Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent Advances in Electrochemical Biosensors for the Detection of Salmonellosis: Current Prospective and Challenges

Salmonellosis is a major cause of foodborne infections, caused by Salmonella, posing a major health risk. It possesses the ability to infiltrate the food supply chain at any point throughout the manufacturing, distribution, processing or quality control process. Salmonella infection has increased severely and requires effective and efficient methods for early monitoring and detection. Traditional methods, such as real-time polymerase chain reaction and culture plate, consume a lot of time and are labor-intensive. Therefore, new quick detection methods for on-field applications are urgently needed. Biosensors provide consumer-friendly approaches for quick on-field diagnoses. In the last few years, there has been a surge in research into the creation of reliable and advanced electrochemical sensors for the detection of Salmonella strains in food samples. Electrochemical sensors provide extensive accuracy and reproducible results. Herein, we present a comprehensive overview of electrochemical sensors for the detection of Salmonella by focusing on various mechanisms of electrochemical transducer. Further, we explain new-generation biosensors (microfluidics, CRISPR- and IOT-based) for point-of care applications. This review also highlights the limitations of developing biosensors in Salmonella detection and future possibilities.
Role of ion accumulation in lofting of submicrometer-sized dielectric particle from dielectric surface by plasma and low-energy electron beam

A particle-in-cell model is used to investigate the dust levitation phenomenon. A submicrometer-sized silicon dioxide particle lying on a silicon dioxide substrate is exposed to a low-energy electron beam and the flux of ions and electrons from a cold plasma. The combined effect of ion and electron accumulation between the particle and the substrate is reported. The results are of interest for dust mitigation in the semiconductor industry, the lunar exploration, and the explanation of the dust levitation.
Research on ELM-based aircraft engine sensor fault diagnosis method

In order to realize aircraft engine sensor fault monitoring and diagnosis more better on embedded ARM11 platform,using extreme learning machine( ELM) instead of BP network algorithm,only need to select node numbers and activation function of hidden layer,greatly reduce large numbers of parameters,slow training process and continuously adjust network parameters and easy to fall into local optimal solution of BP algorithm.Through simulation comparison of two algorithms,verify the superiority of ELM algorithm. The ELM algorithm is then converted into aircraft engine sensor fault diagnosis training and learning software and diagnosis software using C + + programming language,the final test show that test precision of the algorithm software is good,and meet requirement of diagnosis.
DEVELOPMENT AND OPTIMIZATION OF TAZAROTENE LOADED SOLID LIPID NANOPARTICLES FOR TOPICAL DELIVERY

Objective: Psoriasis is an unswervingly recurring, inflammatory, autoimmune disorder of the skin, disturbing about 2–5% of the world population. The main objective for this investigation is to develop and optimize the solid lipid nanoparticles (SLN) formulation of tazarotene for effective drug delivery. Methods: Tazarotene SLNs were fabricated by hot homogenization followed by the ultrasonication using Taguchi’s orthogonal array with eight parameters that could affect the particle size and entrapment efficiency (EE). In view of the outcomes from the examinations of the responses acquired from Taguchi design, three diverse independent variables including sonication time (s), lipid to drug ratio (w/w), and surfactant concentration (%) were carefully chosen for further investigation utilizing central composite design. The lipid dynasan-116, surfactant poloxamer-188, and cosurfactant egg lecithin resulted in better percent drug loading and evaluated for particle size, drug EE, zeta potential, in vitro drug release, and stability. Results: The prepared nanoformulations were evaluated for different parameters and found to be in an acceptable range. In vitro drug release of optimized SLN formulation (F1) was found to be 98.12±1.52%, whereas pure drug release was 42.12 after 60 min, and the major mechanism of drug release follows zero-order kinetics release data for optimized formulation (F1) with non-Fickian (anomalous) with a strong correlation coefficient (R 2 =0.98598) of Korsmeyer-Peppas model. Transmission electron microscopy analysis has demonstrated the presence of individual nanoparticles in spherical shape, and the results were also compatible with particle size measurements. The drug content of tazarotene gel formulation was found to 98.96±0.021%, and the viscosity of gel formulation at 5 rpm was found to be 5.98×103±0.34×103 cp. The release rate (flux) of tazarotene across the membrane and expunged skin diverges pointedly, which specifies the barrier nature of skin. The flux value for SLN based gel formulation (193.454±4.324 μg/cm 2 /h) was found to be higher than that for marketed gel (116.345±2.238 μg/cm 2 /h). The higher flux and Kp values of SLN based gel suggest that it might be able to enter the skin easily as compared with marketed gel with an advantage of low interfacial tension of the emulsifier film that ensures an excellent contact to the skin. Conclusion: From the obtained results, the topically oriented SLN-based gel formulation of tazarotene could be useful in providing effective and site- specific psoriasis treatment.
Conversion of Waste Cooking Oil into Biodiesel

