Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolic phenotype of skeletal muscle in early critical illness

Objectives To characterise the sketetal muscle metabolic phenotype during early critical illness. Methods Vastus lateralis muscle biopsies and serum samples (days 1 and 7) were obtained from 63 intensive care patients (59% male, 54.7±18.0 years, Acute Physiology and Chronic Health Evaluation II score 23.5±6.5). Measurements and main results From day 1 to 7, there was a reduction in mitochondrial beta-oxidation enzyme concentrations, mitochondrial biogenesis markers (PGC1α messenger mRNA expression (−27.4CN (95% CI −123.9 to 14.3); n=23; p=0.025) and mitochondrial DNA copy number (−1859CN (IQR −5557–1325); n=35; p=0.032). Intramuscular ATP content was reduced compared tocompared with controls on day 1 (17.7mmol/kg /dry weight (dw) (95% CI 15.3 to 20.0) vs. 21.7 mmol/kg /dw (95% CI 20.4 to 22.9); p<0.001) and decreased over 7 days (−4.8 mmol/kg dw (IQR −8.0–1.2); n=33; p=0.001). In addition, the ratio of phosphorylated:total AMP-K (the bioenergetic sensor) increased (0.52 (IQR −0.09–2.6); n=31; p<0.001). There was an increase in intramuscular phosphocholine (847.2AU (IQR 232.5–1672); n=15; p=0.022), intramuscular tumour necrosis factor receptor 1 (0.66 µg (IQR −0.44–3.33); n=29; p=0.041) and IL-10 (13.6 ng (IQR 3.4–39.0); n=29; p=0.004). Serum adiponectin (10.3 µg (95% CI 6.8 to 13.7); p<0.001) and ghrelin (16.0 ng/mL (IQR −7–100); p=0.028) increased. Network analysis revealed a close and direct relationship between bioenergetic impairment and reduction in muscle mass and between intramuscular inflammation and impaired anabolic signaling. ATP content and muscle mass were unrelated to lipids delivered. Conclusions Decreased mitochondrial biogenesis and dysregulated lipid oxidation contribute to compromised skeletal muscle bioenergetic status. In addition, intramuscular inflammation was associated with impaired anabolic recovery with lipid delivery observed as bioenergetically inert. Future clinical work will focus on these key areas to ameliorate acute skeletal muscle wasting. Trial registration number NCT01106300.
Maize lateral root developmental plasticity induced by mild water stress. I: Genotypic variation across a high-resolution series of water potentials.

Lateral root developmental plasticity induced by mild water stress was examined across a high-resolution series of growth media water potentials (Ψw ) in two genotypes of maize. The suitability of several media for imposing near-stable Ψw treatments on transpiring plants over prolonged growth periods was assessed. Genotypic differences specific to responses of lateral root growth from the primary root system occurred between cultivars FR697 and B73 over a narrow series of water stress treatments ranging in Ψw from -0.25 to -0.40 MPa. In FR697, both the average length and number of first-order lateral roots were substantially enhanced at a Ψw of -0.25 MPa compared with well-watered controls. These effects were separated spatially, occurring primarily in the upper and lower regions of the axial root, respectively. Furthermore, first-order lateral roots progressively increased in diameter with increasing water stress, resulting in a maximum 2.3-fold increase in root volume at a Ψw of -0.40 MPa. In B73, in contrast, the length, diameter, nor number of lateral roots was increased in any of the water stress treatments. The genotype-specific responses observed over this narrow range of Ψw demonstrate the necessity of high-resolution studies at mild stress levels for characterization of lateral root developmental plasticity.
The Effect of Incentives on Knowledge Sharing in Computer-Mediated Communication: An Experimental Investigation

Do financial incentives increase knowledge sharing in a computermediated environment? Thirty‐six accounting students assigned to groups with different financial incentives (group, piece‐rate, or tournament) searched for errors in accounting‐related spreadsheets, with access to an online chat room they could use for helping others. The dependent variable was the amount of knowledge the students shared with others. Quantitative and qualitative data suggest that the group financial incentives inspired more knowledge sharing than did either tournament or piece‐rate. Results suggest that managers should carefully consider incentive structures in computer‐based systems because incentives potentially affect knowledge sharing.
"Inputting" the Environment: Reconsidering the Environmental Information Matrix

