Miracle-dz/UniFAR-FTUs huggingface dataset:
On the accuracy of appliance identification based on distributed load metering data

Dynamic load management, i.e., allowing electricity utilities to remotely turn electric appliances in households on or off, represents a key element of the smart grid. Appliances should however only be disconnected from mains when no negative side effects, e.g., loss of data or thawing food, are incurred thereby. This motivates the use of appliance identification techniques, which determine the type of an attached appliance based on the continuous sampling of its power consumption. While various implementations based on different sampling resolutions have been presented in existing literature, the achievable classification accuracies have rarely been analyzed. We address this shortcoming and evaluate the accuracy of appliance identification based on the characteristic features of traces collected during the 24 hours of a day. We evaluate our algorithm using more than 1,000 traces of different electrical appliances' power consumptions. The results show that our approach can identify most of the appliances at high accuracy.
A Method Based on AMHI for DDoS Attacks Detection and Defense

The emergence of Distributed Denial of Service (DDoS) attack increases the destructive force of Denial of Service (DoS) attack drastically. Besides bringing more terrible threats, the attack from far and near and the employment of internet protocol (IP) spoofing make the abnormal traffic detection harder and harder. This paper proposes a mechanism defined as AMHI (Address Matching and Hash Inspection) and a method based on it for DDoS attacks detection and defense. Through the simulation experiment, the Address Matching and backup Hash Inspection operations to the suspicious traffic implemented on router interface for local subnet can detect and defend DDoS attacks effectively even when using IP Spoofing. In addition, this method can also decrease a mass of statistical work for the routers, and to some extent ease the pressure of heavy traffic caused by attacks.
Multiloop Controller for N-Stage Cascade Boost Converter

In recent years, the development of new technologies is requiring wider conversion ratios. A possible solution to this problem is to use n-stages connected in cascade; however, the major drawbacks are: (a) the total losses are increased mainly by the active switches, and (b) a more complex control circuitry is required. An alternative solution is to use a cascade boost converter with a single active switch. In this paper, nonlinear and linear models are given for the above converter. A controller is developed using average current-mode control where the current of the first inductor is selected for feedback purposes. For the inner loop, a current gain and a high gain compensator are selected. For the output loop, a conventional PI-controller is designed.
A wireless passive RCS-based temperature sensor using liquid metal and microfluidics technologies

A novel wireless and passive temperature sensor that utilizes microfluidic and liquid metal technologies for the temperature-dependent modification of the sensor's radar echo is introduced. Liquid metal is used to dynamically alter the number of antenna elements activated along a linear array configuration with respect to temperature. In this way, the sensed temperature value can be accurately quantified by the change in radar cross section (RCS) of the device. Simulation and measurements of the backscattered power of the temperature-reconfigurable array were performed to verify the concept and benchmark the sensitivity and temperature range of the sensor. This study is based on the number of elements activated by the short-circuiting of their gap through the temperature-expansion of liquid metal inside a bridging microfluidic channel. For the first time the remote measurement of temperature based on the RCS variability of a microfluidics-realized sensor is presented. It features an RCS range of 9 dBsm at 29.5 GHz corresponding to a tunable temperature range of at least 20°K and a resolution of 1.8 dBsm per element activated resulting in a temperature resolution around 4°K. It has to be noted that numerous major challenges encountered in the feeding and encapsulation of liquid metal inside microfluidic channels were addressed and preliminary guidelines for a novel generation of wireless sensors based on liquid metal and microfluidic technologies have been established for the first time.
Interaction of socio-cultural backgrounds and beliefs with conceptions of the nature of science, societal issues, and instructional ideology among secondary science teachers in Zimbabwe

This article is a review of the literature dealing with the construct science and technology literacy as it relates to teacher knowledge and beliefs regarding the nature of science and scientific knowledge, science and technology related societal issues, science instructional ideology, and traditional culture. The article seeks to demonstrate the relevance of socio-cultural contexts and variables by reviewing aspects of the traditional culture of a developing country, Zimbabwe. It is postulated that an inverse relationship exists between teacher orientation or commitment to traditional world-views and socio-cultural backgrounds and their perception concerning the nature of science, science and technology related societal issues, and science instructional ideology. The postulated relationship has implications for the effective adoption and integration of a scientific world-view into the cognitive and affective repertoire of indigenous students so that it may be spontaneously utilized in problem situations which is currently lacking. Introduction Snow (1961) more than three decades ago described "the gulf of mutual incomprehension" between the scientifically literate and the non-scientifically literate. He said then: They have a curious distorted image of each other. Their attitudes are so different that, even on the level of emotion, they can't find much common ground. The non-scientists have a rooted impression that scientists are shallowly optimistic, unaware of man's condition. (Snow, 1961; pp. 4-5)
A New Theory and Measure of Ethical Work Climate: The Psychological Process Model (PPM) and the Ethical Climate Index (ECI)

