Miracle-dz/UniFAR-FTUs huggingface dataset:
Impacts of Halogen Substitutions on Bisphenol A Compounds Interaction with Human Serum Albumin: Exploring from Spectroscopic Techniques and Computer Simulations

Bisphenol A (BPA) is an endocrine-disrupting compound, and the binding mechanism of BPA with carrier proteins has drawn widespread attention. Halogen substitutions can significantly impact the properties of BPA, resulting in various effects for human health. Here, we selected tetrabromobisphenol A (TBBPA) and tetrachlorobisphenol A (TCBPA) to investigate the interaction between different halogen-substituted BPAs and human serum albumin (HSA). TBBPA/TCBPA spontaneously occupied site I and formed stable binary complexes with HSA. Compared to TCBPA, TBBPA has higher binding affinity to HSA. The effect of different halogen substituents on the negatively charged surface area of BPA was an important reason for the higher binding affinity of TBBPA to HSA compared to TCBPA. Hydrogen bonds and van der Waals forces were crucial in the TCBPA–HSA complex, while the main driving factor for the formation of the TBBPA–HSA complex was hydrophobic interactions. Moreover, the presence of TBBPA/TCBPA changed the secondary structure of HSA. Amino acid residues such as Lys199, Lys195, Phe211, Arg218, His242, Leu481, and Trp214 were found to play crucial roles in the binding process between BPA compounds and HSA. Furthermore, the presence of halogen substituents facilitated the binding of BPA compounds with HSA.
Spatial updating of virtual displays during self-and display rotation

A remarkable accomplishment of the human perceptual system is the experience of a stable world amid changing perspectives. When movement occurs, the cognitive system updates the locations and orientations of objects in the environment accordingly. For example, when an observer turns 90o clockwise, a chair that was initially on the right is now perceived as being in front of the observer. Likewise, when the chair itself is moved from its rightward position to in front of the stationary observer, it is not perceived as a new object in a different location, but rather as the same chair having undergone a displacement. A recent trend in research in how the cognitive system achieves such stability is to focus primarily on the nature of retinal inputs, independently of the type of perspective change carried out (e.g., Biederman & Gerhardstein, 1993, 1995; Bülthoff & Edelman, 1992; Tarr, 1995; Tarr & Bülthoff, 1995; Tarr & Pinker, 1989). Few researchers have examined the role that perspective change itself may play (Simons & Wang, 1998; Wang & Simons, 1999). Although the examples of viewer and object movement described above may result in successful updating, the questions of whether these processes are similarly efficient and, if not, what factors may contribute to the differences are empirical ones. The aim of this paper is to examine these issues more closely. There is some evidence suggesting that spatial updating is not equivalent across different types of perspective change. In much of this work, observers’ updating performance during imagined selfand display movement has been examined (e.g., Amorim & Stucchi, 1997; Huttenlocher & Presson, 1979; Presson, 1982; Wraga, Creem, & Proffitt, 2000). In these experiments, blindfolded participants typically update the memorized locations of objects in a display after either imagining themselves rotating about the display or imagining the display itself rotating. Updating performance is usually found to be faster and more accurate after imagined rotations of the viewer than of the display. This advantage has been shown to persist whether the observer is immersed within the display or separate from it, and also when the display configuration is reduced to only one object (Wraga et al., 2000). A viewer advantage also has been found for spatial updating during physical movement of the self versus physical movement of the display. Simons and Wang (1998) showed that participants’ ability to detect covert changes of a configuration of objects viewed from different perspectives depended on whether the display or the observer
Stereotype susceptibility narrows the gender gap in imagined self-rotation performance

