Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutational Robustness of Gene Regulatory Networks

Mutational robustness of gene regulatory networks refers to their ability to generate constant biological output upon mutations that change network structure. Such networks contain regulatory interactions (transcription factor – target gene interactions) but often also protein-protein interactions between transcription factors. Using computational modeling, we study factors that influence robustness and we infer several network properties governing it. These include the type of mutation, i.e. whether a regulatory interaction or a protein-protein interaction is mutated, and in the case of mutation of a regulatory interaction, the sign of the interaction (activating vs. repressive). In addition, we analyze the effect of combinations of mutations and we compare networks containing monomeric with those containing dimeric transcription factors. Our results are consistent with available data on biological networks, for example based on evolutionary conservation of network features. As a novel and remarkable property, we predict that networks are more robust against mutations in monomer than in dimer transcription factors, a prediction for which analysis of conservation of DNA binding residues in monomeric vs. dimeric transcription factors provides indirect evidence.
Parts per Million Mass Accuracy on an Orbitrap Mass Spectrometer via Lock Mass Injection into a C-trap*S

Mass accuracy is a key parameter of mass spectrometric performance. TOF instruments can reach low parts per million, and FT-ICR instruments are capable of even greater accuracy provided ion numbers are well controlled. Here we demonstrate sub-ppm mass accuracy on a linear ion trap coupled via a radio frequency-only storage trap (C-trap) to the orbitrap mass spectrometer (LTQ Orbitrap). Prior to acquisition of a spectrum, a background ion originating from ambient air is first transferred to the C-trap. Ions forming the MS or MSn spectrum are then added to this species, and all ions are injected into the orbitrap for analysis. Real time recalibration on the “lock mass” by corrections of mass shift removes mass error associated with calibration of the mass scale. The remaining mass error is mainly due to imperfect peaks caused by weak signals and is addressed by averaging the mass measurement over the LC peak, weighted by signal intensity. For peptide database searches in proteomics, we introduce a variable mass tolerance and achieve average absolute mass deviations of 0.48 ppm (standard deviation 0.38 ppm) and maximal deviations of less than 2 ppm. For tandem mass spectra we demonstrate similarly high mass accuracy and discuss its impact on database searching. High and routine mass accuracy in a compact instrument will dramatically improve certainty of peptide and small molecule identification.
EgoNetCloud: Event-based egocentric dynamic network visualization

Event-based egocentric dynamic networks are an important class of networks widely seen in many domains. In this paper, we present a visual analytics approach for these networks by combining data-driven network simplifications with a novel visualization design - EgoNetCloud. In particular, an integrated data processing pipeline is proposed to prune, compress and filter the networks into smaller but salient abstractions. To accommodate the simplified network into the visual design, we introduce a constrained graph layout algorithm on the dynamic network. Through a real-life case study as well as conversations with the domain expert, we demonstrate the effectiveness of the EgoNetCloud design and system in completing analysis tasks on event-based dynamic networks. The user study comparing EgoNetCloud with a working system on academic search confirms the effectiveness and convenience of our visual analytics based approach.
GRAMPS

We introduce GRAMPS, a programming model that generalizes concepts from modern real-time graphics pipelines by exposing a model of execution containing both fixed-function and application-programmable processing stages that exchange data via queues. GRAMPS allows the number, type, and connectivity of these processing stages to be defined by software, permitting arbitrary processing pipelines or even processing graphs. Applications achieve high performance using GRAMPS by expressing advanced rendering algorithms as custom pipelines, then using the pipeline as a rendering engine. We describe the design of GRAMPS, then evaluate it by implementing three pipelines, that is, Direct3D, a ray tracer, and a hybridization of the two, and running them on emulations of two different GRAMPS implementations: a traditional GPU-like architecture and a CPU-like multicore architecture. In our tests, our GRAMPS schedulers run our pipelines with 500 to 1500KB of queue usage at their peaks.
Gaps in understanding health and engagement with healthcare providers across common long-term conditions: a population survey of health literacy in 29 473 Danish citizens

