Miracle-dz/UniFAR-FTUs huggingface dataset:
GIRLS’ ATTITUDE TOWARDS MATHEMATICS AT INTERMEDIATE LEVEL IN FATA

: This paper investigated the attitude of girls’ students towards mathematics and factors affecting their attitude towards the subject at intermediate level in Federally Administered Tribal Area (FATA). The sample of the study was three hundred and thirty 330 pre-medical girls’ students from six 6 higher secondary schools and inter-colleges in Khyber Agency. A convenience sampling technique was used in the selection of schools while students were randomly selected. Data were collected through a researcher-developed questionnaire with (alpha=0.97) and were analyzed through descriptive statistics. Findings revealed that girls’ attitude towards mathematics was negative. Socio-cultural factors, Stereotypic effects, math’s anxiety, lack of role model in mathematics, deficiency of Mathematics teachers and lack of counseling services in schools/colleges were the main factors responsible for students negative attitude towards the subject. It was, therefore, recommended that revision of present math’s course, introducing math’s short courses, inclusion of description of the female role models in the subject, launching of effective awareness campaigns about mathematics career for girls, overcoming the deficiency of mathematics teachers in schools/colleges and establishing counseling services in schools/colleges were necessary for changing students’ attitude to provide them opportunities to join science, technology, engineering and mathematics fields. attitude. The highest mean score for the statement of item no.2 “Female math’s teachers encourage me to take Math’s” was recorded with Mean=1.48, SD=1.24, falls in the range “strongly disagreed” reflecting that respondents have borrowed negative attitude towards mathematics from the attitude of mathematics teachers. These findings support the results of Labudde (2000) and Adesoji (2008), that teacher’s attitude has strong effect on student’s attitude towards Mathematics. Lee (2002) in his research argued that the quality of relationship between teacher and student has an effect on boy’s and girl’s attitude towards the subject which he/she wishes to study. According to Bransford et al.,( 2000), if teacher is competent, having mastery over Math’s, having pedagogy, knowledge of students and knows how to motivate students towards Math’s it will affect students. While the responses of the respondents to the statements of items no. 6, 7 and 8 are “strongly agreed” with Mean scores= 4.13, 4.24 and 4.25 respectively, shows that school/college administration is the main cause of negative attitude of the respondents towards mathematics. In a research Muti (2005), argued that performance of a student depends on management style of the head teachers to motivate students towards Science and Mathematics. These results are in harmony to the findings of Ndambuki & Mutie that due to lack of guidance and counseling services, many students go and leave the school bearing no idea of the kind of job they should train for. These results also support the conclusions drawn by that there is lack of awareness and sense of significance in government schools on need
WEIGHTED EMPIRICAL LIKELIHOOD IN SOME TWO-SAMPLE SEMIPARAMETRIC MODELS WITH VARIOUS TYPES OF CENSORED DATA

In this article, the weighted empirical likelihood is applied to a general setting of two-sample semiparametric models, which includes biased sampling models and case-control logistic regression models as special cases. For various types of censored data, such as right censored data, doubly censored data, interval censored data and partly interval-censored data, the weighted empirical likelihood-based semiparametric maximum likelihood estimator ( ˜ θ n , ˜ F n ) for the underlying parameter θ 0 and distribution F 0 is derived, and the strong consistency of ( ˜ θ n , ˜ F n ) and the asymptotic normality of ˜ θ n are established. Under biased sampling models, the weighted empirical log-likelihood ratio is shown to have an asymptotic scaled chi-squared distribution for censored data aforementioned. For right censored data, doubly censored data and partly interval-censored data, it is shown that √ n( ˜ F n − F 0 ) weakly converges to a centered Gaussian process, which leads to a consistent goodness-of-ﬁt test for the case-control logistic regression models.
PRIVACY PROTECTION SCHEME FOR PREVENTING THE DISCLOSURE INFORMATION OF USERS PROFILES

— this paper is motivated by the recognition of the need for a finer grain and more personalized privacy in data publication of social networks. We propose a privacy protection scheme that not only prevents the disclosure of identity of users but also the disclosure of selected features in users' profiles. An individual user can select which features of her profile she wishes to conceal. The social networks are modeled as graphs in which users are nodes and features are labels. Labels are denoted either as sensitive or as non-sensitive. We treat node labels both as background knowledge an adversary may possess, and as sensitive information that has to be protected. We present privacy protection algorithms that allow for graph data to be published in a form such that an adversary who possesses information about a node's neighborhood cannot safely infer its identity and its sensitive labels. To this aim, the algorithms transform the original graph into a graph in which nodes are sufficiently indistinguishable. The algorithms are designed to do so while losing as little information and while preserving as much utility as possible. We evaluate empirically the extent to which the algorithms preserve the original graph's structure and properties. We show that our solution is effective, efficient and scalable while offering stronger privacy guarantees than those in previous research.
Induced by Cytotoxic Lymphocytes Caspase Dependence of Target Cell Damage

