Miracle-dz/UniFAR-FTUs huggingface dataset:
SleepSensei: An Automated Sleep Quality Monitor and Sleep Duration Estimator

SleepSensei is an automated sleep quality monitor and estimates the sleep duration for a user. It essentially builds a personalized model for determining the apt sleep duration for a given user. In our model, with the help of multiple inter-connected devices, we combine features related to user surroundings and those related to user movements during sleep. We use regression models in our system to calculate "sleep share" of a user, and report an MSE as low as 0.0041 when tested on 7 users, with more than a week's data. We also develop a smart alarm based on the notion of "sleep quota" from the model. The alarm has an average precision of 0.87 from the survey conducted. We also present an in-depth feature analysis to give further insights of individual sleep behavior.
Using Aggregated Relational Data to Feasibly Identify Network Structure Without Network Data

Social network data are often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD): responses to questions of the form "how many of your links have trait k ? " Our method uses ARD to recover parameters of a network formation model, which permits sampling from a distribution over node- or graph-level statistics. We replicate the results of two field experiments that used network data and draw similar conclusions with ARD alone.
Role of SIRT1-mediated mitochondrial and Akt pathways in glioblastoma cell death induced by Cotinus coggygria flavonoid nanoliposomes

Flavonoids, the major polyphenol components in Cotinus coggygria (CC), have been found to show an anticancer effect in our previous study; however, the exact mechanisms of inducing human glioblastoma (GBM) cell death remain to be resolved. In this study, a novel polyvinylpyrrolidone K-30/sodium dodecyl sulfate and polyethyleneglycol-coated liposome loaded with CC flavonoids (CCFs) was developed to enhance solubility and the antibrain tumor effect, and the molecular mechanism regarding how CCF nanoliposomes (CCF-NLs) induce apoptotic cell death in vitro was investigated. DBTRG-05MG GBM cell lines treated with CCF-NLs showed potential antiproliferative effects. Regarding the underlying mechanisms of inducing apoptosis in DBTRG-05MG GBM cells, CCF-NLs were shown to downregulate the expression of antiapoptotic B-cell lymphoma/leukemia 2 (Bcl-2), an apoptosis-related protein family member, but the expression of proapoptotic Bcl-2-associated X protein was enhanced compared with that in controls. CCF-NLs also inhibited the activity of caspase-3 and -9, which is the initiator caspase of the extrinsic and intrinsic apoptotic pathways. Blockade of caspase activation consistently induced apoptosis and inhibited growth in CCF-NL-treated DBTRG-05MG cells. This study further investigated the role of the Akt pathway in the apoptotic cell death by CCF-NLs, showing that CCF-NLs deactivated Akt. Specifically, CCF-NLs downregulated the expression of p-Akt and SIRT1 as well as the level of phosphorylated p53. Together, these results indicated SIRT1/p53-mediated cell death was induced by CCF-NLs, but not by extracellular signal-regulated kinase, in DBTRG-05MG cells. Overall, this study suggested caspase-dependent activation of both the intrinsic and extrinsic signaling pathways, probably through blockade of the SIRT1/p53-mediated mitochondrial and Akt pathways to exert the proapoptotic effect of CCF-NLs in DBTRG-05MG GBM cells.
Thermo-electrical engineering

The engineer's interest in thermo-electric phenomena has in the past been mainly confined to devices, based on the Seebeck effect, for the measurement of temperature and r.f. power and radiation by means of thermocouples or thermopiles constructed from metals. Even with the best combination of metals available the use of the Seebeck effect for generation is barely feasible, and the use of the Peltier effect for refrigeration is quite impracticable.The success of germanium and silicon in the production of transistors and junction rectifiers has encouraged the study of the mechanism of electrical and thermal transport in semiconductors. Thus, it has been possible to select potentially efficient thermo-electric alloys and compounds from the vast range of semiconductors available.In the case of bismuth telluride a high figure-of-merit material has been obtained which makes refrigeration of small volumes a practical proposition. A generator efficiency approaching 5% is possible with bismuth telluride in the case where the ideal efficiency would not exceed 25% with temperature limits of 300–400° K.Many people1 elsewhere have recorded the search for thermo-electric materials and the optimization of their thermo-electric properties. The object here is to explain simply the basic principles of generators and cooling units in a quantitative manner. The salient features which emerge indicate the potentialities of bismuth telluride for the generation of power and heat pumping, in particular refrigeration of small volumes and local cooling.The paper is based on work carried out by the author on the engineering applications of bismuth telluride.
Co-Extrusion Layer Multiplication of Rheologically Mismatched Polymers: A Novel Processing Route

