Miracle-dz/UniFAR-FTUs huggingface dataset:
Extragalactic and cosmological tests of gravity theories with additional scalar or vector fields

Despite the many successes of the current standard model of c osmology on the largest physical scales, it relies on two phenomenologically motivated cons tituents, cold dark matter and dark energy, which account for approximately 95% of the energy-mat ter content of the universe. From a more fundamental point of view, however, the introduction o f a dark energy (DE) component is theoretically challenging and extremely fine-tuned, despi t the many proposals for its dynamics. On the other hand, the concept of cold dark matter (CDM) also s uffers from several issues such as the lack of direct experimental detection, the question of i ts cosmological abundance and problems related to the formation of structure on small scales. A perh aps more natural solution might be that the gravitational interaction genuinely di ffers from that of general relativity, which expresses itself as either one or even both of the above dark components. Here w e consider di fferent possibilities on how to constrain hypothetical modifications to the gravit ational sector, focusing on the subset of tensor-vector-scalar (TeVeS) theory as an alternative t o CDM on galactic scales and a particular class of chameleon models which aim at explaining the coinci dences of DE. Developing an analytic model for nonspherical lenses, we begin our analysis w ith testing TeVeS against observations of multiple-image systems. We then approach the role of lowdensity objects such as cosmic filaments in this framework and discuss potentially observable signatures. Along these lines, we also consider the possibility of massive neutrinos in TeVeS theo ry and outline a general approach for constraining this hypothesis with the help of cluster lense s. This approach is then demonstrated using the cluster lens A2390 with its remarkable straight ar c. Presenting a general framework to explore the nonlinear clustering of density perturbatio ns in coupled scalar field models, we then consider a particular chameleon model and highlight th e possibility of measurable e ff cts on intermediate scales, i.e. those relevant for galaxy cluste rs. Finally, we discuss the prospects of applying similar methods in the context of TeVeS and present an ansatz which allows to cast the linear perturbation equations into a more convenient form.
Coherence factor of speckle from a multi-row probe

The coherence factor provides a quantitative measure of image quality. It is defined as the ratio of the coherent sum across array elements to the incoherent sum and measures the distribution of ultrasonic energy between the main beam and side lobes of a radiation pattern. Values range from 0 to 1. For low values most of the energy is outside of the main beam, and for high values it is in the main beam. The authors have applied the van Cittert-Zernike theorem to determine analytic solutions of the coherence factor for single and multi-row arrays. The solution depends only on the number of rows and columns in a transducer array. With a multi-row probe, the authors imaged a uniform tissue-mimicking phantom and saved coherent signals. Images of the phantom were produced based on coherent and incoherent summations of array elements. They then combined the two images to produce a coherence factor image. Within the focal region, average coherence was 0.50 for the phantom which compares favorably to a value of 0.53 from the analytic solution. Next, phase distortions of pi/2 and pi radians were electronically introduced at specific elements, and the phantom was imaged again. Phase distortion greatly effects energy distribution for coherent summations but has a minimal effect on incoherent summations. An introduced distortion of pi/2 decreased the average coherence factor to 0.33. A distortion of pi further decreased it to 0.11. Results of human studies showed decreased average coherence factors compared to undistorted phantom images. These results suggest that the coherence factor provides a quantitative measure of beam quality for in vivo imaging.
DeepLBCEPred: A Bi-LSTM and multi-scale CNN-based deep learning method for predicting linear B-cell epitopes

The epitope is the site where antigens and antibodies interact and is vital to understanding the immune system. Experimental identification of linear B-cell epitopes (BCEs) is expensive, is labor-consuming, and has a low throughput. Although a few computational methods have been proposed to address this challenge, there is still a long way to go for practical applications. We proposed a deep learning method called DeepLBCEPred for predicting linear BCEs, which consists of bi-directional long short-term memory (Bi-LSTM), feed-forward attention, and multi-scale convolutional neural networks (CNNs). We extensively tested the performance of DeepLBCEPred through cross-validation and independent tests on training and two testing datasets. The empirical results showed that the DeepLBCEPred obtained state-of-the-art performance. We also investigated the contribution of different deep learning elements to recognize linear BCEs. In addition, we have developed a user-friendly web application for linear BCEs prediction, which is freely available for all scientific researchers at: http://www.biolscience. cn/DeepLBCEPred/.
Invasive Mold Infections Following Hurricane Harvey—Houston, Texas

