Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical Analysis of Light Extraction Efficiency of a Core-shell Nanorod Light-emitting Diode

We present a detailed analysis of the light extraction efficiency (LEE) of a core-shell nanorod light emitting diode (LED) using finite-difference time-domain (FDTD) simulations. We found that the LEE has a deep dependence on source positions and polarization directions based on the calculated LEE results for every x and z position inside the core-shell nanorod structure. The LEEs are different for the upper part (pyramid) and the lower part (sidewall) of the core-shell nanorod owing to total internal reflection (TIR) and the generated optical modes in the structure. As a result, the LEE of sidewall is much larger than that of pyramid. The averaged LEE of the core-shell nanorod LED is also investigated with variable p -GaN thickness, n -GaN thickness, and height for the design guidelines for the optimized LEE of core-shell nanorod LEDs.
Cuba's inward-looking development policies:towards sustainable small farming (1990-2008)

While most Latin American countries followed outward-looking policies of agrarian development during the 1990s, Cuba shifted towards food self-provisioning, internal liberalisation and sustainable small farming to face the harsh crisis that followed the socialist demise of the late 1980s. Although it was an indispensable response to the worst crisis in Cuban history, Cuba is today one of the few countries experimenting with alternative development on a national scale. By considering the current context of globalisation in which free trade agreements and progressive agrarian liberalisation have created asymmetrical trade relations, increasing import dependency and vulnerability for small farmers in less developed countries, this paper aims at answering the following questions: 1. Which were the main policies implemented under inward-looking agrarian development in Cuba between 1990 and 2008? 2. What were the changes experienced in agriculture production patterns and land structures prompted by inward-looking development in Cuba? 3. To what extent these new patterns of production and land decentralisation opened opportunities for sustainable small farming production?
MIT Open Access Articles Bonding, antibonding and tunable optical forces in asymmetric membranes

: We demonstrate that tunable attractive (bonding) and repulsive (anti-bonding) forces can arise in highly asymmetric structures coupled to external radiation, a consequence of the bonding/anti-bonding level repulsion of guided-wave resonances that was ﬁrst predicted in symmetric systems. Our focus is a geometry consisting of a photonic-crystal (holey) membrane suspended above an unpatterned layered substrate, supporting planar waveguide modes that can couple via the periodic modulation of the holey membrane. Asymmetric geometries have a clear advantage in ease of fabrication and experimental characterization compared to symmetric double-membrane structures. We show that the asymmetry can also lead to unusual behavior in the force magnitudes of a bonding/antibonding pair as the membrane separation changes, including nonmonotonic de-pendences on the separation. We propose a computational method that obtains the entire force spectrum via a single time-domain simulation, by Fourier-transforming the response to a short pulse and thereby obtaining the frequency-dependent stress tensor. We point out that by operating with two, instead of a single frequency, these evanescent forces can be exploited to tune the spring constant of the membrane without changing its equilibrium separation.
Design of functional binders for high-specific-energy lithium-ion batteries: from molecular structure to electrode properties

The binder adheres to each component of the electrode to maintain the structural integrity and plays an irreplaceable role in a battery despite its low content. Polyvinylidene difluoride (PVDF), as the dominant binder in commercial battery systems (for cathodes), has acceptably balanced properties between chemical/electrochemical stability and adhesive ability. However, in the pursuit of high-specific-energy batteries featuring high mass loading, high voltage, and large volume changes, the PVDF binder is unable to satisfy the versatile electrode demands and extreme operation conditions. Therefore, developing novel binders with task-specific functionality is of urgent need. Herein, we review the recently developed design strategies of functional binders from the insight of molecular design. The functions and failure mechanisms of the binders are elucidated first. Starting from the basic moiety (functional group) of the polymer molecule, how the constituents, molecular structure, and assembly into a supramolecule will affect the properties of the binders, and furthermore the performance of the electrodes, is discussed at length. Finally, we summarize and provide a future outlook on the opportunities and challenges of functional binders towards future high-specific-energy lithium-ion batteries.
AN INVESTTIGATION INTO THE CATEGORYOF FOODS WASTED WITHIN THE HOSPITALITY INDUSTRY IN THE UPPER WEST REGION

