nils-herrmann/clean_scirepeval huggingface dataset:
TerpreT: A Probabilistic Programming Language for Program Induction
Venue: ArXiv

We study machine learning formulations of inductive program synthesis; given input output examples, we try to synthesize source code that maps inputs to corresponding outputs. Our aims are to develop new machine learning approaches based on neural networks and graphical models, and to understand the capabilities of machine learning techniques relative to traditional alternatives, such as those based on constraint solving from the programming languages community. Our key contribution is the proposal of TerpreT, a domain specific language for expressing program synthesis problems. TerpreT is similar to a probabilistic programming language: a model is composed of a specification of a program representation (declarations of random variables) and an interpreter describing how programs map inputs to outputs (a model connecting unknowns to observations) The inference task is to observe a set of input output examples and infer the underlying program. TerpreT has two main benefits. First, it enables rapid exploration of a range of domains, program representations, and interpreter models. Second, it separates the model specification from the inference algorithm, allowing like to like comparisons between different approaches to inference. From a single TerpreT specification we automatically perform inference using four different back ends. These are based on gradient descent, linear program (LP) relaxations for graphical models, discrete satisfiability solving, and the Sketch program synthesis system. We illustrate the value of TerpreT by developing several interpreter models and performing an empirical comparison between alternative inference algorithms. Our key empirical finding is that constraint solvers dominate the gradient descent and LP based formulations. We conclude with suggestions for the machine learning community to make progress on program synthesis.
A deep scattering spectrum Deep Siamese network pipeline for unsupervised acoustic modeling
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Recent work has explored deep architectures for learning acoustic features in an unsupervised or weakly supervised way for phone recognition. Here we investigate the role of the input features, and in particular we test whether standard mel scaled filterbanks could be replaced by inherently richer representations, such as derived from an analytic scattering spectrum. We use a Siamese network using lexical side information similar to a well performing architecture used in the Zero Resource Speech Challenge (2015) and show a substantial improvement when the filterbanks are replaced by scattering features, even though these features yield similar performance when tested without training. This shows that unsupervised and weakly supervised architectures can benefit from richer features than the traditional ones.
It takes a seasoned bird to be a good listener: communication between the sexes
Venue: Current Opinion in Neurobiology

Birds commonly use sound for communication between the sexes. In many songbird species, only males sing and there are pronounced sex differences in the neural song control circuits. By contrast, the auditory circuitry is largely similar in males and females. Both sexes learn to recognize vocalizations heard as juveniles and this shapes auditory response selectivity. Mating vocalizations are restricted to the breeding season, when sex steroid levels are elevated. Auditory cells, from the ear to the cortex, are hormone sensitive. Estrogens are synthesized in the brain and can modulate the activity of auditory neurons. In species that breed seasonally, elevated levels of estradiol in females transiently enhance their auditory responses to conspecific vocalizations, resulting in sex differences in audition.
Mixture Models: Latent Profile and Latent Class Analysis

Latent class analysis (LCA) and latent profile analysis (LPA) are techniques that aim to recover hidden groups from observed data. They are similar to clustering techniques but more flexible because they are based on an explicit model of the data, and allow you to account for the fact that the recovered groups are uncertain. LCA and LPA are useful when you want to reduce a large number of continuous (LPA) or categorical (LCA) variables to a few subgroups. They can also help experimenters in situations where the treatment effect is different for different people, but we do not know which people. This chapter explains how LPA and LCA work, what assumptions are behind the techniques, and how you can use R to apply them.
An Introduction to QR Code Technology
Venue: 2016 International Conference on Information Technology (ICIT)