Abstract Background Characterizing invasive mold infection (IMI) epidemiology in the context of large flooding events is important for public health planning and clinical decision making. Methods We assessed IMI incidence (per 10 000 healthcare encounters) 1 year before and after Hurricane Harvey at 4 hospitals in Houston, Texas. Potential IMI cases were assigned as proven or probable cases using established definitions, and surveillance cases using a novel definition. We used rate ratios to describe IMI incidence and multivariable logistic regression to examine patient characteristics associated with IMI case status. Results IMI incidence was significantly higher posthurricane (3.69 cases) than prehurricane (2.50 cases) (rate ratio, 1.48 [95% confidence interval, 1.10–2.00]), largely driven by surveillance IMI cases. Aspergillus was the most common species cultured (33.5% prehurricane and 39.9% posthurricane). About one-quarter (25.8%) of IMI patients lacked classical IMI risk factors such as hematologic malignancy and transplantations. Overall, 45.1% of IMI patients received intensive care, and in-hospital all-cause mortality was 24.2%. Conclusions IMI incidence likely increased following Hurricane Harvey and outcomes for IMI patients were severe. Patient and clinician education on IMI prevention and identification is warranted, particularly as the frequency of extreme weather events increases due to climate change.
Research Progresses and Applications of Fluorescent Protein Antibodies: A Review Focusing on Nanobodies

Since the discovery of fluorescent proteins (FPs), their rich fluorescence spectra and photochemical properties have promoted widespread biological research applications. FPs can be classified into green fluorescent protein (GFP) and its derivates, red fluorescent protein (RFP) and its derivates, and near-infrared FPs. With the continuous development of FPs, antibodies targeting FPs have emerged. The antibody, a class of immunoglobulin, is the main component of humoral immunity that explicitly recognizes and binds antigens. Monoclonal antibody, originating from a single B cell, has been widely applied in immunoassay, in vitro diagnostics, and drug development. The nanobody is a new type of antibody entirely composed of the variable domain of a heavy-chain antibody. Compared with conventional antibodies, these small and stable nanobodies can be expressed and functional in living cells. In addition, they can easily access grooves, seams, or hidden antigenic epitopes on the surface of the target. This review provides an overview of various FPs, the research progress of their antibodies, particularly nanobodies, and advanced applications of nanobodies targeting FPs. This review will be helpful for further research on nanobodies targeting FPs, making FPs more valuable in biological research.
Phylogenetic structure of the extinction and biotic factors explaining differential survival of terrestrial notosuchians at the Cretaceous–Palaeogene crisis

Although the clade Crocodylomorpha is represented by few extant species (Crocodylia), it has a rich fossil record. Hundreds of species, adapted to terrestrial, semi‐aquatic and marine environments, have existed over more than 200 million years. Numerous studies have attempted to characterize the factors driving the diversification and extinction events of Crocodylomorpha, resulting in ambiguous and even contradictory conclusions, which points to the need for phylogenetically and temporally smaller‐scaled studies. Here, we focus on differential survival at the Cretaceous–Palaeogene (K–Pg) crisis of Notosuchia, a diverse clade of mostly terrestrial Crocodylomorpha that achieved great diversity during the Cretaceous. More precisely, we tested the effect of body size and palaeotemperatures on notosuchian survival probability during the K–Pg crisis as well as the effect of diet on the evolution of their body size. We find that Notosuchia showed an evolutionary trend towards larger body sizes through time, associated with a shift from an omnivorous to a carnivorous diet. This may explain why sebecids were the only notosuchians to survive the K–Pg crisis. We also corroborate the conclusions of previous studies that detected a Lagerstätten effect occurring in the Adamantina Formation (Upper Cretaceous, Brazil, Bauru Group). This work confirms the value of more finely‐scaled macroevolutionary studies for understanding the history of a rich and complex group such as Crocodylomorpha.
Optical bonding reinforced by femtosecond laser welding

