Miracle-dz/UniFAR-FTUs huggingface dataset:
DDR2 and Low Latency Variants

This paper describes a performance examination of the DDR2 DRAM architecture and the proposed cache-enhanced variants. These preliminary studies are based upon ongoing collaboration between the authors and the Joint Electronic Device Engineering Council (JEDEC) Low Latency DRAM Working Group, a working group within the JEDEC 42.3 Future DRAM Task Group. This Task Group is responsible for developing the DDR2 standard. The goal of the Low Latency DRAM Working Group is the creation of a single cache-enhanced (i.e. low-latency) architecture based upon this same interface. There are a number of proposals for reducing the average access time of DRAM devices, most of which involve the addition of SRAM to the DRAM device. As DDR2 is viewed as a future standard, these proposals are frequently applied to a DDR2 interface device. For the same reasons it is advantageous to have a single DDR2 specification, it is similarly beneficial to have a single lowlatency specification. The authors are involved in ongoing research to evaluate which enhancements to the baseline DDR2 devices will yield lower average latency, and for what type of applications. To provide context, experimental results will be compared against those for systems utilizing PC100 SDRAM, DDR133 SDRAM, and Direct Rambus (DRDRAM). This work is just starting to produce performance data. Initial results show performance improvements for low-latency devices that are significant, but less so than a generational change in DRAM interface. It is also apparent that there are at least two classifications of applications: 1) those that saturate the memory bus, for which performance is dependent upon the potential bandwidth and bus utilization of the system; and 2) those that do not contain the access parallelism to fully utilize the memory bus, and for which performance is dependent upon the latency of the average primary memory access.
Burden of acute respiratory infections in a family cohort in Iran

SUMMARY Acute respiratory infections (ARIs) are the most important infectious cause of death, but there is less information of their burden in the community. This study describes the burden of ARI in a cohort of 50 Iranian families visited weekly over 2 months. Eighty-one out of 113 (72%) children and 29/103 (28%) adults had a total of 124 episodes of ARI. Seventy-five per cent of the episodes occurring in children were primary/co-primary compared to 40% of those in adults (P<0·01). Children were more likely to be the first symptomatic cases and infections were frequently transmitted within the family. Frequencies were lowest among adults, low among infants aged <6 months and highest among children aged <5 years (P<0·01). Winter episodes occurred more frequently in January (P<0·01). The high frequency and apparent transmissibility of ARI in this cohort highlights its enormous burden in the community.
Effect of Total Flavonoid and Total Polyphenol from Tartary Buckwheat Sprouts and Their Inhibitor Activities on a-Glycosidase

Tartary buckwheat(TB) is an annual crop with abundant biological nutrition components. This research mainly showed that total flavonoid and total polyphenols contents of tartary buckwheat sprouts(TBS). a-Glycosidase Inhibitor activity of TBS was evaluated in vitro. The research showed that the seeds were surface sterilized with 5% of sodium hypochlorite for experiment. The peak of flavonoids yield in the TBS was 0.34 mg/g and polyphenols was 0.45 mg/g, contents showing a liner correlation of the germination time, when the seeds were germinated for 10 days inhibition cultivating at 27°C after 24 h soaking. The 0.4 g/mL tartary buckwheat sprouts extraction(TBSE) can inhibit the activity of a-Glycosidase 100%.
The fluid dynamics of swimming by jumping in copepods

Copepods swim either continuously by vibrating their feeding appendages or erratically by repeatedly beating their swimming legs, resulting in a series of small jumps. The two swimming modes generate different hydrodynamic disturbances and therefore expose the swimmers differently to rheotactic predators. We developed an impulsive stresslet model to quantify the jump-imposed flow disturbance. The predicted flow consists of two counter-rotating viscous vortex rings of similar intensity, one in the wake and one around the body of the copepod. We showed that the entire jumping flow is spatially limited and temporally ephemeral owing to jump-impulsiveness and viscous decay. In contrast, continuous steady swimming generates two well-extended long-lasting momentum jets both in front of and behind the swimmer, as suggested by the well-known steady stresslet model. Based on the observed jump-swimming kinematics of a small copepod Oithona davisae, we further showed that jump-swimming produces a hydrodynamic disturbance with much smaller spatial extension and shorter temporal duration than that produced by a same-size copepod cruising steadily at the same average translating velocity. Hence, small copepods in jump-swimming are in general much less detectable by rheotactic predators. The present impulsive stresslet model improves a previously published impulsive Stokeslet model that applies only to the wake vortex.
Compilation and virtualization in the HiPEAC vision

