Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulating a virtual target in depth through the invariant relation between optics, acoustics, and inertia

Research on multimodal perception (e.g., of objects in depth) has focused mainly on modal information (e.g., cues) and their integration at some levels of the central nervous system. Nevertheless, animal-environment interactions have simultaneous consequences on several energies (not to say all) that stimulate our perceptual systems. Thus these interactions provide structure not solely to individual energies but also to the way each energy varies relatively to the others (Stoffregen & Bardy, 2001). This relation across energies contains important intermodal information that is available as is any other within-modal pattern investigated so far. We decided to test that intermodal specification hypothesis in the context of egocentric distance perception. The idea is (i) to formalize and manipulate how distance is specified across optics, acoustics and inertias and (ii) to test whether it is perceived and used by humans.
Echinococcus granulosus as a Promising Therapeutic Agent against Triplenegative Breast Cancer

Breast cancer is a major cause of cancer deaths in women, with approximately 1.2 million new cases per year. Current treatment options for breast cancer include surgery, radiation, hormone therapy, and chemotherapy. However, the non-selective cytotoxicity of chemotherapeutic agents often leads to severe side effects, while drug resistance can worsen patient outcomes. Therefore, the development of more effective and less toxic anticancer drugs is a critical need. This study aimed to review the literature on Echinococcus granulosus antigens with anticancer potential against triple-negative breast cancer. Recent studies have suggested that certain parasite antigens may have potential anticancer effects. Specifically, research has shown that echinococcosis, a disease caused by the parasitic cestode Echinococcus granulosus, may have a protective effect against cancer. These findings offer new insights into the potential use of E. granulosus antigens in the development of novel cancer therapies and tumor cell vaccines. The findings of recent studies suggested that E. granulosus antigens may have the potential to be used in effective and less toxic cancer treatments. However, further research is needed to fully understand the mechanisms behind the anticancer effects of these antigens and develop new cancer therapies and vaccines
3-D numerical simulation on inner flow field in rectangular cross section isolator

A time dependent, implicit, finite volume, lower upper numerical method was used to solve the three dimensional compressible Reynolds averaged Navier Stokes equations and simulate the complicated flow phenomena such as shock trains and vortex structures in rectangular isolator caused by the shock wave/boundary layer interaction. Numerical solutions of the interaction in rectangular isolator were obtained, and the numerical results were compared with experimental data.
Evaluating the relationship of Customer and Supplier Involvement relating to Product characteristics on New Product Development by using Structural Equation Modeling

In the present era the changes in needs of customers are increasing along with the tremendous business competition in the prevailing market scenario. Therefore the expansion of economic progress as reflected by the manufacturing sector has focused on the development of new products. The basic purpose of this study is to determine the association between product characteristics, supplier, customer involvement, and the development of new products in the furniture market of Punjab Pakistan. For this study, the data of 180 respondents is collected through a survey questionnaire by using convenience sampling. The gathered data is examined by the structural equational modeling (SEM) through partial least square (PLS). Findings of the study indicate that product characteristics such as product differentiation and modularity have a significant relationship with supplier and customer involvement whereas findings concluded an insignificant relationship between product innovativeness with supplier involvement and product variety with customer involvement. Furthermore, results declared a significant relationship between customer and supplier involvement with new product development. This study will assist the manufacturer of the new product development to provide better marketing services.
Observations and light curve solutions of four ultrashort-period binaries

The paper presents light curve solutions of our observations of four new ultrashort-period eclipsing binaries with MS components. Two of them have periods almost at the upper limit (0.22 days) of the ultrashort-period binaries, while the periods of around 0.18 days of CSS J171508.5+350658 and CSS J214633.8+120016 are amongst the shortest known orbital periods. CSS J171410.0+ 445850, CSS J214633.8+120016 and CSS J224326.0+154532 are over contact binaries with fill out factors around 0.25 while CSS J171508.5+350658 is a semidetached system. The two targets with shortest periods consist of M dwarfs.
Book reviews: Introduction to mathematical programming, applications and algorithms (second edition)

