Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian design of synthetic biological systems

Here we introduce a new design framework for synthetic biology that exploits the advantages of Bayesian model selection. We will argue that the difference between inference and design is that in the former we try to reconstruct the system that has given rise to the data that we observe, whereas in the latter, we seek to construct the system that produces the data that we would like to observe, i.e., the desired behavior. Our approach allows us to exploit methods from Bayesian statistics, including efficient exploration of models spaces and high-dimensional parameter spaces, and the ability to rank models with respect to their ability to generate certain types of data. Bayesian model selection furthermore automatically strikes a balance between complexity and (predictive or explanatory) performance of mathematical models. To deal with the complexities of molecular systems we employ an approximate Bayesian computation scheme which only requires us to simulate from different competing models to arrive at rational criteria for choosing between them. We illustrate the advantages resulting from combining the design and modeling (or in silico prototyping) stages currently seen as separate in synthetic biology by reference to deterministic and stochastic model systems exhibiting adaptive and switch-like behavior, as well as bacterial two-component signaling systems.
Revolutionizing membrane protein overexpression in bacteria

The bacterium Escherichia coli is the most widely used expression host for overexpression trials of membrane proteins. Usually, different strains, culture conditions and expression regimes are screened for to identify the optimal overexpression strategy. However, yields are often not satisfactory, especially for eukaryotic membrane proteins. This has initiated a revolution of membrane protein overexpression in bacteria. Recent studies have shown that it is feasible to (i) engineer or select for E. coli strains with strongly improved membrane protein overexpression characteristics, (ii) use bacteria other than E. coli for the expression of membrane proteins, (iii) engineer or select for membrane protein variants that retain functionality but express better than the wild‐type protein, and (iv) express membrane proteins using E. coli‐based cell‐free systems.
Scaling Laws of Cognitive Networks

Opportunistic secondary spectrum usage has the potential to dramatically increase spectral efficiency and rates of a network of secondary cognitive users. In this work we consider a cognitive network: n pairs of cognitive transmitter and receiver wish to communicate simultaneously in the presence of a single primary transmitter-receiver link. We assume each cognitive transmitter-receiver pair communicates in a realistic single-hop fashion, as cognitive links are likely to be highly localized in space. We first show that under an outage constraint on the primary link's capacity, provided that the density of the cognitive users is constant, the sum-rate of the n cognitive links scales linearly with n as n ¿ ¿. This scaling is in contrast to the sum-rate scaling of ¿n seen in multi-hop ad-hoc networks. We then explore the optimal radius of the primary exclusive region: the region in which no secondary cognitive users may transmit, such that the outage constraint on the primary user is satisfied. We obtain bounds that help the design of this primary exclusive region, outside of which cognitive radios may freely transmit.
Classification of Heart Failure in the Atherosclerosis Risk in Communities (ARIC) Study: A Comparison of Diagnostic Criteria

Background—Population-based research on heart failure (HF) is hindered by lack of consensus on diagnostic criteria. Framingham (FRM), National Health and Nutrition Examination Survey (NHANES), Modified Boston (MBS), Gothenburg (GTH), and International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) code criteria, do not differentiate acute decompensated heart failure (ADHF) from chronic stable HF. We developed a new classification protocol for identifying ADHF in the Atherosclerosis Risk in Communities (ARIC) Study and compared it with these other schemes. Methods and Results—A sample of 1180 hospitalizations with a patient address in 4 study communities and eligible discharge codes were selected. After assessing whether the chart contained evidence of possible HF signs, 705 were fully abstracted. Two independent reviewers classified each case as ADHF, chronic stable HF, or no HF, using ARIC classification guidelines. Fifty-nine percent of cases met ARIC criteria for ADHF and 13.9% and 27.1% were classified as chronic stable HF or no HF, respectively. Among events classified as HF by FRM criteria, 68.4% were validated as ADHF, 9.6% as chronic stable HF, and 21.9% as no HF. However, 92.5% of hospitalizations with a primary ICD-9-CM 428 “heart failure” code were validated as ADHF. Sensitivities of comparison criteria to classify ADHF ranged from 38–95%, positive predictive values from 62–92%, and specificities from 19–96%. Conclusions—Although comparison criteria for classifying HF were moderately sensitive in identifying ADHF, specificity varied when applied to a randomly selected set of suspected HF hospitalizations in the community.
Does the World Economy Swing National Elections?

