Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approximately Optimal Algorithm for Scheduling Phasor Data Transmissions in Smart Grid Networks

In this paper, we devise a scheduling algorithm for ordering transmission of synchrophasor data from the substation to the control center in as short a time frame as possible, within the real-time hierarchical communications infrastructure in the electric grid. The problem is cast in the framework of the classic job scheduling with precedence constraints. The optimization setup comprises the number of phasor measurement units (PMUs) to be installed on the grid, a weight associated with each PMU, processing time at the control center for the PMUs, and precedence constraints between the PMUs. The solution to the PMU placement problem yields the optimum number of PMUs to be installed on the grid, while the processing times are picked uniformly at random from a predefined set. The weight associated with each PMU and the precedence constraints are both assumed known. The scheduling problem is provably NP-hard, so we resort to approximation algorithms, which provide solutions that are suboptimal yet possessing polynomial time complexity. A lower bound on the optimal schedule is derived using branch and bound techniques, and its performance evaluated using standard IEEE test bus systems. The scheduling policy is power grid-centric, since it takes into account the electrical properties of the network under consideration.
Impact of prefix-match changes on IP reachability

Although most studies of Internet routing treat each IP address block (or prefix) independently, the relationship between prefixes is important because routers ultimately forward packets based on the "longest-matching prefix. " In fact, the most-specific prefix for a given destination address may change over time, as BGP routes are announced and withdrawn. Even if the most-specific route is withdrawn, routers may still be able to deliver packets to the destination using a less-specific route. In this paper, we analyze BGP update messages and Netflow traffic traces from a large ISP to characterize both the changes to the longest-matching prefix over time and the resulting effects on end-to-end reachability of the destination hosts. To drive our analysis, we design and implement an efficient online algorithm for tracking changes in the longest-matching prefix for each IP address. We analyze the BGP message traces to identify the reasons for prefix-match changes, including failures, route flapping, sub-prefix hijacking, and load-balancing policies. Our preliminary analysis of the Netflow data suggests that the relationship between BGP updates and IP reachability is sometimes counterintuitive.
Human teratocarcinoma stem cells: Glycolipid antigen expression and modulation during differentiation

Teratocarcinomas are germ cell tumors in which pluripotent stem cells, embryonal carcinoma (EC) cells, undergo differentiation along the pathways resembling those occurring during early embryogenesis. Human EC cell lines established in vitro provide a model for studying embryonic cellular differentiation in a way that is pertinent to early human development. The predominant glycolipid antigens expressd by EC cells of both humans and mice have globoseries core structures; in humans they are terminally modified to yield the monoclonal antibody‐defined stage‐specific embryonic antigens SSEA‐3 and SSEA‐4, and also globo‐ABH antigens; in the mouse terminal modification yields the Forssman antigen rather than SSEA‐3 and ‐4. These observations focus attention on the possible role of the P‐blood group system, which regulates synthesis of globoseries oligosaccharides, in the behavior of cells in the early embryo and in teratocarcinomas. Marked changes in the core structures of the cell surface glycolipids occur as the EC cells differentiate; thus globoseries structures rapidly diminish and are replaced by lactoseries and then by ganglioseries glycolipids. During differentiation of the NTERA‐2 line of pluripotent human EC cells into neurons and other cell types, the various subsets of differentiated cells that arise are distinguished by their differential expression of new glycolipid antigens, particularly ganglioside GT3 (recognized by antibody A2B5), and ganglioside 9‐0‐acetyl GD3 (recognized by antibody ME311). Neurons are found among the A2B5+/ME311− cells.
Biotic and Abiotic Factors Affecting the Flight Activity of Fopius arisanus, an Egg-Pupal Parasitoid of Fruit Fly Pests

ABSTRACT Climatic conditions and the physiological state of aparasitoid may alter its host selection behavior and thus its efficiency as a biological control agent. We studied the influence of these parameters on the behavior of Fopius arisanus (Sonan), an egg-pupal parasitoid of many Tephritidae. In the first experiment, we assessed in field cage assays the influence of temperature, humidity, light intensity, barometric pressure, and wind speed. Both flight and parasitism were mainly affected by temperature and humidity. However, because these two factors were strongly correlated in our experiments, the direct influence of each one cannot be specified. Flight activity was affected by variations in barometric pressure. In a second set of experiments, we conducted release and recapture assays with dyed insects to determine the influence of sex, mating status, egg load, age, and starvation on attraction toward infested fruit. Males were not attracted, suggesting that fruit are not a mating site. The egg load seemed to be a major parameter of foraging motivation. Finally, we showed that flight activity strongly decreased after 48 h of starvation. We observed a possible switch to food in the foraging motivation of starved females, but this result was impaired by poor recoveries: <10% of released females were recaptured after 96 h of starvation. We finally discuss the importance of these observations on the efficiency of F. arisanus as a biological control agent in tropical humid areas.
Some extensions of passive walking formula to active biped robots