The study investigated the category of foods wasted in the hospitality industry in the Upper West Region of Ghana. The study population came from food vendors, chop bar operators, accommodation facilities, and food hawkers within the Upper West Region of Ghana. A stratified sampling approach was used in the selection of the study sample. Subsequently, the Krejcie and Morgan sampling table was used to determine the sample size for the different segments of the population. The study used a survey research design where questionnaire instruments based on a five-point Likert scale were used for the study data collection. Data from this study was an analysis based on descriptive statistics (i.e. frequency and percentage) and inferential statistics such as principal component analysis and multiple regression analysis. Results from the study suggest that the category of foods that often go waste in the understudied hospitality firms in the Upper West Region did not take a singular form but came from several food types. Also, it was established that restaurants‟ operating procedures and policies as well as chefs'/cooks' lack of ideas on how to use left-over food items for other dishes accounted for most of the food wastage in the hospitality sector.
A PATIENT GUIDE TO FAILED ROTATOR CUFF REPAIRS

The most common causes of pain after rotator cuff surgery are (1) that the shoulder is still recovering from the surgery itself and (2) the shoulder has gotten stiff due to lack of movement. It is well known that rotator cuff surgery is a major operation where the rotator cuff tendons (Figure 1) are sewn back to the upper arm bone (humerus) (See a Patient Guide to Rotator Cuff Repair) (Figures 2 and 3).
MeshGit : Diffing and Merging Polygonal Meshes

This paper presents MeshGit , a practical algorithm for difﬁng and merging polygonal meshes. Inspired by version control for text editing, we introduce the mesh edit distance as a measure of the dissimilarity between meshes. This distance is deﬁned as the min- imum cost of matching the vertices and faces of one mesh to those of another. We propose an iterative greedy algorithm to approxi- mate the mesh edit distance, which scales well with model complexity, providing a practical solution to our problem. We translate the mesh correspondence into a set of mesh editing operations that transforms the ﬁrst mesh into the second. The editing operations can be displayed directly to provide a meaningful visual difference between meshes. For merging, we compute the difference between two versions and their common ancestor, as sets of editing operations. We robustly detect conﬂicting operations, automatically ap- ply non-conﬂicting edits, and allow the user to choose how to merge the conﬂicting edits. We evaluate MeshGit by difﬁng and merging a variety of meshes and ﬁnd it to work well for all.
Validation of Analysis of S-Phenyl Mercapturic Acid in Urine by High-Performance Liquid Chromatography – Photodiode Array

Abstract An easy, eclectic, precise, and high-performance liquid chromatography (HPLC) analysis was developed and validated for the estimation of S-phenyl mercapturic acid in urine. The chromatographic separation was achieved using a separation column of the ODS-3 Inertsil type with dimensions of (5μ ,150mm x 4.6mm). The column temperature was set at 45° C. A mobile phase composed of acetonitrile: methanol: deionized water acidified with perchloric acid 60% (v/v/v ratio of 4:1:5, pH=3) was used at a flow rate of 1.5 ml/min and a wavelength of 225 nm for UV detection. System Suitability tests (SSTs) are typically performed to assess the suitability and effectiveness of the entire chromatography system. Retention times of S-phenyl mercapturic acid and Benzoic acid were found to be 17.3 and 15.6 minutes, respectively. The detection limit was 0.126 μg/ml, the quantitative estimation unit was 0.38 μg/ml, and the recovery was 97.183%. S-phenyl mercapturic acid showed a linear signal in the domain of 0.5-20 μg/mL. The developed method has been validated through linearity, precision, accuracy, specificity, LOD, and LOQ. Therefore, the proposed analytical method proved its applicability and efficiency in estimating the benzene metabolite in urine.
LBGM Classifier-Based Automated Identification and Prediction of Epileptic Seizures

