Miracle-dz/UniFAR-FTUs huggingface dataset:
Current Status of Weed Resistance to Herbicides in Rice-Wheat Cropping System in Haryana and its Management

Rice-wheat (R-W) is the most important cropping system in India. Modern technology embedded with dwarf varieties, assured irrigation facilities and improved input supply contributed to an impressive increase in the productivity of this cropping system particularly in North-West India. However, evolution ofresistance in Phalaris minor against isoproturon (Malik and Singh, 1995) aggravated the situation. The resistance affected area ranged between 0.8 and 1.0 million hectares in N-W India mostly contained in the states of Punjab (0.3 m ha) and Haryana (0.5–0.6 m ha) (Franke, 2002). Due to large-scale failure, recommendation of isoproturon was withdrawn and it was replaced with three alternate herbicides (clodinafop, fenoxaprop and sulfosulfuron) in 1997–98. These alternate herbicides brought the P minor infestation under control and restored wheat yield to its previous levels. But, use of alternate herbicides is not a sure one-way bet. Due to possibilities of resistance, if these herbicides not used properly, a gulf exists between risks and benefits. Yadav et al. (2002a, 2005) have already reported red signals of resistance against these alternate herbicides in few biotypes of P minor. Diagnostic survey conducted across eight districts involving 419 farmers in R-W belt of Haryana indicated that large number of farmers (8% in case of sulfosulfuron and 36% in case of clodinafop) used lower than the recommanded dose of herbicides and lower spray volumes and most fanners applied these herbicides using knapsack sprayer fitted with a single flood jetlcut or hollow cone nozzle instead of flat fan nozzle. Only 18% farmers sprayed these herbicides at 30–35 days after sowing (DAS) of whcat and rest 36 and 46% applied them at 35–40 and 40–50 DAS, respectivly. Around 45% farmers either did not know about herbicide rotation or they did not follow it. The use of fenoxaprop has already declined considerably and the level of satisfaction regarding performance of sulfosulfuron and clodinafop is also decreasing year after year. A majority of the growers (79%) blame herbicides available with different brand names in the state for poor quality and thereby poor efficacy. However, faulty spray and wheat seed contamination with Phalaris seeds are other serious problems. There are many brands not recommended by the concerned state university, are available in the market. Growers are unaware about the many of products they are using. Reduction in prices of many brands is being used as sole weapon to enhance sale of different products by various market forces. Looking into the present scenario, it seems that in near future, the problem of herbicide resistance in this weed may again pose a serious threat to the sustainability of wheat productivity. lmmediate steps are required to tackle this problem by in:egrating all possible resistance management option (Malik et al., 1998, 2002; Yadav and Malik, 2005).
Radio-loud narrow-line Seyfert 1 galaxies with high-velocity outflows

Abstract We have studied four radio-loud Narrow-line Seyfert 1 (NLS1) galaxies with extreme optical emission-line shifts, indicating radial outflow velocities of up 2450 km s−1. The shifts are accompanied by strong line broadening, up to 2270 km s−1 in [NeV]. A significant ionization stratification (higher line shift at higher ionization potential) of most ions implies that we see a large-scale wind rather than single, localized jet-cloud interactions. The observations are consistent with a scenario, where the signatures of outflows are maximized because of a pole-on view into the central engine of these radio-loud NLS1 galaxies.
Temporal Reasoning for RDF(S): A Markov Logic based Approach

In this work, we propose a formalism that is suitable to carry out temporal reasoning for probabilistic knowledge bases. In particular, we focus on detecting erroneous statements by exploiting temporal relations of facts. Therefore, we rely on RDF(S) and its associating entailment rules which provide a data representation model as well as a basic logical expressiveness. Moreover, we use Allen 19s interval algebra to express the relations of facts based on their associated temporal information. We carry out reasoning by transforming the statements and constraints to Markov Logic and compute the most probable consistent state (MAP inference) with respect to the defined constraints. Moreover, we evaluate the proposed approach in order to demonstrate its practicality and flexibility.
Relating Molecular Dynamics Simulations to Functional Activity for Gly-Rich Membranolytic Helical Kiadin Peptides

