Miracle-dz/UniFAR-FTUs huggingface dataset:
Profile of the Users and the Most Visited Topics of a Pediatric eHealth Website

Parents need information about their children’s health, and the Internet has become an essential repository for this information. However, there is almost no information about which topics are the most searched, consulted, or shared, or about the main characteristics of pediatric website users. The main aim of this research was to describe the profile of the users of a pediatric website, which topics they searched for, which topics were the most consulted, and which were the most shared. Users’ demographic data were analyzed regarding their use of the Internet to search for information about health. A pediatric website for parents was analyzed. A 26-item questionnaire collected demographical features of the users of the website. Descriptive and analytical analyses were performed. Most participants used general search engines for their health searches, and the most searched keywords were prurigo, barking cough, and laryngitis. The most visited topics were unexplained fever, snots, and laryngitis. The most shared were snots, lipotomy, and dizziness. The users were mainly women (67.8%), with an average age of 38.8 years, and one or two children (89%) with a mean age of 4.6 years. The users who mainly used the Internet for health purposes were women of younger age, and with a higher educational level.
Multiscale Variational Autoencoder Aided Convolutional Neural Network for Pose Estimation of Tunneling Machine Using a Single Monocular Image

With the rising demand of underground construction, intelligent tunneling techniques have been increasingly studied to improve the safety and efficiency of construction. The self-positioning technology of tunneling machines is the cornerstone of intelligent tunneling, which is particularly challenging due to the extreme environments of the underground tunnels. In this article, a novel robust and real-time six degrees of freedom (6-DoF) pose estimation strategy is proposed for tunneling machines based on the computer vision and deep learning methods. A monocular camera is attached to the tunneling machine, and employed to capture the images of the artificial feature object that is set far behind the tunneling machine. A novel multiscale variational autoencoder aided convolutional neural network (MSVAE-CNN) model is developed to estimate the current absolute 6-DoF pose of the tunneling machine in an end-to-end manner using a single monocular image, in which the multitask variational learning scheme is able to enhance the generalization and robustness of the model and the multiscale structure can improve the learning ability of the neural network. In our numerical experiments, a motion capture system is utilized to assist the acquisition of training dataset. The experimental results demonstrate the efficacy of the proposed MSVAE-CNN based pose estimation method.
Skeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction

Recent breakthroughs with numerous visual experiences using mobile devices encourage the research of human-computer interaction (HCI) involving hand gesture recognition for Holograms, Virtual Reality, and Augmented Reality. The rise of these technologies allows educators in medical segments to apply new pedagogy by interacting with virtual content in a coherent learning environment. This paper proposed the Central Nervous System (CNS) interaction using the Skeleton Joints Moment (SJM) approach for dimension reduction with k Nearest Neighbour (k-NN) for hand gesture classification. Over the past few decades, researchers have proposed various techniques in dimension reduction. One of the methods is principal component analysis (PCA). Experimental results indicated that the SJM technique has similar accuracy to PCA, where both methods showed 96% of prediction using hand skeleton joints data. In addition, PCA has a higher uncertainty of mean error 0.75 compared to SJM at only 0.01. Furthermore, PCA has the worst complexity of <inline-formula> <tex-math notation="LaTeX">$O(min(p^{3},n^{3}))$ </tex-math></inline-formula> where SJM <inline-formula> <tex-math notation="LaTeX">$O(n/d)$ </tex-math></inline-formula>. Evaluation results using the T-Test showed a significant difference between SJM and PCA where <inline-formula> <tex-math notation="LaTeX">$p < 0.05$ </tex-math></inline-formula>. Thus, there is evidence to reject the null hypothesis.
Image Adaptive Contrast Enhancement for Low-illumination Lane Lines Based on Improved Retinex and Guided Filter

