Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Response of a Gene Network to Environmental Changes by Fitness-Induced Attractor Selection

Cells switch between various stable genetic programs (attractors) to accommodate environmental conditions. Signal transduction machineries efficiently convey environmental changes to the gene regulation apparatus in order to express the appropriate genetic program. However, since the number of environmental conditions is much larger than that of available genetic programs so that the cell may utilize the same genetic program for a large set of conditions, it may not have evolved a signaling pathway for every environmental condition, notably those that are rarely encountered. Here we show that in the absence of signal transduction, switching to the appropriate attractor state expressing the genes that afford adaptation to the external condition can occur. In a synthetic bistable gene switch in Escherichia coli in which mutually inhibitory operons govern the expression of two genes required in two alternative nutritional environments, cells reliably selected the “adaptive attractor” driven by gene expression noise. A mathematical model suggests that the “non-adaptive attractor” is avoided because in unfavorable conditions, cellular activity is lower, which suppresses mRNA metabolism, leading to larger fluctuations in gene expression. This, in turn, renders the non-adaptive state less stable. Although attractor selection is not as efficient as signal transduction via a dedicated cascade, it is simple and robust, and may represent a primordial mechanism for adaptive responses that preceded the evolution of signaling cascades for the frequently encountered environmental changes.
Distributed adaptive time-varying formation tracking for linear multi-agent systems: A dynamic output approach

In this paper, fully distributed time-varying formation tracking problem for general linear time-invariant (LTI) multi-agent systems is investigated by using an adaptive-based approach. The communication topology is a spanning tree in which a leader's output is available to only a subset of the agents (followers) among which the communication is undirected. The followers can form a time-varying formation that is specified by predefined time-varying vectors and at the same time track the leader's trajectory that is also time-varying. A new class of fully distributed observer-type protocol based on each follower's relative output measurements of neighboring agents is proposed, which does not need the absolute or relative state information that is required in some observer-type protocols. Compared with the existing works, one main contribution of this paper is that the proposed protocol is fully distributed which requires no global information of communication topology and is based on output measurements. Finally, a simulation is provided to verify the effectiveness of the theoretical results.
Ontology-based deep learning for human behavior prediction in health social networks

Human behavior prediction is a key component to studying the spread of wellness and healthy behavior in a social network. In this paper, we introduce an ontology-based Restricted Boltzmann Machine (ORBM) model for human behavior prediction in health social networks. We first propose a bottom-up algorithm to learn the user representation from ontologies. Then the user representation is used to incorporate self-motivation, social influences, and environmental events together in a human behavior prediction model, which extends a well-known deep learning method, Restricted Boltzmann Machines (RBMs), so that the interactions among the behavior determinants are naturally simulated through parameters. To our best knowledge, the ORBM model is the first ontology-based deep learning approach in health informatics for human behavior prediction. Experiments conducted on both real and synthetic data from health social networks have shown the tremendous effectiveness of our approach compared with conventional methods.
Mutations and polymorphisms in the bile salt export pump and the multidrug resistance protein 3 associated with drug-induced liver injury

Objectives Increasing evidence suggests that a genetically determined functional impairment of the hepatocellular efflux transporters bile salt export pump (BSEP, ABCB11) and multidrug resistance protein 3 (MDR3, ABCB4) play a pathophysiological role in the development of drug-induced liver injury. The aim of this study was therefore to describe the extent of genetic variability in ABCB11 and ABCB4 in patients with drug-induced liver injury and to in vitro functionally characterize newly detected ABCB11 mutations and polymorphisms. Methods ABCB11 and ABCB4 were sequenced in 23 patients with drug-induced cholestasis and 13 patients with drug-induced hepatocellular injury. Ninety-five healthy Caucasians served as the control group. Reference and mutant BSEP were expressed in Sf9 cells and ATP-dependent transport of [3H]-taurocholate was measured in a rapid filtration assay. Results Four highly conserved nonsynonymous mutations were specific for drug-induced liver injury [ABCB11: D676Y (drug-induced cholestasis) and G855R (drug-induced cholestasis); ABCB4: I764L (drug-induced cholestasis) and L1082Q (drug-induced hepatocellular injury)]. Furthermore, a polymorphism in exon 13 of ABCB11 (V444A), which is associated with decreased hepatic BSEP expression was significantly more frequent in drug-induced cholestasis patients than in drug-induced hepatocellular injury patients and healthy controls (76 versus 50 and 59% in drug-induced cholestasis patients, drug-induced hepatocellular injury patients and healthy controls, respectively; P<0.05). The in-vitro transport activity of the V444A and the D676Y BSEP constructs was similar, whereas the G855R mutation was nonfunctional. Conclusion In summary, our data support a role of ABCB11 and ABCB4 mutations and polymorphisms in drug-induced cholestasis. Genotyping of selected patients with acquired cholestasis might help to identify individuals with a genetic predisposition.
Sparse fourier transform in any constant dimension with nearly-optimal sample complexity in sublinear time

