Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Convolutional Nets Learning Classification for Artistic Style Transfer

Humans have mastered the skill of creativity for many decades. The process of replicating this mechanism is introduced recently by using neural networks which replicate the functioning of human brain, where each unit in the neural network represents a neuron, which transmits the messages from one neuron to other, to perform subconscious tasks. Usually, there are methods to render an input image in the style of famous art works. This issue of generating art is normally called nonphotorealistic rendering. Previous approaches rely on directly manipulating the pixel representation of the image. While using deep neural networks which are constructed using image recognition, this paper carries out implementations in feature space representing the higher levels of the content image. Previously, deep neural networks are used for object recognition and style recognition to categorize the artworks consistent with the creation time. This paper uses Visual Geometry Group (VGG16) neural network to replicate this dormant task performed by humans. Here, the images are input where one is the content image which contains the features you want to retain in the output image and the style reference image which contains patterns or images of famous paintings and the input image which needs to be style and blend them together to produce a new image where the input image is transformed to look like the content image but “sketched” to look like the style image.
Liver Bacterial Dysbiosis With Non-Tuberculosis Mycobacteria Occurs in SIV-Infected Macaques and Persists During Antiretroviral Therapy

Liver disease is a significant contributor to morbidity and mortality in HIV-infected individuals, even during successful viral suppression with combination antiretroviral therapy (cART). Similar to HIV infection, SIV infection of rhesus macaques is associated with gut microbiome dysbiosis and microbial translocation that can be detected systemically in the blood. As microbes leaving the intestines must first pass through the liver via the portal vein, we evaluated the livers of both SIV-infected (SIV+) and SIV-infected cART treated (SIV+cART) rhesus macaques for evidence of microbial changes compared to uninfected macaques. Dysbiosis was observed in both the SIV+ and SIV+cART macaques, encompassing changes in the relative abundance of several genera, including a reduction in the levels of Lactobacillus and Staphylococcus. Most strikingly, we found an increase in the relative abundance and absolute quantity of bacteria within the Mycobacterium genus in both SIV+ and SIV+cART macaques. Multi-gene sequencing identified a species of atypical mycobacteria similar to the opportunistic pathogen M. smegmatis. Phosphatidyl inositol lipoarabinomannan (PILAM) (a glycolipid cell wall component found in atypical mycobacteria) stimulation in primary human hepatocytes resulted in an upregulation of inflammatory transcriptional responses, including an increase in the chemokines associated with neutrophil recruitment (CXCL1, CXCL5, and CXCL6). These studies provide key insights into SIV associated changes in hepatic microbial composition and indicate a link between microbial components and immune cell recruitment in SIV+ and SIV+cART treated macaques.
Self-Protected Virtual Sensor Network for Microcontroller Fault Detection

This paper introduces a procedure to compare the functional behaviour of individual units of electronic hardware of the same type. The primary use case for this method is to estimate the functional integrity of an unknown device unit based on the behaviour of a known and proven reference unit. This method is based on the so-called virtual sensor network (VSN) approach, where the output quantity of a physical sensor measurement is replicated by a virtual model output. In the present study, this approach is extended to model the functional behaviour of electronic hardware by a neural network (NN) with Long-Short-Term-Memory (LSTM) layers to encapsulate potential time-dependence of the signals. The proposed method is illustrated and validated on measurements from a remote-controlled drone, which is operated with two variants of controller hardware: a reference controller unit and a malfunctioning counterpart. It is demonstrated that the presented approach successfully identifies and describes the unexpected behaviour of the test device. In the presented case study, the model outputs a signal sample prediction in 0.14 ms and achieves a reconstruction accuracy of the validation data with a root mean square error (RMSE) below 0.04 relative to the data range. In addition, three self-protection features (multidimensional boundary-check, Mahalanobis distance, auxiliary autoencoder NN) are introduced to gauge the certainty of the VSN model output.
The wireless networking research based on Zstack

Zstack is an industry-leading ZigBee protocol stack launched by TI company, it includes protocol stack that covers almost all of the features of mesh and network topology, and occupies a very important position in the fierce competitive zigbee field. This paper describes software framework of Zstack protocol stack, and realizes the wireless communication in the experimental platform, its purpose is to master the basic principles and methods of wireless network communication based on Zstack.
Hematological Parameters and Iron Status in Adult Men and Women Using Altitude Adjusted and Unadjusted Hemoglobin Values for Anemia Diagnosis in Cusco, Peru (3400 MASL)

