Miracle-dz/UniFAR-FTUs huggingface dataset:
BACTERIAL INFECTION AND ANTIBIOTIC RESISTANCE IN PATIENTS WITH HUMAN IMMUNODEFICIENCY VIRUS PRESENTING LOWER RESPIRATORY TRACT INFECTION IN NIGERIA

Lower Respiratory Tract Infection (LRTI) is associated with mortality and prolonged antibiotics use among HIV/AIDS patients. Sputum samples were collected from 134 HIV/AIDS patients with LRTI and productive cough, visiting University of Abuja Teaching Hospital, Nigeria, to determine the bacterial aetiologies and antibiotic resistance profile. Adequate for culture sputum samples were observed in only 119 subjects (75 females and 44 males) and cultured using standard procedure. Isolates were identified by biochemical method and 16SrRNA gene amplification, purification, sequencing and database nucleotide blast. Antibiotic susceptibility tests were performed and interpreted according to Clinical and Laboratory Standard Institute (CLSI) procedures. Bacteria associated LRTI was found in 20.2% of the patients and Klebsiella pneumonia (29.7%); Enterobacter cloacae (16.7%); Enterobacter hormaechei subsp. xiangfangensis (12.5%); Pseudomonas parafulva; Pseudomonas aeruginosa; Pseudomonas alcaliphila; Klebsiella aerogenes (8.3%); Comamonas testosteroni; Escherichia coli; Acinetobacter junii; Acinetobacter soli and Acinetobacter baumannii were implicated. Isolates show high resistance to amoxicillin-clavulanic acid at 94.1%, trimethoprim-sulfamethoxazole at 75.0% and cefotaxime at 70.0%. The Multiple Antibiotic Resistance (MAR) index of most isolates (62.5%) is within 0.3-0.8 in a range of 0.0 to 0.8. Isolates of the same species were found to have different MAR index in different patients. However, E. cloacae, E. hormaechei subsp. xiangfangensis, A. baumanni and 71.4% of K. pneumonia were Multi-drug Resistant (MDR). Interestingly, Gentamycin, Ciprofloxacin and Imipenem were effective against MDR isolates and showed significant negative correlation with MAR index. We propose that antibiotics with efficacy against MDR isolates could be used to down regulate the selective pressure of other antibiotics, and these MDR pathogens, including those rarely associated with human infection poses potential threat, similar to Methicillin Resistant Staphylococcus aureus (MRSA). Particularly, among the immunocompromised. Furthermore, HIV/AIDS patients present good metrics for profiling the burden and spread of antibiotic resistant bacteria in poor countries.
Expected hospitality practices and hotel attributes as predictors of American tourists' attitudes and booking intentions toward hotels in Egypt

ARTICLE INFO Abstract This study aims to explore American tourists' expectations of hospitality practices and hotel attributes focusing on hotels in Egypt and to examine the impact of expected hospitality practices and hotel attributes on potential tourists' attitudes and booking intentions. A questionnaire survey was designed and administered among potential tourists. Based on valid data from 300 participants, structure equation modelling SEM using smart PLS 3.0 was performed to examine the hypothesized model. The results indicated that hospitality practices and intangible hotel attributes were highly expected by participants. Hypotheses testing results revealed that both expected hospitality practices and hotel attributes did not directly influence booking intentions, yet they have negatively affected guests' attitudes toward hotels which confirmed the significant mediation effect of guests' attitudes.
Management practices and M&A success

We study whether management practices determine merger and acquisition (M&A) success. We model management as an unobserved (latent) variable in a standard microeconomic model of the firm and derive firm-year management estimates. We validate these estimates against benchmark survey data on management practices and by using Monte Carlo simulation. We show that our measure is among the most important determinants of value creation in M&A deals, substantially increasing the predictive power of models that explain cumulative abnormal returns. Thus, we offer a measure of management practices that identifies the best-performing M&As. Our results are robust to the inclusion of acquirer fixed effects and many control variables, and to several other sensitivity tests. We identify the Q-theory as the key mechanism driving our results.
A Revised View of the Linear Polarization in the Subparsec Core of M87 at 7 mm

