Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetic Resonance Spectroscopy Findings in Perro de Presa Canario Dogs with Spongy Degeneration of the Central Nervous System

2-Month-old, three related Perro de Presa Canario dogs were evaluated for similar neurological symptoms like circling, head pressing, depressed mental status, hypermetria, and vocalization. On magnetic resonance imaging (MRI) of the brain, there were large, bilaterally symmetrical lesions with involvement of thalamus, and brainstem that were T2and FLAIR-hyperintense and T1-iso/hypointense. There was no inclusion of cerebellum. Single-voxel spectroscopy acquisition was located in the thalamus where abnormalities were found in MR images. The results of magnetic resonance spectroscopy (MRS) showed markedly decreased N-acetylaspartic acid value. Euthanasia was performed and lesions consistent with the canine spongy degeneration. Alteration in metabolites in the brain can be determined by MRS, which helps in diagnosing degeneration/leukodystrophy of the central nervous system in dogs.
DNA may store information with base pair and communicate by UV

In this paper,UV is suggested to be the medium of the information transmission in DNA. DNA bases can certainly absorb UV. They also have a typical structure to emit UV. And the stacking way of base pairs in DNA can accelerate the luminescence efficiency. Electrical signaling information from UV could be stored in base pair, in ways such as change of π conjugated electrons. The evaluation and calculation of information in DNA may base on quantum effect of π conjugated electrons and photon entangling. A hypothesis about origin of this UV communication and origin of life is also proposed here, which involve in the irradiation of the circular polarization light and self-organization of aromatic N-heterocycles.The hypotheses can explain some biological phenomena.
LEARNING OBSTACLE BEHAVIOR FOR IMPROVED THREAT MAPPING DURING NAVIGATION

A novel obstacle evaluation system for the visually impaired is proposed and evaluated in this thesis. This system assesses the threat in the environment posed by various kinds of stationary and moving obstacles. It evaluates the behaviors of different classes of obstacles and learns features based on their collision avoidance strategies. For the purpose of crowd simulation, Reciprocal Collision Avoidance strategy has been used here. This idea can further be generalized to any multi-agent environment and can serve as the building block for new obstacle avoidance algorithms. Primary Reader : Dr Austin Reiter
The GEOMON network of Czech catchments provides long‐term insights into altered forest biogeochemistry: From acid atmospheric deposition to climate change

In 1994, a network of small catchments (GEOMON) was established in the Czech Republic to determine input–output element fluxes in semi‐natural forest ecosystems recovering from anthropogenic acidification. The network consists from 16 catchments and the primary observations of elements fluxes were complemented by monitoring of biomass stock, element pools in soil and vegetation, and the main water balance components. Over last three decades, reductions of SO2, NOx and NH3 emissions were followed by sulphur (S) and nitrogen (N) deposition reductions of 75% and 30%, respectively. Steeper declines of strong acid anion concentrations compared to cations (Ca, Mg, Na, K, NH4) in precipitation resulted in precipitation pH increase from 4.5 to 5.2 in bulk precipitation and from 4.0 to 5.1 in spruce throughfall. Stream chemistry responded to changes in deposition: S leaching declined. However at majority of catchments soils acted as a net source of S to runoff, delaying recovery. Stream pH increased at acidic streams (pH < 6) and aluminium concentration decreased. Stream nitrate (NO3) concentration declined by 60%, considerably more than N deposition. Stream NO3 concentration was tightly positively related to stream total dissolved nitrogen to total phosphorus (P) ratio, suggesting the role of P availability on N retention. Trends in dissolved organic carbon fluxes responded to both acidification recovery and to runoff temporal variation. An exceptional drought occurred between 2014 and 2019. Over this recent period, streamflow decreased by ≈ 40% on average compared to 1990s, due to the increases of soil evaporation and vegetation transpiration by ≈ 30% and declines in precipitation by ≈ 15% on average across the elevational gradient. Sharp decreases of stream runoff at catchments <650 m a.s. l. corresponded to areas of recent forest decline caused by bark beetle infestation on drought stressed spruce forests. Understanding of the interactions among legacies of acidification and eutrophication, drought effects on the water cycle and forest disturbance dynamics is requisite for effective management of forested ecosystems under anthropogenic influence.
LHCb RICH collaboration

