Miracle-dz/UniFAR-FTUs huggingface dataset:
Contourlet-Based Acoustic Seabed Ground Discrimination System

In this paper, the problem of automatic segmentation and classification of seafloor using acoustic ground discrimination systems is discussed and a new split and merge algorithm based on contourlet transform is presented. The contourlet transform is a new two-dimensional extension of the wavelet transform using multiscale and directional filter banks. It appears to be a suitable tool for this task, because it allows analysis of images at various levels of resolution as well as directions, which effectively capture smooth contours that are the dominant feature in seabed images. In the proposed approach, the input image of seabed is split into M times M blocks. Each block is classified separately using four levels of contourlet transform with 28 directional bandpass sub-bands. First-order and second-order statistics of the high frequency details from all sub-bands of the contourlet coefficients are extracted as features and a weighted distance classifier is used for block classification. Moreover, the effectiveness of other contourlet domain features such as sub-band energy in discriminating different seabed textures is presented. Finally, the classified blocks on the boundaries of the segmented image, are refined and merged to produce the final segmented image. The proposed method provides a fast tool with enough accuracy that can be implemented in a parallel structure for real-time processing. In addition, the simulation results are compared with the results of wavelet-based methods as well as other well-known techniques to show the effectiveness of our proposed algorithm.
Mental models of physical causality

The aim of this paper is to present a cognitive model of causal reasoning about the psysical world and a related computational system. The cognitive model is based on the theory of mental models and on two main assumptions, the assumption of reasoning by examples and the assumption of causality by contact. The computational model has been developed using an Extended version of the Qualitative Processes Theory (EQPT); the use of the EQPT as a qualitative simulator allows to represent and treat the various commonsense physical domains.
The zebrafish forkhead transcription factor Foxi1 specifies epibranchial placode-derived sensory neurons

Vertebrate epibranchial placodes give rise to visceral sensory neurons that transmit vital information such as heart rate, blood pressure and visceral distension. Despite the pivotal roles they play, the molecular program underlying their development is not well understood. Here we report that the zebrafish mutation no soul, in which epibranchial placodes are defective, disrupts the fork headrelated, winged helix domain-containing protein Foxi1. Foxi1 is expressed in lateral placodal progenitor cells. In the absence of foxi1 activity, progenitor cells fail to express the basic helix-loop-helix gene neurogenin that is essential for the formation of neuronal precursors, and the paired homeodomain containing gene phox2a that is essential for neuronal differentiation and maintenance. Consequently, increased cell death is detected indicating that the placodal progenitor cells take on an apoptotic pathway. Furthermore, ectopic expression of foxi1 is sufficient to induce phox2a-positive and neurogenin-positive cells. Taken together, these findings suggest that Foxi1 is an important determination factor for epibranchial placodal progenitor cells to acquire both neuronal fate and subtype visceral sensory identity.
Phenolics: Occurrence and Immunochemical Detection in Environment and Food

Phenolic compounds may be of natural or anthropogenic origin and be present in the environment as well as in food. They comprise a large and diverse group of compounds that may be either beneficial or harmful for consumers. In this review first a non-exhausting overview of interesting phenolics is given, in particular with regards to their presence in environment and food. For some of these compounds, beneficial, toxicological and/or optionally endocrine disrupting activities will be presented. Further, immunochemical detection and/or isolation methods developed will be discussed, including advantages and disadvantages thereof in comparison with conventional analytical methods such as HPLC, GC, MS. A short overview of new sensor-like methods will also be included for present and future application.
Protease substrate site predictors derived from machine learning on multilevel substrate phage display data

