Miracle-dz/UniFAR-FTUs huggingface dataset:
Melioidosis in India and Bangladesh: A review of case reports

Objective: To conduct an epidemiological and clinical review of published case reports of melioidosis from India and Bangladesh. Methods: Data from published case reports were abstracted and summarized. We further compared the clinical epidemiology of the melioidosis cases in India with case series from highly endemic areas in Northern Australia and Southeast Asia to elucidate any differences in presentations and risk factors between the regions. Results: We identified a total of 99 cases published between 1953 and June 2016, originating from India (n=85) or Bangladesh (n=14). Cases were predominantly male and ranged in age from 1 month to 90 years. Diabetes mellitus was the most common risk factor reported (58%). About 28% of the cases had history of exposure via high-risk occupations or exposure to contaminated water. The overall case fatality rate (CFR) was 26%. Factors influencing mortality included the occurrence of septic shock (CFR, 80%), environmental exposure (CFR, 39%), primary presentation of pneumonia (CFR, 38%), misdiagnosed and/or mistreated cases (CFR, 33%) or the presence of a risk factor (CFR, 29%). Because of the small number of cases in Bangladesh, pattern of clinical epidemiology is limited to India. Soft tissue abscess (37%) was the most common clinical presentation reported from India followed by pneumonia (24%) and osteomyelitis/septic arthritis (18%). Neurological melioidosis (n=10, 12%) presented as pyemic lesions of the brain or meninges. A few cases of prostatic abscess (n=4) in men and parotid abscess (n=4) were also noted. The above patterns were consistent with case series from Southeast Asia and Northern Australia for the most part, in terms of risk factors associated with infection and factors influencing mortality. Differences included clinical presentation of pneumonia which was notably lower than that reported in Southeast Asia and Northern Australia; a higher proportion of neurological and parotid abscess presentation; and a lower CFR compared to that reported in case series in Southeast Asia. About 39% of the cases were misdiagnosed and/or mistreated, suggesting underreporting and under estimation of the true disease burden. Conclusions: The concentration of melioidosis cases in southern and eastern states in India and in Bangladesh, which share climatic conditions and rice farming activities with known endemic areas in Southeast Asia, suggests an endemicity of melioidosis in this region. Thus, increased awareness among healthcare personnel, particularly among clinicians and nurses practicing in rural areas, and improved surveillance through case registries is essential to guide early diagnosis and prompt treatment.
Predicting Future User Activities with Constrained Non-Linear Models

Prediction of future user activities from their history, all past activities, is a challenging problem. One reason is that the number of all potential histories grows exponentially with the length of the 4 history. Recently, deep-learning models have been proposed for solving this problem. It is easy to learn a simple predictor of future user activities, by averaging all past activities of the user and then learning an activity classifier from this average representation, for instance by logistic regression. This approach tends to have a high bias, due to using a simple feature representation and model. It is also easy to apply sequence models in deep learning to learn a predictor of future user activities. This approach tends to have a high variance, because of the large number of parameters in the neural network.
Effects of Organic Pollutants on Bacterial Communities Under Future Climate Change Scenarios

Coastal ecosystems are highly dynamic and can be strongly influenced by climate change, anthropogenic activities (e.g., pollution), and a combination of the two pressures. As a result of climate change, the northern hemisphere is predicted to undergo an increased precipitation regime, leading in turn to higher terrestrial runoff and increased river inflow. This increased runoff will transfer terrestrial dissolved organic matter (tDOM) and anthropogenic contaminants to coastal waters. Such changes can directly influence the resident biology, particularly at the base of the food web, and can influence the partitioning of contaminants and thus their potential impact on the food web. Bacteria have been shown to respond to high tDOM concentration and organic pollutants loads, and could represent the entry of some pollutants into coastal food webs. We carried out a mesocosm experiment to determine the effects of: (1) increased tDOM concentration, (2) organic pollutant exposure, and (3) the combined effect of these two factors, on pelagic bacterial communities. This study showed significant responses in bacterial community composition under the three environmental perturbations tested. The addition of tDOM increased bacterial activity and diversity, while the addition of organic pollutants led to an overall reduction of these parameters, particularly under concurrent elevated tDOM concentration. Furthermore, we identified 33 bacterial taxa contributing to the significant differences observed in community composition, as well as 35 bacterial taxa which responded differently to extended exposure to organic pollutants. These findings point to the potential impact of organic pollutants under future climate change conditions on the basal coastal ecosystem, as well as to the potential utility of natural bacterial communities as efficient indicators of environmental disturbance.
High color-fidelity display using a modified projector

