Miracle-dz/UniFAR-FTUs huggingface dataset:
Classifying Tor Traffic Encrypted Payload Using Machine Learning

Tor, a network offering Internet anonymity, presented both positive and potentially malicious applications, leading to the need for efficient Tor traffic monitoring. While most current traffic classification methods rely on flow-based features, these can be unreliable due to factors like asymmetric routing, and the use of multiple packets for feature computation can lead to processing delays. Recognising the multi-layered encryption of Tor compared to nonTor encrypted payloads, our study explored distinct patterns in their encrypted data. We introduced a novel method using Deep Packet Inspection and machine learning to differentiate between Tor and nonTor traffic based solely on encrypted payload. In the first strand of our research, we investigated hex character analysis of the Tor and nonTor encrypted payloads through statistical testing across 8 groups of application types. Remarkably, our investigation revealed a significant differentiation rate of 94.53% between Tor and nonTor traffic. In the second strand of our research, we aimed to distinguish Tor and nonTor traffic using machine learning, based on encrypted payload features. This proposed feature-based approach proved effective, as evidenced by our classification performance, which attained an average accuracy rate of 95.65% across these 8 groups of applications. Thereby, this study contributes to the efficient classification of Tor and nonTor traffic through features derived solely from a single encrypted payload packet, independent of its position in the traffic flow.
Gastro Retentive Drug Delivery System: Latest Approach towards Novel Drug Delivery

Numerous attempts were improved to access the bioavailability and clinical output of oral dosage forms. Different types of gastro retentive drug delivery systems (GRDDS) was developed to enhance the therapeutic efficacy of medications which are unstable at alkaline pH, results a narrow absorption window with active locally in the stomach, and gets easily solubilized in acidic conditions. So the physiological condition of the stomach and the different elements that influence GRDDS will be discussed. In general, this review will illuminate and direct detailing researchers in planning, formulation, and designing the GRDDS.
Incidents of Complications after Reconstruction of Neglected Achilles Tendon Injury by Baker's Procedure

Introduction: Neglected Achilles tendon ruptures present a significant challenge in orthopedic surgery, with varied outcomes and complications. This study aims to evaluate the effectiveness of Baker's Procedure in the reconstruction of neglected Achilles tendon ruptures and to analyze the associated postoperative outcomes and complications. Methods: This prospective interventional study was conducted from January 1, 2012, to May 31, 2013, at multiple centers in Dhaka, Bangladesh. It included 42 patients aged 18 to 60 years with neglected Tendo-Achilles ruptures, defined as injuries untreated for over 4 weeks. Baker's Procedure, involving gastrocnemius aponeurosis advancement, was employed for reconstruction. Result: Of the 42 participants, 71.43% were male, with a mean age of 30.7 years. Injuries predominantly occurred in the right Achilles tendon (57.14%) and were mainly caused by sharp-metal objects (57.14%) and toilet-pan accidents (35.71%). Postoperative complications included stitch or wound infections (21.43%), pain (14.29%), stiffness (28.57%), and calf-muscle weakness (35.71%). Excellent, good, and fair outcomes were achieved in 64.29%, 21.43%, and 14.29% of patients, respectively. Conclusion: Baker’s Procedure is effective in reconstructing neglected Achilles tendon ruptures, with a majority of patients achieving excellent or good outcomes. However, the relatively high rate of postoperative complications, particularly infections, calf muscle weakness and stiffness, highlights the need for improved surgical and postoperative strategies. These findings underscore the importance of tailored.
Elucidating the Visual Snow Spectrum: A Latent Class Analysis Study

