Miracle-dz/UniFAR-FTUs huggingface dataset:
Dendrimer-coupled sonophoresis-mediated transdermal drug-delivery system for diclofenac

: The purpose of the present study was to develop a novel transdermal drug-delivery system comprising a polyamidoamine dendrimer coupled with sonophoresis to enhance the permeation of diclofenac (DF) through the skin. The novel transdermal drug-delivery system was developed by using a statistical Plackett–Burman design. Hairless male Wistar rat skin was used for the DF-permeation study. Coupling media concentration, ultrasound-application time, duty cycle, distance from probe to skin, and a third-generation polyamidoamine-dendrimer concentration were selected as independent variables, while in vitro drug release was selected as a dependent variable. Independent variables were found to be statistically significant ( P  0.05). DF gel without dendrimer and ultrasound treatment to skin (passive delivery, run 13) showed 56.69 µ g/cm 2 cumulative drug permeated through the skin, while the DF-dendrimer gel without sonophoresis treatment (run 14) showed 257.3 µ g/cm 2 cumulative drug permeated through the skin after 24 hours. However, when the same gel was applied to sonophoresis-treated skin, drastic permeation enhancement was observed. In the case of run 3, the cumulative drug that permeated through the skin was 935.21 µ g/cm 2 . It was concluded that dendrimer-coupled sonophoresis-mediated transdermal drug delivery system has the potential to enhance the permeation of DF through the
Sentiment Analysis of Movie Reviews using Naïve Bayes Method with Gini Index Feature Selection

Sentiment analysis can be used to classify movie reviews whether the movie is good or bad. Unstructured data and a lot of data attributes become a problem in the classification process because it requires much time and computational capabilities. Feature selection in the classification process is needed to overcome computational time. In this paper, we use the Gini Index and multinomial Naive Bayes to reduce the dimension of features and document classification, respectively. Multinomial Naïve Bayes (MNNB) is a popular classifier used for document classification. This study aims to use the Gini Index Text (GIT) for text feature selection with MNNB classifier to classify movie review into positive and negative classes. The data that is used is IMDB dataset that contains reviews in English sentences, the data were divided into two parts, training data is 90% and data testing is 10%. The test results prove that the Gini index as a selection feature can increase accuracy where accuracy without feature selection is 56% and with feature selection of 59.54% with an increase of 3.54%.
Querying multiple bioinformatics information sources: can semantic web research help?

Advances in Semantic Web and Ontologies have pushed the role of semantics to a new frontier: Semantic Composition of Web Services. A good example of such compositions is the querying of multiple bioinformatics data sources. Supporting effective querying over a large collection of bioinformatics data sources presents a number of unique challenges. First, queries over bioinformatics data sources are often complex associative queries over multiple Web documents. Most associations are defined by string matching of textual fragments in two documents. Second, most of the queries required by Genomics researchers involve complex data extraction, and sophisticated workflows that implement the complex associative access. Third but not the least, complex Genomics-specific queries are often reused many times by Genomics researchers, either directly or through some refinements, and are considered as a part of the research results by Genomics researchers. In this short article we present a list of challenging issues in supporting effective querying over bioinformatics data sources and illustrate them through a selection of representative search scenarios provided by biologists. We end the article with a discussion on how the state-of-art research and technological development in Semantic Web, Ontology, Internet Data Management, and Internet Computing Systems can help addressing these issues.
Characterization of γ -Single Valued Neutrosophic Rings and Ideals

In this paper, we investigate the notion of γ -single valued neutrosophic subrings and ideals. Also, several properties related to the algebraic structure of rings and ideals are discussed. Moreover, many characterizations are proposed on γ -single valued neutrosophic subrings and ideals.
POTENSI ANGKUTAN UMUM PARIWISATA DI DAERAH ISTIMEWA YOGYAKARTA

