Miracle-dz/UniFAR-FTUs huggingface dataset:
A Potent and Selective Histamine H4 Receptor Antagonist with Anti-Inflammatory Properties

Histamine mediates its physiological function through binding to four known histamine receptors. Here, we describe the first selective antagonist of the histamine H4 receptor, the newest member of the histamine receptor family, and provide evidence that such antagonists have anti-inflammatory activity in vivo. 1-[(5-chloro-1H-indol-2-yl)carbonyl]-4-methylpiperazine (JNJ 7777120) has a Ki of 4.5 nM versus the human receptor and a pA2 of 8.1. It is equipotent against the human, mouse, and rat receptors. It exhibits at least 1000-fold selectivity over H1, H2, or H3 receptors and has no cross-reactivity against 50 other targets. This compound has an oral bioavailability of ∼30% in rats and 100% in dogs, with a half-life of ∼3 h in both species. JNJ 7777120 blocks histamine-induced chemotaxis and calcium influx in mouse bone marrow-derived mast cells. In addition, it can block the histamine-induced migration of tracheal mast cells from the connective tissue toward the epithelium in mice. JNJ 7777120 significantly blocks neutrophil infiltration in a mouse zymosan-induced peritonitis model. This model is reported to be mast cell-dependent, which suggests that the compound effect may be mediated by mast cells. These results indicate that the histamine H4 receptor plays a role in the inflammatory process. Selective H4 receptor antagonists like JNJ 7777120 may have the potential to be useful in treating inflammation in humans.
Searching for deadlocks while debugging concurrent haskell programs

This paper presents an approach to searching for deadlocks in Concurrent Haskell programs. The search is based on a redefinition of the IO monad which allows the reversal of Concurrent Haskells concurrency primitives. Hence, it is possible to implement this search by a backtracking algorithm checking all possible schedules of the system. It is integrated in the Concurrent Haskell Debugger (CHD), and automatically searches for deadlocks in the background while debugging. The tool is easy to use and the small modifications of the source program are done by a preprocessor. In the tool we use iterative deepening as search strategy which quickly detects deadlocks close to the actual system configuration and utilizes idle time during debugging at the best.
Simone de Beauvoir's Political Thinking

By exploring the life and work of the influential feminist thinker Simone de Beauvoir, this book shows how each of us lives within political and social structures that we can - and must - play a part in transforming. It argues that Beauvoir's careful examination of her own existence can also be understood as a dynamic method for political thinking. As the contributors illustrate, Beauvoir's political thinking proceeds from the bottom up, using examples from individual lives as the basis for understanding and transforming our collective existence. For example, she embraced her responsibility as a French citizen as making her complicit in the French war against Algeria. Here, she sees her role as an oppressor. In other contexts, she looks to the lives of individual women, including herself, to understand the dimensions of gender inequality. This volume's six tightly connected essays home in on the individual's relationship to community, and how one's freedom interacts with the freedom of other people. Here, Beauvoir is read as neither a liberal nor a communitarian. The authors focus on her call for individuals to realize their freedom while remaining consistent with ethical obligations to the community. Beauvoir's account of her own life and the lives of others is interpreted as a method to understand individuals in relations to others, and as within structures of personal, material, and political oppression. Beauvoir's political thinking makes it clear that we cannot avoid political action. To do nothing in the face of oppression denies freedom to everyone, including oneself.
Using Empirically Constructed Lexical Resources for Named Entity Recognition

Because of privacy concerns and the expense involved in creating an annotated corpus, the existing small-annotated corpora might not have sufficient examples for learning to statistically extract all the named-entities precisely. In this work, we evaluate what value may lie in automatically generated features based on distributional semantics when using machine-learning named entity recognition (NER). The features we generated and experimented with include n-nearest words, support vector machine (SVM)-regions, and term clustering, all of which are considered distributional semantic features. The addition of the n-nearest words feature resulted in a greater increase in F-score than by using a manually constructed lexicon to a baseline system. Although the need for relatively small-annotated corpora for retraining is not obviated, lexicons empirically derived from unannotated text can not only supplement manually created lexicons, but also replace them. This phenomenon is observed in extracting concepts from both biomedical literature and clinical notes.
Transcriptomic Analysis of Circulating Leukocytes Reveals Novel Aspects of the Host Systemic Inflammatory Response to Sheep Scab Mites

