bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing Energy Consumption in Smart Homes Using Machine Learning Techniques
Authors: Kumar Neeraj , Sundaram Kalyana , R. Reena , S. Madhumathi
Published: May 2023

The increasing demand for energy utilization in smart homes has led to the exploration of machine learning techniques as a means to optimize energy consumption. This review paper explores the merits and demerits of using machine learning techniques for energy optimization in smart homes. Smart homes are becoming increasingly popular due to the potential benefits they offer, including increased energy efficiency, improved comfort, and enhanced security. However, to achieve these benefits, it is essential to optimize the energy utilization in smart homes. This paper presents machine learning techniques that have been used to optimize energy utilization in smart homes. In this paper proposed the using Stochastic Gradient Descent (SGD) algorithm for optimizing energy utilization in smart homes. However, challenges such as data privacy, accuracy of data collection, and cost may hinder the full adoption of these techniques.
A Review on Infilled frame Structure with respective of various Interface Materials
Authors: Dhinakaran S. , Muthukumar S.
Published: May 2023

During major earthquakes, existing buildings have collapsed or suffered serious damage, resulting in number of losses, severe injuries, and deaths. Based on literature, the influence of this work reviewed the effects of interface with different materials and also to find how infilled frames behave in framed structure. This study's primary goal is to strengthen RC-framed structures and increase the ductility of infilled frames by using interface materials. The research offers a full range and points relevant to ductile parameters for more results in the field of infilled frames using interface materials. In parametric investigation the interface material with interface thickness and the combination of interface material with a particular frame, from that optimum value to be identified. This research benefits researchers, professionals, and specialists the behaviour of various structural systems, as well as innovative mitigation techniques that have been used in the literature to build progressive collapse resistance experimentally.
A Study on non Destructive Tests and Flexural Strengths of Geopolymer Concrete Using Combination of Different Fine Aggregates
Authors: Indhumathi M. , Ragavan V. , Dhanalakshmi A. , Iydia D. Darling Helen
Published: May 2023

Geopolymer concrete is a new technology that deserves more attention in the rapidly evolving sustainable construction industry. Furthermore, to avoid the depletion of natural resources, by-product waste management technologies are essential. Today, river sand is in short supply. DMS (Dredged Marine Sand), on the other hand, which faces disposal and land acquisition issues, proves to be a viable alternative to river sand. In this paper, a mixture of M-Sand and DMS was used in place of river sand, and non-destructive, Flexural strength of beam by monotonic loading and cyclic loadings were investigated. The findings indicated that DMS has attained flexural characteristics and with regard to cracks, very minor and vertical cracks are observed in all beams as in the case of monotonic loading. Further, they originate from the tension zone
Intelligent Control System for Wind Turbine Farms Using IoT and Machine Learning
Authors: S. Radhakrishnan , M. Jasmin , K.K. Senthilkumar , M. Vanitha
Published: May 2023

The development of renewable energy sources is becoming increasingly important due to the depletion of traditional energy sources and the negative environmental impact caused by their use. Wind energyis one of the most promising renewable energy sources, withwind turbine farmsbeingestablishedacross the world. However, the operation and maintenance of wind turbine farms pose significant challenges due to the unpredictable nature of wind and the complex inter relationships between the turbines in the farm. To address these challenges, an intelligent control system that Smart Wind technologies has been proposed. The system utilizes a network of sensors and IoT devices to collect real-time data on wind speed, temperature, humidity, and other relevant parameters.
Assessment of Non-Motorized Transportation on Education Zone in Rajapalayam Town
Authors: Maniarasu P.R. , Vinesh R.
Published: May 2023

