Miracle-dz/UniFAR-FTUs huggingface dataset:
Prophenoloxidase-activating Enzyme of the Silkworm, Bombyx mori

Prophenoloxidase-activating enzyme (PPAE) was purified to homogeneity as judged by SDS-polyacrylamide gel electrophoresis from larval cuticles of the silkworm, Bombyx mori. The purified PPAE preparation was shown to be a mixture of the isozymes of PPAE (PPAE-I and PPAE-II), which were eluted at different retention times in reversed-phase high performance liquid chromatography. PPAE-I and PPAE-II seemed to be post translationally modified isozymes and/or allelic variants. Both PPAE isozymes were proteins composed of two polypeptides (heavy and light chains) that are linked by disulfide linkage(s) and glycosylated serine proteases. The results of cDNA cloning, peptide mapping, and amino acid sequencing of PPAE revealed that PPAE is synthesized as prepro-PPAE with 441 amino acid residues and is activated from pro-PPAE by cleavage of a peptide bond between Lys152 and Ile153. The homology search showed 36.9% identity of PPAE to easter, which is a serine protease involved in dorso-ventral pattern formation in theDrosophila embryo, and indicated the presence of two consecutive clip-like domains in the light chain. A single copy of the PPAE gene was suggested to be present in the silkworm genome. In the fifth instar larvae, PPAE transcripts were detected in the integument, hemocytes, and salivary glands but not in the fat body or mid gut. A polypeptide cross-reactive to mono-specific anti-PPAE/IgG was transiently detected in the extract of eggs between 1 and 3 h after they were laid.
Learning from Skewed Class Multi-relational Databases

Relational databases, with vast amounts of data¨Cfrom financial transactions, marketing surveys, medical records, to health informatics observations¨C and complex schemas, are ubiquitous in our society. Multirelational classification algorithms have been proposed to learn from such relational repositories, where multiple interconnected tables (relations) are involved. These methods search for relevant features both from a target relation (in which each tuple is associated with a class label) and relations related to the target, in order to better classify target relation tuples. However, in many practical database applications, such as credit card fraud detection and disease diagnosis, the target tuples are highly imbalanced. That is, the number of examples of one class (majority class) in the target relation is much higher than the others (minority classes). Many existing methods thus tend to produce poor predictive performance over the underrepresented class in the data. This paper presents a strategy to deal with such imbalanced multirelational data. The method learns from multiple views (feature sets) of relational data in order to construct view learners with different awareness of the imbalanced problem. These different observations possessed by multiple view learners are then combined, in order to yield a model which has better knowledge on both the majority and minority classes in a relational database. Experiments performed on six benchmarking data sets show that the proposed method achieves promising results when compared with other popular relational data mining algorithms, in terms of the ROC curve and AUC value obtained. In particular, an important result indicates that the method is superior when the class imbalanced is very high.
Neurociencia social: una breve introducción al estudio de las bases neurobiológicas de la conducta social

La neurociencia social es una nueva rama de las neurociencias cognitivas cuyo objetivo es el estudio de las bases biologicas (inmunes, endocrinas, neuronales) de la conducta social, combinando las herramientas mas avanzadas de la neurociencia cognitiva como las tecnicas de neuroimagen y la neuropsicologia, junto con la investigacion en ciencias cognitivas y en ciencias sociales como la psicologia social, la economia y las ciencias politicas. En este articulo se hace una breve revision de los temas principales de los cuales se encarga la neurociencia social: percepcion social (percepcion de rostros, cuerpos y acciones); teoria de la mente; entendimiento de las emociones ajenas; entendimiento de uno mismo (autor reconocimiento, sentido de agencia y pertenencia, autor refl exion, auto concepto, memoria autobiografi ca); autorregulacion; actitudes y prejuicios; y rechazo social.
Real‐time nmr studies on a transient folding intermediate of barstar

The refolding of barstar, the intracellular inhibitor of barnase, is dominated by the slow formation of a cis peptidyl prolyl bond in the native protein. The triple mutant C40/82A P27A in which two cysteine residues and one trans proline were replaced by alanine was used as model system to investigate the kinetics and structural consequences of the trans/cis interconversion of Pro48. One‐ and two‐dimensional real‐time NMR spectroscopy was used to follow the trans/cis interconversion after folding was initiated by rapid dilution of the urea denatured protein. Series of 1H, 15N HSQC spectra acquired with and without the addition of peptidyl prolyl isomerase unambiguously revealed the accumulation of a transient trans‐Pro48 intermediate within the dead time of the experiment. Subtle chemical shift differences between the native state and the intermediate spectra indicate that the intermediate is predominantly native‐like with a local rearrangement in the Pro48 loop and in the β‐sheet region including residues Tyr47, Ala82, Thr85, and Val50.
Dynamic Power Management in Wireless Sensor Networks

