression are described. One configures the scan cells themselves to perform the LFSR functionality while the other uses a new idea of "scan windows" to allow the use of a small separate LFSR whose size is independent of the number of scan cells. The proposed scheme can be used either for applying a fully deterministic test set or for mixed-mode built-in self-test (BIST), and it can be used in conjunction with other variations of LFSR reseeding that have been previously proposed to further improve the encoding efficiency.
Radiation response of Al2O3-based MOS capacitors under different bias conditions

We present for the first time real-time γ-ray (60Co) radiation response of MOS capacitors with an atomic layer deposited Al2O3 as insulating layer under different bias conditions. Preirradiation electrical characterization showed voltage instability due to tunneling transitions between the substrate and preexisting defects inside the dielectric layer. Real-time capacitance-voltage (C-V) measurements along irradiation showed two distinguishable regions: For short times, the response is strongly bias dependent (positive voltage shift for positive bias and the opposite for negative bias) with a shape linear with log(t), while for long times the voltage shift is always negative with a linear dependence with dose. This behavior can be explained and reproduced by a physical model that takes into account the superposition of a bias-induced electron trapping/detrapping by tunneling transitions with the substrate (as without radiation) and a radiation-induced hole capture.
Elevated Admission Glucose and Mortality in Patients With Acute Pulmonary Embolism

OBJECTIVE Although associated with adverse outcomes in other cardiopulmonary conditions, the prognostic value of elevated glucose in patients with acute pulmonary embolism (PE) is unknown. We sought to examine the association between glucose levels and mortality and hospital readmission rates for patients with PE. RESEARCH DESIGN AND METHODS We evaluated 13,621 patient discharges with a primary diagnosis of PE from 185 acute care hospitals in Pennsylvania (from January 2000 to November 2002). Admission glucose levels were analyzed as a categorical variable (≤110, >110–140, >140–170, >170–240, and >240 mg/dL). The outcomes were 30-day all-cause mortality and hospital readmission. We used random-intercept logistic regression to assess the independent association between admission glucose levels and mortality and hospital readmission, adjusting for patient (age, sex, race, insurance, comorbid conditions, severity of illness, laboratory parameters, and thrombolysis) and hospital (region, size, and teaching status) factors. RESULTS Elevated glucose (>110 mg/dL) was present in 8,666 (63.6%) patients. Patients with a glucose level ≤110, >110–140, >140–170, >170–240, and >240 mg/dL had a 30-day mortality of 5.6, 8.4, 12.0, 15.6, and 18.3%, respectively (P < 0.001). Compared with patients with a glucose level ≤110 mg/dL, the adjusted odds of dying were greater for patients with a glucose level >110–140 (odds ratio 1.19 [95% CI 1.00–1.42]), >140–170 (1.44 [1.17–1.77]), >170–240 (1.54 [1.26–1.90]), and >240 mg/dL (1.60 [1.26–2.03]), with no difference in the odds of hospital readmission. CONCLUSIONS In patients with acute PE, elevated admission glucose is common and independently associated with short-term mortality.
Black Americans' Implicit Racial Associations And Their Implications for Intergroup Judgment

Abstract Many—though not all—black Americans exhibit an implicit evaluative preference for whites relative to blacks (e.g., Livingston, 2002). Are such biases meaningfully related to blacks' explicit attitudes and actual intergroup judgments? In the present study, 83 black participants who believed they would complete an intellectually challenging task with a partner rated their preferences for (fictitious) black and white potential partners. The less strongly participants implicitly preferred their ingroup, the lower their preference for a black vs. a white work partner. The magnitude of this relationship held even when controlling for explicit attitudes that were related to partner preference. Implicit biases were associated with explicit attitudes regarding black, but not white, persons and with system-justifying ideology (Jost & Banaji, 1994).
Asymptotic Methods in the Probabilistic Analysis of Packing and Partitioning Algorithms

Traditionally, the analysis of computer algorithms has concentrated on combinatorial methods, with the primary objective being worst-case performance bounds. However, in the last 10 years there has been a dramatic increase in the probabilistic analysis of algorithms. One reason is obvious and suggests that the trend will continue: the statistical behavior of an algorithm and the objective it produces is usually more useful than the worst-case behavior, which is frequently determined by pathological problem instances of little practical interest. Another reason is that a broadly applicable collection of problem-solving tools and techniques has developed; currently, there is a major effort in computer science and applied mathematics to extend the methodology and to apply it to classical problems in computer engineering and operations research. These lecture notes describe and illustrate elementary, but fundamental approaches to the probabilistic analysis of combinatorial structures. The theme we have chosen is the class of structures produced by packing and partitioning algorithms. This arena supplies easily stated, but difficult, in fact NP-hard, combinatorial optimization problems that form excellent subjects for probabilistic analysis. Packing and partitioning problems appear in an enormous variety of applications. The resulting, large body of research that has developed around these problems affords many examples of powerful probabilistic techniques. By and large, an exact analysis of the more interesting packing and partitioning algorithms is extremely difficult; success in acquiring insights has relied chiefly on asymptotic methods, which will be a second, parallel theme of our discussion. As we will explain. such methods address more tractable questions. Fir example. an asymptotic analysis normally seeks average-case behavior only in the limit of large problem sizes. Moreover. it may requi re that results be accurate only within unspecified constant factors. The notes start with an introductory section in which problems and notation are defined. The second section describes general approaches along with background results in applied probability; simple illustrations are included. Later sections provide more detailed illusttations drawn from the theories of multiprocessor scheduling and one-dimensional bin packing. • Supponed by NSF Grant DCR 85-09667.
Gene expression profiles of single human mature oocytes in relation to age.

