Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum Supremacy Is Both Closer and Farther than It Appears

As quantum computers improve in the number of qubits and fidelity, the question of when they surpass state-of-the-art classical computation for a well-defined computational task is attracting much attention. The leading candidate task for this milestone entails sampling from the output distribution defined by a random quantum circuit. We develop a massively-parallel simulation tool Rollright that does not require inter-process communication (IPC) or proprietary hardware. We also develop two ways to trade circuit fidelity for computational speedups, so as to match the fidelity of a given quantum computer --- a task previously thought impossible. We report massive speedups for the sampling task over prior software from Microsoft, IBM, Alibaba and Google, as well as supercomputer and GPU-based simulations. By using publicly available Google Cloud Computing, we price such simulations and enable comparisons by total cost across hardware platforms. We simulate approximate sampling from the output of a circuit with 7x8 qubits and depth 1+40+1 by producing one million bitstring probabilities with fidelity 0.5%, at an estimated cost of $35184. The simulation costs scale linearly with fidelity, and using this scaling we estimate that extending circuit depth to 1+48+1 increases costs to one million dollars. Scaling the simulation to 10M bitstring probabilities needed for sampling 1M bitstrings helps comparing simulation to quantum computers. We describe refinements in benchmarks that slow down leading simulators, halving the circuit depth that can be simulated within the same time.
Olfactory Communication via Microbiota: What Is Known in Birds?

Animal bodies harbour a complex and diverse community of microorganisms and accumulating evidence has revealed that microbes can influence the hosts’ behaviour, for example by altering body odours. Microbial communities produce odorant molecules as metabolic by-products and thereby modulate the biochemical signalling profiles of their animal hosts. As the diversity and the relative abundance of microbial species are influenced by several factors including host-specific factors, environmental factors and social interactions, there are substantial individual variations in the composition of microbial communities. In turn, the variations in microbial communities would consequently affect social and communicative behaviour by influencing recognition cues of the hosts. Therefore, microbiota studies have a great potential to expand our understanding of recognition of conspecifics, group members and kin. In this review, we aim to summarize existing knowledge of the factors influencing the microbial communities and the effect of microbiota on olfactory cue production and social and communicative behaviour. We concentrate on avian taxa, yet we also include recent research performed on non-avian species when necessary.
Solid lipid nanoparticles and nanostructured lipid carriers as novel drug delivery systems: applications, advantages and disadvantages

During the recent years, more attentions have been focused on lipid base drug delivery system to overcome some limitations of conventional formulations. Among these delivery systems solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) are promising delivery systems due to the ease of manufacturing processes, scale up capability, biocompatibility, and also biodegradability of formulation constituents and many other advantages which could be related to specific route of administration or nature of the materials are to be loaded to these delivery systems. The aim of this article is to review the advantages and limitations of these delivery systems based on the route of administration and to emphasis the effectiveness of such formulations.
Relapsed, refractory peripheral T-cell lymphoma not otherwise specified successfully treated with allogeneic haematopoietic stem cell transplantation

Peripheral T-cell lymphoma (PTCL) is a rare haematological malignancy accounting for 3.7% of all lymphomas and 10-15% of all non-Hodgkin lymphomas (NHL) [1,2]. Peripheral T-cell lymphoma not otherwise specified (PTCL, NOS) is the commonest subtype of PTCL. However, its’ prevalence is lower in Asia than in the West [3]. Only 11 cases of T-cell lymphoma, NOS were reported in Sri Lanka in 2010 [4]. However, PTCL, NOS subtype is not mentioned in this report. PTCL, NOS is a highly aggressive lymphoma notorious for chemo-refractoriness and frequent relapses. High-dose chemotherapy with autologous stem cell transplantation is incorporated in to primary therapy for young fit patients but remains ineffective for most and has not been tested in a randomized study [5]. Allogeneic haematopoietic stem cell transplantation (allo-HSCT) may offer a potential cure for these patients though the optimal type and timing of transplantation remain to be defined [6].
Tryptophan, kynurenine, kynurenic acid concentrations and indoleamine 2,3‐dioxygenase activity in serum and milk of dairy cows with subclinical mastitis caused by coagulase‐negative staphylococci

