bluuebunny/crossref_metadata_2025_split huggingface dataset:
Internet of things based automated monitoring for indoor aeroponic system
Authors: Roffi Teuku Muhammad , Jamhari Charisma Aulia 
Published: October 2022

On the ever-rising urgency of global food security, efforts are required to develop a robust farming technique. This includes the capability of farming in non-agricultural land or indoor spaces. Farming in the air medium, i.e., aeroponic, has persistently stepped in as a viable solution. Aeroponic farming allows efficient water usage while preventing soil related diseases and pests. With the assistance of light emitting diodes (LEDs) and precise electronic monitoring and control, aeroponic may become the suitable farming technique of the future. This work presents an aeroponic system capable of automated monitoring and control of farming parameters. The system achieved both robustness in indoor farming and remote access by employing LED as an artificial lighting system and the internet-of-things (IoT) connectivity, respectively. The test result demonstrated that the system successfully maintained the root chamber temperature below 30 °C with a typical average temperature of 28.8 °C. The system managed a humidity level which prevented plants from drying out. It was also evident that the LED assistance significantly improved the growth quality of <em>Ipomea reptans</em>. The system, data, and analysis presented in this work is expected to facilitate further development of a robust food production system in overcoming the global food crisis.
A comparative analysis of chronic obstructive pulmonary disease using machine learning, and deep learning
Authors: Ramalingam Ramadoss , Chinnaiyan Vimala 
Published: October 2022

<span lang="EN-US">Chronic obstructive pulmonary disease (COPD) is a general clinical issue in numerous countries considered the fifth reason for inability and the third reason for mortality on a global scale within 2021. From recent reviews, a deep convolutional neural network (CNN) is used in the primary analysis of the deadly COPD, which uses the computed tomography (CT) images procured from the deep learning tools. Detection and analysis of COPD using several image processing techniques, deep learning models, and machine learning models are notable contributions to this review. This research aims to cover the detailed findings on pulmonary diseases or lung diseases, their causes, and symptoms, which will help treat infections with high performance and a swift response. The articles selected have more than 80% accuracy and are tabulated and analyzed for sensitivity, specificity, and area under the curve (AUC) using different methodologies. This research focuses on the various tools and techniques used in COPD analysis and eventually provides an overview of COPD with coronavirus disease 2019 (COVID-19) symptoms. </span>
Fitness function X-means for prolonging wireless sensor networks lifetime
Authors: Radwan Abdelrahman , Abdellatif Nasser , Radwan Eyad , Akhozahieh Maryam 
Published: October 2022

<span lang="EN-US">X-means and k-means are clustering algorithms proposed as a solution for prolonging wireless sensor networks (WSN) lifetime. In general, X-means overcomes k-means limitations such as predetermined number of clusters. The main concept of X-means is to create a network with basic clusters called parents and then generate (</span><em><span lang="EN-US">j</span></em><span lang="EN-US">) number of children clusters by parents splitting. X-means did not provide any criteria for splitting parent’s clusters, nor does it provide a method to determine the acceptable number of children. This article proposes fitness function X-means (FFX-means) as an enhancement of X-means; FFX-means has a new method that determines if the parent clusters are worth splitting or not based on predefined network criteria, and later on it determines the number of children. Furthermore, FFX-means proposes a new cluster-heads selection method, where the cluster-head is selected based on the remaining energy of the node and the intra-cluster distance. The simulation results show that FFX-means extend network lifetime by 11.5% over X-means and 75.34% over k-means. Furthermore, the results show that FFX-means balance the node’s energy consumption, and nearly all nodes depleted their energy within an acceptable range of simulation rounds. </span>
Machine learning for prediction models to mitigate the voltage deviation in photovoltaic-rich distributed network
Authors: Baniyounis Mohammed , Salah Samer Z. , Ghaeb Jasim A. 
Published: October 2022