The EWC is a sub-climate of the broader organizational climate and is conceptually and methodologically related to it. Therefore, I began my dissertation research with an in depth review of the conceptual and methodological developments of the broader construct, the organizational climate. This review provided me with a well grounded understanding of the climate literature in general and the conceptual developments and methodological issues related to studying the construct in particular. All of the issues discussed in chapter one directly affect the development of my theory and measure of EWC. As I progress through this chapter, I explain the reason for including and reviewing each one of the issues.
Mind and Brain: A Critical Appraisal of Cognitive Neuroscience

The search for mind-brain relationships, with a particular emphasis on distinguishing hyperbole from solid empirical results in brain imaging studies.Cognitive neuroscience explores the relationship between our minds and our brains, most recently by drawing on brain imaging techniques to align neural mechanisms with psychological processes. In Mind and Brain, William Uttal offers a critical review of cognitive neuroscience, examining both its history and modern developments in the field. He pays particular attention to the role of brain imaging? especially functional magnetic resonance imaging (fMRI)? in studying the mind-brain relationship. He argues that, despite the explosive growth of this new mode of research, there has been more hyperbole than critical analysis of what experimental outcomes really mean. With Mind and Brain, Uttal attempts a synoptic synthesis of this substantial body of scientific literature. Uttal considers psychological and behavioral concerns that can help guide the neuroscientific discussion; work done before the advent of imaging systems; and what brain imaging has brought to recent research. Cognitive neuroscience, Uttal argues, is truly both cognitive and neuroscientific. Both approaches are necessary and neither is sufficient to make sense of the greatest scientific issue of all: how the brain makes the mind.
AID and Caspase 8 Shape the Germinal Center Response through Apoptosis

Germinal centers (GCs) are clusters of activated B cells that form in secondary lymphoid organs during a T-dependent immune response. B cells enter GCs and become rapidly proliferating centroblasts that express the enzyme activation-induced deaminase (AID) to undergo somatic hypermutation and class-switch recombination. Centroblasts then mature into centrocytes to undergo clonal selection. Within the GC, the highest affinity B cell clones are selected to mature into memory or plasma cells while lower affinity clones undergo apoptosis. We reported previously that murine Aicda−/− GC B cells have enhanced viability and accumulate in GCs. We now show that murine Aicda−/− GC B cells accumulate as centrocytes and inefficiently generate plasma cells. The reduced rate of plasma cell formation was not due to an absence of AID-induced DNA lesions. In addition, we show that the deletion of caspase 8 specifically in murine GC-B cells results in larger GCs and a delay in affinity maturation, demonstrating the importance of apoptosis in GC homeostasis and clonal selection.
Optimizing Data Partition for NoSQL Cluster

The data partition balance impacts the performance of NoSQL systems significantly. Most of the P2P NoSQL systems use consistent hashing to partition data automatically. Currently, these systems use random virtual nodes or manual configuration to divide the consistent hashing ring, which may cause load imbalance and degrade the performance. The problem is pronounced especially for heterogeneous clusters. In this paper, we focus on the partition strategy of consistent hashing ring and propose a data partition quantified criterion. When initializing a cluster, we convert the problem to an optimization problem to find the most even partitioning result. Experiments on Cassandra and Voldemort show these methods are better than current implementations. Besides, the algorithms are very efficient even for heterogeneous clusters.
A¡ective picture perception: gender di¡erences in visual cortex?

Activity in extrastriate visual cortex is greater when people viewemotionalrelativetoneutralpictures.Priorbrainimagingandpsy-chophysiologicalwork has further suggestedabias formen tore-act more strongly to pleasant pictures, and for women to reactmore strongly to unpleasantpictures.Hereweinvestigatedvisualcortical activity using fMRI in 28 men and women during pictureviewing.Menandwomenshowedreliablygreatervisualcorticalre-activity during both pleasant and unpleasant pictures, relative toneutral, consistent with the view that the motivational relevanceofvisualstimulidirectsattentionandenhanceselaborativepercep-tualprocessing.However,mendidshowgreaterextrastriateactiv-ity than women speci¢cally during erotic picture perception,possibly re£ecting a gender-speci¢c visual mechanism for sexualselection. NeuroReport15:1109^1112 c 2004 Lippincott Williams &Wilkins.
Viral load drives disease in humans experimentally infected with respiratory syncytial virus.

