Miracle-dz/UniFAR-FTUs huggingface dataset:
The Similar Structure of Solutions for the Boundary Value Problem of Euler’s Hypergeometric Differential Equation

Using the two basic solutions on the infinite of differential equation,discussed the similar structure of the solutions of the Euler’s hypergeometric differential equation,and defined the similar kernel function of the solutions.It confirmed that the solutions for the boundary value problem of Euler’s hypergeometric differential equation have the unifor expression,it determined uniquely by the left boundary condition only.About changed the right boundary condition,it can obtain the similar structure of the boundary value problem only by changed its similar kernel function.The similar structure of solution is attained in this paper,which is beneficial to understand the inherent laws of analytic soution.
Génération de cartes de disparité denses à partir d'images panoramiques cylindriques haute définition

Résumé –Cette étude porte sur le développement, l’utilisation d’un capteur panoramique cylindrique à très haute définition, et les cartes de profondeur obtenues à partir de deux vues de ce capteur. Partant d’images calibrées, plusieurs étapes sont réalisées: détection et appariement de points d’intérêt, détermination de la SFM, appariement dynamique des lignes épipolaires de l’image. Les résultats obtenus sont les cartes de disparité denses de 2048 * 3600 pixels du panorama étudié.
When Do Radical Flanks Use Violence? Conditions for Violent Protest in Radical Left-Libertarian Activism in Sweden, 1997–2016

Descriptions of social movement factionalism are often based on the dichotomous conception of lawful moderates and violent radicals. In this article, we nuance this distinction by illustrating the complexity of radical flanks through an empirically grounded analysis of protest tactics, in which we ask under what conditions radical flanks are likely to use violent protest tactics. Exploring dominant explanations of political violence, the article shows the necessity of understanding the use of violent protest tactics as part of cognitive and relational processes. The use of violent tactics varies greatly across frames and protest issues, pointing to how different logics of protest are tied to different frames. Also, the use of violence is affected by the presence or absence of moderate allies; the likelihood of violence clearly decreases when radicals and moderates form coalitions when organising protests. The analysis is based on a protest event data set covering over 3,900 nonviolent and violent events by the Radical Left-Libertarian Movement in Sweden, 1997–2016. Notably, the results hold over this entire twenty-year period, suggesting that they are robust and provide a better explanation than historically contingent causes.
Bayesian calibration of geothermal reservoir models via Markov Chain Monte Carlo

The aim of the research described in this thesis is the development of methods for solving computationally intensive computer model calibration problems by sample based inference. Although our primary focus is calibrating computer models of geothermal reservoirs, the methodology we have developed can be applied to a wide range of computer model calibration problems. In this study, the Bayesian framework is employed to construct the posterior distribution over all model parameters consistent with the measured data, accounting for various uncertainties in the calibration process. To construct the posterior distribution for computer model calibration problems, several methods such as the additive bias framework of Kennedy and O’Hagan (2001) and the enhanced error model (Kaipio and Somersalo, 2007) are investigated. Then, the solutions of computer model calibration problems are given by estimating the expected value of statistics of interest over the posterior distribution. Markov chain Monte Carlo (MCMC) sampling, Metropolis-Hastings (MH) algorithm (Metropolis et al., 1953; Hastings, 1970) in particular, is empoyed to explore the posterior distribution, and Monte Carlo integration is used to calculating the expected values. To be able to automatically adjust the proposal densities used in the MH algorithm, the state-of-the-art adaptive MCMC algorithms (Haario et al., 2001; Atchade and Rosenthal, 2005; Andrieu and Moulines, 2006; Roberts and Rosenthal, 2007) are investigated in this thesis. A group components adaptive Metropolis (GCAM) algorithm has been designed, which combines the features of the adaptive Metropolis algorithm (Haario et al., 2001) and the adaptive Metropolis-within-Gibbs algorithm
Population Rescue through an Increase in the Selfing Rate under Pollen Limitation: Plasticity versus Evolution