<span lang="EN-US">The voltage deviation is one of the most crucial power quality issues that occur in electrical power systems. Renewable energy plays a vital role in electrical distribution networks due to the high economic returns. However, the presence of photovoltaic systems changes the nature of the energy flow in the grid and causes many problems such as voltage deviation. In this work, several predictive models are examined for voltage regulation in the Jordanian Sabha distribution network equipped with photovoltaic farms. The augmented grey wolf optimizer is used to train the different predictive models. To evaluate the performance of models, a value of one for regression factor and a low value for root mean square error, mean square error, and mean absolute error are used as standards. In addition, a comparison between nineteen predictive models has been made. The results have proved the capability of linear regression and the gaussian process to restore the bus voltages in the distribution network accurately and quickly and to solve the shortening in the voltage dynamic response caused by the iterative nature of the heuristic algorithm. </span>
Internet of things applications using Raspberry-Pi: a survey
Authors: M. Hosny Khalid , Magdi Amal , Salah Ahmad , El-Komy Osama , Lashin Nabil A. 
Published: October 2022

<span lang="EN-US">The internet of things (IoT) is the communication of everything with anything else, with the primary goal of data transfer over a network. Raspberry Pi, a low-cost computer device with minimal energy consumption is employed in IoT applications designed to accomplish many of the same tasks as a normal desktop computer. Raspberry Pi is a quad-core computer with parallel processing capabilities that may be used to speed up computations and processes. The Raspberry Pi is an extremely useful and promising technology that offers portability, parallelism, low cost, and low power consumption, making it ideal for IoT applications. In this article, the authors provide an overview of IoT and Raspberry Pi and research on IoT applications using Raspberry Pi in various fields, including transportation, agriculture, and medicine. This article will outline the details of several research publications on Raspberry Pi-based IoT applications.</span>
Large-Scale Algorithmic Search Identifies Stiff and Sloppy Dimensions in Synaptic Architectures Consistent With Murine Neocortical Wiring
Authors: Jabri Tarek , MacLean Jason N. 
Published: October 2022

Abstract
Complex systems can be defined by “sloppy” dimensions, meaning that their behavior is unmodified by large changes to specific parameter combinations, and “stiff” dimensions, whose change results in considerable behavioral modification. In the neocortex, sloppiness in synaptic architectures would be crucial to allow for the maintenance of asynchronous irregular spiking dynamics with low firing rates despite a diversity of inputs, states, and short- and long-term plasticity. Using simulations on neural networks with first-order spiking statistics matched to firing in murine visual cortex while varying connectivity parameters, we determined the stiff and sloppy parameters of synaptic architectures across three classes of input (brief, continuous, and cyclical). Algorithmically generated connectivity parameter values drawn from a large portion of the parameter space reveal that specific combinations of excitatory and inhibitory connectivity are stiff and that all other architectural details are sloppy. Stiff dimensions are consistent across input classes with self-sustaining synaptic architectures following brief input occupying a smaller subspace as compared to the other input classes. Experimentally estimated connectivity probabilities from mouse visual cortex are consistent with the connectivity correlations found and fall in the same region of the parameter space as architectures identified algorithmically. This suggests that simple statistical descriptions of spiking dynamics are a sufficient and parsimonious description of neocortical activity when examining structure-function relationships at the mesoscopic scale. Additionally, coarse graining cell types does not prevent the generation of accurate, informative, and interpretable models underlying simple spiking activity. This unbiased investigation provides further evidence of the importance of the interrelationship of excitatory and inhibitory connectivity to establish and maintain stable spiking dynamical regimes in the neocortex.
Bisected graph matching improves automated pairing of bilaterally homologous neurons from connectomes
Authors: Pedigo Benjamin D. , Winding Michael , Priebe Carey E. , Vogelstein Joshua T. 
Published: October 2022

