Miracle-dz/UniFAR-FTUs huggingface dataset:
BeppoSAX Observations of the Maser Seyfert 2 Galaxy ESO 103-G35

We have made BeppoSAX observations of the Seyfert 2/1.9 galaxy ESO 103-G35, which contains a nuclear maser source and is known to be heavily absorbed in the X-rays. Analysis of the X-ray spectra observed by BeppoSAX in 1996 October and 1997 October yields a spectral index αE = 0.74 ± 0.07 (Fν ∝ ν), which is typical of Seyfert galaxies and consistent with earlier observations of this source. The strong, soft X-ray absorption has a column density NH of 1.79 ± 0.09 × 1023 cm-2, again consistent with earlier results. The best-fitting spectrum is that of a power law with a high-energy cutoff at 29 ± 10 keV, a cold (E = 6.3 ± 0.1 keV, rest frame), marginally resolved (σ = 0.35 ± 0.14 keV, FWHM ~ 31 ± 12 × 103 km s-1) Fe Kα line with EW 290 eV (1996), and a mildly ionized Fe K edge at 7.37 keV, τ = 0.24. The Kα line and cold absorption are consistent with origin in an accretion disk/torus through which our line of sight passes at a radial distance of ~50 pc. The Fe K edge is mildly ionized, suggesting the presence of ionized gas, probably in the inner accretion disk close to the central source or in a separate warm absorber. The data quality is too low to distinguish between these possibilities, but the edge-on geometry implied by the water maser emission favors the former. Comparison with earlier observations of ESO 103-G35 shows little or no change in spectral parameters while the flux changes by factors of a few on timescales of a few months. The 2-10 keV flux decreased by a factor of ~2.7 between 1996 October and 1997 October with no detectable change in the count rate greater than 20 keV (i.e., the Phoswich Detector System data). Spectral fits to the combined data sets indicate either a significant hardening of the spectrum (αE ~ 0.5) or an approximately constant or delayed response reflection component. The high-energy cutoff (29 ± 10 keV) is lower than the typical ~300 keV values seen in Seyfert galaxies. A significant subset of similar sources would affect current models of the active galactic nucleus contribution to the cosmic X-ray background which generally assume a high-energy cutoff of ~300 keV.
With no Color and Scent (part II): Metal and Alloy Microstructures-Handmade Replicas of Natural Objects

As a continuation of work on metal and alloy "plants" synthesis on porous membranes by means of pulsed current electroplating volume metallic microstructures resembling such natural objects as shells, cabbage leaves, mushrooms are grown and presented in their modest elegance. Such structures are formed from PdNi and PdCo alloys as well as Ag, Cu and Ni in conditions defined by the shape of membrane pores and the parameters of the pulsed current. It is shown that the obtained complex structures are formed by layers of metallic nanowires as a result of their self-assembly while growing during the pulsed current electroplating process. Depending on the shape of the membrane and the regime of the pulsed current electroplating either one type of shell-like structures or various structures can be grown.
Automated variance modeling for three-dimensional point cloud data via Bayesian neural networks

Abstract Three-dimensional (3-D) point cloud data are increasingly being used to describe a wide range of physical objects in detail, corresponding to customized and flexible shape designs. The advent of a new generation of optical sensors has simplified and reduced the costs of acquiring 3-D data in near-real-time. However, the variation of the acquired point clouds, and methods to describe them, create bottlenecks in manufacturing practices such as Reverse Engineering (RE) and metrology in additive manufacturing. We address this issue by developing an automated variance modeling algorithm that utilizes a physical object’s local geometric descriptors and Bayesian Extreme Learning Machines (BELMs). Our proposed ensemble and residual BELM-variants are trained by a scanning history that is composed of multiple scans of other, distinct objects. The specific scanning history is selected by a new empirical Kullback–Leibler divergence we developed to identify objects that are geometrically similar to an object of interest. A case study of our algorithm on additively manufactured products demonstrates its capability to model the variance of point cloud data for arbitrary freeform shapes based on a scanning history involving simpler, and distinct, shapes. Our algorithm has utility for measuring the process capability of 3-D scanning for RE processes.
Patterns and controls on island‐wide aboveground biomass accumulation in second‐growth forests of Puerto Rico