We propose an OS-directed power management technique to improve the energy efficiency of sensor nodes. Dynamic power management (DPM) is an effective tool in reducing system power consumption without significantly degrading performance. The basic idea is to shut down devices when not needed and wake them up when necessary. DPM, in general, is not a trivial problem. If the energy and performance overheads in sleep-state transition were negligible, then a simple greedy algorithm that makes the system enter the deepest sleep state when idling would be perfect. However, in reality, sleep-state transitioning has the overhead of storing processor state and turning off power. Waking up also takes a finite amount of time. Therefore, implementing the correct policy for sleep-state transitioning is critical for DPM success. It is argued that power-aware methodology uses an embedded microoperating system to reduce node energy consumption by exploiting both sleep state and active power management.
Use of Structure-Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection

An evaluation of a variety of structure-based clustering methods for use in compound selection is presented. The use of MACCS, Unity and Daylight 2D descriptors; Unity 3D rigid and flexible descriptors and two in-house 3D descriptors based on potential pharmacophore points, are considered. The use of Ward's and group-average hierarchical agglomerative, Guenoche hierarchical divisive, and Jarvis−Patrick nonhierarchical clustering methods are compared. The results suggest that 2D descriptors and hierarchical clustering methods are best at separating biologically active molecules from inactives, a prerequisite for a good compound selection method. In particular, the combination of MACCS descriptors and Ward's clustering was optimal.
Dominant negative mutant of Plasmodium Rad51 causes reduced parasite burden in host by abrogating DNA double‐strand break repair

Malaria parasites survive through repairing a plethora of DNA double‐stranded breaks (DSBs) experienced during their asexual growth. In Plasmodium Rad51 mediated homologous recombination (HR) mechanism and homology‐independent alternative end‐joining mechanism have been identified. Here we address whether loss of HR activity can be compensated by other DSB repair mechanisms. Creating a transgenic Plasmodium line defective in HR function, we demonstrate that HR is the most important DSB repair pathway in malarial parasite. Using mouse malaria model we have characterized the dominant negative effect of PfRad51K143R mutant on Plasmodium DSB repair and host–parasite interaction. Our work illustrates that Plasmodium berghei harbouring the mutant protein (PfRad51K143R) failed to repair DSBs as evidenced by hypersensitivity to DNA‐damaging agent. Mice infected with mutant parasites lived significantly longer with markedly reduced parasite burden. To better understand the effect of mutant PfRad51K143R on HR, we used yeast as a surrogate model and established that the presence of PfRad51K143R completely inhibited DNA repair, gene conversion and gene targeting. Biochemical experiment confirmed that very low level of mutant protein was sufficient for complete disruption of wild‐type PfRad51 activity. Hence our work provides evidence that HR pathway of Plasmodium could be efficiently targeted to curb malaria.
When is the Right Time to Start the Fault Tolerance Protection?

In High Performance Computing, Fault Tolerance (FT) becomes a primary concern due to the constant growing and continuous aging of hardware components, which rise failures probability. Failures produce performance degradation to the environment and affect significantly users expected execution time. Rollback-Recovery protocols represent a fundamental component to protect and restore users parallel application execution, although this protection comes with an overhead. This paper proposes a First Protection Point model, which determines the starting point to introduce FT protection gaining benefits in terms of total execution time including failures. A characterization of Rollback-Recovery protocols applied on parallel applications is performed, to obtain key factors for the model design. This model can help users determine which checkpoints can be removed from the application execution when they are used for FT protection purposes, reducing the overhead and at the same time keeping high availability. An analytic model evaluation is developed to show the inflexion point where FT protection starts to provide benefits for users. Finally, three experimental environments are setup, using two private clusters and a public cluster configured in a well-known cloud Amazon EC2. A coordinated checkpoint facility is applied on NAS benchmark applications such as: CG, BT and LU to evaluate the proposed model, obtaining overhead impact reduction for provided Fault Tolerance.
Robot-Assisted Hybrid Esophagectomy Is Associated with a Shorter Length of Stay Compared to Conventional Transthoracic Esophagectomy: A Retrospective Study

