Miracle-dz/UniFAR-FTUs huggingface dataset:
The multipopulation phenomenon in Galactic globular clusters: M4 and M22

Abstract We present an abundance analysis based on high-resolution spectra of red-giant-branch (RGB) stars in the Galactic globular clusters NGC 6121 (M4) and NGC 6656 (M22). Our aim was to study their stellar population in the context of the multipopulation phenomenon recently discovered to affect some globular clusters. Analysis was performed for the following elements: O, Na, Mg, Al, Ca, Fe, Y, and Ba. Spectroscopic data were completed by high-precision wide-field U BV IC ground-based photometry and HST/ACS observations. For M4, we find a well-defined Na–O anticorrelation composed of two distinct groups of stars with significantly different Na and O content. The two groups of Na-rich and Na-poor stars populate two different regions along the RGB. As regards M22, Na and O follow the well-known anticorrelation found in many other GCs. However, at odds with M4, it appears to be continuous without any hint of clumpiness. On the other hand, we identified two clearly separated groups of stars with significantly different abundances of the s-process elements Y, Zr and Ba. The relative numbers of the members of both groups are very similar to the ratio of the stars in the two subgiant branches of M22 recently found by Piotto (2009). The s-element-rich stars are also richer in iron and have higher Ca abundances. This makes M22 the second cluster after ω Centauri where an intrinsic spread in Fe was found. Both spectroscopic and photometric results imply the presence of two stellar populations in M4 and M22, even if both clusters have completely different characteristics.
Effects of Concentrated Long-Chain Omega-3 Polyunsaturated Fatty Acid Supplementation on Quality of Life after Radical Prostatectomy: A Phase II Randomized Placebo-Controlled Trial (RCT-EPA)

Prostate cancer (PCa) and associated treatments incur symptoms that may impact patients’ quality of life. Studies have shown beneficial relationships between diet, especially omega-3 fatty acids, and these symptoms. Unfortunately, only few data describing the relationship between long-chain omega-3 fatty acids (LCn3) and PCa-related symptoms in patients are available. The purpose of this study was to evaluate the effects of LCn3 supplementation on PCa-specific quality of life in 130 men treated by radical prostatectomy. Men were randomized to receive a daily dose of either 3.75 g of fish oil or a placebo starting 7 weeks before surgery and for up to one-year post-surgery. Quality of life was assessed using the validated EPIC-26 and IPSS questionnaires at randomization, at surgery, and every 3 months following surgery. Between-group differences were assessed using linear mixed models. Intention-to-treat analyses showed no significant difference between the two groups. However, at 12-month follow-up, per-protocol analyses showed a significantly greater increase in the urinary irritation function score (better urinary function) (MD = 5.5, p = 0.03) for the LCn3 group compared to placebo. These results suggest that LCn3 supplementation may improve the urinary irritation function in men with PCa treated by radical prostatectomy and support to conduct of larger-scale studies.
Comparison of a Barotropic Blocking Theory with Observation

Abstract In an effort to explain observed blocking phenomena, the work of Charney and DeVore (1979) and Hart (1979) has been extended to incorporate observed zonal topography in a barotropic nonlinear channel model. Multiple stationary equilibria are obtained, one of which, for an appropriate forcing, corresponds exactly to the “normal” winter flow predicted by Charney and Eliassen (1949) from the linearized version of the model. When this forcing is applied in the nonlinear model, other equilibria, related to resonances with the wevenumber 2 and 3 Fourier components of the zonal topography, occur. Wavenumber 1 and 4 resonances could also have occurred with slight modifications of the model. For comparison with observation, semi-objective criteria are adopted for identifying blocking events from daily 500 mb observations of 15 consecutive winter seasons. Following Dole (1979), we demand that there exist sufficiently large geopotential height anomalies for a sufficient length of time. Numerical values of t.
Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future

