Miracle-dz/UniFAR-FTUs huggingface dataset:
A pipeline for identifying endogenous neuropeptides from spectral archives

Shotgun proteomics experiments often provide a big amount of spectra data; however, a big part of them remain unidentified. Many unidentified spectra that are high probably from peptides could be revealed by data mining methods such as clustering. This idea motivates researchers to build 'spectral archives' to identify more peptides from the previously analysed resources. The objective is to build a general way to identify peptides for these high possibility spectra in spectral archives, to help biologists to get more output from the data. We here propose a novel generic pipeline for this approach, based on the PRIDE cluster resources, rather than building a complete archive from scratch. We applied our pipeline to test the identification of endogenous neuropeptides in rat. 33 high probability peptide-induced spectra have been exposed from rat's unidentified spectra in PRIDE cluster's archive.
Integration of resting state functional MRI into clinical practice - A large single institution experience

Functional magnetic resonance imaging (fMRI) is an important tool for pre-surgical evaluation of eloquent cortex. Classic task-based paradigms require patient participation and individual imaging sequence acquisitions for each functional domain that is being assessed. Resting state fMRI (rs-fMRI), however, enables functional localization without patient participation and can evaluate numerous functional domains with a single imaging session. To date, post-processing of this resting state data has been resource intensive, which limits its widespread application for routine clinical use. Through a novel automated algorithm and advanced imaging IT structure, we report the clinical application and the large-scale integration of rs-fMRI into routine neurosurgical practice. One hundred and ninety one consecutive patients underwent a 3T rs-fMRI, 83 of whom also underwent both motor and language task-based fMRI. Data were processed using a novel, automated, multi-layer perceptron algorithm and integrated into stereotactic navigation using a streamlined IT imaging pipeline. One hundred eighty-five studies were performed for intracranial neoplasm, 14 for refractory epilepsy and 33 for vascular malformations or other neurological disorders. Failure rate of rs-fMRI of 13% was significantly better than that for task-based fMRI (38.5%,) (p <0.001). In conclusion, at Washington University in St. Louis, rs-fMRI has become an integral part of standard imaging for neurosurgical planning. Resting state fMRI can be used in all patients, and due to its lower failure rate than task-based fMRI, it is useful for patients who are unable to cooperate with task-based studies.
Closing loops : a unified view from control to information science

The application of feedback mechanism to technical systems is one the most important steps improving the dynamics of technical systems and also to realize new technical solutions. The dynamical behavior of technical systems is considered without and with control, conditions are calculated improving vibrational behaviour first of SISO, since the sixties also of MIMO systems. New mathematical approaches are used to examine the structural inner connections between the system itself and also from the input and to the output. In all of these cases physical values on the input and output side are considered as signals equal to functions of time. Mathematical equations (like ODE/PDE or DAE) are ususally used to describe the I/O behaviour. With the same roots, information scientific approaches are developed in the last 60 years. The objects of information science approaches are data in various pure and combined variations, but mainly numbers. The common root is founded by Wiener (6) and others. Inspired by the success of computing machines, Wiener regrets the feedback mechanism and combines this with algorithms realized on computing machines and thoughts about self-organizing and -optimizing systems (like closed-loop systems are self-optimizing systems with respect to the dynamic behaviour of the output). This gives the new scientific community the name used for over 20-30 years: cybernetics. The mathematical core of this new science focused to technical applications based on mathematics: control and control theory. Up to the eighties this area is growing and several new applications demonstrate daily the success of this ideas. The development of computers, the increasing memory capabilities, the processing speed but especially the success in software technologies decouples the development of applied information science from those of control techniques.
Glucagon Receptor Signaling Regulates Energy Metabolism via Hepatic Farnesoid X Receptor and Fibroblast Growth Factor 21