(1) Background: Current diagnosis of anemia in high altitude populations uses an adjustment of observed hemoglobin (Hb) values. Such an approach has been challenged by findings in different populations in Tibet, Ethiopia and the Andes as inappropriate, as it might incorrectly classify an individual with complete iron stores as anemic. We aimed to assess the suitability of this approach in adult men and women from Cusco, Peru (3400 m); (2) Methods: Complete blood count and iron status biomarkers were measured in 345 subjects (189 females and 156 males), iron status biomarkers were quantified with enzyme-linked immunoassays; (3) Results: Anemia prevalence was overestimated when the altitude-adjustment factor was applied. Hematological parameters were better correlated to iron status biomarkers in the non-adjusted anemia category. When stratified by sex, only women showed a significant association between Hb and other hematological parameters with iron storage and availability (Hepcidin and TFR-F); (4) Conclusion: The prevalence of anemia is overestimated with current guidelines. The rate of anemia using non-adjusted Hb values is more closely related to the rates of anemia or iron deficiency when used hematological parameters, markers of iron status, and measurements of hepcidin and erythropoietin. Sex differences related to iron status were observed, suggesting that men are at a higher risk of iron overload than women at high altitudes. It could be highlighted that a personalized approach is important when assessing a subject, taking in to account hematological parameters as well as origin (Southern Andean or other).
Direct Energy Link Aware Opportunistic Routing in Mobile Hybrid Networks

The proliferation of mobile and IoT devices coupled with the advances in the wireless communication capabilities of these devices have urged the need for novel communication paradigms for such heterogeneous hybrid network. Researchers have proposed opportunistic routing as a mean to leverage the potentials offered by such heterogeneous networks. While multiple opportunistic routing protocols have been proposed, few have explored the presences of Direct Energy (DE) links in the network to construct stable and faster paths towards destinations. We propose DELAR, a novel Direct Energy Link Aware geographic Routing protocol that leverages the presence of DE links to assign forwarding candidates towards a given destination. We implement DELAR based on the DSDV proactive protocol advertisement messages, and simulate the performance of our solution using NS3. Our simulation results show that DELAR achieves better success delivery ratio by constructing paths on the fly to the destination node when DSDV fail to pre-establish and end-to-end path to the same destination.
Nonsense-Mediated mRNA Decay, a Finely Regulated Mechanism

Nonsense-mediated mRNA decay (NMD) is both a mechanism for rapidly eliminating mRNAs carrying a premature termination codon and a pathway that regulates many genes. This implies that NMD must be subject to regulation in order to allow, under certain physiological conditions, the expression of genes that are normally repressed by NMD. Therapeutically, it might be interesting to express certain NMD-repressed genes or to allow the synthesis of functional truncated proteins. Developing such approaches will require a good understanding of NMD regulation. This review describes the different levels of this regulation in human cells.
Comparative Study of High Torque Density Spoke-Type PM In-Wheel Motors for Special Vehicle Traction Applications

With the development of the transportation electrification, the demand for high-performance motor is growing rapidly. High torque density and wide constant power operating range are two key requirements of the electric vehicle (EV) traction applications. Considering the limited voltage and current, a successful EV traction machine should realize good linearity of torque–current characteristic and a proper characteristic current. In order to meet these strict demands, an optimized Fractional-Slot Concentrated-Winding(FSCW) permanent magnet (PM) machine with different rotor structures is proposed in this article based on the traditional spoke-type PM machine topology. The machine structures are introduced and optimized in the design procedure, and a magnetic equivalent circuit model is applied to illustrate its principle. The electromagnetic performances, including back electromotive force, output torque, and efficiency map, are compared between the original and optimized design to highlight the performance improvement of the optimized topology. Finally, a prototype machine has been built for the experimental validation. The experimental results, which agree well with the Finite Element (FE)-predicted results, confirm the validity of the analysis method used in predictions and the advantages of the optimized design.
The effect of coal-derived humic substances and their silver-containing bionanocomposites on arginine balance in peritoneal macrophages of intact mice

Background. Antigen-presenting cells (APCs), especially macrophages, play an important role in the body defense against various pathogens. Their dysfunction and polarization are associated with most inflammatory and autoimmune diseases. The inflammatory process is regulated by activation and / or inhibition of genes differentially expressed by macrophages. Successful correction of inflammation leads firstly to elimination of inflammatory stimuli and then to remodeling and restoration of tissues and organs. It was experimentally confirmed that silvercontaining bionanocomposites based on natural humic substances (HS) obtained from coal of different origin, as well as initial matrices of these HS, are capable of activating pro- and anti-inflammatory properties of macrophages.Aim. To study cytotoxic, pyrogenic, and immunomodulatory properties (arginine balance) of initial HS samples and samples of silver nanoparticles ultradispersed in these HS matrices (HS-AgNPs) in the cell culture of peritoneal macrophages, as well as their effect on pro- and anti-inflammatory properties of APCs.Materials and methods. Cultural and biochemical methods were used in the study.Results. The study showed that the samples CHE-K, CHE-AgNPs, CHS-K, and CHP-K increased M1 macrophage polarization due to stimulation of the NO-synthase activity and inhibition of arginase. The samples CHI-K, CHIAgNPs, CHP-AgNPs, and CHS-AgNPs modulated an alternative M2 or M2-like state of macrophage activation. At the same time, HS are not cytotoxic at effective concentrations, and three out of four studied samples did not contain pyrogenic impurities.Conclusion. The use of HS and their silver-containing bionanocomposites, which have the ability to greatly affect the polarization of antigen-presenting cells, is a promising research area in correction of the inflammatory response for solving an important social and medical problem of treating chronic wounds.
Novel Datasets for Evaluating Song Popularity Prediction Tasks