Abstract Co-extruded films with up to 65 layers of two rheologically mismatched polymer systems – polystyrene/poly(methylmethacrylate) (PS/PMMA) and hard/soft thermoplastic polyurethanes (TPUs) – were successfully produced using a combination of a 9-layer feedblock, low-pressure drop multiplier dies, and external lubricants. Formation of viscoelastic instabilities was studied using a custom visualization and by finite element method (FEM) simulations of a standard multiplier. The results showed that the flow inside the standard multiplier die is highly non-uniform, with severe gradients in shear and normal stresses and viscous encapsulation occurring mainly in the initial multiplication stages where there is enough material available in the low-viscosity layers to proceed with the encapsulation. To mitigate layer degradation the standard 2- or 3-layer feedblock was replaced with a 9-layer one, thereby decreasing the thickness of each layer at the end of the feedblock. Also, subsequent layering was performed using a low flow resistance die. This new multiplier die yields a more uniform flow profile and imparts a more homogeneous thermo-mechanical history on the melt which results in an improved layer stability. Simulations showed that in the standard die the second normal-stress difference (N2) responsible for elastic instabilities at the edges of the die are very high. These can be reduced by inducing slip at the wall resulting in be much improved layer uniformity and stability. This was accomplished experimentally via the use of external lubricants, and the resulting layered structure was indeed much better than was possible to achieve with the conventional multiplier dies.
Non-Negative Spectral Learning and Sparse Regression-Based Dual-Graph Regularized Feature Selection

Feature selection is an important approach for reducing the dimension of high-dimensional data. In recent years, many feature selection algorithms have been proposed, but most of them only exploit information from the data space. They often neglect useful information contained in the feature space, and do not make full use of the characteristics of the data. To overcome this problem, this paper proposes a new unsupervised feature selection algorithm, called non-negative spectral learning and sparse regression-based dual-graph regularized feature selection (NSSRD). NSSRD is based on the feature selection framework of joint embedding learning and sparse regression, but extends this framework by introducing the feature graph. By using low dimensional embedding learning in both data space and feature space, NSSRD simultaneously exploits the geometric information of both spaces. Second, the algorithm uses non-negative constraints to constrain the low-dimensional embedding matrix of both feature space and data space, ensuring that the elements in the matrix are non-negative. Third, NSSRD unifies the embedding matrix of the feature space and the sparse transformation matrix. To ensure the sparsity of the feature array, the sparse transformation matrix is constrained using the ${L_{2,1}}$ -norm. Thus feature selection can obtain accurate discriminative information from these matrices. Finally, NSSRD uses an iterative and alternative updating rule to optimize the objective function, enabling it to select the representative features more quickly and efficiently. This paper explains the objective function, the iterative updating rules and a proof of convergence. Experimental results show that NSSRD is significantly more effective than several other feature selection algorithms from the literature, on a variety of test data.
Ieee Transactions on Information Forensics and Security 1 Latent Laplacian Maximum Entropy Discrimination for Detection of High-utility Anomalies

—Data-driven anomaly detection methods suffer from the drawback of detecting all instances that are statistically rare, irrespective of whether the detected instances have real-world significance or not. In this paper, we are interested in the problem of specifically detecting anomalous instances that are known to have high real-world utility, while ignoring the low-utility statistically anomalous instances. To this end, we propose a novel method called Latent Laplacian Maximum En-tropy Discrimination (LatLapMED) as a potential solution. This method uses the EM algorithm to simultaneously incorporate the Geometric Entropy Minimization principle for identifying statistical anomalies, and the Maximum Entropy Discrimination principle to incorporate utility labels, in order to detect high-utility anomalies. We apply our method in both simulated and real datasets to demonstrate that it has superior performance over existing alternatives that independently pre-process with unsupervised anomaly detection algorithms before classifying.
Nonlinear thermoelectric effects in high-field superconductor-ferromagnet tunnel junctions

Background: Thermoelectric effects result from the coupling of charge and heat transport and can be used for thermometry, cooling and harvesting of thermal energy. The microscopic origin of thermoelectric effects is a broken electron–hole symmetry, which is usually quite small in metal structures. In addition, thermoelectric effects decrease towards low temperatures, which usually makes them vanishingly small in metal nanostructures in the sub-Kelvin regime. Results: We report on a combined experimental and theoretical investigation of thermoelectric effects in superconductor/ferromagnet hybrid structures. We investigate the dependence of thermoelectric currents on the thermal excitation, as well as on the presence of a dc bias voltage across the junction. Conclusion: Large thermoelectric effects are observed in superconductor/ferromagnet and superconductor/normal-metal hybrid structures. The spin-independent signals observed under finite voltage bias are shown to be reciprocal to the physics of superconductor/normal-metal microrefrigerators. The spin-dependent thermoelectric signals in the linear regime are due to the coupling of spin and heat transport, and can be used to design more efficient refrigerators.
Identifying Cytomegalovirus Complications Using the Quantiferon-CMV Assay After Allogeneic Hematopoietic Stem Cell Transplantation

