Miracle-dz/UniFAR-FTUs huggingface dataset:
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning

Recent advances in distributed optimization have shown that Newton-type methods with proper communication compression mechanisms can guarantee fast local rates and low communication cost compared to first order methods. We discover that the communication cost of these methods can be further reduced, sometimes dramatically so, with a surprisingly simple trick: Basis Learn (BL). The idea is to transform the usual representation of the local Hessians via a change of basis in the space of matrices and apply compression tools to the new representation. To demonstrate the potential of using custom bases, we design a new Newton-type method (BL1), which reduces communication cost via both BL technique and bidirectional compression mechanism. Furthermore, we present two alternative extensions (BL2 and BL3) to partial participation to accommodate federated learning applications. We prove local linear and superlinear rates independent of the condition number. Finally, we support our claims with numerical experiments by comparing several first and second order methods.
Categorical Difference and Related Brain Regions of the Attentional Blink Effect

Attentional blink (AB) is a biological effect, showing that for 200 to 500 ms after paying attention to one visual target, it is difficult to notice another target that appears next, and attentional blink magnitude (ABM) is a indicating parameter to measure the degree of this effect. Researchers have shown that different categories of images can access the consciousness of human mind differently, and produce different ranges of ABM values. So in this paper, we compare two different types of images, categorized as animal and object, by predicting ABM values directly from image features extracted from convolutional neural network (CNN), and indirectly from functional magnetic resonance imaging (fMRI) data. First, for two sets of images, we separately extract their average features from layers of Alexnet, a classic model of CNN, then input the features into a trained linear regression model to predict ABM values, and we find higher-level instead of lower-level image features determine the categorical difference in AB effect, and midlevel image features predict ABM values more correctly than low-level and high-level image features. Then we employ fMRI data from different brain regions collected when the subjects viewed 50 test images to predict ABM values, and conclude that brain regions covering relatively broader areas, like LVC, HVC and VC, perform better than other smaller brain regions, which means AB effect is more related to synthetic impact of several visual brain regions than only one particular visual regions.
Weakly saturated hypergraphs and a conjecture of Tuza

Given a fixed hypergraph H , let wsat(n,H) denote the smallest number of edges in an nvertex hypergraph G, with the property that one can sequentially add the edges missing from G, so that whenever an edge is added, a new copy of H is created. The study of wsat(n,H) was introduced by Bollobás in 1968, and turned out to be one of the most influential topics in extremal combinatorics. While for most H very little is known regarding wsat(n,H), Alon proved in 1985 that for every graph H there is a limiting constant CH so that wsat(n,H) = (CH + o(1))n. Tuza conjectured in 1992 that Alon’s theorem can be (appropriately) extended to arbitrary r-uniform hypergraphs. In this paper we prove this conjecture.
A cross-modal fusion network based on self-attention and residual structure for multimodal emotion recognition

The audio-video based multimodal emotion recognition has attracted a lot of attention due to its robust performance. Most of the existing methods focus on proposing different cross-modal fusion strategies. However, these strategies introduce redundancy in the features of different modalities without fully considering the complementary properties between modal information, and these approaches do not guarantee the non-loss of original semantic information during intra- and inter-modal interactions. In this paper, we propose a novel cross-modal fusion network based on self-attention and residual structure (CFN-SR) for multimodal emotion recognition. Firstly, we perform representation learning for audio and video modalities to obtain the semantic features of the two modalities by efficient ResNeXt and 1D CNN, respectively. Secondly, we feed the features of the two modalities into the cross-modal blocks separately to ensure efficient complementarity and completeness of information through the self-attention mechanism and residual structure. Finally, we obtain the output of emotions by splicing the obtained fused representation with the original representation. To verify the effectiveness of the proposed method, we conduct experiments on the RAVDESS dataset. The experimental results show that the proposed CFN-SR achieves the state-of-the-art and obtains 75.76% accuracy with 26.30M parameters. Our code is available at https://github.com/skeletonNN/CFN-SR.
Brain-inspired Cognition in Next-generation Racetrack Memories

