Miracle-dz/UniFAR-FTUs huggingface dataset:
Transformers in Vision: A Survey

Astounding results from Transformer models on natural language tasks have intrigued the vision community to study their application to computer vision problems. Among their salient benefits, Transformers enable modeling long dependencies between input sequence elements and support parallel processing of sequence as compared to recurrent networks, e.g., Long short-term memory. Different from convolutional networks, Transformers require minimal inductive biases for their design and are naturally suited as set-functions. Furthermore, the straightforward design of Transformers allows processing multiple modalities (e.g., images, videos, text, and speech) using similar processing blocks and demonstrates excellent scalability to very large capacity networks and huge datasets. These strengths have led to exciting progress on a number of vision tasks using Transformer networks. This survey aims to provide a comprehensive overview of the Transformer models in the computer vision discipline. We start with an introduction to fundamental concepts behind the success of Transformers, i.e., self-attention, large-scale pre-training, and bidirectional feature encoding. We then cover extensive applications of transformers in vision including popular recognition tasks (e.g., image classification, object detection, action recognition, and segmentation), generative modeling, multi-modal tasks (e.g., visual-question answering, visual reasoning, and visual grounding), video processing (e.g., activity recognition, video forecasting), low-level vision (e.g., image super-resolution, image enhancement, and colorization), and three-dimensional analysis (e.g., point cloud classification and segmentation). We compare the respective advantages and limitations of popular techniques both in terms of architectural design and their experimental value. Finally, we provide an analysis on open research directions and possible future works. We hope this effort will ignite further interest in the community to solve current challenges toward the application of transformer models in computer vision.
Rotated odometers

We describe the infinite interval exchange transformations, called the rotated odometers, which are obtained as compositions of finite interval exchange transformations and the von Neumann–Kakutani map. We show that with respect to Lebesgue measure on the unit interval, every such transformation is measurably isomorphic to the first return map of a rational parallel flow on a translation surface of finite area with infinite genus and a finite number of ends. We describe the dynamics of rotated odometers by means of Bratteli–Vershik systems, derive several of their topological and ergodic properties, and investigate in detail a range of specific examples of rotated odometers.
SetSketch: Filling the Gap between MinHash and HyperLogLog

MinHash and HyperLogLog are sketching algorithms that have become indispensable for set summaries in big data applications. While HyperLogLog allows counting different elements with very little space, MinHash is suitable for the fast comparison of sets as it allows estimating the Jaccard similarity and other joint quantities. This work presents a new data structure called SetSketch that is able to continuously fill the gap between both use cases. Its commutative and idempotent insert operation and its mergeable state make it suitable for distributed environments. Fast, robust, and easy-to-implement estimators for cardinality and joint quantities, as well as the ability to use SetSketch for similarity search, enable versatile applications. The presented joint estimator can also be applied to other data structures such as MinHash, HyperLogLog, or Hyper-MinHash, where it even performs better than the corresponding state-of-the-art estimators in many cases.
Design and Actuator Optimization of Lightweight and Compliant Knee Exoskeleton for Mobility Assistance of Children with Crouch Gait

Pediatric exoskeletons offer great promise to increase mobility for children with crouch gait caused by cerebral palsy. A lightweight, compliant and user-specific actuator is critical for maximizing the benefits of an exoskeleton to users. To date, pediatric exoskeletons generally use the same actuators as adult exoskeletons, which are heavy and resistive to natural movement. There is yet no easy way for robotic exoskeletons to accommodate the changes in design requirements that occur as a child ages. We developed a lightweight (1.65 kg unilateral mass) and compliant pediatric knee exoskeleton with a bandwidth of 22.6 Hz that can provide torque assistance to children with crouch gait using high torque density motor. Experimental results demonstrated that the robot exhibited low mechanical impedance (1.79 Nm average backdrive torque) under the unpowered condition and 0.32 Nm with zero-torque tracking control. Root mean square (RMS) error of torque tracking result is less than 0.73 Nm (5.7% with respect to 12 Nm torque). To achieve optimal age-specific performance, we proposed the first optimization framework that considered both motor and transmission of the actuator system that can produce optimal settings for children between 3 and 18 years old. The optimization generated an optimal motor air gap radius that monotonically increases with age from 0.011 to 0.033 meters, and optimal gear ratio varies from 2.6 to 11.6 (3-13 years old) and 11.6 to 10.2 (13-18 years old), leading to actuators of minimal mass.
Organic‐Inorganic Nanocomposite Membranes as High Temperature Proton Exchange Membranes for a Direct Dimethyl Ether Fuel Cell Application