Objective People with visual snow syndrome (VSS) experience a range of perceptual phenomena, in addition to visual snow (VS; flickering pinpricks of light throughout the visual field). We investigated the patterns of perceptual phenomena associated with VSS in a large sample of people without prior knowledge of VSS or its associated symptoms. Methods and Measures. Two thousand participants completed a screening questionnaire assessing the frequency and severity of perceptual phenomena associated with VSS. We used latent class analysis (LCA), a clustering technique which identifies qualitatively different subgroups within a given population, to investigate whether the presence (or absence) of VS impacted class structure. Results Of 1,846 participants included for analysis, 41.92% experienced VS some of the time, including 4.49% who had VSS without prior knowledge. The mean number of perceptual phenomena experienced was 2.03. Optimal four-class LCA solutions did not substantially differ whether VS was included in the model; instead, classes differed in the frequency and total number of symptoms experienced. Discussion. Our results suggest that the perceptual phenomena associated with VSS are likely to be common in the general population and do not necessarily indicate an underlying pathology. We also showed that visual snow itself does not explain the presence of other perceptual phenomena.
Structures Detection Based on CLSK Model Combined With Shadow Information Using High-Resolution Remote Sensing Images

In light of rapid economic and urban growth, the proliferation of structures including transmission towers, signal poles, and wind generators has become evident. Consequently, precise object detection of these structures emerges as a pivotal approach to enhance infrastructure management. This technique establishes a robust foundation for achieving elevated efficiency, precision, optimized energy management, and heightened safety monitoring. This article introduces a novel model for detecting structure based on channel and large-scale selective kernel (CLSK) model using high-resolution images. The method is rooted in a two-stage target detection network, enabling simultaneous identification of both primary structures and their associated shadows. The incorporation of deformable convolutions augments the model's ability to extract intricate features. Moreover, the introduction of the innovative LSK attention module, along with the CLSK attention module, enhances the optimization of features gleaned from the network's core architecture. Simultaneously, the complete intersection over union loss function refines the network's focus by considering parameters such as center point distance and aspect ratio in addition to the conventional overlapping area. This comprehensive approach facilitates improved feedback on detection outcomes. Empirical evaluation of the proposed network underscores its superior performance when juxtaposed with both conventional network models and the rotating detection box network.
4D Facial Avatar Reconstruction From Monocular Video via Efficient and Controllable Neural Radiance Fields

We present an efficient approach for monocular 4D facial avatar reconstruction using a dynamic neural radiance field (NeRF). Over the years, NeRFs have been popular methods for 3D scene representation, but lack computational efficiency and controllabilty, thus it is impractical for real world application such as AR/VR, teleconferencing, and immersive experiences. Recent the introduction of grid-based encoding by InstantNGP has enabled the rendering process of NeRF much faster, but it is limited to static 3D scenes. To address the issues, we focus on developing a novel dynamic NeRF that allows explicit control over pose and facial expression, while keeping the computational efficiency. By leveraging a low-dimensional basis from the morphable model (3DMM) with elaborately designed spatial encoding branch and ambient encoding branch, we condition a dynamic radiance field in an ambient space, improving controllability and visual quality. Our model achieves rendering speeds approximately 30x faster at training and 100x faster at inference than the baseline (NeRFace), enabling practical approaches for real world applications. Through qualitative and quantitative experiments, we demonstrate the effectiveness of our approach. The dynamic NeRF exhibits superior controllability, enhanced 3D consistency, and improved visual quality. Our efficient model opens new possibilities for real-time applications, revolutionizing AR/VR and teleconferencing experiences.
Silicon Integrated Microwave Photonic Mixer Based on Cascaded Microring Resonator Modulators

In this letter, we propose an ultra-compact integrated microwave photonic mixer employing cascaded silicon microring resonator modulators (MRMs), which achieves a wide RF/LO bandwidth of up to 32 GHz while maintaining a high conversion efficiency of up to −12 dB. According to the experimental results, the conversion efficiency is insensitive to RF power fluctuations and can be enhanced by increasing the optical power. Furthermore, the linearity of the mixer is characterized, which shows a spurious-free dynamic range of 83.8 dBc $\cdot $ Hz2/3. The proposed scheme results in a significant reduction in device footprint, and comparable performance to the microwave photonic mixers reported previously, which demonstrates the feasibility of the silicon microring modulator for analog applications, such as radio over fiber communications, or microwave photonics.
Calibrating Phase Offsets for Commodity WiFi

