Miracle-dz/UniFAR-FTUs huggingface dataset:
The potential effect of microbiota in predicting the freshness of chilled chicken

ABSTRACT 1. The goals of this study were to analyse the changes in microbiota composition of chilled chicken during storage and identify microbial biomarkers related to meat freshness. 2. The study used 16S rDNA sequencing to track the microbiota shift in chilled chicken during storage. Associations between microbiota composition and storage time were analysed and microbial biomarkers were identified. 3. The results showed that microbial diversity of chilled chicken decreased with the storage time. A total of 27 and 24 microbial biomarkers were identified by using orthogonal partial least squares (OPLS) and the random forest regression approach, respectively. The receiver operating characteristic (ROC) curve analysis indicated that the OPLS regression approach had better performance in identifying freshness-related biomarkers. The multiple stepwise regression analysis identified four key microbial biomarkers, including Streptococcus, Carnobacterium, Serratia and Photobacterium genera and constructed a predictive model. 4. The study provided microbial biomarkers and a model related to the freshness of chilled chicken. These findings provide a basis for developing detection methods of the freshness of chilled chicken.
Effects of fecal microbiota transplant on DNA methylation in subjects with metabolic syndrome

ABSTRACT Accumulating evidence shows that microbes with their theater of activity residing within the human intestinal tract (i.e., the gut microbiome) influence host metabolism. Some of the strongest results come from recent fecal microbial transplant (FMT) studies that relate changes in intestinal microbiota to various markers of metabolism as well as the pathophysiology of insulin resistance. Despite these developments, there is still a limited understanding of the multitude of effects associated with FMT on the general physiology of the host, beyond changes in gut microbiome composition. We examined the effect of either allogenic (lean donor) or autologous FMTs on the gut microbiome, plasma metabolome, and epigenomic (DNA methylation) reprogramming in peripheral blood mononuclear cells in individuals with metabolic syndrome measured at baseline (pre-FMT) and after 6 weeks (post-FMT). Insulin sensitivity was determined with a stable isotope-based 2 step hyperinsulinemic clamp and multivariate machine learning methodology was used to uncover discriminative microbes, metabolites, and DNA methylation loci. A larger gut microbiota shift was associated with an allogenic than with autologous FMT. Furthemore, the data results of the the allogenic FMT group data indicates that the introduction of new species can potentially modulate the plasma metabolome and (as a result) the epigenome. Most notably, the introduction of Prevotella ASVs directly correlated with methylation of AFAP1, a gene involved in mitochondrial function, insulin sensitivity, and peripheral insulin resistance (Rd, rate of glucose disappearance). FMT was found to have notable effects on the gut microbiome but also on the host plasma metabolome and the epigenome of immune cells providing new avenues of inquiry in the context of metabolic syndrome treatment for the manipulation of host physiology to achieve improved insulin sensitivity.
Modeling Nitrate-Nitrogen Losses in Response to Tile Drain Depth and Spacing in a Cold Climate

The Agricultural Drainage and Pesticide Transport (ADAPT) model was used to evaluate the effects of tile drain spacing and depth on NO3-N losses in southeastern Minnesota. The model was calibrated and validated using 4 years of monthly flow and nitrate loss data from two tile drained fields (11 and 9.3 ha) in Nicollet County. Half the monitoring data from the 11 ha field were used for calibration and half for validation of the model. The model was also validated using independent monitoring data from the 9.3 ha field. For the calibration period on the 11 ha field, the model predicted mean monthly tile drainage and NO3-N losses of 141.5 m3/day and 5.2 kg/ha, respectively, against measured tile drainage (126.2 m3/day) and NO3-N losses (4.5 kg/ha). For validation, the predicted mean monthly tile drainage and NO3-N losses were 131.7 m3/day and 4.4 kg/ha, respectively, against measured tile drainage and NO3-N losses of 80.4 m3/day and 3.0 kg/ha, respectively. Similar validation results were found with 9.3 ha field. Long-term simulations were made for a wide range of climatic conditions (1954-2003) to evaluate the effects of drain spacing and drain depth on tile drainage and NO3-N losses. Simulations results indicate that increasing spacing and decreasing depth of tile drains reduces the tile drainage and NO3-N losses, and can serve as a remedy to the excess NO3-N losses.
Ahead of Maturation: Enhanced Speech Envelope Training Boosts Rise Time Discrimination in Pre-Readers at Cognitive Risk for Dyslexia