A high color-fidelity display provides accurate spectral reproduction to reduce observer metamerism. In this poster, we implement a multispectral projection display using a modified projector. The modification only requires adding a lens array on the projection optical path to creates multiple copies of images and using color filters to create new primaries. To produce the new primaries with high throughput and low correlation, we proposed a volume maximization-based filter selection approach. We also present an efficient multispectral rendering algorithm to compute the input values of each primary. The experiments show that our multispectral display can accurately approximate desired multispectral images and effectively reduce observer metamerism when compared with the original three primaries projection display.
The Minimum Capacity of HVAC Secondary Systems (with Capacity Reduction by Interzonal Airflow) (RP-1049)

To date, the performance of alternative HVAC secondary systems has been compared using either the systems' energy use directly or by a life-cycle cost analysis. This paper introduces the concept of rating a system's performance by comparing its capacity at a particular operating point to the thermodynamic minimum capacity. A simple ratio, termed the “system effectiveness,” is also introduced to indicate the extent to which the system operates with the minimum possible capacity. This paper describes the calculation of the minimum system capacity as a nonlinear, single-criterion, constrained optimization problem. In particular, it describes the case for the minimization of the system capacity by use of interzonal airflow (the interzonal airflow rates and zone thermal conditions being variables of the optimization). This optimization problem is multi-modal in that the same system capacity can result from more than one interzonal airflow configuration. The optimization problem has been solved here using a genetic algorithm (GA) search method. This paper illustrates the use of the minimum system capacity as a benchmark for the performance of a typical multizone heating, ventilating, and air-conditioning (HVAC) system. The example also illustrates the potential benefit of using interzonal airflow to reduce the required capacity of a system. It can be concluded from the example that the arrangement of the system components is a significant factor in determining the thermal effectiveness of HVAC systems.
Performance characteristics of the tomography setup at the PSI NEUTRA thermal neutron radiography facility

In 1999 a setup for neutron tomography was installed at the thermal neutron radiography facility NEUTRA of the Paul Scherrer Institute's spallation neutron source SINQ. The performance characteristics of this setup have been gradually improved and many tomographic investigations have been performed for industrial and academic clients. Here we report the actual performance characteristics of the NEUTRA tomography setup. We present results of investigations where neutron tomography was successfully used for the nondestructive inspection of industrial objects. The current limitations of neutron tomography are discussed and some prospects for further improvements will be given. The PSI spallation neutron source SINQ
A continuous process for Si nanowires with prescribed lengths

A simple top–down approach for the continuous mass preparation of single crystalline silicon nanowires (SiNWs) with controlled lengths was developed. The approach is based on periodic pulsing of anodic bias during gold-assisted chemical etching of a silicon substrate and subsequent ultrasonic treatment of the resulting porosity-patterned SiNWs for selective breakage of nanowires at the porous segments, and allows us to overcome some of the drawbacks in conventional bottom–up methods for SiNW growth.
A Reference Dataset for Network Traffic Activity Based Intrusion Detection System

The network traffic dataset is a crucial part of anomaly based intrusion detection systems (IDSs). These IDSs train themselves to learn normal and anomalous activities. Properly labeled dataset is used for the training purpose. For the activities based IDSs, proper network traffic activity labeled dataset is the first requirement, however non-availability of such datasets is bottlenecked in the field of IDS research. In this experiment, a synthetic dataset "Panjab University - Intrusion Dataset (PU-IDS)" is created. The purpose of this study is to provide the researchers a reference dataset for the performance evaluation of network traffic activity based IDSs. University of New Brunswick Network Security Laboratory - Knowledge Disscovery in Databases (NSL-KDD) is a benchmark dataset for anomaly detection but it does not contain activity based labeling. So basic characteristics of this dataset are taken for the generation of the new synthetic dataset with various activities based labels. The dataset is first categorized as per protocol and service. Thereafter, as per minimum & maximum values of attributes, activity profiles are synthetically generated. This paper also discusses various statistical characteristics of PU-IDS. The total number of 198533 instances along with 273 of activity profiles are created. This dataset also contain different 98 protocol_service profiles.
Technical Note: On the use of nudging for aerosol–climate model intercomparison studies

