Using Deep Learning to Automate the Diagnosis of Skin Melanoma

Machine learning and image processing techniques have been widely implemented in the field of medicine to help accurately diagnose a multitude of medical conditions. The automated diagnosis of skin melanoma is one such instance. However, a majority of the successful machine learning models that have been implemented in the past have used deep learning approaches where only raw image data has been utilized to train machine learning models, such as neural networks. While they have been quite effective at predicting the condition of these lesions, they lack key information about the images, such as clinical data, and features that medical professionals consistently rely on for diagnosis. This research project will explore methods to enhance machine learning models with three drastically different skin melanoma datasets, each with their own set of unique challenges. Various preprocessing techniques, machine learning models, and feature extraction methods will be compared to determine the most optimal approach for each dataset. In addition, time and space complexities of the approaches will also be analyzed in order to minimize resource consumption without causing major performance degradation to the model

Inflammation affects ontogeny of L-carnitine hmeostasis mechanisms in the developing rat

ABSTRACT This thesis research involved investigations into the effects of inflammation on maturation of L-carnitine homeostasis in developing rat neonates. The overall hypothesis was an inflammatory stimulus will alter the ontogeny of L-carnitine homeostasis pathways and this depends upon when the inflammatory stimulus occurs in postnatal development. The objective was to investigate the potential effect of inflammation on carnitine transporter expression in different age groups of neonates and evaluation of effect of inflammation on ontogeny and activity of enzymes involved in carnitine biosynthesis and whether this differs depending upon when in postnatal development the inflammatory stimulus occurs. Rat pups at postnatal day 3, 7, and 14 received an intraperitoneal injection of lipopolysaccharide (LPS) at a dose known to cause a febrile reaction in rat neonates. L-Carnitine homeostasis pathways underwent significant ontogenesis during postnatal development in the rat. LPS administration caused a significant decrease in free L-carnitine levels in serum and heart tissue and a decrease in mRNA expression levels of the high affinity carnitine transporter, Octn2, in kidney, heart and intestine at all postnatal ages. Furthermore, significant decreases in mRNA expression levels of key enzymes involved in carnitine biosynthesis was observed, while an increase in carnitine palmitoyltransferase mRNA levels were observed at all postnatal ages. Reductions in butyrobetaine hydroxylase mRNA expression were paralleled by reductions in enzyme activity only at postnatal day 3 and 7. Heart creatine phosphate levels were deceased significantly in LPS treated groups in all postnatal ages; however, ADP and ATP levels were unaffected. Collectively, this research provided experimental evidence for a significant effect of inflammation on changes in L-carnitine homeostasis maturation in early neonatal stages. The maturation of physiological processes may be altered by external factors in early postnatal life

Incorporating Demographic Structure and Variable Interaction Types into Community Assembly Models

Theoretical studies of ecological food webs have allowed ecologists to remove the constraints of specific location and timescales from their study of ecological communities; food webs are generally complex and thus empirical study is difficult. Further, this theoretical approach allows ecologists to compare ecological processes and outcomes across any possible food web structures. However, these simulated communities are only as useful as the model from which they were constructed. Modifying existing considerations in these models, and generating new ones, are the jobs of theoretical ecologists that seek to achieve the shared goal of a majority of simulations: representation of real natural systems. However, there are many different models that have been developed, all by individuals with varying approaches to achieving biologically realistic results. The difficulty of comparing and combining every single model is not a feat any one study or model can be expected to accomplish. Instead, the paired studies presented here seek to examine two ubiquitous features of ecological communities that are often omitted from food web models: stage-structured interactions, and networks of varied ecological interaction types. By generating the results of these differing models, the effects of combining approaches on the assembly and stability of communities can be examined

Photo-activated dynamic isomerization induced large density changes in liquid crystal polymers: A molecular dynamics study

Recent experimental results [Liu and Broer, Nat. Commun. 6 8334 (2015)] reveal that light-responsive azo-doped liquid crystal polymers under dual-wavelength illumination exhibit a significant reduction in density. This reduction in density was attributed to dynamic trans-cis-trans isomerization cycles. The light-induced isomerization kinetics suggest that the fraction of isomers undergoing dynamic isomerization increases with the light sources' intensity. However, experiments have shown that such an increase in intensity does not result in a monotonic decrease in density. Further, it was observed that there exists an optimal combination of the intensities of the dual-wavelength illumination that results in a maximum density reduction. The exact reason for the existence of such an optimal combination remains elusive. In this work, we have performed atomistic simulations to confirm the hypothesis that the density reduction is caused by the dynamic trans-cis-trans isomerization cycles. Subsequently, the atomistic simulations are used to decipher the underlying physics responsible for the counter-intuitive relation between density reduction and intensities. Intensity variations are simulated by varying the forward and backward isomerization probabilities. The simulations show that an optimal combination of these two probabilities will exhibit a maximum density reduction corroborating experimental observations. Consequently, we discovered that a specific frequency of the dynamic trans-cis-trans isomerization cycles would induce maximum distortion in the polymer network resulting in significant density reduction