The LHCb experiment has been taking data at the Large Hadron Collider (LHC) at CERN since the end of 2009. One of its key detector components is the Ring-Imaging Cherenkov (RICH) system. This provides charged particle identification over a wide momentum range, from 2–100 GeV/c. The operation and control, software, and online monitoring of the RICH system are described. The particle identification performance is presented, as measured using data from the LHC. Excellent separation of hadronic particle types (π, K, p) is achieved. (To be submitted to EPJC) Authors are listed on the following pages. LHCb RICH collaboration M. Adinolfi, G. Aglieri Rinella, E. Albrecht, T. Bellunato, S. Benson, T. Blake, C. Blanks, S. Brisbane, N.H. Brook, M. Calvi, B. Cameron, R. Cardinale, L. Carson, A. Contu, M. Coombes, C. D’Ambrosio, S. Easo, U. Egede, S. Eisenhardt, E. Fanchini, C. Fitzpatrick, F. Fontanelli, R. Forty, C. Frei, P. Gandini, R. Gao, J. Garra Tico, A. Giachero, V. Gibson, C. Gotti, S. Gregson, T. Gys, S.C. Haines, T. Hampson, N. Harnew, D. Hill, P. Hunt, M. John, C.R. Jones, D. Johnson, N. Kanaya, S. Katvars, U. Kerzel, Y.M. Kim, S. Koblitz, M. Kucharczyk, D. Lambert, R.W. Lambert , A. Main, M. Maino, S. Malde, N. Mangiafave, C. Matteuzzi, G. Mini’, A. Mollen, J. Morant, R. Mountain, J.V. Morris, F. Muheim, R. Muresan, J. Nardulli, P. Owen, A. Papanestis, M. Patel, G.N. Patrick, D.L. Perego, G. Pessina, A. Petrolini, D. Piedigrossi, R. Plackett , S. Playfer, A. Powell, J.H. Rademacker, S. Ricciardi, G.J. Rogers, P. Sail, M. Sannino, T. Savidge, I. Sepp, S. Sigurdsson, F.J.P. Soler, A. Solomin, F. Soomro, A. Sparkes, P. Spradlin, B. Storaci, C. Thomas, S. Topp-Joergensen, N. Torr, O. Ullaland, K. Vervink, D. Voong, D. Websdale, G. Wilkinson, S.A. Wotton, K. Wyllie, F. Xing, R. Young. Sezione INFN di Genova, Genova, Italy Sezione INFN di Milano Bicocca, Milano, Italy European Organization for Nuclear Research (CERN), Geneva, Switzerland H.H. Wills Physics Laboratory, University of Bristol, Bristol, United Kingdom Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom STFC Rutherford Appleton Laboratory, Didcot, United Kingdom School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom Imperial College London, London, United Kingdom Department of Physics, University of Oxford, Oxford, United Kingdom Syracuse University, Syracuse, NY, United states of America Università di Genova, Genova, Italy Università di Milano Bicocca, Milano, Italy Now at Physik-Institut, Universität Zürich, Zürich, Switzerland Now at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest-Magurele, Romania Now at Sezione INFN di Cagliari, Cagliari, Italy Now at Nikhef National Institute for Subatomic Physics and VU University Amsterdam, Amsterdam, The Netherlands
Monetary Convergence of the EU Candidates to the Euro: A Theoretical Framework and Policy Implications

A flexible approach to direct inflation targeting is a viable monetary policy choice for transition economies that is believed to facilitate both the economic transition and the monetary convergence to the euro. Following this assumption, an analytical model investigating the link between the inflation process and monetary variables in transition economies is advanced in this study. The empirical testing is conducted for Poland, the Czech Republic and Hungary. The analysis recommends that the monetary convergence begins with inflation targeting and concludes with a full-fledged euroization. It further advocates the application of flexible benchmarks of monetary convergence that would accommodate various non-monetary factors affecting inflation in transition economies.
Sialic Acid Derivative Synthesis and Inhibitory Activities Against Human Parainfluenza Virus Type 1

