Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of antifeeding prophage (Afp) protein Afp16 in terminating the length of the Afp tailocin and stabilizing its sheath

The Serratia entomophila antifeeding prophage Afp, forms a phage‐tail‐like particle that acts on the New Zealand grass grub, Costelytra zealandica with a 3‐day LD50 of approximately 500 Afp particles per larva. Genes (afp1–18) encoding components of Afp were expressed and their products purified allowing morphological assessment of the products by transmission electron microscopy (TEM). Expression of afp1–15 resulted in the formation of a non‐sheathed structure termed the tube‐baseplate complex or TBC, composed of an irregular‐length tube attached to a baseplate with associated tail fibres. Expression of afp1–16 produced mature, normal‐length Afp particles, whereas coexpression of afp16 with afp1–15 in trans resulted in the formation of aberrant Afp particles of variable lengths. A C‐terminally truncated Afp16 mutant resulted in a phenotype intermediate between mature Afp and TBC. The addition of purified Afp16 to Afp unravelled by acidic treatment resulted in the formation of shorter tubes when specimen pH was adjusted to 7 than those formed in the absence of Afp16. Analysis of TEM images of purified Afp16 revealed a hexameric ring‐like structure similar to that formed by gp3 of phage T4 and gpU of phage λ. Our results suggest that Afp16 terminates tube elongation and is involved in sheath formation.
RGB-D sensor data correction and enhancement by introduction of an additional RGB view

RGB-D sensors are becoming more and more vital to robotics. Sensors such as the Microsoft Kinect and time of flight cameras provide 3D colored point-clouds in real time can play a crucial role in Robot Vision. However these sensors suffer from precision deficiencies, and often the density of the point-clouds they provide is insufficient. In this paper, we present a multi-camera system for correction and enhancement of the data acquired from an RGB-D sensor. Our system consists of two sensors, the RGB-D sensor (main sensor) and a regular RGB camera (auxiliary sensor). We perform the correction and the enhancement of the data acquired from the RGB-D sensor by placing the auxiliary sensor in a close proximity to the target object and taking advantage of the established epipolar geometry. We have managed to reduce the relative error of the raw point-cloud from a Microsoft Kinect RGB-D sensor by 74.5 % and increase its density up to 2.5 times.
Evaluation of the genetic parameters for 10 common and five new ESS core autosomal STR loci in seven major geographic regions and the largest metropolitan province of Turkey

Abstract Background: Situated at the crossroads of Asia, Middle East and Europe, Turkey has an ethnically diverse population of over 78 milllion people. Aim: To investigate the population genetics and potential differences in the autosomal short tandem repeat (STR) polymorphisms across all the major geographic regions and largest metropolitan province of Turkey within the context of the Near Eastern/European genetic landscape. Subjects and methods: Samples from a total of 5299 unrelated individuals were analysed at 10 common [D2S1338, D3S1358, D8S1179, D16S539, D18S51, D19S433, D21S11, FGA, TH01, vWA] and five new European Standard Set (ESS) core autosomal STR loci [D1S1656, D2S441, D10S1248, D12S391, D22S1045]. Results: Allele frequencies, statistical parameters of forensic interest and population differentiation tests were calculated for nine population datasets corresponding to the seven major geographic regions, the largest metropolitan province, and a combined dataset for the entire country. Cumulative results confirmed the presence of significant differences among these nine autosomal datasets themselves and with those from the nearby populations, therefore justifying the differential use of these separate datasets on a case-by-case basis in forensic investigations. Conclusion: This collection of autosomal STR population datasets comprises the largest and most comprehensive of its kind from Turkey so far.
An Efficient Broadcast Encryption Scheme for Wireless Sensor Network