Understanding the heterogeneity of biomass accumulation in second‐growth tropical forests following land use abandonment is important for informing ecosystem carbon models and forest restoration efforts. There is an urgent need for a broad sample of second‐growth forests to enhance our knowledge of carbon accumulation in human‐dominated landscapes, especially for older forests. Puerto Rico has predominantly second‐growth forests, ranging in age from approximately 25 to more than 80 years. We used an island‐wide sample of airborne lidar from the NASA Goddard Lidar, Hyperspectral, and Thermal (G‐LiHT) Airborne Imager collected on March 2017, forest inventory data, and data on forest age, precipitation, soils, and land use to estimate aboveground biomass stocks in moist and wet, second‐growth tropical forests. Biomass accumulation rates in Puerto Rico were lower, on average, than in other Neotropical forests. Median biomass across >16,700 ha of older second‐growth forests was 105 Mg ha−1, and sampled biomass rarely surpassed 250 Mg ha−1. Differences in biomass by age were large and persistent across different substrates and land uses, with a plateau in the pattern of island‐wide biomass accumulation after about 33 years. A spatial regression model showed that multiple factors were related to biomass accumulation, including time since abandonment, geologic substrate, past land use as coffee or pasture, precipitation, topographic wetness index, and slope. Our findings have important consequences for the total carbon storage and expected climate mitigation benefits of large‐scale reforestation efforts, and highlight the value of airborne lidar for quantifying biomass variability in complex tropical landscapes.
The Effect of Necrotic Enteritis Challenge on Production Performance, Cecal Microbiome, and Cecal Tonsil Transcriptome in Broilers

The objective of this study was to identify the effects of experimental necrotic enteritis (NE) infection on the production performance, gut microbiome, and cecal tonsil transcriptome in broiler birds. A total of 192 chicks were not-induced (control) or induced with NE. NE was induced by inoculating Eimeria maxima at 14 d of age and Clostridium perfringens at 19, 20, and 21 d of age. NE challenge increased (p < 0.01) NE lesion score at 7 days post-E.maxima infection (dpi), decreased (p < 0.01) average weight gain and increased (p < 0.01) mortality at 7 and 14 dpi. NE challenge increased (p < 0.05) gut permeability at 5, 6, and 7 dpi and increased ileal C. perfringens load at 5 dpi. NE challenge increased (p < 0.01) Eimeria oocyst shedding at 5, 6, 7, 8 and 14 dpi. NE challenge decreased (p < 0.05) the relative abundance of Lactobacillaceae and increased (p < 0.05) the relative abundance of Campylobacteriaceae, Comamonadaceae, and Ruminococcaceae at 6 dpi. NE challenge upregulated (p < 0.05) genes related to immune response and downregulated (p < 0.05) genes related to lipid metabolism at 6 dpi. It can be concluded that NE infection decreased beneficial bacteria and increased gut permeability.
Digital Rehabilitation for Elbow Pain Musculoskeletal Conditions: A Prospective Longitudinal Cohort Study

Elbow musculoskeletal pain (EP) is a major cause of disability. Telerehabilitation has shown great potential in mitigating musculoskeletal pain conditions, but EP is less explored. This single-arm interventional study investigates clinical outcomes and engagement levels of a completely remote multimodal digital care program (DCP) in patients with EP. The DCP consisted of exercise, education, and cognitive-behavioral therapy for 8 weeks. Primary outcome: disability change (through the Quick Disabilities of the Arm, Shoulder, and Hand questionnaire (QuickDASH), treatment response cut-offs: 12.0-point reduction and 30% change). Secondary outcomes: pain, analgesic intake, surgery intent, mental health, fear–avoidance beliefs, work productivity, and patient engagement. Of the 132 individuals that started the DCP, 112 (84.8%) completed the intervention. Significant improvements were observed in QuickDASH with an average reduction of 48.7% (11.9, 95% CI 9.8; 14.0), with 75.3% of participants reporting ≥30% change and 47.7% reporting ≥12.0 points. Disability change was accompanied by reductions in pain (53.1%), surgery intent (57.5%), anxiety (59.8%), depression (68.9%), fear–avoidance beliefs (34.2%), and productivity impairment (72.3%). Engagement (3.5 (SD 1.4) sessions per week) and satisfaction 8.5/10 (SD 1.6) were high. The significant improvement observed in clinical outcomes, alongside high engagement, and satisfaction suggests patient acceptance of this care delivery mode.
Reality of Moving Groups in the Galaxy

The existence of old dispersed stellar groups within the Milky Way disk is still controversial. Are they the debris of ancient star-forming aggregates, or short-lived artifacts of dynamical origin? With detailed elemental abundance measurements from high quality spectroscopic data, we show that at least one such old dispersed stellar group is a true relic of an earlier phase of star formation. The identification of other such relic structures will provide essential information for probing the evolutionary history of the Milky Way disk.
Modeling core-hole screening in core-excitation spectroscopies

We consider screening of the core-hole potential experienced by the ejected electron in core-excitation processes. This potential affects near-edge structure strongly, but it appears difficult to consistently obtain reliable screened core-hole potentials without substantial computation. Screening effects have both atomic and solid-state (or molecular/cluster) contributions. We emphasize aspects that must be true of “correct” screening models, in an attempt to circumvent the need to carry out full-scale randomphase approximation (RPA) or self-consistent-field calculations of the screening. We present and discuss three spectra computed with RPA and model screened potentials, suggesting ideas to be considered in future work developing screening models.
Data-Efficient Collaborative Decentralized Thermal-Inertial Odometry