Aim To compare the peri- and postoperative data between a hybrid minimally invasive esophagectomy (HMIE) and the conventional Ivor Lewis esophagectomy. Methods Retrospective comparison of perioperative characteristics, postoperative complications, and survival between HMIE and Ivor Lewis esophagectomy. Results 216 patients were included, with 160 procedures performed with the conventional and 56 with the HMIE approach. Lower perioperative blood loss was found in the HMIE group (600 ml versus 200 ml, p < 0.001). Also, a higher median number of lymph nodes were harvested in the HMIE group (median 28) than in the conventional group (median 23) (p = 0.002). The median length of stay was longer in the conventional group compared to the HMIE group (11.5 days versus 10.0 days, p = 0.03). Patients in the HMIE group experienced fewer grade 2 or higher complications than the conventional group (39% versus 57%, p = 0.03). The rate of all pulmonary (51% versus 43%, p = 0.32) and severe pulmonary complications (38% versus 18%, p = 0.23) was not statistically different between the groups. Conclusions The HMIE was associated with lower intraoperative blood loss, a higher lymph node harvest, and a shorter hospital stay. However, the inborn limitations with the retrospective design stress a need for prospective randomized studies. Registration number is DRKS00013023.
Gastrointestinal Parasites and the Neural Control of Gut Functions

Gastrointestinal motility and transport of water and electrolytes play key roles in the pathophysiology of diarrhea upon exposure to enteric parasites. These processes are actively modulated by the enteric nervous system (ENS), which includes efferent, and afferent neurons, as well as interneurons. ENS integrity is essential to the maintenance of homeostatic gut responses. A number of gastrointestinal parasites are known to cause disease by altering the ENS. The mechanisms remain incompletely understood. Cryptosporidium parvum, Giardia duodenalis (syn. Giardia intestinalis, Giardia lamblia), Trypanosoma cruzi, Schistosoma species and others alter gastrointestinal motility, absorption, or secretion at least in part via effects on the ENS. Recent findings also implicate enteric parasites such as C. parvum and G. duodenalis in the development of post-infectious complications such as irritable bowel syndrome, which further underscores their effects on the gut-brain axis. This article critically reviews recent advances and the current state of knowledge on the impact of enteric parasitism on the neural control of gut functions, and provides insights into mechanisms underlying these abnormalities.
Automatic Tagging of Art Images with Color Harmonies and Contrasts Characteristics in Art Image Collections

– In this paper we present a classification of color harmonies and contrasts, which is consistent with human perceiving of visual expression. It is conformed to the possibilities of automatic extraction of visual information from digitalized copies of art images. The classification is done on the base of the three main characteristics of the color most closed to the human perception – hue, saturation and lightness. Functions for automatic features extraction from digital images are defined. These functions are realized as part of a virtual laboratory "Art Painting Image Color Aesthetic and Semantic" (APICAS). The system can be used by designers and art students for searching images, having certain harmonies or contrasts in image collections as well as a for examining specifics of artists or movements. In future we will use the system as a Web 2.0 service, which could be included in a virtual learning environment.
Symmetric Linear Model Predictive Control

This paper studies symmetry in linear model predictive control (MPC). We define symmetry for model predictive control laws and for model predictive control problems. Properties of both MPC symmetries are studied by using a group theory formalism. We show how to efficiently compute MPC symmetries by transforming the search of MPC symmetry generators into a graph automorphism problem. MPC symmetries are then used to design model predictive control algorithms with reduced complexity. The effectiveness of the proposed approach is shown through a simple large-scale MPC problem whose explicit solution can only be found with the method presented in this paper.
Determining 3-D object pose using the complex extended Gaussian image

A method based on the extended Gaussian image (EGI) which can be used to determine the pose of a 3-D object is presented. In this scheme, the weight associated with each outward surface normal is a complex weight. The normal distance of the surface from the predefined origin is encoded as the phase of the weight, while the magnitude of the weight is the visible area of the surface. This approach decouples the orientation and translation determination into two distinct least-squares problems. Experiments involving synthetic data of two polyhedral and two smooth objects as well as real range data of the same smooth objects indicate the feasibility of this method. <<ETX>>
Large-scale detection of in vivo transcription errors

Significance Gene expression requires accurate copying of the DNA template into messenger RNA by RNA polymerases. Errors occurring during this transcription process can lead to the production of nonfunctional proteins, which is likely to be deleterious. Therefore, natural selection is expected to enhance the fidelity of transcription. However, very little is known about the transcription error rates of different organisms. Here we present a unique method for the detection of transcription errors by replicated high-throughput sequencing of cDNA libraries. Applying this method to the model organism Caenorhabditis elegans, we report a large-scale analysis of transcription errors. Future applications of this method should allow a rapid increase in our knowledge of evolutionary forces acting on transcription fidelity. Accurate transmission and expression of genetic information are crucial for the survival of all living organisms. Recently, the coupling of mutation accumulation experiments and next-generation sequencing has greatly expanded our knowledge of the genomic mutation rate in both prokaryotes and eukaryotes. However, because of their transient nature, transcription errors have proven extremely difficult to quantify, and current estimates of transcription fidelity are derived from artificial constructs applied to just a few organisms. Here we report a unique cDNA library preparation technique that allows error detection in natural transcripts at the transcriptome-wide level. Application of this method to the model organism Caenorhabditis elegans revealed a base misincorporation rate in mRNAs of ∼4 × 10−6 per site, with a very biased molecular spectrum. Because the proposed method is readily applicable to other organisms, this innovation provides unique opportunities for studying the incidence of transcription errors across the tree of life.
Learning rule ranking by dynamic construction of context-free grammars using AND/OR graphs