Sialic acids (Neu5Ac, 1) are involved in many biological functions of glycoproteins, glycolipids, and cells. Sialidases are a family of glycosidases that catalyze the removal of α-glycosidically linked sialic acid residues from carbohydrate groups of glycoconjugates. Among the compounds related to the sialic acid family, 2-deoxy-2,3dehydro-N-acetylneuraminic acids (Neu5Ac2en, 2) are known to inhibit sialidases. Human parainfluenza viruses are important respiratory tract pathogens, particularly in children. However, no vaccines or specific therapies for infections caused by these viruses are currently available. This article reviews our progress and current trends of the modification of 2-deoxy-2,3-didehydro sialic acid analogs and biological evaluations of their inhibitory activities against human parainfluenza virus type 1 (hPIV-1) sialidases. A. Introduction Sialic acids, such as N-acetylneuraminic acid (Neu5Ac), N-glycolylneuraminic acid (Neu5Gc), and deaminoneuraminic acid (KDN), are often located at the non-reducing end of glycoconjugates on the cell surface, and play pivotal roles in many cell-surface recognition processes, cell adhesion, and viral receptor recognition (1). The most abundant sialic acid is Neu5Ac (5-acetamido-3,5-dideoxy-D-glycero-D-galactononulosonic acid, 1a) (Fig. 1). Modification of the functional groups on the sialic acid skeleton leads to changes in steric and/or electronic properties of the molecule, which can be used to probe space and charge requirements of sialic acidhPIV-1 シアリダーゼ阻害活性をもつシアル酸誘導体の合成 要 約 シアル酸 (Neu5Ac, 1) は糖タンパク質、糖脂質、細胞に おいて多くの生物学的機能に関わっていることが知られてい る。 シアリダーゼは糖鎖からα グリコシド結合したシアル 酸残基を除去するグリコシダーゼである。 シアル酸関連化合 物の中で、2デオキシ -2,3デヒドロ -N アセチルノイラミン 酸 (Neu5Ac2en, 2) はシアリダーゼ阻害剤として知られている。 ヒューマンパラインフルエンザウイルス (human parainfluenza viruses) (hPIVs) は特に、子供に重篤な呼吸器疾患を引き起こ す。 しかし、現在、これらのウイルスによる感染症に対して ワクチンや有効な治療法はない。 この総説では Neu5Ac2en 誘 導体合成に関する我々の研究と最近の動向、さらにヒューマ ンパラインフルエンザウイルス タイプ 1型 (hPIV-1) シアリ ダーゼに対する阻害活性について紹介する。 A. はじめに シアル酸は、たとえば Neu5Ac、Neu5Gc、KDN として、 細胞表面上の糖鎖の非還元末端にあり、多くの細胞表面の認 識、細胞接着およびウイルスのレセプター認識 (1) で重要な役 割を担っている。 もっとも多く存在するシアル酸は N アセチ ルノイラミン酸 (Neu5Ac, 1a) である ( 図 1) 。 シアル酸骨格上 の官能基の化学修飾により、分子の立体的、電子的な特性に 変化を与え、それによりシアル酸を認識するタンパク質のリ ガンド認識部位の空間の広がりや、必要とされる電荷を調べ ることができる (2)。
Title Learning to translate in real-time with neural machine translation

Translating in real-time, a.k. a. simultaneous translation, outputs translation words before the input sentence ends, which is a challenging problem for conventional machine translation methods. We propose a neural machine translation (NMT) framework for simultaneous translation in which an agent learns to make decisions on when to translate from the interaction with a pre-trained NMT environment. To trade off quality and delay, we extensively explore various targets for delay and design a method for beam-search applicable in the simultaneous MT setting. Experiments against state-of-the-art baselines on two language pairs demonstrate the efficacy of the proposed framework both quantitatively and qualitatively.1
Gamma Distribution IV . Classification Of Denoising Methodology

A fundamental step in image processing is the step of removing various kinds of noise from the image. Sources of noise in an image mostly occur during storage, transmission and acquisition of the image . Image denoising is a applicable issue found in diverse image processing and computer vision problems. There are various existing methods to denoise image. The important property of a good image denoising model is that it should completely remove noise as far as possible as well as preserve edges. The image denosing technique will be mainly depending on the type of the image and noise in cooperating with it. There have been several published algorithms and each approach has its assumptions, advantages, and limitations. This paper presents a review of some noise models and significant work in the area of image denoising.
Noisy candidates and informative politicians: analyzing changes in tweet behavior using tweet quality assessment framework