Hyperdimensional computing (HDC) is an emerging computational framework inspired by the brain that operates on vectors with thousands of dimensions to emulate cognition. Unlike conventional computational frameworks that operate on numbers, HDC, like the brain, uses high-dimensional random vectors and is capable of one-shot learning. HDC is based on a well-defined set of arithmetic operations and is highly error resilient. The core operations of HDC manipulate HD vectors in bulk bit-wise fashion, offering many opportunities to leverage parallelism. Unfortunately, on conventional von Neumann architectures, the continuous movement of HD vectors among the processor and the memory can make the cognition task prohibitively slow and energy intensive. Hardware accelerators only marginally improve related metrics. In contrast, even partial implementations of an HDC framework inside memory can provide considerable performance/energy gains as demonstrated in prior work using memristors. This article presents an architecture based on racetrack memory (RTM) to conduct and accelerate the entire HDC framework within memory. The proposed solution requires minimal additional CMOS circuitry by leveraging a read operation across multiple domains in RTMs called transverse read (TR) to realize exclusive-or (XOR) and addition operations. To minimize the CMOS circuitry overhead, an RTM nanowire-based counting mechanism is proposed. Using language recognition as the example workload, the proposed RTM HDC system reduces the energy consumption by 8.6× compared to the state-of-the-art in-memory implementation. Compared to dedicated hardware design realized with an FPGA, RTM-based HDC processing demonstrates 7.8× and 5.3× improvements in the overall runtime and energy consumption, respectively.
Multi-Cue Adaptive Emotion Recognition Network

Expressing and identifying emotions through facial and physical expressions is a significant part of social interaction. Emotion recognition is an essential task in computer vision due to its various applications and mainly for allowing a more natural interaction between humans and machines. The common approaches for emotion recognition focus on analyzing facial expressions and requires the automatic localization of the face in the image. Although these methods can correctly classify emotion in controlled scenarios, such techniques are limited when dealing with unconstrained daily interactions. We propose a new deep learning approach for emotion recognition based on adaptive multi-cues that extract information from context and body poses, which humans commonly use in social interaction and communication. We compare the proposed approach with the state-of-art approaches in the CAER-S dataset, evaluating different components in a pipeline that reached an accuracy of 89.30%
Discovering and Exploiting Sparse Rewards in a Learned Behavior Space

Learning optimal policies in sparse rewards settings is difficult as the learning agent has little to no feedback on the quality of its actions. In these situations, a good strategy is to focus on exploration, hopefully leading to the discovery of a reward signal to improve on. A learning algorithm capable of dealing with this kind of settings has to be able to (1) explore possible agent behaviors and (2) exploit any possible discovered reward. Exploration algorithms have been proposed that require the definition of a low-dimension behavior space, in which the behavior generated by the agent's policy can be represented. The need to design a priori this space such that it is worth exploring is a major limitation of these algorithms. In this work, we introduce STAX, an algorithm designed to learn a behavior space on-the-fly and to explore it while optimizing any reward discovered. It does so by separating the exploration and learning of the behavior space from the exploitation of the reward through an alternating two-step process. In the first step, STAX builds a repertoire of diverse policies while learning a low-dimensional representation of the high-dimensional observations generated during the policies evaluation. In the exploitation step, emitters optimize the performance of the discovered rewarding solutions. Experiments conducted on three different sparse reward environments show that STAX performs comparably to existing baselines while requiring much less prior information about the task as it autonomously builds the behavior space it explores.
EFFICACY OF ESTRUS SYNCHRONIZATION PROTOCOLS IN NON-DESCRIPT CATTLE OF AZAD JAMMU AND KASHMIR DURING NON-BREEDING AND BREEDING SEASONS