AbstractGraph matching algorithms attempt to find the best correspondence between the nodes of two networks. These techniques have been used to match individual neurons in nanoscale connectomes—in particular, to find pairings of neurons across hemispheres. However, since graph matching techniques deal with two isolated networks, they have only utilized the ipsilateral (same hemisphere) subgraphs when performing the matching. Here, we present a modification to a state-of-the-art graph matching algorithm that allows it to solve what we call the bisected graph matching problem. This modification allows us to leverage the connections between the brain hemispheres when predicting neuron pairs. Via simulations and experiments on real connectome datasets, we show that this approach improves matching accuracy when sufficient edge correlation is present between the contralateral (between hemisphere) subgraphs. We also show how matching accuracy can be further improved by combining our approach with previously proposed extensions to graph matching, which utilize edge types and previously known neuron pairings. We expect that our proposed method will improve future endeavors to accurately match neurons across hemispheres in connectomes, and be useful in other applications where the bisected graph matching problem arises.
Clinical Application of Submental Island Flaps in Repair and Reconstruction of Head and Neck Tumors: Retrospective Review of a Single-Center Experience
Authors: Li Pingdong , Li Haiyang , Ding Shuo , Zhou Jing , Chen Xiaohong , Fang Jugao , Huang Zhigang 
Published: October 2022

Background Based on our cadaveric study findings and the clinical practice, the improved submental island flaps (SIF) used on a case series to reconstruct postoperative defects were reviewed and analyzed, to summarize the technical operation of flap cutting and propose the anterograde anatomical technique of point-line-plane alignment. Methods The cadaveric study was carried out first and a case series of about 23 head and neck tumor cases that underwent one-stage SIF repair were reviewed and followed up. The intraoperative anatomy, the technical essentials for vascular pedicle protection and submandibular lymph nodes treatment, and the rational design of flap incisions were analyzed and described. Results Most patients (21/23, 91.3%), comprising 19 males and 4 females with a mean age of 59 years, recovered completely from the application of SIFs in the repair and reconstruction of head and neck tumors; Only 2 patients experienced partial flap necrosis, which resolved following a local dressing change. The predominant donor site complication was transitory paralysis of the mandibular marginal branch of the facial nerve (MMBFN) (3/23, 13.0%), and the donor site was closed in one stage without skin grafting. The hair growth on skin flaps was not an issue for male patients requiring postoperative radiotherapy. Conclusions SIF is a viable choice for correcting abnormalities of the head and neck tumor with the convenience of flap cutting and the effectiveness of the repair. In addition, it permits simultaneous treatment of the lymph nodes in the region I.
Randomized Clinical and Biochemical Study Comparing the Effect of L-arginine and Sildenafil in Beta Thalassemia Major Children With High Tricuspid Regurgitant Jet Velocity
Authors: El-Khateeb Eman , El-Haggar Sahar Mohamed , El-Razaky Osama , El-Shanshory Mohamed Ramadan , Mostafa Tarek Mohamed 
Published: October 2022

Background: Pulmonary hypertension (PHT) is common in β-thalassemia patients due to hemolysis, iron overload and diminished nitric oxide (NO) levels. Biochemical markers can help to understand the pathophysiology and to introduce new therapies for this condition. Aim: This study aimed to evaluate the effectiveness of L-arginine and sildenafil in thalassemia children with PHT at both clinical and biochemical levels. Methods and Results: In a randomized controlled study, 60 β-thalassemia major children with PHT were divided into 3 equal groups; Control group (Conventional thalassemia and PHT management), L-arginine group (Conventional + Oral L-arginine 0.1 mg.kg−1 daily), and sildenafil group (Conventional + Oral sildenafil 0.25 mg.kg−1 two times a day) for 60 days. Tricuspid Regurgitant Jet Velocity (TRJV) with Doppler echocardiography along with serum levels of NO, asymmetric dimethylarginine (ADMA), interleukin 1-beta (IL-1β), E-selectin, and visfatin were followed-up at baseline, 30, and 60 days after treatment. Both drugs reduced the TRJV significantly. NO was significantly higher in both L-arginine and sildenafil groups after 60 days compared to baseline, while visfatin levels were lower. Only L-arginine reduced ADMA levels compared to baseline, while sildenafil did not. E-selectin and IL-1β levels did not change remarkably by both drugs. NO and TRJV showed significant negative correlations in both treatment groups. Conclusion: L-arginine and sildenafil could clinically ameliorate chronic PHT whereas, L-arginine showed superiority to sildenafil on some biochemical markers.
Genetic Variation, Stress, and Physiological Stress Response in Adults With Food Allergy or Celiac Disease
Authors: Ersig Anne L. , Young Erin E. , Brown Roger L. , Malecki Kristen 
Published: October 2022

