Miracle-dz/UniFAR-FTUs huggingface dataset:
Differentiation between Phyllodes Tumors and Fibroadenomas through Breast Ultrasound: Deep-Learning Model Outperforms Ultrasound Physicians

The preoperative differentiation of breast phyllodes tumors (PTs) from fibroadenomas (FAs) plays a critical role in identifying an appropriate surgical treatment. Although several imaging modalities are available, reliable differentiation between PT and FA remains a great challenge for radiologists in clinical work. Artificial intelligence (AI)-assisted diagnosis has shown promise in distinguishing PT from FA. However, a very small sample size was adopted in previous studies. In this work, we retrospectively enrolled 656 breast tumors (372 FAs and 284 PTs) with 1945 ultrasound images in total. Two experienced ultrasound physicians independently evaluated the ultrasound images. Meanwhile, three deep-learning models (i.e., ResNet, VGG, and GoogLeNet) were applied to classify FAs and PTs. The robustness of the models was evaluated by fivefold cross validation. The performance of each model was assessed by using the receiver operating characteristic (ROC) curve. The area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were also calculated. Among the three models, the ResNet model yielded the highest AUC value, of 0.91, with an accuracy value of 95.3%, a sensitivity value of 96.2%, and a specificity value of 94.7% in the testing data set. In contrast, the two physicians yielded an average AUC value of 0.69, an accuracy value of 70.7%, a sensitivity value of 54.4%, and a specificity value of 53.2%. Our findings indicate that the diagnostic performance of deep learning is better than that of physicians in the distinction of PTs from FAs. This further suggests that AI is a valuable tool for aiding clinical diagnosis, thereby advancing precision therapy.
Fusing probability distributions with information theoretic centers and its application to data retrieval

This work presents two representations for a collection of probability distributions or densities dubbed information theoretic centers (ITCs). Like the common arithmetic mean, the first new center is a convex combination of its constituent densities in the mixture family. Analogously, the second ITC is a weighted geometric mean of densities in the exponential family. In both cases, the weights in the combinations vary as one changes the distributions. These centers minimize the maximum Kullback-Leibler divergence from each distribution in their collections to themselves and exhibit an equi-divergence property, lying equally far from most elements of their collections. The properties of these centers have been established in information theory through the study of channel-capacity and universal codes; drawing on this rich theoretical basis, this work applies them to the problems of indexing for content-based retrieval and to tracking. Many existing techniques in image retrieval cast the problem in terms of probability distributions. That is, these techniques represent each image in the database---as well as incoming query images---as probability distributions, thus reducing the retrieval problem to one of finding a nearest probability distribution under some dissimilarity measure. This work presents an indexing scheme for such techniques wherein an ITC stands in for a subset of distributions in the database. If the search finds that a query lies sufficiently far from such an ITC, the search can safely disregard (i.e., without fear of reducing accuracy) the associated subset of probability distributions without further consideration, thus speeding search. Often in tracking, one represents knowledge about the expected motion of the object of interest by a probability distribution on its next position. This work considers the case in which one must specify a tracker capable of tracking any one of several objects, each with different probability distributions governing its motion. Related is the case in which one object undergoes different "phases" of motion, each of which can be modeled independently (e.g., a car driving straight vs. turning). In this case, an ITC can fuse these different distributions into one, creating one motion model to handle any of the several objects.
miR-3174 Is a New Tumor Suppressor MicroRNA That Inhibits Several Tumor-Promoting Genes in Glioblastoma

microRNAs (miRNAs) play an important role in the pathology of glioblastoma (GBM), which is the most malignant and most common primary malignant brain tumor. miRNAs can target multiple genes simultaneously and are considered as potential therapeutic agents or targets. This study aimed to determine the role of miR-3174 in the pathobiology of GBM using both in vitro and in vivo approaches. This is the first study deciphering the role of miR-3174 in GBM. We studied the expression of miR-3174 and found it to be downregulated in a panel of GBM cell lines, GSCs and tissues relative to astrocytes and normal brain tissue. This finding led us to hypothesize that miR-3174 has a tumor-suppressive role in GBM. Exogenous expression of miR-3174 inhibited GBM cell growth and invasion, and hampered the neurosphere formation ability of GSCs. miR-3174 downregulated the expression of multiple tumor-promoting genes including CD44, MDM2, RHOA, PLAU and CDK6. Further, overexpression of miR-3174 reduced tumor volume in nude mice with intracranial xenografts. Immuno-histochemical study of brain sections with intracranial tumor xenografts revealed the pro-apoptotic and anti-proliferative activity of miR-3174. In conclusion, we demonstrated that miR-3174 has a tumor-suppressive role in GBM and could be exploited for therapeutic purposes.
Segmentation of Medical Images Based on Probabilistic Markov Random Field Model

