Miracle-dz/UniFAR-FTUs huggingface dataset:
Channel Coding for Ultra-Reliable Low-Latency Communication in 5G Systems

This paper investigates block error rate (BLER) performance and computational complexity of candidate channel coding schemes for ultra-reliable low latency communication (URLLC) in 5G. The considered candidates are the same as those identified in 3GPP: turbo, LDPC, polar, and convolutional codes. Details of code constructions and decoding algorithms are provided with computational complexity analysis. Code construction parameters, number of iterations, and list sizes are selected to provide a fair comparison among candidate coding schemes. Simulation results on BLER are shown for several code rates and small-to-moderate block sizes. The results reveal that polar and LDPC codes outperform turbo codes for short block sizes of 40 bits, while the opposite is true for medium block sizes of 200 bits. None of the schemes is a clear winner at all considered block sizes and coding rates. Other aspects like implementation complexity, latency, and flexibility will also be important when deciding the URLLC coding scheme.
Species differences in drug transporters and implications for translating preclinical findings to humans

Introduction: Drug transporters play an important role in the absorption, distribution, and excretion (ADE) of many drugs. In the last several years it has become increasingly clear that there are significant differences between rodents, dog, monkey, and human in the substrate specificity, tissue distribution, and relative abundance of transporters. These differences complicate cross-species extrapolations, which is important when attempting to predict human pharmacokinetics (PK) of drug candidates and assess risk for drug–drug interactions (DDIs). Areas covered: This article provides an overview of species differences for the major transporters involved in drug disposition. Specifically, the article looks at a number of efflux and uptake transporters including multidrug resistance protein MDR1 P-glycoprotein (Pgp), breast cancer resistance protein (BCRP), multidrug resistance proteins (MRPs), members of the multidrug resistance and toxic extrusion protein (MATE) family, as well as members of organic anion transporting polypeptides (OATPs), organic anion transporters (OATs), and organic cation transporters (OCTs). Expert opinion: Quantitative knowledge of species differences of transporters, especially at the protein and functional level is still limited. The current challenge is to extrapolate and integrate data from both preclinical species and humans to quantitatively predict the impact of transporters on drug absorption, disposition, and drug–drug interactions. Increased understanding of species differences in transporter expression and functional activity is needed in order to translate findings from preclinical species to humans. Ultimately, high quality in vitro and in vivo data will aid in the establishment of physiologically based pharmacokinetic (PBPK) models, which will improve the capability to predict PK characteristics of drug candidates in humans.
Interactive Crowd Simulation on Mobile Devices in an Augmented Reality Environment

We propose a technique to do interactive crowd simulation on mobile devices within an Augmented Reality (AR) framework. We localize the camera in a prepared environment that includes a set of natural markers. We use least squares optimization to obtain extrinsic camera parameters. During tracking, the users can create paths for the agents to follow through touch inputs. User-specified paths are converted to Bézier curves. We use navigation mesh-based planning and the user-specified paths interchangeably for global path planning.
FaceTouch: Touch Interaction for Mobile Virtual Reality

We present FaceTouch, a mobile Virtual Reality (VR) headmounted display (HMD) that leverages the backside as a touch-sensitive surface. FaceTouch allows the user to point at and select virtual content inside their field-of-view by touching the corresponding location at the backside of the HMD utilizing their sense of proprioception. This allows for a rich interaction (e.g. gestures) in mobile and nomadic scenarios without having to carry additional accessories (e.g. gamepad). We built a prototype of FaceTouch and present interaction techniques and three example applications that leverage the FaceTouch design space.
Component-based model synthesis for low polygonal models

This paper presents a method for semi-automatically generating a variety of different objects from an initial low polygonal model. Our approach aims at generating large sets of models with small variants with a view to avoiding instance replications which produce unrealistic repetitive patterns. The generation process consists in decomposing the initial object into a set of components. Their geometry and texture are edited and the modified components are then combined together to create a large set of varying models. Our method has been implemented in the Twilight 2 development framework of Eden Games and Widescreen Games and successfully experimented on different types of models.
Performance Evaluation of Scale-Free Graph Algorithms in Low Latency Non-volatile Memory