About 20 million tons of waste cooking oil (WCO) are produced in China every year. The present method of converting WCO to biodiesel suffers from the problems of low economic efficiency and low product (quality). In fact, most of the WCO are illegally used for producing edible oil, which seriously harms the publish health. This project is aimed at utilizing WCO to produce high-quality biodiesel to facilitate an effective use of the waste and minimize the environmental effect.
Geographic Information System–Based Spatial and Statistical Analysis of Severe Crash Hotspot Accessibility to Hospitals

Previous studies have examined hospital accessibility issues, and other work has exhaustively investigated several aspects of roadway crashes, such as their severity and frequency, possible causal factors, and their clustering on networks. However, the nature of the relationship between them, in the accessibility of severe crash hotspots to hospitals with emergency services, is relatively unexplored. Looking at both elements simultaneously is especially critical, given the need to provide the necessary aid to crash victims in a timely manner to help reduce roadway deaths. To the authors’ knowledge, such an assessment has not been attempted before. The objective of this study was twofold. First, the study investigated accessibility through the use of geographic information systems and statistical analysis to detect high-risk locations. Second, the study used hierarchical multinomial logistic regression analysis to examine several environmental, traffic, and human factors to identify the determinants of the crashes that constitute hotspots. The results show that several roadway segments portend an elevated threat of injury and fatalities for drivers and passengers, not only due to a higher probability of being severely injured, but also because of the low accessibility to hospitals having emergency services. The results suggest that particular spatial, traffic, and roadway factors, such as intersection presence or speed limits, substantially imperil traffic safety. The knowledge gained from this study can help agencies and officials pinpoint and investigate high-risk locations to enhance the safety of roadway users.
In vitro propagation and somaclonal variation study of Phlogacanthus thyrsiformis Nees an ethnic medicinal plant

Bodoland Territorial Region is very rich in natural bioresources, and the Bodo tribes of the region use numerous ethnic medicinal plants to treat different kinds of diseases. Phlogacanthus thyrsiformis Nees is an important medicinal shrub species used in the region to treat different kinds of diseases. The objectives of the present study were to develop an efficient in vitro mass propagation technique of the species using nodal explant and study genetic stability in the genome of in vitro propagated plantlets by different RAPD markers. Effective explant surface sterilisation resulted at 2 minutes of treatment with 0.1% mercuric chloride. Explant responses were found most effective in the full strength MS + 1mg/l BAP (6- benzyl amino purine), and explant highest shoot proliferation multiplication and rooting were found in the media MS + 1 mg/l BAP + 0.250 mg/l NAA. Ex vitro rooting of micro propagated plants was most effective when the explants were dipped in 1mg/l IBA for an hour. RAPD assays were conducted using eight sets of random primers (OPC02, OPC05, OPC07, OPC08, OPC09, OPX06, DK2 and OPA01). All the primers except OPC07 and OPA01 formed monomorphic DNA bands in gel electrophoresis and polymorphism was detected by OPC07 and OPA01 primer.
Segmentation of Infant Brain Using Nonnegative Matrix Factorization

This study develops an atlas-based automated framework for segmenting infants’ brains from magnetic resonance imaging (MRI). For the accurate segmentation of different structures of an infant’s brain at the isointense age (6–12 months), our framework integrates features of diffusion tensor imaging (DTI) (e.g., the fractional anisotropy (FA)). A brain diffusion tensor (DT) image and its region map are considered samples of a Markov–Gibbs random field (MGRF) that jointly models visual appearance, shape, and spatial homogeneity of a goal structure. The visual appearance is modeled with an empirical distribution of the probability of the DTI features, fused by their nonnegative matrix factorization (NMF) and allocation to data clusters. Projecting an initial high-dimensional feature space onto a low-dimensional space of the significant fused features with the NMF allows for better separation of the goal structure and its background. The cluster centers in the latter space are determined at the training stage by the K-means clustering. In order to adapt to large infant brain inhomogeneities and segment the brain images more accurately, appearance descriptors of both the first-order and second-order are taken into account in the fused NMF feature space. Additionally, a second-order MGRF model is used to describe the appearance based on the voxel intensities and their pairwise spatial dependencies. An adaptive shape prior that is spatially variant is constructed from a training set of co-aligned images, forming an atlas database. Moreover, the spatial homogeneity of the shape is described with a spatially uniform 3D MGRF of the second-order for region labels. In vivo experiments on nine infant datasets showed promising results in terms of the accuracy, which was computed using three metrics: the 95-percentile modified Hausdorff distance (MHD), the Dice similarity coefficient (DSC), and the absolute volume difference (AVD). Both the quantitative and visual assessments confirm that integrating the proposed NMF-fused DTI feature and intensity MGRF models of visual appearance, the adaptive shape prior, and the shape homogeneity MGRF model is promising in segmenting the infant brain DTI.
Utilization of Spatial Data in Emergency Response: SystemOptimization Based on Analysis of Working Practices