Increased rates of self-fertilization offer reproductive assurance when plant populations experience pollen limitation, but self-fertilization may reduce fitness by exposing deleterious mutations. If an environmental change responsible for pollen limitation also induces plastic mating system shifts toward self-pollination, the reproductive assurance benefit and inbreeding depression cost of increased self-fertilization occur immediately, while the benefit and cost happen more gradually when increased self-fertilization occur through evolution. I built eco-evolutionary models to explore the demographic and genetic conditions in which higher self-fertilization by plasticity and/or evolution rescues populations, following deficits due to a sudden onset of pollen limitation. Rescue is most likely under an intermediate level of selfing rate increase, either through plasticity or evolution, and this critical level of selfing rate increase is higher under stronger pollen limitation. Generally, rescue is more likely through plasticity than through evolution. Under weak pollen limitation, rescue by enhanced self-fertilization may mainly occur through purging of deleterious mutations rather than reproductive assurance. The selfing rate increase conferring the highest rescue probability is lower when the initial population size is smaller. This article shows the importance of plasticity during plant population rescue and offers insights for future studies of the evolution of mating system plasticity.
Oversampled ITOF Imaging Techniques using SPAD-based Quanta Image Sensors

The Quanta Image Sensor (QIS) or digital film sensor is an imaging array of photo-sensitive sites with single bit output (a jot) [1][2]. Binary field images (or jot bit planes) are oversampled in either the spatial or temporal domains to form a multi-bit intensity frame image, where each pixel in the image represents a summation of jots. A single photon avalanche diode (SPAD) based QVGA QIS image sensor is presented in [3] which demonstrates real-time temporal oversampling of single photon global shutter field images. SPAD-based pixels may not scale in pitch to the 100’s of nanometres regime for high spatial resolution QISs, but they have two significant advantages over photo-diode/photo-gate based CMOS image sensors (CIS): the SPAD photo detection mechanism has both picosecond temporal resolution and single-photon sensitivity (typically 100ps RMS and >1V/ph respectively). This temporal resolution has previously been successful demonstrated in time of flight (TOF) imaging [4]. The high sensitivity is ideal for connection to, and triggering of, a time-gated single bit memory pixel circuit [5] or a single photon counter [6]. Exploiting both these advantages, this paper proposes extending the QIS concept to a TOF binary image sensor capturing interleaved time-gated fields which are temporally oversampled to create indirect time of flight (ITOF) depth images. We propose two techniques applicable to oversampled QIS image sensors to implement two-bin ITOF imaging with and without background rejection. These are demonstrated for the first time using a time-gated SPAD-based QIS achieving 4.6x overexposure latitude in intensity and ITOF ranging with 38mm max σ in 60cm range.
Lipid-Sensing Receptor FFAR4 Modulates Pulmonary Epithelial Homeostasis following Immunogenic Exposures Independently of the FFAR4 Ligand Docosahexaenoic Acid (DHA)

The role of pulmonary free fatty acid receptor 4 (FFAR4) is not fully elucidated and we aimed to clarify the impact of FFAR4 on the pulmonary immune response and return to homeostasis. We employed a known high-risk human pulmonary immunogenic exposure to extracts of dust from swine confinement facilities (DE). WT and Ffar4-null mice were repetitively exposed to DE via intranasal instillation and supplemented with docosahexaenoic acid (DHA) by oral gavage. We sought to understand if previous findings of DHA-mediated attenuation of the DE-induced inflammatory response are FFAR4-dependent. We identified that DHA mediates anti-inflammatory effects independent of FFAR4 expression, and that DE-exposed mice lacking FFAR4 had reduced immune cells in the airways, epithelial dysplasia, and impaired pulmonary barrier integrity. Analysis of transcripts using an immunology gene expression panel revealed a role for FFAR4 in lungs related to innate immune initiation of inflammation, cytoprotection, and immune cell migration. Ultimately, the presence of FFAR4 in the lung may regulate cell survival and repair following immune injury, suggestive of potential therapeutic directions for pulmonary disease.
Predictive Learning of Error Recovery with a Sensorized Passivity‐Based Soft Anthropomorphic Hand