Background A simple test to identify recovery of CMV-specific T-cell immunity following hematopoietic stem cell transplantation (HSCT) could assist clinicians in managing CMV-related complications. Methods In an observational, multicenter, prospective study of 94 HSCT recipients we evaluated CMV-specific T-cell immunity at baseline, 3, 6, 9, and 12 months after transplant using the Quantiferon-CMV, an enzyme-linked immunosorbent spot assay (ELISpot), and intracellular cytokine staining. Results At 3 months after HSCT, participants who developed CMV disease (n = 8) compared with CMV reactivation (n = 26) or spontaneous viral control (n = 25) had significantly lower CD8+ T-cell production of interferon-γ (IFN-γ) in response to CMV antigens measured by Quantiferon-CMV (P = .0008). An indeterminate Quantiferon-CMV result had a positive predictive value of 83% and a negative predictive value of 98% for identifying participants at risk of further CMV reactivation. Participants experiencing CMV reactivation compared with patients without CMV reactivation had a reduced proportion of polyfunctional (IFN-γ+/tumor necrosis factor α-positive) CD4+ and CD8+ T cells and a higher proportion of interleukin 2-secreting cells (P = .01 and P = .002, respectively). Conclusions Quantifying CMV-specific T-cell immunity after HSCT can identify participants at increased risk of clinically relevant CMV-related outcomes.
Force encoding in muscle spindles during stretch of passive muscle

Muscle spindle proprioceptive receptors play a primary role in encoding the effects of external mechanical perturbations to the body. During externally-imposed stretches of passive, i.e. electrically-quiescent, muscles, the instantaneous firing rates (IFRs) of muscle spindles are associated with characteristics of stretch such as length and velocity. However, even in passive muscle, there are history-dependent transients of muscle spindle firing that are not uniquely related to muscle length and velocity, nor reproduced by current muscle spindle models. These include acceleration-dependent initial bursts, increased dynamic response to stretch velocity if a muscle has been isometric, and rate relaxation, i.e., a decrease in tonic IFR when a muscle is held at a constant length after being stretched. We collected muscle spindle spike trains across a variety of muscle stretch kinematic conditions, including systematic changes in peak length, velocity, and acceleration. We demonstrate that muscle spindle primary afferents in passive muscle fire in direct relationship to muscle force-related variables, rather than length-related variables. Linear combinations of whole muscle-tendon force and the first time derivative of force (dF/dt) predict the entire time course of transient IFRs in muscle spindle Ia afferents during stretch (i.e., lengthening) of passive muscle, including the initial burst, the dynamic response to lengthening, and rate relaxation following lengthening. Similar to acceleration scaling found previously in postural responses to perturbations, initial burst amplitude scaled equally well to initial stretch acceleration or dF/dt, though later transients were only described by dF/dt. The transient increase in dF/dt at the onset of lengthening reflects muscle short-range stiffness due to cross-bridge dynamics. Our work demonstrates a critical role of muscle cross-bridge dynamics in history-dependent muscle spindle IFRs in passive muscle lengthening conditions relevant to the detection and sensorimotor response to mechanical perturbations to the body, and to previously-described history-dependence in perception of limb position.
Epigenetic modification of the oxytocin and glucocorticoid receptor genes is linked to attachment avoidance in young adults

ABSTRACT Attachment in the context of intimate pair bonds is most frequently studied in terms of the universal strategy to draw near, or away, from significant others at moments of personal distress. However, important interindividual differences in the quality of attachment exist, usually captured through secure versus insecure – anxious and/or avoidant – attachment orientations. Since Bowlby’s pioneering writings on the theory of attachment, it has been assumed that attachment orientations are influenced by both genetic and social factors – what we would today describe and measure as gene by environment interaction mediated by epigenetic DNA modification – but research in humans on this topic remains extremely limited. We for the first time examined relations between intra-individual differences in attachment and epigenetic modification of the oxytocin receptor (OXTR) and glucocorticoid receptor (NR3C1) gene promoter in 109 young adult human participants. Our results revealed that attachment avoidance was significantly and specifically associated with increased OXTR and NR3C1 promoter methylation. These findings offer first tentative clues on the possible etiology of attachment avoidance in humans by showing epigenetic modification in genes related to both social stress regulation and HPA axis functioning.
Meta-analysis of XRCC1 polymorphism and risk of female reproductive system cancer

