Miracle-dz/UniFAR-FTUs huggingface dataset:
Reciprocal Expression of Two Candidate Di-Iron Enzymes Affecting Photosystem I and Light-Harvesting Complex Accumulation

Crd1 (Copper response defect 1), which is required for the maintenance of photosystem I and its associated light-harvesting complexes in copper-deficient (−Cu) and oxygen-deficient (−O2) Chlamydomonas reinhardtii cells, is localized to the thylakoid membrane. A related protein, Cth1 (Copper target homolog 1), is shown to have a similar but not identical function by genetic suppressor analysis of gain-of-function sct1 (suppressor of copper target 1) strains that are transposon-containing alleles at CTH1. The pattern of Crd1 versus Cth1 accumulation is reciprocal; Crd1 abundance is increased in −Cu or −O2 cells, whereas Cth1 accumulates in copper-sufficient (+Cu), oxygenated cells. This expression pattern is determined by a single trans-acting regulatory locus, CRR1 (COPPER RESPONSE REGULATOR 1), which activates transcription in −Cu cells. In +Cu cells, a 2.1-kb Cth1 mRNA is produced and translated, whereas Crd1 is transcribed only at basal levels, leading to Cth1 accumulation in +Cu cells. In −Cu cells, CRR1 function determines the activation of Crd1 expression and the production of an alternative 3.1-kb Cth1 mRNA that is extended at the 5′ end relative to the 2.1-kb mRNA. Synthesis of the 3.1-kb mRNA, which encodes six small upstream open reading frames that possibly result in poor translation, blocks the downstream promoter through transcriptional occlusion. Fluorescence analysis of wild-type, crd1, and sct1 strains indicates that copper-responsive adjustment of the Cth1:Crd1 ratio results in modification of the interactions between photosystem I and associated light-harvesting complexes. The tightly coordinated CRR1-dependent regulation of isoenzymes Cth1 and Crd1 reinforces the notion that copper plays a specific role in the maintenance of chlorophyll proteins.
Forecasting and Perception of Average and Latest Hours Worked by On-Call Anesthesiologists

BACKGROUND: We studied the value of providing information to anesthesia providers about the length of time typically worked during on-call shifts. The mean time at which a shift ends can be used for purposes of trades, payments, or reverse auctions, because the mean is proportional to the total time. The 80th percentile (with a suitable upper confidence limit for uncertainty due to limited sample sizes) can be used for judging the earliest time by which after-work activities reasonably can be planned. METHODS: (A) Three years of operating room (OR) information system data were analyzed. Dependent variables were the earliest times when the numbers of ORs running were always ≤6 ORs, ≤4 ORs, and ≤2 ORs. We progressively built linear regression models for each of the three dependent variables using day of the week, scheduled number of cases, scheduled hours of cases (including turnovers), and linear time trend. Calculations were repeated after excluding residuals. Calculations were repeated using regression trees. (B) Anesthesiologists were surveyed about their perceptions of the mean and 80th percentiles. RESULTS: (A) For the three thresholds and two end points (mean and 80th percentile), differences among days of the week were as large as 45 min. Differences between end points for the same weekdays were as large as 245 min. Comparatively, additional knowledge about the number or hours of cases provided in the late afternoon on the working day before surgery reduced the mean absolute error by only 4.1–6.0 min. Results were insensitive to a variety of analytic methods. Information available more days before the day of surgery (e.g., 1 wk) would have had even less incremental predictive value. (B) The mean absolute error of anesthesiologists’ estimates for 80th percentiles was 60 min, principally because of underestimation of the 80th percentiles. More than half (69%, P = 0.0003) of anesthesiologists’ estimates for 80th percentiles had error >30 min, whereas errors of this magnitude were less for the mean (44%, P = 0.0004). CONCLUSIONS: Historical data from OR or anesthesia information management systems, or from anesthesia billing systems, can be used months before staff scheduling to provide insight to anesthesia providers on respective calls. The data are useful because experience provides limited intuition. Updates on scheduled workload available closer to the day of surgery provided only marginal increases in knowledge over the use of historical data.
Many to Many Matching with Demands and Capacities

