Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-Performance-Security Trade-off in Mobile Edge Computing

Multi-access Edge Computing (MEC) also known as Mobile Edge Computing is a type of edge computing that extends the capabilities of cloud computing by bringing resources to the edge of the network. Traditional cloud computing occurs on remote servers far away from users and IoT devices, whereas MEC allows computing processes to take place at base stations, central offices or other aggregation points within the transport network. However, localization of MEC nodes near the data-generating devices gives rise to several challenges such as launch of several attacks from data-generating or network edge devices on the nodes. In this paper, we simulate Distributed Denial of Service (DDoS) and Routing-based attacks to determine their impact on energy and performance. In addition, we propose a novel approach for mitigating the DDoS attack in MEC nodes. Our approach accurately discriminates between high-rate and low-rate DDoS attacks and provides defence against both of them. Our method has a 90% success rate in successfully detecting and thwarting DDoS attack on MEC nodes.
Treat‐to‐target and sequencing therapies in Crohn's disease

Abstract Crohn's disease (CD) is a chronic immune‐mediated inflammatory condition which can negatively impact a patient's quality of life. The traditional management strategy for CD has focused on symptomatic control, however, this approach fails to prevent organ damage and to change the progressive course of this disease. Thus, the field has moved towards a treat‐to‐target strategy that includes identifying individualized objective targets, choosing a therapy based on individual factors that include disease severity and risk, closely monitoring disease activity at predefined time points, and optimizing therapies as needed. Due to the increasing number of therapies approved for CD, this review explores the various factors which should be considered in the sequencing of treatment options together with using the treat‐to‐target framework to control disease activity early in its course and provide holistic patient care.
Hail recognition through the combined use of radar reflectivity and cloud-top temperatures

Abstract A technique is described whereby the radar reflectivity can he combined with cloud-top temperature, from either satellite imagery and/or sounding analysis, to provide a reliable discrimination between heavy rain and/or hail in convective clouds. Hail sizing is also possible. During an all-season operational evaluation throughout New Zealand, the discrimination scheme yielded a probability of detection of 91% with a false-alarm ratio of only 12%.
Feature Extraction and Analysis of MR Images of Brain Tumors

Brain tumors or brain neoplasms can occur in individuals of any age group; however, its frequency of occurrence is more common in adults than in children. Early diagnosis plays a crucial role in determining the best course of treatment. Advancements in the field of radiological imaging for diagnostic purposes has gained importance over the years due to its non-invasive nature. MRI images can be used to extract and analyze quantifiable features with potential clinical significance. These features can be categorized into three categories: Shape, Texture and Intensity. Centre of tumor, location of tumor within the brain, mean and median intensity values and standard variance are quantifiable measures of these features. Advances in computational methods for analysis and prediction of these features could potentially serve as faster tools for diagnosis of tumors and to provide personalized therapy.
Design of a Felid-like Humanoid Foot for Stability Enhancement

The foot is an important part of humanoid robot locomotion that can help with shock absorption while making contact with the ground. The mechanism of the foot directly affects walking stability. A novel foot mechanism inspired by the toes of felids is proposed. The foot has four bionic modules with soft pads and sharp claws installed at the four corners of a flat foot. This foot can reduce the impact experienced during foot landing and increase the time that the foot is in contact with the ground, which can improve the adaptability of the robot to different ground surface conditions with different levels of stiffness. The main structure of the bionic module is a four-bar linkage consisting of a slide way and a spring. Furthermore, the length of the four-bar linkage and the posture of the claw during insertion into soft ground are optimized to improve the stability and buffering performance. The validity of the proposed foot mechanism has been proved in simulations.
The process of electron acceleration during collisionless magnetic reconnection

