Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotion Detection Deficits and Decreased Empathy in Patients with Alzheimer’s Disease and Parkinson’s Disease Affect Caregiver Mood and Burden

Background: Changes in social cognition occur in patients with Alzheimer’s disease (AD) and Parkinson’s disease (PD) and can be caused by several factors, including emotion recognition deficits and neuropsychiatric symptoms (NPS). The aims of this study were to investigate: (1) group differences on emotion detection between patients diagnosed with AD or PD and their respective caregivers; (2) the association of emotion detection with empathetic ability and NPS in individuals with AD or PD; (3) caregivers’ depression and perceived burden in relation to patients’ ability to detect emotions, empathize with others, presence of NPS; and (4) caregiver’s awareness of emotion detection deficits in patients with AD or Parkinson. Methods: In this study, patients with probable AD (N = 25) or PD (N = 17), and their caregivers (N = 42), performed an emotion detection task (The Awareness of Social Inference Test—Emotion Evaluation Test, TASIT-EET). Patients underwent cognitive assessment, using the Behavioral Neurology Assessment (BNA). In addition, caregivers completed questionnaires to measure empathy (Interpersonal Reactivity Index, IRI) and NPS (Neuropsychiatric Inventory, NPI) in patients and self-reported on depression (Geriatric Depression Scale, GDS) and burden (Zarit Burden Interview, ZBI). Caregivers were also interviewed to measure dementia severity (Clinical Dementia Rating (CDR) Scale) in patients. Results: The results suggest that individuals with AD and PD are significantly worse at recognizing emotions than their caregivers. Moreover, caregivers failed to recognize patients’ emotion recognition deficits and this was associated with increased caregiver burden and depression. Patients’ emotion recognition deficits, decreased empathy and NPS were also related to caregiver burden and depression. Conclusions: Changes in emotion detection and empathy in individuals with AD and PD has implications for caregiver burden and depression and may be amenable to interventions with both patients and caregivers.
A Novel Recurrent Neural Network for Manipulator Control With Improved Noise Tolerance

In this paper, we propose a novel recurrent neural network to resolve the redundancy of manipulators for efficient kinematic control in the presence of noises in a polynomial type. Leveraging the high-order derivative properties of polynomial noises, a deliberately devised neural network is proposed to eliminate the impact of noises and recover the accurate tracking of desired trajectories in workspace. Rigorous analysis shows that the proposed neural law stabilizes the system dynamics and the position tracking error converges to zero in the presence of noises. Extensive simulations verify the theoretical results. Numerical comparisons show that existing dual neural solutions lose stability when exposed to large constant noises or time-varying noises. In contrast, the proposed approach works well and has a low tracking error comparable to noise-free situations.
Perspectives on ruminant nutrition and metabolism. II. Metabolism in ruminant tissues

Abstract The discovery of the dominance of short-chain fatty acids as energy sources in the 1940s and 1950s, as discussed in part I of this review (Annison & Bryden, 1998) led to uncertainties concerning the interrelationships of glucose and acetate in ruminant metabolism. These were resolved in the following decade largely by use of 14C-labelled substrates. Although only small amounts of glucose are absorbed in most dietary situations, glucose availability to ruminant tissues as measured by isotope dilution was shown to be substantial, indicating that gluconeogenesis is a major metabolic activity in both fed and fasted states. Studies with 14C-labelled glucose and acetate revealed that in contrast to non-ruminants, acetate and not glucose is the major precursor of long-chain fatty acids in ruminant tissues. Interest in the measurement of energy metabolism in livestock grew rapidly from the 1950s. Most laboratories adopted indirect calorimetry and precise measurements of the energy expenditure of ruminants contributed to the development of new feeding systems. More recently, alternative approaches to the measurement of energy expenditure have included the use of NMR spectroscopy, isotope dilution and the application of the Fick principle to measure O2 consumption in the whole animal and in defined tissues. The refinement of the classical arterio-venous difference procedure in the study of mammary gland metabolism in the 1960s, particularly when combined with isotope dilution, encouraged the use of these methods to generate quantitative data on the metabolism of a range of defined tissues. The recent introduction of new methods for the continuous monitoring of both blood flow and blood O2 content has greatly increased the precision and scope of arterio-venous difference measurements. The impact of data produced by these and other quantitative procedures on current knowledge of the metabolism of glucose, short-chain fatty acids and lipids, and on N metabolism, is outlined. The role of the portal-drained viscera and liver in N metabolism is discussed in relation to data obtained by the use of multi-catheterized animals. Protein turnover, and the impact of stress (physical, social and disease related) on protein metabolism have been reviewed. The growth of knowledge of mammary gland metabolism and milk synthesis since the first quantitative studies in the 1960s has been charted. Recent findings on the regulation of amino acid uptake and utilization by the mammary gland, and on the control of milk secretion, are of particular interest and importance.
A view model of API economy in city platform as a service