Abstract. Nudging as an assimilation technique has seen increased use in recent years in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5 (CAM5), due to the systematic temperature bias in the standard model and the sensitivity of simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on long-wave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations, and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. Results from both CAM5 and a second aerosol–climate model ECHAM6-HAM2 also indicate that compared to the wind-and-temperature nudging, constraining only winds leads to better agreement with the free-running model in terms of the estimated shortwave cloud forcing and the simulated convective activities. This suggests nudging the horizontal winds but not temperature is a good strategy for the investigation of aerosol indirect effects since it provides well-constrained meteorology without strongly perturbing the model's mean climate.
Spatial Analyses in the Research of Land Cover Changes (A Case Study)

Abstract Increasing human activity significantly influences the geographic environment. The effects of excessive anthropogenic pressure are manifested by changes in land cover and in landscape structure, and land cover changes can particularly well observed in river valleys. In this study we aimed to determine the transformations of land use in 13.9 sq km of the Silesian Voivodeship in southern Poland, including parts of the city of Ruda Slaska and Mikolow County by analyzing changes in land cover that occurred from 1827-2012 and archival and contemporary topographic maps, and aerial photos were used as primary source materials. All materials were prepared with the use of Geographic Information Systems (GIS), using spatial analyses, such as kernel density and point density in order to define land cover structure changes. Results show the development of residential areas and the fragmentation of large structures that have occurred over the time period.
Per-Pixel Calibration for RGB-Depth Natural 3 D Reconstruction on GPU

OF THESIS Per-Pixel Calibration for RGB-Depth Natural 3D Reconstruction on GPU Ever since the Kinect brought low-cost depth cameras into consumer market, great interest has been invigorated into Red-Green-Blue-Depth (RGBD) sensors. Without calibration, a RGBD camera’s horizontal and vertical field of view (FoV) could help generate 3D reconstruction in camera space naturally on graphics processing unit (GPU), which however is badly deformed by the lens distortions and imperfect depth resolution (depth distortion). The camera’s calibration based on a pinhole-camera model and a high-order distortion removal model requires a lot of calculations in the fragment shader. In order to get rid of both the lens distortion and the depth distortion while still be able to do simple calculations in the GPU fragment shader, a novel per-pixel calibration method with look-up table based 3D reconstruction in real-time is proposed, using a rail calibration system. This rail calibration system offers possibilities of collecting infinite calibrating points of dense distributions that can cover all pixels in a sensor, such that not only lens distortions, but depth distortion can also be handled by a per-pixel D to ZW mapping. Instead of utilizing the traditional pinhole camera model, two polynomial mapping models are employed. One is a two-dimensional high-order polynomial mapping from R/C to XW/YW respectively, which handles lens distortions; and the other one is a per-pixel linear mapping from D to ZW , which can handle depth distortion. With only six parameters and three linear equations in the fragment shader, the undistorted 3D world coordinates (XW , YW , ZW ) for every single pixel could be generated in real-time. The per-pixel calibration method could be applied universally on any RGBD cameras. With the alignment of RGB values using a pinhole camera matrix, it could even work on a combination of a random Depth sensor and a random RGB sensor.
Photoelastic analysis of dynamic stress distribution around short implants restored with different materials

Aim: This study aimed at evaluating the stress distribution around a locking tapered short dental implant (4.3 mm x 6 mm), comparing crowns made of metal (CoCr), zirconium (Y-TZP) and acrylic resin. Materials and Methods: The Y-TZP and resin crowns were fabricated by CAD/CAM system, while the CoCr crown was fabricated from lost wax technique. The implant was placed in a rigid photoelastic resin in order to analyze the stress distribution using a polariscope. An axial load starting at 0 (N) up to 200 (N) was applied at the center of the occlusal aspect of the crowns. The photoelastic models and the computer screen (where the data was exhibited) were recorded by video and the images were analyzed and compared at 50N, 100N, 150N and 200N loads. Results: It was observed that resin crown model generated lower stress around the implant. Conclusion: Resin crown generated best stress distribution around locking tapered short implant in comparison with Y-TZP and CoCr crowns.
A DEEP SEARCH FOR FAINT GALAXIES ASSOCIATED WITH VERY LOW REDSHIFT C iv ABSORBERS. III. THE MASS- AND ENVIRONMENT-DEPENDENT CIRCUMGALACTIC MEDIUM