We consider the problem of computing a k-sparse approximation to the Fourier transform of a length N signal. Our main result is a randomized algorithm for computing such an approximation (i.e. achieving ℓ2/ℓ2 sparse recovery guarantees using Fourier measurements) using Od(klogNloglogN) samples of the signal in time domain and Od(klogd+3 N) runtime, where d≥ 1 is the dimensionality of the Fourier transform. The sample complexity matches the Ω(klog(N/k)) lower bound for non-adaptive algorithms due to [DIPW] for any k≤ N1−δ for a constant δ>0 up to an O(loglogN) factor. Prior to our work a result with comparable sample complexity klogN logO(1)logN and sublinear runtime was known for the Fourier transform on the line [IKP], but for any dimension d≥ 2 previously known techniques either suffered from a (logN) factor loss in sample complexity or required Ω(N) runtime.
Anthropometric Indicators Predict Metabolic Syndrome Diagnosis in Maintenance Hemodialysis Patients.

BACKGROUND Obesity has been considered the key in metabolic syndrome (MetS) development, and fat accumulation may be responsible for the occurrence of metabolic abnormalities in hemodialysis patients. The use of gold-standard methods to evaluate obesity is limited, and anthropometric measures may be the simplest methods. However, no study has investigated the association between anthropometric indexes and MetS in these patients. Therefore, the aim was to determine which anthropometric indexes had the best association and prediction for MetS in patients undergoing hemodialysis. METHODS Cross-sectional study that included patients older than 18 years, undergoing hemodialysis for at least 3 months. Patients with liver disease and cancer or those receiving corticosteroids or antiretroviral therapy were excluded. Diagnostic criteria from Harmonizing Metabolic Syndrome were used for the diagnosis of MetS. Anthropometric indexes evaluated were body mass index (BMI); percent standard of triceps skinfold thickness and of middle arm muscle circumference; waist circumference (WC); sagittal abdominal diameter; neck circumference; waist-to-hip, waist-to-thigh, and waist-to-height ratios; sagittal index; conicity index; and body fat percentage. RESULTS Ninety-eight patients were included, 54.1% male, and mean age was 57.8 ± 12.9 years. The prevalence of MetS was 74.5%. Individuals with MetS had increased accumulation of abdominal fat and general obesity. Waist-to-height ratio was the variable independently associated with MetS diagnosis (odds ratio, 1.21; 95% confidence interval, 1.09-1.34; P < .01) and that better predicts MetS, followed by WC and BMI (area under the curve of 0.840, 0.836, and 0.798, respectively, P < .01). CONCLUSION Waist-to-height ratio was the best anthropometric predictor of MetS in maintenance hemodialysis patients.
Effects of a vertebrate predator ( Poecillia reticulata ) presence on Ceriodaphnia cornuta ( Cladocera : Crustacea ) in laboratory conditions

Aim: To detect the induction of morphological and populational alterations on Ceriodaphnia cornuta concerning cyclomorphosis and population dynamic parameters as densities, fecundity rates, juveniles percentage, males presence and ephippia presence in the presence of predators; Methods: Two experiments were performed: Experiments with fishes fed on Ceriodaphnia cornuta – Experiment 1 – and “Fish Water” Experiment – Experiment 2; Results: Main results observed include decrease in primiparous length and increase in Ceriodaphnia cornuta fecundity; Conclusions: The presence of vertebrate predators (Poecilia reticulata) influenced the Ceriodaphnia cornuta population dynamics at fecundity levels and primiparous; Due to the short duration of repetitions, it was possible to observe morphological changes and the production of ephippia; Ceriodaphnia cornuta is susceptible to the presence of vertebrate predators at the population dynamics level and not at the morphological plasticity; The changes occur in Ceriodaphnia cornuta, in the presence of vertebrate predators especially in population dynamics; Possibly C. cornuta presents different response behaviors for each kind of predator.
Targets and Mechanisms of Photodynamic Therapy in Lung Cancer Cells: A Brief Overview

Lung cancer remains one of the most common cancer-related causes of death. This type of cancer typically develops over a period of many years, and if detected at an early enough stage can be eliminated by a variety of treatments including photodynamic therapy (PDT). A critical discussion on the clinical applications of PDT in lung cancer is well outside the scope of the present report, which, in turn focuses on mechanistic and other aspects of the photodynamic action at a molecular and cellular level. The knowledge of these issues at pre-clinical levels is necessary to develop, check and adopt appropriate clinical protocols in the future. This report, besides providing general information, includes a brief overview of present experimental PDT and provides some non-exhaustive information on current strategies aimed at further improving the efficacy, especially in regard to lung cancer cells.
A unified model for decomposition of coherent and partially coherent target scattering using polarimetric SARs