Summers have reignited the debate on the nature of intelligence and its consequences for academic achievement in men and women (Ripley, 2005). Although traditional gender gaps in cognitive performance have diminished over past decades, one of the few exceptions to this trend involves mental rotation, a skill of spatial reasoning that is critical to success in academic fields such as mathematics and science (Feingold, 1988; Masters & Sanders, 1993). Mental rotation tasks consistently yield the largest and most reliable gender differences of any cognitive task, with men’s performance surpassing that of women by approximately 1 SD (Campos, Pérez-Fabello, & GómezJuncal, 2004; Linn & Petersen, 1985; Masters & Sanders, 1993; Voyer, Voyer, & Bryden, 1995). A predominant explanation for the performance gap in mental rotation involves biological factors, such as differential hormonal levels (Geary, 1995; Kimura & Hampson, 1994). However, studies exploring the impact of stereotypes on cognitive performance suggest that social factors might also play a role. For example, in comparison with men, women perform worse on math tests when they are reminded of gender differences in mathematical abilities (Spencer, Steele, & Quinn, 1999). Steele and colleagues (Steele, 1997; Steele, Spencer, & Aronson, 2002) posited that stereotype threat—the fear of confirming a negative stereotype about a group to which one belongs—is responsible for such decrements in cognitive performance. Social psychologists have demonstrated the effects of stereotype threat on numerous other stigmatized groups, including African Americans (Steele & Aronson, 1995), Asian Americans (Shih, Pittinsky, & Ambady, 1999), and the elderly (Levy, 1996). The stereotype-threat literature has yielded at least two other noteworthy findings. The first is that the cognitive performance of dominant groups, such as White men, may also be susceptible to stereotype messages (see, e.g., Aronson et al., 1999; Brown & Josephs, 1999; Leyens, Désert, Croizet, & Darcis, 2000). Aronson et al. found that White men who were exposed to the stereotype that Asian men outperform White men in mathematics performed significantly worse on a math exam than did a control group of White men for whom the stereotype was not mentioned. Leyens et al. found selective deficits in men’s cognitive performance after exposure to the stereotype that men are relatively inefficient at processing affective information. Men made significantly more errors than did women on a subsequent lexical decision task involving affective processing; however, no differences were found between groups for nonaffective judgments, such as distinguishing between words and nonwords. Thus, men’s susceptibility to stereotype messages emphasizing women’s abilities was specific to the task reflecting the stereotype.
AppBox: A Black-Box Application Sandboxing Technique for Mobile App Management Solutions

Several Mobile Device Management (MDM) and Mobile Application Management (MAM) services have been launched on the market. However, these services suffer from two important limitations: reduced granularity and need for app developers to include third party SDKs. We present AppBox, a novel black-box app-sandboxing solution for app customisation for stock Android devices. AppBox enables enterprises to select any app, even highly-obfuscated, from any market and perform a set of target customisations by means of fine-grained security policies. We have implemented and tested AppBox on various smartphones and Android versions. The evaluation shows that AppBox can effectively enforce fine-grained policies on a wide set of existing apps, with an acceptable overhead.
Characterisation and Quantification of Crosstalk on a Velostat-Based Flexible Pressure Sensing Matrix

Crosstalk, in a sensor matrix, is the unwanted signal obtained at a sensor pixel that is not directly related to the stimulus. This paper presents a novel approach towards quantifying the crosstalk characteristics of a sensor matrix. The method involves obtaining the normalized sum of all the neighbouring pixel readings, weighted by their distance from the stimulated pixel. We have used this methodology to characterise the crosstalk for a $5\times 5$ velostat-based flexible pressure sensing matrix that uses a crossbar electrode architecture. The measure thus obtained is a dimensionless value between 0 to 1, 0 indicating no crosstalk and 1 indicating the maximum possible crosstalk. We characterized sensor matrices with three different pitch lengths: 3mm, 4mm, and 5mm. We observe the crosstalk values to lie between 0.032 to 0.17 across different weights and pitches, which indicates a low measure of crosstalk. The 5 mm pitch matrix displayed the least crosstalk, which was expected due to the larger spacing between the pixels. We also characterised the crosstalk for all 25 pixels of a 4 mm pitch matrix and found the mean to be $0.081\pm 0.002$, within the range from 0.0071 to 0.1656.
Improved ECA-DenseNet Framework for Brain MRI Image Classification