QR i.e. "Quick Response" code is a 2D matrix code that is designed by keeping two points under consideration, i.e. it must store large amount of data as compared to 1D barcodes and it must be decoded at high speed using any handheld device like phones. QR code provides high data storage capacity, fast scanning, omnidirectional readability, and many other advantages including, error correction (so that damaged code can also be read successfully) and different type of versions. Different varieties of QR code symbols like logo QR code, encrypted QR code, iQR Code are also available so that user can choose among them according to their need. Now these days, a QR code is applied in different application streams related to marketing, security, academics etc. and gain popularity at a really high pace. Day by day more people are getting aware of this technology and use it accordingly. The popularity of QR code grows rapidly with the growth of smartphone users and thus the QR code is rapidly arriving at high levels of acceptance worldwide.
Aharonov Bohm oscillations in Dirac semimetal Cd3As2 nanowires
Venue: Nature communications

Three dimensional Dirac semimetals, three dimensional analogues of graphene, are unusual quantum materials with massless Dirac fermions, which can be further converted to Weyl fermions by breaking time reversal or inversion symmetry. Topological surface states with Fermi arcs are predicted on the surface and have been observed by angle resolved photoemission spectroscopy experiments. Although the exotic transport properties of the bulk Dirac cones have been demonstrated, it is still a challenge to reveal the surface states via transport measurements due to the highly conductive bulk states. Here, we show Aharonov Bohm oscillations in individual single crystal Cd3As2 nanowires with low carrier concentration and large surface to volume ratio, providing transport evidence of the surface state in three dimensional Dirac semimetals. Moreover, the quantum transport can be modulated by tuning the Fermi level using a gate voltage, enabling a deeper understanding of the rich physics residing in Dirac semimetals.
Quantum oscillation and nontrivial transport in the Dirac semimetal Cd3As2 nanodevice

Here, we report on the Shubnikov de Haas oscillation in high quality Cd3As2 nanowires grown by a chemical vapor deposition approach. The dominant transport of topological Dirac fermions is evident by the nontrivial Berry phase in the Landau Fan diagram. The quantum oscillations rise at a small field of 2 T and preserves up to 100 K, revealing a sizeable Landau level gap and a device mobility of 2138 cm2 V 1 s 1. The angle variable oscillations indicate the isotropy of the bulk Dirac transport. The large estimated mean free path makes the Cd3As2 nanowire a promising platform for the one dimensional transport of Dirac semimetals.
Accuracy of prediction methods for rain noise levels

Determining levels of rain noise can be an important design aspect for various types of buildings, particularly education facilities. Measurements of rain noise levels can be carried out using relevant ISO standards (ISO 140 18:2006, ISO 10140 1:2010/Amd 2:2014, ISO 10140 5:2010 Amd 1:2014) which specify artificial rain types with, for example, constant drop size. While this can provide an indication of the levels of rain noise that might occur in practice, it is not necessarily trivial to estimate real or natural levels of rain noise from the artificial rain noise measurements. The relationship between natural and artificial rain noise levels can be better understood using prediction models. Predicting rain noise levels can also prove helpful in evaluating a range of alternative roof construction types, as rain noise measurement data is often only available for a limited number of construction types. This paper provides a brief overview of a prediction method for rain noise. Emphasis is given to relevant tolerances on prediction accuracy, with reference made to variation in laboratory rain noise level measurements (that is, measurement reproducibility) Prediction results are presented for a number of different constructions to demonstrate the extent of agreement between the prediction method and laboratory results.
Unique Eomes+ NK Cell Subsets Are Present in Uterus and Decidua During Early Pregnancy
Venue: Front. Immunol.

