Miracle-dz/UniFAR-FTUs huggingface dataset:
Metagenome-Wide Association Study and Machine Learning Prediction of Bulk Soil Microbiome and Crop Productivity

Areas within an agricultural field in the same season often differ in crop productivity despite having the same cropping history, crop genotype, and management practices. One hypothesis is that abiotic or biotic factors in the soils differ between areas resulting in these productivity differences. In this study, bulk soil samples collected from a high and a low productivity area from within six agronomic fields in Illinois were quantified for abiotic and biotic characteristics. Extracted DNA from these bulk soil samples were shotgun sequenced. While logistic regression analyses resulted in no significant association between crop productivity and the 26 soil characteristics, principal coordinate analysis and constrained correspondence analysis showed crop productivity explained a major proportion of the taxa variance in the bulk soil microbiome. Metagenome-wide association studies (MWAS) identified more Bradyrhizodium and Gammaproteobacteria in higher productivity areas and more Actinobacteria, Ascomycota, Planctomycetales, and Streptophyta in lower productivity areas. Machine learning using a random forest method successfully predicted productivity based on the microbiome composition with the best accuracy of 0.79 at the order level. Our study showed that crop productivity differences were associated with bulk soil microbiome composition and highlighted several nitrogen utility-related taxa. We demonstrated the merit of MWAS and machine learning for the first time in a plant-microbiome study.
Laparoscopic Sleeve Gastrectomy in a Morbidly Obese Patient with Myasthenia Gravis: A Review of the Management

Myasthenia gravis, a disorder of neuromuscular transmission, presents a unique challenge to the perioperative anesthetic management of morbidly obese patients. This report describes the case of a 27-year-old morbidly obese woman with a past medical history significant for myasthenia gravis and fatty liver disease undergoing bariatric surgery. Anesthesia was induced with intravenous agents and maintained with an inhalational and balanced intravenous technique. The nondepolarizing neuromuscular blocker Cisatracurium was chosen so that no reversal agents were given. Neostigmine was not used to antagonize the effects of Cisatracurium. The goal of this approach was to reduce the risk of complications such as postoperative mechanical ventilation. The anesthetic and surgical techniques used resulted in an uneventful hospital course. Therefore, we can minimize perioperative risks and complications by adjusting the anesthetic plan based on the patient's physiology and comorbidities as well as the pharmacology of the drugs.
Brain Tumor and Seizures: Pathophysiology and Its Implications for Treatment Revisited

Summary: Seizures affect ∼50% of patients with primary and metastatic brain tumors. Partial seizures have the highest incidence, followed by secondarily generalized, depending on histologic subtype, location, and tumor extent. The underlying pathophysiologic mechanisms of tumor‐associated seizures are poorly understood and include theories of altered peritumoral amino acids, regional metabolism, pH, neuronal or glial enzyme and protein expression, as well as immunologic activity. An involvement of changed distribution and function of N‐methyl‐d‐aspartate subclass of glutamate receptors also has been suggested. The often unpredictable responses to seizures after surgical tumor removal add substantial evidence that multiple factors are involved. The therapy of tumor‐related seizures is far from perfect. Several factors contribute to these treatment difficulties, such as tumor growth and drug interactions; however, one of the main reasons for poor seizure control may result from the insufficient or even absent influence of the currently available antiepileptic drugs (AEDs) on most of the pathophysiologic mechanisms of tumor‐related seizures. Studies are needed to elucidate more clearly the pathophysiologic mechanisms of tumor‐related seizures and to identify and develop the optimal AEDs.
Systematic Review of the Properties of Tools Used to Measure Outcomes in Anxiety Intervention Studies for Children with Autism Spectrum Disorders

