Miracle-dz/UniFAR-FTUs huggingface dataset:
Animal Cytogenetics and Comparative Mapping

ABC Fax + 41 61 306 12 34 E-mail karger@karger.ch www.karger. com © 2002 S. Karger AG, Basel 0301–0171/02/0981–0054$18.50/0 Accessible online at: www.karger. com/cgr Abstract. The California condor is the largest flying bird in North America and belongs to a group of New World vultures. Recovering from a near fatal population decline, and currently with only 197 extant individuals, the species remains listed as endangered. Very little genetic information exists for this species, although sexing methods employing chromosome analysis or W-chromosome specific amplification is routinely applied for the management of this monomorphic species. Keeping in mind that genetic conditions like chondrodystrophy have been identified, preliminary steps were undertaken in this study to understand the genome organization of the condor. This included an extensive cytogenetic analysis that provided (i) a chromosome number of 80 (with a likelihood of an extra pair of microchromosomes), and (ii) information on the centromeres, telomeres and nucleolus organizer regions. Further, a comparison between condor and chicken macrochromosomes was obtained by using individual chicken chromosome specific paints 1–9 and Z and W on condor metaphase spreads. Except for chromosomes 4 and Z, each of the chicken (GGA) macrochromosomes painted a single condor (GCA) macrochromosome. GGA4 paint detected complete homology with two condor chromosomes, viz., GCA4 and GCA9 providing additional proof that the latter are ancestral chromosomes in the birds. The chicken Z chromosome showed correspondence with both Z and W in the condor. The homology suggests that the condor sex chromosomes have not completely differentiated during evolution, which is unlike the majority of the non-ratites studied up till now. Overall, the study provides detailed cytogenetic and basic comparative information on condor chromosomes. These findings significantly advance the effort to study the chondrodystrophy that is responsible for over ten percent mortality in the condor.
Analysis of the Outcomes of the Screen-Time Reduction in Computer Vision Syndrome: A Cohort Comparative Study

Purpose To analyze the outcomes of screen-time reduction on the foveal responses that associates computer vision syndrome (CVS) using multifocal electroretinogram (mfERG) examination. Methods This prospective multicenter cohort comparative study included 49 eyes of 49 medical students divided into two groups. Group A (control group) included 25 eyes with no CVS diagnosis while group B (CVS group) included 24 eyes with CVS diagnosis. All students responded to the valid and reliable CVS-Form 3 (CVS-F3) questionnaire and underwent complete ophthalmic and mfERG examinations twice at the time recruitment in the study and four weeks after strict reduction of the daily screen-hours to ≤1 screen-hour daily to document associated foveal responses. Results We documented statistically significant reduction in foveal responses in CVS versus control groups in mean mfERG Rings 1, 2, and 5 with Quadrants 1, 2, and 4 (P=<0.0001, 0.0001, 0.0003, 0.001, 0.002, and 0.006, respectively). Following the screen-time reduction, the second mfERG examination revealed significant post-reduction improvements in foveal responses in CVS group particularly in mean mfERG Rings 1, 2, 3, and 5 with Quadrants 1 and 4 (P=<0.0001, <0.0001, 0.0005, 0.02, <0.0001, and 0.04, respectively). Conclusion This study documented the screen-induced foveal dysfunction that associates CVS using mfERG examination, which revealed remarkable significant improvements in foveal responses in the 4 weeks following strict screen-time reduction. These improvements were also associated with corresponding improvements in the visual performances. We suggest that the potential screen-induced foveal dysfunction outcomes might be reversible with strict screen-time reduction. We also recommend that educational institutional policies should limit online education-hours and redesign the mandated computer system use program to guard against visual sequelae of CVS. Clinical Trials Registration ClinicalTrials.gov (ID: NCT04405648).
Oxidative stress and mitochondrial dysfunction as determinants of ischemic neuronal death and survival