In this paper, we present a new approach to medical image segmentation that is based on Markov random fields and Maximum a posteriori rule. Mathematical image models play a very important role in providing priori information for image segmentation, image reconstruction, etc. A natural way of incorporating spatial correlations into the segmentation process is to use Markov Random Field as a priori model, which is robust to noise. The segmentation process is considered as a pixel labeling problem. It is formulated using Maximum a posteriori (MAP) criterion. The MRF based segmentation method gives a priori information of the local structure contained in the image to get better segmentation accuracy. The simulation results indicate that this proposed algorithm gives a promising solution to medical image segmentation.
Featureless transmission spectra of 12 giant exoplanets observed by GTC/OSIRIS

Exoplanet atmospheres are the key to understanding the nature of exoplanets. To this end, transit spectrophotometry provides us opportunities to investigate the physical properties and chemical compositions of exoplanet atmospheres. We aim to detect potential atmospheric signatures in 12 gaseous giant exoplanets using transit spectrophotometry and we try to constrain their atmospheric properties. The targets of interest were observed using transit spectrophotometry with the GTC OSIRIS instrument. We estimated the transit parameters and obtained the optical transmission spectra of the target planets using a Bayesian framework. We analyzed the spectral features in the transmission spectra based on atmospheric retrievals. Most of the observed transmission spectra were found to be featureless, with only the spectrum of CoRoT-1b showing strong evidence for atmospheric features. However, in combination with the previously published near-infrared transmission spectrum, we found multiple interpretations for the atmosphere of CoRoT-1b due to the lack of decisive evidence for alkali metals or optical absorbers. Featureless spectra are not necessarily indicative of cloudy atmospheres if they poorly constrain the altitudes of cloud decks. Precise constraints on the models of hazes and clouds strongly depend on the significance of the observed spectral features. Further investigations on these exoplanets, especially CoRoT-1b, are required to confirm the properties of their atmospheres.
Methodological Appraisal of Phase 3 Clinical Trials in Geographic Atrophy

Geographic atrophy (GA) secondary to age-related macular degeneration is a common cause of blindness worldwide. Given the recent approval of the first therapy for GA, pegcetacoplan, we critically appraise methodological aspects of the phase 3 clinical trials published so far in this disease in relation to their design, analysis and interpretation. We reviewed some of the key attributes of all phase 3 clinical trials in GA available in the main public registry of clinical trials as of 20 May 2023. The topics discussed included types of endpoints, eligibility criteria, p-value and effect size, study power and sample size, the intention to treat principle, missing data, consistency of results, efficacy–safety balance and application of results. Five phase 3 clinical trials have reported results, either partially or completely: GATHER1, DERBY/OAKS, CHROMA/SPECTRI, SEATTLE and GATE. Although there are many similarities between these trials in terms of endpoints or broad eligibility criteria, they differ in several aspects (metric of the primary endpoint, sample size, type of adverse events, etc.) that can influence the results, which are discussed. Readers should understand key methodological aspects of clinical trials to improve their interpretation. On the other hand, authors should adhere to clinical trial reporting guidelines to communicate what was done and how it was done.
A semi-analytical method to extract the characterization parameters of artificial magnetic conductor metasurfaces using generalized boundary conditions

In this work, a characterization procedure of Artificial Magnetic Conductor (AMC) metasurfaces based on analytical expressions developed using the Generalized Boundary Conditions (GBCs) model is presented. The correlation between the surface susceptibilities of the PEC scatterers and the main frequency points used in the characterization of AMCs are established. Then the susceptibilities of square patch, square loop, Jerusalem cross and second iteration Minkowski fractal PEC scatterers are obtained by two sets of simulations and are used to calculate profiling frequencies and stability parameters. The detailed characterization procedure is presented and the flexibility and effectiveness of the proposed method are compared to full-wave numerical simulations.
Design and analysis of a large cylinder antenna array in Tianlai

In order to make a large area survey, detect a large scale structure and understand dark energy, a large radio interference array with a large number of feeds is required. However, cost and deformation control are main considerations in designing a large antenna array. In this paper we designed a cylinder parabolic structure for antenna array 45m x 40m of "Tianlai" project in Xinjiang, China in 2015. In order to largely reduce weight and cost, the antenna was divided into many assemble units, their structure was optimized by MSC.Patran/Nastran and their reflector deformation under various load cases of gravity, snow and wind was analyzed. For the feed support, we compared different types of structure such as arch-bridge, tower, cable and pole, and by mechanical simulations we found that the arch-bridge structure is very helpful to achieve large span, decrease weight and improve stability, for example, the total weight of optimized structure can be reduced to 43.7% of before. Finally some deformation measurement and experiment methods were discussed, which can be extended to array 100m×100m in the future.
The Sheffer B-type 1 Orthogonal Polynomial Sequences

