Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration and verification testing of the Large Synoptic Survey Telescope camera

We present an overview of the Integration and Verification Testing activities of the Large Synoptic Survey Telescope (LSST) Camera at the SLAC National Accelerator Lab (SLAC). The LSST Camera, the sole instrument for LSST and under construction now, is comprised of a 3.2 Giga-pixel imager and a three element corrector with a 3.5 degree diameter field of view. LSST Camera Integration and Test will be taking place over the next four years, with final delivery to the LSST observatory anticipated in early 2020. We outline the planning for Integration and Test, describe some of the key verification hardware systems being developed, and identify some of the more complicated assembly/integration activities. Specific details of integration and verification hardware systems will be discussed, highlighting some of the technical challenges anticipated.
Collapse Surfaces Of The Octet-Truss Lattice At Different Lattice Angles

Cellular materials are found extensively in nature such as wood, honeycomb, butterfly wings and foam-like structures like trabecular bone and sponge. This class of materials proves to be structurally-efficient by combining low weight with superior mechanical properties. Recent studies have shown there are coupling relations between the mechanical properties of cellular materials and their relative density. Due to its favorable stretching‐dominated behavior, continuum models of the octet‐truss were developed to describe its effective mechanical properties. However, previous studies were only performed for the cubic symmetry case where the lattice angle θ = 45°. In this work, we study the impact of the lattice angle on the effective strength of the octet-truss. A graphical method is utilized to plot the collapse surfaces for plastic yielding and elastic buckling for different loading combinations at different lattice angles. Generally, the (σxz , σzz) loading space is preferable for lattice angles greater than 45°, while the (σxx , σyy) loading space is preferable for lattice angles lower than 45°.
Comparative genomics of flowering behavior in Cannabis sativa

Cannabis sativa L. is a phenotypically diverse and multi-use plant used in the production of fiber, seed, oils, and a class of specialized metabolites known as phytocannabinoids. The last decade has seen a rapid increase in the licit cultivation and processing of C. sativa for medical end-use. Medical morphotypes produce highly branched compact inflorescences which support a high density of glandular trichomes, specialized epidermal hair-like structures that are the site of phytocannabinoid biosynthesis and accumulation. While there is a focus on the regulation of phytocannabinoid pathways, the genetic determinants that govern flowering time and inflorescence structure in C. sativa are less well-defined but equally important. Understanding the molecular mechanisms that underly flowering behavior is key to maximizing phytocannabinoid production. The genetic basis of flowering regulation in C. sativa has been examined using genome-wide association studies, quantitative trait loci mapping and selection analysis, although the lack of a consistent reference genome has confounded attempts to directly compare candidate loci. Here we review the existing knowledge of flowering time control in C. sativa, and, using a common reference genome, we generate an integrated map. The co-location of known and putative flowering time loci within this resource will be essential to improve the understanding of C. sativa phenology.
The Diffeomorphism Field

Integration of Kirillov form on a coadjoint orbit of Virasoro algebra yields the coupling of a background field to Polyakov's two dimensional quantum gravity. This background field is used to be called the diffeomorphism field. Einstein's gravity is dynamically trivial in two dimensions. Moreover, the diffeomorphism field can be interpreted as the gravitational analog of a Yang-Mills field. This raises the question of whether the diffeomorphism field exists in higher dimensions, and plays an essential role in gravity. With this motivation, several dynamical theories for the diffeomorphism field have been constructed by mimicking construction of Yang-Mills theory from Kac-Moody algebra. This thesis constitutes a further development for obtaining a consistent dynamical theory of the diffeomorphism field. The previously proposed theories are thoroughly examined, certain subtleties and problems in them have been discovered and made apparent. Some of these problems have been solved, and for others possible routes to follow have been laid down. Finally, alternative geometric approaches are investigated.
Design of linear quadratic regulator (LQR) control system for flight stability of LSU-05