The aim of the study was to investigate serum and milk concentrations of tryptophan (TRP), kynurenine (KYN), kynurenic acid (KYNA), and indoleamine 2,3-dioxygenase (IDO) activity in cows suffering from subclinical mastitis caused by coagulase-negative staphylococci (MSCNS). TRP and kynurenines were determined by high-performance liquid chromatography (HPLC), and IDO activity was calculated as the KYN/TRP ratio. The blood and milk samples were collected from 40 midlactation Holstein-Fresian cows from two herds in the Lublin region in Poland. In the milk samples from 20 cows with subclinical mastitis, coagulase-negative staphylococci were isolated and in the milk obtained from healthy cows growth of microorganisms was not detected. TRP, KYN and KYNA concentrations were significantly lower in milk of cows with MSCNS compared to control animals (4.47 vs. 7.24 µM, 0.14 vs. 0.21 µM, 1.58 vs. 2.18 nM, respectively). There was no statistically significant difference in TRP and KYNA concentrations in serum between the studied animal groups (32.97 vs. 39.29 µM, 31.3 vs. 26.5 nM, respectively). In turn, the level of KYN was lower in the serum (0.81 vs. 1.13 µM) of cows with mastitis compared to healthy ones. No statistically significant differences in IDO activity, both in serum and in milk (25.24 and 27.55, 28.56 and 27.17, respectively) was revealed between the studied groups. These findings may have potential implications for diagnosis of mastitis in cows because reduction of these parameters in milk might be a marker predicting the occurrence of the disease.
An Upper Extremity Risk Assessment Tool Based on Material Fatigue Failure Theory: The Distal Upper Extremity Tool (DUET)

Objective: Musculoskeletal tissues repeatedly loaded in vitro fail in accordance with material fatigue failure theory, and there is evidence to suggest that the same process occurs in vivo. The current paper presents a new upper extremity risk assessment tool, the Distal Upper Extremity Tool (DUET), predicated on material fatigue failure theory. Methods: DUET requires an estimate of force exertion level and the number of repetitions performed to derive estimates of damage and probabilities of experiencing a distal upper extremity outcome. Damage accrued over multiple tasks may be summed to estimate the cumulative damage (CD) accrued over a workday. Validation of this tool was performed using five distal upper extremity (DUE) outcomes (involving medical visits and pain) from an existing epidemiological database involving data from six automotive manufacturing plants. Logistic regression was used to assess the association of the log of the DUET CD measure to DUE outcomes. Results: Results demonstrated that the log of the DUET CD measure was highly associated with all five DUE outcomes in both crude analyses and those adjusted for site, age, gender, and body mass index (p < .01). A model relating the continuous DUET log CD score to the probability of the DUE outcome Injury + Pain Last Year was developed, which demonstrated a significant dose-response relationship. Conclusions: Results suggest that fatigue failure–based risk assessment techniques are highly associated with DUE outcomes and provide support for the notion that an underlying fatigue failure process may be involved in the development of upper extremity musculoskeletal disorders.
Brief Review: Ergospirometry in Patients with Obstructive Sleep Apnea Syndrome

This brief review summarizes the available literature on the intersection of obstructive sleep apnea syndrome (OSAS) and ergospirometry. Ergospirometry provides an assessment of integrative exercise responses involving pulmonary, cardiovascular, neuropsychological, and skeletal muscle systems, which are not adequately reflected through the measurement of individual organ system functions. Sleep disorders, including OSAS, often exacerbate problems in the operation of the autonomic nervous system, heart function, lung mechanics, anxiety, and muscle metabolism. Patients with OSAS have low aerobic capacity due to dysfunction of these systems, which often affect quality of sleep. Further research is necessary to elucidate the precise mechanisms through which ergospirometry can be useful in the assessment and early identification of patients with OSAS.
Clinical impact of molecular techniques for the presurgical diagnosis of differentiated thyroid cancer diagnosis