Epilepsy is a neurological disease of the brain that causes repeated seizures. Neurologists utilize electroencephalography (EEG) to record epileptic seizures. Automated seizure identification is a crucial step in the diagnosis of epilepsy overcoming the limitations of visual diagnosis. This study makes use of the Children’s Hospital of the Massachusetts Institute of Technology, Boston (CHB-MIT) dataset. The seizure detection system implemented in this research utilized the variational mode decomposition (VMD) method and Light Gradient Boosting Classifier (LGBM). The seizure and no seizure signals are separated using the K-fold cross-validating technique after the linear and non-linear properties are recovered from the band limited-intrinsic mode functions (BL-IMFs). This approach performance is evaluated with the sensitivity, specificity, and accuracy metrics and achieved an average of 82.32%, 86.49%, and 90.53% respectively for all patients in the dataset.
Building detection in aerial images using fusion of U-Net and ResNet architectures

Semantic segmentation describes the procedure of giving each pixel in an image a unique class name. With the increased accessibility of high-resolution remote sensing data, there has been a tremendous increase in interest of urban feature segmentation such as buildings, roads, bridges and railways. Detection of buildings is of great interest in the field of urban planning, disaster management and 3D modelling. Deep learning algorithms are showing positive results such as greater accuracy and are effective in building detection purpose even in challenging conditions. In this study, we have implemented building detection using a deep learning CNN architecture named as Residual Network (ResNet) as a backbone model. U-Net model has been used as base model for building detection purpose for Massachusetts Buildings Dataset. In this paper, initially the aerial image dataset has been trained on U-net model for 10 epochs having 12 batch size and binary cross-entropy-focal-dice loss as loss function. During the evaluation of the aerial image dataset, various ResNet architectures were used as backbone models. Mean Intersection over Union (MeanIoU), Intersection over Union (IoU) score, accuracy, precision, recall, and F1 score were the evaluation measures used. These metrics were assessed by utilizing the same loss functions across all the ResNet architectures. This finding indicates that, when compared to alternative ResNet architectures, the ResNet-101 model offers significantly better results. According to Resnet101, MeanIoU is 72.67%, and IoU score is 87.03%, while accuracy, precision, recall, and F1 score is 93.06%, 86.61%, and 92.91% respectively.
A APOD PWM based Seventeen level Inverter with less Total Harmonic Distortion

In high-powered solar PV arrangements, conventional multi-level inverter (MLI) topologies have drawbacks such as significant total harmonic distortion (THD) and the requirement of several switching components, which raises the overall cost. The size and price of the inverter rise even if adding a large filter component to the input side may greatly decrease THD. Thus, attaining output AC sinewave with reduced THD is a major challenge for MLIs present in literature. A proposed MLI addresses these issues by modifying the cascaded H-Bridge assembly and using Alternate phase opposition disposition (APOD) PWM method to decrease THD at the output. The suggested inverter does not need any extra voltage balancing capacitors or clamping diodes since it contains 6 unidirectional switches and 2 bidirectional switches. For the purpose of producing gate pulses, the switching states and APOD PWM operation are thoroughly discussed. The proposed Multi-Level Inverter (MLI) is analyzed through waveform plots, equations, and mathematical analysis. A steady-state examination reveals that the MLI uses only four DC sources to provide an output voltage with 17 levels. In comparison to current MLI topologies, simulation results of the inverter in three and single phase assemblies show that the proposed MLI performs better and has a much reduced THD. According to the simulation findings, the suggested MLI has a THD of 0.98%, which is much less than the THDs of four standard MLIs, which are 6.1%, 6.63%, 7.3%, and 9.93%. Furthermore, although typical MLIs use more than 10 Switches to create 15 voltage levels, the suggested MLI produces 17 voltage levels with only 8 switching devices.
Printed MIMO Antenna for C and X band Applications