Background Evidence about relevant outcomes is required in the evaluation of clinical interventions for children with autism spectrum disorders (ASD). However, to date, the variety of outcome measurement tools being used, and lack of knowledge about the measurement properties of some, compromise conclusions regarding the most effective interventions. Objectives This two-stage systematic review aimed to identify the tools used in studies evaluating interventions for anxiety for high-functioning children with ASD in middle childhood, and then to evaluate the tools for their appropriateness and measurement properties. Methods Electronic databases including Medline, PsychInfo, Embase, and the Cochrane database and registers were searched for anxiety intervention studies for children with ASD in middle childhood. Articles examining the measurement properties of the tools used were then searched for using a methodological filter in PubMed, and the quality of the papers evaluated using the COSMIN checklist. Results Ten intervention studies were identified in which six tools measuring anxiety and one of overall symptom change were used as primary outcomes. One further tool was included as it is recommended for standard use in UK children's mental health services. Sixty three articles on the properties of the tools were evaluated for the quality of evidence, and the quality of the measurement properties of each tool was summarised. Conclusions Overall three questionnaires were found robust in their measurement properties, the Spence Children's Anxiety Scale, its revised version – the Revised Children's Anxiety and Depression Scale, and also the Screen for Child Anxiety Related Emotional Disorders. Crucially the articles on measurement properties provided almost no evidence on responsiveness to change, nor on the validity of use of the tools for evaluation of interventions for children with ASD. PROSPERO Registration number CRD42012002684.
Functional Characterization of a Dihydroflavanol 4-Reductase from the Fiber of Upland Cotton (Gossypium hirsutum)

Dihydroflavanol 4-reductase (DFR) is a key later enzyme involved in two polyphenols’ (anthocyanins and proanthocyanidins (PAs)) biosynthesis, however it is not characterized in cotton yet. In present reports, a DFR cDNA homolog (designated as GhDFR1) was cloned from developing fibers of upland cotton. Silencing GhDFR1 in cotton by virus-induced gene silencing led to significant decrease in accumulation of anthocyanins and PAs. More interestingly, based on LC-MS analysis, two PA monomers, (–)-epicatachin and (–)-epigallocatachin, remarkably decreased in content in fibers of GhDFR1-silenced plants, but two new monomers, (–)-catachin and (–)-gallocatachin were present compared to the control plants infected with empty vector. The ectopic expression of GhDFR1 in an Arabidopsis TT3 mutant allowed for reconstruction of PAs biosynthesis pathway and led to accumulation of PAs in seed coat. Taken together, these data demonstrate that GhDFR1 contributes to the biosynthesis of anthocyanins and PAs in cotton.
Adhesive Joint Durability Assessed Using Open-faced Peel Specimens

Abstract This paper presents an investigation of the durability of two aluminum-epoxy adhesive systems by means of open-faced peel specimens. A peel analysis model was used to determine the fracture energy from the peel data. Both wet and dry peel tests were conducted in order to distinguish between the reversible and the permanent effects of water. The effects of water on the cohesive properties of the adhesives were also assessed by tension tests. It was found that, for the two-part epoxy adhesive, which plasticized to a large extent, the peel testing should be carried out in a dry state to assess the interfacial weakening. It was also observed that the two-part adhesive was much stiffer in the dry, degraded state, and it was important to take account of such permanent changes in the cohesive properties associated with water uptake when determining the fracture energy from the peel data. In contrast, the one-part epoxy system did not suffer from appreciable cohesive changes, either reversible or permane.
Graph‐based recommendation integrating rating history and domain knowledge: Application to on‐site guidance of museum visitors

Visitors to museums and other cultural heritage sites encounter a wealth of exhibits in a variety of subject areas, but can explore only a small number of them. Moreover, there typically exists rich complementary information that can be delivered to the visitor about exhibits of interest, but only a fraction of this information can be consumed during the limited time of the visit. Recommender systems may help visitors to cope with this information overload. Ideally, the recommender system of choice should model user preferences, as well as background knowledge about the museum's environment, considering aspects of physical and thematic relevancy. We propose a personalized graph‐based recommender framework, representing rating history and background multi‐facet information jointly as a relational graph. A random walk measure is applied to rank available complementary multimedia presentations by their relevancy to a visitor's profile, integrating the various dimensions. We report the results of experiments conducted using authentic data collected at the Hecht museum. An evaluation of multiple graph variants, compared with several popular and state‐of‐the‐art recommendation methods, indicates on advantages of the graph‐based approach.
A 900 MHz, 2.5 mA CMOS frequency synthesizer with an automatic SC tuning loop

