Miracle-dz/UniFAR-FTUs huggingface dataset:
RNA PROCESSING FACTOR 3 Is Crucial for the Accumulation of Mature ccmC Transcripts in Mitochondria of Arabidopsis Accession Columbia 1 [ W ] [ OA ]

RNA PROCESSING FACTOR1 (RPF1) and RPF2 are pentatricopeptide repeat (PPR) proteins involved in 5# processing of different mitochondrial mRNAs in Arabidopsis (Arabidopsis thaliana). Both factors are highly similar to RESTORERS OF FERTILITY (RF), which are part of cytoplasmic male sterility/restoration systems in various plant species. These findings suggest a predominant role of RF-like PPR proteins in posttranscriptional 5# processing. To further explore the functions of this group of proteins, we examined a number of T-DNA lines carrying insertions in the corresponding PPR genes. This screening identified a nearly complete absence of mature ccmC transcripts in an At1g62930 T-DNA insertion line, a phenotype that could be restored by the introduction of the intact At1g62930 gene into the mutant. The insertion in this nuclear gene, which we now call RPF3, also leads to a severe reduction of the CcmC protein in mitochondria. The analysis of C24/rpf3-1 F2 hybrids lacking functional RPF3 genes revealed that this gene has less influence on the generation of the mature ccmC 5# transcript end derived from a distinct ccmC 5# upstream configuration found in mitochondrial DNAs from C24 and other accessions. These data show that a particular function of an RF-like protein is required only in connection with a distinct mtDNA configuration. Our new results further substantiate the fundamental role of RF-like PPR proteins in the posttranscriptional generation of plant mitochondrial 5# transcript termini.
Pre-processing flow for enhancing learning from medical data

Data enhancement is an essential operation when dealing with incomplete and imbalanced data sets. Further classification on such data might prove to be a difficult task. This paper tackles such issues in a specific learning context - medical treatment prediction for breast cancer. We process the problem specific medical data starting from the preparation phase. We apply several data cleaning and selection steps. The resulting data proved to possess an insufficient quality for the learning process. Therefore, we propose and apply several data enhancement steps, such as imputation for handling missing values, feature selection for reducing the dimensionality of the attribute space and a modified version of the SMOTE oversampling algorithm to tackle data imbalance in conjunction with incompleteness. Evaluations of the entire pre-processing flow, performed on the available medical data, have indicated significant improvements in classification performance.
Supporting Incremental Join Queries on Ranked Inputs

This paper investigates the problem of incremental joins of multiple ranked data sets when the join condition is a list of arbitrary user-defined predicates on the input tuples. This problem arises in many important applications dealing with ordered inputs and multiple ranked data sets, and requiring the top solutions. We use multimedia applications as the motivating examples but the problem is equally applicable to traditional database applications involving optimal resource allocation, scheduling, decision making, ranking, etc. We propose an algorithm that enables querying of ordered data sets by imposing arbitrary userdefined join predicates. The basic version of the algorithm does not use any random access but a variation can exploit available indexes for efficient random access based on the join predicates. A special case includes the join scenario considered by Fagin [1] for joins based on identical keys, and in that case, our algorithms perform as efficiently as Fagin’s. Our main contribution, however, is the generalization to join scenarios that were previously unsupported, including cases where random access in the algorithm is not possible due to lack of unique keys. In addition, can support multiple join levels, or nested join hierarchies, which are the norm for modeling multimedia data. We also give -approximation versions of both of the above algorithms. Finally, we give strong optimality results for some of the proposed algorithms, and we study their performance empirically.
The Hippocampal Neuroproteome with Aging and Cognitive Decline: Past Progress and Future Directions

Although steady progress on understanding brain aging has been made over recent decades through standard anatomical, immunohistochemical, and biochemical techniques, the biological basis of non-neurodegenerative cognitive decline with aging remains to be determined. This is due in part to technical limitations of traditional approaches, in which only a small fraction of neurobiologically relevant proteins, mRNAs or metabolites can be assessed at a time. With the development and refinement of proteomic technologies that enable simultaneous quantitative assessment of hundreds to thousands of proteins, neuroproteomic studies of brain aging and cognitive decline are becoming more widespread. This review focuses on the contributions of neuroproteomic investigations to advances in our understanding of age-related deficits of hippocampus-dependent spatial learning and memory. Accumulating neuroproteomic data demonstrate that hippocampal aging involves common themes of dysregulated metabolism, increased oxidative stress, altered protein processing, and decreased synaptic function. Additionally, growing evidence suggests that cognitive decline does not represent a “more aged” phenotype, but rather is associated with specific neuroproteomic changes that occur in addition to age-related alterations. Understanding if and how age-related changes in the hippocampal neuroproteome contribute to cognitive decline and elucidating the pathways and processes that lead to cognitive decline are critical objectives that remain to be achieved. Progress in the field and challenges that remain to be addressed with regard to animal models, behavioral testing, and proteomic reporting are also discussed.
Rhinoplasty and its effects on the perception of beauty