Abstract One of the regional revenues which are given the first priority in the Province of Yogyakarta Special Region is from the tourism sector. The diversity of the tourism potential and tourism development show encouraging achievements within the last 5 years. This study is the first step to see the conditions and problems associated with public transportation services for tourism. This study shows that the permanent public transportation for tourism is potential to be implemented to attract more tourists to come. In addition, this transport can also reduce congestion, reduce the potential for accidents, save travel costs, save energy, and reduce pollution. Keywords : tourism, tourism potential, tourism transport, tourist cost Abstrak Salah satu penerimaan daerah yang mendapat prioritas utama Daerah Istimewa Yogyakarta adalah penerimaan dari sektor pariwisata. Beragamnya potensi pariwisata dan perkembangan pariwisata menunjukan capaian yang menggembirakan dalam kurun waktu 5 tahun terakhir. Penelitian ini merupakan langkah awal untuk melihat kondisi dan permasalahan yang terkait dengan angkutan pariwisata. Studi ini menunjukkan bahwa angkutan khusus pariwisata secara tetap berpotensi untuk diterapkan dalam mendukung peningkatan kunjungan wisatawan. Selain itu angkutan ini juga dapat mengurangi kemacetan, mengurangi potensi kecelakaan, menghemat biaya wisata, penghematan energi, dan mengurangi polusi. Kata-kata kunci : pariwisata, potensi pariwisata, angkutan pariwisata, biaya wisata
Evaluating the Impact of Neonicotinoid and Sulfoximine Pesticides on Honey Bee Workers, Apis mellifera L., under Laboratory Conditions

Application of pesticides can have a negative impact on pollinating honey bees, Apis mellifera L. , ranging from sublethal to lethal concentrations. Consequently, it is important to comprehend any possible impacts of pesticides. Herein, we evaluated the toxicity of specific pesticides (Sulfoxaflor, thiamethoxam, imidacloprid, and acetamiprid) on A. mellifera workers after exposure of 24, 48, 72, and 96 hrs under laboratory conditions. As a result, sulfoxaflor was considered the most toxic compound among the tested pesticides after 24-h of exposure. Further, acetamiprid was found least toxic pesticide. The same trend of toxicity on A. mellifera was observed after 48, 72, and 96 hrs of exposure. These results of the current investigation suggested that sulfoxaflor might be harmful to honey bee workers. This demonstrates the extraordinary sensitivity of local honey bee to routinely applied agricultural pesticides, which may have an impact on the colony level due to the extensive usage of these pesticides in Egypt.
A 61-187.2-GHz Traveling Wave Push-Push Frequency Doubler in a 130 nm SiGe:C BiCMOS Technology With 101.7% Fractional Bandwidth

This paper presents a differential, distributed frequency doubler using the Traveling Wave Principle for wideband operation. Three push-push stages, which are evenly distributed within two input transmission lines and one output transmission line, are employed in a proposed frequency doubler. The proposed doubler attains a 6 dB-bandwidth of 126.2 GHz, encompassing four frequency bands: the entire W- and D-band, and partially extending into the E-band and G-band. The maximum measured output power is -0.48dBm at the doubled frequency of 93 GHz. Furthermore, the fractional bandwidth of 101.7% surpasses the state of the art regardless of the technology employed.
Neural Network Implementation of Gaze-Target Prediction for Human-Robot Interaction

Gaze cues, which initiate an action or behaviour, are necessary for a responsive and intuitive interaction. Using gaze to signal intentions or request an action during conversation is conventional. We propose a new approach to estimate gaze using a neural network architecture, while considering the dynamic patterns of real world gaze behaviour in natural interaction. The main goal is to provide foundation for robot/avatar to communicate with humans using natural multimodal-dialogue. Currently, robotic gaze systems are reactive in nature but our Gaze-Estimation framework can perform unified gaze detection, gaze-object prediction and object-landmark heatmap in a single scene, which paves the way for a more proactive approach. We generated 2.4M gaze predictions of various types of gaze in a more natural setting (GHIGaze). The predicted and categorised gaze data can be used to automate contextualized robotic gaze-tracking behaviour in interaction. We evaluate the performance on a manually-annotated data set and a publicly available gaze-follow dataset. Compared to previously reported methods our model performs better with the closest angular error to that of a human annotator. As future work, we propose an implementable gaze architecture for a social robot from Furhat robotics1.1https://furhatrobotics.com/
Abnormal Detection of Worker by Interaction Analysis of Accident-Causing Objects

