Miracle-dz/UniFAR-FTUs huggingface dataset:
CN and CH Variations in the Globular Cluster M55

Blue spectra of a sample of 24 bright M55 (NGC 6809 = GC 1936-310) red giants within the magnitude range of 11.8<V<14 (−2.3<M V <−0.1) have been obtained with the CTIO 4 m telescope and Argus multifiber spectrograph. Indices sensitive to absorption by the 3883 A CN band were measured from these spectra and combined with the CN data of Smith & Norris [ApJ, 254, 149 (1982)] to yield CN band strength measurements for 47 stars. Aside from the CH star L2406, no stars with unusually strong 3883 A CN bands were detected. Analysis with the aid of synthetic spectra indicates a star-to-star spread in [N/A] of ≤ 0.3 dex
Biologically Important Areas for bowhead whales (Balaena mysticetus): Optimal site selection with integer programming

Place-based approaches to marine conservation identify areas that are crucial to the success of populations, species, communities, or ecosystems, and that may be candidates for special management actions. In the United States, the National Oceanic and Atmospheric Administration defined Biologically Important Areas (BIAs) for cetaceans (whales, dolphins, and porpoises) as areas and periods that individual populations or species are known to preferentially use for certain activities or where small resident populations occur. The activities considered to be biologically important are feeding, migrating, and activities associated with reproduction. We present an approach using spatial optimization to refine the BIA delineation process to be more objective and reproducible for conservation planners and decision makers who wish to use various spatial criteria to address conservation or management objectives. We present a case study concerning feeding bowhead whales (Balaena mysticetus) and bowhead whale calves in the western Beaufort Sea to illustrate the mechanics and benefits of our optimization model. In the case study, we incorporate spatial information about whales’ relative density and optimally delineate BIAs under different thresholds for minimum patch (cluster) size and total area encompassed within the BIA network. Results from our case study showed three consistent patterns related to minimum cluster size (contiguity) and maximum area threshold for both BIA types and all months: (1) cells with the highest whale density were selected when contiguity or maximum area thresholds were small; (2) for a given area threshold, the number of whales inside BIAs was inversely proportional to cluster size; and (3) the number of whales inside BIAs initially increased rapidly as the area threshold increased, but eventually approached an asymptote. Additionally, information on temporal variability in a BIA may influence the development of conservation, management, monitoring, or mitigation methods. To provide additional insight into the ecological characteristics of the BIAs selected during the optimization step, we quantified inter-annual variability in whale occurrence and density within individual BIAs using statistical techniques. The bowhead whale BIAs and associated information that we present can be incorporated with other relevant information (e.g., objectives, stressors, costs, acceptable risk, legal constraints) into conservation and management decision-making processes.
Characterization and Application of the Sugar Transporter Zmo0293 from Zymomonas mobilis

Zymomonas mobilis is a natural ethanologen with many desirable characteristics, which makes it an ideal industrial microbial biocatalyst for the commercial production of desirable bioproducts. Sugar transporters are responsible for the import of substrate sugars and the conversion of ethanol and other products. Glucose-facilitated diffusion protein Glf is responsible for facilitating the diffusion of glucose uptake in Z. mobilis. However, another sugar transporter-encoded gene, ZMO0293, is poorly characterized. We employed gene deletion and heterologous expression mediated by the CRISPR/Cas method to investigate the role of ZMO0293. The results showed that deletion of the ZMO0293 gene slowed growth and reduced ethanol production and the activities of key enzymes involved in glucose metabolism in the presence of high concentrations of glucose. Moreover, ZMO0293 deletion caused different transcriptional changes in some genes of the Entner Doudoroff (ED) pathway in the ZM4-ΔZM0293 strain but not in ZM4 cells. The integrated expression of ZMO0293 restored the growth of the glucose uptake-defective strain Escherichia coli BL21(DE3)-ΔptsG. This study reveals the function of the ZMO0293 gene in Z. mobilis in response to high concentrations of glucose and provides a new biological part for synthetic biology.
Offline performance and energy consumption prediction model of deep learning training tasks

Today, deep learning technology is widely used in a lot of scientific research fields. A crucial question is how to accurately predict the performance and energy consumption of deep learning training (DLT) tasks. Existing prediction methods of DLT tasks either have low accuracy or use too many cluster resources, and few methods focus on the energy consumption prediction. In this paper, we analyze the relationships between the characteristics of performance and energy consumption and the task configurations of DLT tasks. Then we propose an offline prediction model to predict the performance and energy consumption of DLT tasks based on these relationships. The experiment in an actual GPU cluster shows the effectiveness of the prediction model. The average deviation of the prediction model is 4.68%.
Indices of Mediterranean diet adherence and breast cancer risk in a community-based cohort

