Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupled Coccolith-Based Temperature and Productivity High-Resolution Reconstructions in the Eastern Equatorial Pacific During the Last Deglaciation and the Holocene

We present a new high-resolution reconstruction of annual sea-surface temperatures (SSTa) and net primary productivity (NPP) using novel coccolithophore-based models developed for the Eastern Equatorial Pacific (EEP). We combined published coccolithophore census counts from core-tops in the Eastern Pacific with 32 new samples from the Equatorial region, to derive a new statistical model to reconstruct SSTa. Results show that the addition of the new EEP samples improves existing coccolithophore-based SST-calibrations, and allow reconstructing SSTa in the EEP with higher confidence. We also merged the relative abundance of deep-photic species Florisphaera profunda in the same surface sediment samples with existing calibration datasets for tropical regions, to reconstruct annual NPP. Both temperature and productivity calibrations were successfully applied to fossil coccolith data from Ocean Drilling Project Site 1240, in the EEP. The coccolith-based SSTa estimates show a cooling during the Last Glacial Maximum (LGM) and the Younger Dryas, and warming at the start of the Holocene. This pattern differs in the timing and magnitude of the temperature changes from other available SST-reconstructions based on biogeochemical and faunal proxies. We discuss these discrepancies to be the result of different proxy sensitivities to insolation forcing, seasonal bias, and/or preservation artifacts. Reconstructed annual NPP shows a general decreasing trend from the late last glacial period to recent times, which we relate to the weakening of wind-driven equatorial upwelling towards the Holocene. We also calculated carbon export using our SSTa and NPP reconstructions, and compared to other geochemical-based reconstructions for the same location. Our coupled SSTa-NPP reconstruction provides key data to more fully assess the evolution of primary and export productivity as well as organic carbon burial in the EEP, with implications for its role in global biogeochemical cycles across glacial terminations.
The Absolute Magnitudes of RR Lyrae Stars and the Age of the Galaxy

It is shown that the intrinsic spread in the absolute magnitudes of the RR Lyrae variables in a given globular cluster can reach 0.5 magnitudes at a given period or at a given color, due to luminosity evolution away from the zero age horizontal (ZAHB). The size of this intrinsic luminosity spread is largest in clusters of the highest metallicity. The absolute magnitude of the ZAHB itself also differs from cluster to cluster as a function of metallicity, being brightest in clusters of the lowest metallicity. Three independent methods of calibrating the ZAHB RR Lyrae luminosities each show a strong variation of M V (RR) with [Fe/H] . The pulsation equation of P<P^' 5 = Q(M,T e ,L) used with the observed periods, temperatures, and masses of field and of cluster RR Lyraes gives the very steep luminosity-metallicity dependence of dM y (RR)/d[Fe/H] = 0.42. Main sequence fitting of the color-magnitude diagrams of clusters which have modern main-sequence photometry gives a confirming steep slope of 0.39. v
Does bisphenol-A affect alteration of gut microbiome after bariatric/metabolic surgery?: a comparative metagenomic analysis in a long-term high-fat diet induced-obesity rat model

Purpose Bisphenol A (BPA) is a widely used environmental contaminant that is associated with type 2 diabetes mellitus and a shift of gut microbial community. However, little is known about the influence of BPA on gut microbial changes related to bariatric surgery. We investigated whether long-term exposure to dietary BPA causing alterations of gut microbiome occurred after bariatric surgery. Methods Six-week-old male Wistar rats were fed either a high-fat diet (HFD) or HFD + BPA for 40 weeks. Then sleeve gastrectomy (SG) or Roux-en Y gastric bypass (RYGB) was performed in each diet group and observed for 12 weeks postoperatively. Fecal samples were collected at the 40th weeks and 12th postoperative weeks. Using 16S ribosomal RNA gene sequencing analysis on fecal samples, a comparative metagenomic analysis on gut microbiome composition was performed. Results Long-term exposure to HFD with BPA showed higher body weight change and higher level of fasting blood sugar after 40 weeks-diet challenge than those of the HFD only group. After bariatric surgeries, mean body weight of the HFD with BPA group was significantly higher than the HFD only group, but there was no difference between the SG and RYGB groups. The metagenomic analyses demonstrated that long-term exposure to dietary BPA did not affect significant alterations of gut microbiome before and after bariatric surgery, compared with the HFD groups. Conclusion Our results highlighted that BPA was a risk factor for obesity and may contribute to glucose intolerance, but it did not affect alterations of gut microbiome after bariatric/metabolic surgery.
Comparative Evaluation of Two Bracket Systems’ Kinetic Friction: Conventional and Self-Ligating