ABSTRACT Introduction: The gold standard for the presurgical diagnosis of thyroid cancer is fine needle aspiration cytology. In about 30% of cases a final diagnosis is not obtained and surgical treatment is required for diagnostic/therapeutic purposes. To avoid unnecessary thyroidectomies, methods based on molecular markers analysis have been explored over the last 10 years. Areas covered: The present review introduces the limits of the cytological diagnosis of thyroid nodules and describes the molecular techniques for the presurgical diagnosis of these nodules focusing on the use of the Thyroseq-V2 (Rule in) and Afirma (Rule out) tests. Expert commentary: These two types of tests have been clinically applied and validated; however they are still confined to specialized laboratories, either academic or private, and not yet routinely used. The evidence of a positive cost-benefit analysis should encourage to set up molecular pathology laboratories to apply new molecular testing(s). In the meantime, clinical judgment, which must take into consideration several parameters including the age of the patient, the size and number of the nodule(s), the ultrasound pattern and the risk level for malignancy, should guide the decision to operate or to follow up the evolution of the nodule.
Immune response and inflammatory pathway of ulcerative colitis

Abstract Ulcerative colitis (UC) is an idiopathic relapsing inflammatory disease. Although the etiology of UC remains unclear, it could be characterized by inflammation of the intestinal mucosa, starting from the rectum and potentially involving the entire colon. The immune response and inflammatory pathway of UC have shown that tissue damage is driven by dynamic and complexes of cells and cytokines. Various types of cells, including antigen-presenting cells (dendritic cells and macrophages), T helper cells, regulatory T cells, and natural killer T cells, play a crucial role in UC pathogenesis by regulation, suppression, and maintenance of inflammation. Moreover, cytokine networks become an important part due to their signaling function, which is indispensable for cell communication. Pro-inflammatory cytokines [tumor necrosis factor-α, interleukin (IL)-1, IL-6, IL-9, IL-13, and IL-33] play significant roles in upregulation, while anti-inflammatory cytokines (transforming growth factor-β, IL-10, and IL-37) play significant roles in downregulation of disease progression. The pathogenesis of UC consists of immuno-inflammatory pathways related to the multiple components of the intestine, including the epithelial barrier, commensal microflora, antigen recognition, dysregulation of immunological responses, leukocyte recruitment, and genetic factors. The understanding of immuno-inflammatory pathways of UC might lead to the development of a specific therapy and/or a novel treatment that could be more efficient.
Efficient Sequential Learning in Structured and Constrained Environments. (Apprentissage séquentiel efficace dans des environnements structurés avec contraintes)

The main advantage of non-parametric models is that the accuracy of the model (degrees of freedom) adapts to the number of samples. The main drawback is the so-called "curse of kernelization": to learn the model we must first compute a similarity matrix among all samples, which requires quadratic space and time and is unfeasible for large datasets. Nonetheless the underlying effective dimension (effective d.o.f.) of the dataset is often much smaller than its size, and we can replace the dataset with a subset (dictionary) of highly informative samples. Unfortunately, fast data-oblivious selection methods (e.g., uniform sampling) almost always discard useful information, while data-adaptive methods that provably construct an accurate dictionary, such as ridge leverage score (RLS) sampling, have a quadratic time/space cost. In this thesis we introduce a new single-pass streaming RLS sampling approach that sequentially construct the dictionary, where each step compares a new sample only with the current intermediate dictionary and not all past samples. We prove that the size of all intermediate dictionaries scales only with the effective dimension of the dataset, and therefore guarantee a per-step time and space complexity independent from the number of samples. This reduces the overall time required to construct provably accurate dictionaries from quadratic to near-linear, or even logarithmic when parallelized. Finally, for many non-parametric learning problems (e.g., K-PCA, graph SSL, online kernel learning) we we show that we can can use the generated dictionaries to compute approximate solutions in near-linear that are both provably accurate and empirically competitive.
An LC-MS/MS workflow to characterize 16 regio- and stereoisomeric trihydroxyoctadecenoic acids[S]