We propose a system solution to achieve data-efficient, decentralized state estimation for a team of flying robots using thermal images and inertial measurements. Each robot can fly independently, and exchange data when possible to refine its state estimate. Our system front-end applies an online photometric calibration to refine the thermal images so as to enhance feature tracking and place recognition. Our system back-end uses a covariance-intersection fusion strategy to neglect the cross-correlation between agents so as to lower memory usage and computational cost. The communication pipeline uses Vector of Locally Aggregated Descriptors (VLAD) to construct a request-response policy that requires low bandwidth usage. We test our collaborative method on both synthetic and real-world data. Our results show that the proposed method improves by up to <inline-formula><tex-math notation="LaTeX">$46 \%$</tex-math></inline-formula> trajectory estimation with respect to an individual-agent approach, while reducing up to <inline-formula><tex-math notation="LaTeX">$89 \%$</tex-math></inline-formula> the communication exchange. Datasets and code are released to the public, extending the already-public JPL xVIO library.
Mixture Models for the Analysis of Gene Expression

0\. Title page and table of contents 1\. Introduction 1 2\. Finite Mixture Models 9 3\. Mixture Models and Clustering 21 4\. Analysis of Gene Expression Time Courses 33 5\. Analysis of Gene Expression in Lymphoid Developmen 57 6\. Clustering with Constraints for Integration of Heterogeneous Biological Data 89 7\. Discussion 115 Bibliography 119 Erklarung
The Role of Platelets in Diabetic Kidney Disease

Diabetic kidney disease (DKD) is among the most common microvascular complications in patients with diabetes, and it currently accounts for the majority of end-stage kidney disease cases worldwide. The pathogenesis of DKD is complex and multifactorial, including systemic and intra-renal inflammatory and coagulation processes. Activated platelets play a pivotal role in inflammation, coagulation, and fibrosis. Mounting evidence shows that platelets play a role in the pathogenesis and progression of DKD. The potentially beneficial effects of antiplatelet agents in preventing progression of DKD has been studied in animal models and clinical trials. This review summarizes the current knowledge on the role of platelets in DKD, including the potential therapeutic effects of antiplatelet therapies.
Closed-Form Error Propagation on $SE_{n}(3)$ Group for Invariant EKF With Applications to VINS

Pose estimation is important for robotic perception, path planning, etc. Robot poses can be modeled on matrix Lie groups and are usually estimated via filter-based methods. In this letter, we establish the closed-form formula for the error propagation for the Invariant extended Kalman filter (IEKF) in the presence of random noises and apply it to vision-aided inertial navigation. Moreover, we use the theoretic results to add the compensation parts for IEKF. We evaluate our algorithms via numerical simulations and experiments on the OPENVINS platform. Both simulations and the experiments performed on the public EuRoC MAV datasets demonstrate that our algorithm in particular parameters settings outperforms some state-of-art filter-based methods such as the quaternion-based EKF, first estimates Jacobian EKF, etc. The techniques of choice on the parameters are worth further investigating.
Safety of an extension of use of Yarrowia lipolytica yeast biomass as a novel food pursuant to Regulation (EU) 2015/2283

Abstract Following a request from the European Commission, the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) was asked to deliver an opinion on the safety of an extension of use for Yarrowia lipolytica yeast biomass as a novel food (NF) pursuant to Regulation (EU) 2015/2283. The extension of use pertains to the use of the NF as a food ingredient in single meal replacement products for weight reduction for adults at a maximum amount of 6 g NF per day, which is the same amount of NF as already authorised in food supplements for this population group. According to the applicant, food supplements with Yarrowia lipolytica biomass (as already authorised) should not be consumed concomitantly with the meal replacement products in order not to exceed the 6 g NF per day. The Panel considers that the consumption of the NF is not nutritionally disadvantageous under the proposed conditions of use. The Panel concludes that the NF, Yarrowia lipolytica yeast biomass, is safe under the proposed conditions of use.
Limit on the muon neutrino magnetic moment and a measurement of the CCPIP to CCQE cross section ratio

A search for the muon neutrino magnetic moment was conducted using the Mini-BooNE low energy neutrino data. The analysis was performed by analyzing the elastic scattering interactions of muon neutrinos on electrons. The analysis looked for an excess of elastic scattering events above the Standard Model prediction from which a limit on the neutrino magnetic could be set. In this thesis, we report an excess of 15.3 {+-} 6.6(stat){+-}4.1(syst) {nu}{sub {mu}e} events above the expected background. At 90% C.L. , we derived a limit on the muon neutrino magnetic moment of 12.7 x 10{sup -10} {micro}{sub B}. The other analysis reported in this thesis is a measurement of charged current single pion production (CC{pi}{sup +}) to charged current quasi elastic (CCQE) interactions cross sections ratio. This measurement was performed with two different fitting algorithms and the results from both fitters are consistent with each other.
Kajian Identifikasi Risiko Pada Tahap Pelaksanaan Proyek Konstruksi: Studi Kasus Multiple Project Management

