Miracle-dz/UniFAR-FTUs huggingface dataset:
Reference Traffic for Network Resource Dimensioning in FMC Environment

Unassumed teletraffic patterns, such as those caused by extra-high bit-rate mobile user traffic that actively moves in a network, will be become common in telecommunication networks in the 4th generation (4G) era. The unexpectedness and unevenness of their distribution will make it difficult to use ”fundamental traffic, ” which is the conventional concept of? reference traffic, especially in Japan, based on the E.500 ITU-T? standardization series for network resource dimensioning. New radio access technologies are being intensively developed toward 4G, but the argument for traffic engineering is still insufficient. We propose a new model and new metric of reference traffic for handling such cases. The metric is called ”redundancy under general traffic in a closed network. ” We also developed a calculation method approximated using a normal distribution. We discuss the evaluation of this method using Monte Carlo simulations, and show examples of reference traffic by using this method in real operations of next-generation telecommunication carriers toward the fixed and mobile convergence (FMC) network.
A Tutorial Review of Microarray Data Analysis

2 Introduction 3 2.1 High troughput experiments . 4 2.2 Biological background . 4 2.2.1 DNA, proteins and the central dogma . 4 2.2.2 Genes and protein synthesis . 5 2.2.3 Nucleic acids hybridization . 10 2.3 Microarrays . 10 2.3. 1 The technology . 10 2.3. 2 Expression measures . 11
U.S. House Prices Over the Last 30 Years: Bubbles, Regime Shifts and Market (In)Efficiency

This paper studies the evolution of U.S. house prices across 45 metropolitan areas from 1980-2012. It uses a version of the Gordon dividend discount model, modelling price as present value of imputed rents as a measure of "fundamentals. " This allows for a parsimonious specification, using only lagged rents, property values and interest rates (real and nominal) to explain property values. We find that cities share long run fundamentals, but adjust to them slowly at a rate of around 10% per year, which is relatively constant across cities. However we also find sharp differences in short run adjustments across cities, which are correlated with local supply elasticities. Analysis of residuals suggests strong cyclical deviations from fundamentals throughout the period, with a high degree of serial correlation. The bubble period (2000-2007) was longer than usual and appears to have been extended after 2002, when it was dying out, in a way that is coincident with the rise in subprime securitization.
Risk score : a simple method for predicting mortality in ambulatory patients with chronic heart failure

CLINICAL RESEARCH Heart failure/cardiomyopathy
Validation and recalibration of the Framingham cardiovascular disease risk models in an Australian Indigenous cohort

Background In Australia, clinical guidelines for primary prevention of cardiovascular disease recommend the use of the Framingham model to help identify those at high risk of developing the disease. However, this model has not been validated for the Indigenous population. Design Cohort study. Methods Framingham models were applied to the Well Person’s Health Check (WPHC) cohort (followed 1998–2014), which included 1448 Aboriginal and Torres Strait Islanders from remote Indigenous communities in Far North Queensland. Cardiovascular disease risk predicted by the original and recalibrated Framingham models were compared with the observed risk in the WPHC cohort. Results The observed five- and 10-year cardiovascular disease probability of the WPHC cohort was 10.0% (95% confidence interval (CI): 8.5–11.7) and 18.7% (95% CI: 16.7–21.0), respectively. The Framingham models significantly underestimated the cardiovascular disease risk for this cohort by around one-third, with a five-year cardiovascular disease risk estimate of 6.8% (95% CI: 6.4–7.2) and 10-year risk estimates of 12.0% (95% CI: 11.4–12.6) and 14.2% (95% CI: 13.5–14.8). The original Framingham models showed good discrimination ability (C-statistic of 0.67) but a significant lack of calibration (χ2 between 82.56 and 134.67). After recalibration the 2008 Framingham model corrected the underestimation and improved the calibration for five-year risk prediction (χ2 of 18.48). Conclusions The original Framingham models significantly underestimate the absolute cardiovascular disease risk for this Australian Indigenous population. The recalibrated 2008 Framingham model shows good performance on predicting five-year cardiovascular disease risk in this population and was used to calculate the first risk chart based on empirical validation using long-term follow-up data from a remote Australian Indigenous population.
Is early endoscopy in the emergency room beneficial in patients with bleeding peptic ulcer? A "fortuitously controlled" study.