Lapan Surveillance UAV-05 (LSU-05) is an unmanned aerial vehicle designed to cruise time in 6 hours and cruise velocity about 30 m/s. Mission of LSU-05 is surveillance for researchs and observations such as traffics and disaster investigations. This paper aims to design a control system on the LSU-05 to fly steadily. The methods used to stabilize LSU-05 is Linear Quadratic Regulator (LQR). Based on LQR controller, there is obtained transient response for longitudinal motion, td = 0.221s, tr = 0.419s, ts = 0.719s, tp = 1.359s, and Mp = 0%. In other hand, transient response for lateral-directional motion showed that td = 0.186s, tr = 0.515s, ts = 0.87s, tp = 2.02s, and Mp = 0%. The result of simulation showed a good performance for this method.
Chirped pulse amplification in an all-normal-dispersion erbium-doped fiber amplifier

Chirped pulse amplification in an all-normal-dispersion erbium-doped fiber amplifier is presented. Wavelength dependent amplification is examined. It is found that gain dispersion limits the spectral profile of the amplified pulse. If the central wavelength of the seed pulse is far away from that of the gain profile of the amplifier, the gain profile partially shapes the spectrum of the amplified pulse while maintaining the characteristic steep spectral edge at one side. If the optical spectrum of the seed pulse is most covered by the gain profile, the characteristic steep spectral edges will be both maintained. The amplified pulse becomes deformed ultimately with increasing pump power, no matter whether the seed pulse is a transform-limited pulse or a chirped pulse.
A brief report on health disparities between people with depression and people without depression in the United States

ABSTRACT This research aims to illuminate health disparities between people with depression and those without. A sample of 27,164 people without depression and 3,797 people with self-reported depression were selected from the 2013 BRFSS. The results indicate that people with depression have higher odds of having chronic diseases and smoking but lower odds of eating fruits. Despite a higher insured rate of people with depression, more of them experienced financial barriers to health care due to the cost. People with depression had a higher odds of having health insurance, having a healthcare provider, and experiencing financial barriers to healthcare
Fabrication and Validation of a 3D Portable PEGDA Microfluidic Chip for Visual Colorimetric Detection of Captured Breast Cancer Cells

To guide therapeutic strategies and to monitor the state changes in the disease, a low-cost, portable, and easily fabricated microfluidic-chip-integrated three-dimensional (3D) microchamber was designed for capturing and analyzing breast cancer cells. Optimally, a colorimetric sensor array was integrated into a microfluidic chip to discriminate the metabolites of the cells. The ultraviolet polymerization characteristic of poly(ethylene glycol) diacrylate (PEGDA) hydrogel was utilized to rapidly fabricate a three-layer hydrogel microfluidic chip with the designed structure under noninvasive 365 nm laser irradiation. 2-Hydroxyethyl methacrylate (HEMA) was added to the prepolymer in order to increase the adhesive capacity of the microchip’s surface for capturing cells. 1-Vinyl-2-pyrrolidone (NVP) was designed to improve the toughness and reduce the swelling capacity of the hydrogel composite. A non-toxic 3D hydrogel microarray chip (60 mm × 20 mm × 3 mm) with low immunogenicity and high hydrophilicity was created to simulate the real physiological microenvironment of breast tissue. The crisscross channels were designed to ensure homogeneous seeding density. This hydrogel material displayed excellent biocompatibility and tunable physical properties compared with traditional microfluidic chip materials and can be directly processed to obtain the most desirable microstructure. The feasibility of using a PEGDA hydrogel microfluidic chip for the real-time online detection of breast cancer cells’ metabolism was confirmed using a specifically designed colorimetric sensor array with 16 kinds of porphyrin, porphyrin derivatives, and indicator dyes. The results of the principal component analysis (PCA), the hierarchical cluster analysis (HCA), and the linear discriminant analysis (LDA) suggest that the metabolic liquids of different breast cells can be easily distinguished with the developed PEGDA hydrogel microfluidic chip. The PEGDA hydrogel microfluidic chip has potential practicable applicability in distinguishing normal and cancerous breast cells.
Stock market prediction based on deep hybrid RNN model and sentiment analysis

