Miracle-dz/UniFAR-FTUs huggingface dataset:
Strong and Elastic Chitosan/Silk Fibroin Hydrogels Incorporated with Growth-Factor-Loaded Microspheres for Cartilage Tissue Engineering

An emulsification method was developed for fabricating core-shell microspheres with a thick shell layer. Kartogenin (KGN) and platelet-derived growth factor BB (PDGF-BB) were respectively loaded into the core portion and the shell layer of the microspheres with high loading efficiency. The optimally built microspheres were combined with chitosan (CH) and silk fibroin (SF) to construct a new type of composite hydrogel with enhanced strength and elasticity, using genipin or/and tyrosinase as crosslinkers for the intended use in cartilage tissue engineering. The composite hydrogels were found to be thermo-responsive at physiological temperature and pH with well-defined injectability. Rheological measurements revealed that they had an elastic modulus higher than 6 kPa with a high ratio of elastic modulus to viscous modulus, indicative of their mechanically strong features. Compressive measurements demonstrated that they possessed well-defined elasticity. In addition, some gels had the ability to administer the temporal separation release of PDGF-BB and KGN in an approximately linear manner for several weeks. The released PDGF-BB was found to be bioactive based on its effects on Balb/c 3T3 cells. The composite gels supported the growth of seeded chondrocytes while preserving their phenotype. The results suggest that these composite gels have the potential for endogenous cartilage repair.
The Activity of Long-tailed Macaque (Macaca fascicularis) at Plantation Forest in Ogan Komering Ilir Regency, South Sumatera

Long-tailed macaque (Macaca fascicularis) is a quite adaptive animal so it could be found in a diverse range of habitat types, one of the habitats is Plantation Forest on peatlands. This study aims to obtain the information about the activity of long-tailed macaque related to habitat utilization at Plantation The operational activities in the Plantation Forest can affect the activities of long-tailed macaque, changing of food sources, and they have a potential to attack the Acacia plants, so itâ€™s necessary to do research about the activity of long-tailed macaque related to the habitat utilization at Plantation Forest and to acknowledge the types of plants used by long-tailed macaque for food and shelter. This research is a descriptive study and the data are obtained through a focal animal sampling method in April and May 2019 at the Plantation Forest in Sungai Penyabungan District, Ogan Komering Ilir Regency. The focal animal sampling method used at 7.00-17.00 WIB with using interval of 10 minutes. Based on the study, the long-tailed macaque used the active time to feed (24.60%), rest (25.58%), move (27.92%), and social activities (21.89%) included vocalization, agonistic, and grooming. The vegetation parts consumed by the long-tailed macaque are leaves (42.30%), fruits (34.62%), and flowers (23.08%). The vegetation used as food is Acacia crassicarpa, Melaleuca cajuputi, and Melastoma malabathricum. The plant thatâ€™s most often used as food and shelter is Acacia crassicarpa.
CXCL5-mediated accumulation of mature neutrophils in lung cancer tissues impairs the differentiation program of anticancer CD8 T cells and limits the efficacy of checkpoint inhibitors

ABSTRACT Lung tumor-infiltrating neutrophils are known to support growth and dissemination of cancer cells and to suppress T cell responses. However, the precise impact of tissue neutrophils on programming and differentiation of anticancer CD8 T cells in vivo remains poorly understood. Here, we identified cancer cell-autonomous secretion of CXCL5 as sufficient to drive infiltration of mature, protumorigenic neutrophils in a mouse model of non-small cell lung cancer (NSCLC). Consistently, CXCL5 transcripts correlate with neutrophil density and poor prognosis in a large human lung adenocarcinoma compendium. CXCL5 genetic deletion, unlike antibody-mediated depletion, completely and selectively prevented neutrophils accumulation in lung tissues. Depletion of tumor-infiltrating neutrophils promoted expansion of tumor-specific CD8 T cells, differentiation into effector cells and acquisition of cytolytic functions. Transfer of effector CD8 T cells into neutrophil-rich tumors, inhibited IFN-ϒ production, indicating active suppression of effector functions. Importantly, blocking neutrophils infiltration in the lung, overcame resistance to checkpoint blockade. Hence, this study demonstrates that neutrophils curb acquisition of cytolytic functions in lung tumor tissues and suggests targeting of CXCL5 as a strategy to restore anti-tumoral T cell functions.
Neospora caninum SRS2 Protein: Essential Vaccination Targets and Biochemical Features for Next-Generation Vaccine Design

