Miracle-dz/UniFAR-FTUs huggingface dataset:
Yield performance of 14 novel inter‐ and intra‐species Miscanthus hybrids across Europe

Miscanthus, a C4 perennial rhizomatous grass from Asia is a leading candidate for the supply of sustainable biomass needed to grow the bioeconomy. European Miscanthus breeding programmes have recently produced a new range of seeded hybrids with the objective of increasing scalability to large acreages limited by current clonal propagation. For the EU‐GRACE project, new replicated field trials were established in seven locations across Europe in 2018 with eight intraspecific M. sinensis hybrids (sin × sin) and six M. sacchariflorus × M. sinensis (sac × sin) from Dutch and UK breeding programmes, respectively, with clonal Miscanthus × giganteus. The planting density of the sin × sin was double that of sac × sin (30,000 & 15,000 plants ha−1), creating commercially relevant upscaling comparisons between systems. Over the first 3 years, the establishment depended on location and hybrid. The mature sin × sin hybrids formed tight tufts of shoots up to 2.5 m tall which flower and senesce earlier than the taller sac × sin hybrids. Following the third growing season, the highest yields were recorded in Northern Italy at a low altitude (average 13.7 (max 21) Mg DM ha−1) and the lowest yielding was on the industrially damaged marginal land site in Northern France (average 7.0 (max 10) Mg DM ha−1). Moisture contents at spring harvest were lowest in Croatia (21.7%) and highest in Wales, UK (41.6%). Overall, lower moisture contents at harvest, which are highly desirable for transport, storage and for most end‐use applications, were found in sin × sin hybrids than sac × sin (30% and 40%, respectively). Yield depended on climate interactions with the hybrid and their associated planting systems. The sin × sin hybrids appeared better adapted to northern Europe and sac × sin hybrids to southern Europe. Longer‐term yield observations over crop lifespans will be needed to explore the biological (yield persistence) and economic costs and benefits of the different hybrid systems.
Predicting noise‐induced sleep disturbance

The findings of 21 studies of the effects of noise on sleep were reanalyzed in an effort to develop a quantitative dosage‐response relationship. Large and systematic differences in sleep disturbance were observed between the findings of studies conducted in laboratory and in field settings. The influence of noise on sleep was also found to depend on additional factors such as the nature of noise and response metrics, noise source, background noise level, length of study, and sex of test participants. No reliable quantitative model for sleep disturbance could be developed from the studies reviewed.
Systematic Review: Contribution of the Gut Microbiome to the Volatile Metabolic Fingerprint of Colorectal Neoplasia

Colorectal cancer (CRC) has been associated with changes in volatile metabolic profiles in several human biological matrices. This enables its non-invasive detection, but the origin of these volatile organic compounds (VOCs) and their relation to the gut microbiome are not yet fully understood. This systematic review provides an overview of the current understanding of this topic. A systematic search using PubMed, Embase, Medline, Cochrane Library, and the Web of Science according to PRISMA guidelines resulted in seventy-one included studies. In addition, a systematic search was conducted that identified five systematic reviews from which CRC-associated gut microbiota data were extracted. The included studies analyzed VOCs in feces, urine, breath, blood, tissue, and saliva. Eight studies performed microbiota analysis in addition to VOC analysis. The most frequently reported dysregulations over all matrices included short-chain fatty acids, amino acids, proteolytic fermentation products, and products related to the tricarboxylic acid cycle and Warburg metabolism. Many of these dysregulations could be related to the shifts in CRC-associated microbiota, and thus the gut microbiota presumably contributes to the metabolic fingerprint of VOC in CRC. Future research involving VOCs analysis should include simultaneous gut microbiota analysis.
After a Decade of Teleimpedance: A Survey

