Miracle-dz/UniFAR-FTUs huggingface dataset:
On the effects of clouds and hazes in the atmospheres of hot Jupiters: semi‐analytical temperature–pressure profiles

Motivated by the work of Guillot, we present a semi-analytical formalism for calculating the temperature–pressure profiles in hot Jovian atmospheres which includes the effects of clouds/hazes and collision-induced absorption. Using the dual-band approximation, we assume that stellar irradiation and thermal emission from the hot Jupiter occur at distinct wavelengths (‘shortwave’ versus ‘longwave’). For a purely absorbing cloud/haze, we demonstrate its dual effect of cooling and warming the upper and lower atmosphere, respectively, which modifies, in a non-trivial manner, the condition for whether a temperature inversion is present in the upper atmosphere. The warming effect becomes more pronounced as the cloud/haze deck resides at greater depths. If it sits below the shortwave photosphere, the warming effect becomes either more subdued or ceases altogether. If shortwave scattering is present, its dual effect is to warm and cool the upper and lower atmospheres, respectively, thus counteracting the effects of enhanced longwave absorption by the cloud/haze. We make a tentative comparison of a four-parameter model to the temperature–pressure data points inferred from the observations of HD 189733b and estimate that its Bond albedo is approximately 10 per cent. Besides their utility in developing physical intuition, our semi-analytical models are a guide for the parameter space exploration of hot Jovian atmospheres via three-dimensional simulations of atmospheric circulation.
Synthesizing code quality rules from examples

Static Analysis tools have rules for several code quality issues and these rules are created by experts manually. In this paper, we address the problem of automatic synthesis of code quality rules from examples. We formulate the rule synthesis problem as synthesizing first order logic formulas over graph representations of code. We present a new synthesis algorithm RhoSynth that is based on Integer Linear Programming-based graph alignment for identifying code elements of interest to the rule. We bootstrap RhoSynth by leveraging code changes made by developers as the source of positive and negative examples. We also address rule refinement in which the rules are incrementally improved with additional user-provided examples. We validate RhoSynth by synthesizing more than 30 Java code quality rules. These rules have been deployed as part of Amazon CodeGuru Reviewer and their precision exceeds 75% based on developer feedback collected during live code-reviews within Amazon. Through comparisons with recent baselines, we show that current state-of-the-art program synthesis approaches are unable to synthesize most of these rules.
Polymer/graphene nanofoam nanocomposites: Properties and potential

Graphene is a nano-allotrope of carbon. It is a two dimensional (2D) one atom thick single layer of sp2 hybridized carbon atoms. An important form of graphene is the three dimensional (3D) graphene, also known as graphene nanofoam. This review article précises progress in the field of 3D graphene-based polymeric nanocomposites. The 3D macroscopic graphene nanostructures when used to reinforce polymer matrices attain superior structural and physical properties. This article considers the design, fabrication, characteristics, and promising applications of polymer/graphene nanofoam nanocomposites. The graphene nanofoam and polymer/graphene nanofoam nanocomposites have been prepared through advance approaches. The microstructure, electrical conductivity, specific capacitance, radiation shielding, mechanical properties, and other physical properties of the polymer/graphene nanofoam architectures have been studied. Interactions between the polymers and 3D graphene architecture are essential to enhance the nanocomposite performance. Polymer/graphene nanofoam nanocomposites applications are for solar cells, fuel cells, supercapacitors, and electromagnetic interference (EMI) shielding.
Streamer's Hell - Investigating Audience Influence in Live-Streams Beyond the Game

In the context of game live-streams, we focus on whether audience influence options can be extended beyond the game, e.g., to the streamers' environment (e.g., controlling their room lighting), the streamers themselves (e.g., activating vibration feedback on their forearms) and the streamers' hardware and peripheral devices (e.g., switching key bindings). An online study (n=81) showed that viewers have mixed feelings and that the context matters, as only a few game genres are assessed as suitable for such an experience. In a lab-study six streamers experienced the idea while playing a horror game. They saw appeal in extending the influence space, but also again highlighted that context matters and customization options are necessary. The studies hint that although this interactivity is from a technical perspective independent of the content streamed, in practice it is not, as the perception is moderated by e.g., the game and why the streamer is playing it.
Scalable linear invariant generation with Farkas’ lemma