Objectives To (1) quantify levels of subjective health literacy in people with long-term health conditions (diabetes, cardiovascular disease, chronic obstructive pulmonary disease, musculoskeletal disorders, cancer and mental disorders) and compare these to levels in the general population and (2) examine the association between health literacy, socioeconomic characteristics and comorbidity in each long-term condition group. Design Population-based survey in the Central Denmark Region (n=29 473). Main outcome measures Health literacy was measured using two scales from the Health Literacy Questionnaire (HLQ): (1) Ability to understand health information and (2) Ability to actively engage with healthcare providers. Results People with long-term conditions reported more difficulties than the general population in understanding health information and actively engaging with healthcare providers. Wide variation was found between disease groups, with people with cancer having fewer difficulties and people with mental health disorders having more difficulties in actively engaging with healthcare providers than other long-term condition groups. Having more than one long-term condition was associated with more difficulty in engaging with healthcare providers and understanding health information. People with low levels of education had lower health literacy than people with high levels of education. Conclusions Compared with the general population, people with long-term conditions report more difficulties in understanding health information and engaging with healthcare providers. These two dimensions are critical to the provision of patient-centred healthcare and for optimising health outcomes. More effort should be made to respond to the health literacy needs among individuals with long-term conditions, multiple comorbidities and low education levels, to improve health outcomes and to reduce social inequality in health.
Predicting Qualitative Assessments Using Fuzzy Aggregation

Given the complexity and sophistication of many contemporary software systems, it is often difficult to gauge the effectiveness, maintainability, extensibility, and efficiency of their underlying software components. A strategy to evaluate the qualitative attributes of a system's components is to use software metrics as quantitative predictors. We present a fusion strategy that combines the predicted qualitative assessments from multiple classifiers with the anticipated outcome that the aggregated predictions are superior to any individual classifier prediction. Multiple linear classifiers are presented with different, randomly selected, subsets of software metrics. In this study, the software components are from a sophisticated biomedical data analysis system, while the external reference test is a thorough assessment of both complexity and maintainability, by a software architect, of each system component. The fuzzy integration results are compared against the best individual classifier operating on a software metric subset
Impaired parasympathetic augmentation under relaxation in patients with depression as assessed by a novel non-contact microwave radar system

Abstract In order to conduct objective screening of major depressive disorder (MDD), a chair-based system was developed which measures alteration of parasympathetic activation induced by relaxing audio-visual exposure in a non-contact way using dual compact-radars attached to a chair back. The system determines autonomic activation by calculating low (LF) and high frequency (HF) components of heart rate variability (HRV) before and after relaxation. Forty-one subjects (28 normal subjects, 13 MDD subjects) were exposed to relaxing natural sounds and images for 10 min. In order to determine the possibility of MDD from autonomic alteration induced by relaxing, linear discriminant analysis was conducted using LF and HF before and after relaxation. F-test revealed the significance of derived linear discriminant function (p < 0.001). The Mahalanobis distance and U value were 3.2 and 0.89, respectively. The derived linear discriminant function achieved 85% sensitivity (11 out of 13 MDD patients) and 89% specificity (25 out of 28 normal subjects).
Stochastic Evolution of Rules for Playing Normal Form Games

The evolution of boundedly rational rules for playing normal form games is studied within stationary environments of stochastically changing games. Rules are viewed as algorithms prescribing strategies for the different normal form games that arise. It is shown that many of the folk results of evolutionary game theory typically obtained with a fixed game and fixed strategies carry over to the present case. The results are also related to recent experiments on rules and games.
Prediction of welding distortions and residual stresses in a pipe–flange joint using the finite element technique

This paper presents a comparative study of three- and two-dimensional axisymmetric finite element (FE) analyses of a welded pipe–flange joint for residual stresses and deformations in order to identify their merits or demerits. Sequentially coupled thermal stress analysis is performed to simulate single pass metal inert gas welding. Butt weld geometry with a single ‘V’ for a 100 mm nominal diameter pipe and same sized weld neck type ANSI class #300 flange is used. The heat input is modelled by using the Goldak double ellipsoidal heat source model. Temperature dependent material properties are used and deposition of filler metal is obtained by element birth and death feature. Both thermal and structural FE models are validated with experimental measurements. Residual stresses predicted by two-dimensional model are generally on the higher side and hence more conservative. However, we conclude that the three-dimensional FE model is preferable for the prediction of flange face distortion since it is a vital parameter for flange joint performance.
Coping Strategies Used by Iranian Nurses to Deal With Burnout: A Qualitative Research