Stock market movements, stocks, and exchange rates are the primary subjects and active areas of research for analysts and researchers. The stock prices is being influenced by financial news, which has been demonstrated to be an important element in fluctuating stock prices. Furthermore, previous research mostly evaluated shallow characteristics and ignored functional relationships between words in a sentence. Many studies have attempted to analyse the sentiment of investors’ reactions to corresponding news occurrences. In this paper, we proposed a unique methodology for predicting the stock prices trend by using both stock features and financial news. The proposed methodology is the hybrid Recurrent Neural-Network (HyRNN) architecture. This design includes Bidirectional Long Short-Term Memory (Bi-LSTM) on top of the Gated Recurrent Unit (GRU) and stacked Long Short-Term Memory (sLSTM). The performance of HyRNN for forecasting stock price can be considerably improved by mixing the sentiments of financial news with the features of stock as an input to the model. In comparison to earlier statistical models, the suggested model increases the analysing capability of GRU, LSTM, RNN, and proposed models independently. The findings of this study shows the deep learning (DL) approach has high potential for predicting stock price changes.
The Zire experiment on board the NUSES space mission

The Zirè experiment is part of the NUSES (NeUtrino and Seismic Electromagnetic Signals) space mission, proposed by the Gran Sasso Science Institute (GSSI) in collaboration with the Istituto Nazionale di Fisica Nucleare (INFN) and by Thales Alenia Space Italy (TAS-I), involving many Institutes and Universities from Europe and abroad. Zirè will perform measurements of electrons, protons and light nuclei from few up to hundreds of MeVs, for the study of low energy CRs, space weather phenomena and possible Magnetosphere-Litosphere-Ionosphere Coupling (MILC) signals. A further goal of the experiment is to test new tools for the detection of photons in the energy range 0.1 MeV - 50 MeV, allowing the investigation of transient phenomena and steady gamma sources. Zirè will also test an innovative feature for space-based particle detectors, exploiting a full Silicon Photo Multiplier (SiPM) technology for the readout system. In this work, a general overview of the design activities, together with the scientific goals and the development status of the Zirè payload will be presented.
Agroclimatic and Phytosanitary Events and Emerging Technologies for Their Identification in Avocado Crops: A Systematic Literature Review

Avocado is one of the most commercialized and profitable fruits in the international market. Its cultivation and production are centered in countries characterized by tropical and subtropical climatic conditions, many of them with emerging economies. Moreover, the use of technology is key to agricultural production improvement strategies. Using avocado crop data to forecast the potential impacts of biotic and abiotic factors, combined with smart farming technologies, growers can apply measures during a single production phase to reduce the risks caused by pests and weather variations. Therefore, this paper aims to distinguish the most relevant variables related to agroclimatic and phytosanitary events in avocado crops, their incidence on production and risk management, as well as the emerging technologies used for the identification and analysis of pests and diseases in avocados. A scientific literature search was performed, and the first search found 608 studies, and once the screening process was applied, 37 papers were included in this review. In the results, three research questions were answered that described the pests and diseases with high impact on avocado production, along with the data sources and the principal enabling technologies used in the identification of agroclimatic and phytosanitary events in avocados. Some challenges and trends in the parameterization of the technology in field conditions for data collection are also highlighted.
Design and evaluation of a freeform lens by using a method of luminous intensity mapping and a differential equation

