Miracle-dz/UniFAR-FTUs huggingface dataset:
Grazing Soybean to Increase Voluntary Cow Traffic in a Pasture-based Automatic Milking System

Pasture-based automatic milking systems (AMS) require cow traffic to enable cows to be milked. The interval between milkings can be manipulated by strategically allocating pasture. The current experiment investigated the effect of replacing an allocation of grazed pasture with grazed soybean (Glycine max) with the hypothesis that incorporating soybean would increase voluntary cow traffic and milk production. One hundred and eighty mixed age, primiparous and multiparous Holstein-Friesian/Illawarra cows were randomly assigned to two treatment groups (n = 90/group) with a 2×2 Latin square design. Each group was either offered treatments of kikuyu grass (Pennisetum clandestinum Hoach ex Chiov.) pasture (pasture) or soybean from 0900 h to 1500 h during the experimental period which consisted of 2 periods of 3 days following 5 days of training and adaptation in each period with groups crossing over treatments after the first period. The number of cows trafficking to each treatment was similar together with milk yield (mean ≈18 L/cow/d) in this experiment. For the cows that arrived at soybean or pasture there were significant differences in their behaviour and consequently the number of cows exiting each treatment paddock. There was greater cow traffic (more cows and sooner) exiting pasture allocations. Cows that arrived at soybean stayed on the allocation for 25% more time and ate more forage (8.5 kg/cow/d/allocation) relative to pasture (4.7 kg/cow/d/allocation). Pasture cows predominantly replaced eating time with rumination. These findings suggest that replacing pasture with alternative grazeable forages provides no additional incentive to increase voluntary cow traffic to an allocation of feed in AMS. This work highlights the opportunity to increase forage intakes in AMS through the incorporation of alternative forages.
The Impact of Hardware Scheduling Mechanismus on the Performance and Cost of Processor Designs

Hardware schedulers supporting out-of-order execution ar e widespread nowadays. Nevertheless, studies quantifying the impact of schedulers on the performance and cost of processors are rare. The paper tries to close this gap. It turns out that the hardware schedulers can double the performance at a moderate increase (10–24%) in a processor’s gate count. Earlier rearranging of instructio nsallowsfor better performance, but it does not guarantee it. The lack of features like forwarding and non-blocking re sources can nullify this gain. Despite of its out-of-order dispatch capability, the original Scoreboard scheduler, f or example, performs significantly worse than a standard in-order pipeline. The paper also identifies the aspects res ponsible for this poor performance and quantifies their impact. The single most important aspect is the lack of resul t forwarding.
Improving Joint Tracking and Classification with the Transferable Belief Model and terrain information

This paper presents an extension to an existing Joint Tracking and Classification approach for Wireless Sensor Networks. Terrain information and how it restricts target movement is used, along with the estimated target speed, to classify a target using the Transferable Belief Model. When using terrain information, a method is used to take into account the uncertainty of the target position. In addition, a mechanism is added to the Transferable Belief Model to prevent the assignment of belief to outcomes that past behaviour have shown is not possible. The improvements are analysed with the use of three simulated scenarios - the results of which show consistently good classification performance. In each scenario, targets have non-constant velocity trajectories.
Measuring IT security - a method based on common criteria's security functional requirements

A networked defense, and the networked information society, requires both trustworthy information systems and that users and societies trust these systems. Since the trustworthiness of systems depends on the level of IT security, the ability to assess the IT security ability is vital. Currently, there are no efficient methods for establishing the level of IT security in information systems. The main results described in this paper are: a set of security functions needed in systems, based on the security functional requirements of the Common Criteria (CC, 1999) and a method using the set of security functions to assess the securability of components in distributed information systems. Work in progress focuses on system-wide evaluations.
Abnormal Connectional Fingerprint in Schizophrenia: A Novel Network Analysis of Diffusion Tensor Imaging Data