Mitochondria are the powerhouse of the cell. Their primary physiological function is to generate adenosine triphosphate through oxidative phosphorylation via the electron transport chain. Reactive oxygen species generated from mitochondria have been implicated in acute brain injuries such as stroke and neurodegeneration. Recent studies have shown that mitochondrially‐formed oxidants are mediators of molecular signaling, which is implicated in the mitochondria‐dependent apoptotic pathway that involves pro‐ and antiapoptotic protein binding, the release of cytochrome c, and transcription‐independent p53 signaling, leading to neuronal death. Oxidative stress and the redox state of ischemic neurons are also implicated in the signaling pathway that involves phosphatidylinositol 3‐kinase/Akt and downstream signaling, which lead to neuronal survival. Genetically modified mice or rats that over‐express or are deficient in superoxide dismutase have provided strong evidence in support of the role of mitochondrial dysfunction and oxidative stress as determinants of neuronal death/survival after stroke and neurodegeneration.
Prosocial Learning Agents Solve Generalized Stag Hunts Better than Selfish Ones Extended Abstract

1 EXTENDED ABSTRACT Real world interactions are full of coordination problems [2, 3, 8, 14, 15] and thus constructing agents that can solve them is an important problem for artificial intelligence research. One of the simplest, most heavily studied coordination problems is the matrixform, two-player Stag Hunt. In the Stag Hunt, each player makes a choice between a risky action (hunt the stag) and a safe action (forage for mushrooms). Foraging for mushrooms always yields a safe payoff while hunting yields a high payoff if the other player also hunts but a very low payoff if one shows up to hunt alone. This game has two important Nash equilibria: either both players show up to hunt (this is called the payoff dominant equilibrium) or both players stay home and forage (this is called the risk-dominant equilibrium [7]). In the Stag Hunt, when the payoff to hunting alone is sufficiently low, dyads of learners as well as evolving populations converge to the risk-dominant (safe) equilibrium [6, 8, 10, 11]. The intuition here is that even a slight amount of doubt about whether one’s partner will show up causes an agent to choose the safe action. This in turn causes partners to be less likely to hunt in the future and the system trends to the inefficient equilibrium. We are interested in the problem of agent design: our task is to construct an agent that will go into an initially poorly understood environment and make decisions. Our agent must learn from its experiences to update its policy and maximize some scalar reward. However, there will also be other agents which we do not control. These agents will also learn from their experiences. We ask: if the environment has Stag Hunt-like properties, can we make changes to our agent’s learning to improve its outcomes? We focus on reinforcement learning (RL), however, many of our results should generalize to other learning algorithms.
Inter-limb Asymmetries : Are Thresholds a Usable Concept ?

The concept of thresholds have commonly appeared in the literature for the topic of inter-limb asymmetry. However, with an abundance of literature showing asymmetry to be task and metric-specific, the use of thresholds seems flawed. When computed, practitioners are often left with a percentage figure and it is not always entirely obvious how to interpret this value. This article aims to provide practitioners with some guidelines on meaningful ways to use and interpret inter-limb asymmetry data.
RP-HPLC Method for Simultaneous Determination of Captopril and Diuretics: Application in Pharmaceutical Dosage Forms and Human Serum

An isocratic reversed phase high-performance liquid chromatographic (RP-HPLC) method has been developed for the simultaneous determination of captopril and diuretics (furosemide and hydrochlorothiazide) in API, dosage formulations and human serum. Chromatographic separation was achieved on Purospher Start C18 (250 mm x 4.6 mm, 5 μm) and Hypersil ODS C18 (150×4.6mm, 5micron) columns using mobile phase, methanol: water (70:30 v/v) adjusted to pH 3.0 via phosphoric acid 85% having flow rate of 1.0 mL min -1 at ambient temperature with detector set at 225 nm. Calibration curves were linear over range of 5-25 μg mL -1 with a correlation coefficient ± 0.999. LOD and LOQ were in the ranges of 0.4-2.3 μg mL -1 . Intra and inter-run precision and accuracy results were 98.0 to 102%.
Simulation, Image Reconstruction and SiPM Characterisation for a Novel Endoscopic Positron Emission Tomography Detector