Background: Although numerous studies have reported about coping strategies among health care worker throughout the world, but no research-based data are available on the perception of coping strategy among Clinical nurses in the Islamic Republic of Iran. Objective: The aim of the present study was to describe and explore the experiences of Iranian nurses about their coping strategies. Methods: In this study we used a qualitative research approach to explore how Iranian nurses perceive and resolve their burnout at work. Twelve nurses were selected by purposive sampling and in-depth semi structured interviews were conducted. All interviews were tape recorded, transcribed verbatim and then analyzed by means of the conventional qualitative content analysis method. Results: The 5 main themes that evolved from content analysis included “religious responsibility”, “approximation to God”, “spiritual reward”, “Holiness of the job” and “spiritual journey” emerged as the most important among these. Conclusions: The results of this study emphasized that religious or spiritual beliefs give purpose and meaning to nursing interventions, help them tolerate the problems at work, and make nursing care pleasurable. Therefore, although burnout is an important issue in nursing, attending to this dimension of their job is essential and healthcare authorities should pay a special attention to it.
De-noising of auditory brainstem response via diffusion and wavelet transform

Evoked Potentials are event-related activities that occurred as an electrical response from the brain to different sensory stimulations of nervous tissues. In this paper, auditory evoked potentials (AEP) brain responses were collected and examined. The data collection was done twice with three different levels of sound and frequencies. The auditory brain response data were extracted from the noisy original data using the averaging technique and set as a reference signal. We propose new approaches for feature extraction of the auditory brain response using wavelet transforms and diffusion filters algorithms. The wavelet transform has the ability to resolve the data into various levels of decomposition, which facilitate its representation in the frequency and time domain. The diffusion filters, on the other hand enhanced the extracted signals resulting in the noise suppression and thus reducing the error. Performance analysis was done based on signal-to-noise ratio (SNR), mean squared error (MSE) and peak-signal-to-noise ratio (PSNR). The outcome shows that the diffusion technique produces better performance than wavelet transform in all the cases studied.
WeBAL: a web-based assessment library to enhance teaching and learning in engineering

A need exists for classroom-level assessment and evaluation rubrics or instruments to provide meaningful feedback to students on their learning and performance. A web-based assessment library (WeBAL) has been compiled, reviewed, and made available to support engineering faculty when assessing or evaluating students' engineering communication or teamwork activities, two of the a-k skill areas required by the Accreditation Board for Engineering and Technology (ABET) for accreditation of engineering programs and curricula. These instruments are annotated to support selection and classroom usage. A simple, online, menu-based selection process guides faculty users to appropriate instruments to meet specific needs, and all instruments may be downloaded and adapted as desired by faculty.
Effects of Morphology and Doping on the Electronic and Structural Properties of Hydrogenated Silicon Nanowires

We study the electronic and atomic structures of hydrogenated silicon nanowires (SiNWs) by changing the mean diameter, morphology, and orientation using state-of-the-art density functional calculations. Most of the SiNWs are found to have large and direct band gaps, which make them very interesting for silicon-based nano-optoelectronic devices and lasers. The band gap increases with decreasing diameter in all cases because of quantum confinement, but the scaling is dependent on the morphology of the SiNWs. For thin [112] SiNW, the calculated band gap agrees well with the recent experiments. Variation in hydrogen concentration is used to explore the sensing capabilities of different surface morphologies and the associated surface reconstructions. Further studies on p- or n-doping show bulklike modifications in the electronic structure with several advantages that can be used to design nanoscale devices of SiNWs.
Enhancement of radiotherapy efficacy by pleiotropic liposomes encapsulated paclitaxel and perfluorotributylamine

Abstract Paclitaxel (PTX) is widely used as a radiosensitizer in the clinical treatment of cancer. However, the efficacy of chemoradiotherapy is limited by the hostility of the tumor microenvironment such as hypoxia. To overcome this constraint, we designed pleiotropic radiotherapy sensitized liposomes containing perfluorotributylamine (PFTBA) and PTX. The results showed that liposomes significantly accumulated in the tumor site. PFTBA in liposomes dramatically reversed tumor hypoxia and improved the sensitivity of tumor radiotherapy. PTX in liposomes blocked the cell cycle of tumor cells in the radiation-sensitive G2/M phase, which was even greater when combined with PFTBA. In vitro and in vivo tumor treatment further demonstrated remarkably improved therapeutic outcomes in radiotherapy with such biocompatible liposomes. In conclusion, the pleiotropic liposomes encapsulated PFTBA and PTX provide significant radiotherapy sensitization and show promise for future application in clinical medicine.
Trace-Driven Cache Attacks on AES