Computer and communication technologies are leveraging IoT, the Internet of Things. The radical digital transformation empowered by IoT has paved the way of innovating service engineering in the context of cyber-physical space. There is a wide range of opportunities of the API economy using IoT. However, a systematic methodology to assist service engineering in the scope of the API economy is still underexplored. The author presents a view model of the API economy to facilitate API development in a smart city platform. Then, the author discusses transition paths to deal with chasms between different layers of the API economy. Finally, the author discusses the scalability view of APIs.
HiMap: A hierarchical mapping approach for enhancing lifetime reliability of dark silicon manycore systems

Technology scaling into the nano-scale CMOS regime has resulted in increased leakage and roadblock on voltage scaling, which has led to several issues like high power density and elevated on-chip temperature. This consequently aggravates device aging, compromising lifetime reliability of the manycore systems. This paper proposes HiMap, a dynamic hierarchical mapping approach to maximize lifetime reliability of manycore systems while satisfying performance, power, and thermal constraints. HiMap is process variation- and aging-aware. It comprises of two levels: (1) it identifies a region of cores suitable for mapping, and (2) it maps threads in the region and intersperses dark cores for thermal mitigation while considering the current health of the cores. Both the levels strive to reduce aging variance across the chip. We evaluated HiMap for 64-core and 256-core systems. Results demonstrate an improved system lifetime reliability by up to 2 years at the end of 3.25 years of use, as compared to the state-of-the-art.
A New Intrusion Detection System Based on Fast Learning Network and Particle Swarm Optimization

Supervised intrusion detection system is a system that has the capability of learning from examples about the previous attacks to detect new attacks. Using artificial neural network (ANN)-based intrusion detection is promising for reducing the number of false negative or false positives, because ANN has the capability of learning from actual examples. In this paper, a developed learning model for fast learning network (FLN) based on particle swarm optimization (PSO) has been proposed and named as PSO-FLN. The model has been applied to the problem of intrusion detection and validated based on the famous dataset KDD99. Our developed model has been compared against a wide range of meta-heuristic algorithms for training extreme learning machine and FLN classifier. PSO-FLN has outperformed other learning approaches in the testing accuracy of the learning.
The Mechanical Diversity of Stomata and Its Significance in Gas-Exchange Control[OA]

Given that stomatal movement is ultimately a mechanical process and that stomata are morphologically and mechanically diverse, we explored the influence of stomatal mechanical diversity on leaf gas exchange and considered some of the constraints. Mechanical measurements were conducted on the guard cells of four different species exhibiting different stomatal morphologies, including three variants on the classical “kidney” form and one “dumb-bell” type; this information, together with gas-exchange measurements, was used to model and compare their respective operational characteristics. Based on evidence from scanning electron microscope images of cryo-sectioned leaves that were sampled under full sun and high humidity and from pressure probe measurements of the stomatal aperture versus guard cell turgor relationship at maximum and zero epidermal turgor, it was concluded that maximum stomatal apertures (and maximum leaf diffusive conductance) could not be obtained in at least one of the species (the grass Triticum aestivum) without a substantial reduction in subsidiary cell osmotic (and hence turgor) pressure during stomatal opening to overcome the large mechanical advantage of subsidiary cells. A mechanism for this is proposed, with a corollary being greatly accelerated stomatal opening and closure. Gas-exchange measurements on T. aestivum revealed the capability of very rapid stomatal movements, which may be explained by the unique morphology and mechanics of its dumb-bell-shaped stomata coupled with “see-sawing” of osmotic and turgor pressure between guard and subsidiary cells during stomatal opening or closure. Such properties might underlie the success of grasses.
NavigaTone: Seamlessly Embedding Navigation Cues in Mobile Music Listening