INTRODUCTION TO MATHEMATICAL PROGRAMMING, APPLICATIONS AND ALGORITHMS (SECOND EDITION) by Wayne L. Winston Duxbury Press, Belmont, CA 94002, 1995, 818pp. This is not a new book, but I feel it is so outstanding that it should receive some attention. Recently, I had the opportunity to teach a class on linear optimization. Most of the students in this course are industrial engineering majors. I required a textbook that contained the necessary mathematics, but would be accessible to my class, and this book was an ideal match. The biggest asset of this text is the vast collection of applications that the author uses in the exercises and in the context of each subsection. There is an excellent mix of textbook problems as well as applications that come from industry and science. The familiar question, "Where am I going to use this stuff? " was never uttered in this class since the book did such a wonderful job of tying everything to applications. Many textbooks for this kind of class contain examples of applications, but Winston makes a notable effort in casting a wide net when finding applications for the material. This is a particularly perspicuous textbook. Students seemed to have an easy time reading it since it has small chapter sections, skillfully selected examples, and accessible prose. As a result, I was able to rely on the students reading their book, which allowed me to allocate more class time for small group work and to strive for a higher level of comprehension of the material. The text is not without difficulties. Although the title includes the words "Mathematical" and "Programming", it would be fair to say the book is not highly mathematical nor does it involve a whole lot of programming. The author avoids content that is mathematically intensive and keeps his focus on an audience that would prefer to avoid mathematical details. There is little in the way of programming, with some consideration on interpreting the results from pre-packaged software. However, I believe that a majority of students taking linear programming match this target audience quite well. Winston provides enough material to accommodate a year-long course. For a semester course, there is a dilemma as to what to cover. Chapter 1 is a short introduction and Chapter 2 is a crash course in matrix theory. The third chapter covers what a linear programming (LP) problem is and introduces the vocabulary that is used in the subsequent chapters. A complication with this chapter is that considerable time is spent formulating numerous examples of LP problems, whereas the algorithm used to solve these problems awaits, but in Chapter 4. It might be advisable to cover only part of Chapter 3 in order to move more quickly onto solving LP problems. …
On the rank of a real skew symmetric matrix described by an oriented graph

The oriented graph associated to a given real skew symmetric matrix S is defined as the weighted oriented graph whose skew adjacency matrix is S. Denote by the rank of the matrix S and by the minimum skew rank of the graph G. For any real skew symmetric matrix S whose associated oriented graph contains no joining even cycles, we in this paper give a necessary and sufficient condition for , where m is any integer with and denotes the matching number of . As an application of our results, we study the minimum skew rank problem, determining the minimum skew rank of graphs containing no joining even cycles, giving a characterization for graphs with and , respectively.
Key Maternity Care Stakeholders’ Views on Midwives’ Professional Autonomy

Advancement towards the professionalism of midwifery is closely linked to midwives’ professional autonomy. Although the perspectives of Belgian midwives on their professional autonomy have been studied, the views of other maternity care stakeholders are a blind spot. The aim of this study, therefore, was to explore maternity care stakeholders’ views on Belgian midwives’ professional autonomy. A qualitative exploratory study was performed using focus group interviews. A heterogenous group of 27 maternity care stakeholders participated. The variation between midwives, with different levels of autonomy, was reported. The analysis of the data resulted in five themes: (1) The autonomous midwife is adequately educated and committed to continuous professional further education, (2) The autonomous midwife is competent, (3) The autonomous midwife is experienced, (4) The autonomous midwife assures safe and qualitative care, and (5) The autonomous midwife collaborates with all stakeholders in maternity care. A maternity collaborative framework, where all maternity care professionals respect each other’s competences and autonomy, is crucial for providing safe and quality care. To achieve this, it is recommended to implement interprofessional education to establish strong foundations for interprofessional collaboration. Additionally, a regulatory body with supervisory powers can help ensure safe and quality care, while also supporting midwives’ professional autonomy and professionalisation.
Development and Analysis of a Distributed Leak Detection and Localisation System for Crude Oil Pipelines