Today, transportation systems in most cities are no longer sustainable due to carbon emissions into the atmosphere contribute to environmental pollution in terms of quality deficiencies that affects mobility of life in general. The characteristics of sustainable transport are safe, comfortable and efficient in terms of economic and energy consumption and minimize environmental pollution. Non-motorized is vital for sustainable living since it is a green transport of zero emission concept that prioritizes planning, operations and maintenance for walking and cycling over automobiles. This study aims to assess the sustainable transport in terms of non-motor vehicles as per non-motorizedtransport Guidance document published by Ministry Urban Development Government of India in one of the educational zones falls along PAC Ramasamy Raja Salai in Rajapalayam town. We have categorized mode shareusing midblock traffic volume count and derived longitudinal section of that feeder road using road inventory investigation. The characteristics non-motorized transport falls in our study area has gained through questionnaire from user’s feedback. Cyclist along around 900pcu have been moving in our study area during week days. Our sample survey reflects around 50 percentage of our ers had exposed accidents. Based on our preliminary step of assessment in non-motorized transport planning, subsequent process like plan, design and implementation will carry out to attain desired non-motorized goals.
AI based pest detection and alert system for farmers using IoT
Authors: Sargunar Thomas Jaya Christa , Manikandarajan Suhidhana , Kamalakkannan Subha Tinaga
Published: May 2023

Agriculture plays an important role in economy and it is the backbone of the economic system for developing countries. India is one of the key players in agricultural precinct worldwide. Although there are many sophisticated technologies in the field of agriculture, still there is no proper technology to control the problems related to pests. Disinclination to pesticides for controlling agricultural pests is a worldwide problem. To overcome this particular problem, an AI based pest detection model is designed. The purpose of this model is to further illustrate, through classification using an artificial neural network, the effectiveness of acoustic approaches in pest detection. Numerous types of research have demonstrated the viability of acoustic technologies for insect detection and monitoring using different sound parameterization and classification methods. IR sensors and sound sensor are employed to identify the presence of insects. Deep learning technique is used to analyse and categorize the audio signal with the help of AI model to detect the type of pest. This model not only aims on detecting the pest but also alerting the farmers by notifying through their mobile phones with the help of Wi-Fi module and IoT.
Divided Square Difference Cordial Labeling Of Join Some Spider graphs
Authors: Christy T. , Palani G.
Published: May 2023

Let G be a graph with itsvertices and edges. On defining bijective fnnctionρ:V(G) →{0,1,…,p}. For each edge assign the label with 1 if ρ*(ab)=∣ρ(a)2 - ρ(b)2 / ρ(a) - ρ(b)∣ is odd or 0 otherwise such that |eρ(1) -eρ0≤1 then the labeling is called as divided square difference cordial labeling graph. We prove in this paper for relatively possible set of spider graphs with atmost one legs greaterthan one namely J(SP(1m,2n)),J(SP(1m,2n,31)), (SP(1m,2n,32)),J(SP(1m,2n,41)),J(SP(1m,2n,51).
A Survey on Different Algorithms Used in Deep Learning Process
Authors: Chelladurai Kadarkarai , Sujatha Natarajan
Published: May 2023

Deep Learning is a significant tool that communicates with the computer to perform task as a natural human being. Deep learning algorithms exhibits a vital role in defining the features and can assist the large number of processes for the data which are structured or unstructured. In recent years, this concept is receiving quite a lot attention for its exceeding achievements in human-level performance. In deep learning, systematic and rapid development of diverse lifestyle, including marketing, policing, finance, manufacturing and education modeling which creates pioneering technologies such as autonomous systems. Deep learning being a subset of machine learning is tackling problems with advanced features. Deep Learning is basically a neural network with processing units consisting of multiple layers with which it has efficaciously applicable to a wide set of problems in the areas such as image processing, image recognition and natural language processing. This paper gives a brief review on the different approaches, algorithms used in deep learning techniques from the beginning to the present scenario. The main aim of this study is to reveal the advantages features of the handsome approaches utilized in the deep learning process. Deep learning methods are contributing a diversity of assistances not only to online learners but also to institutions that advance in current eLearning platforms. This survey will afford an overview of the key ideas on the concept, approaches, advantages and impact of deep learning in the area of research.
A Comparative Study of Renewable Energy Sources for Power Generation in Rural Areas
Authors: R. Ranganathan , S. Subbaram , G. Indira , N. Arul Arasi , S. Tharmar
Published: May 2023

