Miracle-dz/UniFAR-FTUs huggingface dataset:
Unexpected synergistic and antagonistic antibiotic activity against Staphylococcus biofilms

Objectives To evaluate putative anti-staphylococcal biofilm antibiotic combinations used in the management of periprosthetic joint infections (PJIs). Methods Using the dissolvable bead biofilm assay, the minimum biofilm eradication concentration (MBEC) was determined for the most commonly used antimicrobial agents and combination regimens against staphylococcal PJIs. The established fractional inhibitory concentration (FIC) index was modified to create the fractional biofilm eradication concentration (FBEC) index to evaluate synergism or antagonism between antibiotics. Results Only gentamicin (MBEC 64 mg/L) and daptomycin (MBEC 64 mg/L) were observed to be effective antistaphylococcal agents at clinically achievable concentrations. Supplementation of gentamicin with daptomycin, vancomycin or ciprofloxacin resulted in a similar or lower MBEC than gentamicin alone (FBEC index 0.25-2). Conversely, when rifampicin, clindamycin or linezolid was added to gentamicin, there was an increase in the MBEC of gentamicin relative to its use as a monotherapy (FBEC index 8-32). Conclusions This study found that gentamicin and daptomycin were the only effective single-agent antibiotics against established Staphylococcus biofilms. Interestingly the addition of a bacteriostatic antibiotic was found to antagonize the ability of gentamicin to eradicate Staphylococcus biofilms.
Microencapsulation of model oil in wall matrices consisting of SPI and maltodextrins

Microencapsulation can provide means to entrap, protect and deliver nutritional lipids and related compounds that are susceptible to deterioration. The encapsulation of high lipid loads represents a challenge. The research has investigated the encapsulation by spray drying of a model oil, at a core load of 25–60%, in wall systems consisting of 2.5–10% SPI and 17.5–10% maltodextrin. In general, core-in-wall-emulsions exhibited unimodal PSD and a mean particle diameter < 0.5 µm. Dry microcapsules ranged in diameter from about 5 to less than 50 µm and exhibited only a limited extent of surface indentation. Core domains, in the form of protein-coated droplets, were embedded throughout the wall matrices and no visible cracks connecting these domains with the environment could be detected. Core retention ranged from 72.2 to 95.9% and was significantly affected (p < 0.05) by a combined influence of wall composition and initial core load. Microencapsulation efficiency, MEE, ranged from 25.4 to 91.6% and from 12.4 to 91.4% after 5 and 30 min of extraction, respectively (p < 0.05). MEE was significantly influenced by wall composition, extraction time, initial core load and DE value of the maltodextrins. Results indicated that wall solutions containing as low as 2.5% SPI and 17.5% maltodextrin were very effective as microencapsulating agents for high oil load. Results highlighted the functionality of SPI as microencapsulating agent in food applications and indicated the importance of carefully designing the composition of core-in-wall-emulsions.
Damage index proposals applied to quasi-brittle materials simulated using the lattice discrete element method

The process of damage in quasi-brittle materials is characterized by loss of isotropy for certain load levels. The strain localization, the cooperative effect between damaged regions and the avalanche of ruptures are particular features in measuring the damage in this kind of material. The mentioned features create different forms of energy dissipation, which are not easy to represent with a continuous approach. In the present work, a version of the lattice discrete element method (LDEM) is employed. In this method the fracture and fragmentation are taken into account in a natural manner, since the bars that reached their limit strength during the process are disabled of the system, respecting the energy balance. It is possible to introduce heterogeneity in the model considering the material properties as random fields with spatial Weibull probability distribution and known correlation length. The aim of the present paper is to describe the implementation, in the context of this version of the LDEM, of three classical indexes used to measure the level of damage: a scalar index, and a second- and a fourth-order tensorial index. A simple uniaxial tensile test is used to illustrate the implementation. A discussion about the advantages of applying this tool to analyse the damage evolution in quasi-brittle structures and the possibility to link these indexes with other forms of measurement of damage evolution, such as acoustic emission data, also are commented.
Machine Learning and Decision Support in Critical Care