In the area of emergency management, there is immense potential for improvements in utilization of spatial data. Many optimization approaches can be derived from the Digital Earth vision. Experience gained from strategies that will prove useful can consequently enrich the concept of Digital Earth and find their way into other areas of human activities. The paper presents results of research focused on the use of GIS in emergency management. Working practices of fire rescue service operators were analyzed. The analysis revealed many imperfections concerning spatial data availability, accessibility, accuracy, and also methods of data visualization. Results of this analysis were used as the basis for suggestion of possible optimizations in the areas of data visualization, user interface, data use and cooperation. Special attention is paid to geocollaboration as an approach which could significantly improve effectiveness of decision making processes in emergency management.
Kelekatan, resolusi konflik, dan kepuasan hubungan berpacaran pada dewasa muda: Model analisis jalur

Pola kelekatan merupakan salah satu faktor individual yang secara konsisten ditemukan memengaruhi kepuasan hubungan. Resolusi konflik yang konstruktif juga terbukti dapat meningkatkan kepuasan hubungan. Meski pengaruh kedua faktor tersebut terhadap kepuasan berhubungan telah didukung oleh studi-studi mandiri, studi ini bertujuan untuk mengevaluasi secara komprehensif peran dari kedua faktor itu melalui analisis jalur. Oleh karena itu, penelitian ini berfokus untuk melihat bagaimana pengaruh antara dua pola kelekatan (anxious attachment dan avoidant attachment) dan resolusi konflik (keterlibatan konflik, perilaku positif, dan perilaku menghindar) terhadap kepuasan hubungan berpacaran pada dewasa muda dengan menggunakan analisis jalur (path analysis). Terdapat 824 partisipan dewasa muda (18-36 tahun; Musia = 21.6; SD = 2.54) dalam penelitian ini. Hasil penelitian menunjukkan bahwa anxious attachment, avoidant attachment, dan resolusi konflik secara signifikan berpengaruh terhadap kepuasan hubungan. Penelitian ini menggambarkan bahwa pola kelekatan dan resolusi konflik merupakan faktor penting dalam menjaga stabilitas dan kepuasan hubungan.
A Full Lifecycle Authentication Scheme for Large-Scale Smart IoT Applications

The rapid development of IoT (Internet of Things) brings great convenience to people through the utilization of IoT applications, but also brings huge security challenges. Existing IoT security breaches show that many IoT devices have authentication flaws. Although many IoT authentication schemes were proposed, they are not fit for recent smart IoT applications covering IoT device, back-end sever, and user-end mobile applications. To build the first line of defense for smart IoT systems, this paper proposes a new authentication scheme. The proposed scheme first models the entire lifecycle of the IoT device authentication for real-world scenarios of smart IoT systems that contains factory manufacturing, daily usage, and system resetting. For each stage in the lifecycle, the proposed scheme employs efficient symmetric key mechanisms to achieve the authentication between IoT device, back-end server, and mobile application. The proposed scheme supports both server-free local area network communication and sever-involved remote public area communication. Formal security verification shows that the proposed scheme resists existing attacks. The open-source experimental evaluations also show that the proposed scheme is efficient and promising for practical usage.
The Oral Wound Healing Potential of Thai Propolis Based on Its Antioxidant Activity and Stimulation of Oral Fibroblast Migration and Proliferation

Introduction Propolis has demonstrated wound healing effects. Propolis' effects vary based on its composition and geographical origin. However, there are few reports on the effects of propolis on oral wound healing. The aim of this study was to evaluate the antioxidant and in vitro gingival wound healing effects of the n-hexane extract of propolis (HEP), ethyl acetate extract of propolis (EEP), and aqueous extract of propolis (AEP) fractions of the ethanol extract of Thai propolis. Materials and Methods The crude ethanol extract of propolis was obtained by maceration with 95% ethanol that was sequentially fractionated with hexane, ethyl acetate, and distilled water. The chemical profiles of the samples were assessed by thin-layer chromatography (TLC) and gas chromatography-mass spectrometry (GC-MS). Antioxidant activity was determined using DPPH and FRAP assays. The effects of the propolis fractions on human gingival fibroblast (HGF) proliferation, migration, and in vitro wound healing were determined by MTT, modified Boyden chamber, and scratch assay, respectively. Results We found that solvent polarity greatly affected the extract yield and TLC profiles. The highest extract yield was found in HEP (38.88%), followed by EEP (19.8%) and AEP (1.42%). TLC revealed 7 spots in the crude ethanol extract (Rf 0.36–0.80), 6 spots in HEP (Rf 0.42–0.80) and EEP (Rf 0.36–0.72), and 4 spots in AEP (Rf 0.17–0.79). GC-MS analysis revealed a high amount of triterpenoids in HEP (82.97%) compared with EEP (28.96%). However, no triterpenoid was found in AEP. The highest antioxidant activity and stimulation of HGF proliferation were observed in HEP, followed by EEP and AEP. HEP and EEP, but not AEP, enhanced HGF migration. However, all propolis fractions induced wound closure. Conclusions HEP contained a large amount of triterpenoids. Antioxidant and in vitro wound closure effects were found in HEP, EEP, and AEP fractions.
Affective Polarization of a Protest and a Counterprotest: Million MAGA March v. Million Moron March