Brown et al. (2005) (hereafter Brown et al.) tackle an under-researched and increasingly important aspect of accounting information systems—the potential impact of these systems on the natural environment. They support the claim that AIS gather insufficient information and provide inadequate support for addressing environmental concerns (Gray and Bebbington 2002; Shaltegger and Burritt 2000). The Brown et al. paper in this issue is part of an ongoing research program that explores and adds to understanding of environment reporting and accounting systems. This program includes extensive analysis of corporate environmental accounting and reporting, examines theory and practice in corporate and environmental strategy, and links the two fields.
MCRiceRepGP: a framework for the identification of genes associated with sexual reproduction in rice

Rice is an important cereal crop, being a staple food for over half of the world's population, and sexual reproduction resulting in grain formation underpins global food security. However, despite considerable research efforts, many of the genes, especially long intergenic non-coding RNA (lincRNA) genes, involved in sexual reproduction in rice remain uncharacterized. With an increasing number of public resources becoming available, information from different sources can be combined to perform gene functional annotation. We report the development of MCRiceRepGP, a machine learning framework which integrates heterogeneous evidence and employs multicriteria decision analysis and machine learning to predict coding and lincRNA genes involved in sexual reproduction in rice. The rice genome was reannotated using deep-sequencing transcriptomic data from reproduction-associated tissue/cell types identifying previously unannotated putative protein-coding genes and lincRNAs. MCRiceRepGP was used for genome-wide discovery of sexual reproduction associated coding and lincRNA genes. The protein-coding and lincRNA genes identified have distinct expression profiles, with a large proportion of lincRNAs reaching maximum expression levels in the sperm cells. Some of the genes are potentially linked to male- and female-specific fertility and heat stress tolerance during the reproductive stage. MCRiceRepGP can be used in combination with other genome-wide studies, such as genome-wide association studies, giving greater confidence that the genes identified are associated with the biological process of interest. As more data, especially about mutant plant phenotypes, become available, the power of MCRiceRepGP will grow, providing researchers with a tool to identify candidate genes for future experiments. MCRiceRepGP is available as a web application (http://mcgplannotator.com/MCRiceRepGP/).
Unsupervised clustering of temporal patterns in high-dimensional neuronal ensembles using a novel dissimilarity measure

Temporally ordered multi-neuron patterns likely encode information in the brain. We introduce an unsupervised method, SPOTDisClust (Spike Pattern Optimal Transport Dissimilarity Clustering), for their detection from high-dimensional neural ensembles. SPOTDisClust measures similarity between two ensemble spike patterns by determining the minimum transport cost of transforming their corresponding normalized cross-correlation matrices into each other (SPOTDis). Then, it performs density-based clustering based on the resulting inter-pattern dissimilarity matrix. SPOTDisClust does not require binning and can detect complex patterns (beyond sequential activation) even when high levels of out-of-pattern “noise” spiking are present. Our method handles efficiently the additional information from increasingly large neuronal ensembles and can detect a number of patterns that far exceeds the number of recorded neurons. In an application to neural ensemble data from macaque monkey V1 cortex, SPOTDisClust can identify different moving stimulus directions on the sole basis of temporal spiking patterns. Author summary The brain encodes information by ensembles of neurons, and recent technological developments allow researchers to simultaneously record from over thousands of neurons. Neurons exhibit spontaneous activity patterns, which are constrained by experience and development, limiting the portion of state space that is effectively visited. Patterns of spontaneous activity may contribute to shaping the synaptic connectivity matrix and contribute to memory consolidation, and synaptic plasticity formation depends crucially on the temporal spiking order among neurons. Hence, the unsupervised detection of spike sequences is a sine qua non for understanding how spontaneous activity contributes to memory formation. Yet, sequence detection presents major methodological challenges like the sparsity and stochasticity of neuronal output, and its high dimensionality. We propose a dissimilarity measure between neuronal patterns based on optimal transport theory, determining their similarity from the pairwise cross-correlation matrix, which can be taken as a proxy of the “trace” that is left on the synaptic matrix. We then perform unsupervised clustering and visualization of patterns using density clustering on the dissimilarity matrix and low-dimensional embedding techniques. This method does not require binning of spike times, is robust to noise, jitter and rate fluctuations, and can detect more patterns than the number of neurons.
Prevalence of Tuberculosis and Treatment Outcomes of Patients with Tuberculosis among Inmates in Debrebirhan Prison, North Shoa Ethiopia

