bluuebunny/crossref_metadata_2025_split huggingface dataset:
Processing and characterization of large area InP nanowire photovoltaic devices
Authors: Alcer David , Hrachowina Lukas , Hessman Dan , Borgström Magnus T 
Published: April 2023

Abstract
III−V nanowire (NW) photovoltaic devices promise high efficiencies at reduced materials usage. However, research has so far focused on small devices, mostly ≤1 mm2. In this study, the upscaling potential of axial junction InP NW photovoltaic devices is investigated. Device processing was carried out on a full 2″ wafer, with device sizes up to 1 cm2, which is a significant increase from the mm-scale III−V NW photovoltaic devices published previously. The short-circuit current density of the largest 1 cm2 devices, in which 460 million NWs are contacted in parallel, is on par with smaller devices. This enables a record power generation of 6.0 mW under AM1.5 G illumination, more than one order of magnitude higher than previous III−V NW photovoltaic devices. On the other hand, the fill factor of the larger devices is lower in comparison with smaller devices, which affects the device efficiency. By use of electroluminescence mapping, resistive losses in the indium tin oxide (ITO) front contact are found to limit the fill factor of the large devices. We use combined light-beam induced current (LBIC) and photoluminescence (PL) mapping as a powerful characterization tool for NW photovoltaic devices. From the LBIC and PL maps, local defects can be identified on the fully processed devices.
Revisiting f(R) gravity's rainbow: Inflation and primordial fluctuations
Authors: Leyva Yoelsy , Otalora Giovanni 
Published: April 2023

Abstract
We study inflation and the generation of primordial fluctuations in f(R) gravity's
rainbow. We calculate the cosmological perturbations and then the scalar and tensor primordial
power spectrum. We contrast the predictions of the model with the current observational data from
PLANCK and BICEP/Keck. Particularly, we found new results for the scalar spectral index ns
and
the tensor-to-scalar ratio r along with new observational constraints on the rainbow functions.
Capacity Analysis of Intelligent Reflecting Surface assisted RSMA System with Perfect and Imperfect CSI for 6G
Authors: Aswini K , Surendar M 
Published: April 2023

Abstract
Rate splitting multiple access (RSMA) and intelligent reflecting surface (IRS) are the promising candidates and front runners for 5G and beyond wireless communication. Recent studies have proved RSMA-IRS outperforms non-orthogonal multiple access (NOMA) and enhances the quality of service (QoS). The performance of the downlink RSMA-IRS system is investigated in this paper using perfect and imperfect channel state information (CSI) conditions over the Rayleigh fading channel. Furthermore, the numerical analysis for the sum rate capacity is carriedout for the users under perfect and imperfect conditions. To assess the system’s performance, two distinct scenarios are explored. Initially, the system total capacity of each user’s common and private parts is determined without considering the channel estimate error (CEE). The total capacity for each user’s common part is 10 b/s, for private1 is 8.9 b/s, and for private2 is 6.5 b/s. After introducing CEE, the sum rate for the common part is 8.5 b/s, and the total capacity for private1 and private2 is 7.5 b/s and 6 b/s, respectively. The simulation results show that the perfect CSI, achieves enhanced sum rate than channel with CEE. however, to tolerate the imperfect scenario (CEE) optimum power allocation is determined for attaining the QoS.
Slot Antenna for Ultra-Wideband Automobile Applications at 24 GHz
Authors: Boopathi Rani R , Padmavathi S 
Published: April 2023

Abstract
This research article discusses the investigations on the design of an Ultra-Wideband (UWB) antenna and its performance analysis from 20 to 30 GHz frequency range which is suitable for Short Range (SR) RADAR applications. This is designed by incorporating a rectangular slot on rectangular patch and reducing the ground plane size. The antenna characteristics namely return loss, current distribution, E-plane and H-plane far field patterns, gain over frequency, group delay in the operating frequency and radiation efficiency are investigated through simulations. Brief discussion regarding FCC guidelines related to the use of 24 GHz frequency band is provided. The antenna occupies the size of 10 X 10 X 1.6 mm3. Necessary parametric analyses were performed to confirm the finalized dimensions as optimum. The impedance bandwidth characteristics was measured using VNA (Vector Network Analyzer) and the obtained –10 dB bandwidth agrees with the simulated result.
Enhancing the network lifetime of a wireless sensor network using modified k-means Firefly Optimization
Authors: Joseph Abin John , Asaletha R , Manoj V.J , Nishanth R 
Published: April 2023