Two-dimensional particle-in-cell simulations are performed to study electron acceleration in collisionless magnetic reconnection. The process of electron acceleration is investigated by tracing typical electron trajectories. When there is no initial guide field, the electrons can be accelerated in both the X-type and O-type regions. In the X-type region, the electrons can be reflected back and enter the acceleration region several times before they leave the diffusion region. In this way, the electrons can be accelerated by the inductive electric field to high energy. In the O-type region, the trapped electrons can be accelerated when they are trapped in the magnetic island. When there is an initial guide field, the electrons can only be accelerated in the X-type region, and no obvious acceleration is observed in the O-type region. In the X-type region, the electrons are not demagnetized and they gyrate with the force of the guide field. Although no electron reflection is observed in this region, the acceleration efficiency can be enhanced through staying longer time in the diffusion region due to their gyration motion.
Who Belongs to the Middle Income Class in Europe? The Role of Gender-Specific Occupational Characteristics in Multi-Level Analyses for 17 European Countries

Abstract For many years scholars and politicians discuss the economic importance of the middle income class. Our article contributes to broaden the present state of research by not only examining the structure of the middle class whilst focusing on individual attributes, but by especially taking the role of gender-specific occupational characteristics and country-specific conditions into account. Based on the EU-SILC data 2020 for 17 countries, we analyze which factors affect the structure of the middle income class on the individual, on the occupational and country level. Our findings show that occupational attributes (e.g. part-time rate) prove to be highly relevant in this realm. Moreover, significant gender differences can be observed: women who work in an occupation which is mainly performed by women bear a higher risk of belonging to the lower income class as compared to men.
Electronic structures of lead iodide based low-dimensional crystals

The electronic structures of three-dimensional and two-dimensional lead-halide-based crystals ${\mathrm{CH}}_{3}{\mathrm{NH}}_{3}{\mathrm{PbI}}_{3}$ and $({\mathrm{C}}_{4}{\mathrm{H}}_{9}{\mathrm{NH}}_{3}{)}_{2}{\mathrm{PbI}}_{4}$ are investigated by photoelectron spectroscopy and band calculations using the linear combination of atomic orbitals within the density-functional theory. For both crystals, the top of the valence band is found to consist mainly of the $\ensuremath{\sigma}$-antibonding states of Pb $6s$ and I $5p$ orbitals, and the bottom of the conduction band to be composed primarily of the $\ensuremath{\sigma}$-antibonding states of Pb $6p$ and I $5s$ orbitals. Photoelectron spectra of the valence-band region indicate that the electronic structures change depending on the dimensionality of the crystals. Based on the calculation results, the differences observed in the spectra are rationalized in terms of narrowing bandwidth as the dimensionality decreases from three to two dimensions. It is shown that the bandwidth narrowing of the two-dimensional crystal is due to zero dispersion in the vertical direction and the Jahn-Teller effect in the layered structure. These effects lead to a wideband gap and high exciton stability in $({\mathrm{C}}_{4}{\mathrm{H}}_{9}{\mathrm{NH}}_{3}{)}_{2}{\mathrm{PbI}}_{4}. $
The enumeration of chemical space

In the field of medicinal chemistry, the chemical space describes the ensemble of all organic molecules to be considered when searching for new drugs (estimated >1060 molecules), as well as the property spaces in which these molecules are placed for the sake of describing them. Molecules can be enumerated computationally by the millions, which was first undertaken in the field of computer‐aided structure elucidation. Scoring the enumerated virtual libraries by virtual screening has recently become an attractive strategy to prioritize compounds for synthesis and testing. Enumeration methods include combinatorial linking of fragments, genetic algorithms based on cycles of enumeration and selection by ligand‐based or target‐based scoring functions, and exhaustive enumeration from first principles. The chemical space of molecules following simple rules of chemical stability and synthetic feasibility has been enumerated up to 13 atoms of C, N, O, Cl, S, forming the GDB‐13 database with 977 million structures. The database has been organized in a 42‐dimensional chemical space using molecular quantum numbers (MQN) as descriptors, which can be visualized by projection in two dimensions by principal component analysis, and searched within seconds using a Web browser available at www.gdb. unibe.ch. © 2012 John Wiley & Sons, Ltd.
The Star Patch on the G8 Dwarf chi Bootis A