In recent years, the demand for reliable and sustainable power generation in rural areas has increased due to the lack of access to traditional power grids and the need to reduce reliance on fossil fuels. Renewable energy sources such as solar, wind, and biomass have emerged as viable options for meeting the energy needs of rural communities. This paper proposes a Multi-Criteria Decision Analysis (MCDA) framework for comparing different renewable energy sources for power generation in rural areas. The MCDA framework takes into account multiple criteria such as economic feasibility, environmental impact, and technical feasibility to provide a comprehensive analysis of the different renewable energy sources. The proposed MCDA framework is applied to compare four renewable energy sources: solar power, wind power, hydro power, and biomass power. The results of the MCDA analysis are presented and discussed, and recommendations are provided for the selection of the most suitable renewable energy source for power generation in rural areas.
Ein kurzer Fallbericht zu einem kleinen Mittel:
Ohrläppchenentzündung nach Ohrlochstechen
Authors: Meisl Burgi
Published: May 2023

Bei dem Artikel handelt es sich um einen kurzen Fallbericht zu einem selten
verschriebenen Mittel. Die ungewöhnliche Lokalisation sowie ein
auffälliges Gemütssymptom haben zur Verschreibung
geführt.
Okoubaka aubrevillei – eine Heilpflanze aus der
traditionellen westafrikanischen Medizin und ihr Weg in die
Homöopathie
Authors: Buchheim-Schmidt Susann
Published: May 2023

Im vorliegenden Beitrag wird die Entwicklung des Arzneimittels Okoubaka
aubrevillei, das aus der westafrikanischen Ethnomedizin stammt und sich in der
Homöopathie insbesondere bei Magen-Darm-Erkrankungen bewährt
hat, aufgezeigt. Hierbei werden die Informationen zu Okoubaka in Bezug auf die 3
Säulen eines homöopathischen Arzneimittelbildes dargestellt.
Diskutiert wird auch, inwieweit eine phytotherapeutische Wirkung über
den Gerbstoffanteil der Rinde in homöopathischen Zubereitungen von
Tiefpotenzen noch möglich ist.

Eine bewährte Indikation ist die Prophylaxe von Reisedurchfällen.
Diese wird mit Okoubaka in tiefen D-Potenzen (z. B. in D3) schon einige Tage vor
Beginn der Reise empfohlen. In dem Zusammenhang werden im zweiten Teil des
Beitrags die Ergebnisse einer In-vitro-Untersuchung mit homöopathischen
Zubereitungen aus Okoubaka in einem Gastrointestinalsimulator vom SHIME-Typ
vorgestellt, die eine prophylaktische Einnahme vor einer Reise und
anschließende Konfrontation mit 2 typischen Erregern von
Reisediarrhöen simuliert.
Der Stellenwert des Feedbacks beim Proctoring in der robotergestützten Chirurgie – ein Grundstein des Erfolgskonzeptes?
Authors: Alkatout Ibrahim , Maass Nicolai , Günther Veronika
Published: May 2023

Roboterassistierte Operationsmethoden stellen eine Weiterentwicklung und Ergänzung der konventionellen Laparoskopie dar. Somit ist eine entsprechende Ausbildung der Chirurgen in diesem
Fachgebiet unabdingbar. Gerade für die Anfangsphase eignen sich Simulationsprogramme – ähnlich wie in der Aviatik – hervorragend, um an das technisch herausfordernde Operationsverfahren
heranzuführen. Im weiteren Verlauf, aber noch zu Beginn der Lernkurve, hat sich das Proctoring bewährt, um den zu trainierenden Chirurgen vor Ort zu begleiten, individuell zu schulen und an
komplexere Fälle heranzuführen. Ein wesentlicher Baustein erfolgreicher Trainingskonzepte stellt das Feedback dar: Mit etwas zeitlichem Abstand und schriftlich fixiert erhält der zu
schulende Chirurg eine Zusammenfassung bzw. einen Leitfaden, der sowohl die bestehende Situation als auch Verbesserungsvorschläge und das Zukunftspotenzial darlegt. Die Umsetzung eines
solchen Feedbacks ermöglicht es dem Chirurgen, zusätzlich zur Anzahl an absolvierten Fällen, seine Selbsteinschätzung zu relativieren und Entwicklungsziele anzupassen. Somit stellt das
Feedback die entscheidende Schnittstelle zwischen dem Beginn einer Lernkurve und fortgeschrittenen operativen Fähigkeiten inklusive der Möglichkeit einer realistischen Selbsteinschätzung
dar.
Acylation of Electron-Poor Alkenyl Sulfoxides: Diverse Transformations for the Synthesis of Polysubstituted Phenols and Functionalized Carbocycles
Authors: Xie Yuanyuan , Zhou Hongwei , Li Xiaoyu , Zhang Qianyun
Published: May 2023