Glucagon, an essential regulator of glucose and lipid metabolism, also promotes weight loss, in part through potentiation of fibroblast growth factor 21 (FGF21) secretion. However, FGF21 is only a partial mediator of metabolic actions ensuing from glucagon receptor (GCGR) activation, prompting us to search for additional pathways. Intriguingly, chronic GCGR agonism increases plasma bile acid levels. We hypothesized that GCGR agonism regulates energy metabolism, at least in part, through farnesoid X receptor (FXR). To test this hypothesis, we studied whole-body and liver-specific FXR-knockout (Fxr∆liver) mice. Chronic GCGR agonist (IUB288) administration in diet-induced obese (DIO) Gcgr, Fgf21, and Fxr whole-body or liver-specific knockout (∆liver) mice failed to reduce body weight when compared with wild-type (WT) mice. IUB288 increased energy expenditure and respiration in DIO WT mice, but not Fxr∆liver mice. GCGR agonism increased [14C]palmitate oxidation in hepatocytes isolated from WT mice in a dose-dependent manner, an effect blunted in hepatocytes from Fxr∆liver mice. Our data clearly demonstrate that control of whole-body energy expenditure by GCGR agonism requires intact FXR signaling in the liver. This heretofore-unappreciated aspect of glucagon biology has implications for the use of GCGR agonism in the therapy of metabolic disorders.
Ethyl Acetate Extract of Scindapsus cf. hederaceus Exerts the Inhibitory Bioactivity on Human Non-Small Cell Lung Cancer Cells through Modulating ER Stress

Unfolded protein response (UPR) is a cytoprotective mechanism that alleviates the protein-folding burden in eukaryotic organisms. Moderate activation of UPR is required for maintaining endoplasmic reticulum (ER) homeostasis and profoundly contributes to tumorigenesis. Defects in UPR signaling are implicated in the attenuation of various malignant phenotypes including cell proliferation, migration, and invasion, as well as angiogenesis. This suggests UPR as a promising target in cancer therapy. The pharmacological effects of the plant Scindapsus cf. hederaceus on human cancer cell lines is not understood. In this study, we identified an ethyl acetate extract from Scindapsus cf. hederaceus (SH-EAE), which markedly altered the protein expression of UPR-related genes in human non-small cell lung cancer (NSCLC) cells. Treatment with the SH-EAE led to the dose-dependent suppression of colony forming ability of both H1299 and H460 cells, but not markedly in normal bronchial epithelial BEAS-2B cells. SH-EAE treatment also attenuated the migration and invasion ability of H1299 and H460 cells. Moreover, SH-EAE strikingly suppressed the protein expression of two ER stress sensors, including inositol requiring enzyme-1α (IRE-1α) and protein kinase R-like ER kinase (PERK), and antagonized the induction of C/EBP homologous protein (CHOP) expression by thapsigargin, an ER stress inducer. SH-EAE induced the formation of massive vacuoles which are probably derived from ER. Importantly, SH-EAE impaired the formation of intersegmental vessels (ISV) in zebrafish larvae, an index of angiogenesis, but had no apparent effect on the rate of larval development. Together, our findings demonstrate, for the first time, that the ability of SH-EAE specifically targets the two sensors of UPR, with significant anti-proliferation and anti-migration activities as a crude extract in human NSCLC cells. Our finding also indicates potential applications of SH-EAE in preventing UPR activation in response to Tg-induced ER stress. We suggest that SH-EAE attenuates UPR adaptive pathways for rendering the NSCLC cells intolerant to ER stress.
Relations between modeling behavior and learning in a Computational Thinking based science learning environment