The calibration of phase offsets between RF chains on commodity WiFi chips has been an key obstacle for many WiFi-based applications. In this paper, we conduct extensive experiments to explore the characteristics of the phase offsets. The real experimental results reveal that the phase offsets are actually deterministic. We explain such a phenomena via the circuit design of WiFi chips. We also show that the phase offsets are even the same among different chips. With extensive experiments, we obtain and report the measured phase offset values for the commodity Intel 5300 and Atheros AR9380 WiFi chips. With the observation illustrated in this paper, the calibration of the phase offsets can be simplified greatly.
Effects of Physical Activity on Body Composition, Muscle Strength, and Physical Function in Old Age: Bibliometric and Meta-Analyses

Objectives: Accumulating evidence suggests that physical activity (PA) is an efficient intervention to maintain functional capabilities and mitigate physiological changes in the older population. However, an attempt has yet to be made to comprehensively investigate the published landscape on the subject. Methods: This study had two aims. The first aim was to perform a bibliometric analysis for two keywords, “aging” and “PA”, to analyze the research trend. Since “frailty” was the most noticeable co-occurring keyword with the two keywords, the second aim was to investigate the effects of PA, particularly, resistance training (RT), on frailty using a meta-analysis to provide a summary of the current evidence base. Results: The bibliometric analysis revealed that the number of publications on this research topic has gradually increased, highlighting the importance of understanding the role of PA in aging. The meta-analysis found that RT had significant beneficial effects on physical frailty factors, including handgrip strength, lower limb strength, balance, gait speed, and stair-climbing ability. Conclusion: These findings demonstrate that RT is an effective intervention for improving physical function in frail populations; thus, it has important implications for the development of PA programs for older adults with frailty. Future research is warranted to explore the optimal dose, frequency, and duration of RT programs for older adults, as well as the potential benefits of combining RT with other forms of PA, such as aerobic or balance exercises.
FINet: Frequency Injection Network for Lightweight Camouflaged Object Detection

Existing camouflaged object detection (COD) methods typically have large model parameters and computations, hindering their deployment in real-world applications. Although using lightweight backbones can help alleviate this problem, their weaker feature representation often leads to performance degradation. To address this issue, we observe that frequency information has shown effective for cumbersome networks, but its effectiveness for lightweight ones has not been thoroughly investigated. Biological studies indicate that the human visual system utilizes distinct neural pathways to respond to different frequency stimuli, contributing to specialization and efficiency. Motivated by this, we propose an efficient frequency injection module (FIM) to aid lightweight backbone features by separately injecting detailed high frequency and object-level low frequency cues at each stage. FIM can be used as a plug-and-play component in existing COD networks to enhance backbone features at a low cost. With FIM, our proposed frequency injection network (FINet) achieves competitive performance against most state-of-the-art methods with much faster speed (692FPS for the input size of 384×384) and fewer parameters (3.74 M).
VISUAL LITERACY: COMIC STRIPS AS TEACHING MEDIA IN SIMPLE PRESENT TENSE

This study aims to measure the effectiveness of using comic strips as learning media for seventh-grade students in Simple Present Tense at SMPN 2 Sewon. The problem in this study was the students' understanding of grammar, especially in simple present tense, was low. This research is Quantitative, with a quasi-experimental pre-test and post-test as the research design. The comic strips used in this study were made by the researcher herself. The sample of this study was seventh-grade students, The total amount was 64 students, who were divided into two classes, namely experiment and control. The experiment class was given treatment in the form of comic strips as teaching media after the pre-test, while the control class was not. The results showed sig. (2-tailed) 0.000 < 0.05 and (-8.633) < (-2.039). Based on the result, it can be concluded that there is a significant difference between the learning outcomes in the pre-test and post-test in the experimental class. Comic Strips proved to be effective to be used as teaching media to help students' learning process in English grammar, especially simple present tense.
RESPONSES OF WINTERING GRASSLAND RAPTORS TO HUMAN DISTURBANCE