Clinical data management systems typically provide caregiver teams with useful information, derived from large, sometimes highly heterogeneous, data sources that are often changing dynamically. Over the last decade there has been a significant surge in interest in using these data sources, from simply reusing the standard clinical databases for event prediction or decision support, to including dynamic and patient-specific information into clinical monitoring and prediction problems. However, in most cases, commercial clinical databases have been designed to document clinical activity for reporting, liability, and billing reasons, rather than for developing new algorithms. With increasing excitement surrounding “secondary use of medical records” and “Big Data” analytics, it is important to understand the limitations of current databases and what needs to change in order to enter an era of “precision medicine. ” This review article covers many of the issues involved in the collection and preprocessing of critical care data. The three challenges in critical care are considered: compartmentalization, corruption, and complexity. A range of applications addressing these issues are covered, including the modernization of static acuity scoring; online patient tracking; personalized prediction and risk assessment; artifact detection; state estimation; and incorporation of multimodal data sources such as genomic and free text data.
Provably secure user authentication and key agreement scheme for wireless sensor networks

In recent years, user authentication has emerged as an interesting field of research in wireless sensor networks. Most recently, in 2016, Chang and Le presented a scheme to authenticate the users in wireless sensor network using a password and smart card. They proposed two protocols P1 and P2. P1 is based on exclusive or XOR and hash functions, while P2 deploys elliptic curve cryptography in addition to the two functions used in P1. Although their protocols are efficient, we point out that both P1 and P2 are vulnerable to session specific temporary information attack and offline password guessing attack, while P1 is also vulnerable to session key breach attack. In addition, we show that both the protocols P1 and P2 are inefficient in authentication and password change phases. To withstand these weaknesses found in their protocols, we aim to design a new authentication and key agreement scheme using elliptic curve cryptography. Rigorous formal security proofs using the broadly accepted, the random oracle models, and the Burrows-Abadi-Needham logic and verification using the well-known Automated Validation of Internet Security Protocols and Applications tool are preformed on our scheme. The analysis shows that our designed scheme has the ability to resist a number of known attacks comprising those found in both Chang-Le's protocols. Copyright © 2016 John Wiley & Sons, Ltd.
User Access Management Based on Network Pricing for Social Network Applications

Social applications play a very important role in people’s lives, as users communicate with each other through social networks on a daily basis. This presents a challenge: How does one receive high-quality service from social networks at a low cost? Users can access different kinds of wireless networks from various locations. This paper proposes a user access management strategy based on network pricing such that networks can increase its income and improve service quality. Firstly, network price is treated as an optimizing access parameter, and an unascertained membership algorithm is used to make pricing decisions. Secondly, network price is adjusted dynamically in real time according to network load. Finally, selecting a network is managed and controlled in terms of the market economy. Simulation results show that the proposed scheme can effectively balance network load, reduce network congestion, improve the user's quality of service (QoS) requirements, and increase the network’s income.
Uncoded placement optimization for coded delivery

Existing coded caching schemes fail to simultaneously achieve efficient content placement for non-uniform file popularity and efficient content delivery in the presence of common requests, and hence may not achieve desirable average load under a non-uniform, possibly very skewed, popularity distribution. In addition, existing coded caching schemes usually require the splitting of a file into a large number of subfiles, i.e., high subpacketization, and hence may cause huge implementation complexity. To address the above two challenges, we first present a class of centralized coded caching schemes consisting of a general content placement strategy specified by a file partition parameter, enabling efficient and flexible content placement, and a specific content delivery strategy, enabling load reduction by exploiting common requests of different users. Then we consider two cases, namely, the case without considering the subpacketization issue and the case considering the subpacke-tization issue. In the first case, we formulate the coded caching optimization problem over the considered class of schemes with N2K variables to minimize the average load under an arbitrary file popularity. Imposing some conditions on the file partition parameter, we transform the original optimization problem into a linear optimization problem with N(K + 1) variables under an arbitrary file popularity and a linear optimization problem with K +1 variables under the uniform file popularity. We also show that Yu et al.'s centralized coded caching scheme corresponds to an optimal solution of our problem. In the second case, taking into account the subpacketization issue, we first formulate the coded caching optimization problem over the considered class of schemes to minimize the average load under an arbitrary file popularity subject to a subpacketization constraint involving the ℓ0-norm. By imposing the same conditions and using an exact DC (difference of two convex functions) reformulation method, we convert the original problem with N2K variables into a simplified DC problem with N(K + 1) variables. Then, we use a DC algorithm to solve the simplified DC problem.
Dopamine release from the locus coeruleus to the dorsal hippocampus promotes spatial learning and memory