In 1939, I.M. Sheffer proved that every polynomial sequence belongs to one and only one type. Sheffer extensively developed properties of the B-Type 0 polynomial sequences and determined which sets are also orthogonal. He subsequently generalized his classification method to the case of arbitrary B-Type k by constructing the generalized generating function A(t)exp [ xH1(t) + · · ·+ xHk(t) ] = ∑∞ n=0 Pn(x)t , with Hi(t) = hi,it i + hi,i+1t i+1 + · · · , h1,1 6= 0. Although extensive research has been done on characterizing polynomial sequences, no analysis has yet been completed on sets of type one or higher (k ≥ 1). We present a preliminary analysis of a special case of the B-Type 1 (k = 1) class, which is an extension of the B-Type 0 class, in order to determine which sets, if any, are also orthogonal sets. Lastly, we consider an extension of this research and comment on future considerations. In this work the utilization of computer algebra packages is indispensable, as computational difficulties arise in the B-Type 1 class that are unlike those in the B-Type 0 class.
Hyper contour cryptography with master Birch‐Brown Paruvala‐SLSTM model for enhanced healthcare security

Blockchain is a reliable ledger database that may be used to store various private healthcare data, but uploading and sharing data is difficult due to privacy concerns. Hence, to overcome these issues, a novel HCCLO with master Birch‐Brown Paruvala‐SLSTM model has been proposed to store various patients' medical data and shield it from threats. Hyper Contour Cryptography with Lepidoptera Optimization (HCCLO) has been proposed in this model, which encrypts data to reduce unwanted time stamp creation and prevent private key theft. Also, the Master Birch‐Brown‐Parulava NN design is introduced to prevent a false identity that leads to a data breach, and it allows for private exchange and enhances framework reconciliation, acting as an immune response to information breaks in the chain and preventing data breaches from spreading further. Then, the SLSTM layer implant RF Classifier is introduced to categorize data as user requests and attacks, safeguarding the blocks against changeability caused by malware attacks. The proposed approach offers minimal block mine time, maximum accuracy, and healthcare data security.
Calcitriol, an Active Form of Vitamin D3, Mitigates Skin Barrier Dysfunction in Atopic Dermatitis NC/Nga Mice

Atopic dermatitis and psoriasis are prevalent chronic inflammatory skin diseases that are characterized by dysfunctional skin barriers and substantially impact patients’ quality of life. Vitamin D3 regulates immune responses and keratinocyte differentiation and improves psoriasis symptoms; however, its effects on atopic dermatitis remain unclear. Here, we investigated the effects of calcitriol, an active form of vitamin D3, on an NC/Nga mouse model of atopic dermatitis. We observed that the topical application of calcitriol decreased the dermatitis scores and epidermal thickness of NC/Nga mice with atopic dermatitis compared to untreated mice. In addition, both stratum corneum barrier function as assessed by the measurement of transepidermal water loss and tight junction barrier function as evaluated by biotin tracer permeability assay were improved following calcitriol treatment. Moreover, calcitriol treatment reversed the decrease in the expression of skin barrier-related proteins and decreased the expression of inflammatory cytokines such as interleukin (IL)-13 and IL-33 in mice with atopic dermatitis. These findings suggest that the topical application of calcitriol might improve the symptoms of atopic dermatitis by repairing the dysfunctional epidermal and tight junction barriers. Our results suggest that calcitriol might be a viable therapeutic agent for the treatment of atopic dermatitis in addition to psoriasis.
The Effectiveness of Utilizing Critical Reading Strategies on Enhancing FL Freshmen̓ Reading Comprehension Skills

The present study discussed the effectiveness of utilizing critical reading strategies on developing FL freshmen̓ reading comprehension skills. Sixty participants took part in the present study. They are enrolled at the Faculty of Foreign Languages and Translation Language, Misr University for Science and Technology. They acted as one sampling group that responded to the pre/post-administrations of data collection instruments. Data were collected through a 20-item questionnaire of critical reading strategies and a FL reading comprehension test. The study adopted both methods of data analysis (the quantitative and qualitative). One-way analysis of variance (ANOVA) was employed to determine the statistical significant differences in the pre/post-administrations of the critical reading questionnaire and FL reading comprehension test. It also verifies the effectiveness of utilizing critical reading strategies on the enhancement of the participants’ performance in FL reading comprehension. The study introduced implications on the necessity of incorporating critical thinking strategies in the teaching of EFL reading skill.
HLA-Haplotypes Influence Microbiota Structure in Northwestern Mexican Schoolchildren Predisposed for Celiac Disease or Type 1 Diabetes

