Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-parameter analysis of aero-icing problems via proper orthogonal decomposition and multidimensional interpolation

Steady and unsteady three-dimensional viscous turbulent aero-icing simulations are computationally expensive, especially for certification campaigns when broad parametric studies are needed. To overcome the computational effort of such investigations, a Reduced Order Modeling approach, based on Proper Orthogonal Decomposition and Kriging interpolation, is proposed. Using a database of high-fidelity numerical simulations, experimental data, or combinations of both, the proposed technique allows approximating solutions by linear combination of a limited number of eigenfunctions. Bayesian Kriging, a recent variant, is used to obtain the scalar coefficients for the expansion. The accuracy of the proposed method is assessed against reference solutions from two- and three-dimensional aero-icing simulations as well as against experimental data.
Semantic understanding of high spatial resolution remote sensing images using directional geospatial relationships

ABSTRACT Semantic understanding of high spatial resolution remote sensing (RS) images can be divided into object detection, object labelling, identification of geospatial relationships, and semantic description generation. Geographical relations represent the spatial distribution dependencies between geospatial entities such as points, lines, and polygons, and the topologies among them. Geospatial relations play a very important role in describing the relations between geographic objects. These relations can be broadly classified as topological, directional, and proximity relations. These relations describe the adjacency and association relations between geospatial objects. An approach to identify an appropriate directional geospatial relationship between geo-objects present in high spatial resolution RS images is proposed in this paper. Geospatial objects in the form of the closed boundary are taken as input and relationship triplets are generated. Two approaches have been used in the identification of directional relationships and the results of both approaches are compared. The first approach is based on the centroid of the objects and the second considers whole objects while calculating the direction. These relations are then further represented using a knowledge graph, where nodes represent objects and edges represent their relationship. Knowledge graph plays a very important role in overall scene understanding. It shows the association of all objects with each other. These relationships are then represented in the form of descriptions by using template-based sentence generation. Results show that these directional relationships are accurately identified between each pair of objects using both approaches, but relations generated by considering whole objects are closer to human cognition. Semantic understanding of remote sensing images is of great significance in different applications such as urban surveys, urban planning, and management, military intelligence, etc.
Building a Low-Cost Wireless Biofeedback Solution: Applying Design Science Research Methodology

In recent years, affective computing has emerged as a promising approach to studying user experience, replacing subjective methods that rely on participants’ self-evaluation. Affective computing uses biometrics to recognize people’s emotional states as they interact with a product. However, the cost of medical-grade biofeedback systems is prohibitive for researchers with limited budgets. An alternative solution is to use consumer-grade devices, which are more affordable. However, these devices require proprietary software to collect data, complicating data processing, synchronization, and integration. Additionally, researchers need multiple computers to control the biofeedback system, increasing equipment costs and complexity. To address these challenges, we developed a low-cost biofeedback platform using inexpensive hardware and open-source libraries. Our software can serve as a system development kit for future studies. We conducted a simple experiment with one participant to validate the platform’s effectiveness, using one baseline and two tasks that elicited distinct responses. Our low-cost biofeedback platform provides a reference architecture for researchers with limited budgets who wish to incorporate biometrics into their studies. This platform can be used to develop affective computing models in various domains, including ergonomics, human factors engineering, user experience, human behavioral studies, and human–robot interaction.
How does digital technology affect total factor productivity in manufacturing industries? Empirical evidence from China

Extensive studies have discussed the relationship between digital technology and total factor productivity (T.F.P.) in manufacturing industries, but far less attention is paid to the nonlinear relationship. Based on the panel data of China ’ s manufacturing industries and matching data of National Intellectual Property Public Service Network from 2000 to 2019, this article aims to explore how digital technology affects T.F. P. in manufacturing industries. The result demonstrates that a significant inverted U-shaped relationship is between digital technology and T.F. P. The threshold in high technology manufacturing industries is larger than that in low and middle technology manufacturing industries. With the progress of digital technology, the expenditure of technology and equipment upgrading is increasing. However, the marginal return of technology and equipment is decreasing, besides technology innovation. The case of China perhaps provides new insights into manufacturing industries in developing country to gain sustainable development.
Learning with Tablets in the Primary School: Learners' Perceptions and Impact on Motivation and Academic Performance

This article aims to evaluate the influence of using tablets for learning in the Moroccan educational context on learners’ motivation and academic performance. To do this, we conducted research in primary school, consisting of two stages: the first is based on a questionnaire, which we used to probe the perceptions of learners towards learning with tablets, and the influence of this practice on their motivations; And the second is an experimentation with tablets in classroom to assess the impact on academic performance. Two groups, respectively of 30 and 35 learners, participated in this second part of the study, in which we used student’s t statistic to compare two independent samples. The results showed, on the one hand, a strong motivational power of the use of the tablets on the learning process; and on the other hand, a positive impact on the learners’ academic performance.
H-alpha observations of spiral galaxies in Cancer, A1367, and Coma