In industrial sites, many industrial accidents cause human casualties every year, and deep learning-based object detection and danger zone management technologies are being proposed to minimize accidents. However, existing studies have focused only on object detection which has poor performance when a dangerous situation occurs by interacting two or more accident-causing objects. This paper proposes a method that detects accident risks in advance through object detection and risk interaction analysis between objects. It consists of four modules: image acquisition, object detection, worker action analysis, and risk event detection by dangerous object interaction. YOLOv4 is selected and fine-tuned to detect workers and conveyor objects that cause accidents by interacting objects. After selecting the danger and caution zones, it determines whether or not the detection object exists around the danger zone. A total of 68,621 image datasets collected from industrial sites were created to train and evaluate the system. The mAP of 91.79% for object detection is obtained and the F1 score of 88.9% for risk event detection is obtained.
Pre-workout supplementation of capsaicin does not increase resistance training performance in a multiexercise protocol in trained men

Purpose. The aim of this study was to investigate the acute effect of capsaicin supplementation on performance, perceived exertion, and perceived effects in a resistance training protocol for the lower body. Methods. The sample was 14 young men (22.21 ± 2.55 years; 82.35 ± 5.16 kg; 174 ± 0.7 cm; 9.08 ± 2.73% of body fat), with 4.19 ± 2.98 years of experience in resistance training. The study design was randomised, double-blind and crossover. The subjects performed the training protocol after consuming capsaicin (12 mg) (cAP) or a placebo (PLA). The training protocol was: five sets of Back Squats and Leg Presses 45°, with 70% of 1rM until failure. The interval between sets was 90 seconds and 120 seconds between exercises. The number of maximum repetitions (NMr) and the rate of perceived exertion (rPE) were recorded after each set. Results. The paired t -test showed that there was no statistically significant difference between PLA and cAP in the mean NMr ( p = 0.251; 95%cI = –5.47 – 19.18), mean session volume load (VL) (weight lifted × NMr) ( p = 0.117; 95%cI = –582.70 – 4639.99) and in the mean rPE ( p = 0.458; 95%cI = –0.81 – 0.39). Conclusions. The acute capsaicin supplementation did not change the perception of vigour and side effects. Therefore, pre-workout
Multi-floor danger and responsiveness assessment with autonomous legged robots in catastrophic scenarios

In this work, we propose a strategy to implement the first two steps of the DRABC paradigm (Danger, Response, Airway, Breathing, Circulation) used by rescuers in Search and Rescue (SAR) with the use of a mobile quadruped robot. The robot is programmed to autonomously explore and create a map of the environment with the main objective of identifying areas of danger and reporting them to rescuers (first step of DRABC). While completing this first goal the robot must also identify people still inside the building, mark their position but also evaluate the health state of the person and in particular the response (second step of DRABC). Specifically, we propose new strategies for SAR considering that autonomous behaviour is particularly relevant before the human rescuers arrive: therefore, the policy adopted should privilege covering a broader area in the available time, rather than exploring a smaller area in depth. Strategies have been tested with the Spot robot from Boston Dynamics concerning both exploration and health assessment. The software developed and the tests to validate it are thoroughly described and explained.
Exploring the Interplay between Facial Expression Recognition and Emotional Intelligence in Adults: Implications for Novel Learning Methods