The linear polarization images of the jet in the giant elliptical galaxy M87 have previously been observed with Very Long Baseline Array at 7 mm. They exhibit a complex polarization structure surrounding the optically thick and compact subparsec-scale core. However, given the low level of linear polarization in the core, it is required to verify that this complex structure does not originate from residual instrumental polarization signals in the data. We have performed a new analysis of the same data sets observed in four epochs by using the Generalized Polarization CALibration pipeline (GPCAL). This novel instrumental polarization calibration pipeline overcomes the limitations of LPCAL, a conventional calibration tool used in the previous M87 studies. The resulting images show a compact linear polarization structure with its peak nearly coincident with the total intensity peak, which is significantly different from the results of previous studies. The core linear polarization is characterized as fractional polarization of ∼0.2%–0.6% and polarization angles of ∼66°–92°, showing moderate variability. We demonstrate that, based on tests with synthetic data sets, LPCAL using calibrators having complex polarization structures cannot achieve sufficient calibration accuracy to obtain the true polarization image of M87 due to a breakdown of the “similarity approximation. ” We find that GPCAL obtains more accurate D-terms than LPCAL by using observed closure traces of calibrators that are insensitive to both antenna gain and polarization leakage corruptions. This study suggests that polarization imaging of very weakly polarized sources has become possible with the advanced instrumental polarization calibration techniques.
Propagation Effects in the FRB 20121102A Spectra

We advance theoretical methods for studying propagation effects in fast radio burst (FRB) spectra. We derive their autocorrelation function in the model with diffractive lensing and strong Kolmogorov-type scintillations and analytically obtain the spectra lensed on different plasma density profiles. With these tools, we reanalyze the highest frequency 4–8 GHz data of Gajjar et al. for the repeating FRB 20121102A (FRB 121102). In the data, we discover, first, a remarkable spectral structure of almost equidistant peaks separated by 95 ± 16 MHz. We suggest that it can originate from diffractive lensing of the FRB signals on a compact gravitating object of mass 10−4 M ⊙ or on a plasma underdensity near the source. Second, the spectra include erratic interstellar, presumably Milky Way scintillations. We extract their decorrelation bandwidth 3.3 ± 0.6 MHz at reference frequency 6 GHz. The third feature is a GHz-scale pattern that, as we find, linearly drifts with time and presumably represents a wideband propagation effect, e.g., GHz-scale scintillations. Fourth, many spectra are dominated by a narrow peak at 7.1 GHz. We suggest that it can be caused by propagation through a plasma lens, e.g., in the host galaxy. Fifth, separating the propagation effects, we give strong arguments that the intrinsic progenitor spectrum has a narrow GHz bandwidth and variable central frequency. This confirms expectations from the previous observations. We discuss alternative interpretations of the above spectral features.
Sparse PointPillars: Maintaining and Exploiting Input Sparsity to Improve Runtime on Embedded Systems

Bird's Eye View (BEV) is a popular representation for processing 3D point clouds, and by its nature is fundamentally sparse. Motivated by the computational limitations of mobile robot platforms, we create a fast, high-performance BEV 3D object detector that maintains and exploits this input sparsity to decrease runtimes over non-sparse baselines and avoids the tradeoff between pseudoimage area and runtime. We present results on KITTI, a canonical 3D detection dataset, and Matterport-Chair, a novel Matterport3D-derived chair detection dataset from scenes in real furnished homes. We evaluate runtime characteristics using a desktop GPU, an embedded ML accelerator, and a robot CPU, demonstrating that our method results in significant detection speedups (2 × or more) for embedded systems with only a modest decrease in detection quality. Our work represents a new approach for practitioners to optimize models for embedded systems by maintaining and exploiting input sparsity throughout their entire pipeline to reduce runtime and resource usage while preserving detection performance. All models, weights, experimental configurations, and datasets used are publicly available11https://vedder.io/sparse_point_pillars.
Latent Fine-grained Features embedding model for Unsupervised Zero-shot Learning