A 900 MHz PLL frequency synthesizer implemented in 0.6 /spl mu/m CMOS technology is developed for WINS (Wireless Integrated Network Sensors) applications. It incorporates an automatic SC discrete-tuning loop to extend the frequency tuning range to 20% while the VCO gain from the CMOS varactor continuous-tuning is kept low at only 20 MHz/V, to minimize the reference spurs. This frequency synthesizer achieves a phase noise of -102 dBc/Hz at 100 kHz offset and reference spurs below -55 dBc. The synthesizer, including an on-chip VCO, dissipates only 2.5 mA from a 3 V supply.
Adaptive feedback control using neural networks with PID

FES control is difficult for musculoskeletal system ’s time-variability and dynamic nonlinearity. It of ten needs good performance control models and complex control methods to get better tracking precision, also the high performance control model is hard to build. Neural network (NN) can learn complex nonlinear mappings s o it can be used to identify control model on-line. At t he mean while, PID control is a widely used feedbac k control method for it simplicity. However, its parameters n eed to be confirmed before it using in a control sy stem. By using the NN identifying results, the self-adaptive PID feedback control strategy can be modified in r eal-time. This will improve the wrist tracking precision. Som e testing experiments done on the able-bodied subje ct showed the control method was robust and stability.
Hopes, dreams and anxieties: India's one-child families

ABSTRACT While rapid fertility decline in India in the last two decades has received considerable attention, much of the discourse has focused on a decline in high parity births. However, this paper finds that, almost hidden from the public gaze, a small but significant segment of the Indian population has begun the transition to extremely low fertility. Among the urban, upper income, educated, middle class, it is no longer unusual to find families stopping at one child, even when this child is a girl. Using data from the India Human Development Survey of 2004–2005, we examine the factors that may lead some families to stop at a single child. We conclude that the motivations for this very low fertility are likely to be a more extreme form of those for low fertility rather than reflecting the qualitative change in ideologies and worldviews that is hypothesized to accompany very low fertility during the second demographic transition.
Synthesizing enumeration techniques for language learning

This paper provides positive and negative results on algorithmically synthesizing, from grammars and from decision procedures for classes of languages, learning machines for identifying, from positive data, grammars for the languages in those classes. In the process, the uniformly decidable classes of recursive languages that can be behaviorally correctly identified from positive data are surprisingly characterized by Angluin’s 1980 Condition 2 (the subset principle for preventing overgeneralization).
On-chip structures for timing measurement and test

This paper describes the use of digitally set delay lines in conjunction with MUTEX time comparison circuits, to measure on-chip signal path timing differences to accuracies of better than 10ps. Three methods of time measurement are described. The first, which uses parallel MUTEXs with a tapped delay line, is analogous to a flash AID converter. The second one is similar to a successive approximation method. Both are fast, and efficient, but the second requires less hardware for a large number of bits. The third technique uses a MUTEX to amplify small time differences to a measurable size. Applications for these techniques include adaptive synchronization and input tests, such as data set-up time conditions that currently require the use of very expensive test hardware. We describe an on-chip method of testing these conditions, using uncorrelated signals whose statistics are known, and accurately selecting the conditions to be tested on-chip.
The neuroaesthetics of prose fiction: pitfalls, parameters and prospects

There is a paucity of neuroaesthetic studies on prose fiction. This is in contrast to the very many impressive studies that have been conducted in recent times on the neuroaesthetics of sister arts such as painting, music and dance. Why might this be the case, what are its causes and, of greatest importance, how can it best be resolved? In this article, the pitfalls, parameters and prospects of a neuroaesthetics of prose fiction will be explored. The article itself is part critical review, part methodological proposal and part opinion paper. Its aim is simple: to stimulate, excite and energize thinking in the discipline as to how prose fiction might be fully integrated in the canon of neuroaesthetics and to point to opportunities where neuroimaging studies on literary discourse processing might be conducted in collaborative work bringing humanists and scientists together.
A hidden Markov model to identify combinatorial epigenetic regulation patterns for estrogen receptor α target genes