As humans, we have the natural capability of localizing the origin of sounds. Spatial audio rendering leverages this skill by applying special filters to recorded audio to create the impression that a sound emanates from a certain position in the physical space. A main application for spatial audio on mobile devices is to provide non-visual navigation cues. Current systems require users to either listen to artificial beacon sounds, or the entire audio source (e.g., a song) is repositioned in space, which impacts the listening experience. We present NavigaTone, a system that takes advantage of multi-track recordings and provides directional cues by moving a single track in the auditory space. While minimizing the impact of the navigation component on the listening experience, a user study showed that participants could localize sources as good as with stereo panning while the listening experience was rated to be closer to common music listening.
Advances in the management of erythropoietic protoporphyria – role of afamelanotide

Erythropoietic protoporphyria (EPP) and the phenotypically similar disease X-linked protoporphyria (XLPP) are inherited cutaneous porphyrias characterized clinically by acute non-blistering photosensitivity, intolerance to sunlight, and significantly reduced quality of life. They are due to marked overproduction of protoporphyrin (PP) chiefly by erythroblasts and reticulocytes. In EPP, the underlying genetic defect is in the ferrochelatase gene, which encodes the final enzyme in the heme synthetic pathway. In XLPP, the genetic defect is a gain-of-function mutation, usually a four-base deletion, in the gene that encodes the enzyme 5-aminolevulinic acid synthase-2, the first and rate-controlling enzyme of heme synthesis in developing red blood cells. The excess PP causes acute and painful photosensitivity, being activated by light in the long ultraviolet to blue spectrum (380–420 nm, the Soret band). Although several treatments have been proposed, presently no very effective treatment exists for EPP or XLPP. Afamelanotide (Scenesse®) is a first-in-class synthetic analog of α-melanocyte stimulating hormone. Afamelanotide mimics the naturally occurring hormone to increase skin pigmentation by increasing melanin production in melanocytes, resulting in increased sunlight tolerance in those with EPP/XLPP. Afamelanotide is currently approved for use in the European Union and Switzerland, and it is under review in the United States by the Food and Drug Administration for use in patients with EPP/XLPP. This paper provides a review of the clinical characteristics and current therapies for EPP/XLPP. We discuss the pharmacology, clinical efficacy, safety, and tolerability of afamelanotide and summarize the results of several key Phase II and III clinical trials. These data indicate that afamelanotide is a promising therapy for those with these debilitating diseases.
A Concept of Synchronous ADPLL Networks in Application to Small-Scale Antenna Arrays

In this paper, we introduce a reconfigurable oscillatory network that generates a synchronous and distributed clocking signal. We propose an accurate model of the network to facilitate the study of its design space and ensure that it operates in its optimal, synchronous mode. The network is designed and implemented in a fully integrated 65-nm CMOS system-on-chip that utilizes coupled all digital phase locked loops interconnected as a Cartesian grid. The model and measurements demonstrate frequency and phase synchronization even in the presence of noise and random initial conditions. This network is proposed for small-scale multiple input multiple-output systems that require complete synchronization both in frequency and in phase.
A 2/3-Approximation Algorithm for Vertex-weighted Matching in Bipartite Graphs