Early diagnosis is very important in brain tumors. Although Magnetic Resonance (MRI) is widely used for brain tumor detection, it is difficult to detect the tumor manually. Therefore, computer-aided diagnosis systems have been frequently utilized in recent years. In this study, an Efficient Channel Attention-Dense Convolutional Network (ECA-DenseNet) framework is proposed to detect tumors in patients based on brain MRI images. While detecting the tumor, it is tried to determine which type of tumor is present in the patient. In the developed ECA-DenseNet structure, an ECA block has been added to the dense blocks. The ECA block aimed to discard unimportant information and thus reduce the computation time. The improved DenseNet model has been tested on an open-source dataset. The improved model is compared with DenseNet-121, DenseNet-169, DenseNet-201, and DenseNet-264. The experimental results show the improving model has better classification performance than the others. The accuracy of the proposed model was 95.07%.
Arithmetic Optimization Algorithm Assisted Deep Learning Model for Remote Sensing Image Classification

The spatial resolution of remote sensing images (RSI) was continuously enhanced with the advances in RSI technology. As a fundamental unit of RSI interpretation, the scene is an integration of semantics, multiple objects, and environments. RSI scene understanding not just needs to identify all objects, but needs to observe the topology distribution of many objects in an RSI scene. As a standard representative of deep learning (DL), convolutional neural networks (CNNs) are a promising method to abstract the visual contents of RSI scenes. As a result, CNN was broadly implemented in scene-driven object detection, RSI scene classification, RSI retrieval, etc. This study presents an Arithmetic Optimization Algorithm Assisted Deep Learning Model for Remote Sensing Image Classification (AOADL-RSIC) approach. The presented AOADL-RSIC system exploits Gaussian filtering (GF) approach to eliminate noise. In the presented AOADL-RSIC technique, SqueezeNet model is used for feature extraction process. For the classification of different objects or classes in the RSIs, extreme learning machine (ELM) model is used. Finally, the AOA is applied for the optimum parameter adjustment of the ELM approach. The simulation results of the AOADL-RSIC system are tested on EUROSAT database and the outcome displayed the significance of the AOADL-RSIC approach on image classification process.
Mapping Shrimp Pond Dynamics: A Spatiotemporal Study Using Remote Sensing Data and Machine Learning

Shrimp farming and exporting is the main income source for the southern coastal districts of the Mekong Delta. Monitoring these shrimp ponds is helpful in identifying losses incurred due to natural calamities like floods, sources of water pollution by chemicals used in shrimp farming, and changes in the area of cultivation with an increase in demand for shrimp production. Satellite imagery, which is consistent with good spatial resolution and helpful in providing frequent information with temporal imagery, is a better solution for monitoring these shrimp ponds remotely for a larger spatial extent. The shrimp ponds of Cai Doi Vam township, Ca Mau Province, Viet Nam, were mapped using DMC-3 (TripleSat) and Jilin-1 high-resolution satellite imagery for the years 2019 and 2022. The 3 m spatial resolution shrimp pond extent product showed an overall accuracy of 87.5%, with a producer’s accuracy of 90.91% (errors of omission = 11.09%) and a user’s accuracy of 90.91% (errors of commission = 11.09%) for the shrimp pond class. It was noted that 66 ha of shrimp ponds in 2019 were observed to be dry in 2022, and 39 ha of other ponds had been converted into shrimp ponds in 2022. The continuous monitoring of shrimp ponds helps achieve sustainable aquaculture and acts as crucial input for the decision makers for any interventions.
Evaluation of the effect of amalgam fillings on the diagnosis of proximal caries using cone-beam computed tomography technique