This paper 1 discusses a novel approach for the construction of a context-free grammar based on a sequential processing of sentences. The construction of the grammar is based on a search algorithm for the minimum weight subgraph in an AND/OR graph. Aspects of optimality and robustness are discussed. The algorithm plays an essential role in a model for adaptive learning of probabilistic ordering. The novelty in the proposed model is the combination of well-established methods from two different disciplines: graph theory and statistics. The set-up of this paper is mainly theoretical, and we follow a quite formal approach. There is a close link with Optimality Theory, one of the mainstream approaches in phonology, and with graph theory. The resulting techniques, however, can be applied in a more general domain.
Inorganic fullerene-like tungsten disulfide nanocoating for friction reduction of nickel-titanium alloys.

AIMS To fabricate a friction-reducing coating onto different nickel-titanium (NiTi) substrates using inorganic fullerene-like tungsten disulfide (IF-WS(2)) nanoparticles and to estimate in vitro friction reducing extent of the coating. MATERIALS & METHODS Different NiTi substrates were coated with cobalt and IF-WS(2) nanoparticles film by the electrodeposition procedure. Coating composition analyses was made by scanning-electron microscopy, energy dispersive x-ray spectroscopy, x-ray powder diffractometry and x-ray photoelectron spectroscopy. Friction evaluation was carried out using standard tribological tests and an Instron system. RESULTS Stable and well-adhered cobalt + IF-WS(2) coating of the NiTi substrates was obtained. Friction tests presented up to 66% reduction of the friction coefficient. CONCLUSION NiTi alloy is widely used for many medical appliances; hence, this unique friction-reducing coating could be implemented to provide better manipulation and lower piercing rates.
Coaching for performance : growing people, performance and purpose

This edition includes additional chapters on incorporating meaning and purpose into work, into goal-setting, and a spiritual approach to coaching, together with a final section on "Coaching the Organizations' Culture". Adopted by many of the world's major corporations, this work also argues for using questions, rather than instructions and commands, and following the GROW sequence - Goals, Reality, Options, Will - to generate prompt action and peak performance. It explores the dynamics of team development and it positions coaching as the essential team leadership skill.
Improving server applications with system transactions

Server applications must process requests as quickly as possible. Because some requests depend on earlier requests, there is often a tension between increasing throughput and maintaining the proper semantics for dependent requests. Operating system transactions make it easier to write reliable, high-throughput server applications because they allow the application to execute non-interfering requests in parallel, even if the requests operate on OS state, such as file data. By changing less than 200 lines of application code, we improve performance of a replicated Byzantine Fault Tolerant (BFT) system by up to 88% using server-side speculation, and we improve concurrent performance up to 80% for an IMAP email server by changing only 40 lines. Achieving these results requires substantial enhancements to system transactions, including the ability to pause and resume transactions, and an API to commit transactions in a pre-defined order.
A closer look at visually guided saccades in autism and Asperger’s disorder

Motor impairments have been found to be a significant clinical feature associated with autism and Asperger’s disorder (AD) in addition to core symptoms of communication and social cognition deficits. Motor deficits in high-functioning autism (HFA) and AD may differentiate these disorders, particularly with respect to the role of the cerebellum in motor functioning. Current neuroimaging and behavioral evidence suggests greater disruption of the cerebellum in HFA than AD. Investigations of ocular motor functioning have previously been used in clinical populations to assess the integrity of the cerebellar networks, through examination of saccade accuracy and the integrity of saccade dynamics. Previous investigations of visually guided saccades in HFA and AD have only assessed basic saccade metrics, such as latency, amplitude, and gain, as well as peak velocity. We used a simple visually guided saccade paradigm to further characterize the profile of visually guided saccade metrics and dynamics in HFA and AD. It was found that children with HFA, but not AD, were more inaccurate across both small (5°) and large (10°) target amplitudes, and final eye position was hypometric at 10°. These findings suggest greater functional disturbance of the cerebellum in HFA than AD, and suggest fundamental difficulties with visual error monitoring in HFA.