Let A={a_1,a_2,. ,a_s} and {b_1,b_2,. ,b_t} with s+r=n, the many to many point matching with demands and capacities matches each point a_i in A to at least alpha_i and at most alpha_i points in B, and each point b_j in B to at least beta_j and at most beta_j points in A for all 1 <= i <= s and 1 <= j <= t. In this paper, we present an O(n^4) time and O(n) space algorithm for this problem.
High-Performance and Fault-Tolerant 3D NoC-Bus Hybrid Architecture Using ARB-NET-Based Adaptive Monitoring Platform

The emerging three-dimensional integrated circuits (3D-ICs) achieve greater device integration and enhanced system performance at lower cost and reduced area footprint, thereby offering higher order of connectivity and greater design choices and possibilities. To exploit the intrinsic capability of reduced communication distances in 3D-ICs, three-dimensional NoC-bus hybrid mesh architecture was proposed. Besides its various advantages in terms of area, power consumption, and performance, this architecture has a unique and hitherto previously unexplored possibility to implement an efficient system-wide monitoring network. In this paper, an efficient three-dimensional NoC architecture is proposed which is optimized for system performance, power consumption, and reliability. The mechanism benefits from a congestion-aware and bus failure-tolerant routing algorithm called AdaptiveZ for vertical communication. In addition, we have integrated a low-cost monitoring platform on top of the three-dimensional NoC-Bus Hybrid mesh architecture that can be efficiently used for various system management purposes such as traffic monitoring, fault tolerance, and thermal management. The proposed generic monitoring platform called ARB-NET utilizes bus arbiters to exchange the monitoring information directly with each other without using the data network. As a test case, based on the proposed monitoring platform, a fully congestion-aware and interlayer fault-tolerant routing algorithm named AdaptiveXYZ is presented taking advantage of information generated within bus arbiters. Compared to recently proposed stacked mesh three-dimensional NoCs, our extensive simulations with synthetic and real benchmarks reveal that our architecture using the AdaptiveXYZ routing can help in achieving significant power, performance, and reliability improvements with a negligible hardware overhead.
Increasing Access to Cost Effective Home-Based Rehabilitation for Rural Veteran Stroke Survivors.

INTRODUCTION An estimated 750,000 Americans experience a stroke annually. Most stroke survivors require rehabilitation. Limited access to rehabilitation facilities has a pronounced burden on functional outcomes and quality of life. Robotic devices deliver reproducible therapy without the need for real-time human oversight. This study examined the efficacy of using home-based, telerobotic-assisted devices (Hand and Foot Mentor: HM and FM) to improve functional ability and reduce depression symptoms, while improving access and cost savings associated with rehabilitation. METHODS Twenty stroke survivors performed three months of home-based rehabilitation using a robotic device, while a therapist remotely monitored progress. Baseline and end of treatment function and depression symptoms were assessed. Satisfaction with the device and access to therapy were determined using qualitative surveys. Cost analysis was performed to compare home-based, robotic-assisted therapy to clinic-based physical therapy. RESULTS Compared to baseline, significant improvement in upper extremity function (30.06%, p= 0.046), clinically significant benefits in gait speed (29.03%), moderate improvement in depressive symptoms (28.44%) and modest improvement in distance walked (30.2%) were observed. Participants indicated satisfaction with the device. Home-based robot therapy expanded access to post-stroke rehabilitation for 35% of the people no longer receiving formal services and increased daily access for the remaining 65%, with a cost savings of $2,352 (64.97%) compared to clinic-based therapy. CONCLUSION Stroke survivors made significant clinically meaningful improvements in the use of their impaired extremities using a robotic device in the home. Home-based, robotic therapy reduced costs, while expanding access to a rehabilitation modality for people who would not otherwise have received care.
An Executable Interface Specification for Industrial Embedded System Design