Background Prevalence of tuberculosis in vulnerable groups such as prisoners is usually high, and the problem is worsened by poor treatment outcomes. In spite of this, there is limited information regarding tuberculosis in prisons of Ethiopia. Hence, this study was aimed to assess the prevalence of tuberculosis and treatment outcomes of patients with tuberculosis among inmates of Debrebirhan prison in North Shoa, Ethiopia. Methods A retrospective cross-sectional study was conducted among inmates of Debrebirhan prison. Data were collected by reviewing the medical charts and other records of prison inmates diagnosed and treated for tuberculosis between September 2010 and August 2015. Data were entered and analyzed using SPSS version 21.0. Results A total of 162 patients with tuberculosis were registered and treated at Debrebirhan prison health center within the five years study period. The overall average prevalence was found to be 32 per 1538 (2139 per 100,000) prison inmates. Regarding treatment outcome, 44(27.2%) were cured, 59(36.42%) completed treatment, 2(1.24%) were treatment failures, 6(3.72%) died and 51(31.5%) were not evaluated. The five year's treatment success rate was found to be 63.62%. Area of residence (AOR= 3.59; 95% CI: 1.44, 8.93), duration of imprisonment (AOR = 3.67; 95% CI: 1.53, 8.78) and history of tuberculosis were significantly associated with treatment outcome of tuberculosis. Conclusion This study showed high prevalence of tuberculosis in Debrebirhan prison. It also revealed that the treatment success rate of patients with tuberculosis was lower than the target set by World Health Organization.
Association between sex, race/ethnicity, season, day of week, and alcohol use and related risks in college student athletes and nonathletes

Abstract Objective: To examine personal and social constructs (eg, sex, race) and external influences (ie, competition schedules) that are associated with the pattern and amount of alcohol consumption by student athletes compared to nonathletes. Participants: Students (n = 2,984; 57% female, 61% white, 16% athlete) on a single campus were surveyed in Fall 2011 and Spring 2012. Methods: Anonymous surveys included demographics, alcohol use, and related problems. Results: Student athletes consumed more alcohol than nonathletes, with male and white athletes posing the highest levels of risk for heavy consumption. Expanded examination of in- and out-of-season athletes found out-of-season athletes drink more frequently and more per occasion than their in-season peers. Athletes were more likely than nonathletes to drink on specific days of the week and daily patterns differed between in- and out-of-season athletes. Conclusions: The risk of athlete status is moderated by sex, race, season, and day of the week.
Thin‐layer drying behavior of West Indian lemongrass (Cymbopogan citratus) leaves

Abstract The objectives of this study were to investigate the effect of temperature (40, 50, 60, and 70°C), and air velocity (0.5, 1, and 2 m/s) on the drying behavior of West Indian lemongrass (Cymbopogan citratus) leaves. Drying was carried out in a computer‐controlled tray dryer. Overall, the effect of temperature was seen to be more important than that of air velocity, but the air velocity did have an effect on drying rates at the start of the drying process at 50–70°C. Drying rate constants, diffusivity values, and activation energy were determined. Twenty‐two empirical and semiempirical thin‐layer models were tested, and although model fit varied, the Midilli model could be applied to all data with reasonable prediction of MR values.
Roles and Impacts of Hands-on Software Architects in Five Industrial Case Studies