Abstract Nafion/poly(phenylmethyl silsequioxane) (PPSQ)/calcium hydroxyphosphate (CHP) and Nafion/PPSQ composite membranes are fabricated using homogeneous dispersive mixing and a solvent casting method for direct dimethyl ether fuel cell (DDMEFC) applications for use above 100°C. The recast composite membranes were characterized by means of scanning electron microscopy (SEM), X‐ray diffraction (XRD) analysis, and thermogravimetry (TGA). The results showed that PPSQ and CHP are compatible with the Nafion membrane and improve the initial degradation temperature of the Nafion membrane. In addition, the crystallinity calculated by a Gaussian peak deconvolution technique increases as the PPSQ and CHP increase in composite membranes. This composite membrane showed less fuel crossover compared to both the recast Nafion membrane and Nafion 115. This is likely to be due to the high crystallinity and low water uptake content in the composite membranes. On the other hand, the fuel crossover of the composite membrane impregnating CHP increased as the CHP content increased. This is related to the hydrophilic character of CHP. In addition, the proton conductivity of the composite membranes containing PPSQ and CHP appeared to be higher that of the Nafion membrane at a high temperature. Nafion/PPSQ/CHP and Nafion/PPSQ composite membranes showed better cell performances compared to Nafion 115 at temperatures ranging from 100°C to 120°C and at pressures from 1 atm to 2 atm.
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning

This work addresses adversarial robustness in deep learning by considering deep networks with stochastic local winner-takes-all (LWTA) nonlinearities. This type of network units result in sparse representations from each model layer, as the units are organized in blocks where only one unit generates non-zero output. The main operating principle of the introduced units lies on stochastic arguments, as the network performs posterior sampling over competing units to select the winner. We combine these LWTA arguments with tools from the field of Bayesian non-parametrics, specifically the stick-breaking construction of the Indian Buffet Process, to allow for inferring the sub-part of each layer that is essential for modeling the data at hand. Inference for the proposed network is performed by means of stochastic variational Bayes. We perform a thorough experimental evaluation of our model using benchmark datasets, assuming gradient-based adversarial attacks. As we show, our method achieves high robustness to adversarial perturbations, with state-of-the-art performance in powerful white-box attacks.
Learning General Policies from Small Examples Without Supervision

Generalized planning is concerned with the computation of general policies that solve multiple instances of a planning domain all at once. It has been recently shown that these policies can be computed in two steps: first, a suitable abstraction in the form of a qualitative numerical planning problem (QNP) is learned from sample plans, then the general policies are obtained from the learned QNP using a planner. In this work, we introduce an alternative approach for computing more expressive general policies which does not require sample plans or a QNP planner. The new formulation is very simple and can be cast in terms that are more standard in machine learning: a large but finite pool of features is defined from the predicates in the planning examples using a general grammar, and a small subset of features is sought for separating"good"from"bad"state transitions, and goals from non-goals. The problems of finding such a"separating surface"while labeling the transitions as"good"or"bad"are jointly addressed as a single combinatorial optimization problem expressed as a Weighted Max-SAT problem. The advantage of looking for the simplest policy in the given feature space that solves the given examples, possibly non-optimally, is that many domains have no general, compact policies that are optimal. The approach yields general policies for a number of benchmark domains.
Culturable and Total Fungi in Dust Accumulated in Air Ducts in Single‐Family Houses