Manipulation strategies based on the passive dynamics of soft‐bodied interactions provide robust performances with limited sensory information. They utilize the kinematic structure and passive dynamics of the body to adapt to objects of varying shapes and properties. However, these soft passive interactions make the state of the robotic device influenced by the environment, making control generation and state estimation difficult. This work presents a closed‐loop framework for dynamic interaction‐based grasping that relies on two novelties: 1) a wrist‐driven passive soft anthropomorphic hand that can generate robust grasp strategies using one‐step kinaesthetic teaching and 2) a learning‐based perception system that uses temporal data from sparse tactile sensors to predict and adapt to failures before it happens. With the anthropomorphic soft design and wrist‐driven control, it is shown that controllers can be generated robust to novel objects and location uncertainty. With the learning‐based high‐level perception system and 32 sensing receptors, it is shown that failures can be predicted in advance, further improving the robustness of the entire system by more than doubling the grasping success rate. From over 1000 real‐world grasping trials, both the control and perception framework are also seen to be transferable to novel objects and conditions. An interactive preprint version of the article can be found here: https://doi.org/10.22541/au.167687985. 55182112/v1.
A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT

Abstract. Satellite radar backscatter contains unique information on land surface moisture, vegetation features, and surface roughness and has thus been used in a range of Earth science disciplines. However, there is no single global radar data set that has a relatively long wavelength and a decades-long time span. We here provide the first long-term (since 1992), high-resolution (∼8.9 km instead of the commonly used ∼25 km resolution) monthly satellite radar backscatter data set over global land areas, called the long-term, high-resolution scatterometer (LHScat) data set, by fusing signals from the European Remote Sensing satellite (ERS; 1992–2001; C-band; 5.3 GHz), Quick Scatterometer (QSCAT, 1999–2009; Ku-band; 13.4 GHz), and the Advanced SCATterometer (ASCAT; since 2007; C-band; 5.255 GHz). The 6-year data gap between C-band ERS and ASCAT was filled by modelling a substitute C-band signal during 1999–2009 from Ku-band QSCAT signals and climatic information. To this end, we first rescaled the signals from different sensors, pixel by pixel. We then corrected the monthly signal differences between the C-band and the scaled Ku-band signals by modelling the signal differences from climatic variables (i.e. monthly precipitation, skin temperature, and snow depth) using decision tree regression. The quality of the merged radar signal was assessed by computing the Pearson r, root mean square error (RMSE), and relative RMSE (rRMSE) between the C-band and the corrected Ku-band signals in the overlapping years (1999–2001 and 2007–2009). We obtained high Pearson r values and low RMSE values at both the regional (r≥0.92, RMSE ≤ 0.11 dB, and rRMSE ≤ 0.38) and pixel levels (median r across pixels ≥ 0.64, median RMSE ≤ 0.34 dB, and median rRMSE ≤ 0.88), suggesting high accuracy for the data-merging procedure. The merged radar signals were then validated against the European Space Agency (ESA) ERS-2 data, which provide observations for a subset of global pixels until 2011, even after the failure of on-board gyroscopes in 2001. We found highly concordant monthly dynamics between the merged radar signals and the ESA ERS-2 signals, with regional Pearson r values ranging from 0.79 to 0.98. These results showed that our merged radar data have a consistent C-band signal dynamic. The LHScat data set (https://doi.org/10.6084/m9.figshare.20407857; Tao et al., 2023) is expected to advance our understanding of the long-term changes in, e.g., global vegetation and soil moisture with a high spatial resolution. The data set will be updated on a regular basis to include the latest images acquired by ASCAT and to include even higher spatial and temporal resolutions.
Biomimetic Approaches for Human Arm Motion Generation: Literature Review and Future Directions

