Miracle-dz/UniFAR-FTUs huggingface dataset:
Formulating Ternary Inclusion Complex of Sorafenib Tosylate Using β-Cyclodextrin and Hydrophilic Polymers: Physicochemical Characterization and In Vitro Assessment

Sorafenib tosylate (SFNT) is the first-line drug for hepatocellular carcinoma. It exhibits poor solubility leading to low oral bioavailability subsequently requiring intake of large quantities of drug to exhibit desired efficacy. The present investigation was aimed at enhancing the solubility and dissolution rate of SFNT using complexation method. The binary inclusion complex was prepared with β-cyclodextrin (β-CD). The molecular docking studies confirmed the hosting of SFNT into hydrophobic cavity of β-CD, while the phase solubility studies revealed the stoichiometry of complexation with a stability constant of 735.8 M−1. The ternary complex was prepared by combining the SFNT-β-CD complex with PEG-6000 and HPMC polymers. The results from ATR-IR studies revealed no interaction between drug and excipients. The decreased intensities in ATR-IR peaks and changes in chemical shifts from NMR of SFNT in complexes indicate the possibility of SFNT hosting into the hydrophobic cavity of β-CD. The disappearance of SFNT peak in DSC and XRD studies revealed the amorphization upon complexation. The ternary complexes exhibited improved in vitro solubility (17.54 µg/mL) compared to pure SFNT (0.19 µg/mL) and binary inclusion complex (1.52 µg/mL). The dissolution profile of ternary inclusion complex in 0.1 N HCl was significantly higher compared to binary inclusion complex and pure drug. In cytotoxicity studies, the ternary inclusion complex has shown remarkable effect than the binary inclusion complex and pure drug on HepG2 cell lines.
Drivers of coffee liking: Effect of physicochemical characteristics and aromatic profile on consumers’ acceptability of mono‐origin and mono‐variety coffees

Abstract Few studies have investigated at the same time how physicochemical, volatile, and sensory characteristics affect coffee liking. The aim of this study is to evaluate the influence of geographical origin and variety on physicochemical parameters and volatile compounds composition of mono‐origin and mono‐variety coffees. Check‐all‐that‐apply (CATA) method was used with the aim of identifying the drivers of coffee liking. Moisture content, bulk density, solubility index, color parameters, and phenols and caffeine content were useful parameters for discriminating Robusta from Arabica variety, but not samples from different origins. The hierarchical cluster and principal component analyses performed on the headspace compositions showed a quite sharp ability to group the samples based on their variety. Based on CATA results, roasted attribute, related to the presence of pyrazines, was considered a positive driver of coffee liking unlike grassy and acidic attributes (associated to the presence of acids and aldehydes, respectively). Findings from this study can be a useful tool for coffee manufacturers for a winning market strategy, helping them in the choice of the most suitable raw materials and process conditions in order to produce a well‐balanced beverage by enhancing all the possible positive drivers of acceptability and reducing the negative ones.
Longitudinal study of the immune response and memory following natural bovine respiratory syncytial virus infections in cattle of different age

Human and bovine respiratory syncytial virus (HRSV and BRSV) are closely genetically related and cause respiratory disease in their respective host. Whereas HRSV vaccines are still under development, a multitude of BRSV vaccines are used to reduce clinical signs. To enable the design of vaccination protocols to entirely stop virus circulation, we aimed to investigate the duration, character and efficacy of the immune responses induced by natural infections. The systemic humoral immunity was monitored every two months during two years in 33 dairy cattle in different age cohorts following a natural BRSV outbreak, and again in selected individuals before and after a second outbreak, four years later. Local humoral and systemic cellular responses were also monitored, although less extensively. Based on clinical observations and economic losses linked to decreased milk production, the outbreaks were classified as moderate. Following the first outbreak, most but not all animals developed neutralising antibody responses, BRSV-specific IgG1, IgG2 and HRSV F- and HRSV N-reactive responses that lasted at least two years, and in some cases at least four years. In contrast, no systemic T cell responses were detected and only weak IgA responses were detected in some animals. Seronegative sentinels remained negative, inferring that no new infections occurred between the outbreaks. During the second outbreak, reinfections with clinical signs and virus shedding occurred, but the signs were milder, and the virus shedding was significantly lower than in naïve animals. Whereas the primary infection induced similar antibody titres against the prefusion and the post fusion form of the BRSV F protein, memory responses were significantly stronger against prefusion F. In conclusion, even if natural infections induce a long-lasting immunity, it would probably be necessary to boost memory responses between outbreaks, to stop the circulation of the virus and limit the potential role of previously infected adult cattle in the chain of BRSV transmission.
Ankle Joint Torque Prediction Using an NMS Solver Informed-ANN Model and Transfer Learning