It is a significant challenge to find out suitable cryptography for wireless sensor networks owing to limitations of power, computation capability and storage resources. Many schemes based on public or symmetric key cryptography are investigated. This paper proposes a new broadcast encryption scheme, which can be used for key distribution or directly broadcasting message. The scheme is suitable for typical type of networks. We review identity-based encryption and attribute-based encryption first. Then we describe a key agreement and encryption scheme based on them. We discuss the efficiency and security of our scheme by comparing with traditional public key technique and symmetric key technique.
Selenium and Its Species Distribution in Above-ground Plant Parts of Selenium Enriched Buckwheat (Fagopyrum esculentum Moench)

Common buckwheat ( Fagopyrum esculentum Moench) was foliarly sprayed with a water solution containing 10 mg Se(VI) L^–1 at the beginning of flowering. The total Se content in plant parts in the untreated group was low, whereas in the Se-sprayed group it was approximately 50- to 500-fold higher, depending on the plant part (708 – 4231 ng Se g^–1 DM^–1 (DM: dry matter)). We observed a similar distribution of Se in plant parts in both control and treated groups, with the highest difference in Se content being in ripe seeds. Water-soluble Se compounds were extracted by enzymatic hydrolysis with protease XIV, resulting in above 63% of soluble Se from seeds, ~14% from stems, leaves and inflorescences and less than 1% from husks. Se-species were determined in enzymatic extracts using HPLC-UV-HG-AFS (HPLC–hydride generation–atomic fluorescence spectrometry with UV treatment). The main Se species found in seeds was SeMet (~60% according to total Se content), while in stems, leaves and inflorescences the only form of soluble Se present was Se(VI) (up to 10% of total Se). In husks no Se-species were detected. We observed an instability of Se(IV) in seed extracts as a possible consequence of binding to the matrix components. Therefore, special care concerning sample extraction and the storage time of the extracts should be taken.
Topology and patch‐clamp analysis of the sodium channel in relationship to the anti‐lipid a antibody in campylobacteriosis

An infecting strain VLA2/18 of Campylobacter jejuni was obtained from an individual with campylobacteriosis and used to prepare chicken sera by experimental infection to investigate the role of serum anti‐ganglioside antibodies in Guillain‐Barré syndrome. Both sera of the patient and chicken contained anti‐ganglioside antibodies and anti‐Lipid A (anti‐Kdo2‐Lipid A) antibodies directed against the lipid A portion of the bacterial lipooligosaccharide. The anti‐Kdo2‐Lipid A activities inhibited voltage‐gated Na (Nav) channel of NSC‐34 cells in culture. We hypothesized that anti‐Kdo2‐Lipid A antibody acts on the functional inhibition of Nav1.4. To test this possibility, a rabbit peptide antibody (anti‐Nav1.4 pAb) against a 19‐mer peptide (KELKDNHILNHVGLTDGPR) on the α subunit of Nav1.4 was produced. Anti‐Nav1.4 pAb was cross‐reactive to Kdo2‐Lipid A. Anti‐Kdo2‐lipid A antibody activity in the chicken serum was tested for the Na+ current inhibition in NSC‐34 cells in combination with μ‐Conotoxin and tetrodotoxin. Contrary to our expectations, the anti‐Kdo2‐Lipid A antibody activity was extended to Nav channels other than Nav1.4. By overlapping structural analysis, it was found that there might be multiple peptide epitopes containing certain dipeptides showing a structural similarity with v‐Lipid A. Thus, our study suggests the possibility that there are multiple epitopic peptides on the extracellular domains of Nav1.1 to 1.9, and some of them may represent target sites for anti‐Kdo2‐Lipid A antibody, to induce neurophysiological changes in GBS by disrupting the normal function of the Nav channels. © 2008 Wiley‐Liss, Inc.
Algebraic Dynamic Multilevel Simulation of Coupled Flow and Heat Transfer in Heterogeneous Geothermal Reservoirs with Fluid-Rock Non-Thermal Equilibrium Effects