A protocol with available starting materials and mild conditions was developed for the synthesis of polysubstituted phenols and functionalized carbocycles via acylation of electron-poor alkenyl sulfoxides. The plausible mechanism was investigated.
Initial experience of transpapillary gallbladder biopsy using newly designed device delivery system
Authors: Yane Kei , Tomita Yusuke , Yoshida Masahiro , Sasaki Kou , Imagawa Takayuki , Morita Kotaro , Ihara Hideyuki , Minagawa Takeyoshi , Okagawa Yutaka , Hirayama Michiaki , Sumiyoshi Tetsuya , Kondo Hitoshi
Published: May 2023

Transpapillary gallbladder biopsy has been reported for the diagnosis of gallbladder disease, and this procedure requires special biopsy forceps or a large-diameter pusher catheter. We retrospectively examined consecutive patients who underwent transpapillary gallbladder biopsy using a newly designed device delivery system (Endosheather; Piolax Medical Device, Kanagawa, Japan). We evaluated 11 patients (median age, 71 years [28–85]) who underwent transpapillary gallbladder biopsy from June 2021 to July 2022. The selective gallbladder cannulation and delivery system insertion success rate was 90.9% (10/11). The target lesion biopsy success rate was 63.6% (7/11). The biopsy time (i.e., time to completion of biopsy after successful guidewire placement) was 8.7 (5.4–32.7) min. In 1 patient in whom all 6 gallbladder bile juice cytology results were benign, the biopsy result was suspicious of adenocarcinoma. The final diagnosis for this patient was gallbladder cancer. Adverse events occurred in 2 patients. In 1 patient, acute cholecystitis occurred and required emergency surgery. Transpapillary gallbladder biopsy using the Endosheather is a potential option for the diagnosis of gallbladder disease. A good indication for this technique is considered to be wall thickening at the gallbladder fundus, where it is difficult to differentiate between benign and malignant lesions by imaging modalities such as ultrasonography or endoscopic ultrasound. The addition of transpapillary gallbladder biopsy may be advantageous when performing bile juice cytology using a nasogallbladder drainage tube for the diagnosis of gallbladder disease.
Machine learning-enabled graphene-based electronic olfaction sensors and their olfactory performance assessment
Authors: Huang Shirong , Croy Alexander , Bierling Antonie Louise , Khavrus Vyacheslav , Panes-Ruiz Luis Antonio , Dianat Arezoo , Ibarlucea Bergoi , Cuniberti Gianaurelio
Published: May 2023

Olfaction is an evolutionary old sensory system, which provides sophisticated access to information about our surroundings. In particular, detecting the volatile organic compounds (VOCs) emitted during natural and artificial processes can be used as characteristic fingerprints and help to identify their source. Inspired by the biological example, artificial olfaction aims at achieving similar performance and thus digitizing the sense of smell. Here, we present the development of machine learning-enabled graphene-based electronic olfaction sensors and propose an approach to assess their olfactory performance toward VOCs. Eleven transient kinetic features extracted from the sensing response profile are utilized as their fingerprint information. By mimicking the Sniffin' Sticks test, electronic olfaction sensors exhibit high olfactory performance toward four VOC odors (clove, eucalyptus, lemon, and rose scent) in terms of odor detection threshold, odor discrimination, and identification performance. Upon exposure to binary odor mixtures, response features of electronic olfaction sensors behave more similarly to that of an individual odor, with a tendency that correlates with their ratio, resembling the overshadowing effect in human olfactory perception. Molecular dynamics simulations and density functional theory calculations results reveal competing adsorption mechanisms between odorant molecules and sensing materials. This may facilitate electronic olfaction sensor applications in some emerging fields, such as environmental monitoring or public security.
Performance and emission characteristics of CI engine using hydrogen enrichment in biodiesel blend with additives—A review
Authors: Mehra Deepalika , Kumar Vijay , Choudhary Akhilesh Kumar , Awasthi Mamta
Published: May 2023

