Miracle-dz/UniFAR-FTUs huggingface dataset:
Approximate Message Passing Reconstruction of Quantitative Acoustic Microscopy Images

A novel framework for compressive sensing (CS) data acquisition and reconstruction in quantitative acoustic microscopy (QAM) is presented. Three different CS patterns, adapted to the specifics of QAM systems, were investigated as an alternative to the current raster-scanning approach. They consist of diagonal sampling, a row random, and a spiral scanning pattern and can all significantly reduce both the acquisition time and the amount of sampled data. For subsequent image reconstruction, we design and implement an innovative technique, whereby a recently proposed approximate message passing method is adapted to account for the underlying data statistics. A Cauchy maximum a posteriori image denoising algorithm is thus employed to account for the non-Gaussianity of QAM wavelet coefficients. The proposed methods were tested retrospectively on experimental data acquired with a 250- or 500-MHz QAM system. The experimental data were obtained from a human lymph node sample (250 MHz) and human cornea (500 MHz). Reconstruction results showed that the best performance is obtained using a spiral sensing pattern combined with the Cauchy denoiser in the wavelet domain. The spiral sensing matrix reduced the number of spatial samples by a factor of 2 and led to an excellent peak signal-to-noise ratio of 43.21 dB when reconstructing QAM speed-of-sound images of a human lymph node. These results demonstrate that the CS approach could significantly improve scanning time, while reducing costs of future QAM systems.
A soluble inorganic pyrophosphatase from the cattle tick Rhipicephalus microplus capable of hydrolysing polyphosphates

Polyphosphates have been found in all cell types examined to date and play diverse roles depending on the cell type. In eukaryotic organisms, polyphosphates have been investigated mainly in mammalian cells, and only a few studies have addressed arthropods. Pyrophosphatases have been shown to regulate polyphosphate metabolism. However, these studies were restricted to trypanosomatids. Here we focus on the tick Rhipicephalus microplus, a haematophagous ectoparasite that is highly harmful to cattle. We produced a recombinant R. microplus pyrophosphatase (rRmPPase) with the aim of investigating its kinetic parameters using polyphosphates as substrate. Molecular docking assays of RmPPase with polyphosphates were also carried out. The kinetic and Hill coefficient parameters indicated that rRmPPase has a greater affinity, higher catalytic efficiency and increased cooperativity for sodium phosphate glass type 15 (polyP15) than for sodium tripolyphosphate (polyP3). Through molecular docking, we found that polyP3 binds close to the Mg2+ atoms in the catalytic region of the protein, participating in their coordination network, whereas polyP15 interactions involve negatively charged phosphate groups and basic amino acid residues, such as Lys56, Arg58 and Lys193; polyP15 has a more favourable theoretical binding affinity than polyP3, thus supporting the kinetic data. This study shows, for the first time in arthropods, a pyrophosphatase with polyphosphatase activity, suggesting its participation in polyphosphate metabolism.
Body Mass, Total Body Fat and Visceral Fat Percentage Predict Insulin Resistance Better Than Waist Circumference and Body Mass Index in Healthy Young Male Adult in Indonesia

The incidence of obesity which leads to insulin resistance (IR) and metabolic disorder increases in developing countries including Indonesia. Male adult has higher risk to have abdominal obesity than female which is associated with cardiometabolic disorders. Several anthropometric measurements have been proposed to predict IR. The aim of this study was to investigate whether body mass, body mass index (BMI), waist circumference (WC), body fat percentage (BF) or visceral fat percentage (VF) could become a better predictor of IR in healthy young male adult. Total of 140 healthy young male adults ranging from 18-25 years were recruited in the study. Insulin resistance was measured by calculating Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). Subjects with HOMA-IR value >75th percentile with cut off 3.75 were defined as IR. Anthropometric measurements included body weight, BMI, WC were performed whereas BF and VC were measured by bioelectrical impedance analysis (BIA). IR had significant strong correlation with body weight, BMI, WC, BF and VF. The area under curve of body mass, BF, VF were greater than WC and BMI. Anthropometric measurements correlated strongly with IR but body weight, BF, VF have stronger correlation than WC and BMI in healthy young male adult.
Attacks on Physically-Embedded Data Encryption for Embedded Devices