In this paper, MIMO (Multiple-Input Multiple-Output) antenna is introduced. The proposed MIMO antenna is to achieve a multiband response and high efficiency. This antenna is fabricated on FR4 substrate with the thickness of 0.8 mm. The size of the antenna is 30*30mm2. The field distribution of proposed antenna is observed. The fabricated antenna results is tested and compared. The proposed antenna is suitable candidate for C and X band applications.
Novel Isolated Two Port High Efficient Electrolytic Capacitor Less Led Driver

Light Emitting Diodes(LED) are more efficient and having more life span. Using electrolytic capacitors in the driver reduces the life time of LED but using film or ceramic capacitor not effect the life time of LED so, eliminating the electrolytic capacitor at the output side of the driver circuit became the major area of research. In this paper, A Novel Isolated Two Port High Efficient Electrolytic Capacitor Less LED Driver is presented. The topology discussed in this paper consist of an isolated flyback DC-DC converter operating under DCM (Discontinuous Conduction Mode) is used to obtain unity power factor at the input side of the diode bridge rectifier.Effective ripple ports are installed at the output side of the LED driver to reduce the amount of storage required there and to employ film capacitors as alternatives to electrolytic capacitors. In this paper, a simple constant voltage controller and an hysteresis controller strategy is used. This combination of flyback converter and ripple port at output of LED driver is 93.9% efficient. The driver’s input side achieves a 0.999 power factor. 3.19% of input current THD.
Geospatial Analysis of Crime Against Women

Crime against women is a pressing issue that requires comprehensive analysis and effective solutions. This research paper employs geospatial analysis to investigate the spatial patterns and dynamics of crime against women. The study utilizes a dataset collected from various sources, including government records and public databases. The methodology involves data integration, geocoding, and spatial analysis techniques to explore the spatial distribution of crimes and identify hotspots of women-based crimes. Moreover, advanced visualization techniques are employed to present the results in a clear and meaningful way. The findings of this study contribute to a better understanding of the spatial characteristics of crime against women, facilitating evidence-based policy recommendations for targeted intervention strategies. The research demonstrates the potential of geospatial analysis in enhancing our understanding of the geographical aspects of women's safety and provides insights for future research in this domain.
The Road to Low Fertility

The power of low fertility to transform the European demographic landscape has become a major pre-occupation of policy-makers. Some think that Europe, with inexorably shrinking and ageing populations, is on the brink of a demographically-driven catastrophe. The demographic landscape, however, as this paper argues, is no less complicated and varied than are the forces that are driving current trends in fertility. In the beginning Media folk are fond of writing about ‘Europe’s declining birth rate’ leading inevitably to the disastrous detonation of ‘demographic time-bombs’; part of an understandable media preference for bad news. The story of recent fertility trends, however, is much more complicated. To put modern fertility behaviour into perspective we must go back to the 1930s to the end of the ‘demographic transition’. That was the process, beginning in the 18 th century, whereby the high birth and death rates of traditional society declined to those of the modern world: that is, at most two children on average, with an expectation of life of 75 years and increasing. The transition in countries such as Britain came to an end in the 1930s, if the ‘end’ can be taken to mean the return to an approximate balance between fertility and mortality rates that was left behind in the 18 th century. Around that
Early Prediction of Sepsis using ML Algorithms on Clinical Data

A poorly controlled host reaction to infection results in sepsis, a potentially fatal organ failure. If not treated early, it can cause multiple organ failure, septic shock and even death. Most of the time, it is a serious infection-related consequence, especially in low and middle-income countries where it is a significant contributor to maternal and newborn morbidity and mortality. We are building a model which will predict Sepsis well before time using only vital signs of the patients like Heart Rate, Age, BP, and o2stat level. We have proposed a system that will predict the occurrence of sepsis well before time to save a patient’s life. We will be using Physionet 2019 Challenge dataset for training our ML model to predict the desired output.
Deep Reinforcement Learning-based QoS Aware Routing in Software Defined Networks