MOTIVATION Regulatory proteases modulate proteomic dynamics with a spectrum of specificities against substrate proteins. Predictions of the substrate sites in a proteome for the proteases would facilitate understanding the biological functions of the proteases. High-throughput experiments could generate suitable datasets for machine learning to grasp complex relationships between the substrate sequences and the enzymatic specificities. But the capability in predicting protease substrate sites by integrating the machine learning algorithms with the experimental methodology has yet to be demonstrated. RESULTS Factor Xa, a key regulatory protease in the blood coagulation system, was used as model system, for which effective substrate site predictors were developed and benchmarked. The predictors were derived from bootstrap aggregation (machine learning) algorithms trained with data obtained from multilevel substrate phage display experiments. The experimental sampling and computational learning on substrate specificities can be generalized to proteases for which the active forms are available for the in vitro experiments. AVAILABILITY http://asqa.iis. sinica.edu. tw/fXaWeb/
Understanding the Dark Side of Big Data Clusters: An Analysis beyond Failures

Motivated by the high system complexity of today's datacenters, a large body of related studies tries to understand workloads and resource utilization in datacenters. However, there is little work on exploring unsuccessful job and task executions. In this paper, we study three types of unsuccessful executions in traces of a Google datacenter, namely fail, kill, and eviction. The objective of our analysis is to identify their resource waste, impacts on application performance, and root causes. We first quantitatively show their strong negative impact on CPU, RAM, and DISK usage and on task slowdown. We analyze patterns of unsuccessful jobs and tasks, particularly focusing on their interdependency. Moreover, we uncover their root causes by inspecting key workload and system attributes such as machine locality and concurrency level. Our results help in the design of low-latency and fault-tolerant big-data systems.
Impairment of Angiogenic Sphingosine Kinase-1/Sphingosine-1-Phosphate Receptors Pathway in Preeclampsia

Preeclampsia (PE), is a serious pregnancy disorder characterized in the early gestation by shallow trophoblast invasion, impaired placental neo-angiogenesis, placental hypoxia and ischemia, which leads to maternal and fetal morbidity and mortality. Here we hypothesized that angiogenic sphingosine kinase-1 (SPHK1)/sphingosine-1-phosphate (S1P) receptors pathway is impaired in PE. We found that SPHK1 mRNA and protein expression are down-regulated in term placentae and term chorionic villous explants from patients with PE or severe PE (PES), compared with controls. Moreover, mRNA expression of angiogenic S1PR1 and S1PR3 receptors were decreased in placental samples of PE and PES patients, whereas anti-angiogenic S1PR2 was up-regulated in chorionic villous tissue of PES subjects, pointing to its potential atherogenic and inflammatory properties. Furthermore, in in vitro (JAR cells) and ex vivo (chorionic villous explants) models of placental hypoxia, SPHK1 mRNA and protein were strongly up-regulated under low oxygen tension (1% 02). In contrast, there was no change in SPHK1 expression under the conditions of placental physiological hypoxia (8% 02). In both models, nuclear protein levels of HIF1A were increased at 1% 02 during the time course, but there was no up-regulation at 8% 02, suggesting that SPHK1 and HIF1A might be the part of the same canonical pathway during hypoxia and that both contribute to placental neovascularization during early gestation. Taken together, this study suggest the SPHK1 pathway may play a role in the human early placentation process and may be involved in the pathogenesis of PE.
Transcriptome analysis by strand-specific sequencing of complementary DNA

High-throughput complementary DNA sequencing (RNA-Seq) is a powerful tool for whole-transcriptome analysis, supplying information about a transcript's expression level and structure. However, it is difficult to determine the polarity of transcripts, and therefore identify which strand is transcribed. Here, we present a simple cDNA sequencing protocol that preserves information about a transcript's direction. Using Saccharomyces cerevisiae and mouse brain transcriptomes as models, we demonstrate that knowing the transcript's orientation allows more accurate determination of the structure and expression of genes. It also helps to identify new genes and enables studying promoter-associated and antisense transcription. The transcriptional landscapes we obtained are available online.
FORECASTING SPOT ELECTRICITY PRICES WITH TIME SERIES MODELS