The purpose of this study is to quantitatively assess the performance of graph processing algorithms for large scale-free graphs residing in byte-addressable Non-Volatile Memory (NVM). Our study focuses on static and dynamic graph algorithms previously optimized for external memory in the form of locally attached NAND Flash arrays, with data structures tuned to maximize locality. The evaluation is run on a unique resource, an NVM hardware emulator from Intel capable of inserting delays to memory reads through microcode instructions thatdelay load instructions missing in L3; the emulated NVM appears as separate UMA node (identified by a physical address range) and that is not part of the socket-attached NUMA nodes. In this work, we distinguish two graph processing configurations, 'semi-external' in which the graph is fully resident in NVM but in-flight intermediate data structures reside in DRAM, and 'fully external' in which both the graph and the intermediate data structures reside in NVM. Our goal is to assess the performance impact of NVM latency of up to 3.5X DRAM, with (semi-external) and without (fully external) an application-specific scratchpad for the in-flight data structures. We find a performance penalty of 59.6% in the fully external scenario, which is reduced to 5.2% with the scratchpad. Our results show that graph algorithms employing locality aware data structure layout and processing can benefit immediately from emerging NVMs with minimal performance impact, making NVM a high value resource for large scale graph processing.
Agreement between an online dietary assessment tool (myfood24) and an interviewer-administered 24-h dietary recall in British adolescents aged 11–18 years

Abstract myfood24 Is an online 24-h dietary assessment tool developed for use among British adolescents and adults. Limited information is available regarding the validity of using new technology in assessing nutritional intake among adolescents. Thus, a relative validation of myfood24 against a face-to-face interviewer-administered 24-h multiple-pass recall (MPR) was conducted among seventy-five British adolescents aged 11–18 years. Participants were asked to complete myfood24 and an interviewer-administered MPR on the same day for 2 non-consecutive days at school. Total energy intake (EI) and nutrients recorded by the two methods were compared using intraclass correlation coefficients (ICC), Bland–Altman plots (using between and within-individual information) and weighted κ to assess the agreement. Energy, macronutrients and other reported nutrients from myfood24 demonstrated strong agreement with the interview MPR data, and ICC ranged from 0·46 for Na to 0·88 for EI. There was no significant bias between the two methods for EI, macronutrients and most reported nutrients. The mean difference between myfood24 and the interviewer-administered MPR for EI was −230 kJ (−55 kcal) (95 % CI −490, 30 kJ (−117, 7 kcal); P=0·4) with limits of agreement ranging between 39 % (3336 kJ (−797 kcal)) lower and 34 % (2874 kJ (687 kcal)) higher than the interviewer-administered MPR. There was good agreement in terms of classifying adolescents into tertiles of EI (κ w =0·64). The agreement between day 1 and day 2 was as good for myfood24 as for the interviewer-administered MPR, reflecting the reliability of myfood24. myfood24 Has the potential to collect dietary data of comparable quality with that of an interviewer-administered MPR.
Efficient closed high-utility itemset mining

This paper presents a novel algorithm for discovering closed high-utility itemsets (CHUIs) efficiently. It proposes three strategies to mine CHUIs efficiently: closure jumping, forward closure checking and backward closure checking. It also relies on two new upper-bounds named local utility and sub-tree utility to prune the search space, and a Fast Utility Counting technique to calculate these upper-bounds efficiently. Moreover, it integrates novel efficient database projection and transaction merging techniques. Experimental results shows that the proposed algorithm is up to 71 times faster and consumes up to 18 times less memory than the state-of-art CHUD algorithm.
A low-power, 26-GHz transformer-based regulated cascode transimpedance amplifier in 0.25µm SiGe BiCMOS