It is an irresistible argument that there is a requirement for sustainable resources for energy production as there is an enormous rise in demand for energy. Various sectors involve a wide range of energy consumption shares. Conventional fuels are exhaustible and can be replaced with sustainable substitutes, i.e., biofuels including bio-ethanol, biogas, and biodiesel. Recently, biodiesel has gained popularity due to the availability and affordability of feedstock. To extract biodiesel from vegetable oils, the transesterification process is widely used. Biodiesel blends can be used as a direct substitute in diesel engines, which may result in a slight reduction in hydrocarbons, carbon monoxide, and an increase in oxides of nitrogen. The performance parameters may increase or decrease depending on the blend type and calorific value. The objective of this review is to analyze the performance and emission characteristics of second and third-generation biodiesel blends enriched with hydrogen and to explore techniques for improvement such as the addition of additives. Research has shown that the addition of hydrogen improves combustion, resulting in increased brake thermal efficiency and reduced brake specific fuel consumption. Similarly, the inclusion of additives can reduce the production of oxides of nitrogen during combustion. In conclusion, biodiesel blends enriched with hydrogen and additives can offer improved performance, combustion, and emission characteristics. To meet energy demand sustainably and reduce reliance on conventional fuels, further research is necessary to ensure the long-term viability of biodiesel as a sustainable energy source.
Brillouin and Kerr nonlinearities of a low-index silicon oxynitride platform
Authors: Ye Kaixuan , Klaver Yvan , Jimenez Gordillo Oscar A. , Botter Roel , Daulay Okky , Morichetti Francesco , Melloni Andrea , Marpaung David
Published: May 2023

Nonlinear optical effects including stimulated Brillouin scattering (SBS) and four-wave mixing (FWM) play an important role in microwave photonics, optical frequency combs, and quantum photonics. Harnessing SBS and FWM in a low-loss and versatile integrated platform would open the path to build large-scale Brillouin/Kerr-based photonic integrated circuits. In this letter, we investigate the Brillouin and Kerr properties of a low-index (n = 1.513 @ 1550 nm) silicon oxynitride (SiON) platform. We observed, for the first time, backward Brillouin scattering in SiON waveguides with a Brillouin gain coefficient of 0.3 m−1 W−1, which can potentially be increased to 0.95 m−1 W−1 by just tailoring the waveguide cross section. We also performed FWM experiments in SiON rings and obtained the nonlinear parameter γ of 0.02 m−1 W−1. Our results point to a low-loss and low-index photonic integrated platform that is both Brillouin and Kerr active.
A deep encoder–decoder framework for identifying distinct ligand binding pathways
Authors: Bandyopadhyay Satyabrata , Mondal Jagannath
Published: May 2023

The pathway(s) that a ligand would adopt en route to its trajectory to the native pocket of the receptor protein act as a key determinant of its biological activity. While Molecular Dynamics (MD) simulations have emerged as the method of choice for modeling protein-ligand binding events, the high dimensional nature of the MD-derived trajectories often remains a barrier in the statistical elucidation of distinct ligand binding pathways due to the stochasticity inherent in the ligand’s fluctuation in the solution and around the receptor. Here, we demonstrate that an autoencoder based deep neural network, trained using an objective input feature of a large matrix of residue–ligand distances, can efficiently produce an optimal low-dimensional latent space that stores necessary information on the ligand-binding event. In particular, for a system of L99A mutant of T4 lysozyme interacting with its native ligand, benzene, this deep encoder–decoder framework automatically identifies multiple distinct recognition pathways, without requiring user intervention. The intermediates involve the spatially discrete location of the ligand in different helices of the protein before its eventual recognition of native pose. The compressed subspace derived from the autoencoder provides a quantitatively accurate measure of the free energy and kinetics of ligand binding to the native pocket. The investigation also recommends that while a linear dimensional reduction technique, such as time-structured independent component analysis, can do a decent job of state-space decomposition in cases where the intermediates are long-lived, autoencoder is the method of choice in systems where transient, low-populated intermediates can lead to multiple ligand-binding pathways.
Study of the effects of reference conditions on electrical properties estimation for PV modules under varying operating conditions
Authors: Ma Jiao , Zhang Yunpeng , Lu Hao , Hao Peng , Gu Tingkun , Yang Ming , Zhang Li
Published: May 2023