This paper studies the dynamic principles of passive dynamic walking and proposes novel gait generation and control methods based on it. The authors have clarified a unified property of passive dynamic walking which shows that the walking system's mechanical energy increases proportionally with respect to the position of system's center of mass. Following this, the gait generation problem yields solutions of an indeterminate equation. By solving it for the control torque, active dynamic walking on a level can then be realized. In this paper, we first discuss the solutions and consider the unification of the previous gait generation methods from a variable virtual gravity point of view. Second, its applications to a kneed biped system considering ZMP condition and robust energy referenced control are discussed. The effectiveness of the proposed methods have been investigated through numerical simulations.
Evaluation of a Calibrated 18F-FDG PET Score as a Biomarker for Progression in Alzheimer Disease and Mild Cognitive Impairment

Increasingly, clinical trials are being planned in patients with mild cognitive impairment (MCI) to prevent or delay the onset of dementia in Alzheimer disease (AD) by disease-modifying intervention. Inclusion of imaging techniques as biomarkers for patient selection and assessment of outcome is expected to increase trial efficacy. PET using 18F-FDG provides objective information about the impairment of synaptic function and could, with appropriate standardization, qualify as a biomarker. Methods: We evaluated a predefined quantitative measure (PET score) that is extracted automatically from 18F-FDG PET scans using a sample of controls (n = 44), patients with MCI (n = 94), and patients with mild AD (n = 40) from the Alzheimer Disease Neuroimaging Initiative (ADNI). Subjects received 4 scans and clinical assessments over 2 y. Results: PET scores provide much higher test–retest reliability than standard neuropsychologic test scores (Alzheimer's Disease Assessment Scale–Cognitive [ADAS-cog] and Mini-Mental State Examination) and superior signal strength for measuring progression. At the same time, they are related linearly to ADAS-cog scores, thus providing a valid measure of cognitive impairment. In addition, PET scores at study entry in MCI patients significantly predict clinical progression to dementia with a higher accuracy than Mini-Mental State Examination and ADAS-cog. Conclusion: 18F-FDG PET scores are a valid imaging biomarker to monitor the progression of MCI to AD. Their superior test–retest reliability and signal strength will allow the reduction in the number of subjects needed or shortening of study duration substantially.
Multi-Scale Context Adaptation for Improving Child Automatic Speech Recognition in Child-Adult Spoken Interactions

The mutual influence of participant behavior in a dyadic interaction has been studied for different modalities and quantified by computational models. In this paper, we consider the task of automatic recognition for children’s speech, in the context of child-adult spoken interactions during interviews of children suspected to have been maltreated. Our long-term goal is to provide insights within this immensely important, sensitive domain through large-scale lexical and paralinguistic analysis. We demonstrate improvement in child speech recognition accuracy by conditioning on both the domain and the interlocutor’s (adult) speech. Specifically, we use information from the automatic speech recognizer outputs of the adult’s speech, for which we have more reliable estimates, to modify the recognition system of child’s speech in an unsupervised manner. By learning first at session level, and then at the utterance level, we demonstrate an absolute improvement of upto 28% WER and 55% perplexity over the baseline results. We also report results of a parallel human speech recognition (HSR) experiment where annotators are asked to transcribe child’s speech under two conditions: with and without contextual speech information. Demonstrated ASR improvements and the HSR experiment illustrate the importance of context in aiding child speech recognition, whether by humans or computers.
Defining the early indicators of dyslexia: providing the signposts to intervention