BACKGROUND AND STUDY AIMS In previous randomized trials, early endoscopy improved the outcome in patients with bleeding peptic ulcer, though most of these studies defined "early" as endoscopy performed within 24 hours after admission. Using the length of hospital stay as the primary criterion for the clinical outcome, we compared the results of endoscopy done immediately after admission (early endoscopy in the emergency room, EEE) with endoscopy postponed to a time within the first 24 hours after hospitalization, but still during normal working hours ("delayed" endoscopy in the endoscopy unit, DEU). PATIENTS AND METHODS We conducted a retrospective analysis of data from 81 consecutive patients with bleeding peptic ulcer admitted in 1997 and 1998 (age range 16 - 90 years). Of these 81 patients, 38 underwent DEU (the standard therapy at the hospital) and 43 underwent EEE. Patients in the two groups were comparable with regard to admission criteria, were equally distributed with respect to their risk of adverse outcome (assessed using the Baylor bleeding score and the Rockall score), and differed only in the treatment they received. Endoscopic hemostasis was performed whenever possible in all patients with Forrest types I, IIa, and IIb ulcer bleeding. RESULTS We found similar rates in the two groups for recurrent bleeding (16 % in DEU patients vs. 14 % in EEE patients), persistent bleeding (8 % in DEU patients vs. none in EEE patients), medical complications (21 % in DEU patients vs. 26 % in EEE patients), the need for surgery (8 % in DEU patients vs. 9 % in EEE patients), and the length of hospital stay (5.1 days for DEU patients vs. 5.9 days for EEE patients). None of the differences between the two groups in these parameters were statistically significant. None of the patients died. CONCLUSIONS Early endoscopy in an emergency room did not improve the clinical outcome in our 81 consecutive patients with bleeding peptic ulcer.
A multi-scale computational investigation of cardiac electrophysiology and arrhythmias in acute ischaemia

Sudden cardiac death is one of the leading causes of mortality in the western world. One of the main factors is myocardial ischaemia, when there is a mismatch between blood demand and supply to the heart, which may lead to disturbed cardiac excitation patterns, known as arrhythmias. Ischaemia is a dynamic and complex process, which is characterised by many electrophysiological changes that vary through space and time. Ischaemia-induced arrhythmic mechanisms, and the safety and efficacy of certain therapies are still not fully understood. Most experimental studies are carried out in animal, due to the ethical and practical limitations of human experiments. Therefore, extrapolation of mechanisms from animal to human is challenging, but can be facilitated by in silico models. Since the first cardiac cell model was built over 50 years ago, computer simulations have provided a wealth of information and insight that is not possible to obtain through experiments alone. Therefore, mathematical models and computational simulations provide a powerful and complementary tool for the study of multi-scale problems. The aim of this thesis is to investigate pro-arrhythmic electrophysiological consequences of acute myocardial ischaemia, using a multi-scale computational modelling and simulation framework. Firstly, we present a novel method, combining computational simulations and optical mapping experiments, to characterise ischaemia-induced spatial differences modulating arrhythmic risk in rabbit hearts. Secondly, we use computer models to extend our investigation of acute ischaemia to human, by carrying out a thorough analysis of recent human action potential models under varied ischaemic conditions, to test their applicability to simulate ischaemia. Finally, we combine state-of-the-art knowledge and techniques to build a human whole ventricles model, in which we investigate how anti-arrhythmic drugs modulate arrhythmic mechanisms in the presence of ischaemia.
Water-protein interactions: theory and experiment.