In the scope of the EndoTOFPET-US project, a novel multimodal device for ultrasound (US) endoscopy and positron emission tomography (PET) is being developed. The project aims at detecting and quantifying morphologic and functional biomarkers and developing new biomarkers for pancreas and prostate oncology. The detector system comprises a small detector probe mounted on an ultrasound endoscope and an external detector plate. The detection of the gamma rays is realised by scintillator crystals with Silicon Photomultiplier (SiPM) read-out. For the characterisation of over 4000 SiPMs for the external plate, an automatised measurement and data analysis procedure is established. The key properties of the SiPMs like breakdown voltage and dark count rate (DCR) are extracted. This knowledge is needed both as a quality assurance as well as for the calibration of the detector. The spread between minimum and maximum breakdown voltage within a SiPM array of 4× 4 is at maximum 0.43 V with a mean of 0.15 V and an RMS of 0.06 V. This assures the optimal biasing of each SiPM at its individual operating voltage. The mean DCR amounts to 1.49 MHz with an RMS of 0.54 MHz and is thus well below the acceptable threshold of 3 MHz. Two spare modules from the external plate are re-measured and analysed several years after the module assembly, revealing a potential alteration of the SiPM noise properties over time. For the characterisation of SiPMs from di erent vendors, a software framework for the automatic extraction of performance parameters from pulseheight spectra, including a t of the entire spectrum, is developed and tested. In order to facilitate the modelling of the response of the EndoTOFPET-US detector, a framework is developed which is built around the Geant4-based simulation toolkit GAMOS, to simulate and reconstruct realistic imaging scenarios with this asymmetric PET detector. The simulation studies are used to compare di erent possible detector designs, guide the development of the custom image reconstruction software, and assess the image quality qualitatively and quantitatively. With the help of simple simulated phantoms, the in uence of the amount of probe rotation and acquisition time on the resulting image quality and image resolution is investigated. It is shown that a scan time of approximately 10 minutes and small rotation of around 10◦ yields a saturation in image quality. Furthermore, studies using full-body patient data are presented. The results suggest that the endoscopic approach is able to separate the prostatic lesion well from the
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning

S in Fig 2. The setup was a seek-avoid style task, where one of the two object types in the room gave a reward of +1 and the other gave a reward of -1. The agent was allowed to pick up objects for 60 seconds after which the episode would terminate and a new one would begin; if the agent was able to pick up all the ‘good’ objects in less than 60 seconds, a new episode was begun immediately. The agent was spawned in a random location in the room at the start of each new episode.
C V ] 1 8 Se p 20 17 Fast YOLO : A Fast You Only Look Once System for Real-time Embedded Object Detection in Video

Object detection is considered one of the most challenging problems in this field of computer vision, as it involves the combination of object classification and object localization within a scene. Recently, deep neural networks (DNNs) have been demonstrated to achieve superior object detection performance compared to other approaches, with YOLOv2 (an improved You Only Look Once model) being one of the state-of-the-art in DNN-based object detection methods in terms of both speed and accuracy. Although YOLOv2 can achieve real-time performance on a powerful GPU, it still remains very challenging for leveraging this approach for real-time object detection in video on embedded computing devices with limited computational power and limited memory. In this paper, we propose a new framework called Fast YOLO, a fast You Only Look Once framework which accelerates YOLOv2 to be able to perform object detection in video on embedded devices in a realtime manner. First, we leverage the evolutionary deep intelligence framework to evolve the YOLOv2 network architecture and produce an optimized architecture (referred to as O-YOLOv2 here) that has 2.8X fewer parameters with just a ∼2% IOU drop. To further reduce power consumption on embedded devices while maintaining performance, a motion-adaptive inference method is introduced into the proposed Fast YOLO framework to reduce the frequency of deep inference with O-YOLOv2 based on temporal motion characteristics. Experimental results show that the proposed Fast YOLO framework can reduce the number of deep inferences by an average of 38.13%, and an average speedup of ∼3.3X for objection detection in video compared to the original YOLOv2, leading Fast YOLO to run an average of ∼18FPS on a Nvidia Jetson TX1 em-
Floating Drug Delivery System: A Brief Review