BACKGROUND The development competence of human oocytes declines with increasing age. The objective of this study was to investigate the effect of age on gene expression profile in mature human oocytes. METHODS mRNA was isolated for whole genome gene expression microarray analysis from metaphase II (MII) oocytes donated by IVF or ICSI patients [10 women aged <36 years (younger) and five women aged 37-39 years (both inclusive) (older)] undergoing controlled ovarian stimulation. The oocytes were donated and prepared immediately after recovery from the follicle. RT-PCR on additional four younger and two older oocytes confirmed the array analysis. RESULTS On the basis of 15 independent replicates of single MII oocytes, 7470 genes (10 428 transcripts) were identified as present in the MII oocytes. Of these, 342 genes showed a significantly different expression level between the two age groups; notably, genes annotated to be involved in cell cycle regulation, chromosome alignment (e.g. MAD2L1 binding protein), sister chromatid separation (e.g. separase), oxidative stress and ubiquitination. The top signaling network affected by age was 'cell cycle and organism development' (e.g. SMAD2 and activin B1 receptor). CONCLUSION There is a substantial difference between younger and older oocytes in the transcriptional level of genes involved in central biological functions of the oocytes, thus providing information on processes that may be associated with the ageing phenomenon and possibly contributing to decreased fertility.
Knowledge attitude practice on breast self-examination in a rural area in North Kerala

Background: Breast cancer is the most common cancer in women. It is estimated that 5,08,000 women died due to breast cancer in 2011 globally. Late detection of breast cancer decreased the survival rate to 56% and the 5-year survival rate reached 85% with early detection of breast cancer. Breast self-examination (BSE) is an inexpensive tool which helps women to detect any early changes in their breasts and thus helps to reduce the breast cancer mortality and morbidity. The present study was designed to determine the knowledge, attitude and practice regarding BSE among women aged 25 years and above.Methods: A community-based, cross-sectional study was conducted in rural North Kerala, among 206 women aged ≥25 years selected by cluster sampling. Data was collected using a semi-structured questionnaire.Results: The participants were aged between 25-94 years (mean age 40.15±13.17). 62.6% have heard about BSE. Among the 206 participants, 12% had good knowledge while 10.6% knew the correct technique of doing BSE and only 0.06% knew that BSE must be performed once a month. Though 80.5% have good attitude regarding BSE, only 36% practised BSE and only 0.04% performed it every month. Educational status (high school and below vs higher secondary and above) was found to be significantly associated with knowledge (p<0.001) and practice (p=0.003). Knowledge regarding BSE was significantly associated with practice (p<0.001) while family history of breast cancer was not (p=0.072). Conclusions: The respondents had good attitude regarding BSE but knowledge and practice on BSE were very poor. Educational status has an influence on the knowledge and practice while family history did not have any influence.
SDSS J1534+1615AB: A Novel T Dwarf Binary Found with Keck Laser Guide Star Adaptive Optics and the Potential Role of Binarity in the L/T Transition

We have resolved the newly discovered T dwarf SDSS J153417.05+161546.1 into a 0. ″11 binary using the Keck sodium laser guide star adaptive optics system. With an integrated-light near-IR spectral type of T3.5 ± 0.5, this binary provides a new benchmark for studying the distinctive J-band brightening previously noted among early and mid-T dwarfs, using two brown dwarfs with different spectral types but having a common metallicity and age and very similar surface gravities. We estimate spectral types of T1.5 ± 0.5 and T5.5 ± 0.5 for the two components based on their near-IR colors, consistent with modeling the integrated-light spectrum as the blend of two components. The observed near-IR flux ratios of SDSS J1534+1615 are unique compared to all previously known substellar binaries: the component that is fainter at H and K′ is brighter at J. This inversion of the near-IR fluxes is a manifestation of the J-band brightening within this individual binary system. Therefore, SDSS J1534+1615 demonstrates that the brightening can be intrinsic to ultracool photospheres (e.g., arising from cloud disruption and/or rapid increase in cloud sedimentation) and does not necessarily result from physical variations among the observed ensemble of T dwarfs (e.g., a range in masses, ages, and/or metallicities). We suggest that the apparently large amplitude of the J-band brightening may be due to a high incidence of unresolved binaries and that the true amplitude of the brightening phenomenon could be more modest. This scenario would imply that truly single objects in these spectral subclasses are relatively rare, in agreement with the small effective temperature range inferred for the L/T transition.
Is Crowdsourcing a Source of Worker Empowerment or Exploitation? Understanding Crowd Workers' Perceptions of Crowdsourcing Career

Crowdsourcing offers new forms of work arrangements enabled and facilitated by the advancements in Internet technologies and growing popularity of social media. However, do these new forms of work empower workers to craft their own careers or do they create a sweatshop where workers complete fragmented tasks to earn minimal pay? We posit that career theories and job crafting approaches collectively provide valuable theoretical perspectives for examining this question. By assessing the degree to which these platforms afford or constrain the workers to exert their personal agencies (i.e., affords career and job crafting preferences), we argue, will partially determine whether these new forms of work are a harbinger of worker empowerment or exploitation. Preliminary findings of this exploratory research-in-progress, conducted using two types of workers on Amazon-Mechanical-Turk, reveal that these new forms of work arrangements have a potential for both empowerment and exploitation of workers.
SYSIASS – an intelligent powered wheelchair

This paper explains the motivations and the goals of the SYSIASS project. This project has three major ambitions: to design intelligent devices for both the assisted navigation of the powered wheelchairs and the secure communication of the data and to design multi-modality human machine interaction. Moreover, the challenge of the project is to take the needs of the users and the constraints that it implies into account at each stage of the project development. The devices developed during the project will be evaluated by the users through the clinical trials.