The objective of the present study was to compare the efficacy of estrus synchronization protocols through estrus response and fertility rate in non-descript cattle of Azad Jammu and Kashmir during the non-breeding and breeding seasons. A total of 312 non-descript cows (192) and heifers (120) with body condition score ranging between 3.0 to 3.5 were randomly assigned to receive Ovsynch (159), CIDR alone (74) and CO-Synch+CIDR (79) protocols. Animals were inseminated at 16 h after the second GnRH injection in Ovsynch, and 48 h after CIDR removal in CIDR alone and COSynch+CIDR groups. The results revealed that during non-breeding season, the tendency for success of the Ovsynch protocol was higher in terms of inducing heat and conception rate (CR) in non-descript cows under farm (87.5%) and field (50.0%) conditions compared to CIDR alone and CO-Synch+CIDR groups (P<0.05). Whereas, in the case of nondescript heifers, the CO-Synch+CIDR protocol significantly increased the CR at timed artificial insemination (TAI) under farm (50.0%) and field (33.33%) conditions compared to Ovsynch and CIDR alone groups (P<0.05). During the breeding season, CR/TAI was almost similar in all groups of non-descript cows under field conditions (P>0.05). COSynch+CIDR treatment yielded the higher conception rates (46.15%) in non-descript heifers compared to Ovsynch and CIDR alone groups. It is concluded that treatment of cows with Ovsynch, and heifers with CO-Synch+CIDR protocols may lead to higher CR/TAI and thus have the potential to improve the reproductive performance that can accelerate the rate of genetic improvement through AI.
Backcasting for a Sustainable Future: The Impact After 10 Years

"Backcasting for a sustainable future: the impact after 10 years" is the first book that systematically investigates the follow-up and spin-off of various participatory backcasting experiments seven to ten years after completion. Backcasting literally means looking back from a desirable future that is constructed first. Since the 1990s sustainable futures and system innovations towards sustainability have been explored in participatory backcasting experiments, numerous stakeholders have been involved and first steps have been planned in line with the envisioned sustainable futures. A methodological framework for participatory backcasting is developed, as well as a conceptual framework. The latter uses various concepts and theories from Leitbilder or future visions, actor learning, stakeholder participation, as well as industrial network theory and institutional theory. Three case studies from the Netherlands are described, each consisting of a backcasting experiment and its follow-up and spin-off after ten years: (1) Novel Protein Foods and meat alternatives; (2) Sustainable Households and Nutrition; and (3) Multiple Sustainable Land-use in rural areas. The cases show that participatory backcasting may, but does not automatically lead to substantial follow-up and spin-off at the level of niches or sets of related niches in the research, business, government and public domains. Various factors are identified that affect the emergence and the extent of follow-up and spin-off; these factors can be both internal and external to the backcasting experiment. Follow-up and spin-off are constituted by networks of actors that have been successful in mobilising sufficient resources for establishing the activities. Future visions from the backcasting experiment provide guidance and orientation to follow-up and spin-off in a decentralised way; they show both stability and flexibility during the emergence of follow-up and spin-off, and are influenced by dynamics like exits and entries in the supporting networks
Nutritional Requirements During Training for Special Operation Forces – An Observational Study