In this paper we study simple time series models and assess their forecasting performance. In particular we calibrate ARMA and ARMAX (where the exogenous variable is the system load) processes. Models are tested on a time series of California power market system prices and loads from the period proceeding and including the market crash.
Evaluation of ninety-three major Greek university departments using Google Scholar

In this article, 93 Greek university departments were evaluated according to their academics’ h-index. A representative sample from the fields of social sciences and humanities, sciences, engineering, pharmacy and economics was adopted. In the reported study, 3354 (approximately 1 out of 3) academics serving in Greek universities were evaluated. The number of papers, citations and h-index have been collected for each academic, department, school and university using the Google Scholar scientific database and the citations analysis software program Publish or Perish. Analysis revealed that departments of the same academic discipline but located in different universities are characterised by strong differences on the scientific outcome. In addition, in the majority of the evaluated departments, a significant difference in h-index was observed between academics who report scientific activity on the departments’ website and those who do not. The viability of the adopted method for measuring and ranking the scientific performance of higher education departments proved to be quite high.
Probabilistic polling MAC protocol with unslotted CSMA for wireless sensor networks (WSNs)

Wireless sensor networks (WSNs) may lead to high traffic in network when nodes detect an event and become active to send the data to the sink. Therefore, traffic adaptive medium access control (MAC) protocol for WSNs, with a more strict collision avoidance technique, can help in resolving the issue of collision by allowing less number of sensor nodes to send the data on the shared wireless channel. Probabilistic polling is a receiver-initiated MAC protocol proposed for energy harvesting wireless sensor networks (EH-WSNs), with a channel access mechanism known as contention probability. In this mechanism the receiver sets a pre-condition for the nodes who want to relay their packets to the receiver. Node that satisfies the condition can send their data packets. In this paper, the performance of probabilistic polling protocol for battery powered wireless sensor networks (BP-WSNs) is studied instead of EH-WSNs. Also unslotted CSMA probabilistic polling (UCSMA probabilistic polling) protocol is proposed that uses the contention probability along with un-slotted CSMA/CA as channel access mechanism. The simulation results show that UCSMA probabilistic polling protocol can improve the network performance in term of high throughput and fairness.
Development of a French speech recognizer using a hybrid HMM/MLP system

In this paper we describe the development of a French speech recognizer, and the experiments we carried out on our hybrid HMM/ANN system which combines Arti(cid:12)cial Neural Networks (ANN) and Hidden Markov Models (HMMs). A phone recognition experiment with our baseline system achieved a phone accuracy of about 75% which is very similar to the best results reported in the literature [1]. Preliminary experiments on continuous speech recognition have set a baseline performance for our hybrid HMM/ANN system on BREF using lexicons of di(cid:11)erent sizes. All the experiments were carried out with the STRUT (Speech Training and Recognition Uni(cid:12)ed Toolkit) software [2] and the NOWAY large vocabulary decoder [3]
Deep Impact: Impact Factors and Accounting Research

The impact of accounting research has been the subject of several studies over the past 30 years. Impact factors using citation analysis is the major method of evaluating the impact of accounting research and ranking accounting journals. Studies of the impact of accounting research using citation analysis have been conducted on faculty, doctoral students, and departments of accounting. Impact factor and citation analysis are considered by some to serve as proxies for the value or contribution of a journal or article. However, few question the meaning of impact factors or understand how impact factors are calculated. This paper discusses the meaning of impact factors and their importance in accounting research, and the potential for manipulating impact factors to the detriment of developing and producing accounting knowledge. The purpose of the paper is to pull back the curtain that veils the true meaning of impact factors.
Electronic Theses and Dissertations UC San Diego Peer Reviewed Title : Macroevolutionary and coevolutionary models in biogeography

ix Part I. Macroevolutionary Models 1 Chapter 1. Diversity, endemism, and age distributions in macroevolutionary sources and sinks . 2 Chapter 2. Origination, extinction and dispersal: integrative models for understanding present-day diversity gradients . 18 Part II. Coevolutionary Models 48 Chapter 3. Ecological and reproductive character displacement on an environmental gradient . 49 Chapter 4. Species’ borders and dispersal barriers . 65
Model-based techniques for noise robust speech recognition

