Aspek geografi budaya dalam wilayah pembangunan daerah Nusa Tenggara Barat

Proyek Inventarisasi dan dokumentasi Kebudayaan daerah, direktorat Sejarah dan Nilai Tradisional direktorat Jenderal Kebudayaan departemen Pendidikan dan Kebudayaan telah menghasilkan beberapa macam naskah kebudayaan daerah di antaranya ialah naskah Aspek Geografi Budaya dalam Wilayah Pembangunan daerah Nusa Tenggara Barat Tahun 1979 /1980

Spine system equivalence: A new protocol for standardized multi-axis comparison tests

This is the final version of the paper.Accurately replicating the in-vivo loads of the spine is a critical aspect of in-vitro spine testing, but the complexity of this structure renders this challenging. The design and control capabilities of multi-axis spine systems vary considerably, and though recommendations have been made [1, 2], standardized in-vitro methods have not yet been established. As such, it is often difficult to compare different biomechanical studies [3]. The aim of this study was to use international standards [4, 5], and spine testing recommendations [1-3] to develop a standardized protocol for the evaluation of different multi-axis spinal test systems. The protocol was implemented on three six-axis spine systems, and the data used to establish stiffness and phase angle limits. [...]This research was supported by the Catherine Sharpe Foundation, the Enid Linder Foundation, the Higher Education Innovation Fund, and the University of Bath Alumni Fund

The equivalence of multi-axis spine systems: Recommended stiffness limits using a standardized testing protocol

Author's accepted manuscriptFinal version available from Elsevier via the DOI in this recordThe complexity of multi-axis spine testing often makes it challenging to compare results from different studies. The aim of this work was to develop and implement a standardized testing protocol across three six-axis spine systems, compare them, and provide stiffness and phase angle limits against which other test systems can be compared. Standardized synthetic lumbar specimens (n = 5), comprising three springs embedded in polymer at each end, were tested on each system using pure moments in flexion–extension, lateral bending, and axial rotation. Tests were performed using sine and triangle waves with an amplitude of 8 Nm, a frequency of 0.1 Hz, and with axial preloads of 0 and 500 N. The stiffness, phase angle, and R2 value of the moment against rotation in the principal axis were calculated at the center of each specimen. The tracking error was adopted as a measure of each test system to minimize non-principal loads, defined as the root mean squared difference between actual and target loads. All three test systems demonstrated similar stiffnesses, with small (<14%) but significant differences in 4 of 12 tests. More variability was observed in the phase angle between the principal axis moment and rotation, with significant differences in 10 of 12 tests. Stiffness and phase angle limits were calculated based on the 95% confidence intervals from all three systems. These recommendations can be used with the standard specimen and testing protocol by other research institutions to ensure equivalence of different spine systems, increasing the ability to compare in vitro spine studies.This research was completed with the support of the Catherine Sharpe Foundation, the Enid Linder Foundation, and the University of Bath Alumni Fun

DETECTION OF PNEUMONIA BY USING NINE PRE-TRAINED TRANSFER LEARNING MODELS BASED ON DEEP LEARNING TECHNIQUES

Pneumonia is a serious chest disease that affects the lungs. This disease has become an important issue that must be taken care of in the field of medicine due to its rapid and intense spread, especially among people who are addicted to smoking. This paper presents an efficient prediction system for detecting pneumonia using nine pre-trained transfer learning models based on deep learning technique (Inception v4, SeNet-154, Xception, PolyNet, ResNet-50, DenseNet-121, DenseNet-169, AlexNet, and SqueezeNet). The dataset in this study consisted of 5856 chest x-rays, which were divided into 5216 for training and 624 for the test. In the training phase, the images were pre-processed by resizing the input images to the same dimensions to reduce complexity and computation. The images are then forwarded to the proposed models (Inception v4, SeNet-154, Xception, PolyNet, ResNet-50, DenseNet-121, DenseNet-169, AlexNet, SqueezeNet) to extract features and classify the images as normal or pneumonia. The results of the proposed models (Inception v4, SeNet-154, Xception, PolyNet, ResNet-50, DenseNet-121 DenseNet-169, AlexNet and SqueezeNet) give accuracies (98.72%, 98.94%, 98.88%, 98.72%, 96.2%, 94.69%, 96.29%, 95.01% and 96.10%) respectively. We found that the SeNet-154 model gave the best result with an accuracy of 98.94% with a validation loss (0.018103). When comparing our results with older studies, it should be noted that the proposed method is superior to other methods