Abstract
Developing technology including the Internet of Things, digital services, smart microgrids, and machine-to-machine systems encourage the implementation of self-configuring, automated systems in massive wireless sensor networks (WSNs). Effective Power utilization is critical in order to keep a network operational for the maximum possible time. Sensor nodes, which are small, battery-powered devices, are used in WSNs. As a result, one of the significant research issues in improving the lifespan of a WSN is resource management. A modified k-means (Mk-means) algorithm for clustering has been proposed to select Cluster Head (CH) to minimize energy usage of the nodes. Several optimization methods have been suggested in this area to extend the WSN lifetime. Following that, the Firefly Algorithm (FFA) is employed to generate the optimal routing through the CHs to a Base Station (BS), where multiple fitness functions such as residual energy, distance, and routing traffic are taken into account to optimize the FFA. As a result, information transmission among intermediate CHs in a hierarchy cluster-based design aids in lowering node energy usage. The proposed MKMFA (modified k-means Firefly Algorithm) technique’s performance is evaluated with K-means AODV (Ad-hoc On-demand Distance Vector) and IPC-KMAN(Improved Performance Clustering Using Modified K-Means Algorithm in Mobile Adhoc Networks) using network lifetime, throughput, Load Balancing Factor (LBF), and Packet Delivery Ratio (PDR). This work is based on recent advances in WSNs, which include application fields, design parameters, and lifetime prediction designs.
A Comprehensive Analysis of Various Delineation method for Exudates in Fundus Images using Miniaturized Pi Board
Authors: Ramasubramanian B , Elangovan K , Hemanand D , Kavin Kumar K 
Published: April 2023

Abstract
In current decades, employing clinical imagery analysis to automatically segregate exudates from color fundus pictures has proven to be a difficult endeavor. This paper compares the efficacy of several picture delineation techniques using a Raspberry Pi chip. By employing various techniques to regular publically accessible samples, the optimum delineation methodology is selected, while efficacy is measured using characteristics such as resemblance factors, implementation duration, sensitivity, as well as specificity. The source hue ocular pictures are initially obtained using publicly available resources. Gaussian distortion, impulse distortion, and speckle distortion could all be present in such pictures. As a result, a pre-processing approach is used to the source pictures in effort to reduce the distortion and boost brightness. After that, several delineation methods such as a thresholding technique, mean-shift algorithm, watershed algorithm, distance transform, K-means clustering, Fuzzy C-Means grouping approach and Active Contour Model are used to segment the normal and abnormal region in color fundus images. The Fuzzy C-Means grouping approach yields higher delineation precision yet requires longer execution time, according to the findings.
Real Time Robotic Arm using Leap Motion Controller
Authors: Mariappan R , Gayathri P , Pushpalatha P , Sri Sidhvi Rishik V , Satish T. 
Published: April 2023

Abstract
Robots are playing key role in today’s world. Robots are actively taking part in the industries, hospitals, defense applications as well. This paper describes about how hand gesture movements can control the robotic arm. Hand gesture data is recorded by the leap motion controller. That captured gestures are then processed and sent to the microcontroller. In this paper we are intended to design a robotic arm that is completely useful to the people with disabilities. We are using new kind of sensor called Leap motion controller, which captures the hand gestures in 3D. we develop a robotic arm that is useful for the paralyzed people, industrial applications, medical fields by just simply using the hands, we can guide the leap motion controller so that the robotic arm can perform its operations.
Prediction of Rainfall Analysis Using Logistic Regression and Support Vector Machine
Authors: Praveena R , Babu T R Ganesh , Birunda M , Sudha G , Sukumar P , Gnanasoundharam J 
Published: April 2023