Summary Introduction: Experts on nasal cosmetics and nasal surgery agree that aesthetic rhinoplasty leads to overall facial beautification and the perception of youth in patients. This “assumed truth” has never been proven in the international literature. Aim: To examine increases in facial attractiveness ratings after rhinoplasty surgery. Methods: We conducted a study series by choosing 30 female patients on whom we had operated and 25 evaluators in a single blind trial. The evaluators graded the patients' attractiveness before and after surgery. Results: Beauty indices were significantly improved after the operation. Conclusion: According to the third-party evaluation, the patients appeared prettier after undergoing aesthetic rhinoplasty.
Automatic detection of manner events based on temporal parameters

In this study, we investigated how well acoustic events extracted from a cross-spectral temporal measure could be used to classify the manner and voicing of consonants. In particular, we developed seven measures that look at the strength and time difference between various onsets and offsets of acoustic energy. Consistent with findings by Shannon et al. (1995), our classification results show that manner and voicing information can be determined from dynamic temporal cues.
Systematic Evaluation of Software Product Line Architectures

The architecture of a software product line is one of its most important artifacts as it represents an abstraction of the products that can be generated. It is cru- cial to evaluate the quality attributes of a product line architecture in order to: increase the productivity of the product line process and the quality of the products; provide a means to understand the potential behavior of the products and, consequently, decrease their time to market; and, improve the handling of the product line variability. The evaluation of product line architecture can serve as a basis to analyze the managerial and economical values of a product line for software managers and architects. Most of the current research on the evaluation of product line architecture does not take into account metrics directly obtained from UML models and their variabilities; the met- rics used instead are dif fi cult to be applied in general and to be used for quantitative analysis. This paper presents a Systematic Evaluation Method for UML-based Soft- ware Product Line Architecture, the SystEM-PLA. SystEM-PLA differs from current research as it provides stakeholders with a means to: (i) estimate and analyze potential products; (ii) use predefined basic UML-based metrics to compose quality attribute metrics; (iii) perform feasibility and trade-off analysis of a product line architecture with respect to its quality attributes; and, (iv) make the evaluation of product line architecture more flexible. An example using the SEI's Arcade Game Maker (AGM) product line is presented as a proof of concept, illustrating SystEM-PLA activities. Metrics for complexity and extensibility quality attributes are defined and used to perform a trade-off analysis.
Differential Regulation of Membrane Bound and Soluble ICAM 1 in Human Endothelium and Blood Mononuclear Cells: Effects of Interferon Beta-1a

The membrane-associated Intercellular Adhesion Molecule 1 (mICAM 1) is fundamental for adhesion of leukocytes to endothelial cells. A soluble form of ICAM 1 (sICAM 1) exists in the human serum, and is seen as marker of disease activity in patients suffering from Multiple Sclerosis (MS). High levels of sICAM 1 have been detected in MS patients benefiting from interferon beta (IFN g ) treatment, but little is known on the molecular origins of sICAM 1. This study investigated the interrelationship and the mechanisms of production of sICAM 1 and mICAM 1 in human endothelium (Human Umbilical Vein Endothelial Cells, HUVECs) and mononuclear leukocytes (MNL) upon stimulation with IFN g -1a and other inducers. We found that the expression of mICAM 1 and the release of sICAM 1 are differentially regulated in both these cytotypes. HUVECs and MNL express specific mRNA for both mICAM 1 and sICAM 1, and modification of the content of each of these transcripts results in regulation of both the ICAM 1 isoforms. We show that IFN g -1a is strong regulator of the ICAM 1 RNA splicing machinery. Effect of IFN g -1a over expression of the ICAM 1 isoforms might have a relevant immunomoregulatory role in Multiple Sclerosis.
Active error detection and resolution for speech-to-speech translation

1 We describe a novel two-way speech-to-speech (S2S) translation system that actively detects a wide variety of common error types and resolves them through user-friendly dialog with the user(s). We present algorithms for detecting out-of-vocabulary (OOV) named entities and terms, sense ambiguities, homophones, idioms, ill-formed input, etc. and discuss novel, interactive strategies for recovering from such errors. We also describe our approach for prioritizing different error types and an extensible architecture for implementing these decisions. We demonstrate the efficacy of our system by presenting analysis on live interactions in the English-to-Iraqi Arabic direction that are designed to invoke different error types for spoken language translation. Our analysis shows that the system can successfully resolve 47% of the errors, resulting in a dramatic improvement in the transfer of problematic concepts.
GSK3β Inhibition Promotes Synaptogenesis in Drosophila and Mammalian Neurons