Data encryption is the primary method to protect embedded devices in the hostile environment. The security of the traditional data encryption algorithms relies on keeping the keys secret and they always require a lot of arithmetic and logical computations, which may be not suitable for area critical or power critical embedded devices. At TrustCom 2013, Hou et al. Proposed to use a physical unclonable function (PUF) to build a novel physically-embedded data encryption (PEDE) for embedded devices. The PEDE is lightweight since all it does is xor-ing the plaintext with the output of a PUF. As the PUF is unique and unclonable, only the original physical device can decrypt the cipher text. Without possessing the original PEDE device, adversaries could not determine anything about the plaintext even if both the secret key and the cipher text are available to them. In this paper, we show that the existing PEDE architecture is sensitive to environmental variations, which leads to the fact that the decrypted plaintext does not equal to the original plaintext. Besides the lack of reliability, we also show that the existing PEDE architecture is vulnerable to known-plaintext attack and modeling attack. To address these issues, we propose a secure and robust PEDE architecture.
Cytomegalovirus viral load in cord blood and impact of congenital infection on markers of hematopoietic progenitor cell potency

The low incidence of cytomegalovirus (CMV) infection in neonates decreases the risk of viral transmission with cord blood transplantation. Cord blood donors are screened by testing the maternal sample for total antibodies to CMV. Some cord blood banks also screen cord blood for CMV‐DNA. The aim of this study was to develop and validate a multiplex real‐time polymerase chain reaction assay to measure CMV viral load in cord blood from asymptomatic infants with congenital CMV infection and to assess the impact of CMV infection on cord blood hematopoietic progenitor cell concentrations and colony‐forming unit functionality.
Device-free: an implicit personalisation approach for public interactive displays

Previous research on making public interactive displays more relevant to passers-by has focused on using profiles to personalise the content. However, profiles can potentially compromise privacy and may also create barriers for interaction as implementations usually require users to set up a personal profile, for example, through a smartphone app. In this paper, we explore an implicit personalisation approach for public interactive displays as an alternative to user profiles. We present findings from two evaluation studies of public interactive displays that implicitly adapt the display, based on a user's goals and characteristics. From these studies, we build on our definition of implicit personalisation and derive insights into how the user interface and content on public interactive displays should adapt in order to be perceived relevant by their users.
A deep reinforcement learning approach to preserve connectivity for multi-robot systems

Multi-robot systems have been extensively studied for potential values in various areas and the connectivity within mobile robots plays an important role in many coordination and cooperative applications. In this paper, we adopt a DDPG-based learning framework to address the connectivity preservation problem for multi-robot system. In the implemented framework, a multi-robot simulation environment is developed to provide states and reward feedbacks to the learning agent based on a actor-critic architecture. The DDPG-based agent applies fully connected neural networks to parameterize a Q-function and a policy function. The adopted learning framework and implemented components (the networks and the simulator) can successfully solve the connectivity preservation problem and they are validated by a set of simulation experiments.
Economic burden following allogeneic hematopoietic stem cell transplant in patients with diffuse large B-cell lymphoma

Abstract This study describes short-term and long-term healthcare resource utilization (HRU) and costs following an allogeneic hematopoietic stem cell transplant (HSCT) in adult patients with diffuse large B-cell lymphoma (DLBCL) in a real-world setting. Among 101 patients with DLBCL receiving an allogeneic HSCT, HRU and direct healthcare costs for up to three years after the allogeneic HSCT are described. HRU and costs were substantial, with the most intensive HRU and highest healthcare costs observed during the first year after HSCT (38 inpatient days; 68 days with office visits and average healthcare costs of $455,741). Although HRU and costs decreased over time, they remained high even in the third year after HSCT (four inpatient days; 27 days with office visits and average healthcare costs of $72,957). Overall, this study showed that the economic burden following an allogeneic HSCT in DLBCL patients is significant.
Broadband High-Power W-Band Amplifier MMICs Based on Stacked-HEMT Unit Cells

This paper reports on a broadband high-power amplifier (HPA) millimeter-wave integrated circuit (MMIC) covering the extended W-band (65–125 GHz). The MMIC is based on the Fraunhofer IAF 50-nm gate-length metamorphic high-electron-mobility transistor (mHEMT) technology. The HPA consists of two parallelized unit amplifiers. Each unit amplifier (UA) utilizes four stacked-HEMT unit power cells (UPCs) and four-way power combiners at the input and output. The UPCs stack four transistors with a gate width of $4\times 40~\mu \text{m}$ per HEMT. The UA achieves an average small-signal gain of 19.4 dB and an average saturated output power of 21.6 dBm at least from 70 to 110 GHz. The HPA yields an average small-signal gain of 16.8 dB and an average saturated output power of 22.5 dBm at least from 68 to 110 GHz. A peak output power of 24.1 dBm is achieved at an operating frequency of 75 GHz.
Siderophores and Pathogenecity of Microorganisms