Abstract
Rainfall prediction has a major effect on human civilization and is one of the most difficult, unpredictable activities. Precise and accurate predictions will help to rising human and financial risks pro-actively. This work presents a current supervised learning models of machine learning to focused on the Rainfall Prediction. Rainfall is also a significant issue in the planet because it impacts any single aspects that relies on the human being. Unpredictable and reliable estimation of rainfall is a challenging job today. In this work, gives a maximum outcome and a stronger forecast for rainfall using logistic regression and support Vector Machine (SVM) classifier for better prediction.
Computative Analysis of Various Techniques for Classification of Liver Disease
Authors: Sujith J. , Kumar P. Karthik , Reddy S. Joshi Manohar , Kanhe Aniruddha 
Published: April 2023

Abstract
This paper presents a software-engineered approach using a classification algorithm for the classification of liver disease. The ILPD dataset is used for the proposed work. Different attributes of liver patient records such as direct bilirubin, age, sex, total bilirubin, alphos, albumin, sgpt, globulin ratio, sgot are used to classify liver disease. The proposed Convolution Neural Network classification technique shows an accuracy of 67% and a precision of 71%. Various classification algorithms such as CNN, RNN, ANN, and logistic regression are executed on the liver patient dataset and their accuracy is determined.
A reconfigurable Micro-channel plate “RSP” detector for wide-range application in charged particle detection
Authors: Schössler Sven , Fořt Tomáš , Sobota Jaroslav , Hay Nigel , Milnes James , Jagutzki Ottmar 
Published: April 2023

Abstract
We have developed an MCP detector with reconfigurable
read-out which is capable of recording the position and time
information for single particle counting and alternatively of
operating at high particle flux with optical read-out. This is
achieved by a Resistive Screen with embedded Phosphor (RSP)
anode. On demand, signal pickup electrodes such as a delay-line
array can be attached or removed without interfering with vacuum,
allowing easy switching between the different operation modes. We
show tests of a prototype.
The EXTRA-BL4S experiment for the measurement of the energy and angular distributions of transition radiation X-rays
Authors: Mazziotta Mario Nicola , Loparco Francesco , Anelli Alberto , Belviso Micaela Marialucia , Buquicchio Andrea , Cassano Elena Vera , De Cosmo Matteo , Ginefra Paolo , Martulli Monica Lucia , Picci Clara , Picicci Dario , Soriano Remo Domenico , Tatulli Alberto Pio , Tripaldella Giuseppe , Zupo Vittorio Maria , Muscarella Maria Filomena , Turbacci Stefania , Boselli Margherita , da Cruz E Silva Cristóvão Beirão , Joos Markus , Schütze Paul 
Published: April 2023

Abstract
We have designed and implemented an experiment to measure
the angular distributions and the energy spectra of the transition
radiation X-rays emitted by fast electrons and positrons crossing
different radiators. Our experiment was selected among the proposals
of the 2021 Beamline for Schools contest, a competition for
high-school students organized every year by CERN, and was performed
at the DESY II Test Beam facility area TB21, using a high-purity
beam of electrons or positrons with momenta in the range from 1 to
6 GeV/c. The measurements were performed using a
100 μm thick silicon pixel detector, with a pitch of
55 μm. Our results are consistent with the
expectations from the theoretical models describing the production
of transition radiation in multilayer regular radiators.
Thermodynamics of bidirectional associative memories
Authors: Barra Adriano , Catania Giovanni , Decelle Aurélien , Seoane Beatriz 
Published: April 2023