Since the CTL secreted granule protease granzyme B can activate multiple target caspases, it has been proposed that this pathway is responsible for CTL-induced cytolysis of Fas-negative targets. However, target lysis via the granule exocytosis pathway is completely resistant to caspase inhibitors. To test the possibility that granzymes trigger a postcaspase cytoplasmic apoptotic pathway leading to lysis, we have examined the caspase dependence of several cytoplasmic changes associated with apoptotic death. Rapid prelytic phosphatidylserine externalization was induced in Jurkat target cells by both the Fas ligand (FasL)/Fas and the granule exocytosis effector pathways. This was speciﬁcally blocked by peptide ketone caspase inhibitors when induced by the former, but not by the latter, pathway. A rapid prelytic loss of target mitochondrial c was also induced by both CTL effector pathways, and this was also speciﬁcally blocked by caspase inhibitors when induced by the FasL/Fas, but not by the granule exocytosis, pathway. Similarly, target membrane blebbing induced by CTL via the FasL/Fas, but not via the granule exocytosis, effector pathway was speciﬁcally blocked by caspase inhibitors. In contrast to the above nonnuclear damage, CTL-induced target staining by the lipid probe FM1–43 reﬂecting plasma membrane endocytosis was blocked by caspase inhibitors. Thus, when caspase activation is blocked, the granule exocytosis pathway triggers several parameters of target apoptotic damage in addition to lysis, suggesting that granzymes directly trigger a postcaspase cytoplasmic apoptotic death pathway. The Journal of Immunology, 1998, 161: 2810–2816. by cell mM FM1–43 and cytometer. FM1–43, , these experiments (two-dimensional and deﬁned running effectors and This approach limited these experiments to modest E:T cell
A Review of Non-Isolated High Step-Down Dc-Dc Converters

In this paper, a review of the common techniques used for high step-down dc-dc voltage conversion is presented. First, the limitations of conventional buck & synchronous rectifier buck converters used for high step down dc-dc voltage conversion which include narrow duty cycle, high voltage stress, large ripple and low efficiency are briefly discussed. Then various topologies of non-isolated step-down dc-dc converters are reviewed and discussed. The topologies/techniques used for high step down dc-dc conversion are divided into various groups which include interleaved, quadratic, tapped, switched capacitor, switched inductor, coupled inductor, multi level and buck converter with three state switching cells. Each group of converters is briefly discussed, main circuit structure of each topology is given and their features and limitations are given. Finally a comparison of all the discussed topologies is carried out based on some common features.
Transcriptional Mechanisms Involved in Long-term Potentiation of Hippocampal Neurons

350 words maximum: (PLEASE TYPE) Long-term potentiation (LTP), the persistent strengthening of synaptic connections following high frequency stimulation, is a form of synaptic plasticity proposed to underlie memory formation and consolidation. Despite decades of extensive study our understanding of the molecular mechanisms underpinning LTP remains incomplete. Whilst many of the protein components involved in the mechanisms of LTP have been extensively described the long non-protein-coding RNAs (lncRNAs) remain largely unexplored. Expression of lncRNAs is particularly enriched in the mammalian brain where they potentially impact LTP through regulation of epigentetic processes, transcription, mRNA splicing and translation. Characterisation of all the proteins and lncRNAs involved in LTP may elucidate the molecular mechanisms underlying memory formation and consolidation as well as provide greater insight into perturbation of these processes in developmental and neurodegenerative diseases. This study aimed to comprehensively analyse the transcriptome of primary hippocampal neurons, from neonatal mice, undergoing LTP induction in order to identify and quantify the protein-coding genes and ncRNAs expressed during LTP induction. Furthermore, this project aimed to investigate the transcriptomic changes that result from inhibition of LTP through disruption of synaptic adhesion. Analysis of transcriptome sequencing data led to identification of 64 differentially expressed genes, including four unannotated noncoding lincRNAs, across four distinct LTP conditions. Among those genes four distinct expression patterns could be identified. Gene Ontology (GO) analysis identified numerous enriched GO terms including those associated with intracellular signalling, transcriptional and translational regulation, as well as numerous clusters associated with immune response. The novel unannotated transcripts identified in this study were characterised as putative long intervening noncoding RNAs (lincRNAs), two of which demonstrated potential micropeptide expression. Future studies will determine the role and function of these putative lincRNAs in the induction of LTP. Meta-analysis comparing the results of the present study with those of a recent study on LTP induction in rat hippocampal neurons found no common differentially expressed genes. Declaration relating to disposition of project thesis/dissertation I hereby grant to the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or in part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all property rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstracts International (this is applicable to doctoral theses only). Signature . Witness Signature .
Phytoremediation: A Green Technology to Clean Up the Sites with Low and Moderate Level of Heavy Metals