Nowadays, designers resort to abstraction techniques to conquer the complexity of industrial embedded systems during the design process. However, due to the large semantic gap between the abstractions and the implementation, the designers often fails to apply the abstraction techniques. In this paper, an EIS-based (executable interface specification) approach is proposed for the embedded system design.The proposed approach starts with using interface state diagrams to specify system architectures. A set of rules is introduced to transfer these diagrams into an executable model (EIS model) consistently. By making use of simulation/verification techniques, many architectural design errors can be detected in the EIS model at an early design stage. In the end, the EIS model can be systematically transferred into an interpreted implementation or a compiled implementation based on the constraints of the embedded platform. In this way, the inconsistencies between the high-level abstractions and the implementation can largely be reduced.
Statistical analysis of two non-linear least-squares estimators of sine waves parameters in the colored noise

The authors establish the large-sample accuracy properties of two nonlinear least-squares estimators (NLSEs) of sine waves parameters: the basic NLSE, which ignores the possible correlation of the noise; and the optimal NLSE, which, besides the sine-wave parameters, also estimates the noise correlation (appropriately parameterized). It is shown that these two NLSEs have the same accuracy in large samples. This result provides complete justification for preferring the computationally less-expensive basic NLSE over the optimal NLSE. Both estimators are shown to achieve the Cramer-Rao bound (CRB) as the sample size increases. A simple explicit expression for the CRB matrix is provided which should be useful in studying the performance of sine-wave parameter estimators designed to work in the colored noise case. <<ETX>>
Alternative Sources of Information for Code Smell Detection: Postcards from Far Away

Code smells have been defined as symptoms of poor design and implementation choices. Previous studies showed the negative impact of code smells on the comprehensibility and maintainability of code. For this reasons, several detection techniques have been proposed. Most of them rely on the analysis of the properties extractable from the source code. In the context of this work, we highlight several aspects that can possibly contribute to the improvement of the current state of the art and propose our solutions, based on the analysis on how code smells are actually introduced as well as the usefulness of historical and textual information to realize more reliable code smell detectors. Finally, we present an overview of the open issues and challenges related to code smell detection and management that the research community should focus on in the next future.
Building a RTOS for MPSoC dataflow programming

Multiprocessor Systems-on-Chip (MPSoC) are becoming the standard high performance Digital Signal Processing (DSP) systems. Hardware complexity abstraction is needed to enable efficient MPSoC programming. A major challenge of MPSoC programming is efficiently handling the combination of new features necessary in a MPSoC operating system: load balancing and efficient use of the parallel resources, with the more traditional features of Real-Time Operating Systems (RTOS): resource sharing between applications, task priorities and reactivity to events. This paper presents a method to combine dataflow methods and RTOS features. The resulting system prototypes an RTOS for symmetric multiprocessing MPSoCs whose inputs are dataflow graphs of applications. The prototype is built on the µC/OS-II RTOS. Experimental results are given on a 3GPP Long Term Evolution algorithm executed on a 4-core MPSoC.
Workload Shifting: Contention-Insular Disk Arrays for Big Data Systems

It is well known that in-place update index, unordered log structured index and ordered log structured index are three typical data organizations which are designed to meet different workload requirements respectively and wildly used in big data storage systems. Differentiated workload requirements in different phase of the data lifecycle, e.g. various types of data are injected into the big data storage systems in the write optimized manner, then they are needed to be read in the read optimized manner for analysis, lead to data organization transformation(data transformation for short). However, the simple mixture of foreground data injection and background data transformation causes serious disk contention. Frequent disk head seeks result in low disk throughput, and not only prolong the data transformation process, but also increase foreground data injection latency. In this paper, we propose \emph{Workload Shifting}, a novel log- structured design that shifts background data transformation away from the foreground data injection. Compared with conventional RAID0 disk array, \emph{Workload Shifting} effectively isolates background data transformation and foreground data injections, avoids the disk contention between them to boost their performance. We have implemented \emph{Workload Shifting} prototype on one multiple disks based disk array. Extensive experimental evaluation results show that compared with conventional RAID0 disk arrays, \emph{Workload Shifting} can avoid disk contention and speed up both data injection and data transformation significantly.
Resource-oriented Petri nets in deadlock avoidance of AGV systems