Introduction A Mediterranean-style dietary pattern is believed to have cancer-protective effects. We compared the prospective associations between adherence to four established Mediterranean diet indices and breast cancer risk (including total, postmenopausal, and hormone receptor positive cases) in women in the Framingham Offspring Study. Methods The four indices used two different approaches to measuring adherence to a Mediterranean diet: (a) scores based on the population-specific median intakes of Mediterranean diet-related foods in a given population (i.e., alternate Mediterranean Diet (aMED) index and Mediterranean Diet Score (MDS) index), and (b) scores based on compliance with recommended intakes of relevant foods from the Mediterranean diet pyramid [i.e., Mediterranean Diet (MeDiet) index and Mediterranean Style Dietary Pattern (MSDP) index]. Dietary data were derived from semiquantitative food frequency questionnaires collected in 1991-95. Participants included 1579 women aged ≤ 30 years who were free of prevalent cancer. Women were followed through 2014, and Cox proportional-hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for various confounders. Results During a median follow-up of approximately 18 years, 87 breast cancer cases were documented. Women in the highest (vs. lowest) score category of the pyramid-based scores (i.e., MeDiet or MSDP) had approximately 45% statistically significantly lower breast cancer risks. These effects were even stronger for any hormone receptor positive cases using the MeDiet index (highest vs. lowest score categories: HR = 0.45, 95% CI: 0.22–0.90). Neither of the median intake-based scores (i.e., aMED, MDS) was associated with breast cancer risk. Discussion Our results suggest that the methodology and the composition of Mediterranean diet indices influence their ability to assess conformity to this specific diet pattern and predict breast cancer risk.
Grammaires de levée d'ambiguïtés entre noms et adjectifs

SummaryMost of lexical ambiguity caused by homography can only be resolved by the syntactic analysis of the structures where the homographs appear. Thus, in order to resolve ambiguity caused by the homography between nouns and adjectives, we constructed for Portuguese formal grammars that describe noun phrase structures with adjectives. The formal properties of about 2,000 adjectives have been studied and, according to their behavior, they have been integrated in different classes and sub-classes. The syntactic and distributional properties of those adjectives were coded and associated to the corresponding entries of the Portuguese electronic dictionary DELAS. Furthermore, a library of more than one hundred local grammars for resolving ambiguity was constructed. Those grammars are represented internally by finite transducers that, in combination with the dictionary information, are applied by INTEX to the disambiguation of noun phrases. Some results of disambiguation are briefly discussed and exemplified.
Combining efficiency promotion of an all-fiber coherent combination system with special coupling-ratio fiber couplers for spatial diversity antennas in FSOC

The combination of numerous signals for a spatial diversity Free-Space Optical Communication (FSOC) framework can be actualized based on fiber-optic devices or digital signal processing. The optical combination process is normally achieved in binary tree structure to cascade multiple signals, so the number of input laser beams is subject to binary condition. In this article, we coherently combined an arbitrary number of laser beams by using a modified scheme based on the fiber couplers with specific coupling ratios. The theoretical research of three fibers combination is expressed and the practical combining efficiency of 98.3% is obtained in the experiment, which surpasses the theoretical greatest combining efficiency of customarily using 3-dB couplers. For a particular spatial diversity antenna that consists of 19 apertures, we designed its optical combination module based on specific fiber couplers. In the condition of phase differences among 19 input beams are compensated with SPGD algorithm, the average output power rises 25 to 40 times in the closed loop; the experimental combining efficiency reaches 56.5%, which is very close to the transmission efficiency of 59.3% where the combined module serves as a laser splitter without phase compensation. It means that overlooking the devices’ insert losses, the coherent combining efficiency reaches 95.3%. This study shows that optical combination provides an effective alternative for the digital signals combining process in spatial diversity FSOC.
VALS: Supporting Visual Data Analysis in Longitudinal Clinical Studies

Visual data analysis helps to understand different types of phenomena by allowing experts to explore for relationships, patterns, outliers, unexpected changes, and more. Experts need tools that help them find useful and actionable information in the data so that they can test their hypotheses and develop new ones. This need becomes more evident in longitudinal studies, where there are usually a large number of variables and the process being analyzed can be complex as well. We present VALS (Visual Analytics in Longitudinal Studies), a framework for visually exploring longitudinal clinical data. VALS includes a data model, a task categorization model, and an approach to guidance through feature engineering techniques and interactive visualizations, all of which help analysts perform their analysis tasks. VALS was designed in collaboration with healthcare experts with experience in longitudinal studies. We have also developed a tool prototype for a case study using real-world datasets. The evidence collected in the case study shows the usefulness of a VALS-based visual analytics tool.
Automated Emerging Cyber Threat Identification and Profiling Based on Natural Language Processing