Abstract
In this paper we investigate the equilibrium properties of bidirectional associative memories (BAMs). Introduced by Kosko in 1988 as a generalization of the Hopfield model to a bipartite structure, the simplest architecture is defined by two layers of neurons, with synaptic connections only between units of different layers: even without internal connections within each layer, information storage and retrieval are still possible through the reverberation of neural activities passing from one layer to another. We characterize the computational capabilities of a stochastic extension of this model in the thermodynamic limit, by applying rigorous techniques from statistical physics. A detailed picture of the phase diagram at the replica symmetric level is provided, both at finite temperature and in the noiseless regimes. Also for the latter, the critical load is further investigated up to one step of replica symmetry breaking. An analytical and numerical inspection of the transition curves (namely critical lines splitting the various modes of operation of the machine) is carried out as the control parameters—noise, load and asymmetry between the two layer sizes—are tuned. In particular, with a finite asymmetry between the two layers, it is shown how the BAM can store information more efficiently than the Hopfield model by requiring less parameters to encode a fixed number of patterns. Comparisons are made with numerical simulations of neural dynamics. Finally, a low-load analysis is carried out to explain the retrieval mechanism in the BAM by analogy with two interacting Hopfield models. A potential equivalence with two coupled Restricted Boltmzann Machines is also discussed.
Wearable Sensor-Based Human Activity Recognition System Employing Bi-LSTM Algorithm
Authors: Tehrani Amir , Yadollahzadeh-Tabari Meisam , Zehtab-Salmasi Aidin , Enayatifar Rasul 
Published: April 2023

Abstract
Human activity recognition (HAR) systems employing wearable sensors are a promising area of research for tracking human activity. Recently, wearable devices such as smartwatches and sensors have been developed for activity recognition and monitoring. These systems aim to obtain the subject’s state within his or her environment by exploiting heterogeneous sensors attached to the body. With the development of deep learning, new strategies have emerged to facilitate and solve the HAR problems. In this work, a deep multilayer bidirectional long-short memory (Bi-LSTM) architecture has been implemented to detect human activities. Instead of training a single model as in traditional LSTM methods, two models are presented in the Bi-LSTM scheme, one for learning the input data sequence and the other for learning the reverse sequence. Finally, a new novel postprocessing approach has been proposed based on windowing and voting in the last step to improve the average F1 score. Comprehensive investigations on the three publicly available datasets consisting of a different set of activities were used to evaluate the performance of the proposed framework. The empirical results of this paper on AReM, Mhealth and PAMAP2 datasets attained 95.46, 95.79 and 93.41% average F1 score, respectively. The results also revealed that selecting the window size and implementing the appropriate voting method has a significant effect on improving the average percentage of the F1 score.
Corticotropin-releasing hormone neurons in the central nucleus of amygdala are required for chronic stress-induced hypertension
Authors: Sheng Zhao-Fu , Zhang Hua , Phaup Jeffery G , Zheng PeiRu , Kang XunLei , Liu Zhenguo , Chang Hui-Ming , Yeh Edward T H , Johnson Alan Kim , Pan Hui-Lin , Li De-Pei 
Published: April 2023

Abstract

Aims
Chronic stress is a well-known risk factor for the development of hypertension. However, the underlying mechanisms remain unclear. Corticotropin-releasing hormone (CRH) neurons in the central nucleus of the amygdala (CeA) are involved in the autonomic responses to chronic stress. Here, we determined the role of CeA-CRH neurons in chronic stress-induced hypertension.

Methods and results
Borderline hypertensive rats (BHRs) and Wistar-Kyoto (WKY) rats were subjected to chronic unpredictable stress (CUS). Firing activity and M-currents of CeA-CRH neurons were assessed, and a CRH-Cre-directed chemogenetic approach was used to suppress CeA-CRH neurons. CUS induced a sustained elevation of arterial blood pressure (ABP) and heart rate (HR) in BHRs, while in WKY rats, CUS-induced increases in ABP and HR quickly returned to baseline levels after CUS ended. CeA-CRH neurons displayed significantly higher firing activities in CUS-treated BHRs than unstressed BHRs. Selectively suppressing CeA-CRH neurons by chemogenetic approach attenuated CUS-induced hypertension and decreased elevated sympathetic outflow in CUS-treated BHRs. Also, CUS significantly decreased protein and mRNA levels of Kv7.2 and Kv7.3 channels in the CeA of BHRs. M-currents in CeA-CRH neurons were significantly decreased in CUS-treated BHRs compared with unstressed BHRs. Blocking Kv7 channel with its blocker XE-991 increased the excitability of CeA-CRH neurons in unstressed BHRs but not in CUS-treated BHRs. Microinjection of XE-991 into the CeA increased sympathetic outflow and ABP in unstressed BHRs but not in CUS-treated BHRs.