Among the myeloproliferative diseases, myelofibrosis is a widely heterogeneous entity characterized by a highly variable prognosis. In this context, several prognostic models have been proposed to categorize these patients appropriately. Identifying who deserves more invasive treatments, such as bone marrow transplantation, is a critical clinical need. Age, complete blood count (above all, hemoglobin value), constitutional symptoms, driver mutations, and blast cells have always represented the milestones of the leading models still used worldwide (IPSS, DIPSS, MYSEC-PM). Recently, the advent of new diagnostic techniques (among all, next-generation sequencing) and the extensive use of JAK inhibitor drugs have allowed the development and validation of new models (MIPSS-70 and version 2.0, GIPSS, RR6), which are continuously updated. Finally, the new frontier of artificial intelligence promises to build models capable of drawing an overall survival perspective for each patient. This review aims to collect and summarize the existing standard prognostic models in myelofibrosis and examine the setting where each of these finds its best application.
The kinetic energy spectrum of the two-dimensional enstrophy turbulence cascade

A direct numerical simulation of forced two-dimensional turbulence with hyperviscosity is performed at resolution 40962. A stage is reached at which the flux of enstrophy from large to small scales is approximately constant in time. The cubic and quintic relations for the third-order velocity structure function derived by Lindborg [J. Fluid Mech. 388, 259 (1999)] are verified. The calculated kinetic energy spectrum in the constant enstrophy flux range has the form E(k)=Keω2/3k−3, where eω is the enstrophy dissipation. This is in accordance with the prediction of Kraichnan [Phys. Fluids 10, 1417 (1970)] and Batchelor [Phys. Fluids 12, II233 (1969)]. The logarithmic correction, suggested by Kraichnan [J. Fluid Mech. 47, 525 (1970)], is not present in the calculated spectrum.
Mud‐rich low‐density turbidites in structurally‐controlled intraslope mini‐basin: The influence of flow containment on depositional processes and sedimentation patterns (Szczawa, Oligocene, Polish Outer Carpathians)

This study demonstrates the effectiveness of sedimentological–statistical multivariate analysis of one‐dimensional‐section in the unravelling depositional processes and sedimentation patterns recorded in a contained and partially ponded succession. Turbidite deposition of a 100 m thick mud‐rich Oligocene‐age sequence at Szczawa, the Polish Outer Carpathians, was primarily controlled by topographic confinement and magnitude of incoming flows. Only the largest turbidite flows were subjected to the true flow ponding, while in smaller volume flows the silty/sandy part behaved as unconfined flow and only muddy suspension cloud developed a ponded character. True ponding of low‐density turbidity currents is interpreted for sandstones that show sedimentary structures attesting to flow reflections and combined‐flow processes, and are associated with abnormally thick co‐genetic mudstones, which in turn results in low sandstone‐to‐mudstone ratio, irrespective of turbidite bed thickness. These features testify to pronounced interaction of flows with confining topography. Tractional structures associated with a considerable proportion of fines, namely banded structure and heterolithic bedding, are interpreted as produced during transitional (turbulent to laminar) flow phase in the condition of mud‐rich turbidite flow confinement. These structures are also considered here as indicators of proximity to source area and location on the slope. The co‐occurrence of banded sandstones, hybrid event megabeds and an olistostrome resulted from flows‐trapping, confined basin geometry, which precluded downslope propagation and further transformation of large‐volume flows. Therefore, a structurally‐controlled contained intraslope mini‐basin is proposed here as the most likely depositional setting. This work provides robust field and statistical evidence for ponding processes of low‐density turbidity currents in a structurally‐controlled mini‐basin. The results of this study are consistent with experimental data and recent field studies on ponded turbidites. Therefore, the Szczawa succession may serve as a new reference example of containment processes of low‐density turbidity currents and represents a valuable depositional model for intraslope turbidite succession.
A Novel Melspectrogram Snippet Representation Learning Framework for Severity Detection of Chronic Obstructive Pulmonary Diseases