The general aim of this thesis was to identify the indicators of reading disability and to analyze the effect of these factors in preschool age children in order to determine which factors play a principal role in the development of dyslexia. Various theories of developmental dyslexia have been investigated and the key components of major theories are presented in this paper. It is a generally held view that dyslexia is caused by a deficit in phonological processing which is an inability to understand the sound structure of language. This thesis aims to unite current research findings in order to better classify dyslexia as well as to determine approaches to intervention which are critical to a preschool child’s development of literacy. Three studies were conducted. The goal of study 1 was to determine the discrepancies in performance between non-dyslexic readers and dyslexic readers. Study 2 investigated phonological awareness abilities in preschool age children and their relationship with intelligence. An intervention study was then carried out on the preschool participants to determine the effects of instruction in the alphabetic principle on elements related to intelligence and phonological awareness. The results of this thesis and the studies conducted herein found a wide range of domains that were causal to reading disability. These include visuo-spatial discrimination skills, phonological knowledge and working memory. These studies also indicate that early identification of weaknesses in these areas can be mediated by well informed instruction in letter-sound correspondence and can be a critical determinant of future reading ability.
Genomic insights into cancer-associated aberrant CpG island hypermethylation

Carcinogenesis is thought to occur through a combination of mutational and epimutational events that disrupt key pathways regulating cellular growth and division. The DNA methylomes of cancer cells can exhibit two striking differences from normal cells; a global reduction of DNA methylation levels and the aberrant hypermethylation of some sequences, particularly CpG islands (CGIs). This aberrant hypermethylation is often invoked as a mechanism causing the transcriptional inactivation of tumour suppressor genes that directly drives the carcinogenic process. Here, we review our current understanding of this phenomenon, focusing on how global analysis of cancer methylomes indicates that most affected CGI genes are already silenced prior to aberrant hypermethylation during cancer development. We also discuss how genome-scale analyses of both normal and cancer cells have refined our understanding of the elusive mechanism(s) that may underpin aberrant CGI hypermethylation.
Fault Tolerance and Power Consumption Analysis on Chip-Multi Processors Architectures

With continuous scaling in CMOS technology thenumber of transistors grows more and more in a single die. Today Chip multiprocessors (CMPs) are the most architecturethat used in the computer industry to utilize the huge numbersof transistors. Reliability beside performance and powerdissipation is the most important metric in a processor. Onethe key challenge in employing these enormous transistors isthe unwanted effect of transient and permanent faults, whichthreat the reliability of a CMP. Recently, in order to increasereliability Redundant MultiThreading (RMT) approaches areproposed. In RMT methods, each execution thread duplicated, and these two copies of original thread run on different coreson CMP. Some of most important of execution results such asstore value and store address result will be compared and ifthere is no mismatch execution continue; otherwise the errorsignal will be active. In these work we implement RMT on agate level model of a two-way CMP and estimate failure rate inRMT processor by using of fault injection method and also wecalculate power dissipation and performance overhead of thistechnique. Our simulation experiments show that RMT has91.7% fault detection in respect to 4% power overhead. Performance degradation of RMT fault tolerance techniques isabout 29%. By comparing RMT with traditional informationredundancy techniques such as hamming code we found thatpower consumption in RMT fault tolerance techniques is 20-40 times higher than traditional ones.
Migrating Android Applications to the Cloud

Recently, smartphone technologies have evolved quickly and offered end users the computing power and networking capabilities required to perform useful network and multimedia applications. However, due to limited physical sizes and battery capacities, the current generation of smartphones cannot yet fulfill the requirements of sophisticated applications of which personal computers are capable. One way to solve this problem is to minimize the workload on a smartphone as much as possible by offloading portions of an application to a server. The solution is particularly attractive today as cloud computing provides the needed server resources at relatively low costs. This paper proposes a novel, lightweight application migration mechanism for the users of smartphones to suspend the execution of applications and offload them to the cloud. The authors also developed a framework to perform Android applications efficiently with virtual phones in the cloud with a virtual storage. This paper discusses the migration mechanism and evaluates its effectiveness on the Android smartphone. This approach may effectively offload workload for Android applications even with low-speed mobile network.
Simulation of a site-specific doubly-fed induction generator (DFIG) for wind turbine applications

This paper describes a preliminary study of a 30 kW doubly-fed induction generator (DFIG) used for wind turbine applications. Wind represents a variable-speed intermittent source of energy in nature and can be controlled to be a nearly constant speed but variable-torque input to the wind turbine using blade pitch angle regulation. Wind profile at the installation site is investigated so as to derive parameterized wind speeds, more importantly, the annual cubic-mean speed. This is taken account into the machine design since the machine efficiency varies with turbine mechanical inputs. By coordinating the loss components, it is possible at the machine design stage to select the maximum efficiency to be near the actual optimized load, in a long run, to maximize the overall energy production of the generator. The DFIG is modeled in Matlab with a vector control. The total energy production is used as a key criterion to refine the machine design.
Performance Analysis of MF-TDMA Multi-Carrier Demultiplexer/Demodulators (MCDDs) in the Presence of Critical Degrading Factors