Accurate simulation of fluid flow and heat transfer in geothermal reservoirs is a crucial necessity for optimising energy extraction strategies. However, natural formations (including geothermal ones) extend large length scales (in the order of km), while their properties (e.g., heat and flow conductivity) can change in small (fine) scales (e.g., cm or even below). As such, accurate simulations of filed-scale models are too expensive to be handled by the state-of-the-art commercial simulators. As a matter of fact, these geological models are upscaled excessively in order to reduce the computational costs. Excessive upscaling leads to loss of accuracy and details of the heterogeneous properties, which can result in non-optimum production estimation and operation strategies. As a remedy, in this work, we propose a dynamic multilevel method (ADM) which captures small-scale heterogeneity (i.e., accurate) while preserving the computational efficiency (thus applicable to field-scale models). This development is achieved by combining two major concepts: (1) multiscale basis functions for accurate coarse-scale treatment of heat and flow conductive properties at their original fine-scale, and (2) adaptive mesh refinement strategy to minimise the requirement for employing the fine-scale grid, i.e., when and where needed. These two developments combined in one framework allows for both accurate and efficient simulation of coupled flow-heat equations in subsurface geothermal reservoirs. The fine-scale grid is employed only at the cold water front, where most of the nonlinear (and grid resolution sensitive) interaction is taking place. The rest of the domain is solved at the coarser scales, depending on the gradients (slope of change) of the unknowns. Note that no upscaling is needed due to the employment of multiscale basis functions. Moreover, these basis functions are calculated only once at the beginning and reused for the rest of the time-dependent simulations. Our method allows for non-thermal equilibrium between rock and injected fluid, so to allow for full flexibility and possible added accuracy. Through several test cases, the accuracy of the proposed ADM is investigated by measuring its error compared with the fine-scale fully resolved simulation. Its accuracy, on the other hand, is measured through calculating the average number of active grid cells. Our results, for both homogeneous and heterogeneous models, show that the proposed method employs a fraction of the fine-scale grids to deliver accurate solutions. Therefore, it provides a promising framework for field-scale simulation of geothermal reservoirs.
Robot Arm Path Planning Using Modified Particle Swarm Optimization based on D* algorithm

Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization algorithm is proposed to find an optimal path based on the local search, D* and Euclidean distances. The quintic polynomial equation is utilized to provide a smooth trajectory path. According to the observe results, the modified PSO algorithm is efficiently performs to find an optimal path even in difficult environments.
A Reliable and Energy-Efficient Opportunistic Routing Protocol for Dense Lossy Networks

Power conservation and reliable data delivery are two most critical issues in the design of routing protocols for wireless networks, especially for dense lossy networks. However, traditional routing protocols, which deliver packets along predetermined routing paths with unnecessarily high transmit power, cannot cope well with dynamic and lossy wireless mediums under excessive interference. In order to prolong the lifetime of networks and improve the reliability of networks, this letter proposes a reliable and energy-efficient opportunistic routing (REOR) protocol. REOR effectively utilizes path diversity by jointly selecting optimal transmit power and optimal forwarder set, which significantly postpones the death of nodes and ensures persistent network connectivity with dynamic workload sharing approach. Extensive simulation results demonstrate that REOR achieves up to 50% reliability improvement and 30% energy conservation compared to the benchmark, i.e., the IPv6 routing protocol for low-power and lossy networks.
Synapsins Differentially Control Dopamine and Serotonin Release