ABSTRACT In a low-illumination environment, the contrast between lane lines and the ground is relatively low. Traditional image enhancement algorithms, such as gamma correction, Histogram Equalization, and multiple-scale Retinex, may result in over enhancement and detail loss, which decreases the detection accuracy of driver assistance systems. In this work, we introduce a low-illumination image enhancement algorithm based on improved Retinex theory and apply it to lane-line detection. A luminance channel optimization method based on a bimodal energy function is adopted to select the weight of the linear combination. A guided filter with edge-preservation is applied to obtain the illumination component of the scene. Furthermore, the reflection component is estimated in a hyperbolic tangent space, and the luminance and contrast are adaptively adjusted to obtain the enhanced image. Experimental results show that proposed method can effectively extract the lane-line edges and suppress the noise in the dark area with low lane-line illumination. Moreover, it can improve the detection success rate of an assisted driving system.
Essential Oil and Hydrophilic Antibiotic Co-Encapsulation in Multiple Lipid Nanoparticles: Proof of Concept and In Vitro Activity against Pseudomonas aeruginosa

In the worldwide context of an impending emergence of multidrug-resistant bacteria, this research combined the advantages of multiple lipid nanoparticles (MLNs) and the promising therapeutic use of essential oils (EOs) as a strategy to fight the antibiotic resistance of three Pseudomonas aeruginosa strains with different cefepime (FEP) resistance profiles. MLNs were prepared by ultrasonication using glyceryl trioleate (GTO) and glyceryl tristearate (GTS) as a liquid and a solid lipid, respectively. Rosemary EO (REO) was selected as the model EO. REO/FEP-loaded MLNs were characterized by their small size (~110 nm), important encapsulation efficiency, and high physical stability over time (60 days). An assessment of the antimicrobial activity was performed using antimicrobial susceptibility testing assays against selected P. aeruginosa strains. The assays showed a considerable increase in the antibacterial property of REO-loaded MLNs compared with the effect of crude EO, especially against P. aeruginosa ATCC 9027, in which the minimum inhibitory concentration (MIC) value decreased from 80 to 0.6 mg/mL upon encapsulation. Furthermore, the incorporation of FEP in MLNs stabilized the drug without affecting its antipseudomonal activity. Thus, the ability to co-encapsulate an essential oil and a hydrophilic antibiotic into MLN has been successfully proved, opening new possibilities for the treatment of serious antimicrobial infections.
Analysis of Indoor THz Communication Systems With Finite-Bit DACs and ADCs

Terahertz (THz) communication is foreseen to be a key technology for the 6G wireless communications. In this paper, the performance of downlink Terahertz (THz) communication systems with low-resolution digital-to-analog converters (DACs) at the Access Point (AP) and/or finite-bit analog-to-digital converters (ADCs) at the user sides are investigated. Array-of-subarrays architecture is assumed at the AP, where each RF chain uniquely activates a disjoint subset of antennas, each of which is connected to an exclusive phase shifter. Hybrid precodings including maximum ratio transmission (MRT) and zero-forcing (ZF) precoding are considered. The best beamsteering direction for the phase shifters in the large subarray antenna regime is first proved to be the direction of the line-of-sight (LOS) path. Subsequently, the closed-form expression of the lower-bound of the achievable rate in the large subarray antenna regime is derived, which is the same for both MRT and ZF and is independent of the transmit power. Moreover, numerical results show that the rate loss caused by the phase uncertainties can be negligible in large subarray antenna regime and moderate resolution DACs and ADCs can achieve performance close to the infinite-resolution one. Numerical results validating the analysis are provided as well. Overall, the impact of finite-bit precoding and finite-bit ADCs on the achievable rate of indoor THz communication systems is characterized.
Evolving from Laboratory Toys towards Life-Savers: Small-Scale Magnetic Robotic Systems with Medical Imaging Modalities

Small-scale magnetic robots are remotely actuated and controlled by an externally applied magnetic field. These robots have a characteristic size ranging from several millimetres down to a few nanometres. They are often untethered in order to access constrained and hard-to-reach space buried deep in human body. Thus, they promise to bring revolutionary improvement to minimally invasive diagnostics and therapeutics. However, existing research is still mostly limited to scenarios in over-simplified laboratory environment with unrealistic working conditions. Further advancement of this field demands researchers to consider complex unstructured biological workspace. In order to deliver its promised potentials, next-generation small-scale magnetic robotic systems need to address the constraints and meet the demands of real-world clinical tasks. In particular, integrating medical imaging modalities into the robotic systems is a critical step in their evolution from laboratory toys towards potential life-savers. This review discusses the recent efforts made in this direction to push small-scale magnetic robots towards genuine biomedical applications. This review examines the accomplishment achieved so far and sheds light on the open challenges. It is hoped that this review can offer a perspective on how next-generation robotic systems can not only effectively integrate medical imaging methods, but also take full advantage of the imaging equipments to enable additional functionalities.
Molecular-Genetic Portrait of Breast Cancer with Triple Negative Phenotype