Crude oil leakages and spills (OLS) are some of the problems attributed to pipeline failures in the oil and gas industry’s midstream sector. Consequently, they are monitored via several leakage detection and localisation techniques (LDTs) comprising classical methods and, recently, Internet of Things (IoT)-based systems via wireless sensor networks (WSNs). Although the latter techniques are proven to be more efficient, they are susceptible to other types of failures such as high false alarms or single point of failure (SPOF) due to their centralised implementations. Therefore, in this work, we present a hybrid distributed leakage detection and localisation technique (HyDiLLEch), which combines multiple classical LDTs. The technique is implemented in two versions, a single-hop and a double-hop version. The evaluation of the results is based on the resilience to SPOFs, the accuracy of detection and localisation, and communication efficiency. The results obtained from the placement strategy and the distributed spatial data correlation include increased sensitivity to leakage detection and localisation and the elimination of the SPOF related to the centralised LDTs by increasing the number of node-detecting and localising (NDL) leakages to four and six in the single-hop and double-hop versions, respectively. In addition, the accuracy of leakages is improved from 0 to 32 m in nodes that were physically close to the leakage points while keeping the communication overhead minimal.
Risk Estimation in Non-Enhancing Glioma: Introducing a Clinical Score

Simple Summary The preoperative risk estimation of non-enhancing suspected “low-grade” glioma (NEG) is key in determining the optimal timing of diagnosis and treatment to delay malignant progression and avoid undertreatment. The updated 2021 WHO classification brought new facets to glioma grading. Therefore, we sought to identify preoperative risk factors of malignancy in NEG by considering molecular criteria, including IDH mutation and CDKN2A/B deletion status. A total of 72 NEG patients were analyzed, and a high prevalence of malignant gliomas was detected considering both the traditional WHO grading (WHO grade 3 + 4) and the integrated molecular classification (IDHwt glioblastoma WHO grade 4 and IDHmut astrocytoma WHO grade 4). Easily determinable preoperative factors (age, T2/FLAIR mismatch sign, and SVZ involvement) were identified by uni- and multivariate analyses and incorporated into a score. The score estimates the probability of an NEG harboring a malignant glioma. Finally, the score was validated in a cohort of 40 NEG patients and proved to be a better prediction model than the Pignatti score or the T2/FLAIR mismatch sign. Abstract The preoperative grading of non-enhancing glioma (NEG) remains challenging. Herein, we analyzed clinical and magnetic resonance imaging (MRI) features to predict malignancy in NEG according to the 2021 WHO classification and developed a clinical score, facilitating risk estimation. A discovery cohort (2012–2017, n = 72) was analyzed for MRI and clinical features (T2/FLAIR mismatch sign, subventricular zone (SVZ) involvement, tumor volume, growth rate, age, Pignatti score, and symptoms). Despite a “low-grade” appearance on MRI, 81% of patients were classified as WHO grade 3 or 4. Malignancy was then stratified by: (1) WHO grade (WHO grade 2 vs. WHO grade 3 + 4) and (2) molecular criteria (IDHmut WHO grade 2 + 3 vs. IDHwt glioblastoma + IDHmut astrocytoma WHO grade 4). Age, Pignatti score, SVZ involvement, and T2/FLAIR mismatch sign predicted malignancy only when considering molecular criteria, including IDH mutation and CDKN2A/B deletion status. A multivariate regression confirmed age and T2/FLAIR mismatch sign as independent predictors (p = 0.0009; p = 0.011). A “risk estimation in non-enhancing glioma” (RENEG) score was derived and tested in a validation cohort (2018–2019, n = 40), yielding a higher predictive value than the Pignatti score or the T2/FLAIR mismatch sign (AUC of receiver operating characteristics = 0.89). The prevalence of malignant glioma was high in this series of NEGs, supporting an upfront diagnosis and treatment approach. A clinical score with robust test performance was developed that identifies patients at risk for malignancy.
Osteosarcoma of the Proximal Fibula: A Case Report and Review of the Literature