This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration, except where stated. It has not been submitted in whole or part for a degree at any other university. The length of this thesis including footnotes and appendices is approximately 36,000 words. i Summary This thesis details the development of a model-based noise compensation technique, Parallel Model Combination (PMC). The aim of PMC is to alter the parameters of a set of Hidden Markov Model (HMM) based acoustic models, so that they reeect speech spoken in a new acoustic environment. Diierences in the acoustic environment may result from additive noise, such as cars passing and fans; or convolutional noise, such as channel diierences between training and testing. Both these classes of noise have been found to seriously degrade speech recognition performance and both may be handled within the PMC framework. The eeect of noise on the clean speech distributions and associated parameters was investigated. The shape of the corrupted-speech distribution could become distinctly non-Gaussian, even when Gaussian speech and noise sources were used. This indicates that, to achieve good performance in additive noise, some exibility in the component alignments, or number, is required within a state. For the model parameters, additive noise was found to alter all the means and the variances of both the static and, where present, dynamic coeecients. This shifting of HMM parameters was observed in terms of both a distance measure, the average Kullback-Leibler number on a feature vector component level, and the eeect on word accuracy. For best performance in noise-corrupted environments, it is necessary to compensate all these parameters. Various methods for compensating the HMMs are described. These may be split into two classes. The rst, non-iterative PMC, assumes that the frame/state component alignment associated with the speech models and the clean speech data is unaltered by the addition of noise. This implies that the corrupted-speech distributions are approximately Gaussian, which is known to be false. However, this assumption allows rapid adaptation of the model parameters. The second class of PMC is iterative PMC, where only the frame/state alignment is assumed unaltered. By allowing the component alignment within a state to vary, it is possible to better model the corrupted-speech distribution. One implementation is described, Data-driven Parallel Model Combination (DPMC). A simple and eeective method of estimating the convolutional noise component in the …
A 1 V 250 KPPS 90 NM CMOS pulse based transceiver for CM-range wireless communication

We present a baseband pulse based transceiver for centimeter range wireless communication. It is implemented in 90 nm CMOS technology and uses a 0.5 cm2 on board inductor as antenna to reduce cost and minimize size. All the timing information is extracted from the incoming pulse sequence by means of an on-chip Phase Locked Loop whose output is used to duty cycle the receiver and drive the transmitter, obviating the need for an on board quartz reference. The complete system integrates front end, antenna and clock-recovery in a single module with cm2 size. At 250 Kpps, the transceiver consumes 257 muW (6 muW TX, 181muW RX, 70 muW PLL), corresponding to an energy consumption of InJ/pulse.
Application of the Filariasis CELISA Antifilarial IgG4 Antibody Assay in Surveillance in Lymphatic Filariasis Elimination Programmes in the South Pacific

Elimination of lymphatic filariasis (LF) in the Pacific Island Countries and Territories (PICT) has been defined as <0.1% circulating filarial antigen (CFA) prevalence in children born after the implementation of successful mass drug administrations (MDAs). This research assessed the feasibility of CFA and antibody testing in three countries; Tonga, Vanuatu, and Samoa. Transmission is interrupted in Vanuatu and Tonga as evidenced by no CFA positive children and a low antibody prevalence and titre. Transmission is ongoing in Samoa with microfilaraemic (Mf) and CFA positive children and a high antibody prevalence and titre. Furthermore, areas of transmission were identified with Mf positive adults, but no CFA positive children. These areas had a high antibody prevalence in children. In conclusion, CFA testing in children alone was not useful for identifying areas of residual endemicity in Samoa. Thus, it would be beneficial to include antibody serology in the PICT surveillance strategy.
Here We Grow Again! the Limits of State Financial Crises as Drivers for Policy Change, the Case of Canadian Publicly Funded Health Care, Evidence from Ontario