Invariant generation is a classical problem to automatically generate invariants to aid the formal analysis of programs. In this work, we consider the problem of generating tight linear-invariants over affine programs (i.e., programs with affine guards and updates) without a prescribed goal property. In the literature, the only known sound and complete characterization to solve this problem is via Farkas’ Lemma (FL), and has been implemented through either quantifier elimination or reasonable heuristics. Although FL-based approaches can generate highly accurate linear invariants from the completeness of FL, the main bottleneck to applying these approaches is the scalability issue caused by either non-linear constraints or combinatorial explosion. We base our approach on the only practical FL-based approach [Sankaranarayanan et al., SAS 2004] that applies FL with reasonable heuristics, and develop two novel and independent improvements to leverage the scalability. The first improvement is the novel idea to generate invariants at one program location in a single invariant-generation process, so that the invariants for each location are generated separately rather than together in a single computation. This idea naturally leads to a parallel processing that divides the invariant-generation task for all program locations by assigning the locations separately to multiple processors. Moreover, the idea enables us to develop detailed technical improvements to further reduce the combinatorial explosion in the original work [Sankaranarayanan et al., SAS 2004]. The second improvement is a segmented subsumption testing in the CNF-to-DNF expansion that allows discovering more local subsumptions in advance. We formally prove that our approach has the same accuracy as the original work and thus does not incur accuracy loss on the generated invariants. Moreover, experimental results on representative benchmarks involving non-trivial linear invariants demonstrate that our approach improves the runtime of the original work by several orders of magnitude, even in the non-parallel scenario that sums up the execution time for all program locations. Hence, our approach constitutes the first significant improvement in FL-based approaches for linear invariant generation after almost two decades.
Communication Sequences Indicate Team Cohesion: A Mixed-Methods Study of Ad Hoc League of Legends Teams

Team cohesion is a widely known predictor of performance and collaborative satisfaction. However, how it develops and can be assessed, especially in fast-paced ad hoc dynamic teams, remains unclear. An unobtrusive and objective behavioural measure of cohesion would help identify determinants of cohesion in these teams. We investigated team communication as a potential measure in a mixed-methods study with 48 teams (n=135) in the digital game League of Legends. We first established that cohesion shows similar performance and satisfaction in League of Legends. teams as in non-game teams and confirmed a positive relationship between communication word frequency and cohesion. Further, we conducted an in-depth exploratory qualitative analysis of the communication sequences in a high-cohesion and a low-cohesion team. High cohesion is associated with sequences of apology->encouragement, suggestion->agree/acknowledge, answer->answer, and answer->question, while low-cohesion is associated with sequences of opinion/analysis->opinion/analysis, disagree->disagree, command->disagree, and frustration->frustration. Our findings also show that cohesion is important to team satisfaction independently of the match outcomes. We highlight that communication sequences are more useful than frequencies to determine team cohesion via player interactions.
Bridging the semantic gap between qualitative and quantitative models of distributed systems

Today’s distributed systems must satisfy both qualitative and quantitative properties. These properties are analyzed using very different formal frameworks: expressive untimed and non-probabilistic frameworks, such as TLA+ and Hoare/separation logics, for qualitative properties; and timed/probabilistic-automaton-based ones, such as Uppaal and Prism, for quantitative ones. This requires developing two quite different models of the same system, without guarantees of semantic consistency between them. Furthermore, it is very hard or impossible to represent intrinsic features of distributed object systems—such as unbounded data structures, dynamic object creation, and an unbounded number of messages—using finite automata. In this paper we bridge this semantic gap, overcome the problem of manually having to develop two different models of a system, and solve the representation problem by: (i) defining a transformation from a very general class of distributed systems (a generalization of Agha’s actor model) that maps an untimed non-probabilistic distributed system model suitable for qualitative analysis to a probabilistic timed model suitable for quantitative analysis; and (ii) proving the two models semantically consistent. We formalize our models in rewriting logic, and can therefore use the Maude tool to analyze qualitative properties, and statistical model checking with PVeStA to analyze quantitative properties. We have automated this transformation and integrated it, together with the PVeStA statistical model checker, into the Actors2PMaude tool. We illustrate the expressiveness of our framework and our tool’s ease of use by automatically transforming untimed, qualitative models of numerous distributed system designs—including an industrial data store and a state-of-the-art transaction system—into quantitative models to analyze and compare the performance of different designs.
Nonempirical Interactions for the Nuclear Shell Model: An Update

The nuclear shell model has perhaps been the most important conceptual and computational paradigm for the understanding of the structure of atomic nuclei. While the shell model has been used predominantly in a phenomenological context, there have been efforts stretching back more than half a century to derive shell model parameters based on a realistic interaction between nucleons. More recently, several ab initio many-body methods—in particular, many-body perturbation theory, the no-core shell model, the in-medium similarity renormalization group, and coupled-cluster theory—have developed the capability to provide effective shell model Hamiltonians. We provide an update on the status of these methods and investigate the connections between them and their potential strengths and weaknesses, with a particular focus on the in-medium similarity renormalization group approach. Three-body forces are demonstrated to be important for understanding the modifications needed in phenomenological treatments. We then review some applications of these methods to comparisons with recent experimental measurements, and conclude with some remaining challenges in ab initio shell model theory.
Large effect loci have a prominent role in Darwin’s finch evolution