Human activities can affect the geographic distribution, dispersion patterns, habitat use, fecundity, survival, and activity and energy budgets of wildlife populations (Knight and Cole 1991). In most cases, the magnitude and frequency of disturbances determine whether or not the fitness of affected individuals will be altered. Additive and synergistic effects from multiple sources of disturbance can result in reductions of fitness, even when individual types of disturbance alone have no impact. Experiments are necessary to understand which aspects of human activity affect wildlife, and to develop management schemes that minimize conflicts between animals and human activities (Knight and Skagen 1988, Gutzwiller 1991). One such management practice is the creation of restricted areas that spatially or temporally separate wildlife from potential disturbance. For these buffer zones to be effective, they need to be based on empirical evidence of wildlife responses to disturbance (Knight and Skagen 1988). Most studies of wildlife disturbance have focused on the reproductive period and have addressed single species. As a result, we lack understanding of how concepts relating to human disturbance apply during the nonbreeding season. In addition, comparative studies that examine species assemblages can provide insights not evident from single-species studies (Skagen et al. 1991). We recorded flushing responses (whether animals fled because of a disturbance) and flush distances (the distance between the disturbance and the animal when flushed) of wintering grassland raptors disturbed by pedestrians and vehicles. Our objectives were to compare species-specific responses to the 2 disturbance types, to examine the hypothesis that flush distances positively correlate with species' body size (Cooke 1980), and to calculate minimum distances for species-specific buffer zones.
Sport fans using social media: A study on celebrity sports fans

Social media has become an essential platform for sports fans, athletes, clubs, and teams. This study provides a comprehensive review of the last decade’s research developments in social media, with a particular focus on how sports fans utilize this technology to engage with their interests. The study’s objectives are to explore how sports fans use social media to connect with their favorite athletes and teams, identify relevant theories and concepts that explain the significance of social media for sports fans, and analyze sports fans’ behavior and interactions on social media. Based on a review of 29 selected articles, the study finds that social media serves as a means for fans to express their fandom and that their identities and interactions on social media are framed by use and gratification theory, which is commonly employed in fan and social media research. Additionally, the study reveals that sports feminism has emerged among fans. While instances of racist comments and behavior among diehard fans remain a downside, it is crucial to investigate the importance of digital literacy among sports fans.
Outcomes of a Parent-Delivered Baby-mCIMT Model for Infants at High Risk of Unilateral Cerebral Palsy Using Remote Coaching in Telerehabilitation

There is growing evidence of the positive effects of constraint-induced movement therapy (CIMT) for infants at high risk of unilateral cerebral palsy (UCP) when provided by parents with in-person coaching/supervision from occupational therapists during home visits. The aim of this study is to investigate whether Baby-mCIMT (modifiedCIMT) can be as effective if parents are coached/supervised remotely. In this case-control study, we recruited 20 infants and re-used 18 controls, 4–8-month-old infants in both groups at high risk of UCP. The same protocol regarding inclusion criteria, data collection, and training volume was used in both groups. The training was conducted for two 6-week periods, separated by a 6-week break, consisting of daily 30 min sessions conducted by parents, supported by therapist coaching once a week. The primary outcome was measured using the Hand Assessment for Infants (HAI). There was no difference in the change of HAI units (p = 0.803) or that of the affected-hand raw score (p = 0.942) between the two groups. The remote coaching method was well received by parents. In conclusion, this demonstrates that remote coaching/supervision is as effective as the in-person approach, requiring less time and effort for both families and healthcare providers.
Comparing mass balance and adjoint methods for inverse modeling of nitrogen dioxide columns for global nitrogen oxide emissions