In traditional methods, electrical property estimation of photovoltaic (PV) modules is achieved through two steps. First, a certain condition (usually standard testing condition, STC) is selected as the reference condition, and the physical parameters under the reference condition are extracted from current–voltage data points. Second, physical parameters under varying operating conditions are obtained by transforming equations, and the electrical properties of the PV modules are estimated. In this paper, the influence of different reference conditions on the accuracy of performance estimation is studied. The estimation results using different reference conditions are compared to obtain the error distribution pattern, which has essential reference significance for the selection of reference conditions in practical applications. In addition, a method of the selecting reference condition is proposed. A new objective function is proposed by considering three key operating points for each I–V curve under different operating conditions, which balances accuracy and computational complexity. A large amount of experimental data for different types of PV modules are used to validate the effectiveness and accuracy of the proposed method. In comparison with the traditional methods using STC as the reference condition and existing method in Matlab/Simulink, the results obtained by the proposed method exhibit better accuracy. It can be further used to estimate the output power of PV system under varying operating conditions.
Influence of thermal hysteresis on the heat shuttling effect: The
case of VO2
Authors: Krapez Jean-Claude
Published: May 2023

Thermotronics has attracted much attention driven by the promising potentials offered by devices such as thermal diodes, thermal transistors, and thermal memristors. Heat shuttling (or heat ratcheting, or heat pumping) is a phenomenon exhibited by nonlinear materials presenting temperature-dependent thermal conductivity which, when sandwiched between two thermal baths with one bath subjected to a time-varying temperature, show nonvanishing net heat flow, although the baths share the same average temperature. Phase-change materials (PCMs) like VO2 were recently taken for illustration due to a strong change in conductivity over a small temperature range; energy extraction from the thermal variations of the environment was envisioned thereupon. However, up to now, the impact of PCM hysteresis has been either overlooked or roughly approximated. On the basis of a thermal model simulating partial hysteresis loops and nonhysteretic branches, we demonstrate that the presence of hysteresis profoundly modifies the appearance of the heat-shuttling effect and can constitute a hindrance to its manifestation. Operating configurations to improve its observation have been proposed.
High energy vibrational excitations of nitromethane in liquid water
Authors: Jurado Romero Arnau , Calero Carles , Sibert Edwin L. , Rey Rossend
Published: May 2023

The pathways and timescales of vibrational energy flow in nitromethane are investigated in both gas and condensed phases using classical molecular mechanics, with a particular focus on relaxation in liquid water. We monitor the flow of excess energy deposited in vibrational modes of nitromethane into the surrounding solvent. A marked energy flux anisotropy is found when nitromethane is immersed in liquid water, with a preferential flow to those water molecules in contact to the nitro group. The factors that permit such anisotropic energy relaxation are discussed, along with the potential implications on the molecule’s non-equilibrium dynamics. In addition, the energy flux analysis allows us to identify the solvent motions responsible for the uptake of solute energy, confirming the crucial role of water librations. Finally, we also show that no anisotropic vibrational energy relaxation occurs when nitromethane is surrounded by argon gas.
High-performance strategies for the recent MRSF-TDDFT in GAMESS
Authors: Komarov Konstantin , Mironov Vladimir , Lee Seunghoon , Pham Buu Q. , Gordon Mark S. , Choi Cheol Ho
Published: May 2023