State finance crises can be used as levers to facilitate major policy changes. They can facilitate the opening or widening of windows for major changes in policies and even the over-arching macro-policy paradigm that shapes all other public-policy choices. This paper looks at the limits to this strategy through a case study of publicly funded health care in the Canadian province of Ontario. Ontario has a universal public health insurance system. Decision-makers have long been aware that the aging of society and other evolving factors will place pressures on the system unless the balance within the system of hospital vs. community care is adjusted. In the mid-1990s the government of the time appeared determined to make the necessary reforms, using its financial crisis as a lever. The changes that resulted proved short-lived and a major hospital building program is now under way. The paper explains this failure by reference to Tuohy’s theory of organizing logics. Although crises can be used to overcome some forms of resistance, when resistance is founded in organizing logics and/or founding principles it tends to be more resilient. Such forces must be harnessed in the service of change if reform is to succeed. The paper concludes by assessing what general lessons proponents of health care reform in Canada and other countries can learn from this case.
Oral contraception following abortion

AbstractOral contraceptives (OCs) following induced abortion offer a reliable method to avoid repeated abortion. However, limited data exist supporting the effective use of OCs postabortion. We conducted this systematic review and meta-analysis in the present study reported immediate administration of OCs or combined OCs postabortion may reduce vaginal bleeding time and amount, shorten the menstruation recovery period, increase endometrial thickness 2 to 3 weeks after abortion, and reduce the risk of complications and unintended pregnancies.A total of 8 major authorized Chinese and English databases were screened from January 1960 to November 2014. Randomized controlled trials in which patients had undergone medical or surgical abortions were included. Chinese studies that met the inclusion criteria were divided into 3 groups: administration of OC postmedical abortion (group I; n = 1712), administration of OC postsurgical abortion (group II; n = 8788), and administration of OC in combination with traditional Chinese medicine postsurgical abortion (group III; n = 19,707). In total, 119 of 6160 publications were included in this analysis. Significant difference was observed in group I for vaginal bleeding time (P = 0.0001), the amount of vaginal bleeding (P = 0.03), and menstruation recovery period (P < 0.00001) compared with the control groups. Group II demonstrated a significant difference in vaginal bleeding time (P < 0.00001), the amount of vaginal bleeding (P = 0.0002), menstruation recovery period (P < 0.00001), and endometrial thickness at 2 (P = 0.003) and 3 (P < 0.00001) weeks postabortion compared with the control group. Similarly, a significant difference was observed in group III for reducing vaginal bleeding time (P < 0.00001) and the amount of vaginal bleeding (P < 0.00001), shortening the menstruation recovery period (P < 0.00001), and increasing endometrial thickness 2 and 3 weeks after surgical abortion (P < 0.00001, all). Immediate administration of OCs postabortion may reduce vaginal bleeding time and amount, shorten the menstruation recovery period, increase endometrial thickness 2 to 3 weeks after abortion, and reduce the risk of complications and unintended pregnancies.
A Theory of Volumetric Growth for Compressible Elastic Biological Materials

A general theory of volumetric growth for compressible elastic materials is presented. The authors derive a complete set of governing equations in the present configuration for an elastic material undergoing a continuous growth process. In particular, they obtain two constitutive restrictions from a work-energy principle. First, the authors show that a growing elastic material behaves as a Green-elastic material. Second, they obtain an expression that relates the stress power due to growth to the rate of energy change due to growth. Then, the governing equations for a small increment of growth are derived from the more general theory. The equations for the incremental growth boundary-value problem provide an intuitive description of the quantities that describe growth and are used to implement the theory. The main features of the theory are illustrated with specific examples employing two strain energy functions that have been used to model biological materials.