Satellite observations offer information applicable to top‐down constraints on emission inventories through inverse modeling. Here we compare two methods of inverse modeling for emissions of nitrogen oxides (NOx) from nitrogen dioxide (NO2) columns using the GEOS‐Chem chemical transport model and its adjoint. We treat the adjoint‐based 4D‐Var modeling approach for estimating top‐down emissions as a benchmark against which to evaluate variations on the mass balance method. We use synthetic NO2 columns generated from known NOx emissions to serve as “truth. ” We find that error in mass balance inversions can be reduced by up to a factor of 2 with an iterative process that uses finite difference calculations of the local sensitivity of NO2 columns to a change in emissions. In a simplified experiment to recover local emission perturbations, horizontal smearing effects due to NOx transport are better resolved by the adjoint approach than by mass balance. For more complex emission changes, or at finer resolution, the iterative finite difference mass balance and adjoint methods produce similar global top‐down inventories when inverting hourly synthetic observations, both reducing the a priori error by factors of 3–4. Inversions of simulated satellite observations from low Earth and geostationary orbits also indicate that both the mass balance and adjoint inversions produce similar results, reducing a priori error by a factor of 3. As the iterative finite difference mass balance method provides similar accuracy as the adjoint method, it offers the prospect of accurately estimating top‐down NOx emissions using models that do not have an adjoint.
Biostratigraphy and paleoenvironmental reconstruction of the marine lower Miocene Chechiș Formation in the Transylvanian Basin based on foraminiferal assemblages

Planktonic and benthic foraminiferal assemblages were used for biostratigraphy and paleoenvironmental reconstruction of the marine lower Miocene Chechiș Formation from the Gălpâia section (Sălaj county, Romania) in the northwestern Transylvanian Basin. Planktonic foraminifera suggest an Eggenburgian (Burdigalian) age for the deposits studied and reveal episodes of high primary productivity and mostly cool surface waters. Benthic foraminiferal assemblages indicate paleoenvironmental deepening from outer shelf to upper bathyal settings. Deltaic influences may be observed at the base of the studied section in outer shelf (possibly upper bathyal) environments with oxygenated bottom water and episodic high primary productivity, as a consequence of nutrient input from the land. Changes in paleobathymetry resulted in reduction of primary productivity. The benthic assemblages from the uppermost part of the section are dominated by tubular agglutinated foraminifera and indicate an upper bathyal setting with low organic flux to the sea floor. The sediments of the studied section were deposited during the late stage of the first early Miocene relative sea-level rise in the Transylvanian Basin.
Cancer Nano-Immunotherapy: The Novel and Promising Weapon to Fight Cancer

Cancer is a complex disease that, despite advances in treatment and the greater understanding of the tumor biology until today, continues to be a prevalent and lethal disease. Chemotherapy, radiotherapy, and surgery are the conventional treatments, which have increased the survival for cancer patients. However, the complexity of this disease together with the persistent problems due to tumor progression and recurrence, drug resistance, or side effects of therapy make it necessary to explore new strategies that address the challenges to obtain a positive response. One important point is that tumor cells can interact with the microenvironment, promoting proliferation, dissemination, and immune evasion. Therefore, immunotherapy has emerged as a novel therapy based on the modulation of the immune system for combating cancer, as reflected in the promising results both in preclinical studies and clinical trials obtained. In order to enhance the immune response, the combination of immunotherapy with nanoparticles has been conducted, improving the access of immune cells to the tumor, antigen presentation, as well as the induction of persistent immune responses. Therefore, nanomedicine holds an enormous potential to enhance the efficacy of cancer immunotherapy. Here, we review the most recent advances in specific molecular and cellular immunotherapy and in nano-immunotherapy against cancer in the light of the latest published preclinical studies and clinical trials.