Computational Thinking (CT) is becoming a core element of current K-12 science curricula. In spite of the known synergies between CT and science education, few attempts have been made to leverage this synergy, especially at the middle school level. In previous work with the Computational Thinking for Simulation and Modeling (CTSiM) environment (Basu, et al., 2013; 2014; Sengupta, et al., 2013) we have demonstrated strong synergies between learning science content and CT, with students showing strong learning gains in kinematics, ecology, and CT concepts. However, when working in CTSiM, students also faced a number of difficulties in understanding science concepts and CT constructs, and had to be scaffolded 1-1 by the classroom teacher or the researchers conducting the study (Basu, et al., in review). To better scaffold their learning, we developed a set of hypertext resources and formative assessment quizzes in the system. This paper reports a teacher-led, multi-domain classroom study conducted with 5 grade students using CTSiM. Our results, based on preto post-test gains, and the accuracy of the students’ CTSiM models, demonstrate significant and synergistic learning of science concepts and CT skills in Kinematics and Ecology domains, along with transfer of CT skills across domains.
A Novel Diffuse Fraction‐Based Two‐Leaf Light Use Efficiency Model: An Application Quantifying Photosynthetic Seasonality across 20 AmeriFlux Flux Tower Sites

Diffuse radiation can increase canopy light use efficiency (LUE). This creates the need to differentiate the effects of direct and diffuse radiation when simulating terrestrial gross primary production (GPP). Here, we present a novel GPP model, the diffuse‐fraction‐based two‐leaf model (DTEC), which includes the leaf response to direct and diffuse radiation, and treats maximum LUE for shaded leaves (ɛmsh defined as a power function of the diffuse fraction (Df)) and sunlit leaves (ɛmsu defined as a constant) separately. An Amazonian rainforest site (KM67) was used to calibrate the model by simulating the linear relationship between monthly canopy LUE and Df. This showed a positive response of forest GPP to atmospheric diffuse radiation, and suggested that diffuse radiation was more limiting than global radiation and water availability for Amazon rainforest GPP on a monthly scale. Further evaluation at 20 independent AmeriFlux sites showed that the DTEC model, when driven by monthly meteorological data and MODIS leaf area index (LAI) products, explained 70% of the variability observed in monthly flux tower GPP. This exceeded the 51% accounted for by the MODIS 17A2 big‐leaf GPP product. The DTEC model's explicit accounting for the impacts of diffuse radiation and soil water stress along with its parameterization for C4 and C3 plants was responsible for this difference. The evaluation of DTEC at Amazon rainforest sites demonstrated its potential to capture the unique seasonality of higher GPP during the diffuse radiation‐dominated wet season. Our results highlight the importance of diffuse radiation in seasonal GPP simulation.
On Autistic Behavior Model

Assuming that a behavior of low-functioning persons affected by autism spectrum disorder (ASD) is related to the abstraction ability deficit we propose a simple model in which this ability is described by a distance function $d_{q}$(A,B)= $\Vert$ A-B$\Vert_{q}$, q$\in$ [0,$\infty$], measuring differences between patterns. We posit that, with a decreasing parameter q, the abstraction ability diminishes and, in particular, impairs both supervised and unsupervised learning. We provide suggestions for education and therapy, and explain several examples of autistic behaviors.
1 OVERVIEW OF THE VARIOUS TYPES OF MASS SPECTROMETERS THAT ARE USED IN DRUG DISCOVERY AND DRUG DEVELOPMENT

Since J.J. Dempster published one of the fi rst reports on the detection of volatile organic compounds using electron impact ionization in 1918, signifi cant progress in ion sources and mass analyzers has been achieved. The aim this chapter is to focus on the most commonly used techniques in drug metabolism studies for quantitative or qualitative analysis, and also to discuss some of the “ niche ” techniques. In terms of the ionization techniques, atmospheric pressure ionization ( API ) sources including electrospray (ESI), atmospheric pressure chemical ionization ( APCI ), and atmospheric pressure photoionization ( APPI ) have revolutionized the analysis of low molecular weight compound s ( LMWCs ) by high performance liquid chromatography mass spectrometry ( HPLC MS ). In addition, matrix assisted laser desorption/ ionization ( MALDI ) was originally developed for the characterization of biopolymers, but is also attractive for the analysis of LMWCs and for mass spectrometry imaging ( MSI ) of drugs and their metabolites in tissues. Ambient ionization techniques have also gained interest for the same type of applications. Finally, inductively coupled plasma ( ICP ) mass spectrometry has also been explored as an alternative detector to 14 C labeled drug for drug metabolism studies. Triple quadrupole MS systems have become the workhorse for quantitation and, in combination with linear ion traps (LITs), are very attractive for qualitative/ quantitative workfl ows. Ions traps are still used as standalone mass spectrometers
Dynamical density functional theory for colloidal particles with arbitrary shape

