Miracle-dz/UniFAR-FTUs huggingface dataset:
Diapause Response of the Boll Weevil (Coleoptera: Curculionidae) to Feeding Period Duration and Cotton Square Size

Abstract Distribution of the boll weevil, Anthonomus grandis grandis Boheman (Coleoptera: Curculionidae), in the United States has been greatly reduced by eradication efforts. Still, it remains a key pest of cotton (Gossypium spp., [Malvales: Malvaceae]) in the New World, and has proven difficult to eliminate from Mexico and from southern Texas. In those regions, improved knowledge of boll weevil overwintering ecology may benefit efforts by eradication and management programs. Adult diapause in the boll weevil is well documented, but influences of the feeding period duration between adult eclosion and assessment of diapause remain unstudied. We examined diapause incidence and associated survival for weevils fed for 7, 14, or 21 d after adult eclosion. Diapause incidence of females was less influenced by feeding duration compared with males. For males, highest diapause incidence occurred after 14 d of feeding compared with 7 or 21 d. Host-free survival tended to be higher after 14 d of feeding compared with 7 or 21 d, although many weevils were long-lived (≥80 d) after each feeding period duration. Males exhibited higher survival compared with females, and survival was higher for weevils fed large flower buds (squares) compared with smaller squares. Survival was most influenced by temperature; longevity increased with decreasing temperature except at the lowest temperature (12.8°C). These results suggest an optimal feeding period for induction of diapause and maximized host-free longevity. These findings may permit improved timing of late-season insecticide treatments aimed at reducing overwintering populations, and thereby improve effectiveness of eradication and management programs.
Major component analysis of dynamic networks of physiologic organ interactions

The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function.
LPBR: location prediction based routing protocol for mobile IoT systems

Recent advances in the Internet of Things(IoT) had created unparalleled opportunities and new applications. Low power communication technologies for IoT are critical for this success of IoT applications. IoT communication scenarios include mobile nodes in many IoT applications. This paper reviews state of the art for communication mechanisms in low power mobile scenarios of IoT applications. Such mobile scenarios demand low power routing based on metrics like node movement directions, speeds and energy optimizations. This paper proposes node rank optimization function called LPBR, based on location predictions along with energy. This proposed mechanism is evaluated through simulation study and results are presented in the paper. The simulation study shows more than 10% improvement in performance in terms of throughput of the system.
Risk-Based Design Security Analysis

Implementing security by design in practice often involves the application of threat modeling to elicit security threats and to aid designers in focusing efforts on the most stringent problems first. , Existing threat modeling methodologies are capable of generating lots of threats, yet they lack even basic support to triage these threats, except for relying on the expertise and manual assessment by the threat modeler. ,Since the essence of creating a secure design is to minimize associated risk (and countermeasure costs), risk analysis approaches offer a very compelling solution to this problem. By combining risk analysis and threat modeling, elicited threats in a design can be enriched with risk analysis information in order to provide support in triaging and prioritizing threats and focusing security efforts on the high-risk threats. It requires the following inputs: the asset values, the strengths of countermeasures, and an attacker model. ,In his paper, we provide an integrated threat elicitation and risk analysis approach, implemented in a threat modeling tool prototype, and evaluate it using a real-world application, namely the SecureDrop whistleblower submission system. We show that the security measures implemented in SecureDrop indeed correspond to the high-risk threats identified by our approach. Therefore, the risk-based security analysis provides useful guidance on focusing security efforts on the most important problems first.
Methods for automatic reference trees and multilevel phylogenetic placement

Motivation In most metagenomic sequencing studies, the initial analysis step consists in assessing the evolutionary provenance of the sequences. Phylogenetic (or Evolutionary) Placement methods can be employed to determine the evolutionary position of sequences with respect to a given reference phylogeny. These placement methods do however face certain limitations: The manual selection of reference sequences is labor-intensive; the computational effort to infer reference phylogenies is substantially larger than for methods that rely on sequence similarity; the number of taxa in the reference phylogeny should be small enough to allow for visually inspecting the results. Results We present algorithms to overcome the above limitations. First, we introduce a method to automatically construct representative sequences from databases to infer reference phylogenies. Second, we present an approach for conducting large-scale phylogenetic placements on nested phylogenies. Third, we describe a preprocessing pipeline that allows for handling huge sequence data sets. Our experiments on empirical data show that our methods substantially accelerate the workflow and yield highly accurate placement results. Implementation Freely available under GPLv3 at http://github.com/lczech/gappa. Contact lucas.czech@h-its.org Supplementary Information Supplementary data are available at Bioinformatics online.
Alterations of methionine metabolism in hepatocarcinogenesis: the emergent role of glycine N-methyltransferase in liver injury