We have used large aperture H.cap alpha. photometry of 65 spiral galaxies in the Cancer, Coma, and Abell 1367 clusters to compare the ionized-gas contents and star-formation rates in cluster and field spirals. Overall, we do not observe any significant deficiency of H.cap alpha. emission in the cluster members. Emission strength correlates strongly with integrated galaxy colors, but only weakly with H I content. All three clusters contain several galaxies with unusually strong H.cap alpha. emission, including several H I-poor objects in Coma and A1367. Thus, spirals which appear ''anemic'' in their morphology or exhibit weak H.cap alpha. emission are not necessarily H I poor; conversely, H I poor spirals can show strong H.cap alpha. emission, indicating relatively high current star-formation rates. Gas depletion time scales for some objects in the core of Coma are significantly shorter than the field, indicating rapid stellar and gaseous evolution.
MRI of Implantation Sites Using Parallel Transmission of an Optimized Radiofrequency Excitation Vector

Postoperative care of orthopedic implants is aided by imaging to assess the healing process and the implant status. MRI of implantation sites might be compromised by radiofrequency (RF) heating and RF transmission field (B1+) inhomogeneities induced by electrically conducting implants. This study examines the applicability of safe and B1+-distortion-free MRI of implantation sites using optimized parallel RF field transmission (pTx) based on a multi-objective genetic algorithm (GA). Electromagnetic field simulations were performed for eight eight-channel RF array configurations (f = 297.2 MHz), and the most efficient array was manufactured for phantom experiments at 7.0 T. Circular polarization (CP) and orthogonal projection (OP) algorithms were applied for benchmarking the GA-based shimming. B1+ mapping and MR thermometry and imaging were performed using phantoms mimicking muscle containing conductive implants. The local SAR10g of the entire phantom in GA was 12% and 43.8% less than the CP and OP, respectively. Experimental temperature mapping using the CP yielded ΔT = 2.5–3.0 K, whereas the GA induced no extra heating. GA-based shimming eliminated B1+ artefacts at implantation sites and enabled uniform gradient-echo MRI. To conclude, parallel RF transmission with GA-based excitation vectors provides a technical foundation en route to safe and B1+-distortion-free MRI of implantation sites.
G&D vignettes

Most readers ofGenes&Development todaymay not appreciate that the birth of the journal, in 1987, was an effort for scientists to take control over editorial decisions and publishing at the highest levels. At the time, Cell, Science, andNature each used a professional editorial staff and had not yet metastasized into innumerable specialty journals. Few nonprofit alternatives existed for submitting a full-length study in molecular biology that aimed for the highest levels of science publishing. This is not to disparage society journals, as I was an Editor of two of them, Molecular and Cellular Biology in the 1990s and Development in the 2000s, and worked hard to promote journal quality. The EuropeanMolecular BiologyOrganization started The EMBO Journal, run by scientists, in 1982, and it quickly emerged as a high-level publishing alternative. We in the States needed our own, and Cold Spring Harbor Laboratory stepped in, creating G&D, with its trademark ampersand linkingGenes toDevelopment. Terri Grodzicker, famous for her work in SV40 and adenovirus gene control, became G&D Editor in 1989, after the unfortunate passing of founding editor Steve Prentis and a period when Mike Mathews took the reins. Terri continued as Editor for over 30 years, creating a home for the best work.
MRI Screening in Vestibular Schwannoma: A Deep Learning-based Analysis of Clinical and Audiometric Data

Objective: To find a more objective method of assessing which patients should be screened for a vestibular schwannoma (VS) with magnetic resonance imaging (MRI) using a deep-learning algorithm to assess clinical and audiometric data. Materials and Methods: Clinical and audiometric data were collected for 592 patients who received an audiogram between January 2015 and 2020 at Duke University Health Center with and without VS confirmed by MRI. These data were analyzed using a deep learning-based analysis to determine if the need for MRI screening could be assessed more objectively with adequate sensitivity and specificity. Results: Patients with VS showed slightly elevated, but not statistically significant, mean thresholds compared to those without. Tinnitus, gradual hearing loss, and aural fullness were more common in patients with VS. Of these, only the presence of tinnitus was statistically significant. Several machine learning algorithms were used to incorporate and model the collected clinical and audiometric data, but none were able to distinguish ears with and without confirmed VS. When tumor size was taken into account the analysis was still unable to distinguish a difference. Conclusions: Using audiometric and clinical data, deep learning-based analyses failed to produce an adequately sensitive and specific model for the detection of patients with VS. This suggests that a specific pattern of audiometric asymmetry and clinical symptoms may not necessarily be predictive of the presence/absence of VS to a level that clinicians would be comfortable forgoing an MRI.
CNN-Based Fault Detection of Scan Matching for Accurate SLAM in Dynamic Environments