Previous work on welding of optical materials with ultrashort laser pulses demonstrated that the ability to achieve good contact between components limits the applicability of the technology to only very small components. We have overcome this limitation and demonstrated the capability to weld similar and dissimilar materials using femtosecond laser pulses over several mm2 areas between intimately contacted surfaces. Our joining process is realised in two steps. Firstly, the two pieces which must be joined are direct bonded, thereby inducing optical contact throughout the whole potentially bondable surface. Subsequently, the direct bond is reinforced by the inscription of femtosecond laser weld seams in a sealing pattern in order to enclose the central region of the direct bond. We demonstrated the applicability of this process to identical glass, dissimilar glass and glass-semiconductor. We also measured a mean threefold increase in joint strength for such bonds between fused silica windows with only a few welding seams. The final assembly is free from macroscopic surface deformations. Furthermore, by optimizing the laser exposure parameters, we can avoid microscopic defects inside and around weld seams. Finally, the bonding method does not alter the optical transmission properties at the center of the sealed region. As opposed to the use of adhesives, such bonds resist to important thermal constraints and are free from chemical contaminants, degassing and ageing. Potential applications may be considered in the fields of aerospace, laser manufacturing, semiconductor industry, solar cell protection, precision manufacturing and many more.
Computer-aided Detection of Tuberculosis from Microbiological and Radiographic Images

ABSTRACT Tuberculosis caused by Mycobacterium tuberculosis have been a major challenge for medical and healthcare sectors in many underdeveloped countries with limited diagnosis tools. Tuberculosis can be detected from microscopic slides and chest X-ray but as a result of the high cases of tuberculosis, this method can be tedious for both Microbiologists and Radiologists and can lead to miss-diagnosis. These challenges can be solved by employing Computer-Aided Detection (CAD)via AI-driven models which learn features based on convolution and result in an output with high accuracy. In this paper, we described automated discrimination of X-ray and microscope slide images into tuberculosis and non-tuberculosis cases using pretrained AlexNet Models. The study employed Chest X-ray dataset made available on Kaggle repository and microscopic slide images from both Near East University Hospital and Kaggle repository. For classification of tuberculosis using microscopic slide images, the model achieved 90.56% accuracy, 97.78% sensitivity and 83.33% specificity for 70: 30 splits. For classification of tuberculosis using X-ray images, the model achieved 93.89% accuracy, 96.67% sensitivity and 91.11% specificity for 70:30 splits. Our result is in line with the notion that CNN models can be used for classifying medical images with higher accuracy and precision.
Leveling the Playing Field: A Comparative Reevaluation of Unmodified Eye Tracking as an Input and Interaction Modality for VR

In this study, we establish a much-needed baseline for evaluating eye tracking interactions using an eye tracking enabled Meta Quest 2 VR headset with 30 participants. Each participant went through 1098 targets using multiple conditions representative of AR/VR targeting and selecting tasks, including both traditional standards and those more aligned with AR/VR interactions today. We use circular white world-locked targets, and an eye tracking system with sub-1-degree mean accuracy errors running at approximately 90Hz. In a targeting and button press selection task, we, by design, compare completely unadjusted, cursor-less, eye tracking with controller and head tracking, which both had cursors. Across all inputs, we presented targets in a configuration similar to the ISO 9241–9 reciprocal selection task and another format with targets more evenly distributed near the center. Targets were laid out either flat on a plane or tangent to a sphere and rotated toward the user. Even though we intended this to be a baseline study, we see unmodified eye tracking, without any form of a cursor, or feedback, outperformed the head by 27.9% and performed comparably to the controller (5.63% decrease) in throughput. Eye tracking had improved subjective ratings relative to head in Ease of Use, Adoption, and Fatigue (66.4%, 89.8%, and 116.1 % improvements, respectively) and had similar ratings relative to the controller (reduction by 4.2%, 8.9%, and 5.2% respectively). Eye tracking had a higher miss percentage than controller and head (17.3% vs 4.7% vs 7.2% respectively). Collectively, the results of this baseline study serve as a strong indicator that eye tracking, with even minor sensible interaction design modifications, has tremendous potential in reshaping interactions in next-generation AR/VR head mounted displays.
Boundedness of multilinear singular integral oprators on Hardy and Herz-type spaces