Freeform optical systems are playing an important role in the field of illumination engineering for redistributing the light intensity, because of its capability of achieving accurate and efficient results. The authors have presented the basic idea of the freeform lens design method at the 117th annual meeting of the German Society of Applied Optics (DGAOProceedings). Now, we demonstrate the feasibility of the design method by designing and evaluating a freeform lens. The concepts of luminous intensity mapping, energy conservation and differential equation are combined in designing a lens for non-imaging applications. The required procedures to design a lens including the simulations are explained in detail. The optical performance is investigated by using a numerical simulation of optical ray tracing. For evaluation, the results are compared with another recently published design method, showing the accurate performance of the proposed method using a reduced number of mapping angles. As a part of the tolerance analyses of the fabrication processes, the influence of the light source misalignments (translation and orientation) on the beam-shaping performance is presented. Finally, the importance of considering the extended light source while designing a freeform lens using the proposed method is discussed.
Infinitely many solutions for a class of quasilinear Schrödinger equations involving sign-changing weight functions

ABSTRACT Using a change of variables and the constrained critical point theory, we first prove the existence and multiplicity of solutions for a class of quasilinear Schrödinger equations. Next, we consider a quasilinear equation related to the superfluid film in plasma physics with a sign-changing weight function. Using a new natural constraint, we establish the existence of infinitely many solutions for the equation.
A machine learning-oriented pseudo-field approach to accelerate runtime of molecular dynamics simulation of liquids

ABSTRACT Machine learning methods are increasingly used in research to save time and computational expenses. The data-driven approach relies on existing data for predictions based on statistical inference and interpolation. Liquids, in particular, benefit from machine learning due to their higher computational requirements. In this study, we propose a simple data-driven strategy that employs classical molecular dynamics simulations to generate potential energy spatial distribution data. This data is then used to train a machine learning model by using topologically similar scaled-down systems. The trained model is subsequently employed to predict force field behaviour for complex full-scale systems, resulting in time and computational cost savings. During training, the potential energy pseudo field serves as a model descriptor, while the final predictions are generated using multidimensional regression-based learning (Gaussian Process) and neural architecture learning (Artificial Neural Network), which are integrated into the simulation as lookup tables. Comparing the data-driven and conventional approaches reveals a significant acceleration in overall simulation runtime when appropriately trained machine learning models are utilised. Although the initial training phase of the machine learning models is time-consuming, retraining is unnecessary for future simulations with the same setup. Thus, this approach offers a straightforward means of conducting complex simulations in less time.
Distributed adaptive fault‐tolerant leader‐following formation control of nonlinear uncertain second‐order multi‐agent systems

This paper presents a distributed integrated fault diagnosis and accommodation scheme for leader‐following formation control of a class of nonlinear uncertain second‐order multi‐agent systems. The fault model under consideration includes both process and actuator faults, which may evolve abruptly or incipiently. The time‐varying leader communicates with a small subset of follower agents, and each follower agent communicates to its directly connected neighbors through a bidirectional network with possibly asymmetric weights. A local fault diagnosis and accommodation component are designed for each agent in the distributed system, which consists of a fault detection and isolation module and a reconfigurable controller module comprised of a baseline controller and two adaptive fault‐tolerant controllers, activated after fault detection and after fault isolation, respectively. By using appropriately the designed Lyapunov functions, the closed‐loop stability and asymptotic convergence properties of the leader‐follower formation are rigorously established under different modes of the fault‐tolerant control system.
Appraising the Cognitive Alertness of Night Shift Workers: Case of Bottling Company Operators in Central Northern Nigeria