Friction is an intensely studied feature in orthodontics, as the sliding mechanics approach remains one of the most utilized techniques in current practice, and the question of whether self-ligating brackets produce less friction than conventional brackets still stands. The objective of this study was to compare a self-ligating system with different closing mechanisms and a conventional system with different ligating mechanisms regarding their frictional properties. Laboratory measurements were performed using an advanced materials testing machine generating tensile strength and load at maximum Load values, which were statistically analyzed and compared. These two parameters have been associated with the frictional resistance generated at the archwire–bracket slot interface. Statistically significant results were obtained when comparing the active self-ligating brackets with the passive self-ligating (tensile strength mean 1.953, SD 0.4231; load at maximum moad mean 6.000, SD 1.3000) and conventional brackets (tensile strength mean 1.953, SD 0.4231; load at maximum load mean 6.000, SD 1.3000), as well as when comparing the passive self-ligating brackets with the conventional brackets (tensile strength mean 1.708, SD 0.8628; load at maximum load mean 5.254, SD 2.645). The active self-ligating brackets tended to produce more friction when compared to the passive self-ligating brackets but were similar to conventional brackets with stainless steel ligatures.
Urinary MicroRNA Sensing Using Electrochemical Biosensor to Evaluate Colorectal Cancer Progression

Research in cancer diagnostics has recently established its footing and significance in the biosensor sphere, emphasizing the idea of a unique probe design used as a sensor and actuator, to identify the presence of protein, DNA, RNA, or miRNA. The fluorescein isothiocyanate (FITC) probe and biotinylated probe are designed for a two-pronged approach to the detection of the urinary miR-21 and miR-141, both of which have demonstrated significance in the development and progression of colorectal cancer, a leading cause of mortality and morbidity. The remainder of the apparatus is composed of a modified screen-printed carbon electrode (SPCE), to which the probes adhere, that transduces signals via the redox reaction between H2O2 and HRP, measured with chronoamperometry and cyclic voltammetry. The precise nature of our ultra-non-invasive biosensor makes for a highly sensitive and practical cancer detector, concluded by the significance when establishing disease presence (miR-21 p-value = 0.0176, miR-141 p-value = 0.0032), disease follow-up (miR-21 p-value = 0.00154, miR141 p-value < 0.0005), and even disease severity. This article hopes to emphasize the potential of an additional clinical tool for the management of colorectal cancer.
Incidence of radiographic scoliosis in asymptomatic young Pakistani adults

Background: Adolescent idiopathic scoliosis (AIS) is the most common scoliotic deformity of young adults. Screening of AIS is performed as part of the routine preemployment examination for physically demanding positions. We attempted to establish the incidence of clinically overt scoliosis in an adolescent (16 years old) and young adult (21 years old) population. Methods: We clinically and radiographically (X-rays) evaluated 85 applicants for physically demanding jobs in two age groups: those 16 versus those 21 years of age. Cobb’s angles and kyphosis angles were measured for each group. These data were then categorized into three grades based on radiographically documented scoliotic curvatures. Results: Most 16 years old demonstrated normal Cobb’s angles (90.56%), but kyphosis angles of 20–30° (40.27%). For the 21 years old, most participants had normal Cobb’s angles (93.75%), but exhibited higher than normal kyphosis angles (50%). Conclusion: Most young adults ages 16–21 years applying for physically demanding work were “fit. ” However, the incidence of kyphosis was higher among the 21 years old population. Such screening for idiopathic scoliosis should be more stringently performed in younger patients applying for physically demanding work.
Genomic Variation-Mediating Fluconazole Resistance in Yeast