Do voters reward national leaders who are more competent economic managers, or merely those who happen to be in power when the world economy booms? Using data from 268 democratic elections held between 1978 and 1999, I compare the effect of world growth (luck) and national growth relative to world growth (competence). Both matter, but the effect of luck is larger than the effect of competence. Voters are more likely to reward competence in countries that are richer and better educated; and there is some suggestive evidence that media penetration rates affect the returns to luck and competence.
Evolutionary Psychology and Terrorism

This book explores the evolutionary context of terrorism and political violence. While evolutionary thinking has come to permeate both biological and social-science theorising, it has not yet been applied systematically to the areas of terrorism and political violence. This volume seeks to do this for the first time. It presents a collection of essays on evolutionary psychology and terrorism, which encourage the reader to approach terrorism from a non-traditional perspective, by developing new approaches to understanding it and those who commit such acts of violence. The book identifies evolutionary thought as heuristically important in the understanding of terrorism, explores the key conceptual themes, and provides an evolutionary (and cross-species) understanding of the community-wide effects of terrorist attacks. The contributors bring forward innovative ideas and concepts to assist the practitioner, analyst and academic to better understand and respond to the threat of terrorism. In doing so this book challenges existing assumptions about terrorism and those who carry out such acts, in order to move the debate into new areas characterized by an emphasis on intellectual quality and rigour, an interdisciplinary approach, and a drawing together of theory and practice. The intention is to provide a sufficient discussion to enable the reader to both understand the relevance of evolutionary thinking to terrorism and political violence, and to appreciate the practical implications of conceptualising problems in this way. This book will be of much interest to students of terrorism and political violence, psychology, criminology and security studies.
Tax Policy and Firms ’ Productivity in Emerging Economies : Evidence from Taiwan

This paper investigates the effect of tax policy on productivity in Taiwanese manufacturing firms for the period 2001 to 2008. We first adopt the dynamic random effect (RE) probit model to analyze the determinants of a firm’s decision as to whether or not to apply for tax credits. The results show that the causal effect from past tax credits usage to current tax credits usage exists across industries. Specifically, there is a persistence of tax credits usage for Taiwanese manufacturing firms. This study further employed a panel instrumental variable (IV) approach to control for endogeneity of tax credits and firm heterogeneity in determining firm productivity. It shows that tax credits have significantly positive effect on firm productivity. Moreover, this marginal effect of tax credits is particularly relevant for electronics firms’ productivity. The results indicate that there is a productivity-enhancing effect of tax credits, suggest that the tax policy can enhance firm’s technology in Taiwan. Paper Prepared for Presentation at the 18th International Conference on Computing in Economics and Finance, June 27-29, 2012, Prague, Czech Republic (Preliminary draft, please do not quote.)
Supercapacitor Energy Storage for Wind Energy Applications

As wind energy reaches higher penetration levels, there is a greater need to manage intermittency associated with the individual wind turbine generators. This paper considers the integration of a short-term energy storage device in a doubly fed induction generator design in order to smooth the fast wind-induced power variations. This storage device can also be used to reinforce the dc bus during transients, thereby enhancing its low-voltage ride through (LVRT) capability. The topology is evaluated in terms of its ability to improve the performance both during normal operation and during transients. Results show that when storage is sized based upon the LVRT requirement, it can effectively damp short-term power oscillations, and it provides superior transient performance when compared with conventional topologies
On the association between diabetes and mental disorders in a community sample: results from the German National Health Interview and Examination Survey.

OBJECTIVE To determine the relationship between mental disorders and diabetes in a representative community sample. RESEARCH DESIGN AND METHODS This was a cross-sectional study. Data on diabetes and HbA(1c) values were obtained by structured questionnaires and by laboratory assessments. Current psychiatric disorders were diagnosed by a modified version of the Composite International Diagnostic Interview (CIDI). RESULTS People with diabetes (PWD) were not more likely to meet Diagnostic and Statistical Manual of Psychiatric Disorders, 4th edition (DSM-IV) criteria for at least one mental disorder than were individuals without diabetes. However, a different diagnostic pattern occurred compared with the general population: odds ratios (ORs) for anxiety disorders in PWD were higher (OR 1.93, 95% CI 1.19-3.14). Although PWD had higher prevalence rates of affective disorders, the relationship between diabetes and affective disorders was not statistically significant after controlling for age, sex, marital status, and socioeconomic status. In contrast, the relationship between diabetes and anxiety disorders remained significant after controlling for these variables. In contrast to individuals without mental disorders, PWD with affective or anxiety disorders more frequently had adequate glycemic control. CONCLUSIONS Diabetes was associated with an increased likelihood of anxiety disorders. The association between mental disorders, diabetes, and glycemic control should be evaluated carefully in terms of potentially confounding sociodemographic variables, sample characteristics, and definitions of the disorders.
Probability and nonclassical logic