ABSTRACT Background: Diagnosis of dental caries using cone-beam computed tomography (CBCT) may be hindered due to several introduced and inherent artifacts. The aim of this study was to evaluate the effect of amalgam fillings on the accuracy of diagnosis of proximal caries in CBCT. Materials and Methods: In this in vitro study, 102 extracted human teeth (mandibular and maxillary molars and premolars) were used. Six molars were chosen for mesio-occluso-distal amalgam restorations. Before obtaining the CBCT images, the 96 remaining teeth were stabilized in dental sockets of six dry human skulls in a way that the proximal contacts re-established. Thereafter, six of the molar teeth were replaced by the amalgam-restored teeth and the second group of images was then obtained. All images were evaluated by two independent observers in the panorama view and the presence or absence of caries was recorded. For histopathologic investigations, the teeth were cut and assessed by an oral pathologist using a stereomicroscope. The McNemar test was used for comparison between CBCT assessments and histopathologic evaluations (P < 0.05 was considered statistically significant). In addition, the receiver operating characteristics curve was utilized to evaluate the diagnostic accuracy in different sections of imaging. Results: The result sensitivity and specificity of CBCT imaging in the first group of images before placement of the restored teeth were 0.96 and 0.36, respectively. In the second group of images after placement of the restored teeth, these values were 0.78 and 0.18, respectively. Moreover, statistical analysis showed that there is a good agreement in interproximal caries diagnosis between histopathologic and CBCT imaging findings without placement of amalgam restorations (P < 0.001). However, this agreement does not exist after amalgam restorations (P = 0.84). Conclusion: Diagnosis of proximal caries using CBCT is not an efficient method where there are amalgam restorations adjacent to the suspected teeth.
Application of a Linked Hydrodynamic–Groundwater Model for Accurate Groundwater Simulation in Floodplain Areas: A Case Study of Irtysh River, China

The rich biodiversity in the floodplain area is influenced by both floodplain floods and groundwater (GW). To protect the ecological environment in the floodplain area, it is essential to study the interaction between floodplain floods and GW. The objective of this paper is to propose a coupling strategy between a hydrodynamic model and a GW model to provide an accurate simulation tool for quantifying the interaction between floodplain floods and GW. The case study is conducted in the floodplain area of the middle reaches of the Irtysh River in northwest China. Firstly, a two-dimensional hydrodynamic model based on TELEMAC-2D is constructed to accurately simulate floodplain floods under wetting and drying conditions. Secondly, a GW model based on MODFLOW is developed. Finally, a coupling strategy is proposed to achieve accurate and efficient integration between the hydrodynamic model and the GW model. The calibration and verification results of the model demonstrate high accuracy, with root mean squared error (RMSE) values of 0.51 m and 0.77 m between observed and calculated GW levels for the hydrodynamic–GW coupled model. The water balance results indicate that floodplain floods serve as the largest GW recharge source in the study area, while phreatic evaporation is the primary GW discharge item. This paper represents a novel attempt to couple a two-dimensional hydrodynamic model with a GW model. The research results provide a scientific tool for the ecological restoration of floodplain areas considering both surface water and GW, as well as the comprehensive management and regulation of wetland water resources and the water environment.
Multiple surface plasmon resonances enhanced nonlinear optical microscopy

Abstract The nonlinear optical microscopies of coherent two-photon excited fluorescence and anti-Stokes Raman scattering are strongly enhanced by multiple surface plasmon resonances (MSPRs). The Au@Ag nanorods presented strong MSPRs peaks at 800 and 400 nm, and can enhance nonlinear optical microscopy at fundamental and double frequencies, respectively. A two-dimensional (2D) material of g-C3N4 is employed to study the plasmon-enhanced nonlinear optical microscopy by the femtosecond laser. The electric analysis reveals that the MSPRs of the Au@Ag nanorod can significantly enhance the signals of two-photon excited fluorescence and anti-Stokes Raman scattering by up to the orders of 104 and 1016, respectively. The results demonstrate the great advantages of plasmon-enhanced nonlinear optical microscopy for the optical analysis on 2D materials, thus providing a new adventure for increasing the optical resolutions of nonlinear optical microscopy.
EL GENERO AEOLOSAURUS (SAUROPODA, TITANOSAURIDAE) EN LA FORMACION ALLEN (CAMPANIANO-MAASTRICHTIANO) DE LA PROVINCIA DE RIO NEGRO, ARGENTINA.