Trihydroxyoctadecenoic acids (TriHOMEs) are linoleic acid-derived oxylipins with potential physiological relevance in inflammatory processes as well as in maintaining an intact skin barrier. Due to the high number of possible TriHOME isomers with only subtle differences in their physicochemical properties, the stereochemical analysis is challenging and usually involves a series of laborious analytical procedures. We herein report a straightforward analytical workflow that includes reversed-phase ultra-HPLC-MS/MS for rapid quantification of 9,10,13- and 9,12,13-TriHOME diastereomers and a chiral LC-MS method capable of resolving all sixteen 9,10,13-TriHOME and 9,12,13-TriHOME regio- and stereoisomers. We characterized the workflow (accuracy, 98–120%; precision, coefficient of variation ≤6.1%; limit of detection, 90–98 fg on column; linearity, R2 = 0.998) and used it for stereochemical profiling of TriHOMEs in bronchoalveolar lavage fluid (BALF) of individuals with chronic obstructive pulmonary disease (COPD). All TriHOME isomers were increased in the BALF of COPD patients relative to that of smokers (P ≤ 0.06). In both COPD patients and smokers with normal lung function, TriHOMEs with the 13(S) configuration were enantiomerically enriched relative to the corresponding 13(R) isomers, suggesting at least partial enzymatic control of TriHOME synthesis. This method will be useful for understanding the synthetic sources of these compounds and for elucidating disease mechanisms.
Pioneer Factors in Animals and Plants—Colonizing Chromatin for Gene Regulation

Unlike most transcription factors (TF), pioneer TFs have a specialized role in binding closed regions of chromatin and initiating the subsequent opening of these regions. Thus, pioneer TFs are key factors in gene regulation with critical roles in developmental transitions, including organ biogenesis, tissue development, and cellular differentiation. These developmental events involve some major reprogramming of gene expression patterns, specifically the opening and closing of distinct chromatin regions. Here, we discuss how pioneer TFs are identified using biochemical and genome-wide techniques. What is known about pioneer TFs from animals and plants is reviewed, with a focus on the strategies used by pioneer factors in different organisms. Finally, the different molecular mechanisms pioneer factors used are discussed, highlighting the roles that tertiary and quaternary structures play in nucleosome-compatible DNA-binding.
The Effect of Neurotoxin MPTP and Neuroprotector Isatin on the Profile of Ubiquitinated Brain Mitochondrial Proteins

Mitochondria are a crucial target for the actions of neurotoxins, causing symptoms of Parkinson’s disease in various experimental animal models, and also neuroprotectors. There is evidence that mitochondrial dysfunction induced by the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) influences functioning of the ubiquitin-proteasomal system (UPS) responsible for selective proteolytic degradation of proteins from various intracellular compartments (including mitochondria) and neuroprotective effects of certain anti-Parkisonian agents (monoamine oxidase inhibitors) may be associated with their effects on the UPS. In this study, we have investigated the effect of the neurotoxin MPTP and neuroprotector isatin, and their combination on the profile of ubiquitinated brain mitochondrial proteins. The development of movement disorders induced by MPTP administration caused dramatic changes in the profile of ubiquitinated proteins associated with mitochondria. Pretreatment with the neuroprotector isatin decreased manifestations of MPTP-induced Parkinsonism, and had a significant impact on the profile of ubiquitinated mitochondrial proteins (including oxidative modified proteins). Administration of isatin alone to intact mice also influenced the profile of ubiquitinated mitochondrial proteins, and increased the proportion of oxidized proteins carrying the ubiquitination signature. These alterations in the ubiquitination of mitochondrial proteins observed within 2 h after administration of MPTP and isatin obviously reflect immediate short-term biological responses to these treatments.
Corneal Nerve Migration Rate in a Healthy Control Population.