Synapsins are a family of synaptic vesicle proteins that are important for neurotransmitter release. Here we have used triple knock-out (TKO) mice lacking all three synapsin genes to determine the roles of synapsins in the release of two monoamine neurotransmitters, dopamine and serotonin. Serotonin release evoked by electrical stimulation was identical in substantia nigra pars reticulata slices prepared from TKO and wild-type mice. In contrast, release of dopamine in response to electrical stimulation was approximately doubled in striatum of TKO mice, both in vivo and in striatal slices, in comparison to wild-type controls. This was due to loss of synapsin III, because deletion of synapsin III alone was sufficient to increase dopamine release. Deletion of synapsins also increased the sensitivity of dopamine release to extracellular calcium ions. Although cocaine did not affect the release of serotonin from nigral tissue, this drug did enhance dopamine release. Cocaine-induced facilitation of dopamine release was a function of external calcium, an effect that was reduced in TKO mice. We conclude that synapsins play different roles in the control of release of dopamine and serotonin, with release of dopamine being negatively regulated by synapsins, specifically synapsin III, while serotonin release appears to be relatively independent of synapsins. These results provide further support for the concept that synapsin function in presynaptic terminals varies according to the neurotransmitter being released.
A Trust-Enabling Support for Goal-Based Services

Service-oriented computing allows new applications to be developed by using and/or combining services offered by different providers. In several cases a service needs sensitive information from the clients in order to execute. The existence of a trust relationship between the client and the provider determines which restrictions the service has concerning the use of this information by the service. In this paper we present a metamodel for services computing that incorporates the support for trust relationships. The metamodel provides the means for specifying services and service requests including trust requirements and constraints. The proposed metamodel is encompassed in a framework for goal-based service discovery and composition.
Segmentation and Characterization of Breast Tumor in Mammograms

The objective of this paper is to present a novel approach for the segmentation and characterization of breast tumor. The authors have developed an efficient tumor segmentation technique using conventional Ostu thresholding method aided by morphological reconstruction filtering technique. The parameters extracted are area, major and minor axis length, eccentricity, solidity, average gray level, standard deviation, and entropy. This method is simple, fast and versatile. This can be applied for the segmentation of all types of breast tumor irrespective of their size. The proposed technique has been implemented on MATLAB 7.3 and results are compared with the existing techniques such as standard Ostu thresholding method and region growing method proposed by Zucker. The simulated result shows that the performance of the proposed technique is better than that of existing techniques.
Social adversity contributes to high morbidity in psychoses in immigrants – a national cohort study in two generations of Swedish residents

Background. Recent reports have indicated that immigrants have an elevated risk of schizophrenia as well as an increasing tendency for social exclusion. The aim of this study was to compare rates of schizophrenia and other psychoses in immigrants and their children of different ethnic groups with the majority population in Sweden in relation to social adversity. Method. The study population consists of a national cohort of 1·47 million adults (born 1929–1965) and 1·16 million children and youth (born 1968–1979) in family households from the national census of 1985. Multivariate Cox regression analyses was used to study hospital discharge data during 1991–2000 in relation to socio-economic household indicators from 1985 and 1990 (single adult household, adults having received social welfare, parental unemployment, urban residency, housing and socio-economic status). Results. First as well as second generation immigrants had higher age and sex adjusted risk ratios for schizophrenia as well as for other psychoses (RRs 1·4–3·1 and 1·0–2·0 respectively) compared with the Swedish majority population. These risk ratios decreased considerably after adjusting for socio-economic indicators, for all groups, but particularly for the non-European immigrants. However, an elevated risk still remained in the Finnish and Eastern and Southern European study groups. Conclusions. A higher risk of schizophrenia and psychoses was found in two generations of immigrants of diverse ethnicity. The results indicate that social adversity contributes to the higher risk.
Instant Selection of High Contrast Projections in Multi-Dimensional Data Streams

In many of today’s applications we have to cope with multidimensional data streams containing dimensions which are not relevant to a particular stream mining task. These irrelevant dimensions hinder knowledge discovery as they lead to noisy distributions in the full dimensional space, while knowledge is hidden in some sets of dependent dimensions. This dependence of dimensions may change over time and poses a major open challenge to stream mining. In this work, we focus on dependent dimensions having a high contrast, i.e. they show a clear separation between outliers and clustered objects. We present HCP-StreamMiner, a method for selecting high-contrast projections in multi-dimensional streams. Our quality measure (the contrast) of each projection is statistically determined by comparing the data distribution in a set of dimensions to their marginal distributions. We propose a technique for computing the score out of stream data summaries and a procedure for progressively tracking interesting subspaces. Our method was tested on both synthetic and real world data, and proved to be effective in detecting and tracking high contrast subspaces.
The PADS project: an overview