RATIONALE Respiratory syncytial virus (RSV) is the leading cause of childhood lower respiratory infection, yet viable therapies are lacking. Two major challenges have stalled antiviral development: ethical difficulties in performing pediatric proof-of-concept studies and the prevailing concept that the disease is immune-mediated rather than being driven by viral load. OBJECTIVES The development of a human experimental wild-type RSV infection model to address these challenges. METHODS Healthy volunteers (n = 35), in five cohorts, received increasing quantities (3.0-5.4 log plaque-forming units/person) of wild-type RSV-A intranasally. MEASUREMENTS AND MAIN RESULTS Overall, 77% of volunteers consistently shed virus. Infection rate, viral loads, disease severity, and safety were similar between cohorts and were unrelated to quantity of RSV received. Symptoms began near the time of initial viral detection, peaked in severity near when viral load peaked, and subsided as viral loads (measured by real-time polymerase chain reaction) slowly declined. Viral loads correlated significantly with intranasal proinflammatory cytokine concentrations (IL-6 and IL-8). Increased viral load correlated consistently with increases in multiple different disease measurements (symptoms, physical examination, and amount of nasal mucus). CONCLUSIONS Viral load appears to drive disease manifestations in humans with RSV infection. The observed parallel viral and disease kinetics support a potential clinical benefit of RSV antivirals. This reproducible model facilitates the development of future RSV therapeutics.
Optimal wire retiming without binary search

The problem of retiming over a netlist of macro-blocks to achieve the minimal clock period, where the block internal structures may not be changed and flip-flops may not be inserted on some wire segments, is called the optimal wire retiming problem. To the best of our knowledge, there is no polynomial-time approach to solve it and the existence of such an approach is still an open question. We present a brand new algorithm that solves the optimal wire retiming problem with polynomial-time worst case complexity. Since the new algorithm avoids binary search and is essentially incremental, it has the potential of being combined with other optimization techniques. Experimental results show that the new algorithm is very efficient in practice.
Analyzing Gene Expression from Whole Tissue vs. Different Cell Types Reveals the Central Role of Neurons in Predicting Severity of Alzheimer’s Disease

Alterations in gene expression resulting from Alzheimer’s disease have received considerable attention in recent years. Although expression has been investigated separately in whole brain tissue, in astrocytes and in neurons, a rigorous comparative study quantifying the relative utility of these sources in predicting the progression of Alzheimer’s disease has been lacking. Here we analyze gene expression from neurons, astrocytes and whole tissues across different brain regions, and compare their ability to predict Alzheimer’s disease progression by building pertaining classification models based on gene expression sets annotated to different biological processes. Remarkably, we find that predictions based on neuronal gene expression are significantly more accurate than those based on astrocyte or whole tissue expression. The findings explicate the central role of neurons, particularly as compared to glial cells, in the pathogenesis of Alzheimer’s disease, and emphasize the importance of measuring gene expression in the most relevant (pathogenically ‘proximal’) single cell types.
Overcoming the Prevalent Decomposition in Legacy Code

The potential benefits of advanced separation of concerns (ASOC) techniques are well known and many programmers find the idea of using them appealing. For new software engineering projects these modularization mechanisms offer guidelines of how to structure the system modules. But how can legacy systems profit from them? Code related to concerns not represented in the current modularization has to be carefully identified and extracted while preserving system integrity.
Fault tolerant adaptive neuro-fuzzy based automated cruise controller on FPGA

The objective of the paper is to implement a system which effectively reduces vehicle collisions by using a combination of image processing and neuro-fuzzy based techniques. It uses an image processing module in order to determine the distance of the front vehicle. The distance measurements are given to a sugeno type adaptive neuro-fuzzy system. Since the operation of the system is mission critical in nature, a fault tolerant field programmable gate array (FPGA) implementation of the system is proposed to balance the reliability, availability and performance criteria. Finally, a comparison is made with respect to difference in errors and speed, between neural network and adaptive neuro-fuzzy based methods.
Diagnosing Cerebral Collateral Flow Patterns: Accuracy of Non-Invasive Testing

Objective: With routine use of non-invasive methods to assess the internal carotid artery, it becomes increasingly important to clarify the diagnostic accuracy of transcranial Doppler (TCD) ultrasound and magnetic resonance angiography (MRA) compared with intra-arterial digital subtraction angiography (iaDSA) for the detection of collateral flow via the major intracerebral collateral branches. Subjects and Methods: In a prospective study, we compared TCD via a temporal bone window and MRA (flow direction sensitive phase contrast and time of flight) examinations of the intracranial collateral flow with iaDSA in a cohort of 97 consecutive patients with recent transient or minor disabling cerebral ischaemia associated with an occlusion of the carotid artery (38 contralateral stenosis >70%). Results: iaDSA allowed the evaluation of collateral flow via the anterior and posterior circle of Willis in 97 and 67 patients, respectively, TCD in 76 of 97 and 66 of 67 patients, MRA in 95 of 97 and 66 of 67 patients. MRA and TCD collateral flow measurements via the anterior part of the circle of Willis yielded a sensitivity of 83 and 82%, a specificity of 77 and 79% and a similar accuracy of 80%. MRA and TCD collateral flow measurements via the posterior communicating artery yielded a sensitivity of 33 and 76%, a specificity of 88 and 47% and an accuracy of 47 and 68%. Conclusion: As compared with iaDSA, combined MRA and TCD has a moderate to good diagnostic value for the examination of intracranial collateral flow in patients with symptomatic carotid occlusion.
The impact of organizational justice on work performance: Mediating effects of organizational commitment and leader‐member exchange