Decidual and uterine natural killer (NK) cells have been shown to contribute to the successful pregnancy both in humans and mice. NK cells represent "cytotoxic" group 1 innate lymphoid cells (ILCs) and are distinct from the recently described "helper" ILC1. Here, we show that both in humans and mice the majority of group 1 ILC in endometrium/uterus and decidua express Eomesodermin (Eomes) thus suggesting that they are developmentally related to conventional NK cells. However, they differ from peripheral NK cells. In humans, Eomes+ decidual NK (dNK) cells express CD49a and other markers of tissue residency, including CD103, integrin b7, CD9, and CD69. The expression of CD103 allows the identification of different subsets of IFNg producing Eomes+ NK cells. We show that TGFb can sustain/induce CD103 and CD9 expression in dNK cells and decidual CD34 derived NK cells, indicating that the decidual microenvironment can instruct the phenotype of Eomes+ NK cells. In murine decidua and uterus, Eomes+ cells include CD49a CD49b+ conventional NK cells and CD49a+ cells. Notably, Eomes+CD49a+ cells are absent in spleen and liver. Decidual and uterine Eomes+CD49a+ cells can be dissected in two peculiar cell subsets according to CD49b expression. CD49a+CD49b and CD49a+CD49b+ cells are enriched in immature CD11blowCD27high cells, while CD49a CD49b+ cells contain higher percentages of mature CD11bhighCD27low cells, both in uterus and decidua. Moreover, Eomes+CD49a+CD49b cells decrease during gestation, thus suggesting that this peculiar subset may be required in early pregnancy rather than on later phases. Conversely, a minor Eomes CD49a+ ILC1 population present in decidua and uterus increases during pregnancy. CD49b Eomes+ cells produce mainly TNF, while CD49a CD49b+ conventional NK cells and CD49a+CD49b+ cells produce both IFNg and TNF. Thus, human and murine decidua contains unique subsets of group 1 ILCs, including Eomes+ and Eomes cells, with peculiar phenotypic and functional features. Our study contributes to re examination of the complexity of uterine and decidual ILC subsets in humans and mice and highlights the role of the decidual microenvironment in shaping the features of these cells.
Extracellular Vesicles Originate from the Conceptus and Uterus During Early Pregnancy in Sheep1
Venue: Biology of reproduction

Cells release diverse types of membrane bound vesicles of endosomal and plasma membrane origin, termed exosomes and microvesicles, respectively. Extracellular vesicles (EVs) represent an important mode of intercellular communication by transferring select RNAs, proteins, and lipids between cells. The present studies tested the hypothesis that the elongating ovine conceptus and uterus produces EVs that mediate conceptus maternal interactions during early pregnancy. In Study 1, EVs were purified from uterine luminal fluid of Day 14 cyclic sheep. The EVs were fluorescently labeled with PKH67 dye and infused into the uterine lumen of pregnant sheep for 6 days using an osmotic pump. On Day 14, labeled EVs were observed in the conceptus trophectoderm and uterine epithelia, but not in the uterine stroma or myometrium. In Study 2, Day 14 conceptuses were cultured ex vivo for 24 h and found to release EVs into the culture medium. Proteomics analysis of the Day 14 conceptus derived EVs identified 231 proteins that were enriched for extracellular space and several protein classes, including proteases, protease inhibitors, chaperones and chaperonins. RNA sequencing of Day 14 conceptus derived EVs detected expression of 512 mRNAs. The top expressed genes were overrepresented in ribosomal functions and components. Isolated EVs from conceptuses were fluorescently labeled with PKH67 and infused into the uterine lumen of cyclic sheep for 6 days using an osmotic pump. On Day 14, labeled EVs were observed in the uterine epithelia, but not in the uterine stroma or myometrium. Labeled EVs were not observed in the ovary or in other maternal tissues. These studies support the ideas that EVs emanate from both the conceptus trophectoderm and uterine epithelia, and are involved in intercellular communication between those cells during the establishment of pregnancy in sheep.
Neural predictors of alcohol use and psychopathology symptoms in adolescents
Venue: Development and Psychopathology