Presents a colored resource-oriented Petri net (CROPN) modeling method to deal with conflict and deadlock arising in automated guided vehicles (AGV) systems. Some unique features in AGV systems require further investigation into their deadlock avoidance using CROPN models. The proposed approach can easily handle both bidirectional and unidirectional paths. Bidirectional paths offer additional flexibility, efficiency and less cost than unidirectional paths. Yet they exhibit more challenging AGV management problems. By modeling nodes with places and lanes with transitions, one can easily construct a CROPN model for dynamic AGV systems with changing routes. A control policy suitable for real-time control implementation is then proposed.
Transmission Fourier Transform Raman Spectroscopy of Pharmaceutical Tablet Cores

Transmission Fourier transform (FT) Raman spectroscopy of pharmaceutical tablet cores is demonstrated using traditional, unmodified commercial instrumentation. The benefits of improved precision over backscattering Raman spectroscopy due to increased sample volume are demonstrated. Self-absorption effects on analyte band ratios and sample probe volume are apparent, however. A survey of near-infrared (NIR) absorption spectra in the FT-Raman spectral range (approximately 0 to 3500 wavenumber shift from 1064 nm, or 1064 to 1700 nm) of molecules with a wide range of NIR-active functional groups shows that although absorption at the laser wavelength (1064 nm) is relatively small, some regions of the Raman spectrum coincide with NIR absorbances of 0.5 per cm or greater. Fortunately, the pharmaceutically important regions of the Raman shift spectrum from 0 to 600 cm−1 and from 1400 to 1900 cm−1 exhibit low self-absorption for most organic materials. A statistical analysis of transmission FT-Raman noise in spectra collected from different regions of a pharmaceutical tablet provides insight into both spectral distortion and reduced sampling volume caused by self-absorption.
EDR: An Encounter and Distance Based Routing Protocol for Opportunistic Networks

In an Opportunistic Network (Oppnet), the transmission of messages between mobile devices is achieved in a store-carry-and-forward fashion since nodes store the incoming messages in their buffer and wait until a suitable next hop node is encountered that can carry the message closer to the destination. In such environment, due to the delay-tolerant nature of the network, designing a routing protocol is a challenge. This paper proposes a novel routing protocol called Encounter and Distance based Routing (EDR), which utilizes the so-called forward parameter to determine the next hop selection. This parameter is calculated by taking into account the number of encounters and the distance of each node in the network with respect to a particular destination. Simulation results are provided, showing the superiority of EDR over the History based Prediction for Routing (HBPR) protocol and the ProWait protocol, chosen as benchmark schemes, in terms of hop count, messages dropped, and average latency.
Optimized application of penalized regression methods to diverse genomic data

Motivation: Penalized regression methods have been adopted widely for high-dimensional feature selection and prediction in many bioinformatic and biostatistical contexts. While their theoretical properties are well-understood, specific methodology for their optimal application to genomic data has not been determined. Results: Through simulation of contrasting scenarios of correlated high-dimensional survival data, we compared the LASSO, Ridge and Elastic Net penalties for prediction and variable selection. We found that a 2D tuning of the Elastic Net penalties was necessary to avoid mimicking the performance of LASSO or Ridge regression. Furthermore, we found that in a simulated scenario favoring the LASSO penalty, a univariate pre-filter made the Elastic Net behave more like Ridge regression, which was detrimental to prediction performance. We demonstrate the real-life application of these methods to predicting the survival of cancer patients from microarray data, and to classification of obese and lean individuals from metagenomic data. Based on these results, we provide an optimized set of guidelines for the application of penalized regression for reproducible class comparison and prediction with genomic data. Availability and Implementation: A parallelized implementation of the methods presented for regression and for simulation of synthetic data is provided as the pensim R package, available at http://cran.r-project.org/web/packages/pensim/index.html. Contact: chuttenh@hsph.harvard. edu; juris@ai.utoronto. ca Supplementary Information: Supplementary data are available at Bioinformatics online.
A near-optimal algorithm for computing real roots of sparse polynomials