Nonminimal Couplings in the Early Universe: Multifield Models of Inflation and the Latest Observations

Models of cosmic inflation suggest that our universe underwent an early phase of accelerated expansion, driven by the dynamics of one or more scalar fields. Inflationary models make specific, quantitative predictions for several observable quantities, including particular patterns of temperature anistropies in the cosmic microwave background radiation. Realistic models of high-energy physics include many scalar fields at high energies. Moreover, we may expect these fields to have nonminimal couplings to the spacetime curvature. Such couplings are quite generic, arising as renormalization counterterms when quantizing scalar fields in curved spacetime. In this chapter I review recent research on a general class of multifield inflationary models with nonminimal couplings. Models in this class exhibit a strong attractor behavior: across a wide range of couplings and initial conditions, the fields evolve along a single-field trajectory for most of inflation. Across large regions of phase space and parameter space, therefore, models in this general class yield robust predictions for observable quantities that fall squarely within the "sweet spot" of recent observations.Comment: 17pp, 2 figs. References added to match the published version. Published in {\it At the Frontier of Spacetime: Scalar-Tensor Theory, Bell's Inequality, Mach's Principle, Exotic Smoothness}, ed. T. Asselmeyer-Maluga (Springer, 2016), pp. 41-57, in honor of Carl Brans's 80th birthda

Chikungunya Masquerading as Acute Rheumatism in an Omani Traveler

Chikungunya is a mosquito-borne viral disease. It typically presents as an acute febrile illness associated with a varying degree of arthralgia and musculoskeletal sequelae. Cases of chikungunya have been reported from more than 40 countries in several continents. Chikungunya is often reported in travelers returning to non-endemic/epidemic countries. With increasing international travel, it is vital that clinicians in non-endemic areas are made aware of this rapidly spreading infection. Increasing international travel (for social, leisure, and business) between Oman and several chikungunya endemic countries including Pakistan may facilitate the introduction of chikungunya to Oman. We report the first imported case of chikungunya in an Omani traveler with a link to the current outbreak in Pakistan

The C-Terminal Domain of the Arabinosyltransferase Mycobacterium tuberculosis EmbC Is a Lectin-Like Carbohydrate Binding Module

The D-arabinan-containing polymers arabinogalactan (AG) and lipoarabinomannan (LAM) are essential components of the unique cell envelope of the pathogen Mycobacterium tuberculosis. Biosynthesis of AG and LAM involves a series of membrane-embedded arabinofuranosyl (Araf) transferases whose structures are largely uncharacterised, despite the fact that several of them are pharmacological targets of ethambutol, a frontline drug in tuberculosis therapy. Herein, we present the crystal structure of the C-terminal hydrophilic domain of the ethambutol-sensitive Araf transferase M. tuberculosis EmbC, which is essential for LAM synthesis. The structure of the C-terminal domain of EmbC (EmbCCT) encompasses two sub-domains of different folds, of which subdomain II shows distinct similarity to lectin-like carbohydrate-binding modules (CBM). Co-crystallisation with a cell wall-derived di-arabinoside acceptor analogue and structural comparison with ligand-bound CBMs suggest that EmbCCT contains two separate carbohydrate binding sites, associated with subdomains I and II, respectively. Single-residue substitution of conserved tryptophan residues (Trp868, Trp985) at these respective sites inhibited EmbC-catalysed extension of LAM. The same substitutions differentially abrogated binding of di- and penta-arabinofuranoside acceptor analogues to EmbCCT, linking the loss of activity to compromised acceptor substrate binding, indicating the presence of two separate carbohydrate binding sites, and demonstrating that subdomain II indeed functions as a carbohydrate-binding module. This work provides the first step towards unravelling the structure and function of a GT-C-type glycosyltransferase that is essential in M. tuberculosis. Author Summary Top Tuberculosis (TB), an infectious disease caused by the bacillus Mycobacterium tuberculosis, burdens large swaths of the world population. Treatment of active TB typically requires administration of an antibiotic cocktail over several months that includes the drug ethambutol. This front line compound inhibits a set of arabinosyltransferase enzymes, called EmbA, EmbB and EmbC, which are critical for the synthesis of arabinan, a vital polysaccharide in the pathogen's unique cell envelope. How precisely ethambutol inhibits arabinosyltransferase activity is not clear, in part because structural information of its pharmacological targets has been elusive. Here, we report the high-resolution structure of the C-terminal domain of the ethambutol-target EmbC, a 390-amino acid fragment responsible for acceptor substrate recognition. Combining the X-ray crystallographic analysis with structural comparisons, site-directed mutagenesis, activity and ligand binding assays, we identified two regions in the C-terminal domain of EmbC that are capable of binding acceptor substrate mimics and are critical for activity of the full-length enzyme. Our results begin to define structure-function relationships in a family of structurally uncharacterised membrane-embedded glycosyltransferases, which are an important target for tuberculosis therapy