Adolescence is a period marked by increases in risk taking, sensation seeking, and emotion dysregulation. Neurobiological models of adolescent development propose that lagging development in brain regions associated with affect and behavior control compared to regions associated with reward and emotion processing may underlie these behavioral manifestations. Cross sectional studies have identified several functional brain networks that may contribute to risk for substance use and psychopathology in adolescents. Determining brain structure measures that prospectively predict substance use and psychopathology could refine our understanding of the mechanisms that contribute to these problems, and lead to improved prevention efforts. Participants (N 265) were healthy substance naive adolescents (ages 12 14) who underwent magnetic resonance imaging and then were followed annually for up to 13 years. Cortical thickness and surface area measures for three prefrontal regions (dorsolateral prefrontal cortex, inferior frontal gyrus, and orbitofrontal cortex) and three cortical regions from identified functional networks (anterior cingulate cortex, insular cortex, and parietal cortex) were used to predict subsequent binge drinking, externalizing symptoms, and internalizing symptoms. Thinner dorsolateral prefrontal cortex and inferior frontal cortex in early adolescence predicted more binge drinking and externalizing symptoms, respectively, in late adolescence (ps .05) Having a family history of alcohol use disorder predicted more subsequent binge drinking and externalizing symptoms. Thinner parietal cortex, but not family history, predicted more subsequent internalizing symptoms (p .05) This study emphasizes the temporal association between maturation of the salience, inhibition, and executive control networks in early adolescence and late adolescent behavior outcomes. Our findings indicate that developmental variations in these brain regions predate behavioral outcomes of substance use and psychopathology, and may therefore serve as prospective biomarkers of vulnerability.
Cooperative binding of AP 1 and TEAD4 modulates the balance between vascular smooth muscle and hemogenic cell fate
Venue: Development

The transmission of extracellular signals into the nucleus involves inducible transcription factors, but how different signalling pathways act in a cell type specific fashion is poorly understood. Here, we studied the regulatory role of the AP 1 transcription factor family in blood development using embryonic stem cell differentiation coupled with genome wide transcription factor binding and gene expression analyses. AP 1 factors respond to MAP kinase signalling and comprise dimers of FOS, ATF and JUN proteins. To examine genes regulated by AP 1 and to examine how it interacts with other inducible transcription factors, we abrogated its global DNA binding activity using a dominant negative FOS peptide. We show that FOS and JUN bind to and activate a specific set of vascular genes and that AP 1 inhibition shifts the balance between smooth muscle and hematopoietic differentiation towards blood. Furthermore, AP 1 is required for de novo binding of TEAD4, a transcription factor connected to Hippo signalling. Our bottom up approach demonstrates that AP 1 and TEAD4 associated cis regulatory elements form hubs for multiple signalling responsive transcription factors and define the cistrome that regulates vascular and hematopoietic development by extrinsic signals.  AP 1 activates the expression of vascular genes in hemogenic endothelial cells and is required for de novo binding of the Hippo signaling transcription factor TEAD4.
Osteopontin plays a key role in vascular smooth muscle cell proliferation via EGFR mediated activation of AP 1 and C/EBPb pathways.
Venue: Pharmacological research

Osteopontin (OPN) is known as an active player in the progression of vascular remodeling diseases, however, the precise role in the proliferation of vascular smooth muscle cells (VSMC) is unclear. Thus, this study investigated the role of OPN in VSMC proliferation induced by 4 hydroxynonenal (HNE) and identified the intracellular signaling pathways involved in 4 HNE induced OPN production. In VSMC primary cultured from rat thoracic aorta as well as in VSMC in the media of aorta, HNE enhanced OPN expression in concentration dependent manners. Both the proliferation of cultured VSMC and PCNA positive cells in aortic tissues were also increased by HNE, which were attenuated in OPN deficient cells and aortic tissues isolated from OPN deficient mice, indicating a pivotal role of OPN in HNE induced VSMC proliferation. In the promoter assay, HNE increased OPN promoter activity, which was attenuated when the regions harboring AP 1 and C/EBPb binding sites were mutated. The increased bindings of AP 1 and C/EBPb to the OPN promoter were also demonstrated by ChIP analysis. In addition, the increases in both OPN expression and the activities of AP 1 and C/EBPb by HNE were attenuated by AG1478, an EGFR antagonist. Based on these results, it was suggested that HNE induced OPN expression in VSMC via signaling pathways involving AP 1 and C/EBPb, leading to increases in VSMC proliferation and subsequent vascular remodeling.
Selective advantage of trisomic human cells cultured in non standard conditions
Venue: Scientific reports