A fundamental goal in evolutionary biology is to understand the genetic architecture of adaptive traits and its evolutionary relevance. Using whole-genome data of 3,958 Darwin’s finches on the Galápagos Island of Daphne Major we identify six loci of large effect that explain 46% of the variation in beak size of Geospiza fortis, a key ecological trait. Allele frequency changes across 30 years at these loci affected beak morphology in two ways. An abrupt change in beak size occurred in Geospiza fortis as a result of natural selection associated with a drought, and a more gradual change occurred in G. scandens as a result of introgressive hybridization. This study demonstrates how large effect loci are a major contributor to the genetic architecture of rapid diversification during adaptive radiations. One Sentence Summary Allele frequency change at six loci of large effect causes evolutionary change in key ecological traits.
Dark Matter from new Technicolor Theories

We investigate dark matter candidates emerging in recently proposed technicolor theories. We determine the relic density of the lightest, neutral, stable technibaryon having imposed weak thermal equilibrium conditions and overall electric neutrality of the Universe. In addition we consider sphaleron processes that violate baryon, lepton and technibaryon number. Our analysis is performed in the case of a first order electroweak phase transition as well as a second order one. We argue that, in both cases, the new technibaryon contributes to the dark matter in the Universe. Finally we examine the problem of the constraints on these types of dark matter components from earth based experiments.
Assistive Loading Promotes Goal-Directed Tuning of Stretch Reflex Gains

Abstract Voluntary movements are prepared before they are executed. Preparatory activity has been observed across the CNS and recently documented in first-order neurons of the human PNS (i.e., in muscle spindles). Changes seen in sensory organs suggest that independent modulation of stretch reflex gains may represent an important component of movement preparation. The aim of the current study was to further investigate the preparatory modulation of short-latency stretch reflex responses (SLRs) and long-latency stretch reflex responses (LLRs) of the dominant upper limb of human subjects. Specifically, we investigated how different target parameters (target distance and direction) affect the preparatory tuning of stretch reflex gains in the context of goal-directed reaching, and whether any such tuning depends on preparation duration and the direction of background loads. We found that target distance produced only small variations in reflex gains. In contrast, both SLR and LLR gains were strongly modulated as a function of target direction, in a manner that facilitated the upcoming voluntary movement. This goal-directed tuning of SLR and LLR gains was present or enhanced when the preparatory delay was sufficiently long (>250 ms) and the homonymous muscle was unloaded [i.e., when a background load was first applied in the direction of homonymous muscle action (assistive loading)]. The results extend further support for a relatively slow-evolving process in reach preparation that functions to modulate reflexive muscle stiffness, likely via the independent control of fusimotor neurons. Such control can augment voluntary goal-directed movement and is triggered or enhanced when the homonymous muscle is unloaded.
Aplicando restricciones en un datawarehouse temporal utilizando UML/OCL

Un datawarehouse es una coleccion de datos no volatiles, variables en el tiempo y orientado a un tema especifico utilizado para tomar decisiones. La necesidad de registrar valores que permitan evaluar tendencias, variaciones, maximos y minimos, justifican considerar en el diseno la evolucion temporal de atributos o interrelaciones. La determinacion de restricciones que permitan mantener la consistencia de los datos almacenados e impidan los solapamientos de rangos temporales, permiten conservar la integridad de la base de datos. En la etapa de modelado la determinacion de estas restricciones se realizan de manera informal. Establecer sin ambiguedad las mismas no es posible sin un lenguaje apropiado. Proponemos determinar restricciones en el modelo de datos transformando el esquema multidimensional temporal a UML y emplear OCL para documentar dichas limitaciones.
Inverse kinematic problem and boundary rigidity of Riemannian surfaces

Given a compact manifold with boundary with unknown Riemannian metric. The problem is to reconstruct the metric in a class of conformal metrics from knowledge of lengths of all closed geodesics (kinematic data). An integral inequality is stated which implies uniqueness and stability for this problem. If the conformal class is not known a unique reconstruction is not possible since of shortage of information. It is proved that the list of all geodesic lengths is sufficient for unique determination of a Riemannian metric in a compact surface with boundary up to an automorphism which fix the boundary. Some related problems of integral geometry are studied. Key words: Geodesic curve, Travel-time, Conjugate point, Geodesic flow, Hodograph, Geodesic integral transform.
Circadian regulation of glutamate release pathways shapes synaptic throughput in the brainstem nucleus of the solitary tract (NTS)