In recent years, numerous studies have been conducted to analyze how humans subconsciously optimize various performance criteria while performing a particular task, which has led to the development of robots that are capable of performing tasks with a similar level of efficiency as humans. The complexity of the human body has led researchers to create a framework for robot motion planning to recreate those motions in robotic systems using various redundancy resolution methods. This study conducts a thorough analysis of the relevant literature to provide a detailed exploration of the different redundancy resolution methodologies used in motion generation for mimicking human motion. The studies are investigated and categorized according to the study methodology and various redundancy resolution methods. An examination of the literature revealed a strong trend toward formulating intrinsic strategies that govern human movement through machine learning and artificial intelligence. Subsequently, the paper critically evaluates the existing approaches and highlights their limitations. It also identifies the potential research areas that hold promise for future investigations.
Effect of Dietary Manganese on the Growth Performance, Lipid Metabolism, and Antioxidant Capacity in the Post-Larval Coho Salmon (Oncorhynchus kisutch)

Simple Summary As one of the essential mineral elements, manganese (Mn) is involved in maintaining the growth and physiological function of fish species. An optimal dietary level of manganese accelerated the growth, lipid metabolism, Mn accumulation, and antioxidant capacity of coho salmon. The dietary Mn requirement for post-larvae coho salmon was 17.35 mg kg−1 and 19.75 mg kg−1 according to the SGR and FCR, respectively. An optimal dietary level of manganese had a positive effect on the antioxidant capacity by scavenging free radicals in fish bodies. In addition, dietary Mn improved lipid metabolism, and the signaling pathway of PI3K/AKT/mTOR may be involved in regulating the activity of lipid metabolism enzymes. Abstract In this study, post-larval coho salmon Oncorhynchus kisutch (initial weight 0.37 ± 0.03 g) were fed with 6 experimental diets with increasing manganese (Mn) content (2.4, 8.5, 14.8, 19.8, 24.6, and 33.7 mg kg−1) for 12 weeks. Our results indicated that the feed conversion rate (FCR), specific growth rate (SGR), condition factor (CF), crude protein, moisture, crude lipid, ash, whole-body Mn, and vertebral Mn were affected by the elevation of Mn content in the diet. The activities of hepatic GSH-PX, Mn-SOD, and CAT were enhanced with increasing Mn content in the diet and reached the highest value at 19.8 mg kg−1 Mn. However, the level of hydrogen peroxide (H2O2), superoxide anion (O2·−), and malondialdehyde (MDA) was reduced with increasing Mn content in the diet. In addition, the activity of hepatic lipase (HL) and lipoprotein lipase (LPL) was increased with the elevation of dietary Mn content and reached a peak value at 14.8 mg kg−1 Mn. The activity of fatty acid synthetase (FAS) and the content of nonesterified fatty acid (NEFA) were increased following the elevation of Mn content from 2.4 to 19.8 mg kg−1 in the diet. The results indicated that the appropriate dietary Mn supplementation improved the feeding efficiency, lipid metabolism, and antioxidant capacity of coho salmon. The dietary Mn requirement for post-larval coho salmon was 17.35 mg kg−1 and 19.75 mg kg−1 based on the SGR and FCR, respectively. An optimal dietary level of Mn enhances hepatic lipid metabolism, and the signaling pathway of PI3K/AKT/mTOR may be involved in regulating the activity of enzymes related to lipid metabolism.
MCNPX Estimation of Photoneutron Dose to Eye Voxel Anthropomorphic Phantom From 18 MV Linear Accelerator

The dose due to photoneutron contamination outside the field of irradiation can be significant when using high-energy linear accelerators. The eye is a radiation-sensitive organ, and this risk increases when high linear energy transfer neutron radiation is involved. This study aimed to provide a fast method to estimate photoneutron dose to the eye during radiotherapy. A typical high-energy linear accelerator operating at 18 MV was simulated using the Monte Carlo N-Particle Transport Code System extended version (MCNPX 2.5.0). The latest International Atomic Energy Agency photonuclear data library release was integrated into the code, accounting for the most known elements and isotopes used in typical linear accelerator construction. The photoneutron flux from a 5 × 5 cm2 field size was scored at the treatment table plane and used as a new source for estimating the absorbed dose in a high-resolution eye voxel anthropomorphic phantom. In addition, common shielding media were tested to reduce the photoneutron dose to the eye using common shielding materials. Introducing a 2 cm thickness of common neutron shielding medium reduced the total dose received in the eye voxel anthropomorphic phantom by 54%. In conclusion, individualized treatment based on photoneutron dose assessment is essential to better estimate the secondary dose inside or outside the field of irradiation.
Intramuscular fat formation in fetuses and the effect of increased protein intake during pregnancy in Hanwoo cattle