Purpose - The purpose of this paper is to develop and test a model that identifies the impact of organizational justice on work performance. The model examined the mediating role played by organizational commitment and leader-member exchange (LMX) in linking organizational justice and work performance. Design/methodology/approach - The data were collected from 793 completed questionnaires sampling employees from industries across the People's Republic of China. The questionnaire included scales to measure organizational justice, organizational commitment, LMX, and work performance. The measurement of constructs and the hypothesized relationships among variables were assessed by the use of structural equation modeling. The Baron and Kenny approach was used to test the mediating effects. Findings - First, the relationship of organizational justice to work performance was mostly indirect, mediated by organizational commitment and LMX. Second, among the three kinds of organizational justice, interactional justice was the best predictor of performance. Lastly, organizational commitment accounted for more of the variance than LMX did in the mediating mechanism. Research limitations/implications - The model developed in this article provides important insights in the study of the relationship between organizational justice and work performance. Future research needs to examine the model using a cross-national sample. Originality/value - The link between organizational justice and work performance was mostly mediated by organizational commitment and LMX.
A Relevance-Based Language Modeling approach to DUC 2005

The task in Document Understanding Conferences (DUC 1 ) 2005 is to generate xed length, user oriented, multi document summary. Our approach to address this task is primarily motivated by the observation that metrics based on key concepts overlap give better results when compared to metrics based on n-gram and sentence overlap. In this paper, we present a sentence extraction based summarization system which scores the sentences using Relevance Based Language Modeling, Latent Semantic Indexing and number of special words. From these scored sentences, the system generates a summary of required granularity. Our summarization system was ranked 3 rd ,4 th ,8 th and 17 th in ROUGE-SU4, ROUGE-2, responsiveness and linguistic quality evaluations respectively. In post DUC analysis we found that LSI has negative eect on the systems performance, and the performance gained by 5.4% when it is implemented using language modeling and number of special words.
Control of Dry Season Evapotranspiration over the Amazonian Forest as Inferred from Observations at a Southern Amazon Forest Site

The extent to which soil water storage can support an average dry season evapotranspiration (ET) is investigated using observations from the Rebio Jaru site for the period of 2000 to 2002. During the dry season, when total rainfall is less than 100 mm, the soil moisture storage available to root uptake in the top 3-m layer is sufficient to maintain the ET rate, which is equal to or higher than that in the wet season. With a normal or less-than-normal dry season rainfall, more than 75% of the ET is supplied by soil water below 1 m, whereas during a rainier dry season, about 50% of ET is provided by soil water from below 1 m. Soil moisture below 1-m depth is recharged by rainfall during the previous wet season: dry season rainfall rarely infiltrates to this depth. These results suggest that, even near the southern edge of the Amazon forest, seasonal and moderate interannual rainfall deficits can be mitigated by an increase in root uptake from deeper soil. How dry season ET varies geographically within the Amazon and what might control its geographic distribution are examined by comparing in situ observations from 10 sites from different areas of Amazonia reported during the last two decades. Results show that the average dry season ET varies less than 1 mm day 1 or 30% from the driest to nearly the wettest parts of Amazonia and is largely correlated with the change of surface net radiation of 25% and 30%. Thus the geographic variation of the average dry season ET appears to be mainly determined by the surface radiation.
A novel mutation in the PSEN1 gene (L286P) associated with familial early‐onset dementia of Alzheimer type and lobar haematomas

The aim of this study was to describe a novel mutation in exon 8 of the presenilin gene (L286P) associated with early‐onset autosomal dominant Alzheimer's disease (AD) and lobar haematomas. The proband was a woman who developed cognitive decline with predominant memory loss at the age of 35 years. The patient died at the age of 54 years and the neuropathological examination confirmed the diagnosis of AD. Three of her four siblings, one parent and one sibling of her parent had suffered from cognitive decline at ages between 35 and 42 years. Three of them also presented lobar haematomas. The neuropathological examination, available in one of them, disclosed the presence of severe amyloid angiopathy as the cause of the haematoma. The study of PSEN1 gene with single strand conformation polymorphism technique failed to show abnormalities suggestive of mutations. Direct sequencing disclosed the presence of a missense mutation in codon 286 (L286P) in the proband and her already affected descendent, which was absent in the healthy sibling. L286P is a novel mutation in PSEN1 that causes familial early‐onset AD and brain haematomas related to amyloid angiopathy.