In this work, we predicted ankle joint torque by combining a neuromusculoskeletal (NMS) solver-informed artificial neural network (hybrid-ANN) model with transfer learning based on joint angle and muscle electromyography signals. The hybrid-ANN is an ANN augmented with two kinds of features: 1) experimental measurements – muscle signals and joint angles, and 2) informative physical features extracted from the underlying NMS solver, such as individual muscle force and joint torque. The hybrid-ANN model accuracy in torque prediction was studied in both intra- and inter-subject tests, and compared to the baseline models (NMS and standard-ANN). For each prediction model, seven different cases were studied using data from gait at different speeds and from isokinetic ankle dorsi/plantarflexion motion. Additionally, we integrated a transfer learning method in inter-subject models to improve joint torque prediction accuracy by transferring the learned knowledge from previous participants to a new participant, which could be useful when training data is limited. Our results indicated that better accuracy could be obtained by integrating informative NMS features into a standard ANN model, especially in inter-subject cases; overall, the hybrid-ANN model predicted joint torque with higher accuracy than the baseline models, most notably in inter-subject prediction after adopting the transfer learning technique. We demonstrated the potential of combining physics-based NMS and standard-ANN models with a transfer learning technique in different prediction scenarios. This procedure holds great promise in applications such as assistance-as-needed exoskeleton control strategy design by incorporating the physiological joint torque of the users.
Exploring the relationships between anthropometric indices of adiposity and physical performance in middle-aged and older Brazilian women: a canonical correlation analysis

OBJECTIVES This study analyzed the influence of anthropometric indices of adiposity on the physical performance of middle-aged and older women. METHODS A cross-sectional study was conducted among 368 women from 50 years to 80 years old. Anthropometric and biochemical characteristics were analyzed, and physical performance was evaluated. The statistical analysis used measures of central tendency and dispersion for descriptive data, Pearson correlations to demonstrate the initial associations between the variables, and canonical correlation (CC) to evaluate the relationship between the set of anthropometric adiposity indices and performance-related variables. RESULTS The participants had a mean age of 58.57±8.21 years, a visceral adiposity index of 7.09±4.23, a body mass index of 29.20±4.94 kg/m2, and a conicity index of 1.33±0.07. The average handgrip strength was 25.06±4.89 kgf, gait speed was 1.07±0.23 m/s, and the mean Short Physical Performance Battery (SPPB) score was 10.83±1.36. The first canonical function presented the highest shared variance, CC, and redundancy index (cumulative percentage of variance, 82.52; Wilks’ lambda, 0.66; CC, 0.532; p<0.001). From the analysis of this canonical function, the conicity index (-0.59) displayed inverse correlations with handgrip strength (0.84) and the SPPB (0.68), as well as a direct correlation with gait speed (-0.43). CONCLUSIONS In middle-aged and older women, there was an inverse relationship between the conicity index and muscle strength and power, while a direct relationship was found between the same index and gait speed.
04 08 16 4 v 1 1 0 A ug 2 00 4 Substructure in the Circumstellar Disk around the Young Star AU Mic ( GJ 803 )