Scientific and technological developments in the research and development of new drug delivery systems have been made in recent years by resolving physiological disorders, such as short gastric residence periods and unpredictable gastric emptying times. Dosage forms that can be hold within the stomach are called as Gastro-retentive Dosage Forms (GRDF). Multiple methods used in the prolongation of gastric residence time are floating drug delivery system, swelling and expanding system, polymeric bio-adhesive system, high density system and other delayed gastric emptying system. Medication-based disease treatment is entering a new era in which a increasing range of innovative drug delivery technologies are being used and are available for clinical use. Floating Drug Delivery Systems (FDDS) is one of the gastro-retentive dosage forms used to achieve extended duration of gastric residency. The aim of writing this review on floating drug delivery systems (FDDS) was to compile the recent literature with particular focus on the main floating mechanism to achieve gastric retention. Sustained oral release of gastrointestinal dosage types provides many benefits for drugs with absorption from the upper sections of the gastrointestinal tract and those that function locally throughout the stomach. This review includes the physiology, factors controlling gastric retention time, excipient variables influencing gastric retention, approaches to designing single-unit, hydro-dynamically balanced system and multi-unit floating structure, and aspects of their classification, formulation and evaluation are discussed in detail, and few applications of these systems.
Ieee Transactions on Visualization and Computer Graphics 1 Mixed Media Painting and Portraiture

— This paper presents a technique for mixed media non-photorealistic painting and portraiture. The goal of this work is to transform digital images into renderings that approximate the appearance of mixed media artwork, which incorporates two or more traditional visual media. We achieve this by first separating an input image into distinct regions based on the degree of local detail present in the image. Each region is then processed independently with a user-selected NPR filter. This allows the user to treat highly detailed regions differently from regions of low frequency content. The separately processed regions are then smoothly fused in the gradient domain. In addition, we extend our work to the rendering of mixed media portraits. Portraits pose unique challenges that we address with our method of segmentation, which is based on a composite of face detection and image detail. Our approach offers the user a great deal of flexibility over the end result, while at the same time requiring very little input. This input takes the form of a few simple and discrete choices. The results demonstrate an impressive array of transformational possibilities.
Investigation of Frame Alignments for GMM-based Text-prompted Speaker Verification

The frame alignment acts as an important role in GMM-based speaker verification. In text-prompted speaker verification, it is common practice to use the transcriptions to align speech frames to phonetic units. In this paper, we compare the performance of alignments from hidden Markov model (HMM) and deep neural network (DNN), using the same training data and phonetic units. We incorporate a phonetic Gaussian mixture model (PGMM) in the DNN-based alignment, making the total number of Gaussian mixtures equal to that of the HMM. Based on the Kullback-Leibler divergence (KLD) between the HMM and DNN alignments, we also present a fast and efficient way to verify the text content. Our experiments on RSR2015 Part-3 show that, even with a small training set, the DNN-based alignment outperforms HMM alignment. Results also show that it is not effective to utilize the DNN posteriors in the HMM system. This phenomenon illustrates that under clean conditions (e.g., RSR2015), text-prompted speaker verification does not benefit from the use of transcriptions. However, the prompted text can be used as pass-phrase to enhance the security. The content verification experiment demonstrates the effectiveness of our proposed KLD-based method.
Local Descriptors Optimized for Average Precision Supplementary Material A . Learning Real-Valued Descriptors