Multiple ERI (Electron Repulsion Integral) tensor contractions (METC) with several matrices are ubiquitous in quantum chemistry. In response theories, the contraction operation, rather than ERI computations, can be the major bottleneck, as its computational demands are proportional to the multiplicatively combined contributions of the number of excited states and the kernel pre-factors. This paper presents several high-performance strategies for METC. Optimal approaches involve either the data layout reformations of interim density and Fock matrices, the introduction of intermediate ERI quartet buffer, and loop-reordering optimization for a higher cache hit rate. The combined strategies remarkably improve the performance of the MRSF (mixed reference spin flip)-TDDFT (time-dependent density functional theory) by nearly 300%. The results of this study are not limited to the MRSF-TDDFT method and can be applied to other METC scenarios.
Factors associated with emergency department service outcomes for people with a mental health problem brought in by police: a retrospective cohort study
Authors: Wardrop Rachel , Ranse Jamie , Chaboyer Wendy , Young Jesse T. , Kinner Stuart A. , Crilly Julia
Published: May 2023

Objective This study aimed to identify factors associated with an emergency department (ED) length of stay ≥4 hours (h) and hospital admission for people with a mental health problem brought in by police. Methods We undertook a retrospective, observational cohort study of state-wide adult ED mental health presentations brought in by police from 1 January 2012 to 31 December 2017. We used multivariable logistic regression to determine factors associated with an ED length of stay ≥4 h and hospital admission. Results In total, 9325 ED presentations with a mental health problem brought in by police to Queensland EDs were included. Factors most strongly associated with an ED length of stay ≥4 h included an Australasian Triage Score (ATS) of 1, an age of 85 years or older, night shift arrival and subsequent hospital admission. For hospital admission, an ATS of 1, an age of 85 years or older and an ED length of stay ≥4 h were the strongest factors. Conclusion Findings indicate opportunities for targeted mental health models of care to better support people brought in by police to an ED. Such models should involve ED, pre-hospital providers (police and ambulance) and mental health services to support early intervention and potentially reduce the likelihood of a long ED length of stay and subsequent hospital admission.
Screening, diagnosing and management of Pacific peoples with prediabetes in New Zealand primary healthcare clinics with high concentrations of Pacific peoples: an online survey
Authors: Faletau Julienne , Dobson Rosie , Nosa Vili , McCool Judith
Published: May 2023

Introduction Prediabetes is a condition of elevated blood sugar levels which can increase the risk of type 2 diabetes (T2D) if not managed effectively. Prediabetes is likely to affect about 24.6% of New Zealand (NZ) adults, with estimates of 29% of the Pacific population currently living with the condition. A prediabetes diagnosis is an opportunity for intervention from trusted primary care providers. The study aim was to describe primary healthcare clinician’s knowledge and practice regarding screening, diagnosing and management of prediabetes in Pacific patients. Methods An online survey was conducted with current practicing primary healthcare clinicians between February and April 2021. Eligible participants included clinicians employed in a primary healthcare clinic with over 50% of enrolled patients identified as Pacific. Results Primary healthcare clinicians (n = 30) reported that their prediabetes screening, diagnosis and management were aligned with the NZ Ministry of Health clinical guidelines. The most common factors that prompted screening was a family history of T2D (25/30, 83%), ethnicity (24/30, 80%) weight and BMI (24/30, 80%). The initial management practices involved providing recommendations for dietary changes and physical activity (28/30, 93%) and referring patients to a diabetes prevention lifestyle change programme (16/30, 53%). Discussion Primary healthcare clinicians are the foremost point of engagement with patients and their fāmili (family) in their health journey. Culturally appropriate tools could be useful to assist healthcare providers to communicate to a higher risk population and most clinicians rely on up to date guidelines for screening and management.
Satellite-based environmental variables complement traditional variables in spatio-temporal models of purple martin migration
Authors: Courter Jason R. , Liu Zhen , Neupane Naresh , Arab Ali , Siegrist Joe
Published: May 2023