Background Persistently high chronic stress can lead to maladaptive psychological, behavioral, and physiological stress responses and poor mental and physical health, highlighting the importance of identifying individuals at increased risk. Chronic health condition diagnosis and genetics are 2 characteristics that can influence stress, stress response, and health outcomes. Purpose Food allergy (FA) and celiac disease (CD) require constant vigilance in daily life and can lead to increased stress. The purpose of this exploratory analysis was to examine the association of variants in selected stress-related genes with stress exposures, stress, clinical measures of physiological stress response, and mental health symptoms in adults with and without FA or CD. Methods We compared stress exposures, symptoms of PTSD, depression, anxiety, and stress, BMI, and waist-hip ratio between cases and controls. We analyzed the association of SNPs in genes with known or hypothesized associations with stress-related measures in 124 cases and 124 matched controls: CRHBP (rs7718461, rs10474485), CRHR1 (rs242940) and OXTR (rs2268490). For this exploratory study, p-values ≤ 0.10 were considered suggestive. Results For cases and controls, rs7718461 was associated with stress symptoms, rs2268490 with symptoms of stress and PTSD, and rs242940 with symptoms of stress, PTSD, anxiety, and depression. Further analyses found that stress-related outcomes in individuals with FA or CD may be influenced by SNP genotype. Conclusions Given these suggestive findings, larger prospective studies should examine similar relationships in individuals with other chronic health conditions, incorporating factors such as environmental exposures, individual experiences, and epigenetic modifications.
Spontaneous brachial artery pseudoaneurysm secondary to vasculitis
Authors: Fadoul Mikael A , Tjaden Bruce , Daneshpooy Saba , McMackin Katherine 
Published: October 2022

Background Avoiding operative intervention during the active phase of vasculitis is a central tenant of management of this pathology. For unusual presentations of vascular disease, the early diagnosis of vasculitis is imperative to guide treatment. Methods We present the case of a 68-year-old female who presented with a spontaneous brachial artery pseudoaneurysm and was found to have granulomatosis with polyangiitis. Results and conclusion The management of arterial complications of vasculitis are particularly difficult in the active phase of disease. Our patient had successful resolution of her pseudoaneurysm with ultrasound compression, avoiding open or endovascular intervention during the active phase of disease.
On Variability in Physical Properties of Molded, Expanded Polystyrene
Authors: Bomberg Mark , Kumaran Kumar , Swinton Michael 
Published: October 2022

When computer models are used for predicting field performance of moist insulation products, we must learn how to quantify the variability in measured properties. This is an issue of adequate material characterization. A description by the EPS type is not sufficient. By using additional elements of material characterization such as specimen density, one improves the precision of measurements of physical properties. In the case of thermal properties, a second element of material characterization, namely the coefficient describing attenuation of thermal radiation in the material (specific extinction coefficient) is also needed. In effect, variation in thermal properties of EPS products is fully accounted for when defining only a few parameters such as bulk density, specific extinction coefficient, and thickness and temperature of the specimen.
Effect of Structural Anisotropy on Thermal Ageing in Rigid PU Foams
Authors: Boscoletto A. Boscolo , Cellarosi B. 
Published: October 2022