To contribute to and elucidate the participation of microbiota in celiac disease (CD) and type 1 diabetes (T1D) development, we evaluated the influence of HLA haplotypes, familial risk, and diet on the microbiota of schoolchildren. We conducted a cross-sectional study on 821 apparently healthy schoolchildren, genotyping HLA DQ2/DQ8, and registering familial risk. We analyzed the fecal microbiota using 16S rRNA gene sequencing, and autoantibodies for CD or T1D by ELISA. After analyses, we created three groups: at-high-risk children (Group 1), at-high-risk children plus autoantibodies (Group 2), and nonrisk children (Group 3). HLA influenced the microbiota of Groups 1 and 2, decreasing phylogenetic diversity in comparison to Group 3. The relative abundance of Oscillospiraceae UCG_002, Parabacteroides, Akkermansia, and Alistipes was higher in Group 3 compared to Groups 1 and 2. Moreover, Oscillospiraceae UCG_002 and Parabacteroides were protectors of the autoantibodies’ positivity (RRR = 0.441 and RRR = 0.034, respectively). Conversely, Agathobacter was higher in Group 2, and Lachnospiraceae was in both Groups 1 and 2. Lachnospiraceae correlated positively with the sucrose degradation pathway, while the principal genera in Group 3 were associated with amino acid biosynthesis pathways. In summary, HLA and familial risk influence microbiota composition and functionality in children predisposed to CD or T1D, increasing their autoimmunity risk.
The properties and implementation of the nonlinear vector space connectionist model

The nonlinear vector space expansion connectionist model is shown to have a number of advantages over currently applied networks for application to general connectionist problems. Firstly, it converges to its optimal solution far faster, by several orders of magnitude, than previously proposed networks, and this convergence time does not rise as quickly as a function of the size of the pattern vectors. Secondly, it is unimodal and consequently does not suffer from the problems of local minima such as needing to be reset, getting stuck or uncertainty about having converged. It may thus be left in adaptive mode while being 'on the job' as well as in training. Thirdly, the complete mathematical derivation of the network allows a much fuller understanding of its operation and allows direct application of adaptive filter knowledge. This allows easy parameter tuning and application of other adaptive filter update methods. It also allows the effects of approximation and implementation to be considered. The ability of the network to function well for random connection also allows the possibility of the implementation of the network by use of less exact technologies then electronic digital methods.
Human-Biting Ixodes scapularis Submissions to a Crowd-Funded Tick Testing Program Correlate with the Incidence of Rare Tick-Borne Disease: A Seven-Year Retrospective Study of Anaplasmosis and Babesiosis in Massachusetts

Tick-borne zoonoses pose a serious burden to global public health. To understand the distribution and determinants of these diseases, the many entangled environment–vector–host interactions which influence risk must be considered. Previous studies have evaluated how passive tick testing surveillance measures connect with the incidence of human Lyme disease. The present study sought to extend this to babesiosis and anaplasmosis, two rare tick-borne diseases. Human cases reported to the Massachusetts Department of Health and submissions to TickReport tick testing services between 2015 and 2021 were retrospectively analyzed. Moderate-to-strong town-level correlations using Spearman’s Rho (ρ) were established between Ixodes scapularis submissions (total, infected, adult, and nymphal) and human disease. Aggregated ρ values ranged from 0.708 to 0.830 for anaplasmosis and 0.552 to 0.684 for babesiosis. Point observations maintained similar patterns but were slightly weaker, with mild year-to-year variation. The seasonality of tick submissions and demographics of bite victims also correlated well with reported disease. Future studies should assess how this information may best complement human disease reporting and entomological surveys as proxies for Lyme disease incidence in intervention studies, and how it may be used to better understand the dynamics of human–tick encounters.
Microstructure of NbMoTaTiNi Refractory High-Entropy Alloy Coating Fabricated by Ultrasonic Field-Assisted Laser Cladding Process

Refractory high-entropy alloys (RHEAs) contain alloying elements with a high melting point, promising high-temperature applications due to their unique properties. In this work, laser cladding is used to prepare RHEAS based on NbMoTaTiNi. At the same time as laser cladding, the ultrasonic field is used, and then the microstructural characteristics, grain size, residual stress, wear, and hardness of the coating are evaluated. The results show that the coating is biphasic and includes the γ (Ni) and NbMoTaTiNi phase. The NbMoTaTiNi phase had a uniform distribution throughout the coating when the ultrasonic field was applied, so that when the ultrasonic field was not used, the NbMoTaTiNi powder, in addition to spreading uniformly, had the un-melting of large particles. This caused an increase in the residual tension of the coating. The conversion of columnar grains to the equiaxed, and the reduction in structural defects, were other characteristics of using the ultrasonic field. The formation of equiaxed grains with zigzag grain boundaries reduced the friction coefficient, wear volume loss, and the wear rate of the coating applied with ultrasonic.