Vaccination is a standout preventive measure to combat neosporosis among cattle herds. The present in silico study was done to evaluate the physicochemical properties and potent immunogenic epitopes of N. caninum SRS2 protein as a possible vaccine candidate. Web-based tools were used to predict physicochemical properties, antigenicity, allergenicity, solubility, posttranslational modification (PTM) sites, transmembrane domains and signal peptide, and secondary and tertiary structures as well as intrinsically disordered regions, followed by identification and screening of potential linear and conformational B-cell epitopes and those peptides having affinity to bind mouse major histocompatibility complex (MHC) and cytotoxic T lymphocyte (CTL). The protein had 401 residues with a molecular weight of 42 kDa, representing aliphatic index of 69.35 (thermotolerant) and GRAVY score of -0.294 (hydrophilic). There were 53 PTM sites without a signal peptide in the sequence. Secondary structure comprised mostly by extended strand, followed by helices and coils. The Ramachandran plot of the refined model showed 90.2%, 8.8%, 0.5%, and 0.5% residues in the favored, additional allowed, generously allowed, and disallowed regions, correspondingly. Additionally, various potential B-cell (linear and conformational), CTL, and MHC-binding epitopes were predicted for N. caninum SRS2. These epitopes could be further utilized in the multiepitope vaccine constructs directed against neosporosis.
The pre- and post-pitch-entry physical and technical responses of rugby league interchange players according to starting status

This study quantified the activities of interchange players during the 15 min before and 20 min after initial pitch-entry (INTentry) or re-entry (INTre−entry) for substitutes and starters, respectively, and identified relationships between pre- and post-pitch-entry responses. Fourteen semi-professional rugby league players wore Microelectromechanical Systems and were filmed throughout 10 matches in which they were interchanged (68 observations). Twelve physical and technical variables were analyzed for the pre-match warm-up, five, 10, and 15 min before INTentry or INTre−entry (physical variables only), and five min epochs following match-introduction. Linear mixed models indicated that during the 0–5 min following INTentry, physical and technical responses were typically greater (∼7.1% to 66.3%) than subsequent epochs while total (∼6.2%) and high-speed (37.1%) distance also exceeded the 0–5 min after INTre−entry (p < 0.05). Edge forwards reached higher peak speeds (11.4% to 11.7%) than hookers and middle forwards, but hookers completed more passes (87.4% to 90.5%). Pre-pitch-entry movements were positively associated with post-pitch-entry tackles (r = 0.43 to 0.49) and high-speed distance (r = 0.46), but negatively associated with total distance (r = −0.32 to −0.68). Within tolerable limits, increasing the activity performed during the ∼15 min before pitch-entry could benefit high-speed match-play performance indicators. Transient changes in post-pitch-entry physical and technical responses could reflect self-pacing strategies, contextual factors, or perceived preparedness. The apparent absence of progressive performance-limiting fatigue, characterized by a plateau in responses after the initial five min following INTentry or INTre−entry, may suggest a role for interchange players to provide a more sustained impact and thus achieve interchange objectives.
Name Dependency and Domain Name Resolution Risk Assessment

The Domain name system (DNS) is crucial to Internet services. Previous studies have pointed out that the name dependency in domain name resolution poses a risk to the security of DNS. In this paper, we present measurement results from a dataset containing resolution paths of domain names collected from a large-scale survey. This dataset is used to research the effect of the name dependency on the DNS, reaffirm findings in published work, and notice some significant differences. When name resolution spans multiple domains, it will lead to name dependency and make the resolution process more complex. Furthermore, we assess the risk of domain name resolution: a name resolution fault analysis model and the calculation of the failure probability of name resolution is proposed. The model can identify the key server sets that lead to the resolution failure of a domain name, and quantify the failure probability of its resolution. This research provides a breakthrough point for guiding the configuration, management, deployment, and upgrading of the DNS.
Stand-level growth models for long-term projections of the main species groups in Norway

ABSTRACT Stand-level growth and yield models are important tools that support forest managers and policymakers. We used recent data from the Norwegian National Forest Inventory to develop stand-level models, with components for dominant height, survival (number of survived trees), ingrowth (number of recruited trees), basal area, and total volume, that can predict long-term stand dynamics (i.e. 150 years) for the main species in Norway, namely Norway spruce (Picea abies (L.) Karst. ), Scots pine (Pinus sylvestris L.), and birch (Betula pubescens Ehrh. and Betula pendula Roth). The data used represent the structurally heterogeneous forests found throughout Norway with a wide range of ages, tree size mixtures, and management intensities. This represents an important alternative to the use of dedicated and closely monitored long-term experiments established in single species even-aged forests for the purpose of building these stand-level models. Model examination by means of various fit statistics indicated that the models were unbiased, performed well within the data range and extrapolated to biologically plausible patterns. The proposed models have great potential to form the foundation for more sophisticated models, in which the influence of other factors such as natural disturbances, stand structure including species mixtures, and management practices can be included.
iOS 9 Swift Programming Cookbook