In this paper, the authors study a class of multilinear singular integral operators on product of Hardy spaces. The boundedness of another class of multilinear singular integral operators is also discussed on product of Herz-type spaces. Moreover, as their special cases, the corresponding results of multilinear fractional integral operator and multilinear Calderon-Zygmund operator can be obtained, respectively.
Stability of cnoidal waves for the focusing nonlinear Schrodinger equation with potential

We study the stability of the pulse solutions and the periodic solutions with large spatial periods of the focusing nonlinear Schrodinger equation with a potential. We play with symmetries of the equation and consider the edge bifurcation of the pulse solutions. Our results show spectral instability for all V0 > 0, which is a free parameter in the potential, and spectral stability of the essential spectrum near the origin for V0 0.
A theta function identity and its implications

In this paper we prove a general theta function identity with four parameters by employing the complex variable theory of elliptic functions. This identity plays a central role for the cubic theta function identities. We use this identity to re-derive some important identities of Hirschhorn, Garvan and Borwein about cubic theta functions. We also prove some other cubic theta function identities. A new representation for Π∞ n=1 (1-q n ) 10 is given. The proofs are self-contained and elementary.
M6A-Related Long Non-Coding RNA Displays Utility in Predicting Prognosis, Portraying the Tumor Immune Microenvironment and Guiding Immunotherapy in Pancreatic Ductal Adenocarcinoma

N6-methyladenosine (m6A) lncRNA plays a pivotal role in cancer. However, little is known about its role in pancreatic ductal adenocarcinoma (PDAC) and its tumor immune microenvironment (TIME). Based on The Cancer Genome Atlas (TCGA) cohort, m6A-related lncRNAs (m6A-lncRNA) with prognostic value were filtered using Pearson analysis and univariate Cox regression analysis. Distinct m6A-lncRNA subtypes were divided using unsupervised consensus clustering. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to establish an m6A-lncRNA-based risk score signature. The CIBERSORT and ESTIMATE algorithms were employed to analyze the TIME. The expression pattern of TRAF3IP2-AS1 was examined using qRT-PCR. The influence of TRAF3IP2-AS1 knockdown on cell proliferation was estimated by performing CCK8, EdU and colony-formation assays. Flow cytometry was applied to measure the effect of TRAF3IP2-AS1 knockdown on cell cycle and apoptosis. The in vivo anti-tumor effect of TRAF3IP2-AS1 was validated in a tumor-bearing mouse model. Two m6A-lncRNA subtypes with different TIME features were clarified. A risk score signature was constructed as a prognostic predictor based on m6A-lncRNAs. The risk score also correlated with TIME characterization, which facilitated immunotherapy. Finally, the m6A-lncRNA TRAF3IP2-AS1 was proved to be a tumor suppressor in PDAC. We comprehensively demonstrated m6A-lncRNAs to be useful tools for prognosis prediction, TIME depiction and immunotherapeutic guidance in PDAC.
Combined effects of non-Newtonian rheology and rotational inertia on the squeeze film characteristics of parallel circular discs