Numerous epidemiological studies have evaluated the association between polymorphism in the gene encoding x-ray repair cross complementing 1 (XRCC1) protein and the risk of female reproductive system cancer, but results are inconclusive. To gain a comprehensive picture of available evidence, we searched for relevant studies in the PubMed, EMBASE, Scopus, and Chinese National Knowledge Infrastructure databases up to December 17, 2016. A total of 26 case-control studies were picked out. The pooled odds ratio (OR) with its 95% confidence interval (CI) was calculated to estimate the association. Based on data of all study participants, we did not find a positive association of rs25487 or rs1799782 polymorphism with risk of female reproductive cancer risk. Subgroup analysis, however, identified two alleles as being associated with an increased risk of female reproductive system cancer in Asians: the A allele of rs25487 (heterozygous genetic model, OR 1.16, 95%CI 1.00–1.36), and the T allele of rs1799782 (homozygous model, OR 2.30, 95%CI 1.39–3.82; dominant model, OR 1.28, 95%CI 1.10–1.50; recessive model, OR 2.11, 95%CI 1.33–3.34). Moreover, the AA genotype at rs25489 was determined to be a risk factor for cervical cancer etiology (homozygous model, OR 2.91, 95%CI, 1.17–7.26; recessive model, OR 3.16, 95%CI 1.91–5.24). This meta-analysis suggests that no association between rs25487 or rs1799782 gene polymorphism and risk of female reproductive cancer risk was found. These results should be validated in larger studies.
Droplet-Assisted Laser Direct Nanoscale Writing on Silicon

Nano-structuring using laser direct writing technology has shown great potential for industrial applications. A novel application of water droplets to this technology is proposed in this paper. With a hydrophobic layer and a controlled substrate temperature, a layer of randomly distributed water droplets with a high contact angle is formed on the substrate. These liquid droplets can be used as lenses to enhance the laser intensity at the bottom of the droplets. As a result, nanoscale holes can be fabricated on the substrate by controlling the laser energy density. We successfully fabricated holes with a diameter of 600 nm at a substrate temperature of 12 ∘C and a power density of 1.2 × 108 W/cm2 in our experiments. We also found that the hole diameter was around a ninth of the water droplet diameter. Meanwhile, the machined holes are not affected much by the focal length of the lens, but a hole with less than 100 nm in diameter at the center was observed.
In situ and in vitro evaluation of crude protein degradation and utilisable crude protein content of barley, rye and triticale grains for ruminants

Rations for dairy cows are comprised of high proportions of cereal grains. Thus, despite their low crude protein (CP) content, grains can contribute considerably to the CP intake of dairy cows. This study was conducted to describe and compare ruminal CP degradation of a broad range of barley, rye and triticale genotypes in situ and in vitro and different methods to estimate the utilisable CP at the duodenum (uCP). Twenty samples each of rye, barley and triticale were incubated in situ and in vitro. Exponential regression analyses were used to estimate in situ degradation parameters. Further, the effective degradability (ED), ruminal undegraded CP (UDP) and uCP for ruminal passage rates of 5% and 8% per hr were estimated. The uCP was estimated in vitro and based on two different approaches using in situ UDP data and estimates of microbial synthesised protein (based on fermented organic matter [fOM] or equations of the Gesellschaft für Ernährungsphysiologie). The degradation rate declined from rye (43% per hr) to triticale (27% per hr) to barley (20% per hr), and it exhibited remarkable variation between the genotypes of a single species. The maximal degradable CP fraction also differed between the species, but was overall very high (94%-99%). The lowest washout fraction (26%) and the highest variation in ED (77%-86% and 69%-80% for a passage rate of 5% and 8% per hr, respectively) were found in barley. The in situ uCP content (estimated using fOM) was lower for barley than for rye and triticale at ruminal passage rates of 5% and 8% per hr (barley: 157 g/kg DM at both passage rates; rye and triticale: 168 (at 5% per hr) and 169 (at 8% per hr) g/kg DM). In vitro estimations of uCP did not differ between the grain species and uCP estimated according to GfE was higher for triticale than for barley and rye, which did not differ. The low variation within a single grain species and the weak correlations between ruminal CP degradation and nutrient concentrations suggested that differentiation of ED and uCP between the genotypes of a single grain species is not necessary.
A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life

Motivation: The aim of this study is to assess the performance of RNA‐RNA interaction prediction tools for all domains of life. Results: Minimum free energy (MFE) and alignment methods constitute most of the current RNA interaction prediction algorithms. The MFE tools that include accessibility (i.e. RNAup, IntaRNA and RNAplex) to the final predicted binding energy have better true positive rates (TPRs) with a high positive predictive values (PPVs) in all datasets than other methods. They can also differentiate almost half of the native interactions from background. The algorithms that include effects of internal binding energies to their model and alignment methods seem to have high TPR but relatively low associated PPV compared to accessibility based methods. Availability and Implementation: We shared our wrapper scripts and datasets at Github (github.com/UCanCompBio/RNA_Interactions_Benchmark). All parameters are documented for personal use. Contact: sinan.umu@pg.canterbury. ac.nz Supplementary information: Supplementary data are available at Bioinformatics online.