A 26 GHz transimpedance amplifier (TIA) with transformer-based regulated cascode (RGC) input stage is proposed and analyzed. The transformer enhances the effective transconductance of the TIA's input common-base transistor; reducing the input resistance and providing considerable bandwidth extension. The TIA is implemented in a 0. 25µm BiCMOS technology. Measurement shows the single-ended transimpedance gain of 53dBΩ with −3dB bandwidth of 26 GHz. Total chip power, including an output buffer, is 28.2mW from a 2.5V supply; while core TIA power is 8.2mW. The measured average input-referred noise current spectral density is 21.3 pA/√Hz. Total chip area, including pads, is 960µm×780µm.
On the chromatic number of a random 5‐regular graph

It was only recently shown by Shi and Wormald, using the differential equation method to analyze an appropriate algorithm, that a random 5‐regular graph asymptotically almost surely has chromatic number at most 4. Here, we show that the chromatic number of a random 5‐regular graph is asymptotically almost surely equal to 3, provided a certain four‐variable function has a unique maximum at a given point in a bounded domain. We also describe extensive numerical evidence that strongly suggests that the latter condition holds. The proof applies the small subgraph conditioning method to the number of locally rainbow balanced 3‐colorings, where a coloring is balanced if the number of vertices of each color is equal, and locally rainbow if every vertex is adjacent to at least one vertex of each of the other colors. © 2009 Wiley Periodicals, Inc. J Graph Theory 61: 157–191, 2009
Assessing the Usefulness of a Requirements Monitoring Tool: A Study Involving Industrial Software Engineers

Requirements monitoring approaches support defining and checking the run-time behavior and performance characteristics of complex software systems. However, although numerous monitoring tools have been described in the literature, hardly any empirical studies exist on their usefulness for software engineering practitioners. Empirical data on usefulness, however, is important for practitioners to select and adapt the capabilities of monitoring tools for their application context. This paper first describes common capabilities of requirements monitoring tools and then empirically assesses the usefulness of these capabilities as implemented in the monitoring tool REMINDS. We report findings from an initial assessment of the tool we performed using the Cognitive Dimensions of Notations Framework. We then present results of a usefulness study involving software engineers of a large company from the domain of automation software. Finally, we discuss implications for developers of requirements monitoring tools.
Biological Characterization of ARRY-142886 (AZD6244), a Potent, Highly Selective Mitogen-Activated Protein Kinase Kinase 1/2 Inhibitor

Purpose: The Ras-Raf-mitogen-activated protein kinase kinase (MEK) pathway is overactive in many human cancers and is thus a target for novel therapeutics. We have developed a highly potent and selective inhibitor of MEK1/2. The purpose of these studies has been to show the biological efficacy of ARRY-142886 (AZD6244) in enzymatic, cellular, and animal models. Experimental Design: The ability of ARRY-142886 to inhibit purified MEK1 as well as other kinases was evaluated. Its effects on extracellular signal-regulated kinase (ERK) phosphorylation and proliferation in several cell lines were also determined. Finally, the inhibitor was tested in HT-29 (colorectal) and BxPC3 (pancreatic) xenograft tumor models. Results: The IC50 of ARRY-142886 was determined to be 14 nmol/L against purified MEK1. This activity is not competitive with ATP, which is consistent with the high specificity of compound for MEK1/2. Basal and epidermal growth factor–induced ERK1/2 phosphorylation was inhibited in several cell lines as well as 12-O-tetradecanoylphorbol-13-acetate–induced ERK1/2 phosphorylation in isolated peripheral blood mononuclear cells. Treatment with ARRY-142886 resulted in the growth inhibition of several cell lines containing B-Raf and Ras mutations but had no effect on a normal fibroblast cell line. When dosed orally, ARRY-142886 was capable of inhibiting both ERK1/2 phosphorylation and growth of HT-29 xenograft tumors in nude mice. Tumor regressions were also seen in a BxPC3 xenograft model. In addition, tumors remained responsive to growth inhibition after a 7-day dosing holiday. Conclusions: ARRY-142886 is a potent and selective MEK1/2 inhibitor that is highly active in both in vitro and in vivo tumor models. This compound is currently being investigated in clinical studies.
A SVM-based method for engine maintenance strategy optimization