We consider the maximum vertex-weighted matching problem (MVM), in which non-negative weights are assigned to the vertices of a graph, the weight of a matching is the sum of the weights of the matched vertices, and we are required to compute a matching of maximum weight. We describe an exact algorithm for MVM with $O(|V|\, |E|)$ time complexity, and then we design a $2/3$-approximation algorithm for MVM on bipartite graphs by restricting the length of augmenting paths to at most three. The latter algorithm has time complexity $O(|E| + |V| \log |V|)$. The approximation algorithm solves two MVM problems on bipartite graphs, each with weights only on one vertex part, and then finds a matching from these two matchings using the Mendelsohn-Dulmage Theorem. The approximation ratio of the algorithm is obtained by considering failed vertices, i.e., vertices that the approximation algorithm fails to match but the exact algorithm does. We show that at every step of the algorithm there are two distinct heavier vertices that we can charge each failed vertex to. We have implemented the $2/3$-approximation algorithm for MVM and compare it with four other algorithms: an exact MEM algorithm, the exact MVM algorithm, a $1/2$-approximation algorithm for MVM, and a scaling-based $(1-\epsilon)$-approximation algorithm for MEM. We also show that MVM problems should not be first transformed to MEM problems and solved using exact algorithms for the latter, since this transformation can increase runtimes by several orders of magnitude.
Homotopic particle motion planning for humanoid robotics

Exploiting structure is essential to an understanding of motion planning. Here, we exploit the topology of the environment to discover connected components. Inside a connected component, instead of planning one trajectory in configuration space, motion planning can be seen as optimizing a set of homotopically equivalent particle trajectories. In this paper, we will concentrate on the problem of motion planning for a humanoid robot. Our contributions are: i) finding the homotopy classes of a single footstep trajectory in an environment, ii) finding a single footstep trajectory in a single homotopy class formulated as a convex optimization problem, and iii) finding a feasible upper body trajectory given a footstep trajectory, formulated as a set of convex optimization problems. This view provides us with important insights into the difficulty of motion planning, and – under some assumptions – allows us to provide the number of local minima of a given motion planning problem. We demonstrate our approach on a real humanoid platform with 36-dof in a highly restricted environment.
Improved Spatial Collocation and Parallax Correction Approaches for Calibration Accuracy Validation of Thermal Emissive Band on Geostationary Platform

Calibration accuracy validation (CAV) can usually be realized by intercalibration between different satellites. Under the framework of Global Space-Based Intercalibration System (GSICS), two modifications, improved spatial collocation with variable weighting (VW) and parallax correction (PC) approaches, to enhance the CAV performance are proposed. Distinguished from the uniform weighting method recommended by GSICS, the proposed VW one establishes a novel way of overlapping identification and overlapping area computation that is widely suitable for measurements from both the same and different platforms. Simulations indicate that the uncertainty of the VW method behaves better for the collocated targets far away from satellite’s nadir with a certain geolocation error, and is superior to 0.6 K for most overlapping situations when the geolocation error is less than 0.5 pixels. Case application shows that the VW method can significantly alleviate the uncertainty of assessed biases in brightness temperature (BT) by around 0.1–0.3 K for target nonuniformity larger than 2.5%, where the optimal bias estimation can be implemented with its uncertainty as little as possible. Besides the uncertainty improvement, the PC approach has the capability to reduce the bias of CAV by around 0.2–0.3 K, especially for BT range lower than 220 K with a limited number of paired samples. Long-term results show that the monthly biases of FY-2E and FY-2G satellites were superior to 1.5 and 1.0 K, respectively, where the mean monthly absolute biases of FY-2G IR1-IR3 bands were 0.4, 0.6, and 0.5 K, respectively. The proposed VW and PC methods are recommended for GSICS utilization and will further benefit to a more comprehensive community.
Cortical lenticular opacification: distribution and location in a longitudinal study.