CONTENTS PERSPECTIVES AND OVERVIEW . 577 THEORETICAL CALCULATIONS OF PROTEIN-WATER STRUCTURE AND DYNAMICS . 580 Protein Force Fields . 580 Water Models . 58 1 Energy-Minimization Results. 583 Molecular Dynamics Methods . 585 Limitation s and Uncertainties . 588 EXPERIMENTAL EVIDENCE FOR PROTEIN-WATER INTERACTIONS . 589 Water from X-ray and Neutron-Diff raction Experiments . 589 Internal Waters in Protein Structures . 589 Water at Hydrophobic Surfaces. 591 Emer.qing Water-Hydrogen Bonding Patterns/rom Diff raction Analysis . 593 NM R Studies of Water: Correspondence with X-ray Results . 596 CONCLUSIONS . 598
Effects of behavioral family systems therapy for diabetes on adolescents' family relationships, treatment adherence, and metabolic control.

BACKGROUND Behavioral family systems therapy (BFST) for adolescents with diabetes has improved family relationships and communication, but effects on adherence and metabolic control were weak. We evaluated a revised intervention, BFST for diabetes (BFST-D). METHODS One hundred and four families were randomized to standard care (SC) or to 12 sessions of either an educational support group (ES) or a BFST-D over 6 months. Family relationships, adherence, glycosylated hemoglobin (HbA1c), and health care utilization were measured at baseline and after treatment. RESULTS BFST-D significantly improved family conflict and adherence compared to SC and ES, especially among those with baseline HbA1c > or = 9.0%. BFST-D and ES significantly improved HbA1c compared to SC among those with baseline HbA1c > or = 9.0%. CONCLUSIONS The revised intervention (BFST-D) improved family conflict and treatment adherence significantly, while both ES and BFST-D reduced HbA1c significantly, particularly among adolescents with poor metabolic control. Clinical translation of BFST-D requires further study.
DEVELOPMENT OF NEURAL CONNECTIONS IN CULTURE *

This review will emphasize development of neural connections in several types of central nervous system (CNS) tissue cultures that may be useful as model systems for studies of neurotrophic phenomena. Trophic effects have been defined as ”longterni . interactions between nerves and other cells which initiate or control molecular modification in the other ceIl’’S8 and which may thereby be “responsil)le for the structural, chemical, and functional integrity of the target tissues. ”47 From this point of view, formation and long-term maintenance of syiiaptic junctions, involving membrane specializations in the postsynaptic cells, are clearly neurotrophic effects; their occurrence in nitro in the absence of neural impulse activity suggests mediation by neurotrophic chemical agents.
Social Movements and Networks: Relational Approaches to Collective Action

Introduction 1. Social movements, contentious actions, and social networks: 'from metaphor to substance'? PART I. INDIVIDUAL NETWORKS 2. Social Networks Matter. But How? 3. Movement development and organizational networks: The role of 'single members' in the German Nazi party, 1925-1930 PART II. INTERORGANIZATIONAL NETWORKS 4. Networks in opposition: Linking organizations through activists in the Polish People's Republic 5. 'Leaders' or brokers? Positions and influence in social movement networks 6. Community embeddedness and collaborative governance in the San Francisco Bay Area environmental movement PART III. NETWORKING THE POLITICAL PROCESS 7. Contentious connections in Great Britain, 1828-1834 8. Networks, diffusion, and cycles of collective action 9. Movement in context: Thick networks and Japanese environmental protest PART IV. THEORIES OF NETWORKS, MOVEMENTS, AND COLLECTIVE ACTION 10. Why do networks matter? Rationalist and structuralist interpretations 11. Cross-talk in movements: Reconceiving the culture-network link 12. Beyond structural analysis: toward a more dynamic understanding of social movements 13. Networks and social movements: A research programme
Finding compiler bugs via live code mutation