Risk identification is a part of the Risk Management Process. Multiple Project Management is fundamentally different from a single project. In multiple projects, there is the connectedness of resource allocation and the possibility of conflict between the projects. The research problems analysed are: What is the meaning of risk in a construction project? What is the picture of the multiple projects? What are the potential risks in the multiple projects? What are the recommendations resulting? This research is limited for implementation of construction projects in industrial facilities in Indonesia. Several literature reviews are used as the basis for analysis such as PMBOK, Guide 6th Edition as well as various relevant research results. The research process carried out to examine various things about risks in multiple projects, the Risk Management process, review various relevant research and provide recommendations. The conclusions of this study are: risks are various potentials that can affect the implementation of construction projects, necessary to anticipate risks in the construction projects, potential risks can occur in the all-construction phase, and as results, it is observed that there are various aspects of prevention against risks to minimize the negative impacts in the multiple projects.
Pattern Language as Support to Software Measurement Planning for Statistical Process Control

The growing interest of organizations in improving their software processes has led them to aim at achieving high maturity, where statistical process control (SPC) is required. One of the challenges involved in performing SPC is selecting measures suitable for it. Measures used in SPC can be found in the literature and can be reused by organizations, but the information is dispersed, not favoring reuse. From measures suggested in the literature or used in practical experiences, it is possible to identify patterns that can be used to support organizations in measurement planning. Patterns can be organized as pattern languages, which favor reuse and contribute towards increasing productivity. In this work, from the results of a systematic mapping and a survey, we identified measurement planning patterns in the Goal-Question-Metric format and organized them in a Measurement Planning Pattern Language (MePPLa). MePPLa was created by following a Systematic Approach for creating Measurement Planning Pattern Languages (SAMPPLa), also defined in this work. This paper presents SAMPPLa, MePPLa and the main results of a study carried out to evaluate MePPLa. The results showed that using MePPLa is viable and useful to aid in software measurement planning. Mainly, MePPLa contributes to increasing productivity when creating a measurement plan and the quality of the resulting measurement plan.
ASCA Observation of Cygnus X-1 in the Soft State: Mass of the Compact Object

We describe the ASCA observation of the black hole candidate Cyg X-1 in the soft state of 1996 May and report the mass estimation of the central object from X-ray spectral analysis. The energy spectrum in 0.7-10 keV can be described by the sum of a power law (Γ = 2.3 ± 0.1) and an ultrasoft component; the latter is most probably the emission from an optically thick accretion disk. Through the spectral analysis of the ultrasoft component, we estimated the size of the accretion disk, which is closely related to the Schwarzschild radius and, hence, to the mass of the central object. Taking the general relativistic effects into account, the most probable mass of the compact object is estimated as 12+ 3−1M☉. This value is independent of, yet consistent with, the mass estimate based on the orbital kinematics information.
Math Is Art.

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Analysis of Students Creative Thinking Ability in Environmental Problem Solving

21st century is a period that requires the transformation of life including education in it. Changes that occur include increased interaction between individuals globally, the flood of open information, computing technology that reaches all types of work that can be done anywhere and anytime and the occurrence of cultural integration across borders and even countries. This situation requires individuals to have the resilience to adapt and survive in this century. The quality of teachers in education plays an important role in building various skills of students to face life's demands. Creative thinking skills are one of the competencies needed in this century. Fostering creativity in learning activities is very important to strengthen student resilience in the future. This study aims to provide an overview of students' creative thinking skills on environmental problems. This research uses quantitative descriptive methods. This article begins with the results of an assessment of the ability to think creatively in early semester students in the Biology Education study program major of Prof. Dr. Hamka University then analyze the factors that affect critical thinking skills through a questionnaire instrument to describe learning activities that build creative thinking skills both from the internal and external aspect.
Early fire smoke detection model based on YOLOv5

Aiming at the low detection accuracy of existing fire early smoke target detection models, this paper designs a fire early fire smoke detection model based on YOLOv5. First, check the data to understand the fire-prone scenes and divide them into two categories: indoor and outdoor; Second, according to different scenes, considering the influence of environmental factors such as light and scale, manually collect and label the smoke pictures in the early stage of the fire; Third, The Focal Loss loss function is used instead to alleviate the problem of unbalanced classification in the data set. Experiments on the self-made early fire smoke dataset show that the improved network mAP value is 2.3% higher than that of YOLOv5. The experimental results verify the effectiveness of the algorithm.