PURPOSE To examine the distribution of cortical opacification of the lens by lens quadrant in a longitudinal study. METHODS In 1990, a follow-up assessment of a cohort of Chesapeake Bay watermen, initially studied in 1985, was performed. Four hundred thirty-seven subjects (834 eyes) had gradable cortical photographs for at least one eye in both 1985 and 1990. Cortical photographs were graded by both estimating total area and determining the quadrant with the greatest degree of cortical opacification. RESULTS The prevalence and severity of cortical opacification increased with age with a high degree of concordance (84%) between eyes. For the 47 eyes with cortical opacification > or = 1/8 at baseline, the principal locations of opacification were: inferonasal 63.8%, inferotemporal 17.0%, superonasal 6.4%, and superotemporal 12.8% (P < 0.001, compared with equal distribution by quadrant). Five-year development of new cortical opacification and five-year progression of existing cortical opacification showed even greater preferential occurrence in the inferonasal quadrant of the lens. CONCLUSIONS In this population, the inferonasal quadrant of the lens is the principal site of cortical opacification in both cross-sectional and longitudinal assessment. This finding is consistent with the hypothesis that sunlight exposure is a significant risk factor for cortical opacification.
Stomatal heterogeneity

stomatal conductance’, was induced by applying ABA through the transpiration stream and was detected using Stomatal heterogeneity that is systematic at large starch accumulation and direct visual observation of scales and random at small scales is observed under stomatal apertures. Subsequent studies have found patchy most conditions. The reverse situation, distinguished stomatal conductance in response to many perturbations by the co-ordination of stomatal behaviour at small and have used various techniques to detect it (Beyschlag scales and its disco-ordination at large scales, is and Eckstein, 1998; Pospı́šilová and Šantrůček, 1994; known as ‘patchy stomatal conductance’; it appears Terashima, 1992). to be less common and has yet to be explained Patchy stomatal conductance is interesting for at mechanistically. This phenomenon is reviewed in the least two reasons. Firstly, it can affect the calculation of context of possible mechanisms, and a variety of intercellular CO2 concentration and therefore has importpotential mechanisms are briefly described. Hydraulic ant implications for the interpretation of gas-exchange interactions among stomata are proposed as a mechdata. Secondly, it suggests the existence of previously anism that may explain many aspects of patchiness unsuspected mechanisms, or unrecognized aspects of and are discussed in detail in the context of recent known mechanisms, for stomatal functioning. It is this modelling and experimental work in this area. second aspect of patchy stomatal conductance that provides the focus for this article. Patchy stomatal con
Power factor correction based Hybrid Resonance PWM fed BLDC drive

In this paper a power factor correction (PFC) based Hybrid Resonance Pulse Width Modulation (HRPWM) fed brushless DC motor (BLDC) drive is proposed, analyzed and tested. In this regard, small signal and circuit analysis of HRPWM are calculated in resonance frequency, above-and below-resonance frequency. The control method for regulating DC link voltage is also presented. Furthermore, speed of BLDC motor is controlled by VSI duty cycle variations. Simulation results depict unit power factor, low THD and appropriate speed control.
An Automatically Learning and Discovering Human Fishing Behaviors Scheme for CPSCN

The cyber-physical-social (CPS) computing and networking is a human centric and holistic computing framework which needs to convert the low-level data of physical, cyber, and social worlds into higher level information which can provide insights and help humans make complex decisions. Here, we focus on human fishing behavior recognition for vessel monitoring systems (VMS), an application of CPS. And the recognition of fishing behavior is the key task for studying human fishing activities, monitoring illegal fishing, and protecting fishery resources. However, VMS data basically consist of sequentially recorded position information and do not directly indicate whether a fisherman is fishing or not; thus, converting these low-level CPS data into intuitive information to humans is the primary task. In this paper, an identification model based on multi-step clustering algorithm (MSC-FBI) is proposed to automatically learn and discover fishing behaviors at sea. First, a temporal-spatial distance model is established; then, an improved multi-step clustering algorithm is used to identify human fishing behaviors, and finally, the patterns of different behaviors are extracted from the trajectory, and the unsupervised behavior learning model is established. Using this method, many experiments on different fishing trajectory data were implemented and compared with a traditional identification method based on the Gaussian mixture model (GMM-FBI). The experimental results illustrate the proposed model’s superior performance.