DETECTION OF PERSONAL PROTECTIVE EQUIPMENT IN EXTREME CONSTRUCTION CONDITIONS USING ANN

The number of deaths in the construction industry is greater than in other industries through a number of countermeasures.  Although workers may intentionally or unintentionally neglect to wear such safety measures, Personal protective equipment (PPE) was continuously being developed to prevent this types of accidents. Performing a safety check manually might be difficult since there can be a lot of coworkers at a site. It is essential to identify worker noncompliance with PPE in an automated and real-time manner. Detection of Personal Protective Equipment in Extreme Construction Conditions Using ANN is the topic of this paper. The web-based collection of 2,509 images from video recordings of many construction sites are utilized as the model's training data set. This Artificial Neural Networks (ANN) model is utilised in the study, which makes use of transfer learning and a basic variation of the YOLOv5 deep learning network. A dataset called CHVG to identify the workers PPE. Described model achieves the parameters as Accuracy as 97%, Recall 97% and Precision 96%. Overall, the analysis shows that computer vision-based techniques for automating safety-related compliance processes on construction sites are both feasible and useful

Unstable distal radius fractures fixation with a 2.4 mm volar variable-angle locking plate: radiological and functional assessment

Background: The main objective of this observational study was to evaluate the functional and radiological outcome of variable angle volar plates in intra-articular distal end radius fractures. Methods: Patients with distal end radius fractures (AO type 3C) treated operatively between Jan 2020 and Dec 2020 and then followed up for at least 12 months. A total of 32 patients (11 men and 21 women) with a mean age of 51.9 years were included in the study. The functional outcome was assessed by using modified Mayo wrist score (MMWS), disabilities of the arm, shoulder, and hand (DASH) score, wrist range of motion (ROM) and grip strength relative to the uninjured side and radiological assessment of radial height, volar tilt, and radial inclination. Results: MMWS and DASH scores improved postoperatively over time. Signs of radiographic union started around 12 weeks after surgery. The most common complication observed was finger and wrist stiffness, which was resolved with active wrist and finger movements. Non-union or hardware-related complications/ late complications such as tendon irritation/attrition were not observed with variable angle volar locking plates. Conclusions: Distal end radius fracture fixation with variable angle plate gives favourable radiological and clinical outcomes. These results can be owed to features such as low profile, variable locking, anatomical design and implant biomechanics. The surgeon determined angulation of the distal row of screw fixation may decrease the incidence of joint penetration and improve fixation of radial styloid and lunate facet stability

E-Go Bicycle Intelligent Speed Adaptation System for Catching the Green Light

The expanding growth of electric bikes in recent years underscores their increasing importance as a sustainable and eco-friendly mode of transportation. With zero emissions and the ability to ease urban congestion, e-bikes are becoming a pivotal solution in promoting greener and more efficient commuting habits. However, signalized intersections and frequent stops at traffic lights (TL) are considered uncomfortable for cyclists. This article introduces a personalized and privacy-preserving Intelligent Speed Adaption (ISA) system that helps cyclists adapt to the required speed to catch the green light. In our system design, traffic lights are augmented with Bluetooth Low Energy (BLE) beaconing devices which allow connected e-bikes to get the remaining green light phase duration, estimate the distance to the intersection, and assist the cyclist to catch the green light when necessary. We address the speed adaption problem as a convex optimization problem to ensure smooth and safe acceleration. In addition, a fuzzy logic controller is used to control motor power to reach the recommended speed while considering the human pedal power. We generate different scenarios with various initial velocities, time to red (TTR), slope of the road, and human pedal power to evaluate the system’s performance. The results demonstrate that ISA improves the probability of crossing the traffic light by about 77% compared to the absence of speed adaptation

Formulación y Optimización del Sistema Flotante de Amoxicilina para el tratamiento efectivo de la infección por Helicobacter pylori