Fungal infections pose a serious and growing threat to public health. These infections can be treated with antifungal drugs by killing hazardous fungi in the body. However, the resistance can develop over time when fungi are exposed to antifungal drugs by generating genomic variations, including mutation, aneuploidy, and loss of heterozygosity. The variations could reduce the binding affinity of a drug to its target or block the pathway through which drugs exert their activity. Here, we review genomic variation-mediating fluconazole resistance in the yeast Candida, with the hope of highlighting the functional consequences of genomic variations for the antifungal resistance.
Effects of Heat Stress and Exogenous Salicylic Acid on Secondary Metabolites Biosynthesis in Pleurotus ostreatus (Jacq.) P. Kumm

Pleurotus ostreatus (Jacq.) P. Kumm has high medicinal value, but few studies exist on regulating secondary metabolite biosynthesis. Environmental factors play a substantial role in the accumulation of microbial secondary metabolites. In this study, the effects of heat stress (24 h) and salicylic acid (0.05 mmol/L) treatment on the secondary metabolism of P. ostreatus were analyzed by metabolome, transcriptome, and gene differential expression analysis. Metabolome and transcriptome analyses showed that salicylic acid significantly increased the accumulation of antibiotics and polyketones, while heat stress increased the accumulation of flavonoids, polyketones, terpenoids, and polysaccharides. The content and the biosynthetic genes expression of heparin were markedly increased by heat stress, and the former was increased by 4565.54-fold. This study provides a reference for future studies on secondary metabolite accumulation in edible fungi.
Could 68Ga-PSMA PET/CT Evaluation Reduce the Number of Scheduled Prostate Biopsies in Men Enrolled in Active Surveillance Protocols?

Background: To evaluate the accuracy of 68Ga-prostate specific membrane antigen (PSMA) PET/CT in the diagnosis of clinically significant prostate cancer (csPCa) (Grade Group > 2) in men enrolled in Active Surveillance (AS) protocol. Methods: From May 2013 to May 2021, 173 men with very low-risk PCa were enrolled in an AS protocol study. During the follow-up, 38/173 (22%) men were upgraded and 8/173 (4.6%) decided to leave the AS protocol. After four years from confirmatory biopsy (range: 48–52 months), 30/127 (23.6%) consecutive patients were submitted to mpMRI and 68Ga-PSMA PET/CT scan before scheduled repeated biopsy. All the mpMRI (PI-RADS > 3) and 68Ga-PET/TC standardised uptake value (SUVmax) > 5 g/mL index lesions underwent targeted cores (mpMRI-TPBx and PSMA-TPBx) combined with transperineal saturation prostate biopsy (SPBx: median 20 cores). Results: mpMRI and 68Ga-PSMA PET/CT showed 14/30 (46.6%) and 6/30 (20%) lesions suspicious for PCa. In 2/30 (6.6%) men, a csPCa was found; 68Ga-PSMA-TPBx vs. mpMRI-TPBx vs. SPBx diagnosed 1/2 (50%) vs. 1/2 (50%) vs. 2/2 (100%) csPCa, respectively. In detail, mpMRI and 68Ga-PSMA PET/TC demonstrated 13/30 (43.3%) vs. 5/30 (16.7%) false positive and 1 (50%) vs. 1 (50%) false negative results. Conclusion: 68Ga-PSMA PET/CT did not improve the detection for csPCa of SPBx but would have spared 24/30 (80%) scheduled biopsies showing a lower false positive rate in comparison with mpMRI (20% vs. 43.3%) and a negative predictive value of 85.7% vs. 57.1%, respectively.
Test Sequences for Faults in the Scan Logic