Abstract Fungal spore content in dust accumulated in air ducts was investigated in 24 mechanically ventilated single-family houses of which 15 had also a central air heating system. Dust was collected from the ducts simultaneously with cleaning of the ventilation systems. Besides spore concentrations and flora of culturable fungi, total fungal spore concentrations were determined in dust samples by the aqueous two-phase technique and spore counting with epifluorescence microscopy. Culturable spore concentrations in the dust varied from 104 to 107 CFU/g and total spore concentrations from 107 to 108 spores/g. Total spore concentrations in the duct dust were significantly higher in the air heated houses than in the other mechanically ventilated houses. The difference resulted mainly from a higher proportion of recirculation air and a higher age of the air heated houses. Cladosporium, Penicillium, Aspergillus and yeasts consisted of >90% of fungal flora in the dust. Although total spore concentrations were at the same level both in the exhaust and in the supply ducts in both types of house, culturable fungal spore concentrations were slightly higher in the exhaust ducts than in the supply ducts. The proportion of culturable spores was <5% of total spores in dust accumulated in the ducts.
Feature selection by a genetic algorithm. Application to seed discrimination by artificial vision

Abstract: Genetic algorithms (GAs) are efficient search methods based on theparadigm of natural selection and population genetics. A simple GA was appliedfor selecting the optimal feature subset among an initial feature set of larger size.The performances were tested on a practical pattern recognition problem, whichconsisted on the discrimination between four seed species (two cultivated andtwo adventitious seed species) by artiÐcial vision. A set of 73 features, describingsize, shape and texture, were extracted from colour images in order to character-ise each seed. The goal of the GA was to select the best subset of features whichgave the highest classiÐcation rates when using the nearest neighbour as a classi-Ðcation method. The selected features were represented by binary chromosomeswhich had 73 elements. The number of selected features was directly related tothe probability of initialisation of the population at the Ðrst generation of theGA. When this probability was Ðxed to 0E1, the GA selected about Ðve features.The classiÐcation performances increased with the number of generations. Forexample, 6E25% of the seeds were misclassiÐed by using Ðve features at gener-ation 140, whereas another subset of the same size led to 3% misclassiÐcation atgeneration 400. The present work shows the great potential of GAs for featureselection (dimensionality reduction) problems. 1998 SCI.(J Sci Food Agric 76,77E86 (1998)Key words: feature selection; genetic algorithm; seed; colour image analysis;classiÐcation; discrimination
Optimization of application of nitrogen fertilizers to increase the yield and improve the quality of Chinese cabbage heads

Abstract The study investigates the effects of nitrogen fertilizers on the characteristics of the autumn crop of Chinese cabbage. The rates applied varied from 0 to 225 kg ha−1 (N0, N45, N90, N135, N180, N225); the supply of phosphorus and potassium fertilizers was similar in the all trials, 90 and 150 kg ha−1, respectively. It was found that the optimum nitrogen fertilization rate for the autumn crop of Chinese cabbage was N135. In the case of lower nitrogen rates the yield decreased and the cabbage heads were smaller. Further increase in fertilizer rate (>N135) resulted in a higher percentage of non-standard cabbage heads, while the yield remained almost unchanged compared with N135. The total plant mass of cabbage crop fertilized with N135 was 76 t ha−1; plant residues constituted 33 t ha−1 (43% of the total mass). The yield of market quality cabbage heads was 30 t ha−1 (70% of all the heads produced); the rest of heads were loose, not formed or rot-infected. The optimal amount of total mineral nitrogen (the sum of nitrogen present in the 0–60 cm soil layer and the nitrogen supplied with fertilizers) before planting was 260 kg ha−1. When nitrogen rates were higher than N180 the quality of cabbage heads in terms of the content of vitamin C, nitrates, soluble solids, total solids and sugars decreased.
Steam Volatile Terpenoids from Salvia leucantha