We use the Spatial Transformer module in our networks to handle geometric noise and align input patches. As is standard practice, the Spatial Transformer is initialized to output identity (directly copy input patches), and the learning rate of the affine transformation prediction layer is scaled down by 100x compared to other layers in the network. A naı̈ve application of the Spatial Transformer, however, leads to the boundary effect [7]: when the predicted transformation requires sampling outside the boundaries of the input, the default zero-padding creates unfilled boundaries in the output. Since the input patches to the Spatial Transformer have limited size (42x42 in our network), out-of-boundary sampling frequently happens in operations such as zooming out and rotation, and can affect alignment by introducing unwanted image gradients. Instead, we first pad the input patch by repeating its boundary pixels,1 and then sample according to the predicted transformation, which prevents sharp gradients near boundaries. This is visually illustrate in Fig. 1, using patches from the challenging HPatches dataset, which has the largest amount of geometric noise among the datasets that we consider. Although using zero padding still produces decent alignment, it affects the appearance of sampled patches, and does not help to improve final performance. Our boundary padding produces much more visually plausible patches, and gives a good approximation to re-sampling from the original images.
Polish Palaeobotany: 750 Million Years of Plant History as Revealed in a Century of Studies. Mesozoic Macroflora

Research on Polish Mesozoic macroflora has remarkably changed over the last 100 years. Compared with traditional nineteenth-century taxonomical and evolutionary studies, modern research also investigates of fossil plant diversity, plant interactions with the environment and animals, and deep changes in vegetation influenced by environmental and climate change. In this review, we present the most important turning points in Polish Mesozoic macroflora research and the development of cognitive techniques by discussing selected studies carried out by Polish palaeobotanists.
Study of model evaluation method and of selection method of tuning parameter in Lasso

High-dimensional data sets have been used extensively in recent years. However, their use is computationally expensive, and model features are difficult to capture. Thus, it is necessary to construct a simple and appropriate model. The least absolute shrinkage and selection operator (Lasso) can estimate several regression coefficients as exactly zero, making it possible to estimate a model and select variables at the same time. However, several problems exist. The decision procedure for the tuning parameter, which is the coefficient of the penalty term, is not established, and it is difficult to determine the value of the estimated model. In this paper, we consider a model evaluation method and a selection method for the tuning parameter. We investigate selection methods for the most appropriate tuning parameter and model evaluation methods using the model evaluation indexes RSS, AIC, BIC, and Mallows’s Cp. Let several regression coefficients be zero and vary the number of zeroes. Then, we observe the performances of the evaluation indexes. Furthermore, we observe their performances when the values of the regression coefficients are close to zero and confirm them by simulation.
Peculiarity of Taylor’s and Wavy Vortices Beginning, Generated by a Rotating Magnetic Field

Stationary instability of axisymmetric laminar flow of a viscous conducting liquid in the infinitely long circular cylinder, arising under the influence of coaxially rotating magnetic field (RMF) of any rotary symmetry, has been investigated. The nearest analogue of the conducting liquid flow raised by the rotating magnetic field is Couette flow between two concentric cylinders from which internal one rotates and external remains motionless. While analyzing stability of such flow, Lin [7] has noticed, that the first approximation equations for small perturbations of velocity and pressure allow for periodic solution with respect to φ and : z
ORAL HEALTH AND DIABETES

Dr. Wenche S. Borgnakke is Senior Research Associate in the Department of Periodontics and Oral Medicine, School of Dentistry, University of Michigan, Ann Arbor, MI. Dr. Robert J. Genco is Distinguished Professor of Oral Biology, Microbiology and Immunology, and Director, UB Center for Microbiome Research, State University of New York at Buffalo, Buffalo, NY. Dr. Paul I. Eke is Senior Health Scientist, Office of the Director, Division of Population Health, National Center for Chronic Disease and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA. Dr. George W. Taylor is Professor in the Department of Preventive and Restorative Dental Sciences, Division of Oral Epidemiology and Dental Public Health, and Associate Dean for Diversity and Inclusion at the School of Dentistry, University of California San Francisco, San Francisco, CA.