The PI3K-dependent activation of AKT results in the inhibition of GSK3β in most signaling pathways. These kinases regulate multiple neuronal processes including the control of synapse number as shown for Drosophila and rodents. Alzheimer disease’s patients exhibit high levels of circulating GSK3β and, consequently, pharmacological strategies based on GSK3β antagonists have been designed. The approach, however, has yielded inconclusive results so far. Here, we carried out a comparative study in Drosophila and rats addressing the role of GSK3β in synaptogenesis. In flies, the genetic inhibition of the shaggy-encoded GSK3β increases the number of synapses, while its upregulation leads to synapse loss. Likewise, in three weeks cultured rat hippocampal neurons, the pharmacological inhibition of GSK3β increases synapse density and Synapsin expression. However, experiments on younger cultures (12 days) yielded an opposite effect, a reduction of synapse density. This unexpected finding seems to unveil an age- and dosage-dependent differential response of mammalian neurons to the stimulation/inhibition of GSK3β, a feature that must be considered in the context of human adult neurogenesis and pharmacological treatments for Alzheimer’s disease based on GSK3β antagonists.
Use of Lexical and Syntactic Techniques in Recognizing Handwritten Text

The output of handwritten word recognizers (WR) tends to be very noisy due to various factors. In order to compensate for this behaviour, several choices of the WR must be initially considered. In the case of handwritten sentence/phrase recognition, linguistic constraints may be applied in order to improve the results of the WR. This paper discusses two statistical methods of applying linguistic constraints to the output of an WR on input consisting of sentences/phrases. The first is based on collocations and can be used to promote lower ranked word choices or to propose new words. The second is a Markov model of syntax and is based on syntactic categories (tags) associated with words. In each case, we show the improvement in the word recognition rate as a result of applying these constraints.
Malassezia pachyderznatis: properties and storage

Summary. Five strains of Malassezia pachydermatis isolated from small animals in Bratislava were subcultured, maintained under sterile paraffin oil and preserved in liquid nitrogen. Morphological and physiological characteristics as well as the analysis of long chain fatty acids of the cell mass were determined. The results showed that the maintenance in liquid nitrogen is the most satisfactory method of preservation of pure cultures of Malassezia pachydermatis.
Nonlinear analysis of heart rate dynamics in hyperthyroidism

Studies on the physiology of the cardiovascular system suggested that the generation of the heart rate signal is governed by nonlinear chaotic dynamics. No study investigated the nonlinear dynamics of heart rate in hyperthyroidism. We examined whether the heart rate dynamics of hyperthyroid patients is different from normal controls by the nonlinear analysis of heart rate variability (HRV) with correlation dimension (CD). Thirty-three hyperthyroid Graves’ disease patients (30 females and 3 males; age 31 ± 1 years, means ± SE) and 33 sex-, age-, and body mass index-matched normal controls were recruited to receive one-channel electrocardiogram recording for 30 min. The CD, an index of complexity, was computed from the sequence of normal R–R intervals by the Grassberger and Procaccia algorithm. Compared to the normal controls, the hyperthyroid patients showed significant reductions (P < 0.001) in the mean R–R interval (hyperthyroid 616 ± 15 versus control 868 ± 16 ms), the standard deviation of R–R intervals (25 ± 2 versus 54 ± 4 ms) and CD (5.02 ± 0.11 versus 6.42 ± 0.16). Our study demonstrated for the first time that hyperthyroid patients and normal controls could be distinguished by CD analysis of HRV. In addition, the decreased CD in hyperthyroid patients implies reduced complexity and impaired tolerance to cardiovascular stresses in hyperthyroidism. This finding helps to explain exercise intolerance and irritability manifested by the hyperthyroid patients.
Assessment of sexual dysfunction in patients with Parkinson’s disease: a case–control study

Background: Sexual dysfunction (SD) in patients with Parkinson’s disease (PD) has not been very well studied, as most of the research has methodological restrictions like having no control group, using invalid assessment tools, unidimensional investigation of sexual functions and inclusion of males/females only. This study aimed to examine different sexual functions in patients with PD and compare with matched non‐parkinsonian controls by using a valid instrument. Predicting factors of SD in PD were also investigated.
The G2019S LRRK2 mutation is uncommon amongst Greek patients with sporadic Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting approximately 2% of the population >60 years of age. Although, the etiology of PD is still unknown, the genetic background of the disease has been documented. Recently, a mutation in the LRRK2 gene, G2019S, was associated with 3–41% and 1–2% of familial and sporadic PD, respectively suggesting a pivotal role of LRRK2 in PD. In this report, we examine the association of the G2019S mutation with sporadic late‐onset PD, in an independent cohort of Greek patients and controls.
Estimating the Amount of Information Conveyed by a Population of Neurons