The target scattering vector model (TSVM) introduced in [1] is reconsidered for a unified decomposition of coherent and partially coherent target scattering. The model, which is robust under change of antenna polarization basis, permits a unique representation of target coherent scattering in term of five parameters that are target characteristics. The TSVM is integrated in Cloude’s incoherent decomposition method (ICTD) to derive the TSVM-ICTD, which permits a unique and basis invariant decomposition of natural extended target scattering. It is shown that both phase and magnitude of the complex scattering type should be used for an unambiguous description of symmetric scattering type. The use of the TSVM helicity angle is important for the characterization of the symmetric nature of target scattering. This parameter permits solving for certain scattering type ambiguities that might occur with Cloude α parameter with targets of non-symmetric scattering. Speckle effect on the TSVM parameter estimation is also discussed. It is shown that the TSVM parameters, and in particular the symmetric scattering type, can be significantly biased. The statistics of the coherence are used to determine the minimum window size required for an unbiased estimation of the TSVM decomposition parameters.
Imaging of skin microvessels with optical coherence tomography: potential uses in port wine stains

The knowledge of vascular structures of port wine stains (PWSs) may be useful to select treatment doses and improve therapeutic efficacy. Biopsies are impractical to implement, therefore, it is necessary to develop non-invasive techniques for morphological evaluation. This study aimed to evaluate the application of a novel optical coherence tomography (OCT) system to characterize the vascular structures of PWSs. First, OCT images were obtained from the skin of healthy rabbit ears and compared with the histopathological images. Second, OCT was used to document the differences between PWS lesions and contralateral normal skin; the size and depth of the vascular structures of two clinical types of PWSs were measured and statistically analyzed. The dermal blood vessels of healthy rabbit ears were clearly distinguished from other tissue. There was no statistical difference between the vascular diameter or depth measured by OCT images and histopathological sections (P>0.05). The OCT images of the PWSs could be distinguished from normal skin. There was no statistical difference in the depth of vessels between the purple-type and the proliferative-type PWSs (P>0.05), while there was statistical difference in the diameter of vessels between them (P<0.01). Therefore, OCT is a promising, real-time, in vivo and non-invasive tool with which to characterize the vascular structures of PWSs.
Cancer Pathway Network Analysis Using Cellular Automata

Identification of cancer pathways is the central goal in the cancer gene expression data analysis. Data mining refers to the process analyzing huge data in order to find useful pattern. Data classification is the process of identifying common properties among a set of objects and grouping them into different classes. A cellular automaton is a discrete, dynamical system with simple uniformly interconnected cells. Cellular automata are used in data mining for reasons such as all decisions are made locally depend on the state of the cell and the states of neighboring cells. A high-speed, low-cost pattern-classifier, built around a sparse network referred to as cellular automata (ca) is implemented. Lif-stimulated gene regulatory network involved in breast cancer has been simulated using cellular automata to obtain biomarker genes. Our model outputs the desired genes among inputs with highest priority, which are analysed for their functional involvement in relevant oncological functional enrichment analysis. This approach is a novel one to discover cancer biomarkers in cellular spaces.
THE FLOW FIELD OF A TWO-BLADED HORIZONTAL AXIS TURBINE VIA COMPARISON OF RANS AND LES SIMULATIONS AGAINST EXPERIMENTAL PIV FLUME MEASUREMENTS

VIA COMPARISON OF RANS AND LES SIMULATIONS AGAINST EXPERIMENTAL PIV FLUME MEASUREMENTS Danny Sale1, Alberto Aliseda University of Washington Dept. of Mechanical Engineering Seattle, WA, U.S.A. 1corresponding author: dsale@uw.edu ABSTRACT Experiments and numerical simulations are conducted for an array of axial-flow Marine Hydro-Kinetic (MHK) turbines operating in a flume. This study aims to understand the influence of coherent structures in high Reynolds number wakes on energy extraction and dynamical rotor control processes. In the flume experiments, rotor torque and rotational position measurements are collected, and the flow field is characterized by simultaneous imaging with particle image velocimetry. The performance of 3 turbines are characterized under varying stream-wise spacing and cross-stream offsets. To study the effect of unsteady hydrodynamics, the turbines are outfitted with either open-loop or close-loop feedback rotor-speed controller. In the numerical simulations, turbine models within the class of "actuator methods" are included from LargeEddy-Simulations and Reynolds-Averaged-NavierStokes methods, where these turbine models impose body forces upon the flow field in form of disks or lines.
Propagation of Electrical Trees under the Influence of Mechanical Stresses: A Short Review

