Miracle-dz/UniFAR-FTUs huggingface dataset:
Block Diagonalization Type Precoding Algorithms for IEEE 802.11ac Systems

Block diagonalization (BD) based precoding schemes are well-known linear transmit strategies employed in the downlink of multi-user multiple-input multipleoutput (MU-MIMO) systems. BD type precoding algorithms employed at the transmit side effect the suppression of multi-user interference (MUI) by the decomposition of MU-MIMO broadcast channel into multiple single-user MIMO (SU-MIMO) channels followed by parallelization of the SU-MIMO channels to obtain independent streams of each user. Given that the design of linear precoding algorithms has made significant progress, the implementation of these techniques in standards for wireless local area networks (WLAN) remains an open question. In this work, schemes for implementation of BD based precoding techniques in the framework of IEEE 802.11ac standard are proposed followed by performance evaluation of these techniques in the proposed framework. I analyze the sum-rate and the bit-error-rate (BER) performance of the techniques in my framework and obtain computational complexity-wise as well as performance-wise optimal algorithm for my system.
God Help the Child

'What you do to children matters. And they might never forget'. Sweetness wants to love her child, Bride, but she struggles to love her as a mother should. Bride, now glamorous, grown up, ebony-black and panther-like, wants to love her man, Booker, but she finds herself betrayed by a moment in her past, a moment borne of a desperate burn for the love of her mother. Booker cannot fathom Bride's depths, with his own love-lorn past bending him out of shape. Can they find a way through the damage wrought on their blameless childhood souls, to light and happiness, free from pain? Toni Morrison's fierce and provocative new novel exposes the damage adults wreak on children, and how this echoes through the generations.
Imprecise Datapath Design: An Overclocking Approach

In this article, we describe an alternative circuit design methodology when considering trade-offs between accuracy, performance, and silicon area. We compare two different approaches that could trade accuracy for performance. One is the traditional approach where the precision used in the datapath is limited to meet a target latency. The other is a proposed new approach which simply allows the datapath to operate without timing closure. We demonstrate analytically and experimentally that on average our approach obtains either smaller errors or equivalent faster operating frequencies in comparison to the traditional approach. This is because the worst case caused by timing violations only happens rarely, while precision loss results in errors to most data. We also show that for basic arithmetic operations such as addition, applying our approach to the simple building block of ripple carry adders can achieve better accuracy or performance than using faster adder designs to achieve similar latency.
The crystal structure of Pyrococcus furiosus RecJ implicates it as an ancestor of eukaryotic Cdc45

Abstract RecJ nucleases specifically degrade single-stranded (ss) DNA in the 5′ to 3′ direction. Archaeal RecJ is different from bacterial RecJ in sequence, domain organization, and substrate specificity. The RecJ from archaea Pyrococcus furiosus (PfuRecJ) also hydrolyzes RNA strands in the 3′ to 5′ direction. Like eukaryotic Cdc45 protein, archaeal RecJ forms a complex with MCM helicase and GINS. Here, we report the crystal structures of PfuRecJ and the complex of PfuRecJ and two CMPs. PfuRecJ bind one or two divalent metal ions in its crystal structure. A channel consisting of several positively charged residues is identified in the complex structure, and might be responsible for binding substrate ssDNA and/or releasing single nucleotide products. The deletion of the complex interaction domain (CID) increases the values of kcat/Km of 5′ exonuclease activity on ssDNA and 3′ exonuclease activity on ssRNA by 5- and 4-fold, respectively, indicating that the CID functions as a regulator of enzymatic activity. The DHH domain of PfuRecJ interacts with the C-terminal beta-sheet domain of the GINS51 subunit in the tetrameric GINS complex. The relationship of archaeal and bacterial RecJs, as well as eukaryotic Cdc45, is discussed based on biochemical and structural results.
Liver iron is predictive of death in alcoholic cirrhosis: a multivariate study of 229 consecutive patients with alcoholic and/or hepatitis C virus cirrhosis: a prospective follow up study

BACKGROUND/AIMS A study was undertaken of liver biopsy samples from 229 consecutive patients with alcoholic or hepatitis C virus related cirrhosis who were prospectively followed until January 1996 to evaluate the influence of liver iron content on survival and the occurrence of hepatocellular carcinoma. METHODS Hepatic iron content was measured with a validated semiquantitative score, and its predictive value for survival and the occurrence of hepatocellular carcinoma was assessed. RESULTS 130 patients had detectable iron at enrolment. During follow up (57 (28) months), 95 patients died and 39 patients developed hepatocellular carcinoma. No significant relation was found between hepatic iron and the occurrence of hepatocellular carcinoma. Conversely, the presence of iron was predictive of death in alcoholic patients (p = 0.007) by the log rank test but not in patients with hepatitis C virus related (p = 0.71) or mixed (p = 0.98) cirrhosis. The predictive value of hepatic iron content in patients with alcoholic cirrhosis was confirmed by the Cox model using either a binary coding (p = 0.009; relative risk = 2.27; 95% confidence interval 1.2 to 4.19) or the continuous values (p = 0.002). CONCLUSIONS These results suggest that hepatic iron enhances liver lesions caused by alcohol but not those caused by hepatitis C virus.
Direct Manipulation in Tactile Displays