This paper describes the HiPEAC vision of embedded virtualization as it has developed during two years of discussion among the members of the HiPEAC cluster on binary translation and virtualization. We start from system virtualization and process virtualization and we gradually develop a vision in which the two merge into one virtualization layer for embedded systems. Such a unified virtualization offers solutions for consolidation, performance optimization, software engineering and dealing with legacy hardware components. Four adoption requirements are identified: support for real-time execution, low performance overhead, virtualization of accelerator cores and finally trustworthiness. Finally, we define four research challenges: full virtualization of heterogeneous multi-core platforms, portable performance for heterogeneous multi-cores, virtual machine management interfaces, and standards for embedded virtualization.
Phase coexistence and torpid mixing in the 3-coloring model on ℤd

We show that for all sufficiently large $d$, the uniform proper 3-coloring model (in physics called the 3-state antiferromagnetic Potts model at zero temperature) on ${\mathbb Z}^d$ admits multiple maximal-entropy Gibbs measures. This is a consequence of the following combinatorial result: if a proper 3-coloring is chosen uniformly from a box in ${\mathbb Z}^d$, conditioned on color 0 being given to all the vertices on the boundary of the box which are at an odd distance from a fixed vertex $v$ in the box, then the probability that $v$ gets color 0 is exponentially small in $d$. The proof proceeds through an analysis of a certain type of cutset separating $v$ from the boundary of the box and builds on techniques developed by Galvin and Kahn in their proof of phase transition in the hard-core model on ${\mathbb Z}^d$. Building further on these techniques, we study local Markov chains for sampling proper 3-colorings of the discrete torus ${\mathbb Z}^d_n$. We show that there is a constant $\rho \approx 0.22.
PSI2: Envelope Perfect Sampling of Non Monotone Systems

The famed perfect sampling method of Propp and Wilson uses a backward coupling scheme to compute unbiased samples of the stationary distribution of Markov chains. It has been implemented in a software tool, called PSI2, that proved very efficient for monotone chains coming from queuing networks. However, when the system includes at least one non-monotone event, the backward simulation scheme has to consider all possible states as starting points. This can be avoided by taking a new point of view that consists in bounding all possible trajectories of the Markov chain by envelopes. The new version of PSI2 presented here implements these latest improvements, including envelope techniques and splitting. Envelopes have been introduced by Busic et al(2008). As soon as envelopes couple, then all trajectories must have coupled, so that an unbiased sample is obtained. As for splitting, it consists in generating all the trajectories of the Markov chains inside the envelopes to run a classical backward coupling technique from that point on. Combining these two techniques in PSI2 makes it a more efficient tool that covers a wider class of queuing networks than previously. This includes networks with non-monotone events such as negative customers, arrivals by batches, forks and joins as well as Cox-distribution for services.
Alerts in Healthcare Applications: Process and Data Integration

Urgent requests and critical messages in healthcare applications must be delivered and handled timely instead of in an ad-hoc manner for most current systems. Therefore, we extend a sophisticated alert management system (AMS) to handle process and data integration in healthcare chain workflow management under urgency constraints. Alerts are associated with healthcare tasks to capture the parameters for their routing and urgency requirements in order to match them with the specialties of healthcare personnel or the functionalities of Web Services providers. Monitoring is essential to ensure the timeliness and availability of services as well as to ensure the identification of exceptions. We outline our implementation framework with Web Services for the communications among healthcare service providers together with mobile devices for medical professionals. We demonstrate the applicability of our approach with a prototype medical house-call system (MHCS) and evaluate our approach with medical professionals and various stakeholders.
VHR Object Detection Based on Structural Feature Extraction and Query Expansion