Validating optimizing compilers is challenging because it is hard to generate valid test programs (i.e., those that do not expose any undefined behavior). Equivalence Modulo Inputs (EMI) is an effective, promising methodology to tackle this problem. Given a test program with some inputs, EMI mutates the program to derive variants that are semantically equivalent w.r. t. these inputs. The state-of-the-art instantiations of EMI are Orion and Athena, both of which rely on deleting code from or inserting code into code regions that are not executed under the inputs. Although both have demonstrated their ability in finding many bugs in GCC and LLVM, they are still limited due to their mutation strategies that operate only on dead code regions. This paper presents a novel EMI technique that allows mutation in the entire program (i.e., both live and dead regions). By removing the restriction of mutating only the dead regions, our technique significantly increases the EMI variant space. It also helps to more thoroughly stress test compilers as compilers must optimize mutated live code, whereas mutated dead code might be eliminated. Finally, our technique also makes compiler bugs more noticeable as miscompilations on mutated dead code may not be observable. We have realized the proposed technique in Hermes. The evaluation demonstrates Hermes’s effectiveness. In 13 months, Hermes found 168 confirmed, valid bugs in GCC and LLVM, of which 132 have already been fixed.
An Efficient 2D Method for Training Super-Large Deep Learning Models

Since the rise of Transformer [22] and BERT [6], large language models [7], [12] have been proposed and shown unprecedented performance in tasks like translation, classification, and text generation. However, due to the memory constraint, model parallelism must be used to split the model across multiple processors. Inter-layer partition, intra-layer partition, and sparse activation are the major approaches to achieve model parallelism. Among them, inter-layer partition [10], [11] often requires the model to be explicitly expressed as a stack of sub-modules, the number of which equals to the number of processors, and would introduce either gradient staleness or bubble overhead; while the sparse activation [12] is primarily designed for Google TPU cluster and hard to deploy on GPU servers, intra-layer partition [17], especially Megatron-LM [18], can be easily deployed on GPU servers and has been adopted in subsequent works like Turing-NLG and M6. Though as pioneers of intra-layer parallelism, they still show memory redundancy and sub-optimal communication efficiency, which reveals the space for further improvements. In this work, we leverage SUMMA [21] and propose Optimus, a highly efficient and scalable paradigm for training super-large language models. In Optimus, activations and gradients are partitioned and distributed along processors all the way through forward and backward propagations, with hardly any memory redundancy. The isoefficiency of communication in pure model parallelism improves from W ~ p3 for Megatron-LM, to $W\sim {(\sqrt p \log p)^3}$ for our Optimus. This framework is implemented with open-source deep learning framework, PyTorch, and consolidates existing techniques such as mixed precision training [13], activation checkpointing [5], and data parallelism. In experiments on TACC Frontera supercomputers, Optimus shows 1.48× the speed for training, 1.78× speed for inference, and 8× the maximum batch size over Megatron-LM on 64 GPUs in pure model parallelism; and 1.73× speed for training, 2.32× speed for inference with data parallelism size equaling 2 on 128 GPUs. In pure model parallelism, Optimus surpasses Megatron-LM in weak scaling efficiency by a great margin, and shows an extraordinary increasing strong scaling efficiency. Optimus would facilitate the scaling of language models and serve as a strong thrust in the space exploration of artificial intelligence.
Unlike Chloroquine, Mefloquine Inhibits SARS-CoV-2 Infection in Physiologically Relevant Cells

Repositioning of clinical approved drugs could represent the fastest way to identify therapeutic options during public health emergencies, the majority of drugs explored for repurposing as antivirals for 2019 coronavirus disease (COVID-19) have failed to demonstrate clinical benefit. Without specific antivirals, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues to cause major global mortality. Antimalarial drugs, such as chloroquine (CQ)/hydroxychloroquine (HCQ) and mefloquine have emerged as potential anti-SARS-CoV-2 antivirals. CQ/HCQ entered the Solidarity and RECOVERY clinical trials against COVID-19 and showed lack of efficacy. Importantly, mefloquine is not a 4-aminoquinoline like CQ and HCQ and has been previously repurposed for other respiratory diseases. Unlike the 4-aminoquinolines that accumulate in the high pH of intracellular lysosomes of the lung, the high respiratory tract penetration of mefloquine is driven by its high lipophilicity. While CQ and HCQ exhibit activity in Vero E6 cells, their activity is obviated in TMPRSS2-expressing cells, such as Calu-3 cells, which more accurately recapitulate in vivo entry mechanisms for SARS-CoV-2. Accordingly, here we report the anti-SARS-CoV-2 activity of mefloquine in Calu-3 type II pneumocytes and primary human monocytes. Mefloquine inhibited SARS-CoV-2 replication in Calu-3 cells with low cytotoxicity and EC50 and EC90 values of 1.2 and 5.3 µM, respectively. In addition, mefloquine reduced up to 68% the SARS-CoV-2 RNA levels in infected monocytes, reducing viral-induced inflammation. Mefloquine blocked early steps of the SARS-CoV-2 replicative cycle and was less prone than CQ to induce drug-associated viral mutations and synergized with RNA polymerase inhibitor. The pharmacological parameters of mefloquine are consistent with its plasma exposure in humans and its tissue-to-plasma predicted coefficient points that this drug may accumulate in the lungs. These data indicate that mefloquine could represent an orally available clinically approved drug option against COVID-19 and should not be neglected on the basis of the failure of CQ and HCQ.
Singular Value Decomposition Tutorial