Keck adaptive optics imaging with a physical resolution of 0.4 AU resolves the inner (15–80 AU) disk of AU Mic (GJ 803), the nearest known sca ttered light disk to Earth. The inner disk is asymmetric and possesses a sh arp change in structure at 35 AU. The disk also shows spatially localized e nhancements and deficits at 25–40 AU separations. The overall morphology poi nts to the influence of unseen larger bodies and resembles structures expec ted from recent planet formation. AU Mic is coeval with the archetypical debris disk system β Pic, and the similarities between their two disks point to synchronous disk evolution. Multiple indications of substructure appear to be common in circumstellar disks at an age of≈12 Myr.
Sight and Sound: Counter-mapping the U.S.-Mexico Border Crisis

Jason De León’s Undocumented Migration Project and Valeria Luiselli’s Lost Children Archive are two archival studies of the U.S.-Mexico border crisis that challenge hegemonic practices of documentation, including those historically privileged by the U.S. Department of Homeland Security, human rights activism, and the field of digital humanities alike. Though De León and Luiselli have participated in human rights work while identifying migrant corpses and collecting detainees’ testimonies, both use counter-mapping to interrogate the dominant humanitarian move of restoring visibility and voice, or sight and sound, to human victims. After investigating the ways in which De León and Luiselli privilege visual and sonic counter-mapping, respectively, I model a more multi-sensory counter-mapping practice. Though this practice remains far from perfect, I argue that such digital counter-mapping crosses sight and sound in ways that defy historical divisions among humans and nonhumans. Accordingly, it decenters humans as the sole victims of the U.S.-Mexico border crisis.
I.T. Professionals' Preference for Work From Home Setup: A Conjoint Analysis Approach

Due to constant growth of technology it results to increase efficiency to work remotely, as a result, there is an increase in percentage of I.T. professionals working from home. This study used Conjoint Analysis in order to determine the most preferred work from home setup attributes by I.T. professionals. Using the attributes such as having a dedicated workspace, type of internet connection, type of communication tool, audio tool, accessories for their computer or laptop, type of chair, and frequency of team socials. Using conjoint analysis with orthogonal design, this study was able to evaluate the preference among I.T. professionals. The result of the study showed that the type of Internet Connection is the most important (30.975%). Next is the preference on dedicated workspace (22.633%), the type of accessories (13.059%), Communication tool (10.982%), frequency of team socials (9.152%), type of chairs (6.723%), least is the type of audio tools (6.477%). The result of this study could be used by the employers to improve the work from home conditions of their employees.
Bistable dissipative soliton in cubic-quintic nonlinear medium with multiphoton absorption and gain dispersion

We studied the propagation of optical pulse in a dissipative cubic-quintic nonlinear medium with multiphoton absorption and gain dispersion. Variational method in conjugation with Rayleigh dissipative function is used to analytically solve the governing complex cubic-quintic Ginzburg–Landau equation. Three cases of multiphoton absorption are studied: (i) two-photon absorption (TPA), (ii) three-photon absorption (3PA) and (iii) both TPA and 3PA. For all three cases, the pulse intensity decays and width broadens. The greater the gain dispersion, the wider the pulse. Increasing quintic nonlinearity marginally affects pulse amplitude but significantly reduces pulse broadening. TPA and 3PA, which are functions of positive imaginary parts of, respectively, third- and fifth-order susceptibility, individually cause pulse decay and pulse broadening. Thus, their combination only expedites pulse degradation. Conversely, negative imaginary part of fifth-order susceptibility may lead to an effect that impedes pulse degradation. Matching numerical results are obtained that validates the entire analytical outcome. A suitable gain can arrest both pulse broadening and decay. Such dissipative solitonic pulses, bistable owing to quintic nonlinearity, are found for all cases.
Digital Lab for Basic and Advanced Features of Message Queuing Telemetry Transport (MQTT)