Despite the significant progress made in making robots more intelligent and autonomous, today, teleoperation remains a dominant robot control paradigm for the execution of complex and highly unpredictable tasks. Attempts have been made to make teleoperation systems stable, easy to use, and efficient in terms of physical interactions between the follower remote robot and the environment. In particular, the emergence of torque-controlled robots has permitted to regulate the interaction forces from a distance through direct force or impedance control, enabling them to engage in complex interaction tasks. Exploiting this feature, the concept of teleimpedance control was introduced as an alternative method to bilateral force-reflecting teleoperation. The aim was to create a feed-froward yet contact-efficient teleoperation by enriching the leader commands with desired impedance profiles while executing a task. Since then, the teleimpedance concept has found its way into a wide range of interface and controller designs, as well as application domains. Accordingly, after a decade of research progress, this survey aims to provide: first, a convenient introduction of the concept to new researchers in the field, second, consolidate the existing state-of-the-art for active researchers, third, and discuss the pros and cons of different methods in terms of interface and force feedback to provide guidelines for different applications and future developments.
Model vibrations and inertial bias measurement in a transonic wind tunnel test

Vibration measurements are performed in parallel with the aerodynamic force & moment testing of a commercial aircraft model in the North American Trisonic Wind Tunnel. A tri-axial accelerometer is used to measure the normal, side, and axial acceleration of the model during a pitch polar at transonic speed. It is shown that the model dynamics are characterized by discrete vibration modes with frequencies up to several hundred Herz. These oscillations, which are picked up by the internal balance as inertial forces, are likely to be related to high-frequency unsteadiness in the flow. A qualitative analysis of the axial force inertial bias (sting whip effect) is performed by computing the magnitude-squared coherence function of the axial acceleration and the squared tangential velocity in pitch and yaw. Although strong rotational oscillations in pitch or yaw are unlikely, it is shown that a link between model dynamics and inertial bias cannot be excluded.
Building and analyzing machine learning-based warfarin dose prediction models using scikit-learn

For personalized drug dosing, prediction models may be utilized to overcome the inter-individual variability. Multiple linear regression has been used as a conventional method to model the relationship between patient features and optimal drug dose. However, linear regression cannot capture non-linear relationships and may be adversely affected by non-normal distribution and collinearity of data. To overcome this hurdle, machine learning models have been extensively adapted in drug dose prediction. In this tutorial, random forest and neural network models will be trained in tandem with a multiple linear regression model on the International Warfarin Pharmacogenetics Consortium dataset using the scikit-learn python library. Subsequent model analyses including performance comparison, permutation feature importance computation and partial dependence plotting will be demonstrated. The basic methods of model training and analysis discussed in this article may be implemented in drug dose-related studies.
Factorization in the Invertible Group of a C*-Algebra

Abstract In this paper we consider the following problem: Given a unital C*- algebra A and a collection of elements S in the identity component of the invertible group of A, denoted inv0(A), characterize the group of finite products of elements of S. The particular C*-algebras studied in this paper are either unital purely infinite simple or of the form (A ⊗ K)+, where A is any C*-algebra and K is the compact operators on an infinite dimensional separable Hilbert space. The types of elements used in the factorizations are unipotents (1+ nilpotent), positive invertibles and symmetries (s2 = 1). First we determine the groups of finite products for each collection of elements in (A ⊗ K)+. Then we give upper bounds on the number of factors needed in these cases. The main result, which uses results for (A ⊗ K)+, is that for A unital purely infinite and simple, inv0(A) is generated by each of these collections of elements.
Why Can SVM Be Performed in PCA Transformed Space for Classification?

PCA plus SVM is a popular framework for classification problems. On the one hand, it can avoid the SVM kernel Gram to become overlarge and save storage space. On the other hand, PCA plus SVM approach has been verified effective for classification by experience. This paper focuses on building a theoretical foundation for this framework. By derivation, the equivalence relation between PCA plus SVM and LDA is discovered for binary classification. Moreover, we give a specific analysis about the framework to validate our viewpoint compared with SVM and combined SVM/LDA on ORL face database, Yale face database and real world benchmark data. The experimental results indicate that SVM can be performed in PCA transformed space for classification.
Homoepitaxial growth of GaN by metalorganic vapor phase epitaxy: A benchmark for GaN technology