Dyslexia has frequently been related to atypical auditory temporal processing and speech perception. Results of studies emphasizing speech onset cues and reinforcing the temporal structure of the speech envelope, i.e. envelope enhancement, demonstrated reduced speech perception deficits in individuals with dyslexia. The use of this strategy as an auditory intervention might thus reduce some of the deficits related to dyslexia. Importantly, interventions are most effective when they are provided during kindergarten and first grade. Hence, we provided a tablet-based 12-week preventive auditory and phonics-based intervention to pre-readers at cognitive risk for dyslexia and investigated the effect on auditory temporal processing with a rise time discrimination task. Ninety-one pre-readers at cognitive risk for dyslexia (aged 5-6) were assigned to two groups receiving a phonics-based intervention and playing a story listening game either with (n = 31) or without (n = 31) envelope enhancement or a third group playing control games and listening to non-enhanced stories (n = 29). Rise time discrimination was measured directly before, directly after and one year after the intervention. While the groups listening to non-enhanced stories mainly improved after the intervention during first grade, the group listening to enhanced stories improved during the intervention in kindergarten and subsequently remained stable during first grade. Hence, an envelope enhancement intervention improves auditory processing skills important for the development of phonological skills. This occurred before the onset of reading instruction, preceding the maturational improvement of these skills, hence giving at risk children a head start when learning to read. Research highlights The first investigation of speech envelope enhancement as a potential preventive intervention strategy in pre-readers at cognitive risk for dyslexia Speech envelope enhancement increases the rise time sensitivity of children at cognitive risk for dyslexia Rise time discrimination can be enhanced before formal reading instruction, a crucial period in development
High concentration of oxaliplatin may be a risk factor for vascular pain

Oxaliplatin (L‐OHP) is an antineoplastic agent that frequently causes vascular pain. However, the risk factors for vascular pain are unclear, and prevention methods have not been established. We retrospectively investigated patients who were treated with L‐OHP to examine the influence of patient characteristics and concomitant analgesic use on the incidence of vascular pain.
Real Estate Concepts: A Handbook

The essential reference tool for all real estate, property, planning and construction students. Real Estate Concepts provides built environment students with an easy to use guide to the essential concepts they need to understand in order to succeed in their university courses and future professional careers. Key concepts are arranged, defined and explained by experts in the field to provide the student with a quick and reliable reference throughout their university studies. The subjects are conveniently divided to reflect the key modules studied in most property, real estate, planning and construction courses
The cost-effectiveness of sexual and reproductive health and rights interventions in low- and middle-income countries: a scoping review

Abstract Sexual and reproductive health and rights (SRHR) are an essential component of universal health coverage (UHC). In determining which SRHR interventions to include in their UHC benefits package, countries are advised to evaluate each service based on robust and reliable data, including cost-effectiveness data. We conducted a scoping review of full economic evaluations of the essential SRHR interventions included in the comprehensive package presented by the Guttmacher-Lancet Commission on SRHR. Of the 462 economic evaluations that met the inclusion criteria, the quantity of publications varied across regions, countries, and the components of the SRHR package, with the majority of publications reporting on HIV/AIDS, reproductive cancer, as well as antenatal care, childbirth, and postnatal care. Systematic reviews are needed for these components in support of more conclusive findings and actionable recommendations for programmes and policy. Further evaluations for interventions included in the remaining components are needed to provide a stronger evidence base for decision-making. The economic evaluations reviewed for this article were inherently varied in their applied methodologies, SRHR interventions and comparators, cost and effectiveness data, and cost-effectiveness thresholds, among others. Despite these differences, the vast majority of publications reported the evaluated SRHR interventions to be cost-effective.
An insight into the role of liposomal therapeutics in the reversion of multiple sclerosis

ABSTRACT Introduction Multiple Sclerosis (MS), as an autoimmune disease, has complicated immunopathology, which makes its management relevant to various factors. Novel pharmaceutical vehicles, especially liposomes, can support efficacious handling of this disease both in early detection and prognosis and also in a therapeutic manner. The most well-known triggers of MS onset are the predominance of cellular to humoral immunity and enhancement of inflammatory cytokines level. The installation of liposomes as nanoparticles to control this disease holds great promise up to now. Areas covered Various types of liposomes with different properties and purposes have been formulated and targeted immune cells with their surface manipulations. They may be encapsulated with anti-inflammatory, MS-related therapeutics, or immunodominant myelin-specific peptides for attaining a higher therapeutic efficacy of the drugs or tolerance induction. Cationic liposomes are also highly applicable for gene delivery of the anti-inflammatory cytokines or silencing the inflammatory cytokines. Liposomes have also been used as biotools for comprehending MS pathomechanisms or as diagnostic agents. Expert opinion The efforts to manage MS through nanomedicine, especially liposomal therapeutics, pave a new avenue to a high-throughput medication of this autoimmune disease and their translation to the clinic in the future for overcoming the challenges that MS patients confront.
Ring Size Determines the Conformation, Global Aromaticity and Photophysical Properties of Macrocyclic Oligofurans.