The graph theoretical analysis of structural magnetic resonance imaging (MRI) data has received a great deal of interest in recent years to characterize the organizational principles of brain networks and their alterations in psychiatric disorders, such as schizophrenia. However, the characterization of networks in clinical populations can be challenging, since the comparison of connectivity between groups is influenced by several factors, such as the overall number of connections and the structural abnormalities of the seed regions. To overcome these limitations, the current study employed the whole-brain analysis of connectional fingerprints in diffusion tensor imaging data obtained at 3 T of chronic schizophrenia patients (n = 16) and healthy, age-matched control participants (n = 17). Probabilistic tractography was performed to quantify the connectivity of 110 brain areas. The connectional fingerprint of a brain area represents the set of relative connection probabilities to all its target areas and is, hence, less affected by overall white and gray matter changes than absolute connectivity measures. After detecting brain regions with abnormal connectional fingerprints through similarity measures, we tested each of its relative connection probability between groups. We found altered connectional fingerprints in schizophrenia patients consistent with a dysconnectivity syndrome. While the medial frontal gyrus showed only reduced connectivity, the connectional fingerprints of the inferior frontal gyrus and the putamen mainly contained relatively increased connection probabilities to areas in the frontal, limbic, and subcortical areas. These findings are in line with previous studies that reported abnormalities in striatal–frontal circuits in the pathophysiology of schizophrenia, highlighting the potential utility of connectional fingerprints for the analysis of anatomical networks in the disorder.
Control of entanglement and two-qubit quantum gates with atoms crossing a detuned optical cavity

A scheme is proposed to generate an entangled state between two (Λ-type) four-level atoms that interact effectively by means of a detuned optical cavity and a laser beam that acts perpendicularly to the cavity axis. It is shown how the degree of entanglement for two atoms passing through the cavity can be controlled by manipulating their velocity and the (initial) distance between the atoms. In addition, three realistic schemes are suggested to implement the two-qubit gates within the framework of the suggested atom–cavity–laser setup, namely, the i-swap gate, controlled-Z gate and the controlled- gate. For all these schemes, we analyse and discuss the atomic velocities and inter-atomic distances for which these gates are realized most reliably.
Heterogeneous effects of alcohol on dopamine release in the striatum: a PET study.

BACKGROUND A dopaminergic response to alcohol in humans has not been demonstrated consistently with positron emission tomography (PET). We hypothesized that the effect of alcohol on striatal dopamine (DA) release may be anatomically heterogeneous between subjects. Our approach was to identify voxels that exhibited alcohol-induced DA responses within the striatum, and to determine the relationships between DA responses and alcohol-related behavior. METHODS A novel method was developed to examine the anatomic extent and magnitude of striatal DA responses to alcohol across subjects. Thirteen healthy control subjects underwent 2 PET scans with [11C]raclopride (1 at baseline, 1 with an i.v. alcohol infusion to a target breath alcohol concentration of either 60 or 80 mg%). Parametric images of striatal binding potential (BP) were used to create maps of change in BP (deltaBP, an index of changes in DA levels). The anatomic extent and magnitude of DA responses were determined with voxel extraction methods. Subjective responses ("High," "Intoxication") to the alcohol infusion and behavioral data from the 90-day time-line follow back were assessed for relationships with DA responses to alcohol. RESULTS A voxel-wise t-test between baseline and alcohol BP images did not show any differences in D2/D3 receptor availability between the conditions. Data from the striatal deltaBP maps nevertheless showed that the anatomic extent and magnitude of alcohol-induced DA release in the striatum are correlated with subjective responses to alcohol. CONCLUSIONS The heterogeneity of dopaminergic responses to alcohol across subjects may be a reason for the lack of reports demonstrating DA involvement in alcohol-related behaviors. By allowing for different spatial patterns of DA release within each subject's striata, we showed correlations between alcohol-induced DA release in the striata and behavioral outcomes related to alcohol.
On the Approximability of Sparse PCA