Background: Considering the widespread use of personal protective equipment (PPE) during the COVID-19 pandemic, which conceals facial expressions, this study aims (1) to explore facial expression recognition ability; (2) to assess the ability to read facial expressions under different conditions of face coverage; and (3) to investigate the role of emotional intelligence in facial expression recognition. This multidimensional exploration provides vital insights for creating novel learning methods, emphasizing the pivotal role of emotions. Methods: The study sample comprised 124 Italian adult subjects, consisting of 71 females (57.3%) and 53 males (42.7%), with a mean age of 35.31 years. The present investigation employed the Emotional Intelligence Scale (EIS) and an image-based questionnaire administered via the online platform Google Forms. Student’s t-test and one-way ANOVA were computed with SPSS (v. 29). Results: Significant differences were found based on gender, profession, and level of education in face expression recognition and emotional intelligence. The implications for learning processes are discussed. Conclusion: This study unveils the intricate dynamics of emotion recognition, gender, occupation, level of education’s influence, and emotional intelligence. By incorporating these insights into educational programs, a transformative process can be initiated, nurturing not only empathy, cultural insight, and emotional intelligence but also catalyzing the evolution toward inclusive and emotionally equipped societies.
DIALLEL ANALYSIS OF GRAIN YIELD AND SOME AGRONOMIC TRAITS IN NEW SEVEN YELLOW MAIZE INBRED LINES

: Diallel crosses, without reciprocals, among seven new yellow maize inbred lines derived from different maize populations were made in 2012 season at Giza Agric. Res. Station. The resultant 21 crosses along with two commercial check hybrids, i.e. SC 162 and SC 168 were evaluated in a randomized complete block design with four replications conducted at three locations, i.e. Sakha, Sids and Mallawy Agric. Res. Stations in 2013 season. The results indicated that mean squares due to GCA and SCA were highly significant for all traits studied, i.e. days to 50 % silking, plant and ear heights, ear length, ear diameter, No. of rows per ear, No. of kernel per row and grain yield per feddan indicating the importance of both additive and non-additive gene effects in the inheritance of the traits studied. The ratio of general to specific combining ability mean squares (δ 2 GCA/ δ 2 SCA) exceeded unity for all traits studied, indicating that the additive gene action was more important than non-additive gene action in the inheritance of traits studied. The parental inbred lines P 1 , P 2 , and P 6 had significant positive GCA effects for grain yield. For other traits the best general combiner were P 6 for earliness, and P 3 and P 4 for both shorter plants and lower ear placement. The best cross combinations for earliness were P 1 X P 4 and P 4 X P 6 . Concerning plant and ear heights, the cross P 3 X P 5 had the shortest plants with the lowest ear placement . The cross P 4 X P 6 had the best SCA effects for grain yield. The crosses P 1 xP 2, P 2 xP 6 and P 5 xP 6 significantly outyielded the check hybrid SC 168. These promising crosses may be released as commercial hybrids by maize research program after further evaluation.
Effects of Machining Parameters and Tool Reconditioning on Cutting Force, Tool Wear, Surface Roughness and Burr Formation in Nickel-Based Alloy Milling

Nickel-based superalloys are among the most difficult materials to machine because they have high thermal strength, they are prone to hardening, carbides severely abrade the tool, and they have very poor thermal conductivity. Slot milling is a specific issue as it is characterized by rapid tool wear and frequent tool breakages. This is why reconditioned tools are frequently employed in industrial environments, as they can considerably decrease the expenses associated with tools. The chosen machining strategy also plays a crucial role in the tool’s lifespan and the quality of the machined surface, making it essential to select the appropriate strategy. Hence, the authors have opted for two conventional trochoidal strategies, namely the circular and swinging toolpath, along with a contemporary toolpath known as the Autodesk Inventor HSM Adaptive strategy. The authors investigated the effects of technological parameters and toolpaths on cutting forces, tool wear, surface roughness and burr formation on machined edges. The results show that lower cutting parameters and adaptive strategies lead to the smallest tool loads, tool wear, the best quality of surface roughness and burr formation on machined edges.
Boundary Conditions for Human Gaze Estimation on A Social Robot using State-of-the-Art Models