Object detection is an important task in very high-resolution remote sensing image analysis. Traditional detection approaches are often not sufficiently robust in dealing with the variations of targets and sometimes suffer from limited training samples. In this paper, we tackle these two problems by proposing a novel method for object detection based on structural feature description and query expansion. The feature description combines both local and global information of objects. After initial feature extraction from a query image and representative samples, these descriptors are updated through an augmentation process to better describe the object of interest. The object detection step is implemented using a ranking support vector machine (SVM), which converts the detection task to a ranking query task. The ranking SVM is first trained on a small subset of training data with samples automatically ranked based on similarities to the query image. Then, a novel query expansion method is introduced to update the initial object model by active learning with human inputs on ranking of image pairs. Once the query expansion process is completed, which is determined by measuring entropy changes, the model is then applied to the whole target data set in which objects in different classes shall be detected. We evaluate the proposed method on high-resolution satellite images and demonstrate its clear advantages over several other object detection methods.
Probabilistic Independence of Causal Influences

One practical problem with building large scale Bayesian network models is an exponential growth of the number of numerical parameters in conditional probability tables. Obtaining large number of probabilities from domain experts is too expensive and too time demanding in practice. A widely accepted solution to this problem is the assumption of independence of causal influences (ICI) which allows for parametric models that define conditional probability distributions using only a number of parameters that is linear in the number of causes. ICI models, such as the noisy-OR and the noisy-AND gates, have been widely used by practitioners. In this paper we propose PICI, probabilistic ICI, an extension of the ICI assumption that leads to more expressive parametric models. We provide examples of three PICI models and demonstrate how they can cope with a combination of positive and negative influences, something that is hard for noisy-OR and noisy-AND gates.
False Sharing ans Spatial Locality in Multiprocessor Caches

The performance of the data cache in shared-memory multiprocessors has been shown to be different from that in uniprocessors. In particular, cache miss rates in multiprocessors do not show the sharp drop typical of uniprocessors when the size of the cache block increases. The resulting high cache miss rate is a cause of concern, since it can significantly limit the performance of multiprocessors. Some researchers have speculated that this effect is due to false sharing, the coherence transactions that result when different processors update different words of the same cache block in an interleaved fashion. While the analysis of six applications in the paper confirms that false sharing has a significant impact on the miss rate, the measurements also show that poor spatial locality among accesses to shared data has an even larger impact. To mitigate false sharing and to enhance spatial locality, we optimize the layout of shared data in cache blocks in a programmer-transparent manner. We show that this approach can reduce the number of misses on shared data by about 10% on average. >
A POMDP Approach to Robot Motion Planning under Uncertainty

Motion planning in uncertain and dynamic environments is critical for reliable operation of autonomous robots. Partially observable Markov decision processes (POMDPs) provide a principled general framework for such planning tasks and have been successfully applied to several moderately complex robotic tasks, including navigation, manipulatio n, and target tracking. The challenge now is to scale up POMDP planning algorithms and handle more complex, realistic tasks. This paper outlines ideas aimed at overcoming two major obstacles to the efficiency of POMDP planning: the “curse of dimensionality” and the “curse of history”. Our main objective is to show that using these ideas— along with others—POMDP algorithms can be used successfully for motion planning under uncertainty for robotic tas ks with a large number of states or a long time horizon. We implemented some of our algorithms as a software package Approximate POMDP Planning Library(APPL), now available for download athttp://motion.comp.nus.edu. sg/ projects/pomdp/pomdp.html.
A footprint as a history of movement