Introduction: The ability of pathogenic microorganisms of obtaining iron from host is essential for its survival. Microorganisms require iron for a variety of metabolic processes, so they synthesize and secrete small organic molecules called siderophores that actively chelate iron. The study was carried out to compare the results of siderophore produced by commensals & clinical isolates and co-relate it to pathogenecity. Materials & Methods: De ete ect tion of mic cro ob bi ial l sider rophore p pr roduction w was ca arri ie ed out t qual li itat tivel ly by t the chrome azurol sulfonate (CAS) pla ate a assay. Spectrophotometric assay (Liquid CAS assay) was used for quantitative estimation of siderophore produced by the organisms. Qualitative assay for determining type of siderophore was also carried by Arnow’s & Csaky’s methods. Results: The commensals & the isolates from clinical samples did not show any significant difference in the production of siderophore. It was also observed that the optimum condition for siderophore production by both the commensals & the clinical isolates was at 370C for 24 hours with aeration in an iron deficient medium. Conclusion: One cannot use siderophore production as a determinant of virulence of an organism. Thus, it is concluded that siderophore production may be a necessary feature of a bacterium, but not a determinant of virulence. The siderophore producing potential of a pathogen in vivo cannot be decided on basis of in-vitro assays. But applications of siderophores could be many if well studied.
A cooperative spectrum sensing algorithm based on unsupervised learning

Spectrum sensing is an essential problem in cognitive radio and has been discussed a lot in recent years. In this paper, a cooperative sensing algorithm based on unsupervised learning is proposed. The unsupervised learning framework that does not require the training data to be labeled, including K-means clustering and Gaussian mixture model, is introduced into the scheme. The more robust features including eigenvector and eigenvalue are fed into the classifier. Simulation results are shown to illustrate the performance of the proposed algorithm.
Multi-Disciplinary Research Issues in Cloud Computing

Cloud computing, characterized by on demand availability of resources is gaining a lot of popularity in the present day business scenario. This new computing paradigm is predicted to revolutionize the Information Technology industry with its dynamic and scalable capabilities. Cloud computing is catering to the needs of a wide variety of users, across the different parts of the world with its huge number of offerings. Information technology resources are offered as services over the Internet, which leads to a number of technical and management concerns. Data is stored away from the users' premises, leading to various challenges in maintaining security, privacy and regulatory compliances. Therefore, cloud computing does not involve single discipline rather multi-discipline. Considering this multi-disciplinary involvement, current work focuses on identification of research issues in the cloud computing environment, and categorizing these issues in the technical, legal and management domains. Work further discusses the multi-disciplinary research areas where cloud computing is currently focused and suggests the potential areas for further research.
Automatic depth scanning system for 3D infrared thermography

Abstract Infrared thermography can be used as a pre-, intra- and post-operative imaging technique during medical treatment of patients. Modern infrared thermal cameras are capable of acquiring images with a high sensitivity of 10 mK and beyond. They provide a planar image of an examined 3D object in which this high sensitivity is only reached within a plane perpendicular to the camera axis and defined by the focus of the lens. Out of focus planes are blurred and temperature values are inaccurate. A new 3D infrared thermography system is built by combining a thermal camera with a depth camera. Multiple images at varying focal planes are acquired with the infrared camera using a motorized system. The sharp regions of individual images are projected onto the 3D object’s surface obtained by the depth camera. The system evaluation showed that deviation between measured temperature values and a ground truth is reduced with our system.
Enhanced mechanical properties of multifunctional multiscale glass/carbon/epoxy composite reinforced with carbon nanotubes and simultaneous carbon nanotubes/nanoclays

Hybrid composites are being used in a wide variety of applications especially in the aircraft industry. Therefore, it would be of great use to develop a hybrid composite with a high mechanical performance. With this premise, this studyaimed to imbed secondary nanoscale reinforcement into the matrix of glass/carbon/epoxy composite where amino multi-walled carbon nanotubes and hybridization of amino multi-walled carbon nanotube and Nanoclay (Cloisite 30B) were utilized. The tensile, flexural and impact properties of hybrid composites were evaluated and a comparative study between hybrid composite reinforced with amino-MWCNTs and simultaneous amino-MWCNTs and Nanoclay was conducted. The fractured surfaces of tensile testing and bending testing specimens were characterized with a high precise field emission scanning electron microscopy. The results of the tensile test revealed that incorporation of amino-MWCNTs reduced the ultimate strength of hybrid composite, while the elastic modulus of composite with combination of amino-MWCNTs and Nanoclay increased. It was demonstrated that incorporation of nanotubes and simultaneous presence of both amino MWCNTs and Nanoclay could enhance exclusively the flexural strength of conventional hybrid composite by up to 10.5% and 22% respectively. Also, simultaneous presence of nano-fillers resulted in 12.2% enhancement of impact strength of hybrid composite where amino-MWCNTs exclusively increased it by up to 49.9%. Morphological characterization of composites indicated to strengthen interfacial interaction of fabrics to epoxy when matrix reinforced with nano-fillers, especially in combination of both nanotubes and nanoclays.
Gold Nanoparticles as Carrier(s) for Drug Targeting and Imaging