Significance Successful completion of daily activities relies on the ability to select the relevant features of the environment to pay attention to and remember. Disruptions of these processes can lead to disorders, such as attention-deficit hyperactivity disorder and age-related memory loss. To devise therapeutic strategies, we must understand the neural circuits underlying normal cognition. One important pathway is the signaling of dopamine, a reinforcement-related neurotransmitter, in the hippocampus, a spatial learning and memory center. Surprisingly, the brain region supplying dopamine to the dorsal hippocampus is unclear. This study provides direct evidence that the noradrenergic locus coeruleus coreleases dopamine in the dorsal hippocampus and provides insight into dopamine function in selective attention and spatial learning and memory. Dopamine neurotransmission in the dorsal hippocampus is critical for a range of functions from spatial learning and synaptic plasticity to the deficits underlying psychiatric disorders such as attention-deficit hyperactivity disorder. The ventral tegmental area (VTA) is the presumed source of dopamine in the dorsal hippocampus. However, there is a surprising scarcity of VTA dopamine axons in the dorsal hippocampus despite the dense network of dopamine receptors. We have explored this apparent paradox using optogenetic, biochemical, and behavioral approaches and found that dopaminergic axons and subsequent dopamine release in the dorsal hippocampus originate from neurons of the locus coeruleus (LC). Photostimulation of LC axons produced an increase in dopamine release in the dorsal hippocampus as revealed by high-performance liquid chromatography. Furthermore, optogenetically induced release of dopamine from the LC into the dorsal hippocampus enhanced selective attention and spatial object recognition via the dopamine D1/D5 receptor. These results suggest that spatial learning and memory are energized by the release of dopamine in the dorsal hippocampus from noradrenergic neurons of the LC. The present findings are critical for identifying the neural circuits that enable proper attention selection and successful learning and memory.
The war on cryptococcosis: A Review of the antifungal arsenal

Cryptococcal meningitis is the most common central nervous system infection in the world today. It occurs primarily, but not exclusively, in immunocompromised individuals and despite substantial improvement in management of clinical events like AIDS, the numbers of cases of cryptococcosis remain very high. Unfortunately, despite several antifungal agents available for treatment, morbidity and mortality rates remain high with this fungal infection. In this Review, we will describe the treatments and strategies for success, identify the failures, and provide insights into the future developments / improvements for management. This sugar-coated yeast can play havoc within the human brain. Our goals must be to either prevent or diagnose disease early and treat aggressively with all our clinical tools when disease is detected.
Source Localization of Brain States Associated with Canonical Neuroimaging Postures

Cognitive neuroscientists rarely consider the influence that body position exerts on brain activity; yet, postural variation holds important implications for the acquisition and interpretation of neuroimaging data. Whereas participants in most behavioral and EEG experiments sit upright, many prominent brain imaging techniques (e.g., fMRI) require participants to lie supine. Here we demonstrate that physical comportment profoundly alters baseline brain activity as measured by magnetoencephalography (MEG)—an imaging modality that permits multipostural acquisition. We collected resting-state MEG data from 12 healthy participants in three postures (lying supine, reclining at 45°, and sitting upright). Source-modeling analysis revealed a broadly distributed influence of posture on resting brain function. Sitting upright versus lying supine was associated with greater high-frequency (i.e., beta and gamma) activity in widespread parieto-occipital cortex. Moreover, sitting upright and reclining postures correlated with dampened activity in prefrontal regions across a range of bandwidths (i.e., from alpha to low gamma). The observed effects were large, with a mean Cohen's d of 0.95 (SD = 0.23). In addition to neural activity, physiological parameters such as muscle tension and eye blinks may have contributed to these posture-dependent changes in brain signal. Regardless of the underlying mechanisms, however, the present results have important implications for the acquisition and interpretation of multimodal imaging data (e.g., studies combining fMRI or PET with EEG or MEG). More broadly, our findings indicate that generalizing results—from supine neuroimaging measurements to erect positions typical of ecological human behavior—would call for considering the influence that posture wields on brain dynamics.
Leaf Litter Mixtures Alter Microbial Community Development: Mechanisms for Non-Additive Effects in Litter Decomposition

To what extent microbial community composition can explain variability in ecosystem processes remains an open question in ecology. Microbial decomposer communities can change during litter decomposition due to biotic interactions and shifting substrate availability. Though relative abundance of decomposers may change due to mixing leaf litter, linking these shifts to the non-additive patterns often recorded in mixed species litter decomposition rates has been elusive, and links community composition to ecosystem function. We extracted phospholipid fatty acids (PLFAs) from single species and mixed species leaf litterbags after 10 and 27 months of decomposition in a mixed conifer forest. Total PLFA concentrations were 70% higher on litter mixtures than single litter types after 10 months, but were only 20% higher after 27 months. Similarly, fungal-to-bacterial ratios differed between mixed and single litter types after 10 months of decomposition, but equalized over time. Microbial community composition, as indicated by principal components analyses, differed due to both litter mixing and stage of litter decomposition. PLFA biomarkers a15∶0 and cy17∶0, which indicate gram-positive and gram-negative bacteria respectively, in particular drove these shifts. Total PLFA correlated significantly with single litter mass loss early in decomposition but not at later stages. We conclude that litter mixing alters microbial community development, which can contribute to synergisms in litter decomposition. These findings advance our understanding of how changing forest biodiversity can alter microbial communities and the ecosystem processes they mediate.
Movement Characteristics of Hydrogen Gas Within the Ground and Its Detection at Ground Surface