This paper proposes a method for CNN-based fault detection of the scan-matching algorithm for accurate SLAM in dynamic environments. When there are dynamic objects in an environment, the environment that is detected by a LiDAR sensor changes. Thus, the scan matching of laser scans is likely to fail. Therefore, a more robust scan-matching algorithm to overcome the faults of scan matching is needed for 2D SLAM. The proposed method first receives raw scan data in an unknown environment and executes ICP (Iterative Closest Points) scan matching of laser scans from a 2D LiDAR. Then, the matched scans are converted into images, which are fed into a CNN model for its training to detect the faults of scan matching. Finally, the trained model detects the faults when new scan data are provided. The training and evaluation are performed in various dynamic environments, taking real-world scenarios into account. Experimental results showed that the proposed method accurately detects the faults of scan matching in every experimental environment.
Neutrosophic social structures specificities

This paper is an extension of "(t, i, f)-Neutrosophic Structures" applicability , where were introduced for the first time a new type of structures, called (t, i, f)-Neutrosophic Structures, presented from a neutrosophic logic perspective. In any field of knowledge, each structure is composed from two parts: a space, and a set of axioms (or laws) acting (governing) on it. If the space, or at least one of its axioms (laws), has some indeterminacy of the form (t, i, f) â‰ (1, 0, 0), that structure is a (t, i, f)-Neutrosophic Structure. If the structure is applied to social environment, we have (t, i, f)- Neutrosophic Social Structures. The (t, i, f)- Neutrosophic Social Structures [based on the components t = truth, i = numerical indeterminacy, f = falsehood] are exponential remodeled in social space from the perspective of social actor. The social structure allows an infinite freedom of opinion, that is, everybody believes what he wants. The neutrosophic effervescence of social space is more powerful than of scientific environment for the case of natural sciences.
Design, Synthesis and Biological Evaluation of Quinoline-8-Sulfonamides as Inhibitors of the Tumor Cell-Specific M2 Isoform of Pyruvate Kinase: Preliminary Study

Cancer cells need to carefully regulate their metabolism to keep them growing and dividing under the influence of different nutrients and oxygen levels. Muscle isoform 2 of pyruvate kinase (PKM2) is a key glycolytic enzyme involved in the generation of ATP and is critical for cancer metabolism. PKM2 is expressed in many human tumors and is regulated by complex mechanisms that promote tumor growth and proliferation. Therefore, it is considered an attractive therapeutic target for modulating tumor metabolism. Various modulators regulate PKM2, shifting it between highly active and less active states. In the presented work, a series of 8-quinolinesulfonamide derivatives of PKM2 modulators were designed using molecular docking and molecular dynamics techniques. New compounds were synthesized using the copper-catalyzed azide-alkyne cycloaddition (CuAAC) reaction. Compound 9a was identified in in silico studies as a potent modulator of muscle isoform 2 of pyruvate kinase. The results obtained from in vitro experiments confirmed the ability of compound 9a to reduce the intracellular pyruvate level in A549 lung cancer cells with simultaneous impact on cancer cell viability and cell-cycle phase distribution. Moreover, compound 9a exhibited more cytotoxicity on cancer cells than normal cells, pointing to high selectivity in the mode of action. These findings indicate that the introduction of another quinolinyl fragment to the modulator molecule may have a significant impact on pyruvate levels in cancer cells and provides further directions for future research to find novel analogs suitable for clinical applications in cancer treatment.
Predicting inhabitable areas for locust based on field observation and multi-environmental factors in alpine grassland—A case study in the Qilian Mountain National Park, China

Alpine grassland is one of the most critical grassland types in the world, and it is vulnerable and sensitive to external disturbances. The development and outbreak of locust might result in the irreversible degradation. However, most locust studies have been on the tropical, temperate, and desert areas. Our knowledge of inhabitable areas in alpine grassland still needs to be explored. This study was carried out in the alpine grassland in the Qilian Mountain National Park. Environmental factors (remote sensing vegetation index, meteorology, soil, topography, and grassland types) and their impact on locust density were investigated. Finally, the inhabitable areas of locust in the study area were mapped. The results showed that: (1) six out of 26 factors [including precipitation, solar radiation (average and maximum value), normalized vegetation index (NDVI), soil, and temperature] had great influence on locust density, with a relative contribution (RC) more than 10%. (2) Among all locust density estimation models, those based on average and maximum solar radiation, maximum precipitation, maximum NDVI, average temperature, and clay content in deep soil performed better than others, with R ranging from 0.58 to 0.73 and root mean square error ranging from 21.70 to 25.82 head/m2. (3) The areas most suited for locust growth, development, and frequent outbreak were found in the south of Tianjun County, middle and northwest of Qilian County (account for 27% of the study area), while the inhabitability was weak in south of Gangcha County, northwest of Tianjun County, and most of Delingha City. Thus our study clarified the distribution region and occurrence variation of the locust and provided a scientific basis for locust prevention and control in alpine grassland in the Qilian Mountain National Park.
Necessary conditions for min-max problems and algorithms by a relaxation procedure