Zero-shot learning (ZSL) aims to identify image categories that never appear in the training set by learning a mapping from visual information to the semantic space. For existing works in recent years, it has been paying much attention to user-defined-attributes-based supervised ZSL models and manual annotation-based unsupervised ZSL methods, whilst the important drawback of user-defined attributes is ignored. User-defined attributes usually need to be precisely annotated not only for seen classes but also for unseen classes. This procedure of collecting user-defined attributes is an error-prone and time-consuming work limiting the scalability of the methods to a great extent. Moreover, user-defined attributes are semantic embedding but they are not exhaustive. In this paper, we propose a manual annotation-free unsupervised ZSL method with a great scalability which is a benefit for the large-scale ZSL tasks, just using public word vectors of categories without any dedicated attributes annotation efforts. In addition, our approach can automatically extract latent fine-grained features to reduce visual information losses caused by the absence of user-defined attributes. Extensive experimental results show that our method outperforms the previous methods among the manual annotation-free unsupervised ZSL methods.
Final report of the new BIPM comparison BIPM.RI(II)-K1.Ac-225 of activity measurements of the radionuclide 225Ac to include the 2019 result of the PTB (Germany)

In 2019, the PTB(Germany) has submitted a sample of 225Ac to the International Reference System (SIR) for activity comparison at the Bureau International des Poids et Mesures (BIPM), with comparison identifier BIPM.RI(II)-K1.Ac-225. As PTB is the first participant in the comparison no key comparison reference value (KCRV) and no degrees of equivalence can be calculated. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm. org/kcdb/. The final report has been peer-reviewed and approved for publication by the CCRI, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Visual News: Benchmark and Challenges in News Image Captioning

We propose Visual News Captioner, an entity-aware model for the task of news image captioning. We also introduce Visual News, a large-scale benchmark consisting of more than one million news images along with associated news articles, image captions, author information, and other metadata. Unlike the standard image captioning task, news images depict situations where people, locations, and events are of paramount importance. Our proposed method can effectively combine visual and textual features to generate captions with richer information such as events and entities. More specifically, built upon the Transformer architecture, our model is further equipped with novel multi-modal feature fusion techniques and attention mechanisms, which are designed to generate named entities more accurately. Our method utilizes much fewer parameters while achieving slightly better prediction results than competing methods. Our larger and more diverse Visual News dataset further highlights the remaining challenges in captioning news images.
Voxel-wise binocular energy models for binocular disparity decoding

Binocular disparity is a powerful cue for depth perception in three-dimensional (3D) space. Some neurophysiological studies proposed the binocular phase-shift and position-shift energy models to predict the responses of individual disparity-tuned neurons in cats and macaques. By far, it is unclear how to use binocular energy models to characterize the voxels’ responses in human visual cortex. In this study, we introduced the binocular energy models to the functional magnetic resonance imaging study and constructed the position-shift receptive-field model (Position-RFM) and the phase-shift receptive-field model (Phase-RFM) to predict voxel responses to disparity and to identify novel disparity levels from voxel responses. The results revealed that Phase-RFM outperformed Position-RFM in fitting the voxel responses for all the visual regions. Moreover, the novel disparity levels can be better identified from voxel’s responses in visual regions by Phase-RFM than Position-RFM. The findings may suggest that Phase-RFM can better encode the responses of disparity-tuned neuron populations than Position-RFM for human visual regions.
A fast first-principles approach to model atomic force microscopy on soft, adhesive, and viscoelastic surfaces

Quantitative atomic force microscopy (AFM) on soft polymers remains challenging due to the lack of easy-to-use computational models that accurately capture the physics of the interaction between the tip and sticky, viscoelastic samples. In this work, we enhance Attard’s continuum mechanics-based model, arguably the most rigorous contact model for adhesive viscoelastic samples, via three key enabling strategies. First, the original model’s formalism is rearranged to enable a fast and explicit solution of the model’s ordinary differential equations (ODEs). Second, the deformed surface is reconstructed using a complete set of optimized orthogonal basis functions as opposed to Attard’s original, computationally expensive radial discretization. Third, the model’s governing ODEs are solved using a multi-step numerical method to further stabilize the solution when using for soft and sticky samples. Implementing these enhancements, enhanced Attard’s model (EAM) is more stable, 3+ orders of magnitude faster, and equally accurate when compared to the original model. These facilitate EAM’s inclusion into simulations of various AFM operating modes. We demonstrate EAM based simulations of quasi-static force spectroscopy and amplitude modulation AFM approach curves on soft sticky polymer surfaces. On a typical desktop computer, simulation of an amplitude modulation approach curve with EAM takes less than a minute as compared to ≈15 h by the original Attard’s model. We expect EAM to be of interest to the AFM community because it facilitates the inclusion of rigorous models of tip-sample contact in simulations on polymer samples. EAM is available as part of the VEDA set of simulation tools deployed on nanoHUB.org cyber-infrastructure.
Recognition and Application of Tunnel Water Accumulation Based on Computer Vision