Abstract Understanding adipocyte development in fetus during bovine pregnancy is important for strengthening fattening technology. Additionally, nutritional level of dams during pregnancy has the potential to improve offspring growth and fat development. The purpose of this study is to evaluate the intramuscular adipocyte development and expression level of related genes in bovine fetus, and the effect of increased crude protein (CP) intake during pregnancy on the growth performance and carcass characteristics of male offspring. Eighty six pregnant Hanwoo cows (average body weight, 551.5 ± 51.3 kg, age 5.29 ± 0.61 y) were used. Fetuses were collected at 90, 180 and 270 d of gestation from 18 pregnant Hanwoo cows. The remaining 68 pregnant cows were randomly assigned to 2 feeding groups. The control (CON) group was provided the standard protein diet (n = 34), and treatment (TRT) group was provided a diet with a 5% increase in CP intake (n = 34). Male offspring were divided into two groups according to protein treatment of the pregnant cows: CON male offspring (CON-O) and TRT male offspring (TRT-O). Intramuscular adipocytes were found in the fetal skeletal muscle after 180 days of gestation. Male calf’s birth weight increased in the TRT group compared to that in the CON group (p < 0.002). The final body weight (p < 0.003) and average daily gain (p < 0.019) of male offspring were significantly higher in TRT-O than in CON-O. The feed conversion ratio was also improved by 10.5% in TRT-O compared to that in CON-O (p < 0.026). Carcass weight was significantly higher in the TRT-O group than that in the CON-O group (p < 0.003), and back fat was thicker in the TRT-O group (p = 0.07). The gross receipts and net income were higher in TRT-O than in CON-O (p < 0.04). Thus, fetal intramuscular fat can be formed from the mid-gestation period, and increased CP intake during pregnancy can increase net income by improving the growth and carcass weight of male offspring rather than intramuscular fat.
Bolocam: a millimeter-wave bolometric camera

We describe the design of Bolocam, a bolometric camera for millimeter-wave observations at the Caltech Submillimeter Observatory. Bolocam will have 144 diffraction-limited detectors operating at 300 mK, an 8 arcminute field of view, and a sky noise limited NEFD of approximately 35 mJy Hz-1/2 per pixel at (lambda) equals 1.4 mm. Observations will be possible at one of (lambda) equals 1.1. , 1.4, or 2.1 mm per observing run. The detector array consists of sensitive NTD Ge thermistors bonded to silicon nitride micromesh absorbers patterned on a single wafer of silicon. This is a new technology in millimeter-wave detector array construction. To increase detector packing density, the feed horns will be spaced by 1.26 f(lambda) (at (lambda) equals 1.4 mm), rather than the conventional 2 f(lambda) . DC stable read out electronics will enable on-the-fly mapping and drift scanning. We will use Bolocam to map Galactic dust emission, to search for protogalaxies, and to observe the Sunyaev- Zel'dovich effect toward galaxy clusters.
Potentially unlimited variance reduction in importance sampling of Markov chains

We consider the application of importance sampling in steady-state simulations of finite Markov chains. We show that, for a large class of performance measures, there is a choice of the alternative transition matrix for which the ratio of the variance of the importance sampling estimator to the variance of the naive simulation estimator converges to zero as the sample path length goes to infinity. Obtaining this ‘optimal’ transition matrix involves computing the performance measure of interest, so the optimal matrix cannot be computed in precisely those situations where simulation is required to estimate steady-state performance. However, our results show that alternative transition matrices of the form Q = P + E/T, where P is the original transition matrix and T is the sample path length, can be expected to provide good results. Moreover, we provide an iterative algorithm for obtaining alternative transition matrices of this form that converge to the optimal matrix as the number of iterations increases, and present an example that shows that spending some computer time iterating this algorithm and then conducting the simulation with the resulting alternative transition matrix may provide considerable variance reduction when compared to naive simulation.