Starting from the many-particle Smoluchowski equation, we derive a dynamical density functional theory for Brownian particles with an arbitrary shape. Both passive and active (self-propelled) particles are considered. The resulting theory constitutes a microscopic framework to explore the collective dynamical behavior of biaxial particles in non-equilibrium. For spherical and uniaxial particles, earlier derived dynamical density functional theories are recovered as special cases. Our study is motivated by recent experimental progress in preparing colloidal particles with many different biaxial shapes.
Demo Abstract: TotTernary - A Wearable Platform for Social Interaction Tracking

We present TotTernary, the first infrastructure-free, long-term research platform which enables domain scientists to measure human interactions with previously unprecedented accuracy and flexibility. The platform can be tailored to varying scenarios by adjusting the ranging fidelity and the update rate and demonstrates dynamic adaptation to its environment. As a mobile, accurate, and reliable system for ranging measurements, it allows users to gather both distance and position information with decimeter accuracy. Measuring only 61 × 35 mm and weighing 7.7 g, it integrates two radios to achieve both low-power neighbour discovery and direct user interactions using Bluetooth Low Energy as well as precise ultra-wide band ranging measurements. The system introduces a novel energy-efficient ranging protocol with linear message complexity to achieve life times of up to 39 days. Furthermore, leveraging both antenna and frequency diversity, we demonstrate that the median ranging error can be reduced by up to 86% through an efficient aggregation of measurements over multiple channels. Our system is capable of highly reliable and consistent measurements with as little as 14.8 cm of ranging error in the 99th percentile and a 90% confidence interval of 11.3 cm.
A Constrained Maximum Likelihood Estimator for Unguided Social Sensing

This paper develops a constrained expectation maximization algorithm (CEM) that improves the accuracy of truth estimation in unguided social sensing applications. Unguided social sensing refers to the act of leveraging naturally occurring observations on social media as “sensor measurements”, when the sources post at will and not in response to specific sensing campaigns or surveys. A key challenge in social sensing, in general, lies in estimating the veracity of reported observations, when the sources reporting these observations are of unknown reliability and their observations themselves cannot be readily verified. This problem is known as fact-finding. Unsupervised solutions have been proposed to the fact-finding problem that explore notions of internal data consistency in order to estimate observation veracity. This paper observes that unguided social sensing gives rise to a new (and very simple) constraint that dramatically reduces the space of feasible fact-finding solutions, hence significantly improving the quality of fact-finding results. The constraint relies on a simple approximate test of source independence, applicable to unguided sensing, and incorporates information about the number of independent sources of an observation to constrain the posterior estimate of its probability of correctness. Two different approaches are developed to test the independence of sources for purposes of applying this constraint, leading to two flavors of the CEM algorithm, we call CEM and CEM-Jaccard. We show using both simulation and real data sets collected from Twitter that by forcing the algorithm to converge to a solution in which the constraint is satisfied, the quality of solutions is significantly improved.
Fusion of Infrared Thermal Image and Visible Image for 3D Thermal Model Reconstruction Using Smartphone Sensors