A chronic obstructive pulmonary disease (COPD) is a major public health concern across the world. Since it is an incurable disease, early detection and accurate diagnosis are very crucial for preventing the progression of the disease. Lung sounds provide reliable and accurate prognoses for identifying respiratory diseases. Recently, Altan et al. recorded 12-channel real-time lung sound dataset, namely, RespiratoryDatabase@TR, for five different severity levels of COPD at the Antakya State Hospital, Turkey, and proposed deep learning frameworks for two-class COPD classification and five-class classification using a deep belief network (DBN) classifier and an extreme learning machine (ELM) classifier, respectively. The classification accuracies (ACC) of 95.84% and 94.31% were achieved for two classes and five classes, respectively. In this article, we have proposed a melspectrogram snippet representation learning framework for both two-class and five-class COPD classification. The proposed framework consists of the following stages: data augmentation and preprocessing, melspectrogram snippet representation generation from lung sound, and fine-tuning of a pretrained YAMNet. An experimental analysis on the RespiratoryDatabase@TR dataset demonstrates that the proposed framework achieves the accuracies of 99.25% and 96.14% for binary and multiclass COPD severity classification, respectively, which are superior to the only existing methods proposed by Altan et al. for severity analysis of COPD using lung sounds.
Effects of mismatch negative elicited by auditory deviant of horizontal locations in virtual space

The encoding of auditory spatial through neural circuits in auditory cortexes is ongoing research. The mismatch negativity (MMN) is a sensitive indicator of pre-attention auditory change detection, which has been to explore the potential mechanism of the auditory spatial information cortex. This paper studies the MMN response affected by the horizontal location deviance in virtual space using a passive oddball paradigm. The results showed that the MMN amplitude increased and latency decreased with the increase of spatial deviance at 30~90°, and the MMN amplitude and latency decreased with the increase of spatial deviance at 120~180°. But MMN amplitude and latency did not show obvious regularity at 180~330°. The topography showed that the right spatial deviance processed by the auditory system had the contralateral hemisphere dominance, and the left spatial deviance processed by the auditory system may be the combination of the right and contralateral hemisphere dominance. This study not only helps to further understand the pre-conscious processing mechanism of auditory spatial but also provides an objective reference for doctors to evaluate spatial hearing ability.
Psychometric Properties of the Brazilian Version of the Quality of Dying and Death for Adult Family Members of ICU Patients

Death is a complex, subjective phenomenon that requires an understanding of experiences to be qualified to provide care during the end-of-life process. This study aimed to analyze the psychometric properties of the Portuguese version (Brazil) of the Quality of Dying and Death (QODD) scale on family members of patients who died in adult intensive care units. A methodological study was conducted with 326 family members of patients that died in three ICUs of public hospitals in the state of São Paulo, Brazil. For this study, the QODD 3.2a (25 items and six domains) was administered during the period from December 2020 to March 2022. The analysis was performed using the classic theory of the tests and the goodness of fit of the model was tested using confirmatory factor analysis. We have used Spearman’s correlation coefficients between the scores of the overall scale and domains. Cronbach’s alpha coefficient and the intraclass correlation coefficient (ICC) were used for the evaluation of internal consistency and temporal stability, respectively. The Horn’s parallel analysis indicated two factors that were not confirmed in the exploratory factor analysis. A single factor retained 18 of the initial 25 items and the analysis of the goodness of fit to the unidimensional model resulted in the following: CFI = 0.7545, TLI = 0.690, chi-squared = 767.33, df = 135, RMSEA = 0.121 with 90%CI, and p = 5.04409. The inter-item correlations indicated a predominance of weak correlations among the items of the instrument. The items with the largest number of moderate correlations were questions 13b, 9b, and 10b and a strong correlation was found between questions 15b and 16b. Cronbach’s alpha coefficient was 0.8 and the ICC was 0.9. The Quality of Dying and Death—Version 3.2a (intensive therapy) in Brazilian Portuguese has a unidimensional structure and acceptable reliability. However, it did not obtain a good fit to the proposed factorial model.
A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale

In this paper, we study to improve acoustical methods to identify endangered whale calls with emphasis on the blue whale (Balaenoptera musculus) and fin whale (Balaenoptera physalus). A promising method using wavelet scattering transform and deep learning is proposed here to detect/classify the whale calls quite precisely in the increasingly noisy ocean with a small dataset. The performances shown in terms of classification accuracy (>97%) demonstrate the efficiency of the proposed method which outperforms the relevant state-of-the-art methods. In this way, passive acoustic technology can be enhanced to monitor endangered whale calls. Efficient tracking of their numbers, migration paths and habitat become vital to whale conservation by lowering the number of preventable injuries and deaths while making progress in their recovery.
Variability Study of the SX Phoenicis Star BL Camelopardalis

New time-series photometric observations of BL Cam in the V band and white light were made during 2005 to 2007 at the Xinglong Station of China. The frequency analysis confirms two closely separated frequencies, 25.181 d−1 and 25.571 d−1, but the frequency of 31–32 d−1 reported in the literature was not detected in the new data. New times of maximum light were determined from both our light curves and those available on Internet, allowing a more comprehensive study of the O−C diagram, together with the times of maximum light in the literature. A new interpretation, including the period increasing before 1988 and decreasing since 1992 of BL Cam and the light-time effect in a binary system, looks plausible.
Organization of Storm Track Anomalies by Recurring Low-Frequency Circulation Anomalies

Abstract From previous studies it is known that anomalous momentum fluxes by bandpass eddies are important in maintaining long-lasting tropospheric flow anomalies. Evidence is presented that suggests that these anomalous fluxes do not occur at random but happen because the structure of storm track activity is modified by the presence of prominent low-frequency, large-scale circulation anomalies. This behavior is noted in an extended integration of a perpetual January simulation with a general circulation model (GCM). Because nonlinear feedbacks between low- and high-frequency variability make it difficult to establish causal relationships between these two ranges of variability, a model is constructed that approximates the storm track activity that would be expected to accompany a given low frequency without including the feedback of the high frequencies onto the low-frequency state. This model is based on the linearized primitive equations and uses a series of short integrations from random initial condi.
Parasite and Pesticide Impacts on the Bumblebee (Bombus terrestris) Haemolymph Proteome

Pesticides pose a potential threat to bee health, especially in combination with other stressors, such as parasites. However, pesticide risk assessment tests pesticides in isolation from other stresses, i.e., on otherwise healthy bees. Through molecular analysis, the specific impacts of a pesticide or its interaction with another stressor can be elucidated. Molecular mass profiling by MALDI BeeTyping® was used on bee haemolymph to explore the signature of pesticidal and parasitic stressor impacts. This approach was complemented by bottom-up proteomics to investigate the modulation of the haemoproteome. We tested acute oral doses of three pesticides—glyphosate, Amistar and sulfoxaflor—on the bumblebee Bombus terrestris, alongside the gut parasite Crithidia bombi. We found no impact of any pesticide on parasite intensity and no impact of sulfoxaflor or glyphosate on survival or weight change. Amistar caused weight loss and 19–41% mortality. Haemoproteome analysis showed various protein dysregulations. The major pathways dysregulated were those involved in insect defences and immune responses, with Amistar having the strongest impact on these dysregulated pathways. Our results show that even when no response can be seen at a whole organism level, MALDI BeeTyping® can detect effects. Mass spectrometry analysis of bee haemolymph provides a pertinent tool to evaluate stressor impacts on bee health, even at the level of individuals.
Brain endothelial cells exposure to malaria parasites links type I interferon signalling to antigen presentation, immunoproteasome activation, endothelium disruption, and cellular metabolism