Kiadins are in silico designed peptides with a strong similarity to diPGLa-H, a tandem sequence of PGLa-H (KIAKVALKAL) and with single, double or quadruple glycine substitutions. They were found to show high variability in their activity and selectivity against Gram-negative and Gram-positive bacteria, as well as cytotoxicity against host cells, which are influenced by the number and placing of glycine residues along the sequence. The conformational flexibility introduced by these substitutions contributes differently peptide structuring and to their interactions with the model membranes, as observed by molecular dynamics simulations. We relate these results to experimentally determined data on the structure of kiadins and their interactions with liposomes having a phospholipid membrane composition similar to simulation membrane models, as well as to their antibacterial and cytotoxic activities, and also discuss the challenges in interpreting these multiscale experiments and understanding why the presence of glycine residues in the sequence affected the antibacterial potency and toxicity towards host cells in a different manner.
Testing Distributed Parameter Hypotheses for the Detection of Climate Change.

A general statistical methodology, based on testing alternative distributed parameter hypotheses, is proposed as a method for deciding whether or not anthropogenic influences are causing climate change. This methodology provides a framework for including known uncertainties in the definition of the hypotheses by allowing model parameters to be specified by probability distributions and thereby allowing the definition of more realistic hypotheses. The method can be used to derive the unique statistical test that minimizes errors in test conclusions. The method is applied to illustrative detection problems by first defining alternative hypotheses for global mean temperature; second, deriving the most powerful test and calculating its statistics; third, applying the test to observed temperature records; and finally, illustrating the test statistics and results on a receiver or relative operating characteristic curve showing the relation between false positive and false negative test errors. It is demonstrated, with an illustrative example, that proper accounting for the uncertainty in all the parameters can produce very different statistical conclusions than the conclusions that would be obtained by simply fixing some parameters at nominal values.
Landscape(T): A Robust and Low-cost Sensor Positioning System Using the Dual of Target Tracking

References [1] S. Julier and J. Uhlmann, “Unscented Filtering and Nonlinear Estimation”, Proc. of the IEEE, Vol. 92, No. 3, March 2004 [2] L. Zhang et al., “A Novel Distributed Sensor Positioning System Using the Dual of Target Tracking”, online technical report, http://www.cs. iusb.edu/~liqzhang/Liqiang_Landscape. pdf (A short version published in IEEE WiMob’05). [3] Y. Shang et al., “Localization from Connectivity in Sensor Networks”, IEEE Transactions on Parallel and Distributed Systems, Vol. 15, No. 11, November 2004.  The state (3D position) of the ith sensor at the nth iteration is: xi(n) = {xi1(n), xi2(n), xi3(n)}.  For static sensors, the state and observation equations are: xi(n+1) = xi(n) + wi(n), yi(n) = ((Δ xi1(n)) + (Δ xi2(n)) + (Δ xi3(n))) + vi(n), where yi(n) is the observed distance between the nth beacon and the ith sensor, Δ xi1(n) = x1(n) xi1(n), Δ xi2(n) = x2(n) xi2(n), Δ xi3(n) = x3(n) xi3(n), and (x1(n), x2(n), x3(n)) is the 3D position of the nth beacon. wi(n) and vi(n) are noise sequences. Online dynamic state estimation:
Scaled InAlN/GaN HEMT on Sapphire With fT/fmax of 190/301 GHz