Les observations spectroscopiques de cette naine rouge montrent que des variations dans l'asymetrie des raies spectrales et dans les largeurs equivalentes apparaissent periodiquement tous les 6.43 jours. Un modele est presente pour tenter de reproduire ces variations: on montre que la presence d'une enorme tache stellaire baptisee patch stellaire, 200 K plus froide que le reste de la surface stellaire et couvrant 10% environ du disque est compatible avec les donnees observees
Effectiveness and Acceptability of Conversational Agents for Smoking Cessation: A Systematic Review and Meta-analysis

Abstract Introduction Conversational agents (CAs; computer programs that use artificial intelligence to simulate a conversation with users through natural language) have evolved considerably in recent years to support healthcare by providing autonomous, interactive, and accessible services, making them potentially useful for supporting smoking cessation. We performed a systematic review and meta-analysis to provide an overarching evaluation of their effectiveness and acceptability to inform future development and adoption. Aims and Methods PsycInfo, Web of Science, ACM Digital Library, IEEE Xplore, Medline, EMBASE, Communication and Mass Media Complete, and CINAHL Complete were searched for studies examining the use of CAs for smoking cessation. Data from eligible studies were extracted and used for random-effects meta-analyses. Results The search yielded 1245 publications with 13 studies eligible for systematic review (total N = 8236) and six studies for random-effects meta-analyses. All studies reported positive effects on cessation-related outcomes. A meta-analysis with randomized controlled trials reporting on abstinence yielded a sample-weighted odds ratio of 1.66 (95% CI = 1.33% to 2.07%, p < .001), favoring CAs over comparison groups. A narrative synthesis of all included studies showed overall high acceptability, while some barriers were identified from user feedback. Overall, included studies were diverse in design with mixed quality, and evidence of publication bias was identified. A lack of theoretical foundations was noted, as well as a clear need for relational communication in future designs. Conclusions The effectiveness and acceptability of CAs for smoking cessation are promising. However, standardization of reporting and designing of the agents is warranted for a more comprehensive evaluation. Implications This is the first systematic review to provide insight into the use of CAs to support smoking cessation. Our findings demonstrated initial promise in the effectiveness and user acceptability of these agents. We also identified a lack of theoretical and methodological limitations to improve future study design and intervention delivery.
Assessment of Exercise Intensity for Uphill Walking in Healthy Adults Performed Indoors and Outdoors

Background: Borg’s rating of perceived exertion (BRPE) scale is a simple, but subjective tool to grade physical strain during exercise. As a result, it is widely used for the prescription of exercise intensity, especially for cardiovascular disease prevention. The purpose of this study was to assess and compare relationships between BRPE and physiological measures of exercise intensity during uphill walking indoors and outdoors. Methods: 134 healthy participants [median age: 56 years (IQR 52–63)] completed a maximal graded walking test indoors on a treadmill using the modified Bruce protocol, and a submaximal 1 km outdoor uphill cardio-trekking test (1 km CTT). Heart rate (HR) and oxygen consumption (V̇O2) were continuously measured throughout both tests. BRPE was simultaneously assessed at the end of each increment on the treadmill, while the maximal BRPE value was noted at the end of the 1 km CTT. Results: On the treadmill, BRPE correlated very high with relative HR (%HRmax) (ρ = 0.88, p < 0.001) and V̇O2 (%V̇O2max) (ρ = 0.89, p < 0.001). During the 1 km CTT, a small correlation between BRPE and %HRmax (ρ = 0.24, p < 0.05), respectively %V̇O2max was found (ρ = 0.24, p < 0.05). Conclusions: Criterion validity of BRPE during uphill walking depends on the environment and is higher during a treadmill test compared to a natural environment. Adding sensor-based, objective exercise-intensity parameters such as HR holds promise to improve intensity prescription and health safety during uphill walking in a natural environment.
Differentiation of nonnegative measurable function Choquet integral over real fuzzy measure space and its application to financial option trading model