Due to the abundant application background, the optimization of maintenance problem has been extensively studied in the past decades. Besides the well-known difficulty of large state space and large action space, the pervasive application of digital computers forces us to consider the new constraint of limited memory space. The given memory space restricts what strategies can be explored during the optimization procedure. By explicitly quantifying the minimal memory space to store a strategy using support vector machine, we propose to describe simple strategies exactly and only approximate complex strategies. This selective approximation can best utilize the given memory space for any description mechanism. We use numerical results on illustrative examples to show how the selective approximation improves the solution quality. We hope this work sheds some insights to best utilize the memory space for practical engine maintenance strategy optimization problems
Migration decisions and persistent earnings differentials: Evidence from Thailand

I estimate the perceived cost of internal migration and associated labor supply elasticity in Thailand using the revealed-preference location decisions of workers. I develop a multiperiod model of the location decision where observed earnings are an imperfect proxy for the net present value of a migration. I use global commodity prices to construct instruments that identify permanent and transitory components of local earnings. Reduced-form evidence suggests that workers are sensitive to the share of the permanent component in an earnings innovation. Given this, I estimate a structural model of migration to recover cost parameters, exploiting variation in net present value induced by the instruments. Over a range of discount rates, I estimate the average cost of migration to an individual to lie between 0.3 and 1.1 times annual earnings. Fixed costs of moving (which include both financial and psychic costs) account for 60 percent of this, with the remaining 40 percent varying by distance. Furthermore, variation in idiosyncratic preferences is more than double the spatial variation in earnings. Using the parameter estimates of the model, I find that migration contributes 8.6 percentage points to local labor supply elasticity, split almost evenly between workers entering a province and fewer locals exiting. The model suggests that 20% of long-term earnings differentials over space can be attributed to perceived moving costs. ∗ Email: ashenoy@mit.edu. I am grateful to my advisors Abhijit Banerjee, Esther Duflo, and Rob Townsend for their excellent guidance. I also thank Isaiah Andrews, David Atkin, Jie Bai, Alex Bartik, Emily Breza, Arun Chan­ drasekhar, Ludovica Gazze, Nathan Hendren, Gaston Illanes, Anil Jain, Matthew Lowe, Benjamin Marx, Rachael Meager, Sarah Moshary, Jon Petkun, Otis Reid, Natalia Rigol, Frank Schilbach, Maheshwor Shrestha, Michael Stepner, Paulo Somaini, Melanie Wasserman, Ariel Zucker, and the participants of several MIT Development and International seminars and lunches for helpful feedback and advice. I am grateful to Jiaqiang Chen and researchers at the University of the Thai Chamber of Commerce for help obtaining the data. This work was supported by a National Science Foundation Graduate Research Fellowship. Any mistakes that remain are my own.
SURVEY AND ANALYSIS OF VARIOUS STEGANOGRAPHIC TECHNIQUES

Steganography is a method of secret communication that hides the existence of hidden message. The hidden message can be text, image, audio, video, etc. The innocent files can be a cover image after inserting the message into the cover image using stego-key, it is reffered to as stego-image. Steganography becomes more important due to the exponential growth and secret communication of potential computer users on the internet. Steganography is different from cryptography in the way that cryptography hides the contents of secret message where as steganography is about hiding the message. In this paper various steganographic techniques have been analyzed. This paper also gives an overview of steganography, its applications, how it is different from cryptography and different methods of steganography.
EFFECT OF PARTICLE ALIGNMENT ON MECHANICAL PROPERTIES OF NEAT CELLULOSE NANOCRYSTAL FILMS

Shear-based film casting methods were used to cast neat films from wood-based cellulose nanocrystal (CNC) suspensions. The degree of CNC alignment in dried films was characterized using the Hermans order parameter (S), and the film elastic modulus (E), ultimate tensile strength (sf ), elongation at failure (ef), and work of fracture (WF) were measured with respect to casting direction and CNC alignment. The degree of CNC alignment in dried films was found to increase with higher casting shear rates (0, 10∙s -1 , and 100∙s -1 ) and at higher suspension pH (~3 versus ~7). The maximum orientation (S=0.53) was achieved for CNC suspensions having a neutral pH and sheared at a rate of 100∙s -1
An efficient shape based feature for retrieval of healthcare literatures using CBIR technique