Infestation of ovine skin with the ectoparasitic mite Psoroptes ovis results in the development of a rapid cutaneous inflammatory response, leading to the crusted skin lesions characteristic of sheep scab. To facilitate the identification of novel diagnostic and therapeutic targets, a better understanding of the host-parasite relationship in sheep scab is essential. Although our knowledge of the host's local cutaneous inflammatory response to sheep scab has increased in recent years, we still know relatively little about the mechanisms of this response at the systemic level. This study used a combined network and pathway analysis of the in vivo transcriptomic response of circulating leukocytes to infestation with P. ovis, during a 6 week period. Network graph analysis identified six temporally-associated gene clusters, which separated into two distinct sub-networks within the graph, representing those genes either up or down-regulated during the time course. Functional and pathway analysis of these clusters identified novel insights into the host systemic response to P. ovis infestation, including roles for the complement system, clotting cascade and fibrinolysis. These analyses also highlighted potential mechanisms by which the systemic immune response to sheep scab can influence local tissue responses via enhanced leukocyte activation and extravasation. By analysing the transcriptomic responses of circulating leukocytes in sheep following infestation with P. ovis, this study has provided key insights into the inflammatory response to infestation and has also demonstrated the utility of these cells as a proxy of events occurring at local tissue sites, providing insight into the mechanisms by which a local allergen-induced inflammatory response may be controlled.
Search for OFDM synchronization waveforms with good aperiodic autocorrelations

The problem of searching for OFDM synchronization waveforms with good aperiodic autocorrelation properties is addressed. A synchronization waveform is embedded within data in the form of pilot tones. Selection of the sub-channel locations to be reserved for synchronization pilots is critical, as each different selection results in a waveform with a different sidelobe pattern. The optimal pilot tone location selection problem is mathematically intractable and an exhaustive search for practical systems is infeasible. A genetic algorithm is employed for searching the locations of a number of pilot tones among all OFDM subcarriers, such that the resulting time waveform has good autocorrelation properties. The performance of the generated synchronization waveforms was evaluated in a simulated OFDM system and it was demonstrated that they achieve the desired frame synchronization performance. It was observed that the genetic algorithm accomplishes the task much faster than a random search.
Detecting social context: A method for social event classification using naturalistic multimodal data

As intelligent interactive systems become prevalent in human social environments, it is important they are able to understand social context. Humans process information to derive expected behaviors from their social context; however to date few autonomous systems have taken advantage of this rich resource of information. Social context processing is a broad problem area, and in this paper we focus specifically on social event detection. We used machine learning techniques to automatically classify 320 multinational YouTube videos of eight complex social events, including interviews, parties, weddings, and sporting events. This paper presents three major contributions. First, we demonstrate fairly high classification accuracy on extremely noisy, real-world data. Second, we show that a multimodal approach plays a significant role in achieving such accuracy (video and audio features together outperform either one alone). Third, we provide evidence that high level social information can be extracted from video automatically. These findings will be useful to researchers in the fields of affective computing, human-machine interaction, and robotics, as they design systems to leverage social context.
Time-dependent transport in interacting and noninteracting resonant-tunneling systems.

We consider a mesoscopic region coupled to two leads under the influence of external timedependent voltages. The time dependence is coupled to source and drain contacts, the gates controlling the tunnel-barrier heights, or to the gates that define the mesoscopic region. We derive, with the Keldysh nonequilibrium-Green-function technique, a formal expression for the fully nonlinear, time-dependent current through the system. The analysis admits arbitary interactions in the mesoscopic region, but the leads are treated as noninteracting. For proportionate coupling to the leads, the time-averaged current is simply the integral between the chemical potentials of the time-averaged density of states, weighted by the coupling to the leads, in close analogy to the time-independent result of Meir and Wingreen [Phys. Rev. Lett. 68, 2512 (1992)]. Analytical and numerical results for the exactly solvable noninteracting resonant-tunneling system are presented. Due to the coherence between the leads and the resonant site, the current does not follow the driving signal adiabatically: a "ringing" current is found as a response to a voltage pulse, and a complex time dependence results in the case of harmonic driving voltages. We also establish a connection to recent linear-response calculations, and to earlier studies of electron-phonon scattering effects in resonant tunneling.
Robust EZW Image Compression using Rate -

The EZW(Embedded Zerotree Wavelet)-like image compression algorithms lack the error-resilience ability in noisy transmission environments. We propose the channel-optimized source coding scheme to improve the robustness of them. First, a block-based method is adopted to localize the error eeects. Then we assign bits to each block by applying dynamic bit allocation to the block-based EZW algorithm based on the rate-distortion functions computed from the channel noise models. The performance of our method was evaluated on both the binary symmetric channel and burst noise channel models.
Novel RC Compact Thermal Model of HV Inverter Module for Electro-Thermal Coupling Simulation

This paper describes a novel RC compact thermal model which has the capability of representing thermal behavior of multi chip inverter module peculiar to HV. This RC compact thermal model can take into account lateral heat spreading within the modules and thermal interference among Si chips. The thermal model was validated in comparison of temperature transient responses among the results calculated using the proposed model and FEM. The electro-thermal coupling simulation using this RC compact thermal model offers reasonable accuracy for prediction of the Si chip temperature in HV inverter module.
Tissue Homeostasis in the Wing Disc of Drosophila melanogaster: Immediate Response to Massive Damage during Development