Functional test sequences are used as manufacturing tests to complement scan-based tests. Functional test sequences target defects in the functional logic of the circuit. However, they may fail because of defects in the scan logic that prevent the circuit from operating correctly in functional mode. It is advantageous to detect such defects by dedicated test sequences before attempting to apply functional test sequences. The computation of dedicated test sequences for faults in the scan logic is the topic of this brief. The procedure described in this brief accepts a pool of functional test sequences. It identifies subsequences from the pool that are effective for detecting faults in the scan logic while balancing their lengths. It then compacts the sequences to reduce their total length further. Experimental results for benchmark circuits demonstrate large variations among different circuits in the total length of the sequences and significant reductions in the total length for all the circuits considered.
Early Prediction of Lung Cancers Using Deep Saliency Capsule and Pre-Trained Deep Learning Frameworks

Lung cancer is the cellular fission of abnormal cells inside the lungs that leads to 72% of total deaths worldwide. Lung cancer are also recognized to be one of the leading causes of mortality, with a chance of survival of only 19%. Tumors can be diagnosed using a variety of procedures, including X-rays, CT scans, biopsies, and PET-CT scans. From the above techniques, Computer Tomography (CT) scan technique is considered to be one of the most powerful tools for an early diagnosis of lung cancers. Recently, machine and deep learning algorithms have picked up peak energy, and this aids in building a strong diagnosis and prediction system using CT scan images. But achieving the best performances in diagnosis still remains on the darker side of the research. To solve this problem, this paper proposes novel saliency-based capsule networks for better segmentation and employs the optimized pre-trained transfer learning for the better prediction of lung cancers from the input CT images. The integration of capsule-based saliency segmentation leads to the reduction and eventually reduces the risk of computational complexity and overfitting problem. Additionally, hyperparameters of pretrained networks are tuned by the whale optimization algorithm to improve the prediction accuracy by sacrificing the complexity. The extensive experimentation carried out using the LUNA-16 and LIDC Lung Image datasets and various performance metrics such as accuracy, precision, recall, specificity, and F1-score are evaluated and analyzed. Experimental results demonstrate that the proposed framework has achieved the peak performance of 98.5% accuracy, 99.0% precision, 98.8% recall, and 99.1% F1-score and outperformed the DenseNet, AlexNet, Resnets-50, Resnets-100, VGG-16, and Inception models.
LGST-Drop: label-guided structural dropout for spatial–temporal convolutional neural networks

Abstract. Region dropout regularization strategies have proven to be highly effective at improving the generalization performance of convolutional neural networks (CNNs) in a variety of computer vision tasks including image classification, object detection, and semantic segmentation because these strategies enable models to focus on a wider range of image region information. However, for action recognition, models need to be able to extract not only useful spatial information but also important temporal and motion information, which cannot be satisfied by traditional regularization strategies. We propose a spatiotemporal dropout strategy to meet the need for regularization in spatial–temporal CNNs. We call it label guided spatial–temporal drop (LGST-Drop); it not only provides effectively structured dropout in the spatial dimension but also regularizes motion information in the temporal dimension. In addition, LGST-Drop’s mask is guided by the predicted categories of the model itself, which we called temporary labels. Extensive experiments on several standard datasets from action recognition domains show the usefulness of the proposed technique in comparison with the previous methods and theirstate-of-the-art variant algorithms.
Results of an Innovative Program for Surveillance, Prophylaxis, and Treatment of Infectious Complications Following Allogeneic Stem Cell Transplantation in Hematological Malignancies (BATMO Protocol)