Tactile displays have predominantly been used for information transfer using patterns or as assistive feedback for interactions. With recent advances in hardware for conveying increasingly rich tactile information that mirrors visual information, and the increasing viability of wearables that remain in constant contact with the skin, there is a compelling argument for exploring tactile interactions as rich as visual displays. Direct Manipulation underlies much of the advances in visual interactions. In this work, we introduce the concept of a Direct Manipulation-enabled Tactile display (DMT). We define the concepts of a tactile screen, tactile pixel, tactile pointer, and tactile target which enable tactile pointing, selection and drag & drop. We build a proof of concept tactile display and study its precision limits. We further develop a performance model for DMTs based on a tactile target acquisition study. Finally, we study user performance in a real-world DMT menu application. The results show that users are able to use the application with relative ease and speed.
Genomic and EST microsatellites for Rhododendron aureum (Ericaceae) and cross-amplification in other congeneric species.

UNLABELLED PREMISE OF THE STUDY Our objective of this study was to develop genomic and expressed sequence tag (EST)-derived microsatellites for the endangered species Rhododendron aureum and access their transferability in R. dauricum and R. brachycarpum. • METHODS AND RESULTS Twelve genomic microsatellites were isolated in R. aureum using the Fast Isolation by AFLP of Sequences Containing repeats (FIASCO) protocol and seven EST-derived microsatellites were characterized by screening the Rhododendron dbEST database of GenBank. The number of alleles per locus ranged from one to eight. The observed and expected heterozygosity varied from 0.00 to 1.00 and from 0.00 to 0.73, respectively. • CONCLUSIONS A total of 19 microsatellite loci were developed for R. aureum. Sixteen and 10 of these loci were successfully amplified in R. brachycarpum and R. dauricum, respectively. These microsatellite markers will have potential applications in genetic diversity and conservation genetics studies.
Multivariate Regression Trees for Analysis of Abundance Data

Summary. Multivariate regression tree methodology is developed and illustrated in a study predicting the abundance of several cooccurring plant species in Missouri Ozark forests. The technique is a variation of the approach of Segal (1992) for longitudinal data. It has the potential to be applied to many different types of problems in which analysts want to predict the simultaneous cooccurrence of several dependent variables. Multivariate regression trees can also be used as an alternative to cluster analysis in situations where clusters are defined by a set of independent variables and the researcher wants clusters as homogeneous as possible with respect to a group of dependent variables.
Indigenising Knowledge Base for Consequential Education in Ethiopia – A Conceptual Model

The uniqueness of Ethiopian socio-cultural environment creates challenges for teachers and scholars due to the questionable accuracy and applicability of Euro-American theories and concepts that are being taught in various disciplines in Ethiopia. How far cross-cultural theories have soundness for universal application? How far Euro-American theories are unassailable in Ethiopian cultural context? These are some of the exigent questions often raised by scholarly teachers, educationists as well as critical students in search of consequential education. Consequential education is a process of learning where the teacher encourages critical examination of multiple sources of knowledge and theories in diverse learning styles with the intention that the acquired knowledge is centred, located, oriented, and grounded on the learner’s culture, which could be applied, translated appropriately by the learner and thus be well equipped to be productive locally and globally. In view of enhancing consequential education by indigenising the local knowledge base in Ethiopia, the objectives of this paper are twofold: i) Identify key constructs, components and obstacles for indigenising Ethiopian knowledge base; ii) Prepare a conceptual model of indigenization for consequential education in Ethiopia. This qualitative study used a mixture of ethnography and phenomenology methods to collect data. Specifically, Delphi debate, brainstorming, storytelling/informal conversation and document analysis were used. The study identified many local cultural constructs that need extensive research so that local knowledge base could be established and local theories formulated. In view of this, the need for qualitative Ethiocentric (Ethiopia based) research is highlighted. A few myths were spotted out that are the barriers to indigenising knowledge base in Ethiopia. Inspired by the findings, the authors propose a Pyramid Model of Indigenization for Consequential Education in Ethiopia.
Genome-Wide Association Study of Calcium Accumulation in Grains of European Wheat Cultivars