In this brief, a scaled In<inline-formula> <tex-math notation="LaTeX">$_{{0}. {17}}$ </tex-math></inline-formula>Al<inline-formula> <tex-math notation="LaTeX">$_{{0}. {83}}\text{N}$ </tex-math></inline-formula>/GaN high-electron-mobility transistor (HEMT) was fabricated on sapphire substrate with 47-nm <inline-formula> <tex-math notation="LaTeX">${T}$ </tex-math></inline-formula>-gate length, 300-nm source–drain distance, and selective area regrown <inline-formula> <tex-math notation="LaTeX">$\text{n}^{+}$ </tex-math></inline-formula>-GaN. The device exhibits cutoff frequencies <inline-formula> <tex-math notation="LaTeX">${f}_{\text {T}}/{f}_{\text {max}}$ </tex-math></inline-formula> of 190/301 GHz, which gives a record sqrt (<inline-formula> <tex-math notation="LaTeX">${f}_{\text {T}} \times {f}_{\text {max}}{)}$ </tex-math></inline-formula> = 239 GHz among reported Ga-polar GaN-on-sapphire HEMTs. The device shows a maximum current density, a peak external direct current transconductance, and an <inline-formula> <tex-math notation="LaTeX">${I}_{\text {on}}/{I}_{\text {off}}$ </tex-math></inline-formula> ratio of 1.45 A/mm, 610 mS/mm, and <inline-formula> <tex-math notation="LaTeX">$2.9\times 10^{6}$ </tex-math></inline-formula>, respectively. Drain-induced barrier lowering of 75 mV/V is measured at <inline-formula> <tex-math notation="LaTeX">${I}_{\text {ds}}$ </tex-math></inline-formula> = 1 mA/mm between <inline-formula> <tex-math notation="LaTeX">${V}_{\text {ds}}$ </tex-math></inline-formula> = 1 V and 5 V. The three-terminal OFF-state breakdown voltage is 14.7 V. The effective electron velocity of the 2-D electron gas (2DEG) under the gate foot is estimated to be <inline-formula> <tex-math notation="LaTeX">$1.4\times 10^{7}$ </tex-math></inline-formula> cm/s. These characteristics of this Ga-polar millimeter wave (mm-wave) GaN-on-sapphire HEMT are comparable with those state-of-the-art counterparts on SiC substrates.
Estimating the Interferometric Vertical Wavenumber From Range Shifts

The estimation of the interferometric vertical wavenumber over sloped terrain is an integral step for many interferometric and tomographic synthetic aperture radar (SAR) applications. The state of the art for this estimation is to calculate the angle of incidence and the local terrain slope after geometric corregistration has been performed. In this letter, an alternative approach for estimating the vertical wavenumber is proposed that requires only the estimation of the range corregistration shifts. This considerably simplifies the calculation effort without compromising the estimation performance. The proposed approach is demonstrated on Advanced Land Observing Satellite (ALOS) phased array L-band synthetic aperture radar (PALSAR) data and compared against the conventional methodology.
Nonlinear Dynamics of Prestressed Panels in Low Supersonic Turbulent Flow

It is known that the aeroelastic stability of elastic plates significantly decreases in low supersonic flow. A further reduction may arise due to compressive in-plane loads, which can be caused by deformations of the adjacent structure. Thus, this is an important subject in the design of supersonic aircraft or rockets. Encouraged by recent studies that have shown an increase in aerodynamic damping due to a turbulent boundary layer, the present study applies three different aerodynamic models coupled with the von Karman plate equation to show that there is as well a significant enlargement of the static stability regions of a flat plate subjected to quasi-static in-plane loads at Mach 1.2. However, it has also been found that, despite a turbulent boundary layer, the critical dynamic pressure for flutter almost drops to zero if the in-plane load approaches the critical load for Euler buckling. Further analysis on postcritical flutter revealed that a flexible panel subjected to a boundary layer behaves simil.
Structuring middle-class aspirations: the role of place-based habitus and higher education

Abstract This qualitative case study provides an analysis of the structuring of middle-class aspirations at one rural university in the United States. Using a Bourdieusian framework offered by Zipin and colleagues, findings suggest that although student participants in our study are similarly positioned relative to social class background, those from distinct geographic areas (i.e. rural and urban) displayed key differences in expressions of college-going and future aspirations. We argue that place, as an important feature of one’s habitus, structures students’ college-going and future aspirations. Within the highly stratified context of higher education in the United States, few scholars have acknowledged the power of geography and place in shaping behaviors, choices, and possibilities for students. In doing so, this research contributes to a growing global body of literature examining the role of place in shaping students’ higher education aspirations, access, experiences, and outcomes.
Annihilators of Skew Derivations with Engel Conditions on Lie Ideals