Protest movements around the world have become increasingly likely to incite counterprotests that adopt an opposing stance. This study examines how a protest and a counterprotest interact with and shape each other as digitally networked connective action. My empirical focus is the so-called Million MAGA March—in which supporters of U.S. President Donald Trump protested the “stealing” of the November 2020 election by his rival, Joe Biden—and a counterprotest that erupted simultaneously. Drawing on a computational mixed-methods approach to examine two corpora of tweets featuring hashtags used by protesters and counterprotesters, respectively, the study identifies three mutually reinforcing dimensions of protest–counterprotest interaction: affective repertoires, discursive strategies, and network structures. It argues that “affective polarization”—or negative partisanship driven by hostility toward an outgroup—offers a useful conceptual means of understanding the significance of affect and collective identity in digital social movements, especially protest–counterprotest interactions. In doing so, the study also addresses concerns that “big data” methods are insensitive to the role of identity and expressive communication in social movements. Finally, the study demonstrates how online and offline political action are mutually constitutive aspects of contemporary contentious politics.
Robust fault diagnosis of rolling bearing via phase space reconstruction of intrinsic mode functions and neural network under various operating conditions

Rolling bearings are important components in mechanical, civil, and aerospace engineering. The practical working conditions of rolling bearings are complex; hence, fault diagnosis of rolling bearings under various operating conditions is very challenging. This paper proposes a novel approach to fault diagnosis of rotary machinery using phase space reconstruction (PSR) of intrinsic mode functions (IMFs) and neural network under various operating conditions. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is employed to decompose vibration signal of rotary component into IMFs denoting high-to-low instantaneous frequencies adaptively. PSR constructs one-dimensional IMFs to high-dimensional IMFs, which helps reveal the underlying nonlinear geometric topology via the reconstructed inherent and hidden dynamical characteristics of the one-dimensional vibration signal. To explore intrinsic dynamical properties, interquartile range (IQR) of Euclidean distance (ED) values of high-dimensional IMFs are extracted as condition indicators and used as input of back propagation (BP) neural network to fulfill fault identification of rolling bearings. The effectiveness and superiority of the proposed approach have been validated by theoretical derivations, numerical simulations and experimental data. The results show that the proposed approach is promising in fault diagnosis of rotary machinery under various operating conditions.
Perceptions of Lecturers, Administrators, and Students About the Workplace as Learning Environment for Undergraduate Medical Students at a National Referral and Teaching Hospital in Uganda

Purpose The workplace is an important element of the learning ecosystem for medical students during their competence development. It offers engagement opportunities that enable students to participate in clinical activities as part of learning in their preparation for future clinical practice. The purpose of this study was to explore the perceptions and experiences of lecturers, administrators, and students of Makerere University College of Health Sciences about the workplace, at Mulago National Referral and Teaching Hospital, as a learning environment for the undergraduate medical students with the ultimate aim of identifying opportunities and challenges to learner competence development in the learning environment for purposes of improvement. Methods The study design was cross-sectional descriptive with a qualitative approach using key informant interviews for the lecturers and administrators and focus group discussions for the students. The framework method was used to perform thematic data analysis. Results The workplace was perceived to be well endowed with adequate patient numbers, a suitable case mix and unrestricted access to patients which enhanced competence development. The challenges reported included inadequate resources, such as infrastructure, equipment and supplies and overcrowding, which compromised competence development. The resource challenge appeared insurmountable in the context of two autonomous institutions with divergent planning priorities in terms of teaching, research, and patient care. Conclusion There were mixed perceptions about the learning environment at the hospital with both enabling and challenging factors on the backdrop of two autonomous institutions with divergent planning priorities in terms of teaching, research, and patient care. In order to improve the workplace as a learning environment, it is imperative that the two institutions find common ground in terms of clinical care, students’ teaching and provision of supplies that are essential not only for patient care but competence development of the learners who are the clinicians of tomorrow.