The present paper deals with the phenomenon of electrical treeing in solid insulation, under the influence of mechanical stresses. In this short review, it is indicated that mechanical stressing can affect the propagation of electrical trees and –depending on whether it is tensile or compressive- it can facilitate (or render more difficult) the breakdown. In aged insulating materials, electrical trees can appear very quickly and can lead to breakdown.
Three-dimensional periodic materials as seismic base isolator for nuclear infrastructure

Recent advance of periodic materials from the field of solid-state physics into that of earthquake engineering has resulted in a novel seismic isolation technique. In this study, we developed a new configuration of structural foundation using a three-dimensional (3D) periodic material for seismic isolation of critical infrastructure, particularly nuclear infrastructure. To this aim, we first performed analytical and finite element studies to compare two different types of 3D unit cells, i.e., Bragg Scattering and Locally resonant unit cells, to investigate their characteristics and applicability as a seismic isolator. We then designed a large scale test specimen based on the Bragg-scattering type unit cell using common construction materials: reinforced concrete blocks and polyurethane sheets. The designed test specimen was constructed and tested using a shake table subjected to different types of excitations in the horizontal and vertical directions as well as the torsional mode. The dynamic response of a small modular reactor (SMR) building model protected by the 3D periodic foundation demonstrates that 90% response reduction was achieved within the frequency band gaps. The response attenuation was achieved in all three tested directions. Moreover, the periodic foundation-isolated SMR building exhibited a stable response with negligible rocking on the structural system.
Biofilm Structure of Foodborne Pathogens

The ability of many bacteria to adhere to surfaces and to form biofilms has major implications in a variety of industries including the food industry, where biofilms create a persistent source of contamination. It is reported that biofilms are more resistant to antimicrobials compared to planktonic cells. The colonization of bacteria on the food processing surfaces and even the food structure, such as milk molecules, and thus the formation of biofilms has become a major concern for food plants.
Algorithm to automatically solve security policy conflicts among IP devices configurations

One of the most critical aspects of security problems is the impossibility of accurately checking a system real weaknesses. In a complex and distributed environment this problem is greatly accentuated. During the process of configuration and implementation of the network security policies errors can occur, resulting in holes in security and, consequently, compromising the entire system functionality. These errors are often very hard to detect by performing a manual or visual inspection. For this reason, automatic management of this phase is required. Here we propose an algorithm to automatically tune up the configurations of the network devices in order to avoid unexpected and unwanted network behaviours. This algorithm will be described in all its phases and some results of the software implementation will be shown.
Real-time quantitative polymerase chain reaction for virus infection diagnostics.

BACKGROUND The development of real-time quantitative polymerase chain reaction (real-time qPCR) technology for the quantification and detection of the target genome with high sensitivity offers great advantages for the diagnosis of infectious diseases. This technique has become widely used for the diagnosis and assessment of viral infectious diseases. OBJECTIVES The aim of this review is to describe the technologies of real-time qPCR that have been developed recently, applications of the real-time qPCR on virus infectious diseases, and to discuss the circumstances of real-time qPCR in the area of virus infectious diseases. CONCLUSION The possibility of false-positive and false-negative results always exists when performing real-time qPCR. Reducing these risks is important. The use of real-time qPCR in the field of diagnostics for viral infections is likely to increase. The standard of performance of real-time qPCR in each institute needs to be maintained, thus requiring the establishment of a framework for the standardization of assay quality among the laboratories responsible for the diagnosis of infectious diseases.
Expanding the Scope and Impact of Collaborative Planning

Problem: As planners grow increasingly confident that they have settled on the right concepts and methods to conduct stakeholder-based collaboration, they are not considering what can be achieved through other collaborative approaches. Purpose: We aimed to explore how creating a network of place- and stakeholder-based collaboratives using communities of practice could strengthen individual collaboratives and achieve network synergies. Methods: Using a case study approach, we draw out lessons for collaborative planning from our research on the U.S. Fire Learning Network (FLN), a collaborative initiative to restore ecosystems that depend on fire. We analyzed data from over 140 interviews, hundreds of documents including restoration plans, newsletters, meeting summaries, maps, and various other reports, and observations at more than a dozen regional and national meetings. Results and conclusions: We conclude that the FLN nurtures expertise in ecological fire restoration and collaborative planning by linking multi-stakeholder collaboratives to regional communities of practice. Moreover, this linkage creates and sustains a network of collaboratives that amplify the potential for fundamental change in the culture and practice of fire management. Takeaway for practice: A community of practice is an effective approach to collaboration in situations where the purpose is to expand expertise rather than to resolve conflict and reach consensus. Moreover, a community of practice can link stakeholder-based collaboratives to create a whole greater than the sum of its parts. Realizing this potential requires questioning the universality of some of the core principles of stakeholder-based collaborative planning and diversifying the collaborative planning toolkit. Research support: This research was supported by the Northern Research Station of the U. S. Forest Service and The Nature Conservancy.