The Message Queuing Telemetry Transport (MQTT) application layer protocol is the de-facto first choice in building Internet of Things (IoT) systems and applications. Being a fundamental component in virtually all IoT projects, a wrong MQTT configuration or usage may lead to critical problems for both system owner and users. Driven by the need for further problem-driven MQTT training involving challenging IoT use cases, we propose Online-MQTT, an online lab course for MQTT. Online-MQTT is designed to be used by a wide range of learners while pinpointing to two crucial research gaps. We build on the unique Open DigiLab4U infrastructure to realize our scalable MQTT online lab. We first elaborate on our educational considerations such as the selection of topics, the target group, our didactic approach and finally technical challenges to accomplish an MQTT experiment with remote access to physical assets. Next, we detail the course content, by illustrating MQTT basic features and drawing the learning path towards demonstrating two current research gaps, i.e., enhancing MQTT with semantics and real-time capabilities. The main achievement is an online MQTT course that is expected to be of high interest for MQTT beginners, experts and researchers.
Outage Statistics of Hybrid Double-RIS System Assisted by Aerial AF-Relay for Multi-hop Communications

This paper considers single-input single-output (SISO) multi-hop wireless communication system (M-WCS) that consists of two dual-hop re-configurable intelligent surface (RIS)-enabled links that are connected by a unmanned aerial vehicle (UAV)-amplify-and-forward relay (AFR) in order to extend coverage. In particular, probability density function (PDF) $p_{R_{2}^{2}}(\gamma_{tr,2})$ and cumulative distribution function (CDF) $F_{R_{2}^{2}}(\gamma_{tr,2})$ of end-to-end SNR for the hybrid double RIS-enabled communications (RIS-ECs) with a UAV-AFR over dissimilar Rayleigh-Nakagami-m fading channels are derived. Capitalizing on the obtained mathematical expressions the system performance analysis in terms of outage probability (OP) $P_{R_{2}^{2}}(\gamma_{tr,2})$ is further performed, graphically presented and analysed for different number of RIS modules and under various severity conditions. Moreover, we provide comparison between double RIS-ECs link with UAV-AFR and RIS-ECs link without UAVAFR in terms of outage statistics. It is further analysed that the RIS-ECs with UAV-AFR can not only extend the coverage but also can be deployed with sufficiently large number of RIS elements to improve the system performances.
Microwave Characterization of NinjaFlex Filament Using Performance Probe for Developing 3D-Printed Wearable Antennas

This paper presents the microwave characterization of NinjaFlex 3D-printing filament using Keysight 85070E Perfor-mance Probe. The electromagnetic properties (dielectric constant and dielectric loss factor) of the NinjaFlex are measured from 200 MHz to 20 GHz, and its loss tangents values $(\tan\delta)$ are calculated accordingly. The results are compared with previously reported techniques based on ring resonator and Keysight N1501A High Temperature Dielectric Probe. To investigate the application of NinjaFlex filament for antenna manufacturing, a triangular edge-fed patch antenna is designed and simulated based on the measured electromagnetic properties. To examine the antenna's potential for wearable applications, numerical and experimental tests are conducted on its performance under structural de-formation such as bending and in proximity of human body. The reflection coefficient of the fabricated antenna are measured in flat and bent conditions and the results are presented and compared with the simulation.
DICON: A Domain-Independent Consent Management for Personal Data Protection

The development of technology accelerated the digital transformation of information systems. As a consequence of this digitization, data became available at any time and in any place. However, despite this ease of data accessibility, persons’ privacy concerns and threats to data privacy have emerged. Thus, serious privacy problems arise while collecting, storing, accessing, sharing, and archiving personal data. Consent management aims to prevent these problems by preserving privacy and protecting personal data. Hence, there are international treaties and legal regulations for personal data protection which state that consent is required to collect, store, manage and share personal data. In this study, a Semantic Web-based personal consent management model is proposed to protect personal data privacy. The proposed model is domain-independent and aims to control and manage the consent of a person. In order to provide the privacy protection of personal data, the proposed model allows individuals to establish their privacy preferences by determining who can access their personal information, for what purposes, and under what circumstances. For this purpose, a group of ontology is created to ensure the informed consent process. The proposed consent management model is generic. As similar to general personal information, personal health information is also sensitive and must be protected from data leakage. Therefore, the proposed generic model is implemented with Semantic Web technologies and demonstrated for the healthcare domain.
Deep Neural Network for Localization of Mobile Users using Raytracing