Night shift, a common work schedule in 24-hour production companies has been posing some after-effects on workers’ health, ranging from physical to psychological, and lack of response to these effects could result in cognitive deficiencies for workers and increased downtime for organisations. The objective of this study is to evaluate the effect of the night shift on the response time of workers to digital visual stimuli as compared to the day shift. Twenty-two shift operators from a bottling line between the ages of 25 and 35 years were subjected to psychomotor vigilance test (PVT) using an android PVT application (Versor-PVT Version 1.03) to assess their response times to visual stimuli and analysed using the SPSS software to determine the data distribution, skewness, and kurtosis. Based on the determined data distribution, Wilcoxon signed rank test (WSRT) was utilised to determine the level of significance of the differences between the two of them. The recorded minimum and maximum average response times for post-day and post-night shifts respectively were: 609.94 ms and 733.64 ms; 644.56 ms and 944.17 ms. Results clearly showed that night shift has significant negative impact on the response time of tested operators, such as delayed ability to respond to situations, including fault rectification, thus causing safety concern, and reducing productivity. In conclusion, additional cost is imminently incurred on the part of the organisation in settling medical bills and compensations. The WSRT analysis indicated that there is 95% probability of generating similar results on repeating the experiment under same conditions.
Exact alignment recovery for correlated Erdos Renyi graphs

We consider the problem of perfectly recovering the vertex correspondence between two correlated \ER (ER) graphs on the same vertex set. The correspondence between the vertices can be obscured by randomly permuting the vertex labels of one of the graphs. We determine the information-theoretic threshold for exact recovery, i.e. the conditions under which the entire vertex correspondence can be correctly recovered given unbounded computational resources.
Evaluation of Blood Pressure Status and Mortality in Turkey: Findings from Chronic Diseases and Risk Factors Cohort Study

Background and objectives: An important Non-Communicable Disease risk factor, hypertension (HT), is highly prevalent and controlled HT rates are not sufficient which increases the risk of developing premature deaths. The purpose of the study is to evaluate differences in all-cause and cardiovascular-related mortality according to HT status by using national data from Chronic Diseases and Risk Factors Survey in Turkey (2011–2017). Materials and Methods: Cox regression models were used to estimate hazard ratios (HR) for predicting the all-cause and cardiovascular system-related mortalities. Median follow-up period was 6.2 years. Results: Among individuals with HT, 41.8% was untreated, 30.1% received treatment and had controlled blood pressure, and 28.1% were under treatment but had uncontrolled BP levels. The hazard for mortality among treated & uncontrolled hypertensive participants was significantly higher for all-cause (HR = 1.32, 95% CI = 1.06–1.65), cardiovascular (HR = 2.11, 95% CI = 1.46–3.06), heart disease (HR = 2.24, 95% CI = 1.46–3.43), and Coronary Heart Disease mortality (HR = 2.66, 95% CI = 1.56–4.53) compared to normotensive participants. Conclusions: Individuals with HT who were treated but do not have controlled blood pressure in Turkey had a significantly increased risk of Cardiovascular Disease and all-cause mortality. Along with studies investigating the causes of uncontrolled blood pressure despite initiation of treatment, support should be provided to patients in cases of non-adherence to antihypertensive medication or life change recommendations.
On mathematical modeling of the propagation of a wave ensemble within an individual axon

The long history of studying the propagation of an action potential has revealed that an electrical signal is accompanied by mechanical and thermal effects. All these effects together generate an ensemble of waves. The consistent models of such a complex phenomenon can be derived by using properly the fundamental physical principles. In this paper, attention is paid to the analysis of concepts of continuum physics that constitute a basis for deriving the mathematical models which describe the emergence and propagation of a wave ensemble in an axon. Such studies are interdisciplinary and based on biology, physics, mathematics, and chemistry. The governing equations for the action potential together with mechanical and thermal effects are derived starting from basics: Maxwell equations, conservation of momentum, Fourier's law, etc., but modified following experimental studies in electrophysiology. Several ideas from continuum physics like external forces and internal variables can also be used in deriving the corresponding models. Some mathematical concepts used in modeling are also briefly described. A brief overview of several mathematical models is presented that allows us to analyze the present ideas of modeling. Most mathematical models deal with the propagation of signals in a healthy axon. Further analysis is needed for better modeling the pathological situations and the explanation of the influence of the structural details like the myelin sheath or the cytoskeleton in the axoplasm. The future possible trends in improving the models are envisaged.