Let <i>p</i> ∈ Z[<i>x</i>] be an arbitrary polynomial of degree <i>n</i> with <i>k</i> non-zero integer coefficients of absolute value less than 2<sup>τ</sup>. In this paper, we answer the open question whether the real roots of <i>p</i> can be computed with a number of arithmetic operations over the rational numbers that is polynomial in the input size of the sparse representation of <i>p</i>. More precisely, we give a deterministic, complete, and certified algorithm that determines isolating intervals for all real roots of <i>p</i> with <i>O</i>(<i>k</i><sup>3</sup>·log(<i>n</i>τ)·log<i>n</i>) many exact arithmetic operations over the rational numbers. When using approximate but certified arithmetic, the bit complexity of our algorithm is bounded by Õ(<i>k</i><sup>4</sup>·<i>n</i>·(τ+<i>k</i>)), where Õ(·) indicates the omission of logarithmic factors. Hence, for sufficiently sparse polynomials (i.e. <i>k</i> = <i>O</i>(log<sup><i>c</i></sup>(<i>n</i>τ)) for a constant <i>c</i>), the bit complexity is Õ(<i>n</i>τ), which is optimal up to logarithmic factors.
Wavefront reconstruction using intensity measurements for real-time adaptive optics

The crucial step in adaptive optics feedback control is the reconstruction of the wavefront from wavefront sensor measurements. One of the sensors commonly used is the (Shack-)Hartmann sensor, which makes the wavefront reconstruction problem linear, in a least-squares sense. In this paper, a new methodology is proposed to reconstruct the wavefront for real-time adaptive optics control using the complete intensity measurements provided by the sensor, instead of the classical centroid algorithm which approximates the local wavefront slopes. In addition to an outline of the new wavefront reconstruction method, its performance is illustrated via a numerical simulation study. The advantages of the new method are highlighted by comparing it, in both open- and closed-loop, with a modal reconstruction algorithm that uses local wavefront slopes.
A FUN-SCALE for Understanding the Hedonic Value of a Product: The Destination Context

ABSTRACT “Fun” is one of the most frequently referenced sensory and hedonic phenomena in many different contexts of life, which merits scientific attention especially when consumer behavior is investigated with an experiential view of consumption. However, scientific definition and measurement of “fun” is virtually non-existent in literature. Thus, this study aims to develop a scale of fun with structural (underlying dimensions) and psychometric (reliability and validity) properties to assess the hedonic value of a destination as a product. Several stages of content analysis, data collection, exploratory factor analysis and confirmatory factor analysis for scale purification resulted in a FUN-SCALE with 12 items assembling into four factors that were named social vigor, psychological zest, emotional spark, and flow.
Communication recovery with emergency aerial networks

In spite of the significant advancements in wireless connectivity, the static form of the network infrastructure cannot guarantee an uninterrupted operation of the ever-growing wireless consumer electronics in emergency situations such as natural disasters. In such occasions, employing flexible aerial nodes can tackle this issue by recovering the communication rapidly, when the need for connectivity is of utmost importance. In this paper, we study the use of aerial nodes for communication recovery after a communication breakdown. We provide an analytical model of the recovery probability that demonstrates the capabilities of such networks. In the performance evaluation, we show the effects of the altitude and the distance between the aerial nodes on the recovery probability and verify them with simulations. Moreover, we introduce our testbed and preliminary experimental work that shows promising results for aerial networks. Finally, we discuss useful insights for the network design and present some open issues that exist in this field.