Software-Defined Networks (SDN) is the nextgen network technology which helps in efficient management of networks. The important concept underlying SDN is the separation of the data plane and control plane. The data plane devices serve as forwarding devices and decision-making is shifted to a controller which operates on the control plane. Recently, machine intelligence is used by researchers to enhance SDN-based centralised control by routing and flow management which helps in optimal network traffic management. In this work, we propose a machine learning-based system to optimize the routing efficiency of a network. A deep reinforcement learning-based routing algorithm called Advantage Actor-Critic (A2C) is used to compute optimal routes. The results are compared with two algorithms namely Dijkstra’s shortest path and deep neural network algorithm called Actor-Critic (AC) Networks. Simulation results using Mininet emulator reveals that routing with A2C provides higher throughput and a lower average delay in comparison with AC.
Experimental Investigation Of An Ultra-thin Vapor Chamber With Water And Pure 2-propanol As Working Fluids

Vapor chambers present a highly effective solution for dissipating high heat flux in thin, high-powered electronic devices. In this context, an ultra-thin vapor chamber measuring just 1.5 mm in thickness was developed specifically for experimental investigations. Certain pure alcohols have shown potential thermal Marangoni effects, primarily due to temperature gradients within the fluid bulk. This phenomenon is anticipated to yield improved evaporation characteristics compared to conventional pure fluids. To explore this possibility, the study selected two distinct working fluids, water, and pure 2-propanol, for experimentation. The focus was on observing the influence of the working fluid's charge ratio on key parameters such as the vapor chamber's thermal resistance, evaporator temperature, evaporator heat transfer coefficient, and condenser temperature.The findings revealed a strong correlation between the charge level of the working fluid and the vapor chamber's thermal performance, considering a fixed input power. Pure 2-propanol exhibited lower thermal resistance and evaporator temperature at lower charge levels than pure water. However, at very high charge levels, both of these parameters were lower for pure water. Predictions of the Marangoni number strongly support this charge-dependent thermal behavior exhibited by the two pure fluids.
Application of Deep Learning Strategy for Multi-classification of Indian Heritage Images

For the benefit of the world, heritage conservation and protection has been an active and important area of research. Heritage is considerably more than simply maintaining, unearthing, exhibiting, or restoring a collection of antiquated items. A heritage term covers a large range of inherited traditions, monuments buildings, stones, culture, birds, animals, and many more, which collectively depicts the quality of the legacy of a country. The preservation and digitization of cultural heritage are yet uncharted territories for many scholars therefore, an efficient heritage recognition and classification (HRC) model has been created based on deep learning (DL) strategy. The complete model conduction and implementation have been done using various Indian heritage images comprises of 10000 images containing four categories of heritage images namely animals, birds, monuments, and paintings. The complete process outcome resulted in a recognition accuracy of 94.32% using the binary classification technique, whereas 95.43% accuracy has been observed for further multi-classification tasks of heritage category images. The suggested study will assist in sustainable development, environmental upgradation, heritage preservation, and economic evolution for society and researchers in the aforementioned field.
Full-Duplex Antenna Using Bow-Tie-shaped DGS BPF

A novel design is introduced in this paper for the full-duplex operation in wireless communication systems using a shared square patch antenna. The duplex antenna consists of a single corner slotted square radiating patch and defected ground structures (DGSs) of bow-tie-shaped with partial ground planes. The dual-polarization and frequency diversity techniques are implemented to attain the isolation between the antenna ports. The DGS bandpass filters (BPFs) are embedded underneath the microstrip feedlines from the antenna ports. The designed dual-band antenna resonates at 2.61 GHz and 2.75 GHz, achieves the minimum interport isolation of 42 dB in both entire operative bands, attains the maximum isolation of 45 dB, and has an excellent frequency spacing ratio of r = 0.05. Also, the proposed design can operate in the entire S-band by adequately scaling the sizes of bow-tie-shaped DGSs that regulate the resonant frequency of the incorporated BPFs. Furthermore, the DGS BPFs have good cut-off characteristics, selectivity, and a channel bandwidth of about BW ≤ 820 MHz. The proposed antenna offers bidirectional radiation patterns in both E and H planes at the resonating frequency of the dual bands.