MOTIVATION Many studies have shown that epigenetic changes, such as altered DNA methylation and histone modifications, are linked to estrogen receptor α (ERα)-positive tumors and disease prognoses. Several recent studies have applied high-throughput technologies such as ChIP-seq and MBD-seq to interrogate the altered architectures of ERα regulation in tamoxifen (Tam)-resistant breast cancer cells. However, the details of combinatorial epigenetic regulation of ERα target genes in breast cancers with acquired Tam resistance have not yet been fully examined. RESULTS We developed a computational approach to identify and analyze epigenetic patterns associated with Tam resistance in the MCF7-T cell line as opposed to the Tam-sensitive MCF7 cell line, with the goal of understanding the underlying mechanisms of epigenetic regulatory influence on resistance to Tam treatment in breast cancer. In this study, we used ChIP-seq of ERα, RNA polymerase II, three histone modifications and MBD-seq data of DNA methylation in MCF7 and MCF7-T cells to train hidden Markov models (HMMs). We applied the Bayesian information criterion to determine that a 20-state HMM was best, which was reduced to a 14-state HMM with a Bayesian information criterion score of 1.21291 × 10(7). We further identified four classes of biologically meaningful states in this breast cancer cell model system, and a set of ERα combinatorial epigenetic regulated target genes. The correlated gene expression level and gene ontology analyses showed that different gene ontology terms were enriched with Tam-resistant versus sensitive breast cancer cells. Our study illustrates the applicability of HMM-based analysis of genome-wide high-throughput genomic data to study epigenetic influences on E2/ERα regulation in breast cancer.
PERCEPTIONS IN PREDICTING ACTOR AND PARTNER SEXUAL AND RELATIONAL SATISFACTION IN COUPLE RELATIONSHIPS

OF THESIS PERCEPTIONS IN PREDICTING ACTOR AND PARTNER SEXUAL AND RELATIONAL SATISFACTION IN COUPLE RELATIONSHIPS The present exploration of perceptual accuracy and bias in romantic relationships bridges a gap in the literature on the ability of partners to estimate one another’s level of relational and sexual satisfaction, and its impact on their own and their partner’s level of satisfaction. A sample of 50 couples, recruited internationally, in continuously monogamous relationships of at least six-months in length completed online assessments of their relationship. The degree of accuracy and bias of their perception was established by comparing actor’s estimates of their partner’s satisfaction with the partner’s actual, self-reported satisfaction scores. The actor-partner interdependence model (APIM; Kenny, Kashy, & Cook, 2006) revealed significant partner effects (but no actor effects): the underestimation of perceived partner’s sexual and relational satisfaction predicted an increase in partner’s actual sexual and relational satisfaction. Overestimation of partner’s satisfaction, on the other hand, predicted a decrease in partner’s actual satisfaction. Authors hypothesize that under-perception of partner’s satisfaction motivates corrective relationship behaviors, which, in turn, increases the experience of satisfaction of the relationship partner.
Economic Impacts of Non-Native Forest Insects in the Continental United States

Reliable estimates of the impacts and costs of biological invasions are critical to developing credible management, trade and regulatory policies. Worldwide, forests and urban trees provide important ecosystem services as well as economic and social benefits, but are threatened by non-native insects. More than 450 non-native forest insects are established in the United States but estimates of broad-scale economic impacts associated with these species are largely unavailable. We developed a novel modeling approach that maximizes the use of available data, accounts for multiple sources of uncertainty, and provides cost estimates for three major feeding guilds of non-native forest insects. For each guild, we calculated the economic damages for five cost categories and we estimated the probability of future introductions of damaging pests. We found that costs are largely borne by homeowners and municipal governments. Wood- and phloem-boring insects are anticipated to cause the largest economic impacts by annually inducing nearly $1.7 billion in local government expenditures and approximately $830 million in lost residential property values. Given observations of new species, there is a 32% chance that another highly destructive borer species will invade the U.S. in the next 10 years. Our damage estimates provide a crucial but previously missing component of cost-benefit analyses to evaluate policies and management options intended to reduce species introductions. The modeling approach we developed is highly flexible and could be similarly employed to estimate damages in other countries or natural resource sectors.
Finding experts and their eetails in e-mail corpora