Two typical MCDD (multi-carrier demultiplexer/demodulator) architectures, M-MCD (multistage multicarrier demultiplexer) and PPF (polyphase FFT) suitable for multimedia service via the on-board processing (OBP) satellite, are analytically modeled and their error performances are numerically evaluated in the presence of five degrading factors including: narrow-band AWGN, carrier frequency offset, phase error, ISI and quantization error. Cumulative effects of these factors on the BERs of the two different MCDD structures are also assessed and compared for possible tradeoff under MF-TDMA (Multi-Frequency Time Division Multiplex Access) scheme using QPSK modulation. Results show that both architectures are commonly vulnerable to most degrading factors. However, combined effect of phase error with AWGN is more critical to M-MCD than PPF. In addition, PPF method proves to be more sensitive to quantization error than M-MCD. When all five degrading factors are considered, MCDD using PPF method exhibits better BER performance than that of M-MCD, especially when carrier phase error is significant.
Total plasma antioxidant capacity is not always decreased in sepsis.

OBJECTIVE To compare total plasma antioxidant capacity and selected individual antioxidants in patients with varying degrees of severity of sepsis. DESIGN A prospective, observational, consecutive case study. SETTING A 16-bed intensive care unit (ICU) in a university teaching hospital. INTERVENTIONS None. PATIENTS Forty-six healthy controls, ten ICU patients, nine patients with systemic inflammatory response syndrome (SIRS), 11 septic patients, and 14 septic shock patients. Plasma was obtained in healthy patients scheduled for minor surgery immediately before anesthesia and in ICU patients within 24 hrs of admittance to the unit or diagnosis of SIRS, sepsis, or septic shock. MEASUREMENTS AND MAIN RESULTS Using the total peroxyl radical trapping method, we found plasma antioxidant capacity to be lower in septic patients but higher in septic shock patients, as compared with controls. Bilirubin was the greatest contributor to the increase with shock, followed by uric acid. Neopterin also correlated with the peroxyl radical trapping antioxidant parameter values. CONCLUSION Although total plasma antioxidant capacity is decreased from normal levels in septic patients, an increase in some oxidants contributes to an increased total antioxidant capacity in septic shock patients.
A Fat to Forget: Trans Fat Consumption and Memory

Purpose We sought to assess the relation of dietary trans fatty acid (dTFA) consumption to word-memory. Methods We analyzed cross-sectional data from the 1999-2005 UCSD Statin Study. Participants were 1018 adult men and non-procreative women age ≥20 without diagnosed diabetes, CVD, or extreme LDL-cholesterol. Primary analyses focused on men, as only men (N = 694) were effectively represented in younger adult ages. “Recurrent words” assessed word memory. dTFA (grams/day) estimates were calculated from the Fred Hutchinson Food Frequency Questionnaire. Regression, stratified at age 45, assessed the relation between memory and dTFA in various adjustment models. Major findings were replicated in the full sample (including women). Potential mediators were examined. Results An age-by-dTFA interaction was significant. dTFA adversely predicted memory in younger adults (only), robust to adjustment model. Each gram/day dTFA was associated with an estimated 0.76 fewer words recalled (full model) (SE = 0.27, 95%CI = 0.22,1.3, P = 0.006). Adjustment for systolic blood pressure, waist circumference and BMI (but not lipid or glycemic variables) attenuated the relationship, consistent with mediation by factors involving, relating to, or concurrently influencing, these factors. Conclusion Greater dTFA was significantly associated with worse word recall in younger adults. Prooxidant and energetic detriments of dTFA and triangulation with other evidence offer prospects for causality.
A Literature Survey of Early Time Series Classification and Deep Learning

This paper provides an overview of current literature on time series classification approaches, in particular of early time series classification. A very common and effective time series classification approach is the 1-Nearest Neighbor classifier, with different distance measures such as the Euclidean or dynamic time warping distances. This paper starts by reviewing these baseline methods. More recently, with the gain in popularity in the application of deep neural networks to the field of computer vision, research has focused on developing deep learning architectures for time series classification as well. The literature in the field of deep learning for time series classification has shown promising results. Early time series classification aims to classify a time series with as few temporal observations as possible, while keeping the loss of classification accuracy at a minimum. Prominent early classification frameworks reviewed by this paper include, but are not limited to, ECTS, RelClass and ECDIRE. These works have shown that early time series classification may be feasible and performant, but they also show room for improvement.