Fuzzy measure shift differentiation of the Choquet integral for a nonnegative measurable function taken with respect to a fuzzy measure over a real fuzzy measure space is proposed. It is applied to financial engineering. First, a real interval limited Choquet integral for a nonnegative measurable function taken with respect to a fuzzy measure over a real fuzzy measure space is given, then a fuzzy measure left shift differential coefficient, a fuzzy measure right shift differential coefficient, a fuzzy measure shift differential coefficient, and a fuzzy measure shift derived function of the real interval limited Choquet integral for a nonnegative measurable function over a real fuzzy measure space along the domain are defined by the limitation process of a fuzzy measure shift. Two examples of a fuzzy measure shift differentiation are given, where fuzzy measure distributions are either a continuous distribution or a discrete distribution, to understand the notion of the fuzzy measure shift differentiation. Moreover, they are applied to financial option trading. The pricing models of a European call option premium and a European put option premium are defined using the real interval limited Choquet integral for a nonnegative measurable function over a real fuzzy measure space. Then, the distribution of underlying securities of an option trading at the expiration date is given as a /spl lambda/-fuzzy measure, where the total fuzzy measure is equal to one. An important risk index, the delta, which is the rate of change of the premium with respect to underlying security price is defined using the fuzzy measure shift differentiation of the real interval limited Choquet integral for a nonnegative measurable function over a real fuzzy measure space. Finally, these option trading models based on the real interval limited Choquet integral over a real fuzzy measure space is tested with the real market data and is compared with the popular option trading model based on the probability measure and logarithmic normal distribution defined by Black and Sholes (1973).
R Shiny App for the Automated Deconvolution of NMR Spectra to Quantify the Solid-State Forms of Pharmaceutical Mixtures

Bioavailability and chemical stability are important characteristics of drug products that are strongly affected by the solid-state structure of the active pharmaceutical ingredient (API). In pharmaceutical development and quality control activities, solid-state NMR (ssNMR) has proved to be an excellent tool for the detection and accurate quantification of undesired solid-state forms. To obtain correct quantitative outcomes, the resulting spectrum of an analytical sample should be deconvoluted into the individual spectra of the pure components. However, the ssNMR deconvolution is particularly challenging due to the following: the relatively large line widths that may lead to severe peak overlap, multiple spinning sidebands as a result of applying Magic Angle Spinning (MAS), and highly irregular peak shapes commonly observed in mixture spectra. To address these challenges, we created a tailored and automated deconvolution approach of ssNMR mixture spectra that involves a linear combination modelling (LCM) of previously acquired reference spectra of pure solid-state components. For optimal model performance, the template and mixture spectra should be acquired under the same conditions and experimental settings. In addition to the parameters controlling the contributions of the components in the mixture, the proposed model includes terms for spectral processing such as phase correction and horizontal shifting that are all jointly estimated via a non-linear, constrained optimisation algorithm. Finally, our novel procedure has been implemented in a fully functional and user-friendly R Shiny webtool (hence no local R installation required) that offers interactive data visualisations, manual adjustments to the automated deconvolution results, and the traceability and reproducibility of analyses.
Compression of the dc drain current by electron trapping in AlGaN/GaN modulation doped field-effect transistors

The frequently observed dc drain current compression of AlGaN/GaN modulation doped field-effect transistors is associated with partial loss of the two-dimensional electron gas caused by electron trapping. The behavior of the temperature-dependent electron concentration and persistent photoconductivity at low temperature in the AlGaN/GaN modulation doped heterostructure are indicative of the presence of DX centers in the AlGaN layer. Deep-level transient spectroscopy of the drain current reveals carrier trapping with activation energy of 0.28 eV. However, this value appears to be too small to explain the compression of the dc drain current or to attribute these traps to DX centers in AlGaN.
DESIGNING THE SUSTAINABILITY REPORTING MODEL FOR VILLAGE-OWNED ENTERPRISE BASED ON TRI HITA KARANA : A CONCEPTUAL APPROACH