We present methods for finding experts (and their contact details) using e-mail messages. We locate messages on a topic, and then find the associated experts. Our approach is unsupervised: both the list of potential experts and their personal details are obtained automatically from e-mail message headers and signatures, respectively. Evaluation is done using the e-mail lists in the W3C corpus.
Uniform Generation of NP-Witnesses Using an NP-Oracle

A uniform generation procedure for NP is an algorithm that, given any input in a fixed NP-language, outputs a uniformly distributed NP-witness for membership of the input in the language. We present a uniform generation procedure for NP that runs in probabilistic polynomial time with an NP-oracle. This improves upon results of M. Jerrum et al. (1986, Theoret. Comput. Sci.43, 169? 188), which either require a ? P2 oracle or obtain only almost uniform generation. Our procedure utilizes ideas originating in the works of M. Sipser, and L. Stockmeyer (respectively, 1983, in Proceedings of the 15th Annual Symposium on the Theory of Computing, ACM, New York), and Jerrum et al. (1986).
Cognition to Genes via the Brain in the Study of Conduct Disorder

Although a single diagnostic label, conduct disorder, is currently applied to children exhibiting antisocial behaviour, multiple routes to the same behavioural phenomena exist. Morton and Frith's (1995) causal modelling has been fundamentally important in influencing models of cognitive/affective and associated neural differences between callous-unemotional (CU) and reactive/threat-based antisocial behaviour. Current behavioural genetic research is still catching up with the developmental cognitive neuroscience, and very few genetically informative studies differentiate between these two subtypes of antisocial behaviour. Our own work with preadolescent twins suggests that while the CU subtype is genetically vulnerable to antisocial behaviour, the non-CU subtype manifests a primarily environmental aetiology to their antisocial behaviour. Molecular genetic work to date has not differentiated between these two subtypes, and we highlight why it might be of interest to do so. Finally, we discuss how the novel approach of imaging genetics could be harnessed to study genes to cognition pathways for different subtypes of conduct disorder. Uta Frith's contributions to articulating research strategies for developmental disorders are important in conducting and interpreting this work.
Investigating the Prevalence of Preterm Birth in Iranian Population: A Systematic Review and Meta-Analysis

Introduction: Despite medical advances, preterm delivery remains a global problem in developed and developing countries. The present study was aimed at conducting a systematic review and meta-analysis of studies on the prevalence of preterm delivery in Iran. Methods: This study was carried out on studies conducted in Iran by searching databases of SID, Magiran, Irandoc, MEDLIB, Iranmedex, PubMed, Web of science, Google Scholar and Scopus. The search was conducted using advanced search and keywords of preterm delivery and equivalents of it in Mesh and their Farsi’s Synonymous in all articles from 2000-2016.After extracting the data, the data were combined using a random model. Heterogeneity of the studies was assessed using Q test I2 index and the data were analyzed using STATA Ver.11 software. Results: The total number of samples in this study was 41773. In 19 reviewed articles, the overall prevalence of preterm delivery, based on the random effects model, was estimated to be a total of 10% (95% CI, 9-12). The lowest prevalence of preterm labor was 5.4% in Bam and the highest prevalence was 19.85% in Tehran. There was no significant difference between the prevalence of preterm delivery compared to year of study and sample size. Conclusion: This study reviewed the findings of previous studies and showed that preterm delivery is a relatively prevalent problem in Iran. Therefore, adopting appropriate interventions in many cases including life skills training, self-care and increasing pregnancy care to reduce these consequences and their following complications in high risk patients seem necessary.