Politicians use Twitter as a strategic tool for campaigning and posting messages once elected. Our work focuses on the ways U.S. state governors’ use twitter differently when they were campaigning vs. after they have taken office. Our data consists of tweets posted by wining gubernatorial candidates during and six months after the 2014 elections. Using regression analysis, we find that post-election tweet volume is related to factors such as pre-election tweet volume, incumbency status, and if they were a third party candidate. We also develop and utilize a novel Tweet Quality Assessment Framework (TQAF) to show that during elections politicians try to engage topically with their audience more than once elected, but tend to produce higher quality information once in office. Our work contributes to the understanding of politician’s use of Twitter. We also believe our TQAF will be useful for researchers wishing to compare differences in tweet behavior across time or groups.
Identification of TACC 1 , NOV , and PTTG 1 as new candidate genes associated with endocrine therapy resistance in breast cancer

Cross-resistance to molecules used in endocrine therapy is among the main challenges in the treatment of estrogen receptor-a (ERa) positive breast cancer. In this study, we used two different cell models of resistance to anti-estrogens: MVLN/CL6.7 cells and VP229/VP267 cells selected after exposure to tamoxifen respectively in vitro and in vivo to characterize a phenotype rarely observed, i.e. acquisition of cross-resistance to the pure ER antagonist fulvestrant. As MVLN/CL6.7 cells and VP229/VP267 cell lines are original and valuable models of cross-resistance to tamoxifen and fulvestrant, we examined candidate genes using a RTQ-PCR strategy to identify new biomarkers of endocrine resistance. Out of the 26 candidate genes tested, 19 displayed deregulation of expression at the basal level in at least one of the two resistant cell lines. Eight genes (TACC1, NOV, PTTG1, MAD2L1, BAK1, TGFB2, BIRC5, and CCNE2) were significantly overexpressed in samples from ER-positive breast cancer patients who relapsed after tamoxifen treatment (nZ24) compared with samples from patients who did not (nZ24). Five genes (TACC1, NOV, PTTG1, BAK1, and TGFB2) were correlated with significantly shorter relapse-free survival (univariate analysis). Finally, we identified TACC1 and a three-gene expression signature (TACC1, NOV, and PTTG1) as independent prognostic markers (multivariate analysis). Aberrant mRNA and protein levels of TACC1, NOV, and PTTG1 were also observed under tamoxifen and/or fulvestrant exposure in resistant CL6.7 cells compared with their respective control MVLN cells. In conclusion, our data identify TACC1, NOV, and PTTG1 as promising new markers that could be used in the clinical management of ER-positive breast cancer patients. Journal of Molecular Endocrinology (2009) 42, 87–103
Optimal powertrain control of a series hybrid electric vehicle using Pontryagin ’ s Minimum Principle

in the current study, a model-based controller for off-line optimization of fuel consumption of a Hybrid Electric Vehicle (HEV) is presented. To find the optimal controller, first a simple mathematical model for a series HEV is formulated. The objective is defined using the simple model and implementation of Pontryagin’s Minimum Principle. To solve the optimal control problem numerically, two different methods (Shooting Method and Steepest Descent Method) are used, and the results are presented and compared. It turned out that the steepest descent method is more appropriate for this application.
PREDICTIVE PROVISIONING OF WORKLOADS FOR DYNAMIC APPLICATION SCALING IN CLOUD ENVIRONMENTS

The large scale emergence of cloud platforms induce the tendency to virtualize application workloads that traditionally ran on physical machines. At the same time, cloud providers advertise unlimited resources available to the customers at any time for a fixed price. These factors create the opportunity for customers to easily scale up and down the infrastructure depending on the real time requirements, reducing the overall costs for providing the service. Cloud platforms today provide a threshold trigger mechanism that can trigger provisioning or deprovisioning of additional resources.This paper argues that the threshold approach is not enough for some real life application scaling requirements and introduces a predictive mechanism that allows accurate and proactive provisioning of workloads. The prediction algorithm is based on the observation that for some applications a usage pattern exists, and this usage pattern is repetitive. This paper presents the usage pattern identified in a large scale travel booking application and the execution of the algorithm on this data. The algorithm tested using IBM CloudBurst 2.1 deployment using a benchmark application and results are discussed.
Coping Strategies of Senior High School Graduating Students with Academic Tasks