Circadian regulation of autonomic reflex pathways pairs physiological function with the daily light cycle. The brainstem nucleus of the solitary tract (NTS) is a key candidate for rhythmic control of the autonomic nervous system. Here we investigated circadian regulation of NTS neurotransmission and synaptic throughput using patch-clamp electrophysiology in brainstem slices from mice. We found that spontaneous quantal glutamate release on to NTS neurons showed strong circadian rhythmicity, with the highest rate of release during the light phase and the lowest in the dark, that were sufficient to drive day / night differences in constitutive postsynaptic action potential firing. In contrast, afferent-evoked action potential throughput was enhanced during the dark and diminished in the light. Afferent-driven synchronous release pathways showed a similar decrease in release probability that did not explain the enhanced synaptic throughput during the night. However, analysis of postsynaptic membrane properties revealed diurnal changes in conductance; which, when coupled with the circadian changes in glutamate release pathways, tuned synaptic throughput between the light and dark phases. These coordinated pre- / postsynaptic changes encode nuanced control over synaptic performance and pair NTS action potential firing and vagal throughput with time of day.
Defining the Roles of Pyruvate Oxidation, TCA Cycle, and Mannitol Metabolism in Methicillin-Resistant Staphylococcus aureus Catheter-Associated Urinary Tract Infection

While Staphylococcus aureus has historically not been considered a uropathogen, S. aureus urinary tract infection (UTI) is clinically significant in certain patient populations, including those with chronic indwelling urinary catheters. Moreover, most S. aureus strains causing catheter-associated UTI (CAUTI) are methicillin-resistant S. aureus (MRSA). ABSTRACT Methicillin-resistant Staphylococcus aureus (MRSA) is an important cause of complicated urinary tract infection (UTI) associated with the use of indwelling urinary catheters. Previous reports have revealed host and pathogen effectors critical for MRSA uropathogenesis. Here, we sought to determine the significance of specific metabolic pathways during MRSA UTI. First, we identified four mutants from the Nebraska transposon mutant library in the MRSA JE2 background that grew normally in rich medium but displayed significantly reduced growth in pooled human urine (HU). This prompted us to transduce the uropathogenic MRSA 1369 strain with the transposon mutants in sucD and fumC (tricarboxylic acid [TCA] cycle), mtlD (mannitol metabolism), and lpdA (pyruvate oxidation). Notably, sucD, fumC, and mtlD were also significantly upregulated in the MRSA 1369 strain upon exposure to HU. Compared to the WT, the MRSA 1369 lpdA mutant was significantly defective for (i) growth in HU, and (ii) colonization of the urinary tract and dissemination to the kidneys and the spleen in the mouse model of catheter-associated UTI (CAUTI), which may be attributed to its increased membrane hydrophobicity and higher susceptibility to killing by human blood. In contrast to their counterparts in the JE2 background, the sucD, fumC, and mtlD mutants in the MRSA 1369 background grew normally in HU; however, they displayed significant fitness defects in the CAUTI mouse model. Overall, identification of novel metabolic pathways important for the urinary fitness and survival of MRSA can be used for the development of novel therapeutics. IMPORTANCE While Staphylococcus aureus has historically not been considered a uropathogen, S. aureus urinary tract infection (UTI) is clinically significant in certain patient populations, including those with chronic indwelling urinary catheters. Moreover, most S. aureus strains causing catheter-associated UTI (CAUTI) are methicillin-resistant S. aureus (MRSA). MRSA is difficult to treat due to limited treatment options and the potential to deteriorate into life-threatening bacteremia, urosepsis, and shock. In this study, we found that pathways involved in pyruvate oxidation, TCA cycle, and mannitol metabolism are important for MRSA fitness and survival in the urinary tract. Improved understanding of the metabolic needs of MRSA in the urinary tract may help us develop novel inhibitors of MRSA metabolism that can be used to treat MRSA-CAUTI more effectively.
Self-bound many-body states of quasi-one-dimensional dipolar Fermi gases: Exploiting Bose-Fermi mappings for generalized contact interactions

Using a combination of results from exact mappings and from mean-field theory we explore the phase diagram of quasi-one-dimensional systems of identical fermions with attractive dipolar interactions. We demonstrate that at low density these systems provide a realization of a single-component one-dimensional Fermi gas with a generalized contact interaction. Using an exact duality between one-dimensional Fermi and Bose gases, we show that when the dipole moment is strong enough, bound many-body states exist, and we calculate the critical coupling strength for the emergence of these states. At higher densities, the Hartree-Fock approximation is accurate, and by combining the two approaches we determine the structure of the phase diagram. The many-body bound states should be accessible in future experiments with ultracold polar molecules.