In π-conjugated macrocycles, there is a trade-off between the global and local expression of effects such as aromaticity, with the outcome of the trade-off determined by the geometry and aromaticity of the constituent units. Compared with other aromatic rings, furan aromaticity is relatively low, and therefore global effects in macrocyclic furans are expected to be more pronounced. Following our introduction of macrocyclic oligofuran, we present the first synthesis of a series of π-conjugated bifuran macrocycles of various ring sizes, from trimer to hexamer, and characterize them using both computational and experimental methods. The properties of macrocyclic oligofurans change considerably with size: The smaller trimer is rigid, non-emissive and planar as revealed by its single crystal structure, and displays global antiaromaticity, while the larger pentamer and hexamer are flexible, emissive, have non-planar structures, and exhibit local aromaticity. The results are supported by NICS and ACID calculations that indicate the global antiaromaticity of planar furan macrocycles, and by transient absorption measurements showing sharp absorption bands for the trimer and only the internal conversion decay pathway.
Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the Microvasculature

Supplemental Digital Content is available in the text. Background: The microvasculature, the smallest blood vessels in the body, has key roles in maintenance of organ health and tumorigenesis. The retinal fundus is a window for human in vivo noninvasive assessment of the microvasculature. Large-scale complementary machine learning-based assessment of the retinal vasculature with phenome-wide and genome-wide analyses may yield new insights into human health and disease. Methods: We used 97 895 retinal fundus images from 54 813 UK Biobank participants. Using convolutional neural networks to segment the retinal microvasculature, we calculated vascular density and fractal dimension as a measure of vascular branching complexity. We associated these indices with 1866 incident International Classification of Diseases–based conditions (median 10-year follow-up) and 88 quantitative traits, adjusting for age, sex, smoking status, and ethnicity. Results: Low retinal vascular fractal dimension and density were significantly associated with higher risks for incident mortality, hypertension, congestive heart failure, renal failure, type 2 diabetes, sleep apnea, anemia, and multiple ocular conditions, as well as corresponding quantitative traits. Genome-wide association of vascular fractal dimension and density identified 7 and 13 novel loci, respectively, that were enriched for pathways linked to angiogenesis (eg, vascular endothelial growth factor, platelet-derived growth factor receptor, angiopoietin, and WNT signaling pathways) and inflammation (eg, interleukin, cytokine signaling). Conclusions: Our results indicate that the retinal vasculature may serve as a biomarker for future cardiometabolic and ocular disease and provide insights into genes and biological pathways influencing microvascular indices. Moreover, such a framework highlights how deep learning of images can quantify an interpretable phenotype for integration with electronic health record, biomarker, and genetic data to inform risk prediction and risk modification.
Virtual reality in post-stroke neurorehabilitation – a systematic review and meta-analysis

ABSTRACT Background Stroke is a neurological disorder and one of the leading causes of disability worldwide. The patient may lose the ability to adequately move the extremities, perceive sensations, or ambulate independently. Recent experimental studies have reported the beneficial influence of virtual reality training strategies on improving overall functional abilities for stroke survivors. Methods Conducted a systematic review of the literature using the following keywords to retrieve the data: stroke, virtual reality, motor deficits, neurorehabilitation, cognitive impairments, and sensory deficits. A random-effect meta-analysis was performed for seven scales – one cognitive (MMSE) and six motor (Fugl-Meyer, Berg Balance Scale, Time up and go, Wolf motor function, 10 m walk, Brunnstrom score) Objective To organize and compare all the available data regarding the effectiveness of virtual reality for stroke rehabilitation Results This literature reviewed 150 studies and included 46 for qualitative and 27 for quantitative analysis. There was no statistically significant difference between groups in MMSE score (MD = 0.24, 95%CI = ((−0.42) -(0.9)), p = . 47, I2 = 0%) and Fugl-Meyer score (MD = (−0.38), 95%CI = ((−12.88)-(12.11)), p = . 95, I2 = 98%) . The statistical significance was not reached in any of the other outcomes. Conclusions This review supports that stroke rehabilitation programs incorporating virtual reality are associated with improved functional outcomes, but there is no statistically significant difference compared to standard therapy.
Generalized Backward doubly SDEs driven by L\'evy processes with discontinuous and linear growth coefficients

This paper deals with generalized backward doubly stochastic differential equations driven by a Lévy process (GBDSDEL, in short). Under left or right continuous and linear growth conditions, we prove the existence of minimal (resp. maximal) solutions. MSC:Primary: 60F05, 60H15; Secondary: 60J30
Learning equilibria with personalized incentives in a class of nonmonotone games

We consider quadratic, nonmonotone generalized Nash equilibrium problems with symmetric interactions among the agents. Albeit this class of games is known to admit a potential function, its formal expression can be unavailable in several real-world applications. For this reason, we propose a two-layer Nash equilibrium seeking scheme in which a central coordinator exploits noisy feedback from the agents to design personalized incentives for them. By making use of those incentives, the agents compute a solution to an extended game, and then return feedback measures to the coordinator. We show that our algorithm returns an equilibrium if the coordinator is endowed with standard learning policies, and corroborate our results on a numerical instance of a hypomonotone game.
Approximation methods for control of acoustic/structure models with piezoceramic actuators