Mineral concentrations in cereals are important for human health, especially for people who depend mainly on consuming cereal diet. In this study, we carried out a genome-wide association study (GWAS) of calcium concentrations in wheat (Triticum aestivum L.) grains using a European wheat diversity panel of 353 varieties [339 winter wheat (WW) plus 14 of spring wheat (SW)] and phenotypic data based on two field seasons. High genotyping densities of single-nucleotide polymorphism (SNP) markers were obtained from the application of the 90k iSELECT ILLUMINA chip and a 35k Affymetrix chip. Inductively coupled plasma optical emission spectrometry (ICP-OES) was used to measure the calcium concentrations of the wheat grains. Best linear unbiased estimates (BLUEs) for calcium were calculated across the seasons and ranged from 288.20 to 647.50 among the varieties (μg g-1 DW) with a mean equaling 438.102 (μg g-1 DW), and the heritability was 0.73. A total of 485 SNP marker–trait associations (MTAs) were detected in data obtained from grains cultivated in both of the two seasons and BLUE values by considering associations with a -log10 (P-value) ≥3.0. Among these SNP markers, we detected 276 markers with a positive allele effect and 209 markers with a negative allele effect. These MTAs were found on all chromosomes except chromosomes 3D, 4B, and 4D. The most significant association was located on chromosome 5A (114.5 cM) and was linked to a gene encoding cation/sugar symporter activity as a potential candidate gene. Additionally, a number of candidate genes for the uptake or transport of calcium were located near significantly associated SNPs. This analysis highlights a number of genomic regions and candidate genes for further analysis as well as the challenges faced when mapping environmentally variable traits in genetically highly diverse variety panels. The research demonstrates the feasibility of the GWAS approach for illuminating the genetic architecture of calcium-concentration in wheat grains and for identifying putative candidate genes underlying this trait.
CSDA: Rule-based complex sensor data aggregation system for M2M gateway

To reduce the server load and communication cost of machine-to-machine (M2M) systems, sensor data are aggregated in M2M gateways. The C language is typically used for programming the aggregation logic, and the program is embedded into the firmware. However, developing aggregation programs is difficult for M2M service providers because it requires gateway-specific knowledge, and consideration must be given to CPU and memory resources. In addition, modifying aggregation logic requires firmware updates, which are risky. We propose a rule-based sensor data aggregation system, called the complex sensor data aggregator (CSDA) for M2M gateways. Data aggregation is categorized into filtering, statistical calculation, and concatenation. The proposed CSDA supports this aggregation process in three steps: the input, data processing, and output steps. The behaviors of these steps are configured by an XML based rule. The CSDA also supports update modules, which download and overwrite aggregation rules from the server when the modification of data aggregation logic is required. In this case, firmware updates are not necessary. The proposed system is evaluated in an M2M gateway experimental environment. Results show that developing CSDA configurations is much easier than using C because the configuration amount decreases by 10%. In addition, the performance evaluation demonstrates the proposed system's ability to operate on M2M gateways. CPU usage was less than 10%, even with a heavy load, and memory consumption was 128 Kbytes.
Performance Evaluation of Energy-Aware Best Fit Decreasing Algorithms for Cloud Environments

Cloud computing is emerging computational paradigm that provide resources to perform complex tasks. Large datacenters are used to facilitate the incoming tasks by providing resources, such as CPU, memory, storage, and network bandwidth. Datacenters offers hosting and processing of complex tasks and services, where servers and cooling systems consume huge amount of energy. Excessive amount of energy consumption results in large power bills and Green House gases (GHG) emissions. Substantial amount of energy can be saved by powering down servers that are idle. Various authors have come up with energy efficient solutions that try to minimize overall energy consumption. One set of energy-efficient solutions is based on best fit decreasing (BFD) algorithm. In this paper, we evaluate the performance of existing energy efficient BFD algorithms based on various workloads and migration techniques. Moreover, considering the significance of Service Level Agreement (SLA), we introduce SLA-awareness in traditional BFD algorithm to minimize the SLA violation. We present the analysis and observations for each of the considered techniques based on total energy consumption, average SLA violations, and SLA performance degradation due to migration.
Building Reliable Storage Clouds: Models, Fundamental Tradeoffs, and Solutions