Everybody has a struggle in life and manifest his way of handling stress. Stress may be physical, emotional, and mental stress, this research design used is descriptive correlation. The researchers conducted the survey among the students in the Senior High School. With 104 respondents and by complete enumeration, GAS 12 males are 11 while females are 27; ABM 12 males are 3 while females are 32; HUMSS 12 males are 11 while females are 20. Quantitative data were processed by using Chi-square with yates correction. The result would show the correlation between rhe perceived level of stress in terms of physical, emotional, and mental. Generally, students are expected to have an appropriate coping mechanism to their perceived level of stress physical, emotional, and mental. Students may used positive or negative coping strategies. Teachers may help them in coping their stress.
Development of an Elastic Material Model for BCC Lattice Cell Structures Using Finite Element Analysis and Neural Networks Approaches

Lattice cell structures (LCS) are being investigated for applications in sandwich composites. To obtain an optimized design, finite element analysis (FEA) -based computational approach can be used for detailed analyses of such structures, sometime at full scale. However, developing a large-scale model for a lattice-based structure is computationally expensive. If an equivalent solid FEA model can be developed using the equivalent solid mechanical properties of a lattice structure, the computational time will be greatly reduced. The main idea of this research is to develop a material model which is equivalent to the mechanical response of a lattice structure. In this study, the mechanical behavior of a body centered cubic (BCC) configuration under compression and within elastic limit is considered. First, the FEA approach and theoretical calculations are used on a single unit cell BCC for several cases (different strut diameters and cell sizes) to predict equivalent solid properties. The results are then used to develop a neural network (NN) model so that the equivalent solid properties of a BCC lattice of any configuration can be predicted. The input data of NN are bulk material properties and output data are equivalent solid mechanical properties. Two separate FEA models are then developed for samples under compression: one with 5 × 5 × 4 cell BCC and one completely solid with equivalent solid properties obtained from NN. In addition, 5 × 5 × 4 cell BCC LCS specimens are fabricated on a Fused Deposition Modeling uPrint SEplus 3D printer using Acrylonitrile Butadiene Styrene (ABS) and tested under compression. Experimental load-displacement behavior and the results obtained from both the FEA models are in good agreement within the elastic limit.
Probing compressed top squark scenarios at the LHC at 14 TeV

A feasibility study is presented for the search of the lightest top squark in a compressed scenario, where its mass is approximately equal to the sum of the masses of the top quark and the lightest neutralino. The study is performed in the final state of two b-jets, one lepton, large missing energy, and two high-$E_{\rm T}$ jets with large separation in pseudo-rapidity, in opposite hemispheres, and with large dijet mass. The LHC could discover compressed top squarks with mass up to approximately 340 GeV (390 GeV) with an integrated luminosity of 1000 ifb (3000 ifb).
Development of Integrated Portable Device and Mobile Apps for Homecare System: Body Temperature and Respiration Rate

A Homecare system is a system that collects patient’ vital signs and health information. Vital signs abnormalities appear several hours before the patient health quality decrease. Therefore, the home care system can be applied to prevent chronic diseases. It is estimated that 25% of chronic disease patients can be prevented by checking vital signs regularly. In this research, an Android-based portable product development that integrates measurements of body temperature and respiration rate is developed. Body temperature will be detected by an infrared temperature sensor. A thermistor will be used to calculate the respiration rate. A thermistor is a resistor whose resistance is dependent on temperature. The accuracy achieved by body temperature measurement is 84% with ±1.37% precision. The accuracy achieved by the respiration rate measurement is 98% with ±3.98% precision. The two gauges are integrated into the microcomputer with a serial communication channel. And then, the measurement results that have been processed on the microcomputer are sent to Android using Bluetooth. Measurement results can be displayed and saved on the Android application. Product portability parameters are measured by weight, size, durability, and power supply. The power supply for this system uses a power bank where the measuring system can be turned on for 3 hours. This research can be applied to a homecare system that collects patients’ vital signs and health information.
Fetomaternal Outcome in Hypertensive disorders Complicationg Pregnancy-an Analysis

1 DNB senior Resident Department of Obstetrics and Gynaecology, North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences Shillong, Meghalaya, India 2,3 Assistant Professor, Department of Obstetrics and Gynaecology, North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences Shillong, Meghalaya, India 4 Associate Professor in department of Paediatric, North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences Shillong, Meghalaya, India 5 DNB Professor and Head Department of Obstetrics and Gynaecology, North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya, India