Whether software architects should also code is an enduring question. In order to satisfy performance, security, reliability and other quality concerns, architects need to compare and carefully choose a combination of architectural patterns, styles or tactics. Then later in the development cycle, these architectural choices must be implemented completely and correctly so there will not be any drift from envisioned design. In this paper, we use data analytics-based techniques to study five large-scale software systems, examining the impact and the role of software architects who write code on software quality. Our quantitative study is augmented with a follow-up interview of architects. This paper provides empirical evidence for supporting the pragmatic opinions that architects should write code. Our analysis shows that implementing architectural tactics is more complex than delivering functionality, tactics are more error prone than software functionalities, and the architects tend to introduce fewer bugs into the implementation of architectural tactics compared to the developers.
Measurement System for Attitude of Anterior Pelvic Plane and Implantation of Prothesis in THR Surgery

With the average age of population increasing in the world, the number of total hip replacement (THR) surgeries increases year by year. However, the failure rate of THR surgeries is up to 10% following primary surgery and 28% after revision arthroplasty, which has direct correlation to the implantation angles between prosthesis and pelvis. To improve the implanting accuracy of the prosthesis, we propose a measurement system and estimation algorithms. The system includes three parts: an initial attitude measurement instrument, which is used to determine the initial attitude of the anterior pelvic plane (APP), a real-time attitude measurement instrument, which aims to acquire the real-time attitude of the APP, and an acetabular cup angle measurement instrument, which obtains the relative angles between prosthesis and pelvis. Each of them is based on inertial measurement unit (IMU) and magnetometer. A quaternion-based extended Kalman filter is adopted to fuse the data from IMU and magnetometer to estimate the orientation, and the algorithm calculating the attitude of pelvis and relative angles between pelvis and prosthesis is designed in this paper. The reliability of this system, from the measurement point of view, has been verified by experiments. The experimental results show that the root-mean-square errors of APP attitude and acetabular cup implanting orientation are less than 1.6° and 3° with standard uncertainty of less than 0.22° and 0.17°, respectively. The accuracy of our system meets the requirement of the THR surgeries.
Capacity fading detection of rectangular LiFePO4 battery by tomographic image

Detection of the power battery capacity and its fading is still a problem, owing to the commonly test method time-consuming and destructively. Based on the principle of battery electrochemistry and computer tomography, the X-ray computed tomography image detection of battery capacity fading is proposed because of the advantage of quick, accurate and non-destructive. A kind of typical rectangular LiFePO4 battery which used in pure electric vehicle is experiment object. The structure morphological change is extracted by tomography image of battery in different capacity fading. Combining with the traditional electrochemical performance detection, the relationship between the electrochemical performance parameter and the structure morphological parameter is studied. The experimental result shows that the variation of active material's area is relate to the capacity fading of battery. The more the active material's area decrease, the more the capacity fading. The X-ray computed tomography image detection method is a practical, quickly, and non-destructively method to detect capacity fading.
Multi-granularity fuzzy soft probability rough sets

Based on the probabilistic rough sets, the concept of multi-granularity fuzzy soft probabilistic rough sets (MGFSPR- sets) is introduced. A pair of multi-granularity fuzzy soft probabilistic approximation is proposed. Basic properties of multi- granularity soft probabilistic rough approximations are presented. New type of Bayes decision under multi-granularity fuzzy soft probabilistic rough sets model is studied.
Coupled Tensor Decomposition for Hyperspectral Pansharpening

This paper aims to effectively preserve the spatial and spectral information of hyperspectral (HS) images. For this purpose, the author proposed a new image fusion method based on coupled tensor decomposition (CTD). First, the wanted high spatial resolution HS (HRHS) images were decomposed into the core tensor and basis matrices. Assuming that the basis matrices can be calculated from low spatial resolution HS (LRHS) images, the core tensor was estimated from the high spatial resolution multispectral (HRMS) images based on the relationship between HRHS and HRMS images. Finally, the HRHS images were obtained by reconstructing the core tensor with basis matrices. Owing to the good properties of tensor, the proposed method achieved better fusion results on different data sets than those of the contrastive methods. The research findings shed new light on hyperspectral pansharpening.
Semidefinite Programming for NLOS Error Mitigation in TDOA Localization