Abstract The essential oil from the aerial parts of Salvia leucantha Cav. (Lamiaceae) was analyzed by GC, GC/MS and NMR spectroscopy. The oil was found rich in sesquiterpene hydrocarbons; β-caryophyllene (13.9%), α-guaiene (12.6%), cis-muurola-3,5-diene (10.8%), germacrene D (13.8%) and bicyclogermacrene (8.7%). Bornyl acetate constituted 23.9% of the oil. This is the first detailed report on the essential oil composition based on capillary GC and GC/MS analyses.
Optimization of Farmyard Manure to Substitute Mineral Fertilizer for Sustainable Productivity and Higher Carbon Sequestration Potential and Profitability under Gardenpea-French Bean Cropping System in the Indian Himalayas

Carbon sequestration potential (CSP) and sustainability of gardenpea-french bean cropping system was assessed with farmyard manure (FYM) application vis-à-vis mineral fertilization as recommended NPK (NPK) and integrated nutrient management practices (INM) after six years’ cropping in Indian Himalayas. Application of 20 tons FYM ha−1 provided highest CSP (0.527 Mg C ha−1 year−1) in soil and sustainability index. With the help of quadratic equations, it was estimated that maximum profit (optimum yield) and turn over of invested money could be achieved with application of 20.0 and 15.6 t FYM ha−1, respectively. Application of 5.9 and 8.9 tons FYM ha−1 would substitute NPK and INM, respectively. Pod number plant−1 was the most important yield-contributing attribute as found from principal component analysis. Pod yield could be modelled through multiple linear equation with help of yield attributes.
An agri-environmental phosphorus saturation index for acid coarse-textured soils.

Potato (Solanum tuberosum L.) is a high P demanding crop contributing to P saturation of acid coarse-textured soils. The P status is commonly assessed agronomically by soil testing of P (STP) and environmentally by soil P saturation or P solubility indexes. The aim of this work was to develop a P fertilizer recommendation model integrating P environmental risk and crop response probability, using P and Al extracted by the Mehlich-III soil testing method (mg P or Al L 1 of soil) and expressed as (P/Al) M-III percentage. The environmentally critical (P/Al) M III percentage was 15%, corresponding to the critical degree of phosphate saturation (DPS) value of 25% (oxalate extraction procedure) proposed in the Netherlands. Using the Cate-Nelson procedure, the critical (P/Al) M III percentage across 78 field experiments was 8.2% as determined by inductively coupled-argon plasma (ICP). Probability of potato response to P was close to 100% even above the critical STP values as shown by power tests on relative yields. The P recommendation model was computed from conditional expectations of 50 and 80% within each fertility group below 15% as (P/Al) M III+ Above 15%, the model recommended 21 kg P ha ', the amount of P exported by a tuber harvest of approximately 42 Mg ha '. Using conversion equations with 114 soil samples for STP methods, fertility groups built for Quebec acid coarse-textured soils were found to be comparable with those currently used in the Netherlands and Lower Saxony (Germany). The (P/Al) M III percentage provided a reliable and unifying criterion for making environmentally acceptable and agronomically efficient P recommendations for sustainable potato production.
Constrained formation of 2-(1-(arylimino)ethyl)-7-arylimino-6,6-dimethylcyclopentapyridines and their cobalt(II) chloride complexes: synthesis, characterization and ethylene polymerization

A series of 2-(1-(arylimino)ethyl)-7-arylimino-6,6-dimethylcyclopentapyridine derivatives (L1-L5) was synthesized, and individually reacted with cobalt(II) chloride to form the corresponding cobalt chloride complexes (C1-C4). These compounds were characterized, and the single crystal X-ray diffraction for two representative cobalt complexes was carried out. The molecular structures indicate that 2,7-bis(arylimino)cyclopentapyridines act as tridentate ligands; however, one of the Co-N coordinative bonds is weak due to the spatial separation of nitrogen atoms. Upon activation with either MAO or MMAO, all cobalt complexes exhibit catalytic activities toward ethylene. Polymerization takes place in the presence of MAO with activities of approximately 10(4) g of PE per (mol of Co) per h, but oligomerization occurs in the presence of MMAO with the activities higher by one order of magnitude. The resultant products, either polyethylenes or oligomers, display high linearity. Relatively low activities observed for cobalt complexes discussed reflect the importance of the appropriate spatial arrangement of the three donor nitrogen atoms.
Isothermal and Nonisothermal Evaporation from Four Sandy Soils of Different Water Repellency