For decision making under uncertainty, a rational optimality criterion is min-max. Min-max problems such that the minimizer makes an optimal decision against the worst case that might be chosen by the maximizer are studied. This paper presents necessary conditions and computational methods for a min-max solution (not a saddle point solution). Those conditions are stated in a form like Kuhn-Tucker theorem. The computational methods are based on the relaxation procedure. A min-max problem such that the minimizer and the maximizer are subject to separate constraints is primarily studied. But it is shown that the obtained results can be applied for the unseparate constraint case by use of duality theory.
Interventional Pain Procedures: A Narrative Review Focusing On Safety and Complications. PART 2 Interventional Procedures For Back Pain

Abstract In patients where conservative approaches have failed to relieve from chronic pain, interventional procedures may be an option in well selected patients. In recent years there has been an increase in the use and development of invasive procedures. Concomitantly, there has also been an increase in the complications associated with these procedures. Taken this into consideration, it is important for healthcare providers to take a cautious and vigilant approach, with a focus on patient safety, in order to minimize the risk of adverse events and ensure the best possible outcome for the patient. This may include careful selection of patients for procedures, use of proper techniques and equipment, and close monitoring and follow-up after the procedure. The aim of this narrative review is to summarize the primary complications associated with commonly performed image-guided (fluoroscopy or ultrasound-guided) interventional procedures and provide strategies to reduce the risk of these complications. We conclude that although complications from interventional pain procedures can be mitigated to a certain degree, they cannot be eliminated altogether. In order to avoid adverse events, patient safety should be given considerable attention and physicians should be constantly aware of the possibility of developing complications.
People’s action for climate justice: a systematic review

ABSTRACT Increasing recognition of the multi-faceted injustices of climate change has led to growing interest in the actions people can take to advance climate justice (CJ). Yet, within the empirical literature on climate change action by everyday people, limited research has considered climate justice as a framework for action. To explore the current state of the literature on this critical topic, this systematic review examined 74 peer-reviewed articles (2008–2020) focused on CJ action. Within this rapidly-growing literature, we found that – in contrast to traditional definitions of action, which often emphasize individual behavioural shifts with consequences for the environment – people’s involvement in CJ action was largely framed as a collective pursuit with consequences for humanity. Moreover, in this multidisciplinary literature with data collected across 69 countries, CJ action was employed by children, youth, adults, and elders in diverse forms – from activism (e.g. protests) to community-based initiatives (e.g. restoration projects) – aimed at systemic change to prevent future climate-driven harms.
Liquid-gas transition and coexistence in ground-state bosons with spin twist

We study the thermodynamic liquid-gas transition and coexistence (LGTC) for ground-state bosons under contact interactions. We find that the LGTC can be facilitated by the mismatch of spin polarization, dubbed"spin twist,"between single-particle and interaction channels of bosons with spin degrees of freedom. Such a spin twist uniquely stabilizes the gas phase by creating an effective repulsion for low-density bosons, thereby enabling LGTC in the presence of a quantum droplet at a much larger density. We have demonstrated the scheme for binary bosons subject to Rabi coupling and magnetic detuning, where the liquid-gas transition can be conveniently tuned and their coexistence can be characterized by a discontinuous density profile in a harmonic trap. The spin twist scheme for LGTC can be generalized to a wide class of quantum systems with competing single-particle and interaction orders.
Strong Limit Theorems for Pairwise NQD Random Variables

A number of strong laws of large numbers for sequences of pairwise negative quadrant dependent (NQD) random variables have been established by using the generalized three series theorem. In this article, we obtain a strong law of large numbers by using the truncation technique and method of subsequences instead of the generalized three series theorem. Our result generalizes and improves on the corresponding one in Li and Yang (2008). We also obtain a complete convergence result for an array of rowwise pairwise NQD random variables.
Gun Code Binary Image Algorithm Based on Wavelet Packet and Niblack Method

Aiming at the characteristics of the gun code image that characters are easy to wear and contrast gradient is too large or too small,a binarization method based on wavelet packet filter floating threshold and Niblack method is proposed.Firstly,the image is filtered using wavelet packet filter and binarized with the low pass image after filtering.Then,the image is binarized with the Niblack method to obtain the second fusing image.Finally,two fusing images are merged based on the minimum principle of image gray values to get the final binarization image.Experimental results show that the method has a good performance in binarization effect and adaptation range and can imply in many situation.