The methionine and folate cycles play a fundamental role in cell physiology and their alteration is involved in liver injury and hepatocarcinogenesis. Glycine N-methyltransferase is implicated in methyl group supply, DNA methylation, and nucleotide biosynthesis. It regulates the cellular S-adenosylmethionine/S-adenosylhomocysteine ratio and S-adenosylmethionine-dependent methyl transfer reactions. Glycine N-methyltransferase is absent in fast-growing hepatocellular carcinomas and present at a low level in slower growing HCC ones. The mechanism of tumor suppression by glycine N-methyltransferase is not completely known. Glycine N-methyltransferase inhibits hepatocellular carcinoma growth through interaction with Dep domain-containing mechanistic target of rapamycin (mTor)-interacting protein, a binding protein overexpressed in hepatocellular carcinoma. The interaction of the phosphatase and tensin homolog inhibitor, phosphatidylinositol 3,4,5-trisphosphate-dependent rac exchanger, with glycine N-methyltransferase enhances proteasomal degradation of this exchanger by the E3 ubiquitin ligase HectH. Glycine N-methyltransferase also regulates genes related to detoxification and antioxidation pathways. It supports pyrimidine and purine syntheses and minimizes uracil incorporation into DNA as consequence of folate depletion. However, recent evidence indicates that glycine N-methyltransferase targeted into nucleus still exerts strong anti-proliferative effects independent of its catalytic activity, while its restriction to cytoplasm prevents these effects. Our current knowledge suggest that glycine N-methyltransferase plays a fundamental, even if not yet completely known, role in cellular physiology and highlights the need to further investigate this role in normal and cancer cells.
Evaluating health information apps on real life smart phone use

As the population is increasing day by day and the people are more interesting to know about their health information especially the elderly people, so they interact with the online technologies. Now it is important to design the Interface in such a way that the people do not feel frustrated by using them moreover the interface should be user -friendly and the people will not require any training in using these online technologies to view their health information. In this study, the role of emotional valence and arousal, their satisfaction level, the applications usability and what is the reason the different age group people prefer a specific interface format over others will be identified. As the term usability is concerned with both functional and pleasure related terms so, in this research different questionnaires such as SUS (System Usability Scale), QUIS(Questionnaire for User Interface Satisfaction), SAM(Self-Assessment Manikin) were conducted among the young and the older adults and their outcomes also analyzed on gender base. The results have shown that the youth preferred Animated apps rather than the Numeric and Diagrammatic which were preferred by the older adults. After the perception of the old and young people, it was found that apps should provide each function as the user demand and appeal of the different Healthcare apps in such a way that attracts the attention of a large audience. Therefore, there should need to design the interface in such a way that provides the easy navigational facility to the people that increase their satisfaction with their own ability to seek and use sources of health information.
Repertoire of plant RING E3 ubiquitin ligases revisited: New groups counting gene families and single genes

E3 ubiquitin ligases of the ubiquitin proteasome system (UPS) mediate recognition of substrates and later transfer the ubiquitin (Ub). They are the most expanded components of the system. The Really Interesting New Gene (RING) domain contains 40–60 residues that are highly represented among E3 ubiquitin ligases. The Arabidopsis thaliana E3 ubiquitin ligases with a RING finger primarily contain RING-HC or RING-H2 type domains or less frequently RING-v, RING-C2, RING-D, RING-S/T and RING-G type domains. Our previous work on three E3 ubiquitin ligase families with a RING-H2 type domain, ATL, BTL, and CTL, suggested that a phylogenetic distribution based on the RING domain allowed for the creation a catalog of known domains or unknown conserved motifs. This work provided a useful and comprehensive view of particular families of RING E3 ubiquitin ligases. We updated the annotation of A. thaliana RING proteins and surveyed RING proteins from 30 species across eukaryotes. Based on domain architecture profile of the A. thaliana proteins, we catalogued 4711 RING finger proteins into 107 groups, including 66 previously described gene families or single genes and 36 novel families or undescribed genes. Forty-four groups were specific to a plant lineage while 41 groups consisted of proteins found in all eukaryotic species. Our present study updates the current classification of plant RING finger proteins and reiterates the importance of these proteins in plant growth and adaptation.
Detecting and tracking ongoing topics in psychotherapeutic conversations