Osteosarcoma is the most common primary malignant bone tumor, especially in younger patients. Diagnosis is based on the combined evaluation of radiological, clinical, and pathological examinations. It is usually located in the distal femur, proximal tibia, and proximal humerus. The fibula is a rare localization for osteosarcoma. Surgery in this region is challenging due to the complex anatomic structures around the knee. Especially the peroneal nerve, lateral collateral ligament (LCL), and popliteal vessel branches are of critical importance. However, additional structures such as the arcuate ligament, biceps femoris, and iliotibial band play an essential role in the stabilization of the knee. Thus, these structures must be protected as much as possible. This case report aims to present the diagnosis and treatment process of conventional osteosarcoma in the proximal fibula, which was located close to the peroneal nerve and required LCL reconstruction after the resection.
Skill Level Classification in Basketball Free-Throws Using a Single Inertial Sensor

Wearable sensors are an emerging technology, with growing evidence supporting their application in sport performance enhancement. This study utilized data collected from a tri-axial inertial sensor on the wrist of ten recreational and eight professional basketball players while they performed free-throws, to classify their skill levels. We employed a fully connected convolutional neural network (CNN) for the classification task, using 64% of the data for training, 16% for validation, and the remaining 20% for testing the model’s performance. In the case of considering a single parameter from the inertial sensor, the most accurate individual components were upward acceleration (AX), with an accuracy of 82% (sensitivity = 0.79; specificity = 0.84), forward acceleration (AZ), with an accuracy of 80% (sensitivity = 0.78; specificity = 0.83), and wrist angular velocity in the sagittal plane (GY), with an accuracy of 77% (sensitivity = 0.73; specificity = 0.79). The highest accuracy of the classification was achieved when these CNN inputs utilized a stack-up matrix of these three axes, resulting in an accuracy of 88% (sensitivity = 0.87, specificity = 0.90). Applying the CNN to data from a single wearable sensor successfully classified basketball players as recreational or professional with an accuracy of up to 88%. This study represents a step towards the development of a biofeedback device to improve free-throw shooting technique.
Dust-Obscured Radio AGNS from the Wise Survey

Feedback from accreting BH (AGN) is thought to be responsible for the co-evolution of BHs and galaxies. It is likely to be prominent in the most luminous dust-obscured quasars, particularly those containing radio sources too luminous to be powered by starbursts. In order to investigate the feedback mechanism in detail, we select a unique sample containing ~ 200 of the most luminous obscured QSOs by cross-matching the WISE catalog with the FIRST and NVSS radio surveys. We present overall statistics for the observed range of colors and radio/mid-IR flux density ratio. We also present our efforts to understand the physical and evolutionary nature of these extreme feedback candidates using various telescopes such as Magellan, SOAR, Herschel, and ALMA.
Metal Ions Release from Welded Co—Cr Dental Alloys

Cobalt–chromium alloys (Co-Cr) are widely used in dentistry due to their excellent mechanical properties and corrosion resistance. Since prosthetic materials must be permanently stable in the oral cavity, it is very important to determine the release of ions from alloys in the oral cavity. In dentistry today, metals and alloys are mainly joined by laser and tungsten inert gas (TIG) welding. Therefore, in this work, the release of metal ions from six different Co-Cr alloys joined by these two welding methods was quantified to determine the effects of the welding method on an ion release. Static immersion tests, atomic absorption spectrometry and statistical analysis were performed for this purpose. The results showed that laser-welded alloys release a lower amount of metal ions compared to TIG-welded alloys.
Temporal Information Fusion Network for Driving Behavior Prediction