The foot of a moving animal interacts with the substrate in three phases: touch-down, weight-bearing and kick-off. We examine the morphological effects of these phases in foot prints of Cretaceous dinosaurs (theropods and ornithopods) at the Lark Quarry Environmental Park, western Queensland, Australia. -Authors
3D Face Pose Tracking from Monocular Camera via Sparse Representation of Synthesized Faces

This paper presents a new method to track head pose efficiently from monocular camera via sparse representation of synthesized faces. In our framework, the appearance model is trained using a database of synthesized face generated from the first video frame. The pose estimation is based on the similarity distance between the observations of landmarks and their reconstructions. The reconstruction is the texture extracted around the landmark, represented as a sparse linear combination of positive training samples after solving ‘1-norm problem. The approach finds the position of new landmarks and face pose by minimizing an energy function as the sum of these distances while simultaneously constraining the shape by a 3D face. Our framework gives encouraging pose estimation results on the Boston University Face Tracking (BUFT) dataset.
Branching Processes and Non-Commuting Random Variables in Population Biology

Branching processes are a well-established tool in mathematical biology used to study the dynamics of rareed populations where agents act independently and small stochastic density-independent changes in population sizes. However, they are often avoided by non-mathematicians because of their reliance on generating functions. Generating functions are powerful computational aids but are often dicult to motivate. In this paper, I review branching process theory using a non-commuting random variable description of multiplication as mnemonic for generating functions. Starting from the elementary denition of multiplication, I show how uncertainty leads to a natural generalization of integer multiplication without the commutative property, and how this in-turn is connected to the well-established study of generating functions. Non-commuting random-variable methods are described in detail and illustrated using examples.
Pre-emptive analgesic and haemodynamic efficacy of combined spinal-epidural neostigmine delivery.

OBJECTIVE To determine the effect of pre-emptive epidurally administered 4 or 8 mcg/kg neostigmine on analgesia, mean arterial pressure, heart rate and side effects in intra and postoperative period. STUDY DESIGN Randomized, double blinded, controlled clinical trial. PLACE AND DURATION OF STUDY Ankara Numune Training and Research Hospital, Turkey, from January to December 2008. METHODOLOGY Forty-five patients scheduled for lower extremity surgery were included in the study following the approval of the ethics committee and the patients. The study group was split into three groups and received combined spinalepidural anaesthesia. Diluting with 10 ml normal saline, group N4 and group N8 were delivered 4 mcg/kg and 8 mcg/kg epidural neostigmine, respectively, whereas group SF received 10 ml epidural saline. Lidocaine (2%) at 1.2 mg/kg dose was preferred for spinal anaesthesia. Analgesic efficacy, time to first analgesic requirement, Visual Analog Scale, Fentanyl consumption in the postoperative patient-controlled epidural analgesia, and delivered/required number of boluses, were evaluated. Haemodynamic data and side effects were noted. RESULTS Statistically, analgesic consumptions at 12 and 24 hours in the N8 group was lower than those in the SF group, the number of delivered boluses was lower in the N8 group compared with the SF and N4 groups, number of required boluses was lower in the N8 group than in the SF group. In terms of haemodynamics and side effects, no difference was found between the groups regarding the entire intraoperative and postoperative parameters. CONCLUSION Epidural Neostigmine administration at 8 mcg/kg was found to be a viable additional agent against analgesia, with the postoperative period depending on the dosage.
Procalcitonin Level in Neonatal Sepsis