Recent advances in healthcare such as Evidence Based Medicine (EBM) and Clinical Decision Support Systems (CDSS) requires practitioners to frequently access archived historical healthcare literatures and images. As the majority of healthcare literatures contain images such as medical images, clip arts, waveforms, flow charts and block diagrams, in this paper we present the use of Content Based Image Retrieval (CBIR) for efficient healthcare literature search and retrieval. We introduce a novel shape based feature called Fourier Edge Orientation Autocorrelogram (FEOAC) for search and retrieval of healthcare literatures. Scale and translation invariant Edge Orientation Autocorrelogram (EOAC) feature is made rotation invariant by applying Fourier transform. This Fourier based shape feature also reduces the feature set dimension enabling faster retrieval of document images in large databases. Experimental results show that FEOAC outperforms EOAC for search and retrieval of healthcare document images, with improved precision and recall rates.
Setting the boundary free: a composite approach to surface parameterization

In the last decade, surface mesh parameterization has emerged as a standard technique in computer graphics. The ever increasing need for processing large and highly detailed data sets fosters the development of efficient parameterization techniques that can capture the geometry of the input meshes and produce low distortion planar maps. We present a set of novel techniques allowing for low distortion parameterization. In particular, we address one of the major shortcomings of linear methods by allowing the parametric representation to evolve freely on the plane without any fixed boundary vertices. Our method consists of several simple steps, each solving a linear problem. Our results exhibit a fair balance between high-quality and computational efficiency.
Robust error correction in infofuses

An infofuse is a combustible fuse in which information is encoded through the patterning of metallic salts, with transmission in the optical range simply associated with burning. The constraints, advantages and unique error statistics of physical chemistry require us to rethink coding and decoding schemes for these systems. We take advantage of the non-binary nature of our signal with a single bit representing one of N=7 states to produce a code that, using a single or pair of intensity thresholds, allows the recovery of the intended signal with an arbitrarily high recovery probability, given reasonable assumptions about the distribution of errors in the system. An analysis of our experiments with infofuses shows that the code presented is consistent with these schemes, and encouraging for the field of chemical communication and infochemistry given the vast permutations and combinations of allowable non-binary signals.
Applications of SELDI-MS technology in oncology

• Introduction • Surface enhanced laser desorption/ionisation‐mass spectrometry • Sampling • Clinical applications ‐ Detection and diagnosis ‐ Pre‐operative staging of disease ‐ Predicting response to therapy ‐ Metastasis and disease progression ‐ Drug resistance • In vitro applications ‐ Cell culture models • Protein interactions • Advantages over conventional technologies • Limitations • Conclusions
Speaker identification using minimum classification error training

We use a minimum classification error (MCE) training paradigm to build a speaker identification system. The training is optimized at the string level for a text-dependent speaker identification task. Experiments performed on a small set speaker identification task show that MCE training can reduce closed-set identification errors by up to 20-25% over a baseline system trained using maximum likelihood estimation. Further experiments suggest that additional improvement can be obtained by using some additional training data from speakers outside the set of registered speakers, leading to an overall reduction of the closed-set identification errors by about 35%.
A probabilistic algorithm for spatial color image segmentation

Finite mixture models are one of the most widely and commonly used probabilistic techniques for image segmentation. Although the most well known and commonly used distribution when considering mixture models is the Gaussian, it is certainly not the best approximation for image segmentation and other related image processing problems. In this paper, we propose to use finite Dirichlet mixture model (DMM), which offers more flexibility in data modeling, for image segmentation. A maximum likelihood (ML) based algorithm is applied for estimating the resulted segmentation model's parameters. Spatial information is also employed for figuring out the number of regions in an image and two color spaces are investigated and compared. The experimental results show that the proposed segmentation framework yields good overall performance that is better than a comparable technique based on Gaussian mixture model.