Cache based side-channel attacks have recently been attracted significant attention due to the new developments in the field. In this paper, we present efficient trace-driven cache attacks on a widely used implementation of the AES cryptosystem. We also evaluate the cost of the proposed attacks in detail under the assumption of a noiseless environment. We develop an accurate mathematical model that we use in the cost analysis of our attacks. We use two different metrics, specifically, the expected number of necessary traces and the cost of the analysis phase, for the cost evaluation purposes. Each of these metrics represents the cost of a different phase of the attack.
Scalable Semi-Supervised Aggregation of Classifiers

We present and empirically evaluate an efficient algorithm that learns to aggregate the predictions of an ensemble of binary classifiers. The algorithm uses the structure of the ensemble predictions on unlabeled data to yield significant performance improvements. It does this without making assumptions on the structure or origin of the ensemble, without parameters, and as scalably as linear learning. We empirically demonstrate these performance gains with random forests.
A virtual and distributed control layer with proximity awareness for group conferencing in P2PSIP

There is an increasing demand to access voice or video group conferences without the burden of a dedicated infrastructure, but at any place and in an ad hoc fashion. Corresponding solutions require a lightweight, fully distributed cooperation among parties that share and manage the conference in an efficient, self-adaptive way. The technology framework of P2PSIP can be seen as a promising starting point to meet these objectives. In this paper, we make several contributions towards such a distributed, virtualized control layer based on P2PSIP that seamlessly scales and adapts to the user needs. We propose a P2P-signaling protocol scheme for a distributed conference control with SIP, that splits the semantic of Identifier and Locator of a SIP conference URI in a standard-compliant manner. This protocol scheme serves as further basis for a virtualization in RELOAD. We further design and evaluate a self-organizing communication layer that provides load sharing and churn resilience with proximity-awareness. Finally, we address key aspects of security and trust, as well as compatibility for conference unaware clients.
Probabilistic Modeling of Nodal Charging Demand Based on Spatial-Temporal Dynamics of Moving Electric Vehicles

High penetration of electric vehicles (EVs) as moving loads in power system have drawn increasing concerns about their negative impacts. Due to the spatial-temporal random dynamics of EVs, it is a challenge for identification and positioning of the space and time varying impacts. Most previous studies investigated system-wide EV charging demand based on data analysis with deterministic charging location and time. In this circumstance, this paper proposes a probabilistic model for nodal charging demand based on the spatial-temporal dynamics of moving EVs. Following the introduction to the integrated system with graph theory, a spatial-temporal model of moving EV loads is established based on random trip chain and Markov decision process (MDP). The nodal EV charging demands are derived from the charging probabilities of single and multiple EVs. The system studies show that this model is capable to assess the nodal charging demand due to the spatial-temporal distribution of moving EVs.
Molecular Characterization of Intestinal Microbiota in Infants Fed With Soymilk

Background: Intestinal bacteria play an important role in the postnatal development of the immune system. The composition of gut microbiota is profoundly influenced by the infant's diet, but there is little information about the effects of soymilk on the composition of intestinal biota. The present study was designed to investigate the intestinal ecosystem of the newborn in relation to the consumption of soymilk. Materials and Methods: Twelve infants had their bovine milk–based formula replaced with soymilk. The intestinal microbial composition of the infants was investigated before and after the change by means of polymerase chain reaction-denaturing gradient gel electrophoresis. In addition, species-specific amplification of 10 Bifidobacterium species, 3 Ruminococcus species, and the Bacteroides group was performed. Results: Denaturing gradient gel electrophoresis analysis revealed bacterial profiles characterized by numerous bands typical for each subject. No variations were detected by species-specific polymerase chain reaction. Conclusions: The data demonstrate that soymilk feeding does not alter the intestinal flora of infants and decrease the intestinal bifidobacterial population.
Algorithm amalgam: morphing waveform based methods, sinusoidal models and STRAIGHT

A tool to investigate an important fundamental question in speech processing is proposed aiming to promote research on voice quality and para and non linguistic aspects of speech. The proposed method effectively emulates waveform-based methods, sinusoidal models and the high quality source filter model STRAIGHT The key idea that enables blending these seemingly disjoint algorithms is a group delay based representation of signal excitation. By using a STRAIGHT-based smoothed time-frequency representation that is shared by these three types of speech processing methods, a unified source representation is used to implement the proposed system. Informal listening tests using the proposed system indicated that phase manipulation introduces different timbre, but it does not need to reproduce the exact waveform to reproduce the same timbre. This may suggest that the possibility of further information reduction exists in synthesizing close to natural quality speech.