Classical tautologies have probability. Classical contradictions have probability. These familiar features reflect a connection between standard probability theory and classical logic. In contexts in which classical logic is questioned—to deal with the paradoxes of self-reference, or vague propositions, for the purposes of scientific theory or metaphysical anti-realism—we must equally question standard probability theory. Section 1 covers the intended interpretation of ‘nonclassical logic’ and ‘probability’. Section 2 reviews the connection between classical logic and classical probability. Section 3 briefly reviews salient aspects of nonclassical logic, laying out a couple of simple examples to fix ideas. Section 4 explores modifications of probability theory. The variations laid down will be motivated initially by formal analogies to the classical setting. In section 5, however, we look at two foundational justifications for the presentations of ‘nonclassical probabilities’ that are arrived at. Sections 6-7 describe extensions of the nonclassical framework: to conditionalization and decision theory in particular. Section 8 will consider some alternative approaches, and section 9 evaluates progress.
Changes in the Expression of Vascular Endothelial Growth Factor after Fetal Tracheal Occlusion in an Experimental Model of Congenital Diaphragmatic Hernia

Introduction. Vascular endothelial growth factor (VEGF), an angiogenic factor secreted by type II pneumocytes, could play a role in congenital diaphragmatic hernia (CDH) pathogenesis. Animal studies suggest that VEGF accelerates lung growth. Aim. To quantify VEGF on fetal lungs in a nitrofen rat model for CDH and to analyze the effect of tracheal occlusion (TO) in VEGF in fetal lung rats after nitrofen and in control rats not exposed to nitrofen. Methods. Pregnant rats received nitrofen on day 9.5 of gestation. Fetuses were divided into 2 groups: those that underwent TO on day 20 and those that did not. On day 21, fetuses were delivered, and the lungs were dissected for subsequent VEGF quantification. Results. CDH was detected in 43% of the fetuses that received nitrofen. Fetuses with CDH showed significantly reduced lung weight/fetal weight ratio and lower VEGF levels than the remainder. A higher VEGF value was observed after TO. Conclusions. VEGF protein was significantly lower in fetuses with CDH. TO induced a significant increase in VEGF compared to the fetuses that did not undergo TO. Although not statistically significant, we observed higher VEGF levels in fetuses with CDH and TO compared to fetuses with CDH and no further intervention.
“I Can Get Through This and I Will Get Through This”: The unfolding journey of teenage motherhood in and beyond foster care

Using a series of 18 in-depth qualitative interviews from six participants, the present study employed Interpretative Phenomenological Analysis (IPA) to explore emerging conceptualizations of motherhood among young mothers who gave birth as teenagers while living in foster care. Analysis revealed three themes: Ambivalent Beginnings, Coming into Our Own, and Finding Our Way, which, together, offer an understanding of youths’ interpretation of their experiences of motherhood over time. Findings extend and complicate a risk-only view of teenage pregnancy within foster care settings. They call for a compassionate view of mothering and attuned intervention in these challenging circumstances in order to support both mother and infant mental health and well-being. Study findings further suggest a need for ongoing, relationship-based parenting support coupled with thoughtful pregnancy planning, foster parent training in coming alongside teens rather than either withdrawing or taking over, and nurturing postpartum support.
Performance Provisioning and Energy Efficiency in Cloud and Distributed Computing Systems

In recent years, the issue of energy consumption in high performance computing (HPC) systems has attracted a great deal of attention. In response to this, many energy-aware algorithms have been developed in different layers of HPC systems, including the hardware layer, service layer and system layer. These algorithms are of two types: first, algorithms which directly try to improve the energy by tweaking frequency operation or scheduling algorithms; and second, algorithms which focus on improving the performance of the system, with the assumption that efficient running of a system may indirectly save more energy. In this thesis, we develop algorithms in both layers. First, we introduce three algorithms to directly improve the energy of scheduled tasks at the hardware level by using Dynamic Voltage Frequency Scaling (DVFS). Second, we propose two algorithms for modelling and resource provisioning of MapReduce applications (a well-known parametric distributed framework currently used by Google, Yahoo, Facebook and LinkedIn) based on its configuration parameters. Certainly, estimating the performance (e.g., execution time or CPU clock ticks) of a MapReduce application can be later used for smart scheduling of such applications in clouds or clusters. To evaluate the algorithms, we have conducted extensive simulation and real experiments on a 5-node physical cluster with up to 25 virtual nodes, using both synthetic and real world applications. Also, the proposed new algorithms are compared with existing algorithms by experimentation, and the experimental results reveal new information on the performance of these algorithms, as well as on the properties of MapReduce and DVFS. In the end, three open problems are revealed by the experimental observations, and their importance is explained.
Situation Characteristics Are Age Graded