Estimating the success of a song before its release is an important music industry task. Current work uses audio descriptors to predict the success (popularity) of a song, where typical measures of success are chart measures such as peak position and streaming measures such as listener-count. Currently, a wide range of datasets is used for that purpose, but most of them are not publicly available; likewise, available datasets are restricted either in size, available features, or popularity measures. This substantially impedes the evaluation of the predictive power of a wide range of models. Therefore, we present two novel datasets called HSP-S and HSP-L based on data from AcousticBrainz, Billboard Hot 100, the Million Song Dataset, and last.fm. Both datasets contain audio features, Mel-spectrograms as well as streaming listener- and play-counts. The larger HSP-L dataset contains 73,482 songs, whereas the smaller HSP-S dataset contains 7,736 songs and additionally features Billboard Hot 100 chart measures. In contrast to previous publicly available datasets, our datasets contain substantially more songs and richer and more diverse features. We solely utilize data from the public domain, allowing to evaluate and compare a wide range of models on our datasets. To demonstrate the use of the datasets, we perform a regression and a classification (popular/unpopular) task on both datasets using a wide variety of models to predict song popularity for all target measures.
A compact circularly polarized half‐mode substrate integrated waveguide‐based leaky‐wave antenna array with wide range of dual‐beam scanning

In this article, a compact circularly polarized (CP) leaky‐wave antenna (LWA) array based on half‐mode substrate integrated waveguide (HMSIW) structure is proposed, which has the capability of dual‐beam scanning in wide range through broadside. This array consists of two HMSIW LWAs with periodic π‐shaped slots, which can excite‐first space harmonic mode with CP waves, and an HMSIW power‐recycling semicircular structure, which is designed between the end of the first LWA and the start of second LWA to generate two symmetrical scanning beams. Moreover, the structure of this array is optimized to make the two beams have similar gain values. The results validate that the proposed array has one CP beam scanning from −62 to 14° and another CP beam scanning from 60 to −16° when the operating frequency changes from 5.2 to 7.5 GHz. The measured gains and axial ratios are also given and show good agreements with the full‐wave simulated results.
A Simple Method for the Detection of Biofilms Using a Heatable Capacitive Sensor Structure (CSS): Description, Proof of Concept, and Some Technical Improvements

This article presents a novel method for the detection of biofilms based on a heatable, capacitive sensor structure (CSS). Biofilms are capable of strongly binding large amounts of water to their extracellular biopolymer matrix, which is detectable via its dielectric properties. A main challenge is to determine the difference between the inherent occurring presence of moisture in the ecosystem, which is necessary to form a biofilm and an actual formed biofilm. Therefore, the CSS is carefully heated to evaporate unbound surface moisture and determine whether there is a remaining residual alternation of the capacitance in comparison to the dry state. As a reproduceable substitute for complex, real biofilms, a hygroscopic, medical hydrogel-based on polysaccharides was used and applied by spray coating. Printed circuit boards (PCB) in different geometries and materials were used as CSS and compared in terms of their performance. A layer-thickness of 20 µm for the hydrogel coating to be sufficiently detected was defined as a realistic condition based on known values for real biofilms cited in literature. For this thickness a double-meander structure proves to be preferable over interdigitating and spiral geometries. It does offer a 30% lower, yet sufficient sensitivity, but shows advantages in manufacturing (one layer instead of two) and conductive heating capability. In the experiments, free water showed virtually no residual change, while the hydrogel-coated CSS still shows an approx. 300% higher value compared to a dry capacity. Yet, the overall small capacities of about 6–30 pF in dry state are difficult to measure and therefore sensitive to interferences and noise, which results in a high deviation. The principle of measurement can be evaluated as proofed by the carried out experiments, though offering room for improvement in the design of the study. The new method might be especially useful for pipes (e.g., hydrodynamically ineffective sensors installed in a pipe wall) if they at least are not permanently flooded with an aqueous medium, but can occasionally dry. If the internal surface is still only moist, it can be dried by initial heating.
Perceived HIV stigmatization and association with cervical screening adoption among HIV-positive women in a Nigerian Secondary Health Facility: Implications for psychological interventions