Soil water evaporation is an important component of the surface energy balance. Evaporation also affects plant available water content of soil. Soil wettability is known to affect water-holding capacity and water flow, but the impact of soil water repellency on evaporation has not been thoroughly investigated. The objective of the study was to measure and analyze isothermal and nonisothermal evaporation rates for four sandy soils showing different degrees of water repellency. Eight vertical soil columns (two of each soil) were exposed to isothermal conditions (20 ± 1°C), and another eight soil columns were exposed to nonisothermal conditions. During the nonisothermal experiment, the top boundary temperature was held constant at 21°C, and the bottom boundary temperature was constant at 55°C, thus maintaining a constant thermal gradient. After 195 d of evaporation, each column was sectioned to determine the soil water content distribution along its axis. A numerical model based on the Philip-de Vries theory was used to predict soil water flow. Deviations between predicted and measured values increased with increasing contact angle. Isothermal cumulative evaporation was 25% lower for water repellent soil than for the most wettable soil. Nonisothermal cumulative evaporation was 75% larger than isothermal evaporation for the wettable soil but only 14% larger than isothermal evaporation of the most water repellent soil. Evaporation and residual water contents, especially in the surface layer, were found to be strongly affected by soil wettability.
The Brightness of VisorSat-Design Starlink Satellites

The mean of 430 visual magnitudes of VisorSats adjusted to a distance of 550-km (the operational altitude) is 5.92 +/-0.04. This is the characteristic brightness of these satellites when observed at zenith. VisorSats average 1.29 magnitudes fainter than the original-design Starlink satellites and, thus, they are
Refining activation downsampling with SoftPool

Convolutional Neural Networks (CNNs) use pooling to decrease the size of activation maps. This process is crucial to increase the receptive fields and to reduce computational requirements of subsequent convolutions. An important feature of the pooling operation is the minimization of information loss, with respect to the initial activation maps, without a significant impact on the computation and memory overhead. To meet these requirements, we propose SoftPool: a fast and efficient method for exponentially weighted activation downsampling. Through experiments across a range of architectures and pooling methods, we demonstrate that SoftPool can retain more information in the reduced activation maps. This refined downsampling leads to improvements in a CNN’s classification accuracy. Experiments with pooling layer substitutions on ImageNet1K show an increase in accuracy over both original architectures and other pooling methods. We also test SoftPool on video datasets for action recognition. Again, through the direct replacement of pooling layers, we observe consistent performance improvements while computational loads and memory requirements remain limited1.
Successive Null-Space Precoder Design for Downlink MU-MIMO with Rate Splitting and Single-Stage SIC

In this paper, we consider the precoder design for an under-loaded or critically loaded downlink multi-user multiple-input multiple-output (MU-MIMO) communication system. We propose novel precoding and decoding schemes which enhance system performance based on rate splitting at the transmitter and single-stage successive interference cancellation at the receivers. The proposed successive null-space (SNS) precoding scheme utilizes linear combinations of the null-space basis vectors of the successively augmented MIMO channel matrices of the users as precoding vectors to adjust the inter-user-interference experienced by the receivers. We formulate a non-convex weighted sum rate (WSR) optimization problem, and solve it via successive convex approximation to obtain a suboptimal solution for the precoding vectors and the associated power allocation. Our simulation results reveal that the proposed SNS precoders outperform block diagonalization based linear and rate splitting designs, and in many cases, have a relatively small gap to the maximum sum rate achieved by dirty paper coding.