The authors thank DST-FIST Lab (RERDS-CPR), R&D Director, for providing necessary facilities and assistance to perform this research work.Introducción: El objetivo del presente estudio fue formular y caracterizar el Sistema Flotante (FRS, siglas en Inglés) de Amoxicilina para prolongar el tiempo de residencia gástrica y liberación del fármaco para el enfoque efectivo del Helicobacter pylori. Método: Para el presente estudio se seleccionaron como factores goma guar, Monoestearato de glicerilo (GMS), carbonato de calcio. Como reacciones, se seleccionaros el período de congelación (h), el lapso de flotación (min), y el porcentaje acumulado de liberación del fármaco (CDR). Para la experimentación se seleccionaron el diseño factorial 23 con réplicas. Resultados: Se observó que la goma guar y el GMS fueron los factores principales que afectaron el período de congelación y mostraron un efecto sinérgico (positivo). Mientras que la goma guar y el carbonato de calcio mostraron un efecto positivo y el GMS mostró un efecto antagónico (negativo) en el lapso de flotación. El porcentaje CDR mostró un efecto antagónico en todos los factores. Se emplearon curvas de nivel para identificar el diseño del espacio, análisis numéricos posteriores produjeron 12 soluciones óptimas en base a la deseabilidad. El FRS mostró un mayor AUCo-t, Cmax, tmaxy t1/2 cuando se comparó con la formulación comercial, aproximadamente 2.30 cambios múltiplos y prolongación con liberación sostenida por más de 24 h que pudo deberse a una mejor congelación. Conclusiones: Se puede concluir que el sistema flotante se desarrolló satisfactoriamente por la aplicación del Diseño de Experimentos (DoE) con menores ensayos y utilizando fácilmente los excipientes disponibles para una mejor flotación, congelación y suministro constante del fármaco.Introduction: The aim of the present study was to develop and to characterize the floating raft system (FRS) of Amoxicillin to enhance gastric residence time and drug release to target Helicobacter pylori effectively. Method: In the present study, guar gum, glyceryl monostearate (GMS), calcium carbonate were selected as factors. Gelation duration (h), floating lag time (min), and % Cumulative drug release (CDR) were selected as responses. 23 factorial design with replicates was selected for experimentation. Results: It was observed that guar gum and GMS were the major factors affecting gelation duration, increase in the quantity of both guar gum and GMS increased gelation duration i.e., sustained gelation period (24 h). Floating time increased with an increase in the amount of guar gum and calcium carbonate, whereas an increase in the quantity of GMS decreased floating time. Guar gum, calcium carbonate, and GMS exhibited an antagonistic effect on % CDR. Contour plots were used to identify design space; further numerical analysis yielded 12 best solutions based on desirability. FRS exhibited greater AUCo-t, Cmax, tmax, and t1/2 when compared to marketed formulation approximately 2.30 folds enhancement and prolongation with a sustained release for greater than 24 h that might be due to better gelation. Conclusions: It can be concluded that the floating raft system was successfully developed by the Design of experiment (DoE) application with fewer trails and by utilizing easily available excipients for better floating, gelation, and sustained delivery of the drug

Metal-assisted red light-induced efficient DNA cleavage by dipyridoquinoxaline-copper(II) complex

Complete cleavage of double stranded pUC19 DNA by the complex [Cu(dpq)2(H2O)](ClO4)2 (dpq, dipyridoquinoxaline) has been observed on irradiation at 694 nm from a pulsed ruby laser, assisted by the metal d-band transition as well as the quinoxaline triplet states in the absence of any external additives

Region-based Convolutional Neural Network Driven Alzheimer’s Severity Prediction

It's important to note that Alzheimer's disease can also affect individuals over the age of 60, and in fact, the risk of developing Alzheimer's increases with age. Additionally, while deep learning approaches have shown promising results in detecting Alzheimer's disease, they are not the only techniques available for diagnosis and treatment. That being said, using Region-based Convolutional Neural Network (RCNN) for efficient feature extraction and classification can be a valuable tool in detecting Alzheimer's disease. This new approach to identifying Alzheimer's disease could lead to a more accurate and personalized diagnosis. It can also help in early treatment and intervention. However, it's still important to continue developing new methods and techniques for this disorder. Considering this our work proposes an innovative Region-based Convolutional Neural Network Driven Alzheimer’s Severity Prediction approach in this paper. The exhaustive experimental result carried out, which proves the efficacy of our Alzheimer prediction system