A prospective study was conducted in a tertiary care centre from June 2015 to October 2016 to evaluate role of serum procalcitonin (PCT) level in predicting neonatal sepsis and comparison with CRP as a marker of neonatal sepsis. 100 neonates admitted in newborn intensive care unit (NICU) from the study group. These newborns were categorized into proven sepsis, suspected sepsis and control group based on symptoms and signs of infection and blood culture findings. Procalcitonin and CRP level were done for all these newborns. These levels were then statistically compared for all the groups. Out of 80 cases, 48 cases were of early onset sepsis and rest 32 were of late onset sepsis (LOS). 47(97.9%) out of 48 cases with early onset sepsis had positive procalcitonin level, while 30 (93.75%) out of 32 cases with LOS had positive procalcitonin value. 9 (18.75%) out of 48 cases with EOS had positive CRP value, while 15(46.87%) out of 32 cases with LOS had positive CRP value. Mean PCT was 33.75 + 13.75 ng/dl, 29.58 + 13.87 ng/dl and 0.335 + 0.4 ng/dl for proven sepsis, suspected sepsis and control groups respectively. Corresponding values for CRP were 1.33 1.74, 2.264 3.02 and ± ± 0.97 2.87 ng/dl respectively for proven sepsis, suspected sepsis and control group. The sensitivity, specificity, PPV and ± NPV of procalcitonin was 96.25%, 85%, 96.25% and 85% and the sensitivity, specificity, PPV and NPV of CRP were 30%, 90%, 92.33% and 25% respectively. On comparing CRP and procalcitonin, there was statistically significant difference (p < 0.005) for early onset sepsis, while there was no significant difference (p > 0.05) for late of onset sepsis. Procalcitonin is highly sensitive marker in early onset sepsis with good positive and negative predictive value and high sensitivity.
An Approximate Framework for Flexible Network Flow Screening

Network security analysts presently lack tools for routinely screening large collections of network traffic for structures of interest. This is particularly the case when the structures of interest are embodied as summaries of sets of related traffic, essentially behaviour descriptions. This paper sketches a methodology to provide such capability, in the context of flow data. The methodology generates approximate search results, and uses a modular construction to provide the capability to tailor queries for multiple views of the behaviour structure of interest. At core, the methodology involves approximate sequential search procedures. The methodology is framed by a discussion of a large university network.
Privacy Preserving Interoperability for eHealth Systems

Development and implementation of convenient, miniaturized and integrated instruments that enable therapeutic drug monitoring and dosage individualization for the patients will significantly improve modern therapeutics. To make it possible we aim at tackling the following questions: how to achieve (semantic) interoperability and medical data integration in a distributed environment; and how to ensure privacy of the patients in case of reusing medical data for providing personalized recommendations that enhance patient care.
Chapter 4: Direct and indirect drivers of change in biodiversity and nature’s contributions to people

Jayne Belnap (USA), Laura K. Brown (Canada), Ernesto Brugnoli (Uruguay), Jana E. Compton (USA), Richard H. Coupe (USA), Marcello Hernández-Blanco (Costa Rica), Forest Isbell (USA), Julie Lockwood (USA), Juan Pablo Lozoya Azcárate (Uruguay), David McGuire (USA), Anibal Pauchard (Chile), Ramon Pichs-Madruga (Cuba), Ricardo Ribeiro Rodrigues (Brazil), Gerardo Arturo Sanchez-Azofeifa (Costa Rica/Canada), Alvaro Soutullo (Uruguay), Avelino Suarez (Cuba), Elizabeth Troutt (Canada)
Band level fusion using quaternion representation for extended multi-spectral face recognition

With the availability of sensor technology across the broad electromagnetic spectrum, multi-spectral imaging is increasingly used in biometric systems. Especially for face recognition, multi-spectral imaging has gained a lot of attention due to it's invariant property against variation caused by unknown illumination. However, obtaining best performance using multi-spectral imaging is still a challenge due to presence of a modality gap between the spectral imaging data and redundant band information. In this paper, we propose a fused band representation with a set of selected bands represented in Quaternion space for spectral band images to efficiently maintain the inter band relationship in spatial domain. The selection is based on measuring the information content in bands using entropy and fusion is carried out in Quaternion space for three best bands. The features from newly obtained image is collaboratively represented to achieve robust performance. The proposed approach is experimentally validated on the extended multi-spectral face database of 168 subjects, whose spectral band images are captured in 9 narrow spectral bands in visible and near infrared range (530nm to 1000nm). The quantitative performance analysis, obtained using the proposed method indicates 96.13% recognition rate at Rank-1, outperforming other state-of-the-art methods.