Nanotechnology has been explored for its prospective to deliver bioactives in potentially safer concentrations through both passive and active targeting. Inorganic nanomaterials particularly gold nanoparticles find tremendous applications in biomedicine. In this review, common synthesis techniques and biofunctionalization strategies and areas of applications for gold nanoparticles are discussed. Gold nanoparticles can be considered as advanced platforms for combined therapeutic and diagnostic applications due to their unique physicochemical properties including large specific surface area, adaptability to surface modification, biocompatibility and stability. Further they possess photothermal and radiosensitization characteristics. They possess unique properties in terms of their use in drug delivery, therapeutic, biodiagonostics and imaging applications.
CSI-Based Device-Free Wireless Localization and Activity Recognition Using Radio Image Features

Device-free wireless localization and activity recognition is an emerging technique, which could estimate the location and activity of a person without equipping him/her with any device. It deduces the state of a person by analyzing his/her influence on surrounding wireless signals. Therefore, how to characterize the influence of human behaviors is the key question. In this paper, we explore and exploit a radio image processing approach to better characterize the influence of human behaviors on Wi-Fi signals. Traditional methods deal with channel state information (CSI) measurements on each channel independently. However, CSI measurements on different channels are correlated, and thus lots of useful information involved with channel correlation may be lost. This motivates us to look on CSI measurements from multiple channels as a radio image and deal with it from the two-dimensional perspective. Specifically, we transform CSI measurements from multiple channels into a radio image, extract color and texture features from the radio image, adopt a deep learning network to learn optimized deep features from image features, and estimate the location and activity of a person using a machine learning approach. Benefits from the informative and discriminative deep image features and experimental results in two clutter laboratories confirm the excellent performance of the proposed system.
Deep feature selection and projection for cross-age face retrieval

While traditional PIE (pose, illumination and expression) face variations have been well settled by latest methods, a new kind of variation, cross-age variation, is drawing attention from researchers. Most of the existing methods fail to maintain the effectiveness in real world applications that contain significant gap of age. Cross-age variation is caused by the shape deformation and texture changing of human faces while people getting old. It will result in tremendous intra-personal changes of face feature that deteriorate the performance of algorithms. This paper proposed a deep feature based framework for face retrieval problem. Our framework uses deep CNNs feature descriptor and two well designed post-processing methods to achieve age-invariance. To the best of our knowledge, this is the first deep feature based method in cross-age face retrieval problem. The deep CNNs model we use is firstly trained on traditional PIE datasets and then fine-tuned by cross-age dataset. The feature selection and projection post-processing we propose is also proved to be very effective in eliminating cross-age variation of deep CNNs feature. The experiments conducted on Cross-Age Celebrity Dataset (CACD), which is the largest public dataset containing cross-age variation, show that our framework outperforms previous state-of-the-art methods.
Predictors for Symptomatic Intracranial Hemorrhage After Endovascular Treatment of Acute Ischemic Stroke

Background and Purpose— Symptomatic intracranial hemorrhage (SICH) pose a major safety concern for endovascular treatment of acute ischemic stroke. This study aimed to evaluate the risk and related factors of SICH after endovascular treatment in a real-world practice. Methods— Patients with stroke treated with stent-like retrievers for recanalizing a blocked artery in anterior circulation were enrolled from 21 stroke centers in China. Intracranial hemorrhage was classified as symptomatic and asymptomatic ones according to Heidelberg Bleeding Classification. Logistic regression was used to identify predictors for SICH. Results— Of the 632 enrolled patients, 101 (16.0%) were diagnosed with SICH within 72 hours after endovascular treatment. Ninety-day mortality was higher in patients with SICH than in patients without SICH (65.3% versus 18.8%; P<0.001). On multivariate analysis, baseline neutrophil ratio >0.83 (odds ratio [OR], 2.07; 95% confidence interval [CI], 1.24–3.46), pretreatment Alberta Stroke Program Early Computed Tomography Score of <6 (OR, 2.27; 95% CI, 1.24–4.14), stroke of cardioembolism type (OR, 1.91; 95% CI, 1.13–3.25), poor collateral circulation (OR, 1.97; 95% CI, 1.16–3.36), delay from symptoms onset to groin puncture >270 minutes (OR, 1.70; 95% CI, 1.03–2.80), >3 passes with retriever (OR, 2.55; 95% CI, 1.40–4.65) were associated with SICH after endovascular treatment. Conclusions— Incidence of SICH after thrombectomy is higher in Asian patients with acute ischemic stroke. Cardioembolic stroke, poor collateral circulation, delayed endovascular treatment, multiple passes with stent retriever device, lower pretreatment Alberta Stroke Program Early Computed Tomography Score, higher baseline neutrophil ratio may increase the risk of SICH.