Carefully optimized low-pressure metalorganic vapor phase epitaxy is used for homoepitaxial growth on distinctively pretreated GaN bulk single crystal substrates. Thereby, outstanding structural and optical qualities of the material have been achieved, exhibiting photoluminescence linewidths for bound excitons as narrow as 95 μeV. These extremely sharp lines reveal fine structures, not reported for GaN. Additionally, all three free excitons as well as their excited states are visible in low-temperature photoluminescence at 2 K. These transitions are clearly identified by reflectance measurements. X-ray diffraction analysis of these layers reveal about 20 arcsec linewidth for the (0004) reflex using CuKα radiation.
Hot White Dwarfs in the Extreme Ultraviolet Explorer Survey. II. Mass Distribution, Space Density, and Population Age

We present new effective temperature and surface gravity determinations for a sample of 90 hot white dwarfs detected in the Extreme Ultraviolet Explorer (EUVE) all-sky survey. The measurements, based on spectroscopy of the Balmer line series obtained at the Michigan-Dartmouth-MIT Observatory, Mount Stromlo Observatory, Lick Observatory, and Cerro Tololo Inter-American Observatory, are used to constrain the space density as well as the population age and mass distribution of a sample of 110 EUV-selected DA white dwarfs in the solar neighborhood. We find a mass spectrum narrowly peaked over 0.56 M☉, indicative of a C-O core with a thin hydrogen layer, and a significant population of 10 ultramassive (M ≥ 1.1 M☉) white dwarfs; we also find that all objects fall between effective temperatures of ≈ 25,000 and ≈ 75,000 K and that most are younger than 30 Myr. Using Wood's evolutionary models we determine a DA white dwarf birthrate in the solar neighborhood of (0.7-1.0) × 10-12 pc-3 yr-1. Although most objects are on normal C-O cooling tracks, we suggest that a few low-mass white dwarfs and the population of ultramassive white dwarfs may follow different paths with, respectively, He, and, possibly, O-Ne-Mg cores.
Extension of the hybrid linear programming method to optimize simultaneously the design and operation of groundwater utilization systems

This article proposes a hybrid linear programming (LP-LP) methodology for the simultaneous optimal design and operation of groundwater utilization systems. The proposed model is an extension of an earlier LP-LP model proposed by the authors for the optimal operation of a set of existing wells. The proposed model can be used to optimally determine the number, configuration and pumping rates of the operational wells out of potential wells with fixed locations to minimize the total cost of utilizing a two-dimensional confined aquifer under steady-state flow conditions. The model is able to take into account the well installation, piping and pump installation costs in addition to the operational costs, including the cost of energy and maintenance. The solution to the problem is defined by well locations and their pumping rates, minimizing the total cost while satisfying a downstream demand, lower/upper bound on the pumping rates, and lower/upper bound on the water level drawdown at the wells. A discretized version of the differential equation governing the flow is first embedded into the model formulation as a set of additional constraints. The resulting mixed-integer highly constrained nonlinear optimization problem is then decomposed into two subproblems with different sets of decision variables, one with a piezometric head and the other with the operational well locations and the corresponding pumping rates. The binary variables representing the well locations are approximated by a continuous variable leading to two LP subproblems. Having started with a random value for all decision variables, the two subproblems are solved iteratively until convergence is achieved. The performance and ability of the proposed method are tested against a hypothetical problem from the literature and the results are presented and compared with those obtained using a mixed-integer nonlinear programming method. The results show the efficiency and effectiveness of the proposed method for solving practical groundwater management problems.
Jets from neutron star X-ray binaries: towards a unified scheme

Abstract Systematic multi-wavelength studies of neutron stars (NSs) have shown a jet and disk-jet coupling phenomenology which resembles, although with some important differences, that observed in black holes; ultra-relativistic transient ejection, steady compact jets, accretion-ejection cycles are indeed observed in NSs. I will review our observational knowledge of jet in NS X-ray binaries, focusing on the role of the parameters of the system which might be involved in the production of jets. First, I will discuss the role of the accretion rate, presenting a unified scheme for accretion-jet production throughout the different sub-classes of low-magnetic field NSs. Then, I will attempt to (make the first steps to) quantify the role of spin and magnetic field in powering the jet.
Improved numerical inverse kinematics for human pose estimation