Recent technological advances have made the simultaneous recording of the activity of many neurons common. However, estimating the amount of information conveyed by the discharge of a neural population remains a significant challenge. Here we describe our recently published analysis method that assists in such estimates. We describe the key concepts and assumptions on which the method is based, illustrate its use with data from both simulated and real neurons recorded from the lateral geniculate nucleus of a monkey, and show how it can be used to calculate redundancy and synergy among neuronal groups.
A User Authentication Scheme with Privacy Protection for Wireless Sensor Networks ⋆

In wireless sensor networks, user authentication is a wireless mutual authentication process between a user and sensor nodes by which people could acquire the environmental information around them. It is really necessary because in the upcoming ubiquitous age, people will want to utilize this information for enhancing their daily activities. Since a sensor node has very limited resources, we want to provide the information only to legitimate users in order to conserve the small power consumption. For this purpose, sensor node must verify the user in an efficient and secure manner. In addition, we must protect the privacy of the user because all messages are broadcasted on the air which means that an attacker can easily infringe the privacy of the user by eavesdropping the broadcasted messages. In this paper, we propose an efficient and secure user authentication scheme which utilizes the local time of each sensor nodes and protects the privacy of user.
Optimal input design for system identification using spectral decomposition

ABSTRACT The aim of this paper is to design a band-limited optimal input with power constraints for identifying a linear multi-input multi-output system, with nominal parameter values specified. Using spectral decomposition theorem, the power spectrum is written as . The matrix is expressed in terms of a truncated basis for , where is the cut-off frequency. The elements of the Fisher Information Matrix and the power constraints become homogeneous quadratics in basis coefficients. The optimality criterion used are -optimality, -optimality, -optimality and -optimality. This optimization problem is not known to be convex. A bi-linear formulation gives a lower bound on the optimum, while an upper bound is obtained through a convex relaxation. These bounds can be computed efficiently. The lower bound is used as a suboptimal solution, its sub-optimality determined by the difference between the bounds. Simulations reveal that the bounds match in many instances, implying global optimality.
An automatic shadowdetection and compensation method for remote sensed color images

An effective and robust method for shadow detection and compensation in remote sensed color images is presented. Based on particular properties of shadows in HIS color space, thresholds are chosen automatically to detect shadows, and a homogenous operator is carried out on the intensity component to preserve shadow shape. Afterwards, the segmented shadows are compensated directly in HIS color space, and then converted back to RGB color space, avoiding the compensation results seem unnatural. Experimental results demonstrate the effectiveness and feasibility of the presented method
An Atlas for Schistosoma mansoni Organs and Life-Cycle Stages Using Cell Type-Specific Markers and Confocal Microscopy

Schistosomiasis (bilharzia) is a tropical disease caused by trematode parasites (Schistosoma) that affects hundreds of millions of people in the developing world. Currently only a single drug (praziquantel) is available to treat this disease, highlighting the importance of developing new techniques to study Schistosoma. While molecular advances, including RNA interference and the availability of complete genome sequences for two Schistosoma species, will help to revolutionize studies of these animals, an array of tools for visualizing the consequences of experimental perturbations on tissue integrity and development needs to be made widely available. To this end, we screened a battery of commercially available stains, antibodies and fluorescently labeled lectins, many of which have not been described previously for analyzing schistosomes, for their ability to label various cell and tissue types in the cercarial stage of S. mansoni. This analysis uncovered more than 20 new markers that label most cercarial tissues, including the tegument, the musculature, the protonephridia, the secretory system and the nervous system. Using these markers we present a high-resolution visual depiction of cercarial anatomy. Examining the effectiveness of a subset of these markers in S. mansoni adults and miracidia, we demonstrate the value of these tools for labeling tissues in a variety of life-cycle stages. The methodologies described here will facilitate functional analyses aimed at understanding fundamental biological processes in these parasites.
A Magnetic Measurement System and Identification Method for Buried Magnetic Materials Within Wet and Dry Soils

In this paper, a new magnetic measurement system is developed to determine upper surfaces of buried magnetic materials, particularly land mines. This measurement system uses the magnetic-anomaly-detection method. It also has intelligent identification software based on an image matching algorithm. It is aimed to determine and identify the buried ferromagnetic materials with minimum energy consumption. It is concentrated on the detection and identification of the shapes of upper surfaces of buried magnetic materials in dry and wet conditions. The effect of humidity in the detection process for detection is tested. In this paper, we used sensor images to identify various ferromagnetic materials and similar objects. Sensor images of soils at various humidities covering the objects were obtained. We used the speeded-up-feature-transform algorithm in the comparison process of the images. Dry soil sample images match with the corresponding wet soil samples with the highest matching rate. The images for different objects can easily be distinguished by the matching process.