6 Vector Terminology 6 6.1 Vector Length . 6 6.2 Vector Addition . 6 6.3 Scalar Multiplication . 6 6.4 Inner Product . 6 6.5 Orthogonality . 7 6.6 Normal Vector . 7 6.7 Orthonormal Vectors . 7 6.8 Gram-Schmidt Orthonormalization Process . 7
Transparent Machine Learning for Information Extraction: State-of-the-Art and the Future

The rise of Big Data analytics over unstructured text has led to renewed interest in information extraction (IE). These applications need effective IE as a first step towards solving end-to-end real world problems (e.g. biology, medicine, finance, media and entertainment, etc). Much recent NLP research has focused on addressing specific IE problems using a pipeline of multiple machine learning techniques. This approach requires an analyst with the expertise to answer questions such as: “What ML techniques should I combine to solve this problem? ”; “What features will be useful for the composite pipeline? ”; and “Why is my model giving the wrong answer on this document? ”. The need for this expertise creates problems in real world applications. It is very difficult in practice to find an analyst who both understands the real world problem and has deep knowledge of applied machine learning. As a result, the real impact by current IE research does not match up to the abundant opportunities available.In this tutorial, we introduce the concept of transparent machine learning. A transparent ML technique is one that:- produces models that a typical real world use can read and understand;- uses algorithms that a typical real world user can understand; and- allows a real world user to adapt models to new domains.The tutorial is aimed at IE researchers in both the academic and industry communities who are interested in developing and applying transparent ML.
Utility-oriented internetworking of content delivery networks

Today’s Internet content providers primarily use Content Delivery Networks (CDNs) to deliver content to end-users with the aim to enhance their Web access experience. Yet the prevalent commercial CDNs, operating in isolation, often face resource over-provisioning, degraded performance, and Service Level Agreement (SLA) violations, thus incurring high operational costs and limiting the scope and scale of their services. To move beyond these shortcomings, this thesis establishes the basis for developing advanced and efficient content delivery solutions that are scalable, high performance, and cost-effective. It introduces techniques to enable coordination and cooperation between multiple content delivery services, which is termed as “CDN peering”. In this context, this thesis addresses five key issues―when to peer (triggering circumstances), how to peer (interaction strategies), whom to peer with (resource discovery), how to manage and enforce operational policies (request-redirection and load sharing), and how to demonstrate peering applicability (measurement study and proof-of-concept implementation). Thesis Contributions: To support the thesis that the resource over-provisioning and degraded performance problems of existing CDNs can be overcome, thus improving Web access experience of Internet end-users, we have: • identified the key research challenges and core technical issues for CDN peering, along with a systematic understanding of the CDN space by covering relevant applications, features and implementation techniques, captured in a comprehensive taxonomy of CDNs; • developed a novel architectural framework, which provides the basis for CDN peering, formed by a set of autonomous CDNs that cooperate through an interconnection mechanism, providing the infrastructure and facilities to virtualize the service of multiple providers; • devised Quality-of-Service (QoS)-oriented analytical performance models to demonstrate the effects of CDN peering and predict end-user perceived performance, thus facilitating to make concrete QoS performance guarantees for a CDN provider; • developed enabling techniques, i.e. resource discovery, server selection, and request-redirection algorithms, for CDN peering to achieve service