Contamination of soil and water with heavy metals is a serious concern worldwide. It adversely affects - plant growth as well as human health. Remdiation of these contaminated soils and water using phytoremediation provides an opportunity to regain the prestine state of the soil and water environment. This review discusses about the cost effective phytoremediation technology that can be used to remove heavy metalsand other pollutants from contaminated soil and water. Plants having hyperaccumulators use their internal complex system of highly effective homeostatic mechanisms to control the uptake, accumulation, trafficking, and detoxification of metals. A concise overview of numerous approaches of phytoremediation in this review demonstrates that despite of some limitations, phytoremediation is an effective approach for the removal of heavy metals and other contaminants from soil and water.
AIS Electronic Library (AISeL) AIS Electronic Library (AISeL) Feral Practices Feral Practices

In this paper we introduce the concept of feral practices which we define as the usage of information technology which deviates from the standard organizational norms and which exists beyond the control and/or knowledge of the organizational IT management. We argue towards using a ‘practice’ perspective in understanding non-compliant IT practices where we suggest a greater emphasis on usage of IT artifacts rather than the artifacts itself. We also outline a scope of feral practices by clarifying some of the concepts associated with the phenomenon. We propose a model based on the Merton’s Theory of Anomie, which seeks to explain why feral practices come about and what are the technological and social influences and supporting factors which lead to this phenomenon. This study thus intends to build a conceptual base for future studies on feral practices by providing a holistic view on the phenomenon and also identify directions for future research. staff
UnCaDo: Unsure Causal Discovery

Most algorithms to learn causal relationships from data assume that the pro vided data perfectly mirrors the (in)dependencies in the system under study. This allo ws us to recover the correct dependence skeleton and the representative of the Markov eq uivalence class of Bayesian networks that models the data. This complete partially directed acyclic graph contains some directed links that represent a direct causal influence from parent to c In this paper we relax the mentioned requirement by allowingunsure edges in the dependence skeleton. These unsure edges can then be validated and oriented or discarded by performing exp eriments. We present the UnCaDo (UNsure CAusal DiscOvery) algorithm which proposes a nu mber of necessary experiments that need to be done to gain sufficient causal information to co mplete the graph. MOTS-CLES :Reseau Bayesien Causal, Apprentissage de Structure.
Environmental injustice in America: Racial disparities in exposure to air pollution health damages from freight trucking

PM 2.5 produced by freight trucks has adverse impacts on human health. However, it is unknown to what extent freight trucking affects communities of color and the total public health burden arising from the sector. Based on spatially resolved US federal government data, we explore the geographic distribution of freight trucking emissions and demonstrate that Black and Hispanic populations are more likely to be exposed to elevated emissions from freight trucks. Our results indicate that freight trucks contribute ~10% of NO x and ~12% of CO 2 emissions from all sources in the continental US. The annual costs to human health and the environment due to NO x , PM 2.5 , SO 2 , and CO 2 from freight trucking in the US are estimated respectively to be $11B, $5.5B, $110M, and $30B. Overall, the sector is responsible for nearly two-fifths (~$47B out of $120B) of all transportation-related public health damages.
Ascertaining price formation in cryptocurrency markets with machine learning

The cryptocurrency market is amongst the fastest-growing of all the financial markets in the world. Unlike traditional markets, such as equities, foreign exchange and commodities, cryptocurrency market is considered to have larger volatility and illiquidity. This paper is inspired by the recent success of using machine learning for stock market prediction. In this work, we analyze and present the characteristics of the cryptocurrency market in a high-frequency setting. In particular, we applied a machine learning approach to predict the direction of the mid-price changes on the upcoming tick. We show that there are universal features amongst cryptocurrencies which lead to models outperforming asset-specific ones. We also show that there is little point in feeding machine learning models with long sequences of data points; predictions do not improve. Furthermore, we solve the technical challenge to design a lean predictor, which performs well on live data downloaded from crypto exchanges. A novel retraining method is defined and adopted towards this end. Finally, the trade-off between model accuracy and frequency of training is analyzed in the context of multi-label prediction. Overall, we demonstrate that promising results are possible for cryptocurrencies on live data, by achieving a consistent $ 78\% $ 78% accuracy on the prediction of the mid-price movement on live exchange rate of Bitcoins vs. US dollars.
Congestion Avoidance TCP Improvements for Video Streaming