Introduction Cerebral malaria (CM) lethality is attributable to induction of brain edema induction but the cellular mechanisms involving brain microvascular endothelium in CM pathogenesis are unexplored. Results Activation of the STING-INFb-CXCL10 axis in brain endothelial cells (BECs) is a prominent component of the innate immune response in CM development in mouse models. Using a T cell-reporter system, we show that Type 1 IFN signaling in BECs exposed to Plasmodium berghei-infected erythrocytes (PbA-IE), functionally enhances MHC Class-I antigen presentation through gamma-interferon independent immunoproteasome activation and impacted the proteome functionally related to vesicle trafficking, protein processing/folding and antigen presentation. In vitro assays showed that Type 1 IFN signaling and immunoproteasome activation are also involved in the dysfunction of the endothelial barrier through disturbing gene expression in the Wnt/ß-catenin signaling pathway. We demonstrate that IE exposure induces a substantial increase in BECs glucose uptake while glycolysis blockade abrogates INFb secretion impairing immunoproteasome activation, antigen presentation and Wnt/ß-catenin signaling. Discussion Metabolome analysis show that energy demand and production are markedly increased in BECs exposed to IE as revealed by enriched content in glucose and amino acid catabolites. In accordance, glycolysis blockade in vivo delayed the clinical onset of CM in mice. Together the results show that increase in glucose uptake upon IE exposure licenses Type 1 IFN signaling and subsequent immunoproteasome activation contributing to enhanced antigen presentation and impairment of endothelial barrier function. This work raises the hypothesis that Type 1 IFN signaling-immunoproteasome induction in BECs contributes to CM pathology and fatality (1) by increasing antigen presentation to cytotoxic CD8+ T cells and (2) by promoting endothelial barrier dysfunction, that likely favor brain vasogenic edema.
Microbial Contamination and Antibiotic Resistance in Marketed Food in Bangladesh: Current Situation and Possible Improvements

Antimicrobial resistance (AMR) is a public health problem worldwide. Bangladesh, like its neighboring countries, faces many public health challenges, including access to safe food, inadequate food surveillance, as well as increasing AMR. This study investigated bacterial contamination and the AMR profile of pathogens in marketed food in Bangladesh and explored barriers to reducing AMR in the country. We collected 366 tomatoes, 359 chicken and 249 fish samples from 732 vendors in traditional markets in urban, peri-urban and rural areas in Bangladesh, as well as from 121 modern retails in Dhaka capital to analyse Vibrio cholerae and Escherichia coli in fish, Salmonella in chicken, and Salmonella and E. coli in tomatoes. Antibiotic susceptibility against 11 antibiotics was tested using a disc diffusion test and interpreted by an automated zone inhibition reader. In addition, a qualitative study using key informant interviews was conducted to explore antimicrobial use and AMR reduction potential in Bangladesh. We found E. coli in 14.21% of tomatoes and 26.91% of fish samples, while 7.38% of tomatoes and 17.27% of chicken were positive for Salmonella, and 44.98% of fish were positive for Vibrio cholerae. In total 231/319 (72.4%) of all pathogens isolated were multidrug-resistant (MDR) (resistant to three or more antibiotic groups). Qualitative interviews revealed an inadequate surveillance system for antibiotic use and AMR in Bangladesh, especially in the agriculture sector. To be able to fully understand the human health risks from bacterial hazards in the food and the AMR situation in Bangladesh, a nationwide study with a one health approach should be conducted, within all sectors, including AMR testing as well as assessment of the antimicrobial use and its drivers.
Design Compact YOLO based Network for Small Target Detection on Infrared Image

most YOLO object detection neural networks prefer to focus on traditional RGB image, but previous studies rarely consider special YOLO network with compact architecture for infrared image. In this paper, we analyze original YOLO network architecture, and we propose a compact YOLO based network by using different blocks from previous work for small target detection on infrared image. We use small target detection layer, GhostConv convolution, Focus structure, Focal EIOU Loss and soft NMS modules to improve original YOLO network structure, which improves the accuracy and speed of target detection for infrared image. The experimental results show that the accuracy of target detection of original model can be effectively improved by adding the small target detection layer, the Focus structure and the BI-FPN structure. By replacing the GhostConv convolution, the calculation speed is significantly improved. At last, after the model is quantized and deployed with NCNN framework, the object detection speed can reached to 35ms per infrared image.