We propose a real-time pose estimation method that addresses the weaknesses of the numerical inverse kinematics method. Using conventional inverse kinematics based on the numerical method requires many iterations; moreover, a singularity in the Jacobian matrix as well as a local minimum problem can occur. To solve these problems, we propose an inverse kinematics method combined with an unscented Kalman filter (UKF) to recover intermediate joint information. Because the numerical inverse kinematics method optimizes a state, the solution can often converge to the local minimum and require many iterations. We use several sigma points for analysis to find the optimum state by using an unscented transform. The improved method using a UKF converges faster than the numerical inverse kinematics method for the global minimum of the existing inverse kinematics. We use 2-D image processes to extract body areas from the input images, and a 3-D reconstruction algorithm is used to estimate the 3-D positions of the extracted human body area. Using the improved method, we generate intermediate joints for each body part and the results show that the proposed method reduces the computational complexity and increases the accuracy of estimation compared to conventional numerical inverse kinematics.
WiCRF: Weighted Bimodal Constrained LiDAR Odometry and Mapping With Robust Features

Accurate localization is a fundamental capability of autonomous driving systems, and LiDAR has been widely used for localization systems in recent years due to its high reliability and accuracy. In this paper, we propose a robust and accurate LiDAR SLAM, which innovates feature point extraction and motion constraint construction. For feature extraction, the proposed adaptive point roughness evaluation based on geometric scaling effectively improves the stability and accuracy of feature points (plane, line). Then, outliers are removed with a dynamic threshold filter, which improves the accuracy of outlier recognition. For motion constraint construction, the proposed weighted bimodal least squares is employed to optimize the relative pose between current frame and point map. The map stores both 3D coordinates and vectors (principal or normal vectors). Using vectors in current frame and point map, bimodal reprojection constraints are constructed. And all constraints are weighted according to the neighboring vector distribution in the map, which effectively reduces the negative impact of vector errors on registration. Our solution is tested in multiple datasets and achieve better performance in terms of accuracy and robustness.
Calculated magnetocrystalline anisotropy of a FePd ordered alloy: Electron-density dependence on the direction of magnetization

The magnetocrystalline anisotropy energy of a CuAu(I) ${\mathrm{Fe}}_{50}{\mathrm{Pd}}_{50}$ alloy has been calculated by using a full potential linear augmented planar wave (FLAPW) method. The tetragonal unit-cell distances have been extracted from the x-ray data of ordered FePd films grown by sputtering technique [P. Caro, A. Cebollada, D. Ravelosona, F. Briones, D. Garc\'{\i}a, M. V\'azquez, and A. Hernando, J. Appl. Phys. 81, 5050 (1997)]. This ordered alloy presents a high uniaxial magnetic anisotropy with an easy magnetization direction oriented along the tetragonal axis (c axis) of its unit cell. We reproduce the measured uniaxial character as well as the magnitude of its magnetic anisotropy. Three ground-state configurations have been calculated attending to the direction of the magnetization relative to the c axis: 0\ifmmode^\circ\else\textdegree\fi{}, 45\ifmmode^\circ\else\textdegree\fi{}, and 90\ifmmode^\circ\else\textdegree\fi{}. The comparison among these states enables us to describe the changes of the electronic density associated to the changes of the direction of the magnetization.
Surveillance of Severe Acute Respiratory Infection and Influenza Vaccine Effectiveness among Hospitalized Italian Adults, 2021/22 Season