Thermal infrared imagery provides temperature information on target objects, and has been widely applied in non-destructive testing. However, thermal infrared imagery is not always able to display detailed textures of inspected objects, which hampers the understanding of geometric entities consisting of temperature information. Although some commercial software has been developed for 3D thermal model displays, the software requires the use of expensive specific thermal infrared sensors. This study proposes a cost-effective method for 3D thermal model reconstruction based on image-based modeling. Two smart phones and a low-cost thermal infrared camera are employed to acquire visible images and thermal images, respectively, that are fused for 3D thermal model reconstruction. The experiment results demonstrate that the proposed method is able to effectively reconstruct a 3D thermal model which extremely approximates its corresponding entity. The total computational time for the 3D thermal model reconstruction is intensive while generating dense points required for the creation of a geometric entity. Future work will improve the efficiency of the proposed method in order to expand its potential applications to in-time monitoring.
FSIM: A Fast and Scalable Influence Maximization Algorithm Based on Community Detection

Influence maximization algorithms try to select a set of individuals in social networks that are more influential. The Influence maximization problem is important in marketing and many researchers has researched on it and proposed new algorithms. All proposed algorithms are not scalable and are very time consuming for very large social networks generally. In this paper, a fast and scalable influence maximization algorithm called FSIM is proposed based on community detection. FSIM algorithm decreases number of nodes that must be examined without loss of the operations quality therefore it can find seeds quickly. FSIM can maximize influence in large social networks. Experimental results show FSIM is faster and more scalable than existing algorithms.
A Live Trapping and Handling Technique for River Otter

Capture and handling techniques developed by river otter (Lutra canadensis) trappers, were evaluated during a 3-year telemetric study in the coastal marsh of Louisiana. A modified No. 11 Victor leghold trap was found to be the most practical and efficient live trap for otters in a marsh habitat. A total of 30 otters were captured. Trap-related injuries were infrequent and not serious. Eighty-four percent of the captured otters sustained minor cuts or no injury at all. Trapped otter were handled safely and efficiently by means of a long-handled net. This handling technique was also used to handle 5 captive otter on several occasions. Proc. Annu. Cont. Southeast. Assoc. Fish and Wi Idl. Agencies 37:182-189 Increases in fur prices during the mid-1970s and the listing of the river otter on Appendix II of the Convention of International Trade of Endangered Species (CITES) in 1976 created a demand for more biological information on the species. Prior to 1974, much of the research on river otter dealt with food habits (Lagler and Ostenson 1942, Wilson 1954, Ryder 1955, Greer 1955, Hamilton 1961, McDaniel 1963, Sheldon and Toll 1964, Knudsen and Hale 1968). Since 1974, many studies have concentrated on population characteristics and ecology of the river otter (Tabor and Wight 1977, Lauhachinda 1978, Mowbray et al. 1979, Melquist and Hornocker 1983). Melquist and Hornocker (1979) working in Idaho were the first to examine the problem of capturing and handling otter for telemetric and related research. Robi1 Present address: Louisiana Cooperative Extension Service, 1105 West Port Street, Abbeville, LA 70510. 1983 Proc. Annu. Conf. SEAFWA Live Trapping and Handling River Otter 183 cheaux and Linscombe (1979), working with coastal furbearers, found a restraining snare to be the most efficient tool for handling all furbearers except the river otter. In 1978, the International Association of Fish and Wildlife Agencies (IAFWA) reported 22 state agencies and 5 Canadian provinces were conducting otter research (Deems and Pursley 1978). During recent years, several states have initiated programs to restock otter. Colorado began restocking in 1976 (Harvey Donoho, pers. commun. 1981). Arizona and Missouri are currently involved in otter restocking projects. In 1979, the Louisiana Department of Wildlife and Fisheries initiated a telemetric study of river otter activity and habitat preference in the coastal marsh of Southwest Louisiana. Live trapping and handling requirements of the study necessitated an investigation of techniques. The objective of this study was the evaluation of techniques that produce minimum stress or injury to the animal, are reasonably safe for the researcher, and are efficient in capturing and handling otter. This paper presents the results of this investigation. The manuscript was typed by M. Hebert with illustrations by J. Marte.