The time window between the disclosure of a new cyber vulnerability and its use by cybercriminals has been getting smaller and smaller over time. Recent episodes, such as Log4j vulnerability, exemplifies this well. Within hours after the exploit being released, attackers started scanning the internet looking for vulnerable hosts to deploy threats like cryptocurrency miners and ransomware on vulnerable systems. Thus, it becomes imperative for the cybersecurity defense strategy to detect threats and their capabilities as early as possible to maximize the success of prevention actions. Although crucial, discovering new threats is a challenging activity for security analysts due to the immense volume of data and information sources to be analyzed for signs that a threat is emerging. In this sense, we present a framework for automatic identification and profiling of emerging threats using Twitter messages as a source of events and MITRE ATT&CK as a source of knowledge for threat characterization. The framework comprises three main parts: identification of cyber threats and their names; profiling the identified threat in terms of its intentions or goals by employing two machine learning layers to filter and classify tweets; and alarm generation based on the threat’s risk. The main contribution of our work is the approach to characterize or profile the identified threats in terms of their intentions or goals, providing additional context on the threat and avenues for mitigation. In our experiments, the profiling stage reached an F1 score of 77% in correctly profiling discovered threats.
Anaerobic duration predicts biogeochemical consequences of oxygen depletion in lakes

Lake deoxygenation is of growing concern because it threatens ecosystem services delivery. Complete deoxygenation, anoxia, is projected to prolong and expand in lakes, promoting the production or release of nutrients, greenhouse gases and metals from the water column and sediments. Accumulation of these compounds cannot be easily predicted thus hindering our capacity to forecast the ecological consequences of global changes on aquatic ecosystems. Here, we used monitoring data of four lakes to develop a novel tool, anaerobic duration, to study anaerobic processes in lake waters. Anaerobic duration explained, as a single predictor, 21–60% of the variation for ammonium, phosphorus and a dissolved organic matter fluorophore. Anaerobic duration could be modeled using only two oxygen profiles and lake bathymetry, making it an easily applicable tool to interpret and extrapolate biogeochemical data. This novel tool thus has the potential to transform widely available oxygen profiles into an ecologically meaningful variable.
Improved Regimes in High Pressure Magnetic Discharges

Field-Reversed Configuration (FRC) [1] and Gas-Dynamic Tr ap (GDT) [2] represent compact system, which is a special magnetic geometry for plasma confinement. Theoretical and experimental study of gas-dynamic regimes with high energy content is carried out. The approach to a high beta (b is the ratio of plasma pressure to magnetic pressure) magnetic systems assumed different regimes of plasma with beta > 0.5 that is proper to compact devices such as tori and mirror traps. Both FRC and GDT traps are axial symmetric configurations, has open field lines and poloidal magnetic field only. Last experimental results on GDT have shown the po ssibility to build the stationary system with high beta. Analysis of the global energy and particle balance together with the Monte-Carlo equilibrium modelling allowed to conclude that two-component plasma confined in a steady-state regime. The characteristic plasma lifetimes are 4 to 5 times less then the experiment duration. A peripheral gas-puff near the mirror region enabled to maintain the radial profile of background plasma during the all neutral beam injection (NBI) pulse. This report is focused mainly on ambipolar effect and the po ssibility of further increasing the fast ion energy content and β. Improved gas-dynamic regimes in high pressure magnetic discharges and microinstabilities arising are described. Synthesized hot ion plasmoid (SHIP) experiment in the compact mirror section attached to the GDT central cell and the scheme of compact tori (FRC formation) for the compact mirror cell of GDT device are presented. Fusion prospects (reactor, neutron source, material studies) of such systems with high-energy (fast) particles [3, 4] and hybrid FRC + GDT scheme proposed by author from Bauman Moscow State Technical University (BMSTU) are discussed. NOMENCLATURE AND ABBREVIATION b = ratio of plasma pressure to magnetic pressure τE = energy lifetime
Leptopus hispanus and Erianotus lanosus: the first DNA-assisted records of Leptopodidae (Hemiptera, Heteroptera) for the fauna of Georgia

The shore-bug (Leptopodidae Brullé, 1836) family is reported from Georgia for the first time upon several finds of Leptopus hispanus Rambur, 1840, and Erianotus lanosus (Dufour, 1834) (Hemiptera, Heteroptera). These species are widespread from the Mediterranean to Central Asia, including the Caucasus. Barcodes of the species, collecting information, and pictures of specimens are given.
Exploring Leadership Style and Employee Attitude through Cluster and Sentiment Analyses of In-Depth Interviews of Employees