Conclusions
CeA-CRH neurons are required for chronic stress-induced sustained hypertension. The hyperactivity of CeA-CRH neurons may be due to impaired Kv7 channel activity, which represents a new mechanism involved in chronic stress-induced hypertension.
The clinical and biochemical significance of 11-oxygenated androgens in human health and disease
Authors: Storbeck Karl-Heinz , O’Reilly Michael W 
Published: April 2023

Abstract
For many decades, the prevailing paradigm in endocrinology was that testosterone and 5α-dihydrotestosterone are the only potent androgens in the context of human physiology. The more recent identification of adrenal derived 11-oxygenated androgens and particularly 11-ketotestosterone have challenged these established norms, prompting a revaluation of the androgen pool, particularly in women. Since being recognized as bone fide androgens in humans, numerous studies have focused their attention on understanding the role of 11-oxygenated androgens in human health and disease and have implicated them as role players in conditions such as castration resistant prostate cancer, congenital adrenal hyperplasia, polycystic ovary syndrome, Cushing's syndrome, and premature adrenarche. This review therefore provides an overview of our current knowledge on the biosynthesis and activity of 11-oxygenated androgens with a focus on their role in disease states. We also highlight important analytical considerations for measuring this unique class of steroid hormone.
New gene markers for classification and quantification ofFaecalibacteriumspp. in the human gut
Authors: Tanno Hiroki , Chatel Jean-Marc , Martin Rebeca , Mariat Denis , Sakamoto Mitsuo , Yamazaki Masao , Salminen Seppo , Gueimonde Miguel , Endo Akihito 
Published: April 2023

AbstractFaecalibacterium prausnitzii is a promising biomarker of a healthy human microbiota. However, previous studies reported the heterogeneity of this species and found the presence of several distinct groups at the species level among F. prausnitzii strains. Our recent study revealed that methods previously developed for quantification of F. prausnitzii were not specific to the species level because of the heterogeneity within the F. prausnitzii species and the application of 16S rRNA gene, which is an invalid genetic marker for the species. Therefore, previously available data failed to provide information on different groups, which limits our understanding of the importance of this organism for host health. Here, we propose an alternative gene marker for quantification of F. prausnitzii-related taxa. A total of nine group-specific primer pairs were designed by targeting rpoA gene sequences. The newly developed rpoA-based qPCR successfully quantified targeted groups. Application of the developed qPCR assay in six healthy adults revealed marked differences in abundance and prevalence among the different targeted groups in stool samples. The developed assay will facilitate detailed understanding of the impact of Faecalibacterium populations at the group level on human health and to understand the links between depletion of specific groups in Faecalibacterium and different human disorders.
What if State Logic Rests on Enslavement? Radical Alternatives in Laila Lalami’s The Moor’s Account
Authors: Mami Fouad 
Published: April 2023

Abstract
This article provides a detailed assessment of Laila Lalami’s novel The Moor’s Account (2014), in which a slave decides to escape upon becoming certain that his enslaver will never act on a prior understanding to free him. Still, his desertion carries with it the ultimate price: never seeing his home or country again. The article explores what that imaginative escape into the wilderness signifies in respect to statehood, both as an idea and as a practice. The evolving events of the novel suggest that polities create domestication not by accident, but by default. For, in Lalami’s novel, the state sells chimerical illusions to the aspiring bourgeoisie in the form of abstract debts, whose repayment fattens state coffers and enslaves the aspiring bourgeoisie. Such a stance vis-à-vis the state and its logic raises a concern with Lalami’s readership since the postcolonial arrangement rarely diverges, if at all, from this immanent logic, the one that hinges on the state’s tendential predilection for enslavement. Lalami’s readers are therefore invited to reconsider their bias against statelessness if circumventing slavery is indeed possible. The article sceptically considers whether, by pursuing such a radical approach, Lalami could be romanticizing statelessness as an easy means of circumventing postcoloniality. This essay will be engaging not only to literary scholars, but also to political economists, development planners, city designers and environmentalists.