This conceptual article aims to provide a new perspective on the possibility of implementing the concept ofsustainability in small business organizations. This conceptual article focuses on developing a sustainabilityreporting model for village-owned enterprise (VOE). The novelty shown in this conceptual article is the use oflocal Balinese wisdom, namely the Tri Hita Karana concept in helping to develop a sustainability reportingmodel for village-owned enterprise. The method of writing this conceptual article uses library research byfocusing on relevant documents and literatures. The results and discussions have been compiled to produce asustainability reporting model for village-owned enterprise. Future research can continue this conceptual articleby trying to implement the sustainability reporting model in village-owned enterprise.
The clinical relationship between histamine-1 receptor antagonists and risk of cancer: a systematic review and meta-analysis

ABSTRACT Background A systematic research was performed to review the relationship between use of histamine-1 receptor antagonists and cancer risk. Method Databases were searched up to December 2021. Case-control and cohort studies evaluating the relationship between use of histamine-1 receptor antagonists and risk of cancer were selected. The major outcome was cancer risk. Odds ratio (OR) with 95% confidence intervals (CIs) was calculated. Subgroup, cumulative, and sensitivity analysis and Egger test were performed. Results Five case-controls and one cohort study were included. According to cohort study, use of antihistamines were not associated with cancer risk (RR = 0.92, 95% CI = (0.78–1.07). In case-controls, the frequency of antihistamine use in cases and controls was 11.28% and 14.82% respectively which was associated with decreased cancer risk (p value = 0.02, OR = 0.93, 95%CI = (0.87, 0.99)). Sensitivity analysis showed a change in direction of pooled OR by omitting some studies. Sub-group analysis according to type of cancer showed a decrease in cancer risk in antihistamine users in glioma (p value = 0.03). Conclusion Antihistamines might reduce the risk of certain cancers. More studies with defined background of allergy are needed which can clarify the relevancy of different types of cancer with anti-H1 receptors.
Numerical modeling of the magnetization of a permanent magnet and its effect on the electromechanical performance of a brushless direct current motor

This article investigates the electromechanical performance of a brushless dc (BLDC) motor due to the magnetization patterns of a permanent magnet, i.e., rectangular, trapezoidal, and sinusoidal magnetization. A driving circuit equation considering the switching action of the pulse width modulation inverter is coupled with Maxwell’s equation to obtain the nonlinear time-stepping finite element equation for the magnetic field analysis. Newton–Euler’s equations are used to determine the mechanical motion of a rotor due to electromechanical excitation. The results show that rectangular magnetization results in the low phase current for a specified torque. However, sinusoidal magnetization produces the smallest magnetic force and may result in the sound mechanical operation of a BLDC motor.
A Fruit Detection Method for Vague Environment High-Density Fruit Orchards

In Horticulture, an automatic fruit plucking systems may significantly cut labor expenses while improving picking efficiency. Currently, an autonomous fruit plucking system depends heavily on vision intelligence to identify fruit from the background. Most known approaches are being tested under steady environmental conditions, where the light illumination is relatively perpetual, and the fruits are unimpeded. However, the large-scale implementation of autonomous fruit picking systems is hampered because of the increased ramification of the surrounding environment, including fluctuations in illumination and pervasive occlusion. We propose a fruit recognition technique based on finetuned YOLOv5s to address fruit plucking challenges. The proposed technique detects Custard Apple, Pomegranate, and Waxberry fruits. First, fruit images from a real-world setting were gathered and preprocessed to create a dataset. The model is then trained on the dataset to precisely recognize the fruits. The experimental findings demonstrate that Precision, Recall, mAP 0.5, and mAP 0.5:0.95 were 90.4%, 86.4%, 89.4%, and 68.5%, respectively, outperforming the existing approaches and having significant implications for autonomous fruit picking systems in orchards.