Ready to build stunning apps for iPhone, iPad, and Apple Watch? This cookbook-completely rewritten with all-new material-provides 90 proven solutions for tackling the latest features in iOS 9 and watchOS 2.0. Written exclusively in Apple's Swift language, these code-rich recipes show you how to use dynamic user interfaces, interactive maps, multitasking functionality, Apple's new UI Testing framework, and many other features. This cookbook is ideal for intermediate and advanced iOS developers looking to work with the newest versions of Apple's mobile operating systems. Each recipe includes reusable code, available on GitHub, that you can put to work right away. Work with new features in Swift 2, Xcode 7, and Interface Builder Build standalone apps for Apple Watch Create vibrant user interfaces with new UIKit features Use Swift to connect with the iOS contacts database Block ads or obtrusive content with Safari Content Blockers Make your app content searchable with Spotlight APIs Add Picture in Picture playback functionality to iPad apps Take advantage of MapKit and Core Location updates Use Apple's new UI Testing framework Liven up your UI with gravity and turbulence fields
IIb‐RAD‐sequencing coupled with random forest classification indicates regional population structuring and sex‐specific differentiation in salmon lice (Lepeophtheirus salmonis)

Abstract The aquaculture industry has been dealing with salmon lice problems forming serious threats to salmonid farming. Several treatment approaches have been used to control the parasite. Treatment effectiveness must be optimized, and the systematic genetic differences between subpopulations must be studied to monitor louse species and enhance targeted control measures. We have used IIb‐RAD sequencing in tandem with a random forest classification algorithm to detect the regional genetic structure of the Norwegian salmon lice and identify important markers for sex differentiation of this species. We identified 19,428 single nucleotide polymorphisms (SNPs) from 95 individuals of salmon lice. These SNPs, however, were not able to distinguish the differential structure of lice populations. Using the random forest algorithm, we selected 91 SNPs important for geographical classification and 14 SNPs important for sex classification. The geographically important SNP data substantially improved the genetic understanding of the population structure and classified regional demographic clusters along the Norwegian coast. We also uncovered SNP markers that could help determine the sex of the salmon louse. A large portion of the SNPs identified to be under directional selection was also ranked highly important by random forest. According to our findings, there is a regional population structure of salmon lice associated with the geographical location along the Norwegian coastline.
An Optical Image Encryption Method Using Hopfield Neural Network

In this paper, aiming to solve the problem of vital information security as well as neural network application in optical encryption system, we propose an optical image encryption method by using the Hopfield neural network. The algorithm uses a fuzzy single neuronal dynamic system and a chaotic Hopfield neural network for chaotic sequence generation and then obtains chaotic random phase masks. Initially, the original images are decomposed into sub-signals through wavelet packet transform, and the sub-signals are divided into two layers by adaptive classification after scrambling. The double random-phase encoding in 4f system and Fresnel domain is implemented on two layers, respectively. The sub-signals are performed with different conversions according to their standard deviation to assure that the local information’s security is guaranteed. Meanwhile, the parameters such as wavelength and diffraction distance are considered as additional keys, which can enhance the overall security. Then, inverse wavelet packet transform is applied to reconstruct the image, and a second scrambling is implemented. In order to handle and manage the parameters used in the scheme, the public key cryptosystem is applied. Finally, experiments and security analysis are presented to demonstrate the feasibility and robustness of the proposed scheme.
Elastic Fibre Proteins in Elastogenesis and Wound Healing

As essential components of our connective tissues, elastic fibres give tissues such as major blood vessels, skin and the lungs their elasticity. Their formation is complex and co-ordinately regulated by multiple factors. In this review, we describe key players in elastogenesis: fibrillin-1, tropoelastin, latent TGFβ binding protein-4, and fibulin-4 and -5. We summarise their roles in elastogenesis, discuss the effect of their mutations on relevant diseases, and describe their interactions involved in forming the elastic fibre network. Moreover, we look into their roles in wound repair for a better understanding of their potential application in tissue regeneration.
Nonlinear normal modes in mechanical systems: concept and computation with numerical continuation

The purpose of this Project is, first and foremost, to disclose the topic of nonlinear vibrations and oscillations in mechanical systems and, namely, nonlinear normal modes NNMs to a greater audience of researchers and technicians. To do so, first of all, the dynamical behavior and properties of nonlinear mechanical systems is outlined from the analysis of a pair of exemplary models with the harmonic balanced method. The conclusions drawn are contrasted with the Linear Vibration Theory. Then, it is argued how the nonlinear normal modes could, in spite of their limitations, predict the frequency response of a mechanical system. After discussing those introductory concepts, I present a Matlab package called 'NNMcont' developed by a group of researchers from the University of Liege. This package allows the analysis of nonlinear normal modes of vibration in a range of mechanical systems as extensions of the linear modes. This package relies on numerical methods and a 'continuation algorithm' for the computation of the nonlinear normal modes of a conservative mechanical system. In order to prove its functionality, a two degrees of freedom mechanical system with elastic nonlinearities is analized. This model comprises a mass suspended on a foundation by means of a spring-viscous damper mechanism -analogous to a very simplified model of most suspended structures and machines- that has attached a mass damper as a passive vibration control system. The results of the computation are displayed on frequency energy plots showing the NNMs branches along with modal curves and time-series plots for each normal mode. Finally, a critical analysis of the results obtained is carried out with an eye on devising what they can tell the researcher about the dynamical properties of the system.
Small-scale species richness of plant communities with similar biomass: the influence of habitat types in the context of historical hypothesis (Western Caucasus and Ciscaucasia, Black and Azov Seas, Russia)