The current work examines mean-level patterns of major dimensions of situation characteristics—the Situational Eight DIAMONDS—across the life span. Using population-representative data from the 2013 and 2014 American Time Use Survey (Study 1) and the 2012 German Socioeconomic Panel (Study 2), we tested hypotheses generated from research on situation cues and personality development. Results demonstrated that the DIAMONDS characteristics were age graded: Individuals tended to be in different kinds of situations as a function of their age. Furthermore, there was evidence that some patterns were country specific, whereas others replicated across the United States and Germany. Overall, these studies suggest that—much like personality traits—situation characteristics have predictable mean-level patterns over the life span.
Automatic Container Code Recognition via Spatial Transformer Networks and Connected Component Region Proposals

Container identification and recognition is still performed manually or in a semi-automatic fashion in multiple ports globally. This results in errors and inefficiencies in port operations. The problem of automatic container identification and recognition is challenging as the ISO standard only prescribes the pattern of the code and does not specify other parameters such as the foreground and background colors, font type and size, orientation of characters (horizontal or vertical) so on. Additionally, the corrugated surface of container body makes the two dimensional projection of the text on three dimensional containers slanted and jagged. We propose a solution in the form of an end-to-end pipeline that uses Region Proposals generated based on Connected Components for text detection in conjunction with Spatial Transformer Networks for text recognition. We demonstrate via our experimental results that the pipeline is reliable and robust even in situations when the code characters are highly distorted and outperforms the state-of-the-art results for text detection and recognition over the containers. We achieve text coverage rate of 100% and text recognition rate of 99.64%.
Generative Models of Grounded Language Learning with Ambiguous Supervision

“Grounded” language learning is the process of learning the semantics of natural language with respect to relevant perceptual inputs. Toward this goal, computational systems are trained with data in the form of natural language sentences paired with relevant but ambiguous perceptual contexts. With such ambiguous supervision, it is required to resolve the ambiguity between a natural language (NL) sentence and a corresponding set of possible logical meaning representations (MR). My research focuses on devising effective models for simultaneously disambiguating such supervision and learning the underlying semantics of language to map NL sentences into proper logical forms. Specifically, I will present two probabilistic generative models for learning such correspondences. The models are applied to two publicly available datasets in two different domains, sportscasting and navigation, and compared with previous work on the same data. I will first present a probabilistic generative model that learns the mappings from NL sentences into logical forms where the true meaning of each NL sentence is one of a handful of candidate logical MRs. It simultaneously disambiguates the meaning of each sentence in the training data and learns to probabilistically map a NL sentence to its MR form depicted in a single tree structure. Evaluations are performed on the RoboCup sportscasting corpous, which show that it outperforms previous methods. Next, I present a PCFG induction model for grounded language learning that extends the model of Borschinger, Jones, and Johnson (2011) by utilizing a semantic lexicon. Borschinger et al.’s approach works well when there is limited ambiguity such as in the sportscasting task, but it does not scale well to highly ambiguous situations when there are large sets of potential meaning possibilities for each sentence, such as in the navigation instruction following task studied by Chen and Mooney (2011). Our model overcomes such limitations by employing a semantic lexicon as the basic building block for PCFG rule generation. Our model also allows for novel combination of MR outputs when parsing novel test sentences. For future work, I propose to extend our PCFG induction model in several ways: improving the lexicon learning algorithm, discriminative re-ranking of top-k parses, and integrating the meaning representation language (MRL) grammar for extra structural information. The longer-term agenda includes applying our approach to summarized machine translation, using real perception data such as robot sensorimeter and images/videos, and joint learning with other natural language processing tasks.
Trophic polymorphism in a terrestrial salamander

Question: Does habitat heterogeneity promote trophic polymorphism in a terrestrial salamander? Hypothesis: Eastern red-backed salamanders (Plethodon cinereus) in upland and lowland habitats differ morphologically because their prey’s size differs between those habitats. Field site: Five mature hardwood forests in central New York and northern Pennsylvania, USA, with known differences in diet between upland and lowland habitats. Methods: We collected animals and examined their stomach contents and their cranial morphology, the latter with digital stereomicroscope images and morphometric methods. Results: We found morphological differences between upland and lowland salamanders, although there was a considerable phenotypic range for both habitats. Lowland salamanders generally had relatively shorter heads and a lower jaw/head ratio, and upland salamanders generally had the converse. Within and among habitats, cranial morphology was associated with diet, where salamanders with lowland-like morphology consumed more large prey and fewer small prey, and salamanders with upland-like morphology consumed the converse. Conclusions: The observed trophic polymorphism and association with food use within populations suggests that this variation may accentuate variation at larger scales, and may play an important role in diversification within the genus.