In today’s fast-paced business environment, leaders who fail to recognize and respond to the emotions of their employees can result in stagnation or a lack of growth in their organization. In light of this, the current study presents a method for identifying leadership styles based on the perspectives of employees, exploring their perceptions of specific leadership traits. Drawing upon the Multifactor Leadership Questionnaire framework, this study aims to identify the leadership style of Tony Wedding Studio by conducting in-depth interviews with its employees. Through sentiment and cluster analyses of the collected data, the study identifies Idealized Influence Attributes and Laissez-faire as key leadership style traits. Additionally, this study sheds light on how employees react to and feel about their leader’s leadership style, providing valuable insights for organizational development and leadership training. Overall, this study emphasizes the importance of understanding and responding to employee perspectives in effective leadership.
ASPEN plus modelling of air-CO2 and air-steam-CO2 gasification of Parthenium hysterophorous for hydrogen and carbon monoxide rich syngas production

Abstract The simulation modelling of air-CO2 and air-steam-CO2 gasification of the aggressive weed, Parthenium hysterophorous is performed using an ASPEN Plus simulator and the outcomes are compared with an existing gasification study taken from the literature. The effect of temperature on the biomass gasification process, and the generation of the gases carbon monoxide (CO), carbon dioxide (CO2), hydrogen (H2), and methane (CH4) are estimated in the temperature range of 300 – 1000 °C. The objectives of this study are to identify the important processes within the operating variables of elemental parameters with the gasifying agents (air-CO2 and air-steam-CO2) and to understand how temperature impacts the yield of syngas. Research findings from the gasification of biomass by air-CO2 and air-steam-CO2 are also used for comparison. The syngas yield appears to be significantly impacted by temperature variation. Due to the introduction of CO2, the studies of the gas evolution in this gasification process demonstrate a substantial increase in the output % of H2 and CO due to the introduction of CO2.
One-way acoustic beam splitting in spatial four-waveguide couplers designed by adiabatic passage

In this work, we introduce quantum-mechanical adiabatic passage into the design of spatial acoustic four-waveguide (WG) couplers. Thanks to the agreement in form between the Schrödinger equation in quantum mechanics and the coupled-mode equation of classical wave, the behavior of propagating wave in coupled WGs is capable of mapping to quantum states driven by external fields. By coupling the input and output WGs with a mediator WG in space, an apparent beam splitting is realized and the ratio of intensity can be customized arbitrarily by altering the space-dependent coupling strengths. Moreover, a one-way propagation feature is exhibited in the spatial coupler when an appropriate loss is introduced in the mediator WG owing to the existence of dark state. This work builds a bridge between quantum adiabatic technology and acoustic beam splitter, which may have potential applications in acoustic communication, filtering and detection.
Studying wildfire behavior using FIRETEC

A coupled atmospheric/wildfire behavior model is described that utilizes physics-based process models to represent wildfire behavior. Five simulations are presented, four of which are highly idealized situations that are meant to illustrate some of the dependencies of the model on environmental conditions. The fifth simulation consists of a fire burning in complex terrain with non-homogeneous vegetation and realistic meteorological conditions. The simulated fire behavior develops out of the coupling of a set of very complex processes and not from prescribed rules based on empirical data. This represents a new direction in wildfire modeling that we believe will eventually help decision makers and land managers do their jobs more effectively.
Approaches for Stereo Matching

This review focuses on the last decade's development of the computational stereopsis for recovering three-dimensional information. The main components of the stereo analysis are exposed: image acquisition and camera modeling, feature selection, feature matching and disparity interpretation. A brief survey is given of the well known feature selection approaches and the estimation parameters for this selection are mentioned. The difficulties in identifying correspondent locations in the two images are explained. Methods as to how effectively to constrain the search for correct solution of the correspondence problem are discussed, as are strategies for the whole matching process. Reasons for the occurrence of matching errors are considered. Some recently proposed approaches, employing new ideas in the modeling of stereo matching in terms of energy minimization, are described. Acknowledging the importance of computation time for real-time applications, special attention is paid to parallelism as a way to achieve the required level of performance. The development of trinocular stereo analysis as an alternative to the conventional binocular one, is described. Finally a classification based on the test images for verification of the stereo matching algorithms, is supplied
Ocean thermal infrared remote sensing image registration combining AKAZE features and area feature

It is necessary to register the geometric position of ocean thermal infrared images to obtain information such as ocean temperature. The thermal infrared images are usually blurred because of the different imaging mechanisms. At the same time, it is difficult to obtain sufficient and uniformly distributed control points for geometric correction since the texture of ocean remote sensing images is relatively simple. Aiming at the above problems, a method combining point features based on the AKAZE algorithm and surface features as control data is proposed to register and correct thermal infrared images. And a verification experiment is designed using SDGSAT-1 thermal infrared images and Landsat optical images. The experimental results show that the proposed method can effectively register and correct SDGSAT-1 thermal infrared images with Landsat optical images in ocean areas.