Using Hubble Space Telescope Cosmic Origins Spectrograph observations of 89 QSO sightlines through the Sloan Digital Sky Survey footprint, we study the relationships between C iv absorption systems and the properties of nearby galaxies, as well as the large-scale environment. To maintain sensitivity to very faint galaxies, we restrict our sample to , which defines a complete galaxy survey to or stellar mass . We report two principal findings. First, for galaxies with impact parameter , C iv detection strongly depends on the luminosity/stellar mass of the nearby galaxy. C iv is preferentially associated with galaxies with lower-mass galaxies rarely exhibit significant C iv absorption (covering fraction for 11 galaxies with ). Second, C iv detection within the population depends on environment. Using a fixed-aperture environmental density metric for galaxies with ρ < 160 kpc at , we find that (8/14) of galaxies in low-density regions (regions with fewer than seven galaxies within 1.5 Mpc) have affiliated C iv absorption; however, none (0/7) of the galaxies in denser regions show C iv. Similarly, the C iv detection rate is lower for galaxies residing in groups with dark matter halo masses of . In contrast to C iv, H i is pervasive in the circumgalactic medium without regard to mass or environment. These results indicate that C iv absorbers with trace the halos of galaxies but also reflect larger-scale environmental conditions.
Human Pluripotent Stem Cells as Tools for High-throughput and High-content Screening in Drug Discovery

A significant bottleneck in drug discovery is the lack of suitable models for sensitive, reliable, and rapid assessment of lead molecules in preclinical stages of drug discovery. Human pluripotent stem cells (hPSCs) derived either from early human blastocysts (human embryonic stem cells) or by reprogramming somatic cells to a pluripotent state (human-induced pluripotent stem cells) can be propagated extensively in vitro while retaining the ability to differentiate into any specialized cell type within the body. In this review, we discuss how these unique features of hPSCs could offer a way of producing relevant in vitro models amenable to high-throughput testing for drug discovery. We summarize recent progress in inducing differentiation of hPSCs to specific cell types, and describe the ongoing efforts in applying hPSCs and their differentiated derivatives in disease modeling, drug discovery, and developmental toxicology. Moreover, we review the applications of high-content imaging assays in detecting the changes in the phenotype of hPSCs and their differentiated progeny. Finally, we highlight challenges that need to be overcome in order for the application of hPSC technology to fully benefit drug discovery.
High-Speed MWIR Upconversion Spectroscopy

Infrared spectroscopy is a key technology for process analytical applications. Although stronger spectroscopic features are found in the mid-infrared at wavelengths beyond 3 μm, the near-infrared range is often favored due to better detector performance. In this work, continuous-wave nonlinearoptical upconversion is used to transfer signals from the mid-wave infrared to the near-infrared range where high-speed and high-sensitivity detectors are readily available. A grating spectrometer device for the mid-wave range, based on nonlinear-optical upconversion is presented as a promising tool for high-speed mid-infrared spectroscopy. The system is characterized for resolution and sensitivity. The high spectra acquisition rate allows combustion analysis in the wavelength range from 3.7 to 4.7 μm with outstanding time resolution.
THE LINEAR CAUCHY PROBLEM FOR A CLASS OF DIFFERENTIAL EQUATIONS WITH DISTRIBUTIONAL COEFFICIENTS

We consider the problem X = ∑n i=1 UiX (n−i) + V , X(t0) = ai in dimension 1 (X ∈ D′ is unknown, n is a positive integer, V ∈ D′, U1, ., Un ∈ C∞⊕D′p m, D′p m = D′p ∩ D′ m, D′p is the space of distributions of order ≤ p in the sense of Schwartz, D′ m is the space of distributions with nowhere-dense support, a1, ., an ∈ C and t0 ∈ IR). Necessary and sufficient conditions for existence and uniqueness of this problem in C ⊕D′ m where q = max(n, n− 1 + p) are given and also the way of getting an explicit solution when it exists. The solutions are considered in a generalized sense defined with the help of the distributional product we introduced in [2] and they are consistent with the usual solutions. As an example we takeX (t) = i g δ(t)X(t), X(t0) = 1 for a certain t0 < 0 (i = √ −1, g ∈ IR and δ is the Dirac measure) and we prove that in our sense, its unique solution in C ⊕D′ m is X(t) = 1 + i g δ(t) (Colombeau [1] also considers this problem with another approach). More examples are presented.