—Video streaming has become the major source of Internet trafﬁc nowadays. Considering that content delivery network providers have adopted Video over Hypertext Transfer Protocol/Transmission Control Protocol (HTTP/TCP) as the preferred protocol stack for video streaming, understanding TCP performance in transporting video streams has become paramount. In our previous work, we have shown how Slow Start of TCP variants play a deﬁnite role in the quality of video experience. In this paper, we research mechanisms within congestion avoidance phase of TCP to enhance video streaming experience. We utilize network performance measurers, as well as video quality metrics, to characterize the performance and interaction between network and application layers of video streams for various network scenarios. We show that video transport performance can be enhanced when playout buffer space is used within TCP congestion avoidance phase.
Efficient Mechanisms for Spatial Approximate String Search for Querying Geographical Databases

-Spatial databases have become popular and they are queried frequently in order to obtain required information. In the search process approximate string search plays an important role in spatial databases. Especially, the range queries with approximate string are a challenging job to be achieved. This is the open problem to be solved with respect to spatial approximate string search. Recently Li et al. proposed a solution for the problem. Their solution considers the query as spatial approximate string (SAS) query. The solution was provided both in Euclidean space and road networks using min-wise signatures and MHR-tree. In this paper we proposed a system which is an extension to the existing system which focuses on building a framework that is capable of examining spatial approximate substring queries, designing methods that are more update friendly to solve the selectivity estimation problem for range queries on road networks represented by spatial database. Thus the proposed system reduces the execution cost and space consumption.
Improved VoIP QoS over Wireless Networks

: Voice over Internet Protocol (VoIP) is a famous time-sensitive voice communication application over the Internet. This technology has observed multiplicative growth in both wired as well as wireless networks. Every day thousands of devices are made which are compatible with the 802.11 and experience good throughput at PHY layer due to introduction of 802.11b, 802.11g, 802.11n and 802.11a standards. The Data link layer uses Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol which allows equal license-free channel sharing between nodes communicating in half duplex mode. CSMA/CA lacks in Quality of Service (QoS) support and priority provision to handle real-time multimedia applications. Challenges of the wireless networks make VoIP implementation a tough task. An amendment of WLANs 802.11e ensures the desired order of preference for channel access to the time-bound applications but the implementation still needs certain points to be considered and worked upon. A novel channel access scheme is developed which ensures QoS of VoIP over any size of wireless network.
AIS Electronic Library (AISeL) A Contingency Theory Motivated Framework to Select Information System Development Methods

Several change-driven (agile) information systems development (ISD) methods have been launched during the recent years. In addition to agile ISD methods it is still possible to succeed also with plan-driven ISD methods. To facilitate ISD method selections that maximize the probability of ISD project success we crafted and evaluated an ISD method selection framework based on the idea of matching the properties of ISD methods and the characteristics of the business contexts where ISD methods are used. We conducted a systematic literature search to evaluate whether the proposed framework is also able to capture the findings of prior ISD method selection research and to guide future empirical research. From over 1000 potential articles we identified 42 articles that address ISD method selection. We discovered that the proposed framework was able to explain the findings of prior research. between plan-driven and change-driven ISD methods. The
Ultra Low Power CMOS Phase Locked Loop synthesizer for Very High Frequencies

— This paper describes the design of an essential component in wireless transceivers, the frequency synthesizer. The synthesizer is implemented using Phase Locked Loop (PLL). Second order PLL, type II, with a reference frequency 10MHz is designed using 180nm analog CMOS process technology. The synthesizer generates signals in frequency range of 10-100 MHz. The simulated power consumption of the system is 37 µ W with a deviation from the true periodicity; root mean square periodic jitter is in range of 5 ps.
An Efficient and Flexible Stochastic CGRA Mapping Approach

Coarse-Grained Reconfigurable Array (CGRA) architectures are promising high-performance and power-efficient platforms. However, mapping applications efficiently on CGRA is a challenging task. This is known to be an NP complete problem. Hence, finding good mapping solutions for a given CGRA architecture within a reasonable time is complex. Additionally, finding scalability in compilation time and memory footprint for large heterogeneous CGRAs is also a well known problem. In this article, we present a stochastic mapping approach that can efficiently explore the architecture space and allows finding best of solutions while having limited and steady use of memory footprint. Experimental results show that our compilation flow allows to reach performances with low-complexity CGRA architectures that are as good as those obtained with more complex ones thanks to the better exploration of the mapping solution space. Parameters considered in our experiments are number of tiles, Register File (RF) size, number of load/store (LS) units, network topologies, and so on. Our results demonstrate that high-quality compilation for a wide range of applications is possible within reasonable run-times. Experiments with several DSP benchmarks show that the best CGRA configuration from the architectural exploration surpasses an ultra low-power DSP optimized RISC-V CPU to achieve up to 15.28× (with an average of 6× and minimum of 3.4×) performance gain and 29.7× (with an average of 13.5× and minimum of 6.3×) energy gain with an area overhead of 1.5× only.