Appearance-based methods are a promising solution for gaze estimation, as they eliminate the need for additional devices and calibration. This makes them particularly well-suited for human-robot interaction (HRI) research. However, until recently their performance was under par compared to traditional eye-trackers. Recent breakthroughs have been made with the release of two large-scale datasets with a wide range of gaze directions (Gaze360 and ETH-XGaze) and the accompanying state-of-the-art deep neural networks (L2CS and ETH). In this paper, we systematically evaluate the performance of these two appearance-based models on a social robot. In our setup, we vary the distance from the robot (1-3m) and camera resolution (640*480 and 3840*2160) and analyze the performance in terms of accuracy and precision. We find that the L2CS model trained on the Gaze360 dataset combined with a 4K camera achieves the best performance on the 2 m and 3 m distances. We show that a simple offset correction on pitch and yaw can further increase the accuracy and precision by 18.6% and 9.6% respectively. We conclude that for a range up to 3 m appearance-based gaze estimation models provide a promising approach for application in HRI research.
Governing the emissive properties of 4-aminobiphenyl-2-pyrimidine push–pull systems via the restricted torsion of N,N-disubstituted amino groups

Donor–acceptor-substituted biphenyl derivatives are particularly interesting model compounds, which exhibit intramolecular charge transfer because of the extent of charge transfer between both substituents. The connection of a 4-[1,1′-biphenyl]-4-yl-2-pyrimidinyl) moiety to differently disubstituted amino groups at the biphenyl terminal can offer push–pull compounds with distinctive photophysical properties. Herein, we report a comprehensive study of the influence of the torsion angle of the disubstituted amino group on the emissive properties of two pull–push systems: 4-[4-(4-N,N-dimethylaminophenyl)phenyl]-2,6-diphenylpyrimidine (D1) and 4-[4-(4-N,N-diphenylaminophenyl)phenyl]-2,6-diphenylpyrimidine (D2). The torsion angle of the disubstituted amino group, either N,N-dimethyl-amine or N,N-diphenyl-amine, at the biphenyl end governs their emissive properties. A drastic fluorescence quenching occurs in D1 as the solvent polarity increases, whereas D2 maintains its emission independently of the solvent polarity. Theoretical calculations on D1 support the presence of a twisted geometry for the lowest energy, charge-transfer excited state (S1,90), which corresponds to the minimum energy structure in polar solvents and presents a small energy barrier to move from the excited to the ground state, thereby favoring the non-radiative pathway and reducing the fluorescence efficiency. In contrast, this twisted structure is absent in D2 due to the steric hindrance of the phenyl groups attached to the amine group, making the non-radiative decay less favorable. Our findings provide insights into the crucial role of the substituent in the donor moiety of donor–acceptor systems on both the singlet excited state and the intramolecular charge-transfer process.
Performance Evaluation of DualSPHysics and COMCOT Programs through Numerical Testing for Simulating Tsunami Propagation and Overtopping on Seawalls

A tsunami is a destructive wave that can cause massive damage to coastal infrastructure. One of the disaster mitigation measures that can be chosen is the construction of coastal protection infrastructure, such as a seawall. Seawalls play a crucial role in protecting coastal areas as they can reduce wave energy and minimize the impact of tsunami-induced damage. However, during the 2011 Japan tsunami, the seawall built in Taro city failed as it proved to be less effective in handling the tsunami waves. The research conducted aims to model the propagation and overtopping of tsunami waves on the seawall, initially carried out through physical laboratory experiments, and later transformed into numerical test models using the Smoothed Particle Hydrodynamics (SPH) method and the Cornell Multigrid Coupled Tsunami (COMCOT) model. In this study, the parameters being compared include wave height, wave propagation, and overtopping on the seawall under two scenarios : the run-up of solitary waves on a shore without a seawall and the overtopping condition with a seawall using the Solitary Wave generation type, following the experiments conducted by Huang et al en 2022. Several parameters in the laboratory case study should be considered to expand our understanding of the systematically discussed tsunami propagation and overtopping processes and evaluate the capabilities of the SPH and COMCOT models.