PURPOSE The purpose of this study was to establish an age-dependent normative range and factors affecting the migration rate of the corneal subbasal nerve plexus in a healthy control population. METHODS Corneal nerve migration rate was measured in 60 healthy participants grouped by age: A, aged 20 to 39 years (n = 20); B, 40 to 59 years (n = 20); and C, 60 to 79 years (n = 20). Laser-scanning corneal confocal microscopy was performed on the right eye of all participants at baseline and again after 3 weeks. Fully automated software was used to montage the frames. Distinctive nerve landmarks were manually reidentified between the two montages, and a software program was developed to measure the migration of these landmark points to determine corneal nerve migration rate in micrometers per week (μm/wk). RESULTS The mean ± SD age of all participants in the study was 47.5 ± 15.5 years; 62% of participants were male. The average corneal nerve migration rates of groups A, B, and C were 42.0 ± 14.0, 42.3 ± 15.5, and 42.0 ± 10.8 μm/wk, respectively (P = .99). There was no difference in corneal nerve migration rate between male (41.1 ± 13.5 μm/wk) and female (43.7 ± 13.2 μm/wk) participants (P = .47). There was no significant correlation between age (P = .97), smoking (P = .46), alcohol use (P = .61), and body mass index (P = .49, respectively) with corneal nerve migration rate. However, exercise frequency correlated significantly (P = .04) with corneal nerve migration rate. CONCLUSIONS Corneal nerve migration rate varies in healthy individuals and is not affected by age, sex, or body mass index but is related to physical activity.
SDN/NFV‐enabled performance estimation framework for SFC optimization

Many network function virtualization management and orchestration frameworks have been proposed to offer an agile and automated service deployment with a set of virtual network function (VNF) placement and chaining algorithms. However, once the services are deployed, less attention is paid to the subsequent supervision on their performance which may be affected by the dynamic changing network conditions. In order to guarantee the performance of services, this article designs and presents a service function chain performance estimation framework, which can be used to complement the network function virtualization orchestrators by providing performance estimation and optimization for the already deployed services. In particular, the performance estimation is implemented based on the min‐plus algebra theory, and the optimization is fulfilled by using two VNF migration approaches on the basis of greedy and load balance, respectively. The proposed framework can (1) evaluate and compare existing VNF placement algorithms by statistics on service performance estimation, (2) estimate and optimize the performance of services by using VNF migration approaches, (3) integrate the VNF placement algorithms and VNF migration approaches, thus producing more efficient future solutions. Finally, this article presents an implementation of the proposed framework and evaluates its effectiveness in an experimental environment.
Fast Sketch Segmentation and Labeling With Deep Learning

We present a simple and efficient method based on deep learning to automatically decompose sketched objects into semantically valid parts. We train a deep neural network to transfer existing segmentations and labelings from three-dimensional (3-D) models to freehand sketches without requiring numerous well-annotated sketches as training data. The network takes the binary image of a sketched object as input and produces a corresponding segmentation map with per-pixel labelings as output. A subsequent postprocess procedure with multilabel graph cuts further refines the segmentation and labeling result. We validate our proposed method on two sketch datasets. Experiments show that our method outperforms the state-of-the-art method in terms of segmentation and labeling accuracy and is significantly faster, enabling further integration in interactive drawing systems. We demonstrate the efficiency of our method in a sketch-based modeling application that automatically transforms input sketches into 3-D models by part assembly.
Patterns of vector species richness and species composition as drivers of Chagas disease occurrence in Brazil

ABSTRACT Chagas disease represents one of the major health issue in Latin America. Epidemiological control is focused on disease vectors, so studies on the ecology of triatomine vectors constitute a central strategy. Recently, research at large spatial scale has been produced, and authors commonly rely on the assumption that geographical regions presenting good environmental conditions for most vector species are also those with high risk of infection. In the present work, we provide an explicit evaluation for this assumption. Employing species distribution models and epidemiological data for Chagas disease in Brazilian territory, our results show that species richness is a poor predictor for the observed pattern of Chagas disease occurrence. Species composition proved to be a better predictor. We stress that research on macroecology of infectious diseases should go beyond the analysis of biodiversity patterns and consider human infections as a central part of the focal ecological systems.