Water accumulation in tunnel threatens the safety of driving and the tunnel itself. In order to detect the tunnel waterlogging in time, a method based on computer vision is proposed. This method utilizes Laplace transform for image preprocessing to remove fuzzy image, uses the network MobileNetV2 to build a tunnel waterlogging recognition model, and then smooths the prediction results. Based on this method, a tunnel waterlogging recognition and early warning platform is developed which applied to a city video surveillance system successfully. The results show that: the tunnel waterlogging recognition method based on computer vision has high accuracy, tiny computation and low cost. The existing video monitoring system can be upgraded intelligently without installing any hardware, so as to realize the active recognition and early warning of tunnel water accumulation.
Hydrogen sulfide (H2S) - therapeutic relevance in rehabilitation and balneotherapy Systematic literature review and meta-analysis based on the PRISMA paradig

Background. An active molecule in sulfurous mineral - therapeutic waters and also in sapropelic mud is H2S, a hormetic gaseous molecule that can actively penetrate the skin. While high levels of H2S are extremely toxic, low levels are tolerated and have potential cytoprotective effects, with anti-inflammatory and antioxidant applications. Objective. This systematic review aims to rigorously select related articles and identify within their content the main possible uses of hydrogen sulfide from balneary sources and to explain its physiological mechanisms and therapeutic properties. Methods. To elaborate our systematic review, we have searched for relevant open access articles in 6 international databases: Cochrane , Elsevier , NCBI/PubMed , NCBI/PMC , PEDro , and ISI Web of Knowledge/Science , published from January 2016 until July 2021. The contextually quested keywords combinations/ syntaxes used are specified on this page. The eligible articles were analyzed in detail regarding pathologies addressed by hydrogen sulfide. All articles with any design (reviews, randomized controlled trials, non-randomized controlled trials, case-control studies, cross-sectional studies), if eligible according to the above-mentioned selection methodology, containing in the title the selected combinations, were included in the analysis. Articles were excluded in the second phase if they did not reach the relevance criterion. Results. Our search identified, first, 291 articles. After eliminating the duplicates and non-ISI articles, remained 121 papers. In the second phase, we applied a PEDro selection filter, resulting in 108 articles that passed the relevance criterion and were included in this systematic review. Conclusions. H2S biology and medical relevance are not fully understood and used adequately for sanogenic or medical purposes. More research is needed to fully understand the mechanisms and importance of this therapeutic gase. The link between balneotherapy and medical rehabilitation regarding the usage of hydrogen sulfide emphasises the unity for this medical speciality.
Two Types of Curved Hyperreflective Structures on Optical Coherence Tomography Images of the Outer Retina of Eyes with Different Macular Disorders