The goal of the PADS project, which started in 2001, is to make it easier for data analysts to extract useful information from ad hoc data files. This paper does not report new results, but rather gives an overview of the project and how it helps bridge the gap between the unmanaged world of ad hoc data and the managed world of typed programming languages and databases. In particular, the paper reviews the design of PADS data description languages, describes the generated parsing tools and discusses the importance of meta-data. It also sketches the formal semantics, discusses useful tools and how can they can be generated automatically from PADS descriptions, and describes an inferencing system that can learn useful PADS descriptions from positive examples of the data format.
Diode-Pumped High Energy and High Average Power All-Solid-State Picosecond Amplifier Systems

We present our research on the high energy picosecond laser operating at a repetition rate of 1 kHz and the high average power picosecond laser running at 100 kHz based on bulk Nd-doped crystals. With diode-pumped solid state (DPSS) hybrid amplifiers consisting of a picosecond oscillator, a regenerative amplifier, end-pumped single-pass amplifiers, and a side-pumped amplifier, an output energy of 64.8 mJ at a repetition rate of 1 kHz was achieved. An average power of 37.5 W at a repetition rate of 100 kHz pumped by continuous wave laser diodes was obtained. Compact, stable and high power DPSS laser amplifier systems with good beam qualities are excellent picosecond sources for high power optical parametric chirped pulse amplification (OPCPA) and high-efficiency laser processing.
Saccharomyces cerevisiae Ccr4–Not complex contributes to the control of Msn2p‐dependent transcription by the Ras/cAMP pathway

The Ccr4–Not complex is a global regulator of transcription that affects genes positively and negatively and is thought to modulate the activity of TFIID. In the present work, we provide evidence that the Ccr4–Not complex may contribute to transcriptional regulation by the Ras/cAMP pathway. Several observations support this model. First, Msn2/4p‐dependent transcription, which is known to be under negative control of cAMP‐dependent protein kinase (PKA), is derepressed in all ccr4–not mutants. This phenotype is paralleled by specific post‐translational modification defects of Msn2p in ccr4–not mutants relative to wild‐type cells. Secondly, mutations in various NOT genes result in a synthetic temperature‐sensitive growth defect when combined with mutations that compromise cells for PKA activity and at least partially suppress the effects of both a dominant‐active RAS2Val‐19 allele and loss of Rim15p. Thirdly, Not3p and Not5p, which are modified and subsequently degraded by stress signals that also lead to increased Msn2/4p‐dependent activity, show a specific two‐hybrid interaction with Tpk2p. Together, our results suggest that the Ccr4–Not complex may function as an effector of the Ras/cAMP pathway that contributes to repress basal, stress‐ and starvation‐induced transcription by Msn2/4p.
A theorem on probabilistic constant depth Computations

1. In t roduc t ion I{t~txml, ly there has been much interest ill tht, comput:Ltional power of circuits o1' bounded dt;pth. In particular Furst, Saxe and Sipser [FSS], and indcpentlently Ajtai [Aj] in a different form, have shown that no polynomial size circuits of bounded depth can compute the parity function of n boolean variables (and other related functions such as the majority function, the exact number of ones in the input, etc.). On the other hand, Stockmeyer [St] showed that probabilistic bounded depth circuits can approximate the exact number of ones in the input with very low probability of error. Tlmse results lead to the following interesting question: (*) Are probabilistic constant depth circuits more powerful than deterministic ones? While it is well known [BG] that (non uniform) deterministic polynomial size circuits are as powerful as probabilistic ones, the question is still open for bounded depth circuits. This is so because the reduction given by Bennet and Gill [BG]