The combined effects of non-Newtonian couple stresses and rotational inertia on the squeeze film behaviours between parallel rotating circular discs have been analysed in this paper. On the basis of Stokes micro-continuum theory, the non-Newtonian Reynolds-type equation including the rotational inertial effects is derived, and applied to predict the squeeze film performance. According to the results obtained and discussed, the effects of rotational inertia yield a lower squeeze-film load-carrying capacity; however, the presence of non-Newtonian couple stresses provides an increase in the load-carrying capacity and the approaching time. Better squeeze film characteristics of rotating circular discs are achieved by the use of a non-Newtonian couple stress fluid.
New Insights into the Phytochemical Profile and Biological Properties of Lycium intricatum Bois. (Solanaceae)

This work aimed to boost the valorisation of Lycium intricatum Boiss. L. as a source of high added value bioproducts. For that purpose, leaves and root ethanol extracts and fractions (chloroform, ethyl acetate, n-butanol, and water) were prepared and evaluated for radical scavenging activity (RSA) on 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radicals, ferric reducing antioxidant power (FRAP), and metal chelating potential against copper and iron ions. Extracts were also appraised for in vitro inhibition of enzymes implicated on the onset of neurological diseases (acetylcholinesterase: AChE and butyrylcholinesterase: BuChE), type-2 diabetes mellitus (T2DM, α-glucosidase), obesity/acne (lipase), and skin hyperpigmentation/food oxidation (tyrosinase). The total content of phenolics (TPC), flavonoids (TFC), and hydrolysable tannins (THTC) was evaluated by colorimetric methods, while the phenolic profile was determined by high-performance liquid chromatography, coupled to a diode-array ultraviolet detector (HPLC-UV-DAD). Extracts had significant RSA and FRAP, and moderate copper chelation, but no iron chelating capacity. Samples had a higher activity towards α-glucosidase and tyrosinase, especially those from roots, a low capacity to inhibit AChE, and no activity towards BuChE and lipase. The ethyl acetate fraction of roots had the highest TPC and THTC, whereas the ethyl acetate fraction of leaves had the highest flavonoid levels. Gallic, gentisic, ferulic, and trans-cinnamic acids were identified in both organs. The results suggest that L. intricatum is a promising source of bioactive compounds with food, pharmaceutical, and biomedical applications.
Online Calibration Study of Non-Contact Current Sensors for Three-Phase Four-Wire Power Cables

Three-phase four-wire power cables are a primary kind of power transmission method in low-voltage distribution networks. This paper addresses the problem that calibration currents are not easily electrified during the transporting of three-phase four-wire power cable measurements, and proposes a method for obtaining the magnetic field strength distribution in the tangential direction around the cable, finally enabling online self-calibration. The simulation and experimental results show that this method can self-calibrate the sensor arrays and reconstruct the phase current waveforms in three-phase four-wire power cables without calibration currents, and this method is not affected by disturbances such as wire diameter, current amplitudes, and high-frequency harmonics. This study reduces the time and equipment costs required to calibrate the sensing module compared to related studies using calibration currents. This research offers the possibility of fusing sensing modules directly with running primary equipment, and the development of hand-held measurement devices.
Spiral Shaped Photonic Crystal Fiber-Based Surface Plasmon Resonance Biosensor for Cancer Cell Detection

This work presents the design and simulation of an all-optical sensor for detection of cancer cells. The proposed device is based on the surface plasmon resonance effect on a spiral shaped photonic crystal fiber structure. The finite element method (FEM) based simulations are carried out for the different cancer cells, such as HELA, Basal, Jurkat, and MDA-MB-231, MCF7, and PC12 detection. The sensor has shown the maximum sensitivity of −289 RIU−1 for the refractive index of the detection of breast cancer cell with the resolution of 2.33 × 10−4. The sensor is effective for the refractive index range of 1.36 to 1.401. The structure is based on spiral shaped photonic crystal fiber, and has shown promising linear sensing response to support the practical feasibility of the device. The proposed sensor design is effective in detecting cervical cancer, skin cancer, blood cancer, breast cancer type 1, breast cancer type 2, and adrenal gland cancer.