Abstract : The active control of acoustic pressure in a two dimensional cavity with a flexible boundary (a beam) is considered. Specifically, this control is implemented via piezoceramic patches on the beam which produce pure bending moments. The incorporation of the feedback control in this manner leads to a system with an unbounded input term. Approximation methods in the context of a Linear Quadratic Regulator state space formulation are discussed and numerical results demonstrating the effectiveness of this approach in computing feedback controls for noise reduction are presented.
Interstellar Extinction and Elemental Abundances: Individual Sight Lines

While it is well recognized that both the Galactic interstellar extinction curves and the gas-phase abundances of dust-forming elements exhibit considerable variations from one sight line to another, as yet most of the dust extinction modeling efforts have been directed to the Galactic average extinction curve, which is obtained by averaging over many clouds of different gas and dust properties. Therefore, any details concerning the relationship between the dust properties and the interstellar environments are lost. Here we utilize the wealth of extinction and elemental abundance data obtained by space telescopes and explore the dust properties of a large number of individual sight lines. We model the observed extinction curve of each sight line and derive the abundances of the major dust-forming elements (i.e., C, O, Si, Mg, and Fe) required to be tied up in dust (i.e., dust depletion). We then confront the derived dust depletions with the observed gas-phase abundances of these elements and investigate the environmental effects on the dust properties and elemental depletions. It is found that for the majority of the sight lines the interstellar oxygen atoms are fully accommodated by gas and dust and therefore there does not appear to be a “missing oxygen” problem. For those sight lines with an extinction-to-hydrogen column density A V /N H ≳ 4.8 × 10−22 mag cm2 H−1 there are shortages of C, Si, Mg, and Fe elements for making dust to account for the observed extinction, even if the interstellar C/H, Si/H, Mg/H, and Fe/H abundances are assumed to be protosolar abundances augmented by Galactic chemical evolution.
A new differential stacked spiral inductor with improved self‐resonance frequency

A new silicon‐based differential stacked spiral inductor (DSSI) was implemented using a standard 0.18‐μm complimentary metal‐oxide semiconductor technology. Based on the measured two‐port S‐parameter using a standard de‐embedding procedure, the self‐resonance frequency, fsr, and quality factor, Q, of the new DSSI were compared with a conventional DSSI. The fsr of the new DSSI was nearly twice as high as that of the conventional DSSI, and the Q value of the new DSSI was also enhanced. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:1024–1026, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.25900
Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems

We consider the problem of controlling a Linear Quadratic Regulator (LQR) system over a finite horizon T with fixed and known cost matrices Q,R, but unknown and non-stationary dynamics A_t, B_t. The sequence of dynamics matrices can be arbitrary, but with a total variation, V_T, assumed to be o(T) and unknown to the controller. Under the assumption that a sequence of stabilizing, but potentially sub-optimal controllers is available for all t, we present an algorithm that achieves the optimal dynamic regret of O(V_T^2/5 T^3/5 ). With piecewise constant dynamics, our algorithm achieves the optimal regret of O(sqrtST ) where S is the number of switches. The crux of our algorithm is an adaptive non-stationarity detection strategy, which builds on an approach recently developed for contextual Multi-armed Bandit problems. We also argue that non-adaptive forgetting (e.g., restarting or using sliding window learning with a static window size) may not be regret optimal for the LQR problem, even when the window size is optimally tuned with the knowledge of $V_T$. The main technical challenge in the analysis of our algorithm is to prove that the ordinary least squares (OLS) estimator has a small bias when the parameter to be estimated is non-stationary. Our analysis also highlights that the key motif driving the regret is that the LQR problem is in spirit a bandit problem with linear feedback and locally quadratic cost. This motif is more universal than the LQR problem itself, and therefore we believe our results should find wider application.
Multi-Scale Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition

Skeleton data is of low dimension. However, there is a trend of using very deep and complicated feedforward neural networks to model the skeleton sequence without considering the complexity in recent year. In this paper, a simple yet effective multi-scale semantics-guided neural network (MS-SGN) is proposed for skeleton-based action recognition. We explicitly introduce the high level semantics of joints (joint type and frame index) into the network to enhance the feature representation capability of joints. Moreover, a multi-scale strategy is proposed to be robust to the temporal scale variations. In addition, we exploit the relationship of joints hierarchically through two modules, i.e., a joint-level module for modeling the correlations of joints in the same frame and a frame-level module for modeling the temporal dependencies of frames. With an order of magnitude smaller model size than most previous methods, MSSGN achieves the state-of-the-art performance on the NTU60, NTU120, and SYSU datasets.