It is well known that Sparse PCA (Sparse Principal Component Analysis) is NP-hard to solve exactly on worst-case instances. What is the complexity of solving Sparse PCA approximately? Our contributions include: 1. a simple and efficient algorithm that achieves ann 1=3 -approximation; 2. NP-hardness of approximation to within (1 "), for some small constant" > 0; 3. SSE-hardness of approximation to within any constant factor; and 4. an exp exp p log logn (“quasi-quasi-polynomial”) gap for the standard semidefinite program.
Utility of quantitative polymerase chain reaction in leptospirosis diagnosis: association of level of leptospiremia and clinical manifestations in Sri Lanka.

BACKGROUND Quantitative polymerase chain reaction (qPCR), despite cost and logistical challenges, has the potential to provide accurate and timely diagnosis for leptospirosis at the point-of-care in endemic areas. We studied optimal sample types for qPCR, timing of sampling, and clinical manifestations in relation to quantitative leptospiremia. METHODS A new qPCR assay using pathogenic Leptospira-specific 16S ribosomal RNA (rRNA) gene Taqman primers and an optimized temperature stepdown protocol was used to analyze patient blood samples. Serum was compared with whole blood as sample source. Quantitative leptospiremia was compared with clinical manifestations of leptospirosis and outcome. RESULTS The diagnostic sensitivity of qPCR of whole blood and serum was 18.4% (95% confidence interval [CI]: 9.97%-31.4%) and 51.0% (95% CI: 37.5%-64.4%) respectively. The qPCR on suspected cases confirmed infection in 58 of 381 cases (15.2%). Of these, 6 cases confirmed by nested polymerase chain reaction (PCR) and sequencing were serologically negative using a standard but not regionally optimized microscopic agglutination test panel. The bacterial load in serum/blood ranged from 10(2) to 10(6) Leptospira/mL. Median leptospiral load for uncomplicated, renal failure, myocarditis, and multi-organ failure patients were 8616, 11007, 36100, and 15882 Leptospira/mL respectively. The qPCR window of positivity ranged from day 2 to day 15; sensitivity of qPCR was not affected by the length of the interval between the onset of symptoms and sample collection (P = .328). CONCLUSIONS Quantitative PCR shows potential as a valid diagnostic test with a wider window of positivity than previously thought. Quantitative leptospiremia in serum/whole blood samples did not directly correlate with clinical manifestations of outcome in this patient population.
Learning Parametric Sparse Models for Image Super-Resolution

Learning accurate prior knowledge of natural images is of great importance for single image super-resolution (SR). Existing SR methods either learn the prior from the low/high-resolution patch pairs or estimate the prior models from the input low-resolution (LR) image. Specifically, high-frequency details are learned in the former methods. Though effective, they are heuristic and have limitations in dealing with blurred LR images; while the latter suffers from the limitations of frequency aliasing. In this paper, we propose to combine those two lines of ideas for image super-resolution. More specifically, the parametric sparse prior of the desirable high-resolution (HR) image patches are learned from both the input low-resolution (LR) image and a training image dataset. With the learned sparse priors, the sparse codes and thus the HR image patches can be accurately recovered by solving a sparse coding problem. Experimental results show that the proposed SR method outperforms existing state-of-the-art methods in terms of both subjective and objective image qualities.
Exploring Diversity in Immigrant Assimilation and Transnationalism: The Case of Poles and Russian Jews in Philadelphia

This article investigates different patterns of coexistence of assimilation and transnational engagements (A/T) among recent Polish and Jewish Russian immigrants in Philadelphia and the particular constellations of circumstances that generate these outcomes. It then integrates this analysis into a broader comparative examination of the simultaneity of A/T among residentially dispersed Asian Indians, first-wave Cubans in Miami, and Jamaicans, undocumented Chinese, and Dominicans in New York. The main factors shaping the most common A/T patterns in these seven immigrant groups at the global, sending and receiving society national, and local levels are identified.
Mixture of Switching Linear Dynamics to Discover Behavior Patterns in Object Tracks