Distributed storage has been an active research area for decades. With the proliferation of cloud computing, there has been a rejuvenated interest in two perspectives. The first perspective is seen through the lenses of the cloud providers: how should we build global storage services for cloud hosted services and applications at scale with high reliability and availability guarantees, but also in a cost effective way? The second perspective is seen through the lenses of the service providers that utilize public clouds: how can we achieve high I/O performance over cloud storage within a cost budget? In this manuscript, we first present various kinds of distributed storage systems, their operational characteristics and the key techniques to improve their performance. We then focus on cloud storage, exclusively. Cloud storage has massive scales with the promise to provide as much storage capacity as their tenants demand. Cloud providers also promise very high durability, availability, and I/O performance. In this context, we cover the fundamental tradeoffs between storage efficiency and network bandwidth as well as I/O throughput and latency. Erasure codes play an essential role in these tradeoffs and, thus, we also present their design and usage in the context of cloud storage broadly. We pay particular attention on various queuing models and the corresponding performance analysis in the presence of coded storage. We provide exact and approximate solutions under various settings and assumptions. We describe optimal or near-optimal scheduling and coding strategies that are established based on these analyses.
The capillary bed offers the largest hemodynamic resistance to the cortical blood supply

The cortical angioarchitecture is a key factor in controlling cerebral blood flow and oxygen metabolism. Difficulties in imaging the complex microanatomy of the cortex have so far restricted insight about blood flow distribution in the microcirculation. A new methodology combining advanced microscopy data with large scale hemodynamic simulations enabled us to quantify the effect of the angioarchitecture on the cerebral microcirculation. High-resolution images of the mouse primary somatosensory cortex were input into with a comprehensive computational model of cerebral perfusion and oxygen supply ranging from the pial vessels to individual brain cells. Simulations of blood flow, hematocrit and oxygen tension show that the wide variation of hemodynamic states in the tortuous, randomly organized capillary bed is responsible for relatively uniform cortical tissue perfusion and oxygenation. Computational analysis of microcirculatory blood flow and pressure drops further indicates that the capillary bed, including capillaries adjacent to feeding arterioles (d < 10 µm), are the largest contributors to hydraulic resistance.
Examining the clinical and genetic overlap of Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder traits

Attention deficit hyperactivity disorder (ADHD) is a common and impairing neurodevelopmental disorder, which frequently co-occurs with autism spectrum disorder (ASD). Both disorders are highly heritable and recent studies report a substantial degree of overlap in genetic risks for ADHD and ASD. The overall objective of this thesis is to examine the clinical co-occurrence and shared genetic susceptibility of these conditions, as well as of related developmental problems. First, the presentation of ASD traits is examined in a clinical sample of children diagnosed with ADHD. This is followed by an assessment of whether the presence of ASD traits in children with ADHD is associated with additional cognitive or developmental difficulties. Lastly, it is investigated whether common genetic risk variants which are associated with clinically-diagnosed ADHD are also associated with ADHD traits, ASD-like social-communication difficulties and neurocognitive abilities (i.e. IQ, working memory, inhibitory control and facial emotion recognition) in children from a general population sample. The results show that ASD traits split into separate, albeit correlated dimensions of social-communication difficulties and restrictive, repetitive behaviours (RRBs) in children with ADHD. They also suggest that there may be some overlap of RRBs and hyperactive-impulsive ADHD symptoms. Increasing levels of ASD traits in children with ADHD are found to index more ADHD symptoms, as well as lower cognitive abilities and a greater likelihood of developmental difficulties. Finally, the results demonstrate that common genetic risk variants relevant to ADHD diagnosis are associated with ADHD and social-communication problems as well as cognitive difficulties (lower IQ and working memory abilities) in children in the general population. This thesis extends our understanding of the clinical importance of assessing ASD in the context of ADHD. Furthermore, the findings demonstrate that common genetic risk variants for childhood ADHD are also relevant to other neurodevelopmental and cognitive outcomes in the general population.
Latent Feature Independent Cascade Model for Social Propagation

People share various types of information including opinions on hot topics, bookmarking activity and rumors via online communities. To make it possible to predict future trends in online communities, it is important that we develop a model of information diffusion through social networks and a method for estimating its parameters. In this paper, we present a latent feature independent cascade model, which can effectively estimate diffusion probabilities by capturing the influences between latent communities. In particular, we incorporate two types of latent features for each node. The first represents the features as a sender and the second represents the features as a receiver. We demonstrate experimentally that the proposed model can estimate the diffusion probabilities more accurately than commonly used methods. We also show the effectiveness of the proposed model for estimating information spread.
Toward plot de-interlacing in TV series using scenes clustering

Multiple sub-stories usually coexist in every episode of a TV series. We propose several variants of an approach for plot de-interlacing based on scenes clustering - with the ultimate goal of providing the end-user with tools for fast and easy overview of one episode, one season or the whole TV series. Each scene can be described in three different ways (based on color histograms, speaker diarization or automatic speech recognition outputs) and four clustering approaches are investigated, one of them based on a graphical representation of the video. Experiments are performed on two TV series of different lengths and formats. We show that semantic descriptors (such as speaker diarization) give the best results and underline that our approach provides useful information for plot de-interlacing.