An abnormal chromosome number, a condition known as aneuploidy, is a ubiquitous feature of cancer cells. A number of studies have shown that aneuploidy impairs cellular fitness. However, there is also evidence that aneuploidy can arise in response to specific challenges and can confer a selective advantage under certain environmental stresses. Cancer cells are likely exposed to a number of challenging conditions arising within the tumor microenvironment. To investigate whether aneuploidy may confer a selective advantage to cancer cells, we employed a controlled experimental system. We used the diploid, colorectal cancer cell line DLD1 and two DLD1 derived cell lines carrying single chromosome aneuploidies to assess a number of cancer cell properties. Such properties, which included rates of proliferation and apoptosis, anchorage independent growth, and invasiveness, were assessed both under standard culture conditions and under conditions of stress (i.e. serum starvation, drug treatment, hypoxia) Similar experiments were performed in diploid vs. aneuploid non transformed human primary cells. Overall, our data show that aneuploidy can confer selective advantage to human cells cultured under non standard conditions. These findings indicate that aneuploidy can increase the adaptability of cells, even those, such as cancer cells, that are already characterized by increased proliferative capacity and aggressive tumorigenic phenotypes.
An agent based stock flow consistent model of the sustainable transition in the energy sector

In this paper, we investigate the effects on the economy of a feed in tariff policy mechanism aimed to foster investments in renewable energy production capacity. To this purpose, we employ an enriched version of the agent based Eurace macroeconomic model, where we have included an energy sector with a fossil fuel power producer as well as a renewable energy based one. Both power producers take pricing and capacity investment decisions based on the price of imported fossil fuel and the feed in tariff government policy. Results show that the feed in tariff policy is effective in fostering the sustainability transition of the energy sector and that it increases the level of investments with a positive impact on the unemployment rates. Moreover, we observe that its financing costs do not impact government finances, which actually improve following the better economic conditions. For high policy intensity, however, we observe an increasing GDP share of the investment sector in the economy, due to the building up of renewable production capacity, with a resulting crowding out of consumption, higher interest rates and prices. The final outcome on household well being therefore depends on what extent the chosen value judgment recognizes the importance of an economically and ecologically sustainable growth path.
Local utopia policy selection for multi objective reinforcement learning
Venue: 2016 IEEE Symposium Series on Computational Intelligence (SSCI)

Many real world applications are characterized by multiple conflicting objectives. In such problems, optimality is replaced by Pareto optimality and the goal is to find the Pareto frontier, a set of solutions representing different compromises among the objectives. Despite recent advances in multi objective optimization, the selection, given the Pareto frontier, of a Pareto optimal policy is still an important problem, prominent in practical applications such as economics and robotics. In this paper, we present a versatile approach for selecting a policy from the Pareto frontier according to user defined preferences. Exploiting a novel scalarization function and heuristics, our approach provides an easy to use and effective method for Pareto optimal policy selection. Furthermore, the scalarization is applicable in multiple policy learning strategies for approximating Pareto frontiers. To show the simplicity and effectiveness of our algorithm, we evaluate it on two problems and compare it to classical multi objective reinforcement learning approaches.
Graves' Disease.
Venue: The New England journal of medicine

What is Graves' disease? A: Graves' disease is an autoimmune disease that affects the thyroid. The thyroid is a small gland in the front of the neck. It makes hormones called T3 and T4 that regulate how the body uses energy. Thyroid hormone levels are controlled by the pituitary, which is a pea sized gland in the brain. It makes thyroid stimulating hormone (TSH) which triggers the thyroid to make thyroid hormone.