We present a novel non-parametric Bayesian model to jointly discover the dynamics of low-level actions and high-level behaviors of tracked objects. In our approach, actions capture both linear, low-level object dynamics, and an additional spatial distribution on where the dynamic occurs. Furthermore, behavior classes capture high-level temporal motion dependencies in Markov chains of actions, thus each learned behavior is a switching linear dynamical system. The number of actions and behaviors is discovered from the data itself using Dirichlet Processes. We are especially interested in cases where tracks can exhibit large kinematic and spatial variations, e.g. person tracks in open environments, as found in the visual surveillance and intelligent vehicle domains. The model handles real-valued features directly, so no information is lost by quantizing measurements into `visual words', and variations in standing, walking and running can be discovered without discrete thresholds. We describe inference using Markov Chain Monte Carlo sampling and validate our approach on several artificial and real-world pedestrian track datasets from the surveillance and intelligent vehicle domain. We show that our model can distinguish between relevant behavior patterns that an existing state-of-the-art hierarchical model for clustering and simpler model variants cannot. The software and the artificial and surveillance datasets are made publicly available for benchmarking purposes.
Complexin-I Is Required for High-Fidelity Transmission at the Endbulb of Held Auditory Synapse

Complexins (CPXs I–IV) presumably act as regulators of the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) complex, but their function in the intact mammalian nervous system is not well established. Here, we explored the role of CPXs in the mouse auditory system. Hearing was impaired in CPX I knock-out mice but normal in knock-out mice for CPXs II, III, IV, and III/IV as measured by auditory brainstem responses. Complexins were not detectable in cochlear hair cells but CPX I was expressed in spiral ganglion neurons (SGNs) that give rise to the auditory nerve. Ca2+-dependent exocytosis of inner hair cells and sound encoding by SGNs were unaffected in CPX I knock-out mice. In the absence of CPX I, the resting release probability in the endbulb of Held synapses of the auditory nerve fibers with bushy cells in the cochlear nucleus was reduced. As predicted by computational modeling, bushy cells had decreased spike rates at sound onset as well as longer and more variable first spike latencies explaining the abnormal auditory brainstem responses. In addition, we found synaptic transmission to outlast the stimulus at many endbulb of Held synapses in vitro and in vivo, suggesting impaired synchronization of release to stimulus offset. Although sound encoding in the cochlea proceeds in the absence of complexins, CPX I is required for faithful processing of sound onset and offset in the cochlear nucleus.
Accessibility Devices for Mobile Interfaces Extensions: A Survey

The development of mobile applications that consider accessibility can uniquely make use of software extensions to provide special interfaces to people with impairments. However, such extensions are limited so that the use of external devices is a natural alternative. The current market provides several accessibility devices that can be coupled to mobile devices, extending their interface abilities. However, there is not a work that compares such devices and assists the job of developers in finding an adequate device in accordance with their needs. Considering this scenario, this paper analyzed 60 scientific articles and over 250 relevant sites to identify devices that facilitate the use of applications running on mobile operating systems for impaired people. At the final of the process, 15 products were analyzed and compared against predefined features. Apart the number of existing devices for accessibility, it is possible to conclude that the market is still requiring a higher variety of options and further researches to provide a better level of accessibility for impaired users.
Reclassifying the spectrum of septic patients using lactate: severe sepsis, cryptic shock, vasoplegic shock and dysoxic shock