Since enormous hazards are caused by traffic crashes every year, ensuring safe driving is a hot topic in transportation. Technologies related to the Advanced Driver Assistance System (ADAS) are evolving rapidly. But without an adequate understanding of driving intention, ADAS usually can’t help the driver prepare for the danger in advance. This paper focuses on the fusion strategy of driver and environment information and proposes a lightweight end-to-end model, temporal information fusion network (TIFN). Driving behavior is the interactive result of the driver and the external world. To better understand the driver’s intention, the state update cell (STU) is proposed to introduce the influence of environment information into the driver’s state modeling, inspired by the selective attention of the human cognition process. Meanwhile, semantic segmentation features are extracted to offer clear clues affecting driver attention in place of motion optical flow images and binary value vectors. Finally, the driver’s intention and environment state are combined to make a joint prediction. The experiments evaluated on Brain4cars and IESDD show that the proposed approach has superior performance than other approaches that only use camera data.
Efficient Quantization Method for Biometric Fingerprint ImageCompression

The choice of quantization method and the requirement to achieve a trade-off between compressed image quality and degradation are very crucial in the overall performance of a lossy image compression algorithm. In this paper, uniform and non-uniform scalar quantization schemes of biometric fingerprint image were studied. Comparative analyses of non-uniform quantization methods were also conducted and these include dither-based quantization and the Lloyd-Max quantization methods. The quality of the quantized output fingerprint image was determined in terms of Signal-to-Quantization Noise Ratio (SQNR). The degree of distortion or quantization error was determined in terms of the Mean Square Quantization Error (MSQE). The non-uniform quantization method performed better than the uniform quantization method in terms of the SQNR and MSQE values. It was also found out that, the performance of dither-based non-uniform quantization on biometric fingerprint image is not as efficient as the LloydMax approach when the number of bits used in the quantization process increased. The results showed that the higher the number of bits used in the quantization process the higher the quality and the less the distortion in the resulting images.
Fractal and Statistic Analysis of Planar Shape of Meandering Rivers

The planar shape of large scale meandering rivers in nature is a kind of multi-scale fractal structuref,or which,fractal analysis was carried out in this paper by calculating the fractal box dimension of the center line of meandering river channels.The curvature and irregularity of large scale rivers were described with fractal dimensions.Besides,a method was established for river meander identification,generalization and statistic,and then applied in the analysis of the geometric shape of the Yellow River and the Yangtze River,etc.Statistic results of river meanders provide valuable information for related engineering constructionr,iver recovery and theoretical analysis.
Gut Microbiota-Derived Short-Chain Fatty Acids: Novel Regulators of Intestinal Serotonin Transporter

Serotonin (5-HT) is a key neurotransmitter synthesized both in the gut and the central nervous system. It exerts its signaling through specific receptors (5-HTR), which regulate numerous behaviors and functions such as mood, cognitive function, platelet aggregation, gastrointestinal motility, and inflammation. Serotonin activity is determined mainly by the extracellular availability of 5-HT, which is controlled by the serotonin transporter (SERT). Recent studies indicate that, by activation of innate immunity receptors, gut microbiota can modulate serotonergic signaling by SERT modulation. As part of its function, gut microbiota metabolize nutrients from diet to produce different by-products, including short-chain fatty acids (SCFAs): propionate, acetate, and butyrate. However, it is not known whether these SCFAs regulate the serotonergic system. The objective of this study was to analyze the effect of SCFAs on the gastrointestinal serotonergic system using the Caco-2/TC7 cell line that expresses SERT and several receptors constitutively. Cells were treated with different SCFAs concentrations, and SERT function and expression were evaluated. In addition, the expression of 5-HT receptors 1A, 2A, 2B, 3A, 4, and 7 was also studied. Our results show that the microbiota-derived SCFAs regulate intestinal serotonergic system, both individually and in combination, modulating the function and expression of SERT and the 5-HT1A, 5-HT2B, and 5-HT7 receptors expression. Our data highlight the role of gut microbiota in the modulation of intestinal homeostasis and suggest microbiome modulation as a potential therapeutic treatment for intestinal pathologies and neuropsychiatric disorders involving serotonin.