Hyperreflective materials on Spectral-Domain Optical Coherence Tomography (SD-OCT) images of eyes with different retinal disorders may have diverse shapes and origins and are a prognostic marker of disease progression. This study documents using SD-OCT the presence of Curved Hyper Reflective Structures (CHRS) in the outer macula of eyes with different retinal disorders. A retrospective case series of 22 eyes of 21 patients with CHRS is described. In addition, 12 eyes of 12 patients with other kinds of intra retinal hyperreflective structures were investigated. CHRS, which form curved thin lines or broad bands between the outer plexiform layer and external limiting membrane (ELM) in the macula, were found in eyes without edema. Thin CHRS were secondary to dry age-related macular degeneration (AMD; n=10 eyes), glaucoma (n=2), wet AMD, chorioretinitis, macular scarring, anterior ischemic optic neuropathy, proliferative diabetic retinopathy, adult-onset foveomacular vitelliform dystrophy, and ocular ischemia (each n=1), respectively. Broad CHRS were caused by hemorrhages in the inner foveal layers (n=3). CHRS were associated with focal photoreceptor layer defects. The defects were present before the formation of thin CHRS and during or after the formation of broad CHRS. The retina of eyes with edema showed hyper reflective foci and cystoid cavities which contained hypoor medium-reflective fluid and hyper reflective material, but not CHRS. It is concluded that CHRS in the outer macula are found in eyes with different retinal disorders without edema. Thin CHRS likely develop after photoreceptor damage from the ELM. Broad CHRS are caused by hemorrhages within the inner foveal layers.
EFFECT OF BERBERINE ON OXIDATIVE STRESS CAUSED BY EIMERIA TENELLA IN CHICKEN

After coccidia infect chickens, the cecum of chickens produces oxidative stress, which is aggravated by the propagation of coccidia. The disruption of the balance of oxidant/antioxidant system causes chickens to suffer from diseases. Berberine has been shown to prevent cecum epithelial barrier damage from coccidia by suppressing the reproduction of coccidia and restore the normal functions of chicks’ cecum. In the current study, effect of berberine (BBR) on the oxidative damage caused by coccidiosis was investigated. Forty-eight three-week-old chicks treated in different ways. All livers, serum and caeca were collected and the degree of oxidative stress and antioxidant enzyme activity were evaluated. The results showed that the increase in contents of free radicals in serum and cecum caused by Eimeria tenella were eliminated after daily treatment with berberine. Furthermore, level of lipid peroxidation was decreased, and superoxide dismutase activities were increased in the experimental groups treated by berberine compared to the infected birds. RT-PCR assay showed that mRNA level of superoxide dismutase was not affected by berberine. Taken together, berberine alleviates oxidative stress by increasing the activity of antioxidant enzymes such as superoxide dismutase. However, it is independent of mRNA expression of superoxide dismutase.
Self-Supervised Neural Topic Modeling

Topic models are useful tools for analyzing and interpreting the main underlying themes of large corpora of text. Most topic models rely on word co-occurrence for computing a topic, i.e., a weighted set of words that together represent a high-level semantic concept. In this paper, we propose a new light-weight Self-Supervised Neural Topic Model (SNTM) that learns a rich context by learning a topic representation jointly from three co-occurring words and a document that the triplet originates from. Our experimental results indicate that our proposed neural topic model, SNTM, outperforms previously existing topic models in coherence metrics as well as document clustering accuracy. Moreover, apart from the topic coherence and clustering performance, the proposed neural topic model has a number of advantages, namely, being computationally efficient and easy to train.
Plasma N-terminal pro-brain natriuretic peptide level as a marker of adverse outcome in patients with co-existing diabetes, chronic kidney disease and heart failure

Introduction: N-terminal pro–B-type natriuretic peptide (NT-proBNP) is a novel marker of cardiac disease and heart failure; both are in patients with diabetes and chronic kidney disease. Objectives: This study aimed to investigate the NT-proBNP and adverse outcome in patients with diabetes complicated by chronic kidney disease (CKD). Patients and Methods: We measured the serum levels of NT-proBNP. The association of this novel marker with re-hospitalization and mortality rate were prospectively compared among the studied groups. Results: Among 120 patients, baseline NT-proBNP at the time of admission was significantly elevated in patients with CKD (P= 0.001). Levels of NT-proBNP were significantly elevated in patients with diabetes and CKD than those with CKD alone (P= 0.04) at the end of follow-up. Higher proBNP levels significantly correlated with decreased glomerular filtration rate (GFR) and higher serum creatinine levels (P= 0.03, P< 0.001, respectively). In addition, increased mortality was noticed in those patients. Conclusion: NT-proBNP levels have prognostic implication in the setting of CKD, diabetes mellitus and heart failure. Adverse outcomes are; a higher rate of need for dialysis, re-hospitalization and increased mortality which are correlated with levels of NT-proBNP.