Background: Responses to exercise training can vary greatly between individuals. For special operation forces, low responses to training can hamper performance. In this study, we objectively measured strength and fitness during special operation forces training, and assessed potential determinants of the training response. Methods: Twenty subjects were enrolled, and measurements were taken before and after a 9-week training program. Muscular strength was measured as one-repetition-maximum on four instruments, and physical fitness by the Cooper-test. Body composition was measured using deuterium dilution, physical activity by accelerometry and diet quality by food records. Level of significance was p<0.05. Results: During the 9-week training period, body strength increased by 0.33±0.24 N/kg (+7%, P<0.001, and physical fitness increased by 3.5±3.4 mL/min/kg (+6%, P=0.001). Gains in strength were inversely associated with strength at baseline, and positively with activity intensity during the training program. We observed no effect of training on body weight, but body composition was significantly different at follow-up as compared to baseline (16.9±2.5% to 14.9±2.5% body fat, P=0.03). Energy intake was 4491±506 kcal/d and energy balance was -243±306 kcal/d (P=0.04). Average physical activity level was 2.6±0.2 and the average duration of moderate-to-vigorous physical activity was 5:53±0:36h. Over time, physical activity did not change significantly. After adjustment for underreporting, intakes of vitamin C and D were insufficient on average and for most participants.Conclusions: Improvements in strength were modulated by strength prior to the intervention, and moderate-to-vigorous physical activity during the training. Thus, compensatory declines in physical activity may hamper the effectiveness of the exercise program.
Multimodal feedback cues on manual lifting in virtual environments

Improper manipulation of real-world objects increases the risk of developing work- related back injuries. In an effort to reduce such a risk and encourage appropriate lifting and moving methods, a Virtual Environment (VE) was employed. Virtual simulations can be used for ergonomic analysis. In this work, the VEs made use of multiple feedback techniques to allow a person to estimate the forces acting on their lower back. A person's head and hand movements were tracked in real-time whilst manipulating an object. A NIOSH lifting equation was used to calculate and determine the Lifting Index whereby the results were conveyed in real time. Visual display feedback techniques were designed and the effect of cues to enhance user performance was experimentally evaluated. The feedback cues provide the user with information about the forces acting on their lower back as they perform manual lifting tasks in VEs. Four different methods were compared and contrasted: No Feedback, Text, Colour and Combined Colour and Text. This work also investigated various types of auditory feedback technique to support object manipulation in VEs. Auditory feedback has been demonstrated to convey information in computer applications effectively, but little work has been reported on the efficacy of such techniques, particularly for ergonomic design. Four different methods were compared and contrasted: No Feedback, White-noise, Pitch and Tempo. A combined Audio-Visual (AV) technique was also examined by mixing both senses. The effect of Tactile Augmentation was also examined. Three different weights (real) were used and the results obtained by experiment were compared with the experiment using virtual weights in order to evaluate whether or not the presence of a real weighted object enhanced people's sense of realism. The goals of this study were to explore various senses of feedback technique (visual, auditory and tactile), compare the performance characteristics of each technique and understand their relative advantages and drawbacks.
ROLE OF CONSUMER PSYCHOLOGICAL STUDIES IN FAST FOOD INDUSTRY

This study examines the behavior of consumer in fast food industry. The customer psychology strongly effected from other customer’s word of mouth, review’s and pricing policy of a company. In this study, we examine the consumer psychology with three factors (referent price, referent deservingness and fair pricing). The three factors become a cause to reduce the anger of consumer and due to this customer satisfy from the operations of fast food industry. We distribute more than 300 questionnaire for analyze our research hypothesis. After analyze we conclude that referent price does not impact on customer anger but it impact on satisfaction of customer. The referent deservingness and price fairness has significant impact on anger of customer and satisfaction of customer. This study provides useful information to fast food sector regarding customer psychology.
Using biomechanical constraints to improve video-based motion capture