As the world evolves towards faster data transmission, there is an ever-increasing demand for better user localization which will find application in transport, medicine, and robotics. In this study, we present an accurate localization algorithm for mobile users using deep neural network with Bayesian optimization and a communication channel operating at 3.75GHz frequency. We design a deep neural network model which facilitates and speeds up the localization process. The deep neural network (DNN) is utilized in this study to locate moving user equipment (UEs) with randomly assigned velocities. Using preliminary computer simulations, we present a method for training a neural network that extracts channel parameters (features) that are used to estimate location. Our method produces localization accuracy for line of sight (LOS) users, less than 1 m error, and the accuracy can further be improved by implementing higher rate of data sets.
Parameter Extraction Methodology of 1D2R PV Cell Electrical Model for Indoor Applications

Electrical models are used to compare the properties of PV cells and solar panels and to predict the characteristics of their I-V curves. Even though there is much research on the evaluation of these models for outdoor conditions, their indoor performance is still not fully investigated, despite the increasing interest for IoT applications. This work describes a method for extracting the parameters of a $20\times 40$ mm PV cell for the 1D2R electrical model at indoor conditions. An analytical procedure is presented, in which the 5 model parameters are calculated from 6 PV cell characteristic points. Translation equations are estimated for the characteristic points in function of illuminance level, reducing the amount of measurements. Results demonstrated good accuracy of the electrical model concerning measurement data for both procedures, with R2 greater than 0.97. This modeling is fundamental for emulating the electrical behavior of PV cells under indoor conditions and can be used as input for characterization of energy harvesting circuits.
5G Business Models for Mobile Network Operators—A Survey

Emerging Fifth-generation (5G) mobile networks and associated technologies are expected to provide multi-service wireless applications with diverse specifications intended to address not only consumer-based smartphone applications, but also the needs of various vertical industry markets (e.g., healthcare, education, energy, mining, agriculture, manufacturing, and so forth). This paper extends 5G networks’ technology orientation towards attaining economic value for all key 5G stakeholders, including customers, mobile network operators (MNOs), equipment vendors, public institutions, private enterprises, digital business start-ups and other third parties. Although several surveys and tutorials have discussed business models in connection with 5G networks, there is no comprehensive study on business models for emerging 5G networks from the MNO’s perspective. In this survey article, we present and investigate key advances on business models for 5G networks and 5G MNOs in particular, from industry, use cases and research community perspectives. The paper focuses the theoretical business model concept from both strategic management and technological innovation perspectives. Thereafter, we discuss conventional business models for MNOs before presenting particular disruptive business models which can be considered for rolling out 5G networks with an aim to improve business efficiency. Additionally, the paper explores the emerging network deployment concept of private 5G networks and their related business models. Finally, we present some of the open research challenges and provide possible guidelines for implementing 5G business models based on various countries’ socio-economic status and relevant 5G use cases applicable in a specific context of emerging economies.
Systematic Literature Review on Process Mining in Learning Management System

In the era of Industry 4.0, information systems record a huge amount of event logs. Process Mining (PM) techniques can evaluate a Learning Management System (LMS) usage based on actual learner’s activity as recorded in the event logs. Similar systematic review research has highlighted the use of PM in LMS datasets and essential issues for future research. Our research is motivated by the fact that no literature reviews consider the process mining application in the learning process design. This paper aims to present the use of PM in LMS related to the deviation between learning design and actual execution. This literature study selects 20 out of 52 published articles from 2017 until 2021 based on the criteria and quality assessment. These articles were analyzed based on the research objectives, PM technique, and the tools used. The results show that student behavior is heavily related to the deviation between learning design and actual execution. Three perspectives are found in approaching student behavior: comparison of student behavior, performance prediction based on student behavior, and learning strategy evaluation. This structured literature review may help LMS learning designers improve learning design to suit student behavior.