Simple Summary Breast cancer is a genetically heterogeneous disease with different molecular biological and clinical characteristics. The available knowledge about the genetic heterogeneity of the most aggressive molecular subtype of breast cancer—triple-negative—has led to discoveries in drug treatment. Identification of the molecular-genetic phenotype of breast cancer is an important prognostic factor of the disease and allows personalization of the patient’s treatment. Abstract Understanding of the genetic mechanisms and identification of the biological markers of tumor progression that form the individual molecular phenotype of transformed cells can characterize the degree of tumor malignancy, the ability to metastasize, the hormonal sensitivity, and the effectiveness of chemotherapy, etc. Breast cancer (BC) is a genetically heterogeneous disease with different molecular biological and clinical characteristics. The available knowledge about the genetic heterogeneity of the most aggressive molecular subtype of breast cancer—triple-negative (TN)—has led to discoveries in drug treatment, including the use of DNA damaging agents (platinum and PARP inhibitors) for these tumors, as well as the use of immunotherapy. Most importantly, the ability to prescribe optimal drug treatment regimens for patients with TNBC based on knowledge of the molecular-genetic characteristics of this subtype of BC will allow the achievement of high rates of overall and disease-free survival. Thus, identification of the molecular-genetic phenotype of breast cancer is an important prognostic factor of the disease and allows personalization of the patient’s treatment.
An improved secure and efficient group key agreement scheme in VANETs

VANET is a wireless mobile network that can provide communication for vehicles and roadside units. The security and efficiency of its key agreement scheme are critical. After analyzing the security defects of the VANET key agreement scheme of Liu et al., an improved secure and efficient group key agreement scheme in VANETs is proposed in this paper. We construct a group key agreement scheme replacing the bilinear pair with elliptic curve cryptography, which can achieve a higher level of security. A strict security analysis is given to prove that the scheme meets various security requirements of VANETs. Compared with similar schemes, the performance analysis shows that the computation cost and communication cost of the proposed scheme are significantly reduced.
Workers who experience high levels of job pressure tend to encounter more negative personal and social outcomes , including risks to their health and well-being

Analyses of the 2008 National Study of the Changing Workforce demonstrate that job pressure is associated with greater anxiety and job dissatisfaction. In this paper we ask, What conditions protect workers? The conventional buffering hypothesis in the Job-Demands Resource (JD-R) model predicts that job resources should attenuate the relationship. We test whether the conventional buffering hypothesis depends on socioeconomic status (SES). Support for conventional buffering is evident only for job dissatisfaction— and that generalizes across SES. When anxiety is assessed, however, we observe an SES contingency: Job resources attenuate the positive association between job pressure and anxiety among workers with lower SES, but exacerbate it among those with higher SES. We discuss the implications of this SEScontingent pattern for theoretical scenarios about “resource reinforcement,” “resource substitution,” and the “stress of higher status. ” Future research should consider SES indicators as potential contingencies in the relationship between job conditions and mental health.
Patient Experiences