One of the key aspects in a psychotherapeutic conversation is the understanding of topics dynamics driving the dialogue. This may provide insights on the therapeutic strategy adopted by the counselor for the specific patient, providing the opportunity of building up artificial intelligence (AI) based methods for recommending the most appropriate therapy for a new patient. In this paper, we propose a method able to detect and track topics in real-life psychotherapeutic conversations based on Partially Labeled Dirichlet Allocation. Topics detection helps in summarizing the semantic themes used during the therapeutic conversations, and in predicting a specific topic for each talk-turn. The conversation is modeled by means of a distribution of ongoing topics propagating through each talk sequence. Tracking of topics aims at exploring the dynamics of the conversation and at offering insights into the underlying conversation logic and strategy. We present an alternative way to look at face-to-face conversations in conjunction with a new approach that combines topic modeling and transitions matrices to elicit valuable knowledge.
Has your smartphone replaced your brain? Construction and validation of the Extended Mind Questionnaire (XMQ)

As digital devices, such as smartphones, are becoming ever more absorbed in the daily lives of adolescents, a major assumption is that they start taking over basic functions of the human mind. A main focus of current debate and research is therefore on investigating adolescents’ use of digital technologies. However, the lack of an instrument measuring the degree to which adolescents offload cognitive and social functions to technology hinders debate and research. This paper tests the reliability and validity of the Extended Mind Questionnaire (XMQ) which measures the degree to which digital technology is used to offload cognitive and social functions. In a first study on young adults (n = 63), we constructed a 12-tem scale, which proved to be highly reliable. A large-scale study on teenagers (n = 947) demonstrated the high structural validity, reliability, and construct and criterion validity of the XMQ. In sum, these studies provide evidence that the XMQ is psychometrically sound and valid, and can be useful in future research on the consequences of digital technology in the daily lives of adolescents.
Modulating the bitterness of Empeltre olive oil by partitioning polyphenols between oil and water phases: Effect on quality and shelf life

Bitterness is a positive sensorial attribute of olive oil that mainly depends on phenol concentration. However, excessive bitterness may be unpleasant for consumers. The aim of this investigation was to evaluate if partitioning polyphenols between oil and water phases could modulate the bitterness of an Empeltre olive oil containing a phenolic concentration higher than the typical content for this olive oil variety. The linear relationship observed between the percentage of oil in the extraction system and the percentage of phenols removed from the oil permitted estimating the olive oil-to-water ratio required to reduce the concentration of phenols for a given value in order to modulate Empeltre olive oil bitterness. Olive oils after liquid–liquid extraction did not develop any negative sensory attributes, and their physicochemical parameters were not substantially affected. Liquid–liquid extraction using water as a solvent is a procedure capable of effectively reducing the total phenol compounds of Empeltre extra virgin olive oil and, as a consequence, of reducing its bitterness intensity without affecting the highest commercial category determined by the parameters legally established by European Community regulations just after extraction and during nine months of storage.
Binding site matching in rational drug design: algorithms and applications

Interactions between proteins and small molecules are critical for biological functions. These interactions often occur in small cavities within protein structures, known as ligand-binding pockets. Understanding the physicochemical qualities of binding pockets is essential to improve not only our basic knowledge of biological systems, but also drug development procedures. In order to quantify similarities among pockets in terms of their geometries and chemical properties, either bound ligands can be compared to one another or binding sites can be matched directly. Both perspectives routinely take advantage of computational methods including various techniques to represent and compare small molecules as well as local protein structures. In this review, we survey 12 tools widely used to match pockets. These methods are divided into five categories based on the algorithm implemented to construct binding-site alignments. In addition to the comprehensive analysis of their algorithms, test sets and the performance of each method are described. We also discuss general pharmacological applications of computational pocket matching in drug repurposing, polypharmacology and side effects. Reflecting on the importance of these techniques in drug discovery, in the end, we elaborate on the development of more accurate meta-predictors, the incorporation of protein flexibility and the integration of powerful artificial intelligence technologies such as deep learning.
ConvNet based QRS multilead delineator in electrocardiogram signals