THE GENUS AEOLOSAURUS (SAUROPODA, TITANOSAURIDAE) IN THE ALLEN FORMATION (CAMPANIAN-MAASTRICHTIAN) OF RIO NEGRO PROVINCE, ARGENTINA. Remains assigned to Aeolosaurus Powell, 1986 from the Allen Formation are described. The specimen differs from the holotype of Aeolosaurus rionegrinus Powell, 1986 in the length of the prezigapophyses, relative position of the postzigapophyses, and radius and ischium morphology. Considerations on a specimen tentatively assigned to the type species, and modified diagnosis of genus are included. Association of dermal plates to the specimen here described is commented.
An open toolkit for tracking open science partnership implementation and impact [version 1; peer review: 1 approved, 1 approved with reservations]

Serious concerns about the way research is organized collectively are increasingly being raised. They include the escalating costs of research and lower research productivity, low public trust in researchers to report the truth, lack of diversity, poor community engagement, ethical concerns over research practices, and irreproducibility. Open science (OS) collaborations comprise of a set of practices including open access publication, open data sharing and the absence of restrictive intellectual property rights with which institutions, firms, governments and communities are experimenting in order to overcome these concerns. We gathered two groups of international representatives from a large variety of stakeholders to construct a toolkit to guide and facilitate data collection about OS and non-OS collaborations. Ultimately, the toolkit will be used to assess and study the impact of OS collaborations on research and innovation. The toolkit contains the following four elements: 1) an annual report form of quantitative data to be completed by OS partnership administrators; 2) a series of semi-structured interview guides of stakeholders; 3) a survey form of participants in OS collaborations; and 4) a set of other quantitative measures best collected by other organizations, such as research foundations and governmental or intergovernmental agencies. We opened our toolkit to community comment and input. We present the resulting toolkit for use by government and philanthropic grantors, institutions, researchers and community organizations with the aim of measuring the implementation and impact of OS partnership across these organizations. We invite these and other stakeholders to not only measure, but to share the resulting data so that social scientists and policy makers can analyse the data across projects.
Fabrication and Testing of a PneuNet Actuator-Based Caterpillar Like Amphibian Soft Robot for Multi-Terrain Applications

Bio-inspired structures provide several new possibilities in the area of robotics due to their superiority and diversity in execution. Researchers have been developing various robotic applications with the combination of soft materials such as silicone and various 3D printed materials. These kinds of soft robots can be useful for various human-robotic interactions such as search and rescue, medical surgery and so on. In this work, we present the fabrication and characterization of a small caterpillar-like soft robot (7 cm $\times 3.5$ cm $\times 3$ cm) powered using PneuNet actuation. Due to the limitations of traditional robotics, we believe that such soft material-based robots can be effective in various applications. The fabricated silicone-based PneuNet soft robot, which moves like a caterpillar, has also been embedded with an ESP camera module and LED light to enable applications such as surveillance and search-and-rescue. This soft robotic actuator can also perform tasks on various types of terrains, including ice and water surface. We find that the normalized distance travelled per actuation cycle on gravel to be 0.23 BL.
Longitudinal Analysis of the ASES and Constant–Murley Scores, and the Internal Rotation/Shift and Jobe Tests Following Arthroscopic Repair of Supraspinatus Lesions

It is essential to investigate patients post-surgery using functional surveys like the American Shoulder and Elbow Surgeons Shoulder (ASES) and the Constant–Murley shoulder (CMS) scores, as well as clinical tests, such as the Internal Rotation and Shift (IRO/Shift) and Jobe tests. In this study, 51 out of an initial 87 patients underwent an arthroscopic supraspinatus repair (22 single-row, 16 double-row, 13 debridement). Testing occurred pre-surgery, and 3 and 6 months post-surgery. Both surveys showed significant improvements over time among all 87 patients, but there were no differences between groups (lesion/no lesion) (p > 0.815) or time × group (p > 0.895). The IRO/Shift test showed a stronger ability to distinguish between both groups (positive vs. negative) with respect to the ASES and CMS scores over time, but the Jobe test did not (p > 0.100). Improvements in the CMS scores and the Jobe test were lower following repair compared to the ASES and IRO/Shift test. Most patients returned to adequate levels of functional abilities at 6 months post-surgery. The time required to return to activities of daily living and negative clinical tests was longer for the double-row repair patients compared to the single-row and debridement groups. In conclusion, both the functional surveys and the clinical tests demonstrated improvements following surgery.