Let R be a prime ring, L a noncentral Lie ideal of R, and a ∈ R. Set [x, y]1 = [x, y] = xy − yx for x, y ∈ R and inductively [x, y]k = [[x, y]k−1, y] for k > 1. Suppose that δ is a nonzero σ-derivation of R such that a[δ(x), x]k = 0 for all x ∈ L, where σ is an automorphism of R and k is a fixed positive integer. Then a = 0 except when char R = 2 and R ⊆ M2(F), the 2 × 2 matrix ring over a field F.
Diagnosis and Management of Malnutrition in Patients with Heart Failure

Heart failure is a disease with an increasingly greater prevalence due to the aging population, the development of new drugs, and the organization of healthcare processes. Malnutrition has been identified as a poor prognostic factor in these patients, very often linked to frailty or to other comorbidities, meaning that early diagnosis and treatment are essential. This paper reviews some important aspects of the pathophysiology, detection, and management of malnutrition in patients with heart failure.
Effects of ultrasound-induced stress on gut microbiota of mice

Background and Aim: Prolonged stress causes deleterious effects on both the organism and its microbiota. In this study, we examined the effects of exposure to variable frequency ultrasound (US) on the gut microbiota-liver-brain axis of mice. Materials and Methods: This study was conducted on 20 mature clinically healthy sexually naive C57BL/6J male mice (42–45 days old). Group 1 (Normal) consisted of healthy intact mice (n = 10). Group 2 (Stress) consisted of mice subjected to US-induced stress (n = 10) for 20 days with alternating frequencies (20–45 kHz). Stool samples were collected on days 0, 10, and 20, and the corresponding DNA was later subjected to 16SrRNA sequencing. After mice were sacrificed on day 21, the leukocyte count, blood serum biochemical parameters, and liver and brain antioxidant status were measured. Behavioral testing was performed on days 17, 18, and 19. Results: Ultrasound lead to higher stress and anxiety levels; increase in creatinine by 8.29% and gamma-glutamyltransferase activity by 5 times, a decrease in alkaline phosphatase activity by 38.23%, increase of de Ritis coefficient by 21.34%; increased liver and brain superoxide dismutase level by 20.8% and 21.5%, respectively; the stress-related changes in the gut microbiota composition – Bacteroidaceae and Firmicutes. Conclusion: Subjecting mice to 20 days of US-induced stress leads to systemic disorders due to oxidative stress and a decrease in the diversity of the gut microbiota.
Azimuth Estimation of Swimming Fish by Artificial Lateral Line System

Localization and sensing in the underwater environment has been a significant but difficult problem in the field of robotics. The lateral line system (LLS) is an essential component of underwater localization and sensing for most fish. Inspired by the LLS, scientists have designed varieties of artificial lateral line systems (ALLSs) and researched their applications. This paper investigates on using ALLS for azimuth sensing in a wide range of distance and angle, even in all directions, between two robotic fish. Specifically, we consider the scenario when a robotic boxfish with ALLS stays still and uses its ALLS to obtain the flow signals, while a carangidae robotic fish swims around it freely. To estimate the azimuth of the swimming robot, first, the fast Fourier transform (FFT) and discrete wavelet transformation (DWT) are adopted to pre-process the ALLS’s data and analyze the quantity of the data. Then, two analysis model methods are proposed, that is, phase difference-based method and intensity-based method. Under the guidance of the above two methods, we adopt a recurrent neural network (RNN) to estimate the azimuth. The experimental results show that bases on ALLS and RNN, we are able to estimate the azimuth of swimming robotic fish in a wide range of around 7 times the size of the sensor array and in all directions.
Advanced Manufacturing in Industry 5.0: A Survey of Key Enabling Technologies and Future Trends

A revolution in advanced manufacturing has been driven by digital technology in the fourth industrial revolution, also known as Industry 4.0, and has resulted in a substantial increase in profits for the industry. In a new paradigm of Industry 5.0, advanced manufacturing will step further and be capable of offering customized products and a better user experience. A number of key enabling technologies are expected to play crucial roles in assisting Industry 5.0 in meeting higher demands of data acquisition and processing, communications, and collaborative robots in the advanced manufacturing process. The aim of this survey is to provide novel insights into advanced manufacturing in Industry 5.0 by summarizing the latest progress of key enabling technologies, such as artificial intelligence of things (AIoT), beyond 5G communications, and collaborative robotics. Finally, key directions for future research to enable this vision to become a reality, such as the industrial metaverse, are outlined.
Oriented Infrared Vehicle Detection in Aerial Images via Mining Frequency and Semantic Information