The surface electrocardiogram (ECG) is the most widely adopted test to diagnose cardiac diseases. Extracting critical biomarkers from these signals, such as the QRS width, requires delineating the fundamental waves in them. However, even though ECG signals significantly change depending on the recording methodology and cardiac condition, the available QRS delineators are hard to adapt to non-considered cases. We present a machine learning-based multilead ECG delineation method which can successfully delineate QRS complexes. Our approach reached root-mean-square errors (RMSE) of 12.1±0.5 and 18.5±1.1 ms for QRS onset and offset, respectively, when evaluated on the QT database; thus, demonstrating to be comparable to the state-of-the-art. Moreover, these results are similar to the RMSE calculated from differences between the two cardiologists that annotated this database, namely, 14.7 ms for the QRS onset and 17.2 ms for the offset.
Development of in vitro - in vivo correlations for newly optimized Nimesulide formulations

Use of the human volunteers in bioequivalence studies is being discouraged by the Food and drug administration after the introduction of biowaiver approaches. In-vitro in-vivo correlation (IVIVC) with the level A is accepted for the registration of new molecules. In the present study deconvolution technique with numeric approaches was applied after compressing and in vitro validating the 100mg Nimesulide immediate, intermediate and slow release tablets. Single centered, crossover, randomized study was conducted in four phases with a two-week washout period to obtain the plasma drug concentration data after administrating test and reference products in male healthy volunteers. KineticaTM 4.4. 1 (Thermoelectron corp, USA) was used for the calculation of two ways ANOVA with 90% CI from both log transformed and non- transformed data and Phoenix WinNonlin 7 and it's IVIVC toolkit version 7.0 was used for the application of numeric approaches of IVIVC. Results revealed that the individual internal percentage prediction error for AUCinf and Cmax were found to be < 15% while their average values were < 10% in all medium. Numeric values of % PE at pH 6.8 and pH 7.4 (50 rpm in USP II and 100 rpm in USP I and II apparatus) were found to be (2.5842, 2.9789 and, 7.1732; 7.0944, 2.4721 and 4.350) for AUCinf and (2.5842, 0.5736 and 4.6928; 5.6214, 3.0551 and -2.4711) values for Cmax respectively. The low values of prediction errors demonstrate that the correlation model is projecting the in vivo response of each formulation. Percentage External error (% PE) was not required because individual values of percentage internal error (%PE) of Cmax and AUClast were not >15. In order to predict point to point correlation between fraction drug dissolved and drug absorbed, their mean r2 value was found to be > 0.9112 which showed a linear correlation in slightly alkaline pH.
Basal ganglia and cerebellar pathology in X-linked dystonia-parkinsonism

X-linked dystonia-parkinsonism is a neurodegenerative movement disorder characterized by adult-onset dystonia combined with parkinsonism over the disease course. Previous imaging and pathological findings indicate exclusive striatal atrophy with predominant pathology of the striosomal compartment in the dystonic phase of X-linked dystonia-parkinsonism. The striosome occupies 10-15% of the entire striatal volume and the density of striosomes follows a rostrocaudal gradient with the rostral striatum being considered striosome-rich. Recent quantitative MRI analyses provided evidence for an additional involvement of the white matter and the pallidum. In this study, we aimed to (i) disentangle the degree of atrophy in the different subdivisions of the striatum; (ii) investigate changes of cortical morphology; and (iii) elucidate the role of the cerebellum in X-linked dystonia-parkinsonism. T1-weighted MRI scans were acquired in 17 male X-linked dystonia-parkinsonism patients with predominant dystonia (40.1 ± 7.5 years) and 17 ethnicity-matched male healthy controls (35.2 ± 7.4 years). Voxel-based morphometry used a region of interest-based approach for the basal ganglia and primary motor cortex, whole brain analysis, and a separate analysis of the cerebellum. Cortical thickness and subcortical volume were measured. Volume loss in X-linked dystonia-parkinsonism affected all parts of the striatum (-29% voxel intensity) but was most pronounced in the associative subdivision (-41%; P < 0.001). The volume loss also involved the external and internal pallidum, albeit to a lesser extent than the striatum (-19% and -12%, P<0.001). Cortical thickness was reduced in the frontal (-4.3%) and temporal cortex (-6.1%). In addition, we found grey matter pathology in the associative part of the cerebellum and increased voxel intensities in the anterior sensorimotor part of the cerebellum and the dorsal ponto-mesencephalic brainstem. Taken together, our analysis of subcortical and cortical grey matter in the dystonic phase of X-linked dystonia-parkinsonism showed that (i) the striosome-enriched rostral striatum was most severely affected; and (ii) cortical thickness was only reduced in those regions that predominantly have anatomical connections to striosomes. Moreover, the cerebellum may be implicated in both disease-related and compensatory changes, highlighting the significance of the cerebellum in the pathophysiology of dystonia.