Following an extremely low incidence of influenza during the first waves of the ongoing COVID-19 pandemic, the 2021/22 Northern Hemisphere winter season saw a resurgence of influenza virus circulation. The aim of this study was to describe epidemiology of severe acute respiratory infections (SARIs) among Italian adults and estimate the 2021/22 season influenza vaccine effectiveness. For this purpose, a test-negative case-control study was conducted in a geographically representative sample of Italian hospitals. Of 753 SARI patients analyzed, 2.5% (N = 19) tested positive for influenza, most of which belonged to the A(H3N2) subtype. Phylogenetic analysis showed that these belonged to the subclade 3C.2a1b. 2a.2, which was antigenically different from the 2021/22 A(H3N2) vaccine component. Most (89.5%) cases were registered among non-vaccinated individuals, suggesting a protective effect of influenza vaccination. Due to a limited number of cases, vaccine effectiveness estimated through the Firth’s penalized logistic regression was highly imprecise, being 83.4% (95% CI: 25.8–97.4%) and 83.1% (95% CI: 22.2–97.3%) against any influenza type A and A(H3N2), respectively. Exclusion of SARS-CoV-2-positive controls from the model did not significantly change the base-case estimates. Within the study limitations, influenza vaccination appeared to be effective against laboratory-confirmed SARI.
QTL for yield per plant under water deficit and well-watered conditions and drought susceptibility index in soybean (Glycine max (L.) Merr.)

Abstract Drought has historically represented the greatest abiotic stress to adversely affect the stability of soybean (Glycine max (L.) Merr. ) yields in non-irrigated field conditions. To investigate the genetic basis underlying drought tolerance in soybean, we screened the seed yield per plant (YP) in a natural diversity panel of 149 accessions under both water deficit (drought-stressed; YP-S) and well-watered (full irrigation; YP-W) conditions in field and greenhouse trials and calculated a drought susceptibility index (DSI) based on the differences in yield between treatments within each accession. A total of 19 quantitative trait loci (QTLs) were identified: eight were significantly associated with YP-W, 10 were associated with YP-S, 2 were associated with DSI and one QTL was associated with both YP-S and DSI. We then compared QTLs identified here with previously reported markers and found that these loci were located in regions associated with yield-related and other agronomic traits. In particular, YP-S-associated single nucleotide polymorphism (SNP) ss246509299 in chromosome (Chr.) 8, and YP-W-associated ss249310678 on Chr. 17 were both previously correlated with canopy wilt. Eight significant QTLs were located within eight genes. Glyma.18g092200, contained ss249600231 and annotated as GmWRKY168, is reportedly responsive to cadmium. This study helps to resolve which loci contribute to yield under drought stress in soybean, and can potentially serve as markers for selection of elite, high-yield and drought tolerant varieties.
Field performance of cryopreserved seed-derived tomato plants and post-thaw survival of viral-infected meristems

The effectiveness of different cryopreservation techniques of tomato meristems isolated from viral-infected plants ‘Irishka’ cultivar was determined. The pieces of stem were protected with dimethyl sulfoxide and propylene glycol and cooled in vapour phase of liquid nitrogen (–170 °C). For the vitrification and droplet-vitrification protocols, the meristems were treated with loading solution and dehydrated with different plant vitrification solutions (PVS1 modified, PVS2, 88 % PVS3, PVSN). The samples were placed to sterilized aluminum foil pieces, in 1.2 ml cryovials or in 50 µl aluminum pans for differential scanning calorimetry and were directly immersed into liquid nitrogen. Acсording to the dehydration technique, the meristems were dehydrated with sterile airflow for 120 min. The post-thaw survival rates of meristems (from 34.2 to 78.5 %) were observerved only for 50 µl aluminum pans and airflow dehydration. We determined the productivity of plants, obtaned from cryopreserved seeds (‘Seven’, ‘Potiron Ecarlate’ and ‘Druzhba’ cultivars). We observed increasing in total and marketable yields for the plants grown from the cryopreserved seeds for all the cultivars. Total number of diseased plants decreased by 33 % for ‘Seven’, for ‘Potiron Ecarlate’ it did by 6.7 %, for that of ‘Druzhba’ the total percentage of sick and healthy plants did not differ after seeds cryopreservation.