Infrared vehicle detection based on aerial images has significant applications in military and civilian fields for the perception ability under low-light and foggy conditions. However, it remains challenging due to the following characteristics. First, infrared textures and edges are blurred, implying a plenty of low-frequency signals and a shortage of detailed descriptions. Second, objects in infrared images present different patterns depending on their thermal radiations, which hamper the feature extraction of convolution kernels. Third, infrared images lack color information, which means that fewer features for classification and regression can be used. Inspired by cognitive neuroscience that humans perceive the entirety from low-frequency information and discern details from high-frequency information, we devise a new framework for oriented infrared vehicle detection called infrared information mining detector (I2MDet) to tackle the above challenges. It consists of two significant designs: the kaleidoscope module and the semantic feature supplement module (SFSM). In the kaleidoscope module, we explore the effect of kernel sizes and dilation rates on frequency information mining with kaleidoscope-like equivalent kernels. Features in this module are extracted by adaptive involution operators instead of convolution kernels to deal with multiple patterns. The SFSM provides the network with features beneficial for classification and regression. On the one hand, the network is guided to learn more meaningful features under semantic supervision. On the other hand, features output by the SFSM supplement the detection head with semantic information. Experimental results on the public dataset DroneVehicle demonstrate that our proposed approach achieves outstanding performance on oriented infrared vehicle detection.
Multiscale Deblurred Feature Extraction Network for Automatic Four-Rod Target Detection in MRTD Measuring Process of Thermal Imagers

The minimum resolvable temperature difference (MRTD) at which a four-rod target can be resolved is a critical parameter used to assess the comprehensive performance of thermal imaging systems, which is important for technological innovation in military and other fields. Recently, there have been some attempts to use an automatic objective approach based on deep learning to take the place of the classical manual subjective MRTD measurement approach, which is strongly affected by the psychological subjective factors of the experimenter and is limited in accuracy and speed. However, the scale variability of four-rod targets and the low pixels of infrared thermal cameras have turned out to be a challenging problem for automatic MRTD measurement. We propose a multiscale deblurred feature extraction network (MDF-Net), a backbone based on a yolov5 neural network, in an attempt to solve the aforementioned problem. We first present a global attention mechanism (GAM) attention module to represent strong images of the four-rod targets. Next, a Rep VGG module is introduced to decrease the blur. Our experiments show that the proposed method achieves the desired effect and state-of-the-art detection results, which innovatively improve the accuracy of four-rod target detection to 82.3% and thus make it possible for the thermal imagers to see further and to respond faster and more accurately.
Implementation of an edge-fog-cloud computing IoT architecture in aircraft components

This paper presents a deployment of an IoT architecture in aircraft wings based on a physical asset, three IoT platforms, MATLAB® on a personal computer and ThingSpeak as a cloud. The IoT architecture was designed considering five layers and implemented using a simple wireless sensor network. Temperature, humidity, air quality and air pressure were collected, pre-processed and visualised in real-time to improve the reliability of aircraft components. The results show that embedding sensory capability into wing components can create a smart ecosystem that will support different IoT-enabled services in-flight, and it can also be used for predictive maintenance purposes. Graphical abstract
Channel-Level Event-Triggered Communication Scheme for Path Tracking Control of Autonomous Ground Vehicles With Distributed Sensors

In this article, a channel-level event-triggered communication scheme is investigated for path tracking control of autonomous ground vehicles via an in-vehicle network to ensure path tracking performance while reducing network resource utilization. First, a path tracking system is established considering the effect of norm bounded uncertainty on lateral vehicle dynamics, and a state feedback path tracking controller is designed within the Takagi–Sugeno fuzzy framework. Next, a decentralized event-triggered communication scheme is adopted between the sensors and controller, which makes it possible to save communication resources at the channel level. Finally, the results in the CarSim-Simulink joint-simulation environment show that the proposed controller can ensure a reliable path tracking performance in both lateral offset and heading error. At the same time, compared with the simple time-triggered scheme, the proposed method can effectively reduce the usage of communication resources by more than 80%.