In motion capture applications whose aim is to recover human body postures from various input, the high dimensionality of the problem makes it desirable to reduce the size of the search-space by eliminating a priori impossible configurations. This can be carried out by constraining the posture recovery process in various ways. Most recent work in this area has focused on applying camera viewpoint-related constraints to eliminate erroneous solutions. When camera calibration parameters are available, they provide an extremely efficient tool for disambiguating not only posture estimation, but also 3D reconstruction and data segmentation. Increased robustness is indeed to be gained from enforcing such constraints, which we prove in the context of an optical motion capture framework. Our contribution in this respect resides in having applied such constraints consistently to each main step involved in a motion capture process, namely marker reconstruction and segmentation, followed by posture recovery. These steps are made inter-dependent, where each one constrains the other. A more application-independent approach is to encode constraints directly within the human body model, such as limits on the rotational joints. This being an almost unexplored research subject, our efforts were mainly directed at determining a new method for measuring, representing and applying such joint limits. To the present day, the few existing range of motion boundary representations present severe drawbacks that call for an alternative formulation. The joint limits paradigm we propose not only overcomes these drawbacks, but also allows to capture intra- and inter-joint rotation dependencies, these being essential to realistic joint motion representation. The range of motion boundary is defined by an implicit surface, its analytical expression enabling us to readily establish whether a given joint rotation is valid or not. Furthermore, its continuous and differentiable nature provides us with a means of elegantly incorporating such a constraint within an optimisation process for posture recovery. Applying constrained optimisation to our body model and stereo data extracted from video sequence, we demonstrate the clearly resulting decrease in posture estimation errors. As a bonus, we have integrated our joint limits representation in character animation packages to show how motion can be naturally constrained in this manner.
The Skin Properties of Sites Predisposed to Pressure Ulcers in Bedridden Elderly Patients: A Cross-sectional Study

Background: Previous studies have not specifically measured skin characteristics at common sites of pressure ulcers in high-risk older patients. Therefore, this study aimed to clarify the physiological skin characteristics at common pressure ulcer sites and their relationship with pressure ulcer risk and demographic/laboratory data in bedridden older Japanese patients. Methods: Fifty-five older patients (32 female) with a mean age of 82.4 ± 9.8 years (range, 61-103 years) in a long-term care facility and 25 female Japanese university students with a mean age of 21.4 ± 1.3 years (range, 20-22 years) were recruited for the study. Skin surface temperature, epidermal water content, transepidermal water loss (TEWL), skin erythema/redness, skin elasticity, and skin thickness were measured noninvasively and compared between age groups. The sacral and two heel areas were evaluated as they constitute sites predisposed to pressure ulcers, while the mid-to-lower back area was designated as the control site. Additionally, the correlation between demographic/laboratory data and skin physiological indices was determined. Results: Elderly patients showed a low epidermal water content at both heels (right heel, 14.8 ± 9.1 arbitrary units, AU.; left heel, 14.4 ± 8.3 AU). TEWL remained acceptable at all sites in older patients despite the presence of dry skin (back, 7.1 ± 1.8 g/hm2; sacrum, 7.4 ± 3.0 g/hm2; right heel, 17.7 ± 7.1 g/hm2; left heel, 19.4 ± 8.1 g/hm2). Back (0.61 ± 0.13 AU) and sacral (0.67 ± 0.11 AU) skin elasticity and sacral skin thickness (0.97 ± 0.56 cm) were significantly lower than those of healthy young people (0.86 ± 0.04 AU, 0.87 ± 0.05 AU, and 2.27 ± 0.84 cm, respectively; p < .001 for all sites). Moderate positive correlations were observed between back skin elasticity and serum albumin level (r = .445, p < .001), and between sacral skin thickness and BMI (r = .506, p < .001) in older patients. Conclusions: Older patients have a lower epidermal water content and skin elasticity and thickness but not higher TEWL at sites predisposed to pressure ulcers. Moderate correlations were found between skin characteristics and demographic/laboratory data.
Creativity and invention exemplified in the development of a new instrument

A new instrument for nondestructive testing of metals uses a four-point probe and a sensitive electronics package to measure the resistivity and to detect cracks and voids. Both the development of the instrument and its implementation as a product are relatively well documented. The inventive process was very brief and straightforward. An attempt is made to explore what was the inventive act in the development of this instrument, and what made the invention occur when it did. It is concluded that both the technology and the user needs were well established and widely known for at least 15 years before the inventors came along and put the pieces together; thus the key ingredient added in 1982 was the inventor. <<ETX>>