The use of blowing agents as an alternative to conventional chloro-fluorocarbons (CFCs) and the quality of foaming process can lead to non-homogeneity of the foam structure with the presence of defects along the panel thickness. These defects appear as holes in cell windows or cavities. Accurate measurements of thermal conductivity were made on test specimens having different thicknesses obtained by cutting away the external faces of the panels. This type of characterization of foams blown with alternative blowing agents allowed us to understand their ageing behaviour (natural and accelerated) and the problems related to the scaling factor. Moreover this study pointed out how the effective diffusion coefficients of gases involved in the ageing process can have different values along the thickness of a sample. All these observations were related with morphological analyses. Our studies showed that sampling procedure and model design are very important for a correct analysis of ageing phenomena. Good agreement between experimental and theoretical data was found, allowing us to verify the validity of the method used to characterize non-homogeneous foams.
Endometriosis prevalence and incidence trends in a large population-based study in Catalonia (Spain) from 2009 to 2018
Authors: Medina-Perucha Laura , Pistillo Andrea , Raventós Berta , Jacques-Aviñó Constanza , Munrós-Feliu Jordina , Martínez-Bueno Cristina , Valls-Llobet Carme , Carmona Francisco , López-Jiménez Tomàs , Pujolar-Díaz Georgina , Flo Arcas Eva , Berenguera Anna , Duarte-Salles Talita 
Published: October 2022

Objective: Endometriosis greatly impacts women’s health and quality of life. However, research on the prevalence and incidence of endometriosis remains inconclusive. This study assesses time trends in the prevalence and incidence of endometriosis diagnoses in Catalonia (Spain) from 2009 to 2018, considering differences by age and socioeconomic status. Methods: Population-based cohort study using data from the Information System for Research in Primary Care (SIDIAP) database. Data were included from over 2.4 million women aged 15–55 years between 1 January 2006 and 31 December 2018. Results: A total of 2,337,717 women were selected as the incident population; 0.7% had an endometriosis diagnosis. Median (interquartile range) age at diagnosis was 37 (32–43) years. Most women were European (92.3%) and lived in urban areas (73.6%). Overall prevalence of endometriosis consistently increased during the 2009–2018 period, and it was 1.24% in 2018. Trends were the highest for women with less socioeconomic deprivation and for the 35–44 years age group. Median incidence rates were 94.9 (92.6–102.9) per 100,000 women-years, being the highest in women aged 35–44 years throughout the whole study period. Overall, incidence increased between 2015 and 2017, and plateaued or decreased in 2018. Incidence rates in women from the most deprived and rural areas were lower, although incidence time trends by socioeconomic status were unclear. Conclusion: Healthcare services and public health strategies need to be strengthened to ensure timely endometriosis diagnosis and treatment. Special attention should be given to the most affected populations and the social inequities of health.
Accuracy of an Off-Label Transmitter and Data Manager Paired With an Intermittent Scanned Continuous Glucose Monitor in Adults With Type 1 Diabetes
Authors: Villa-Tamayo María F. , Builes-Montaño Carlos E. , Ramirez-Rincón Alex , Carvajal Javier , Rivadeneira Pablo S. 
Published: October 2022

Background: This work evaluates the accuracy and agreement between the FreeStyle Libre sensor (FSL) and an off-label converted real-time continuous glucose monitor (c-rtCGM) device consisting of the MiaoMiao transmitter and the xDrip+ application which can be coupled to the FSL. Methods: Four weeks of glucose data were collected from 21 participants with type 1 diabetes using the c-rtCGM and FSL: two weeks with a single initial calibration (uncalibrated) and two weeks with a daily calibration (calibrated). Accuracy and agreement evaluation included mean absolute relative difference (MARD), the %20/20 rule, Bland-Altman plots, and the Consensus Error Grid analysis. Results: Values reported by the c-rtCGM system compared with the FSL resulted in an overall MARD of 12.06% and 84.71% of the results falling within Consensus Error Grid Zone A when the device is calibrated. For uncalibrated devices, an overall MARD of 17.49% was obtained. Decreased accuracy was shown in the hypoglycemic range and for rates of change greater than 2 mg/dL/min. The between-device bias also incremented with increasing glucose values. Conclusion: Measurements recorded by the c-rtCGM were found to be accurate when compared with FSL data only when performing daily c-rtCGM device calibrations. High drops in accuracy and agreement between devices occurred when the c-rtCGM was not calibrated.