HGF Mediates the Anti-inflammatory Effects of PRP on Injured Tendons

Platelet-rich plasma (PRP) containing hepatocyte growth factor (HGF) and other growth factors are widely used in orthopaedic/sports medicine to repair injured tendons. While PRP treatment is reported to decrease pain in patients with tendon injury, the mechanism of this effect is not clear. Tendon pain is often associated with tendon inflammation, and HGF is known to protect tissues from inflammatory damages. Therefore, we hypothesized that HGF in PRP causes the anti-inflammatory effects. To test this hypothesis, we performed in vitro experiments on rabbit tendon cells and in vivo experiments on a mouse Achilles tendon injury model. We found that addition of PRP or HGF decreased gene expression of COX-1, COX-2, and mPGES-1, induced by the treatment of tendon cells in vitro with IL-1β. Further, the treatment of tendon cell cultures with HGF antibodies reduced the suppressive effects of PRP or HGF on IL-1β-induced COX-1, COX-2, and mPGES-1 gene expressions. Treatment with PRP or HGF almost completely blocked the cellular production of PGE2 and the expression of COX proteins. Finally, injection of PRP or HGF into wounded mouse Achilles tendons in vivo decreased PGE2 production in the tendinous tissues. Injection of platelet-poor plasma (PPP) however, did not reduce PGE2 levels in the wounded tendons, but the injection of HGF antibody inhibited the effects of PRP and HGF. Further, injection of PRP or HGF also decreased COX-1 and COX-2 proteins. These results indicate that PRP exerts anti-inflammatory effects on injured tendons through HGF. This study provides basic scientific evidence to support the use of PRP to treat injured tendons because PRP can reduce inflammation and thereby reduce the associated pain caused by high levels of PGE2. © 2013 Zhang et al

An Efficient Coding Hypothesis Links Sparsity and Selectivity of Neural Responses

To what extent are sensory responses in the brain compatible with first-order principles? The efficient coding hypothesis projects that neurons use as few spikes as possible to faithfully represent natural stimuli. However, many sparsely firing neurons in higher brain areas seem to violate this hypothesis in that they respond more to familiar stimuli than to nonfamiliar stimuli. We reconcile this discrepancy by showing that efficient sensory responses give rise to stimulus selectivity that depends on the stimulus-independent firing threshold and the balance between excitatory and inhibitory inputs. We construct a cost function that enforces minimal firing rates in model neurons by linearly punishing suprathreshold synaptic currents. By contrast, subthreshold currents are punished quadratically, which allows us to optimally reconstruct sensory inputs from elicited responses. We train synaptic currents on many renditions of a particular bird's own song (BOS) and few renditions of conspecific birds' songs (CONs). During training, model neurons develop a response selectivity with complex dependence on the firing threshold. At low thresholds, they fire densely and prefer CON and the reverse BOS (REV) over BOS. However, at high thresholds or when hyperpolarized, they fire sparsely and prefer BOS over REV and over CON. Based on this selectivity reversal, our model suggests that preference for a highly familiar stimulus corresponds to a high-threshold or strong-inhibition regime of an efficient coding strategy. Our findings apply to songbird mirror neurons, and in general, they suggest that the brain may be endowed with simple mechanisms to rapidly change selectivity of neural responses to focus sensory processing on either familiar or nonfamiliar stimuli. In summary, we find support for the efficient coding hypothesis and provide new insights into the interplay between the sparsity and selectivity of neural responses

Characterization of complex networks: A survey of measurements

Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.Comment: A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the author