Faculty Discussant: Olihe Okoro, PhDArticle 1: Patient Experiences at Enhanced-Service Pharmacies in IowaChen Huang, Graduate Student; William Doucette, PhD, FAPhA, RPh; Michael Andreski, RPh, PhD; Anthony Pudlo, PharmD, MBAArticle 2: The Perspective of African-born HIV Minnesotans of their Interaction with PharmacistsAlina Cernasev, PharmD, MSc; William L. Larson, PharmD, BCGP, BCACP; Cynthia Peden-McAlpine, PhD, ACNS, BS; Todd Rockwood, PhD, MA, BS; Paul Ranelli, PhD, MS; Olihe Okoro, PhD, MPH, MPharm; Jon C. Schommer, PhDArticle 3: Association between Insurance Characteristics and Patient Activation among Medicare Beneficiaries with Type 2 DiabetesDandan Zheng, MS, PhD Student; Joseph Thomas III, PhD, ProfessorArticle 4: How Do Health Literacy And Risk Perception Impact Older Adult Misuse Of Over-The-Counter Medications? Apoorva Reddy, BS; Jamie Stone, MS; Michelle Chui, PharmD, PhDArticle 5: A Qualitative Approach to Patient Experiences in MigraineDeepika Rao, MS Candidate; Elham Heidari, PharmD, MS Candidate Vincent Giannetti, PhD; Andrea R. Pfalzgraf, PhD, MPH; Carroline Lobo, MS, PhDArticle 6: The Medication Experience of African American Women with Early Stage Chronic KidneyDiseaseLisa Hillman, PharmD, BCACP; Olihe Okoro, PhD, MPH; Djenane Ramalho de Oliveira, PhD; Jon Schommer, PhDArticle 7: Pharmacist-Delivered Patient-Centered Care: Exploring an Untested AssumptionAnthony W. Olson, PharmD; Jon C. Schommer, PhD
Resource Allocation Approach for Optimal Routing in IoT Wireless Mesh Networks

Information networks organized according to Internet of Things (IoT) mesh topology have received great recognition over the past one and a half to two decades of years. The scale of projects grows from millions of users connected to hundreds of thousands of access points. IoT mesh nodes offer more fascinating regulations linking a variety of networks and radio technologies and therefore fully meet the ever-growing requirements of subscribers as mobility, quality of service (QoS) and the security. The possibility of organizing local or metropolitan networks using a mesh network topology, desegregating into wide area networks without any difficulty or effort, is considered a tempting condition for urban and individual users. This article, introduces optimal routing protocol for IoT Wireless Mesh Network (WMN) by optimizing the channel and frequency resources of the network based on mathematical calculations for resource allocation. We propose an approach to the synthesis of mesh networks, which allows determining the required number of connections between network nodes, as well as their channel width for a given frequency range while ensuring the minimum data transmission delay time. Optimization results show that the function value is improved for more than 16% and the proposed algorithm provides the most rational use of the allocated frequency range.
Estimating the dielectric parameters of water and gel using reflectance and transmission at 1.85 to 2.07 THz

The THz/Far-IR Beamline at the Australian Synchrotron was used to demonstrate a novel method of estimating the dielectric properties of water based substances in the 2.0 THz region. The method involves using an ATR apparatus with a diamond crystal in a way that converts the apparatus to a reflection/transmission mode by using a mirror at a set distance from the crystal/sample interface to reflect the transmitted portion of the incoming beam back to the detector. The method can extract the full dielectric properties of a sample. The method is only limited by the frequency range of the source and the sensitivity range of the detector. It is best suited to studies at 2.0 THz and above with a diamond crystal ATR apparatus, since the combination of the refractive index of diamond (n=2.40) and water (n=1.95 at 2.0 THz) are in the optimal ratio to produce excellent contrast. Water and water based gel were used to demonstrate the technique.
Robotic Psychology: A PRISMA Systematic Review on Social-Robot-Based Interventions in Psychological Domains

Current technological advancements have allowed robots to be successfully employed in the healthcare sector. However, the recently acquired ability of social robots to process social information and act according to it has potentially made them very well suited to support or conduct psychological interventions. The present paper carried out a systematic review of the available literature regarding social-robot-based interventions in psychological domains using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The inclusion criteria were: (i) publication date until 2020; (ii) being an empirical study, master thesis, or project report; (iii) written in English or Italian languages (the two languages spoken by the authors); (iv) published in a scholarly peer-reviewed journal or conference proceedings, or were Ph.D. or master’s theses; and (v) assessed “social robot”-based intervention in psychological domains. Overall, the review showed that three main areas may benefit from social-robot-based interventions: social skills, mood, and wellbeing (e.g., stress and anxiety levels). Interestingly, social robots seemed to have a performance comparable to, and sometimes even better than, human operators. The main, but not exclusive, target of robot-based interventions in the psychological field was children with autism spectrum disorder (ASD). As evidence is, however, still limited and in an embryonic state, deeper investigations are needed to assess the full potential of social robots for the purposes of psychological intervention. This is relevant, considering the role that social robots could have in overcoming barriers to access psychological assessment and therapies.
Freezing Tolerance Enhancement and Thermographic Observation of Whole Peach Trees Applied with Cellulose Nanocrystals under Realistic Spring Frost Conditions Using a Soil–Fruit–Daylit–System