Abstract HIV-positive women are at risk of cervical cancer, but many barriers hinder them from adopting cervical screening. Therefore, focus group discussions and in-depth interviews were conducted to explore perceived HIV stigmatization and association with cervical screening adoption in a sample of HIV-positive women who never screened for cervical cancer. It was found that participants who had not disclosed their HIV status to others did not experience perceived HIV stigmatization. Further, perceived HIV stigmatization did not hinder cervical screening adoption due to assertiveness among participants. Those who had not experienced perceived HIV stigmatization due to non-status disclosure were unaware of their susceptibility to cervical cancer. Some participants who had not experienced perceived HIV stigmatization were aware of cervical cancer but were reluctant to screen due to religion-related denial. Some participants who experienced perceived HIV stigmatization perceived that the experience hindered cervical screening adoption. Our findings will inform psychological interventions that may strengthen cervical screening adoption in this patient group.
The Effect of Ultrasonic Treatment on the Binding of the Inclusion Complex β-Cyclodextrin-peppermint Oil with Cellulose Material

The purpose of the research was to measure the increase in the binding of inclusion complexes β-cyclodextrin-peppermint oil (β-CD_PM) to cellulose in cotton and cotton/polyester material with BTCA as the crosslinking agent by applying an ultrasonic bath at room temperature and a frequency of 80 kHz for 10 min. After sonication, the samples were left in a bath for 24 h after which they were dried, thermocondensed and subjected to a number of wash cycles. The treated samples were analysed with Attenuated total reflection (ATR) units heated up to 300 °C (Golden Gate (FTIR-ATR)) to monitor chemical changes indicative of crosslinking, while physico-chemical changes in the samples were monitored by using Fourier transform infrared spectroscopy (FTIR-ATR). Mechanical properties were measured according to EN ISO 13934-1:1999, and coloristic changes were evaluated by the whiteness degree according to CIE (WCIE) and the yellowing index (YI), while antimicrobial activity was determined according to AATCC TM 147-2016. The results show a physico-chemical modification of the UZV-treated cellulosic material. Moreover, partial antimicrobial efficacy on Gram-negative bacteria was confirmed for treated fabrics.
Traffic Light and Back-light Recognition using Deep Learning and Image Processing with Raspberry Pi

Traffic light detection and back-light recognition are essential research topics in the area of intelligent vehicles because they avoid vehicle collision and provide driver safety. Improved detection and semantic clarity may aid in the prevention of traffic accidents by self-driving cars at crowded junctions, thus improving overall driving safety. Complex traffic situations, on the other hand, make it more difficult for algorithms to identify and recognize objects. The latest state-of-the-art algorithms based on Deep Learning and Computer Vision are successfully addressing the majority of real-time problems for autonomous driving, such as detecting traffic signals, traffic signs, and pedestrians. We propose a combination of deep learning and image processing methods while using the MobileNetSSD (deep neural network architecture) model with transfer learning for real-time detection and identification of traffic lights and back-light. This inference model is obtained from frameworks such as Tensor-Flow and Tensor-Flow Lite which is trained on the COCO data. This study investigates the feasibility of executing object detection on the Raspberry Pi 3B+, a widely used embedded computing board. The algorithm’s performance is measured in terms of frames per second (FPS), accuracy, and inference time.
Metabolic Reprogramming of Glioblastoma Cells during HCMV Infection Induces Secretome-Mediated Paracrine Effects in the Microenvironment

Glioblastoma (GBM) is an aggressive primary central nervous system neoplasia with limited therapeutic options and poor prognosis. Following reports of cytomegalovirus (HCMV) in GBM tumors, the anti-viral drug Valganciclovir was administered and found to significantly increase the longevity of GBM patients. While these findings suggest a role for HCMV in GBM, the relationship between them is not clear and remains controversial. Treatment with anti-viral drugs may prove clinically useful; however, their results do not explain the underlying mechanism between HCMV infection and GBM progression. We hypothesized that HCMV infection would metabolically reprogram GBM cells and that these changes would allow for increased tumor progression. We infected LN-18 GBM cells and employed a Seahorse Bioanalyzer to characterize cellular metabolism. Increased mitochondrial respiration and glycolytic rates were observed following infection. These changes were accompanied by elevated production of reactive oxygen species and lactate. Due to lactate’s numerous tumor-promoting effects, we examined the impact of paracrine signaling of HCMV-infected GBM cells on uninfected stromal cells. Our results indicated that, independent of viral transmission, the secretome of HCMV-infected GBM cells was able to alter the expression of key metabolic proteins and epigenetic markers. This suggests a mechanism of action where reprogramming of GBM cells alters the surrounding tumor microenvironment to be permissive to tumor progression in a manner akin to the Reverse-Warburg Effect. Overall, this suggests a potential oncomodulatory role for HCMV in the context of GBM.