We compared the species richness of the plant communities of different habitats on different sites of the biomass gradient. The analysis was based on data on 1089 above-ground biomass samples taken from the sites 0.25 m2 of terrestrial herbaceous communities of the Western Caucasus and Ciscaucasia (30–2800 m a.s.l.) and 317 samples taken from the same sites of the macrophytobenthos of the Black and Azov Seas (0.5–10 m depth). Results showed that a certain amount of biomass, sampled in communities of different types, includes, on average, a significantly different number of species. Thus, among terrestrial plant communities, highmountain communities of the Western Caucasus are characterized by the highest species richness in most ranges of the biomass gradient; communities of herb layer of shaded forests – on the contrary, the lowest richness. The macrophytobenthos of the Black Sea is characterized by lower species richness than most of the terrestrial communities, but higher species richness than the benthic communities of the Azov Sea. We showed that significant difference in the small-scale species richness of these communities can be plausibly explained by the peculiarities of their history.
Recent advances in single-molecule spectroscopy studies on light-harvesting processes in oxygenic photosynthesis

Photosynthetic light-harvesting complexes (LHCs) play a crucial role in concentrating the photon energy from the sun that otherwise excites a typical pigment molecule, such as chlorophyll-a, only several times a second. Densely packed pigments in the complexes ensure efficient energy transfer to the reaction center. At the same time, LHCs have the ability to switch to an energy-quenching state and thus play a photoprotective role under excessive light conditions. Photoprotection is especially important for oxygenic photosynthetic organisms because toxic reactive oxygen species can be generated through photochemistry under aerobic conditions. Because of the extreme complexity of the systems in which various types of pigment molecules strongly interact with each other and with the surrounding protein matrixes, there has been long-standing difficulty in understanding the molecular mechanisms underlying the flexible switching between the light-harvesting and quenching states. Single-molecule spectroscopy studies are suitable to reveal the conformational dynamics of LHCs reflected in the fluorescence properties that are obscured in ordinary ensemble measurements. Recent advanced single-molecule spectroscopy studies have revealed the dynamical fluctuations of LHCs in their fluorescence peak position, intensity, and lifetime. The observed dynamics seem relevant to the conformational plasticity required for the flexible activations of photoprotective energy quenching. In this review, we survey recent advances in the single-molecule spectroscopy study of the light-harvesting systems of oxygenic photosynthesis.
Dynamic adaptive resource management in a virtualized numa multicore system for optimizing power, energy, and performance

A Non-Uniform Memory-Access (NUMA) machine is currently the most deployed type of a hardware architecture for high performance computing. System virtualization on the other hand is increasingly adopted for various reasons. In a virtualized NUMA system, the NUMA attributes are transparent to guest OS's. Thus, a Virtual Machine Monitor (VMM) is required to have NUMA-aware resource management. Tradeoffs between performance, power, and energy are observable as virtual cores (vcores) and/or virtual addresses are mapped in different ways. For example, sparsely located vcores have an advantage in memory caching compared to densely located vcores. On the other hand, densely located vcores tend to save power. Such tradeoffs lead to an abstract question: how a VMM as a resource manager can optimally or near-optimally execute guests under a NUMA architecture. In my dissertation, I claim that it is possible to solve this problem in real time through a dynamic adaptive system. Workload-aware scheduling, mapping, and shared resource management are controlled by adaptive schemes. The user may demand one of three objectives: performance, energy, or power. My system also incorporates a new detection framework that observes shared memory access behaviors with minimum over- heads, and includes models that estimate performance, power, and workloads' resource demands. The system uses a simple heuristic policy if it is sufficient to optimize the user demand objective. My dynamic adaptive system, called NUMA-aware Virtualized Adaptive Runtime (NAVAR), was designed, implemented, and evaluated with benchmarks from PARSEC, SPEC OMP, and NAS suites. It can achieve more than a 10% performance and energy benefit over the default static policy. And, its performance is never worse than the default. When NAVAR includes developed offline models, these models are validated with the separate validation set from the training set. NAVAR is also deployed and tested in two test machines, and its overheads suggest that it will be highly extensible for scaled NUMA multicore machines.