Non-line-of-sight (NLOS) error mitigation for the time-of-arrival (TOA) localization has been extensively studied, but these methods cannot be directly applied for the time-difference-of-arrival (TDOA) systems. Recent work has applied convex optimization for NLOS error mitigation in TDOA systems. Issues remain unsolved with this technique include the convex hull problem, reference-anchor selection problem, and difficulties dealing with a wide range of NLOS-caused ranging errors. This letter proposes a new technique to transform a TDOA model into a TOA model and develops a semidefinite programming method with new constraints for effective NLOS error mitigation in TDOA systems. Major advantages of this method include: 1) it resolves the issues such as convex hull and reference-anchor selection issues that existing schemes are facing; 2) it does not require any a priori information about NLOS links or NLOS error statistics; and 3) it achieves a better performance than existing convex optimization schemes, which is verified in both simulation and real experiments.
3D Environment Measurement and Reconstruction Based on LiDAR

In this paper, we propose 3D Environment Measurement and Reconstruction Based on LiDAR. Human life is surrounded by a variety of sensors. Through the combination of different sensors, a designer can carry out environmental testing and then replace the human perception system. The principle of Velodyne LiDAR adopts the time of flight (ToF) technology based on infrared laser light. According to the known of the speed of light, the relative distance between the object and LiDAR can be calculated. Therefore, we proposed a system design for the static object with segmentation technology based on 3D LiDAR. At first, we decode the 3D LiDAR information, which transmits the UDP format of data packets that include the information of distance, angle, reflectivity, and time stamp. Above of all results can be performed the point cloud of the coordinate system in the 3D environment. Then we define the Euclidean clustering threshold to do the object segmentation. Finally, we design a digital chip with additional CORDIC circuit based on the lookup table to achieve the sine and cosine value conversion of angle.
Fundamental Limits on a Class of Secure Asymmetric Multilevel Diversity Coding Systems

In the future communication applications, users may obtain their messages that have different importance levels distributively from several available sources, such as distributed storage or even devices belonging to other users. This scenario is the best modeled by the multilevel diversity coding systems (MDCS). To achieve perfect (information-theoretic) secrecy against wiretap channels, this paper investigates the fundamental limits on the secure rate region of the asymmetric MDCS (AMDCS), which include the symmetric case as a special case. Threshold perfect secrecy is added to the AMDCS model. The eavesdropper may have access to any one but not more than one subset of the channels but know nothing about the sources, as long as the size of the subset is not above the security level. The question of whether superposition (source separation) coding is optimal for such an AMDCS with threshold perfect secrecy is answered. A class of secure AMDCS (S-AMDCS) with an arbitrary number of encoders is solved, and it is shown that linear codes are optimal for this class of instances. However, in contrast with the secure symmetric MDCS, superposition is shown to be not optimal for S-AMDCS in general. In addition, necessary conditions on the existence of a secrecy key are determined as a design guideline.
Analysis of Pure and Slotted ALOHA With Multi-Packet Reception and Variable Packet Size

Multiple packet reception (MPR) is becoming a viable reality for wireless random access protocols thanks to advances in the physical layer and new coding techniques. In the simplest <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-MPR model, a receiver can resolve up to <inline-formula> <tex-math notation="LaTeX">$K\geq 1$ </tex-math></inline-formula> parallel transmissions. We extend the classical analysis of pure and slotted ALOHA to <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-MPR devices with arbitrary degree <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> for fixed and variable packet size. Through a parsimonious modeling approach, we derive relatively simple analytical expressions. In this way, we gain insight and quantitative understanding on the fundamental tradeoffs between pure and slotted ALOHA and on the scaling of maximum achievable throughput with <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>.