Background Infectious complications are a significant cause of morbidity and mortality in patients undergoing allogeneic haematopoietic stem cell transplantation (Allo-SCT). The BATMO (Best-Antimicrobial-Therapy-TMO) is an innovative program for infection prevention and management and has been used in our centre since 2019. The specific features of the BATMO protocol regard both prophylaxis during neutropenia (abandonment of fluoroquinolone, posaconazole use in high-risk patients, aerosolized liposomal amphotericin B use until engraftment or a need for antifungal treatment, and letermovir use in CMV-positive recipients from day 0 to day +100) and therapy (empirical antibiotics based on patient clinical history and colonization, new antibiotics used in second-line according to antibiogram with the exception of carbapenemase-producing K pneumoniae for which the use in first-line therapy is chosen). Methods Data on the infectious complications of 116 transplant patients before BATMO protocol (Cohort A; 2016 - 2018) were compared to those of 84 transplant patients following the introduction of the BATMO protocol (Cohort B; 2019 - 2021). The clinical and transplant characteristics of the 2 Cohorts were comparable, even though patients in Cohort B were at a higher risk of developing bacterial, fungal, and CMV infections, due to a significantly higher proportion of myeloablative regimens and haploidentical donors. Results No change in the incidence of infections with organ localization was observed between the two Cohorts. A significant reduction in Clostridioides difficile infections by day +100 was observed in Cohort B (47% vs. 15%; p=0.04). At day +30, a higher incidence of Gram-negative bloodstream infections (BSIs) was observed in Cohort B (12% vs. 23%; p=0.05). By day +100 and between days +100 and +180, the incidence of BSIs and of the various etiological agents, the mortality from Gram-negative bacteria, and the incidence of invasive fungal infections were not different in the two Cohorts. The incidence of CMV reactivations by day +100 dropped drastically in patients of Cohort B, following letermovir registration (51% vs. 15%; p=0.00001). Discussion The results of this study suggest that the BATMO program is safe. In particular, the choice to avoid prophylaxis with fluoroquinolone was associated with an increase in Gram-negative BSIs by day +30, but this did not translate into higher levels of mortality. Moreover, this strategy was associated with a significant reduction of Clostridiodes difficile infections. The efficacy of anti-CMV prophylaxis with letermovir was confirmed by a significant reduction in CMV reactivations. Even though patients in Cohort B were at higher risk of developing fungal infections (more haploidentical transplants with more myeloablative regimens), the extensive use of posaconazole for prophylaxis balanced this risk, and no increase in the incidence of fungal-associated complications was observed.
A Beam-Scanning Printed Dipole Antenna Fed by a Rectangular Patch With Periodic Structures

In this letter, a beam-scanning printed dipole antenna fed by a rectangular patch with periodic structures is proposed. A simple rectangular patch embedded with rampart line structures is used as the novel feeding structure for the planar dipole. The embedded rampart line structures are used to reduce the size and radiation of the rectangular patch, which facilitates feeding. By exciting the coupled modes of the dipoles, continuous and gradual phase differences for the dipole arms can be achieved so as to achieve beam scanning. A double-layer reflector and director are used to enhanced the antenna gains. In the simulated results, the dipoles radiated a beam that scanned from −48° to 14° in the azimuth planes as frequency changed. The measured results show consistent scanning beams within the operating bands from 3.16 to 3.24 GHz. The measured gain ranged from 3.27 to 5.58 dBi within the corresponding bands. Furthermore, the proposed antenna had a high radiation efficiency close to 90%, as well as a compact size.
Prediction Model of International Trade Risk Based on Stochastic Time-Series Neural Network

With the extreme deterioration of domestic and foreign trade environment, international competition is becoming increasingly fierce. At the same time, many enterprises have loopholes in industrial structure and finance, resulting in many risks in their international trade. Therefore, we must take corresponding measures to effectively manage and avoid risks and realize the healthy and sustainable development of foreign trade enterprises and enterprise economy. This paper designs and proposes a risk prediction model combining ARIMA and BP neural network. The model can get good prediction in different time series and effectively avoid the risk. The model proposed in this paper optimizes the structure of the design model with the support of ARIMA algorithm and BP neural network algorithm and has good accuracy and error control for different time series. The purpose of establishing time series prediction model is to improve the prediction accuracy of the model, and it is also an effective way to enhance the practicability of the prediction model. Applying intersequence analysis method to financial risk prediction can greatly improve efficiency and save cost and has broad application prospects.