Due to recent abnormal weather caused by global warming, peach flowering has gradually accelerated, and spring frost damage caused by premature de-acclimation has increased. In this study, under a simulated spring frost environment using a Soil–Fruit–Daylit–System (SFDS) chamber, we investigated whether treatment with 2% cellulose nanocrystals (CNCs) could enhance the freezing tolerance of the flower buds from 2-year-old whole peach trees. Visual changes in the ice propagation were observed using an infrared camera at the same time. After the peach flower buds in the calyx red stage were placed in the SFDS chamber with a minimum temperature of −4 °C for ~20 h, the percentage of browning in the pistils and stamens was 57.0% in the control group and 14.1% in the group treated with 2% CNCs. During the first pink stage, the percentages of browning in the pistils and stamens in the control group and the group treated with 2% CNCs were 98.2% and 70.3%, respectively. However, when peach flower buds in the group treated with 2% CNCs were exposed to a −6 °C-targeted chamber, they could not mitigate frost injury. Almost all flower buds were damaged. Infrared thermal images showed that the first exotherm in the control group began at 2:33:03 am, whereas that of the group treated with 2% CNCs began at 3:01:33 am. The control started to express exothermic behavior at −4.2 °C, while the group treated with 2% CNCs started expressing exothermic behavior at −5.1 °C. Thus, treatment with 2% CNCs enhanced the freezing tolerance by −0.9 °C and delayed the first instance of exothermic behavior by ~28 min. These results indicate that treatment with 2% CNCs could mitigate the frost damage of peach flower buds in a frost environment of −5 °C.
Cerebellar White Matter Abnormalities in Charcot–Marie–Tooth Disease: A Combined Volumetry and Diffusion Tensor Imaging Analysis

Charcot–Marie–Tooth disease (CMT) is a genetically heterogeneous hereditary peripheral neuropathy. Brain volumetry and diffusion tensor imaging (DTI) were performed in 47 controls and 47 CMT patients with PMP22 duplication (n = 10), MFN2 (n = 15), GJB1 (n = 11), or NEFL mutations (n = 11) to investigate for structural changes in the cerebellum. Volume of cerebellar white matter (WM) was significantly reduced in CMT patients with NEFL mutations. Abnormal DTI findings were observed in the superior, middle, and inferior cerebellar peduncles, predominantly in NEFL mutations and partly in GJB1 mutations. Cerebellar ataxia was more prevalent in the NEFL mutation group (72.7%) than the GJB1 mutation group (9.1%) but was not observed in other genotypic subtypes, which indicates that structural cerebellar abnormalities were associated with the presence of cerebellar ataxia. However, NEFL and GJB1 mutations did not affect cerebellar gray matter (GM), and neither cerebellar GM nor WM abnormalities were observed in the PMP22 duplication or MFN2 mutation groups. We found structural evidence of cerebellar WM abnormalities in CMT patients with NEFL and GJB1 mutations and an association between cerebellar WM involvement and cerebellar ataxia in these genetic subtypes, especially in the NEFL subgroup. Therefore, we suggest that neuroimaging, such as MRI volumetry or DTI, for CMT patients could play an important role in detecting abnormalities of cerebellar WM.
Pleistocene climate oscillations and habitat connectivity contributed to avian beta‐diversity in the megadiverse Colombian Paramo ecosystems

The role of evolutionary history in shaping the patterns of species distributions is generally explored at coarse spatial extents. However, at small spatial extents, the combined effects of history and ecological processes on local diversity has received less attention. We test the relative importance of historical and ecological factors on the spatial distribution of bird taxonomic (TβD) and phylogenetic (PβD) β‐diversity on Paramo ecosystems.