Hydrogen gas is expected to be a clean, environmentally friendly future energy source. As a method to supply hydrogen gas to a fuel cell station, the use of buried pipelines is being studied in Japan and elsewhere. To realize this idea, ensuring safety is very important. Specifically, the understanding of hydrogen gas movement characteristics, including the extent and speed of movement within the ground in the event of a hydrogen leak, is extremely important, as is the reliability assessment of pipeline materials in order to establish the basis for the design and maintenance of safe facilities. To establish a foundation for ensuring the safety of buried hydrogen supply pipelines, full-scale experiments on underground hydrogen gas leakage and numerical simulation were performed. The release and movement characteristics of hydrogen gas within soil were investigated and measured with the objective of establishing hydrogen gas leak detection technology. KeywordsRoad Base; Buried Pipeline; Partially Saturated Soil; Hydrogen Gas Permeability
Nonparabolicity Effects of the Ultra-thin Body Double-gate MOSFETs

In this paper, the band-structure of ultra-thin body (UTB) double-gate (DG) MOSFETs is calculated by empirical tight-binding model, and the the nonparabolicity effects are included in the model by the modified Schrödinger equation with the fitting parameters which are extracted from the band-structure by expanding the dispersion relationship in a power series up to the third order. The characteristics of UTB-DG MOSFET current are simulated and the results are compared by the non-equilibrium Green’s function (NEGF) transport theory based on effective mass approximation (EMA), parabolic quantumconfined masses (PQM) and nonparabolicity effect model (NPE). It is shown that the saturation current is overestimated in the models based on EMA and PQM compared with the model including NPE, and the value rises to 4% when Tsi equals to 3nm. The difference between NPE model and PQM model increases with increment of Vg, but less sensitive to Vds.
Perceptions of Appropriateness of Accommodations for University Students: Does Disability Type Matter?

Purpose: The purpose of this experiment was to examine the impact of disability type and accommodation type on participants’ perceptions of the appropriateness of accommodations on university campuses. Research Method: Participants were 223 university students who evaluated the written symptom descriptions of 8 hypothetical university students with disabilities to determine whether a series of 8 different accommodations would be appropriate for them. Results: Perceptions of accommodation appropriateness were impacted by both the type of disability and the type of accommodation under consideration. The results indicated that accommodations for psychiatric disabilities and invisible physical disabilities were less likely to be viewed as appropriate regardless of how well they addressed the symptoms of the disability. Conclusions: Students with psychiatric and invisible physical disabilities may be especially vulnerable to negative peer perceptions if they receive accommodations. These attitudinal barriers make it harder for students with disabilities to integrate into the college social environment. Students with disabilities who do not feel welcome are less likely to self-advocate to acquire the accommodations that they need and are therefore less likely to succeed in their course work. Our results highlight the importance of programs that encourage the integration of students with disabilities and decrease the stigma of disability on campus.
Influence of Stereoscopic Camera System Alignment Error on the Accuracy of 3D Reconstruction

The article deals with the influence of inaccurate rotation of cameras in camera system alignment on 3D reconstruction accuracy. The accuracy of the all three spatial coordinates is analyzed for two alignments (setups) of 3D cameras. In the first setup, a 3D system with parallel optical axes of the cameras is analyzed. In this stereoscopic setup, the deterministic relations are derived by the trigonometry and basic stereoscopic formulas. The second alignment is a generalized setup with cameras in arbitrary positions. The analysis of the situation in the general setup is closely related with the influence of errors of the points' correspondences. Therefore the relation between errors of points' correspondences and reconstruction of the spatial position of the point was investigated. This issue is very complex. The worst case analysis was executed with the use of Monte Carlo method. The aim is to estimate a critical situation and the possible extent of these errors. Analysis of the generalized system and derived relations for normal system represent a significant improvement of the spatial coordinates accuracy analysis. A practical experiment was executed which confirmed the proposed relations.