All organisms have developed mechanisms to respond to organ or tissue damage that may appear during development or during the adult life. This process of regeneration is a major long-standing problem in Developmental Biology. We are using the Drosophila melanogaster wing imaginal disc to study the response to major damage inflicted during development. Using the Gal4/UAS/Gal80TS conditional system, we have induced massive cell killing by forcing activity of the pro-apoptotic gene hid in two major regions of the disc as defined by Gal4 inserts in the genes rotund (rn) and spalt (sal). The procedure ensures that at the end of a 40–48 hrs of ablation period the great majority of the cells of the original Rn or Sal domains have been eliminated. The results indicate that the damage provokes an immediate response aimed to keep the integrity of the epithelium and to repair the region under ablation. This includes an increase in cell proliferation to compensate for the cell loss and the replacement of the dead cells by others from outside of the damaged area. The response is almost contemporaneous with the damage, so that at the end of the ablation period the targeted region is already reconstructed. We find that the proliferative response is largely systemic, as the number of cells in division increases all over the disc. Furthermore, our results indicate that the Dpp and Wg pathways are not specifically involved in the regenerative response, but that activity of the JNK pathway is necessary both inside and outside the ablated domain for its reconstruction.
Beyond mothers and children: finding the family in pediatric psychology.

a new invention, and few families owned one. Children were to be reared in a two-parent family consisting of one set of biological parents and their children. Adoptions were generally kept secret. Unwed motherhood, homosexuality, and alcoholism were shameful topics discussed only behind closed doors. There was no sex education in schools. Divorce was taboo, and most people had never heard of marijuana. Racial segregation was legal and interracial marriage was illegal. If a woman with children worked outside the home, she was pitied because her husband was not a good provider. Women with serious careers did not marry. In pediatrics, antibiotics were newly available and IM penicillin was cheerfully administered to children for all sorts of infections without any knowledge of the potential for sensitivities or the development of resistant bacterial strains. There was no 911 emergency response system, no organ transplantation, no dialysis, no treatment for cancer. Humans were thought to have 48 chromosomes, and DNA had not yet been discovered. The concept of child abuse did not exist, but doubt was beginning to be cast on the syndrome of spontaneous subdural hematoma, which had been described in the literature (Caffey, 1946). Children with physical and mental disabilities were routinely excluded from school. If their disabilities were severe, they were institutionalized— permanently. Iron deficiency anemia and polio were among the top pediatric problems. (There was no iron-fortified infant formula and no polio vaccine.) Infectious diseases accounted for the majority Journal of Pediatric Psychology, Vol. 25, No. 3, 2000, pp. 161–169
An Analysis of a FETI-DP Algorithm on Irregular Subdomains in the Plane

In the theory for domain decomposition algorithms of the iterative substructuring family, each subdomain is typically assumed to be the union of a few coarse triangles or tetrahedra. This is an unrealistic assumption, in particular if the subdomains result from the use of a mesh partitioner, in which case they might not even have uniformly Lipschitz continuous boundaries. The purpose of this study is to derive bounds for the condition number of these preconditioned conjugate gradient methods which depend only on a parameter in an isoperimetric inequality, two geometric parameters characterizing John and uniform domains, and the maximum number of edges of any subdomain. A related purpose is to explore to what extent well-known technical tools previously developed for quite regular subdomains can be extended to much more irregular subdomains. Some of these results are valid for any John domain, while an extension theorem, which is needed in this study, requires that the subdomains have complements which are uniform. The results, so far, are complete only for problems in two dimensions. Details are worked out for a FETI-DP algorithm and numerical results support the findings. Some of the numerical experiments illustrate that care must be taken when selecting the scaling of the preconditioners in the case of irregular subdomains.
Direct Importance Estimation with Gaussian Mixture Models

The ratio of two probability densities is called the importance and its estimation has gathered a great deal of attention these days since the importance can be used for various data processing purposes. In this paper, we propose a new importance estimation method using Gaussian mixture models (GMMs). Our method is an extention of the Kullback-Leibler importance estimation procedure (KLIEP), an importance estimation method using linear or kernel models. An advantage of GMMs is that covariance matrices can also be learned through an expectation-maximization procedure, so the proposed method—which we call the Gaussian mixture KLIEP (GM—KLIEP)—is expected to work well when the true importance function has high correlation. Through experiments, we show the validity of the proposed approach.
Advanced Microbubbles as a Multifunctional Platform Combining Imaging and Therapy