Objective The current definition of severe sepsis and septic shock includes a heterogeneous profile of patients. Although the prognostic value of hyperlactatemia is well established, hyperlactatemia is observed in patients with and without shock. The present study aimed to compare the prognosis of septic patients by stratifying them according to two factors: hyperlactatemia and persistent hypotension. Methods The present study is a secondary analysis of an observational study conducted in ten hospitals in Brazil (Rede Amil - SP). Septic patients with initial lactate measurements in the first 6 hours of diagnosis were included and divided into 4 groups according to hyperlactatemia (lactate >4mmol/L) and persistent hypotension: (1) severe sepsis (without both criteria); (2) cryptic shock (hyperlactatemia without persistent hypotension); (3) vasoplegic shock (persistent hypotension without hyperlactatemia); and (4) dysoxic shock (both criteria). Results In total, 1,948 patients were analyzed, and the sepsis group represented 52% of the patients, followed by 28% with vasoplegic shock, 12% with dysoxic shock and 8% with cryptic shock. Survival at 28 days differed among the groups (p<0.001). Survival was highest among the severe sepsis group (69%, p<0.001 versus others), similar in the cryptic and vasoplegic shock groups (53%, p=0.39), and lowest in the dysoxic shock group (38%, p<0.001 versus others). In the adjusted analysis, the survival at 28 days remained different among the groups (p<0.001) and the dysoxic shock group exhibited the highest hazard ratio (HR=2.99, 95%CI 2.21-4.05). Conclusion The definition of sepsis includes four different profiles if we consider the presence of hyperlactatemia. Further studies are needed to better characterize septic patients, to understand the etiology and to design adequate targeted treatments.
ambientROOM: integrating ambient media with architectural space

We envision that the physical architectural space we inhabit will be a new form of interface between humans and digital information. This paper and video present the design of the ambientROOM, an interface to information for processing in the background of awareness. This information is displayed through various subtle displays of light, sound, and movement. Physical objects are also employed as controls for these “ambient media. ”
Adaptive Changes of the Insig1/SREBP1/SCD1 Set Point Help Adipose Tissue to Cope With Increased Storage Demands of Obesity

The epidemic of obesity imposes unprecedented challenges on human adipose tissue (WAT) storage capacity that may benefit from adaptive mechanisms to maintain adipocyte functionality. Here, we demonstrate that changes in the regulatory feedback set point control of Insig1/SREBP1 represent an adaptive response that preserves WAT lipid homeostasis in obese and insulin-resistant states. In our experiments, we show that Insig1 mRNA expression decreases in WAT from mice with obesity-associated insulin resistance and from morbidly obese humans and in in vitro models of adipocyte insulin resistance. Insig1 downregulation is part of an adaptive response that promotes the maintenance of SREBP1 maturation and facilitates lipogenesis and availability of appropriate levels of fatty acid unsaturation, partially compensating the antilipogenic effect associated with insulin resistance. We describe for the first time the existence of this adaptive mechanism in WAT, which involves Insig1/SREBP1 and preserves the degree of lipid unsaturation under conditions of obesity-induced insulin resistance. These adaptive mechanisms contribute to maintain lipid desaturation through preferential SCD1 regulation and facilitate fat storage in WAT, despite on-going metabolic stress.
A novel artificial landmark for monocular global visual localization of indoor robots

To obtain the pose of a monocular camera installed on the robot relative to the static artificial landmarks in a prepared room is one of many good methods for indoor robot localization. However, the point correspondence problem caused by rotation of cameras and the point detection precision problem are not paid enough attention to. In this paper, we proposed a novel coplanar landmark and a method to calculate the camera pose. The landmark is composed of two carefully placed polygons to contain point correspondence information. In this way, the camera can rotate arbitrarily relative to the landmark. What's more, there are many parallel line pairs and perpendicular line pairs to impose more constraints on the camera pose. In our method, the SUSAN detector is used for edge detection. The line segments of the two polygons are then detected by RANSAC algorithm. After sorting the lines, the corners of each polygon are extracted by intersection of neighboring lines instead of detecting corners directly to improve precision. Once the intrinsic camera parameters and the coordinates of line segments and corners in the world frame and the image frame are derived, the camera pose can be obtained easily from the homography between the world frame and the image frame. Through the analysis of the experimental data, it can be concluded that the robustness and accuracy are much improved, and the rate is high enough for real-time indoor robot localization.