Microbubbles as traditional ultrasound contrast agents have seen tremendous developments and bio-applications in the past decades. Due to their outstanding performance, advanced microbubbles as a multifunctional platform combining both imaging and therapy have been increasingly attracting attention. Associated with ultrasound-mediated stimuli, targeting drug transportation with high precision can be established and, as a consequence, a synergistic treatment strategy may prevail, which implies a bright perspective for this brand-new technology. This perspective article will summarize the latest developments on the advanced microbubbles, and review their emerging biomedical applications for the vast community of both applied ultrasound and functional ultrasound-based materials.
Path dependence, initial conditions, and routines in organizations: The Toyota production system re-examined

The notion of path dependence was first explicitly used to explain prevailing technical standards (David 1985; Arthur 1989). It has also been discussed in recent decades as a useful way of analysing the development of a range of other subjects, including national innovation systems (Iammarino 2005), industrial districts (Kenney and von Burg 1999) and politics (Pierson 2004). For a long time, at the micro-level of individual organizations a much less elaborate use of the concept has been made (with the notable exception of David 1994) and it is only recently that interest in this field of application has expanded further (for example, Sydow et al. 2005). I argue that using path dependence for the historical analysis of organizational change can be very fruitful. To do so, however, the key elements of path dependence — sensitivity to initial conditions and lock-in mechanisms — need to be conceptualized more precisely and linked to one another.
Specular surface reconstruction for multi-camera corneal topographer arrangements

A novel specular surface reconstruction approach developed for and used in an experimental multi-camera corneal topographer arrangement is presented in the paper. The tear-film coated, and therefore specular, corneal surface is mathematically reconstructed from the corneal images taken simultaneously by the calibrated cameras of the arrangement. The surface reconstruction is achieved by the joint solution of partial differential equations (PDE's) that is derived from the mapping between the measurement-pattern and its virtual images taken by the cameras. The PDE's - each given in an advantageous form for one of the cameras - describe the phenomenon of light-reflection at the corneal surface. The portions of the corneal surface that reflect - possibly different - measurement-pattern points to more than one camera convey starting points for the mathematical reconstruction of the surface.
Synergy of Dynamic Frequency Scaling and Demotion on DRAM Power Management: Models and Optimizations

Main memory (or DRAM) is one of the most significant components to the computer system's performance and energy consumption. Dynamic frequency scaling (DFS) and DRAM low-power states (Demotion) are two main-stream techniques for DRAM power management. DFS reduces the operation frequency of memory channels and DRAM devices when the memory bandwidth is under-utilized, whereas demotion transits individual memory ranks to low-power states during long idle periods. Despite that there have been fruitful research work for DFS and demotion separately, little attention has been paid to the synergy between these two techniques. To bridge this gap, this paper conducts a comprehensive study on the synergy between DFS and demotion. In particular, we leverage queuing theory to develop analytical models for the energy consumption and performance of DRAM systems with DFS and demotion. These models provide valuable insights into the synergy between DFS and demotion. We further attempt to minimize the energy consumption by considering both DFS and demotion while keeping a pre-defined performance penalty budget. To reduce the optimization complexity, we develop simple yet effective heuristics to search near-optimum DFS-demotion configurations. We experimentally compare our design with other state-of-the-art DRAM energy saving policies using detailed simulations of a large set of workloads. Experimental results show the accuracy of our analytical models and the effectiveness of our optimizations.
Transcription Factor Families Have Much Higher Expansion Rates in Plants than in Animals1

Transcription factors (TFs), which are central to the regulation of gene expression, are usually members of multigene families. In plants, they are involved in diverse processes such as developmental control and elicitation of defense and stress responses. To investigate if differences exist in the expansion patterns of TF gene families between plants and other eukaryotes, we first used Arabidopsis (Arabidopsis thaliana) TFs to identify TF DNA-binding domains. These DNA-binding domains were then used to identify related sequences in 25 other eukaryotic genomes. Interestingly, among 19 families that are shared between animals and plants, more than 14 are larger in plants than in animals. After examining the lineage-specific expansion of TF families in two plants, eight animals, and two fungi, we found that TF families shared among these organisms have undergone much more dramatic expansion in plants than in other eukaryotes. Moreover, this elevated expansion rate of plant TF is not simply due to higher duplication rates of plant genomes but also to a higher degree of expansion compared to other plant genes. Further, in many Arabidopsis-rice (Oryza sativa) TF orthologous groups, the degree of lineage-specific expansion in Arabidopsis is correlated with that in rice. This pattern of parallel expansion is much more pronounced than the whole-genome trend in rice and Arabidopsis. The high rate of expansion among plant TF genes and their propensity for parallel expansion suggest frequent adaptive responses to selection pressure common among higher plants.