Context As advanced satellite-based environmental data become widely accessible, emerging opportunities exist to understand avian lifecycle events at continental scales. Although this growing toolbox offers much promise, an abundance of options may appear overwhelming to ecologists and point to the need for interdisciplinary collaborations to develop and interpret complex, spatio-temporal models. Aims Here, we demonstrate that satellite-based environmental variables complement conventional variables in spatio-temporal phenology models. The objective of this case study was to assess the degree to which including more sophisticated, satellite-based greenness data in association with a customised growing degree-day metric, can improve traditional phenological models based solely on monthly temperature and precipitation. Methods Using 2001–2018 purple martin (Progne subis) first arrival dates (n = 49 481) from the Purple Martin Conservation Association, we develop a predictive model for their first arrival dates on the basis of traditional temperature and precipitation values from ground-based meteorological stations, the MODIS satellite-based greenness index, and a more sophisticated growing degree-day metric. We used a Bayesian framework to construct 10 spatio-temporal candidate models on the basis of different combinations of predictor variables and our best model included a combination of both traditional and customised MODIS-based variables. Key results Our results indicated that purple martins arrive earlier when greening occurs earlier than the mean, which is also associated with warmer spring temperatures. In addition, wetter February months also predicted earlier martin arrivals. There was no directional change in purple martin first arrival dates from 2001 to 2018 in our study region. Conclusions Our results suggest that satellite-based environmental variables complement traditional variables such as mean monthly temperature and precipitation in models of purple martin migratory phenology. Implications Including emerging and conventional variables in spatio-temporal models allows complex migratory changes to be detected and interpreted at broad spatial scales, which is critical as Citizen Science efforts expand. Our results also pointed to the importance of assembling interdisciplinary research teams to assess the utility of novel data products.
Formation of amyloid loops in brain tissues is controlled by the flexibility of protofibril chains
Authors: Miller Alyssa , Wei Jiapeng , Meehan Sarah , Dobson Christopher M. , Welland Mark E. , Klenerman David , Vendruscolo Michele , Ruggeri Francesco Simone , Knowles Tuomas P. J.
Published: May 2023

Neurodegenerative diseases, such as Alzheimer’s disease (AD), are associated with protein misfolding and aggregation into amyloid fibrils. Increasing evidence suggests that soluble, low-molecular-weight aggregates play a key role in disease-associated toxicity. Within this population of aggregates, closed-loop pore-like structures have been observed for a variety of amyloid systems, and their presence in brain tissues is associated with high levels of neuropathology. However, their mechanism of formation and relationship with mature fibrils have largely remained challenging to elucidate. Here, we use atomic force microscopy and statistical theory of biopolymers to characterize amyloid ring structures derived from the brains of AD patients. We analyze the bending fluctuations of protofibrils and show that the process of loop formation is governed by the mechanical properties of their chains. We conclude that ex vivo protofibril chains possess greater flexibility than that imparted by hydrogen-bonded networks characteristic of mature amyloid fibrils, such that they are able to form end-to-end connections. These results explain the diversity in the structures formed from protein aggregation and shed light on the links between early forms of flexible ring-forming aggregates and their role in disease.
Carbonates and intermediate-depth seismicity: Stable and unstable shear in altered subducting plates and overlying mantle
Authors: Prakash Abhishek , Holyoke Caleb W. , Kelemen Peter B. , Kirby Stephen H. , Kronenberg Andreas K. , Lamb William M.
Published: May 2023

A model for intermediate-depth earthquakes of subduction zones is evaluated based on shear localization, shear heating, and runaway creep within thin carbonate layers in an altered downgoing oceanic plate and the overlying mantle wedge. Thermal shear instabilities in carbonate lenses add to potential mechanisms for intermediate-depth seismicity, which are based on serpentine dehydration and embrittlement of altered slabs or viscous shear instabilities in narrow fine-grained olivine shear zones. Peridotites in subducting plates and the overlying mantle wedge may be altered by reactions with CO
2
-bearing fluids sourced from seawater or the deep mantle, to form carbonate minerals, in addition to hydrous silicates. Effective viscosities of magnesian carbonates are higher than those for antigorite serpentine and they are markedly lower than those for H
2
O-saturated olivine. However, magnesian carbonates may extend to greater mantle depths than hydrous silicates at temperatures and pressures of subduction zones. Strain rates within altered downgoing mantle peridotites may be localized within carbonated layers following slab dehydration. A simple model of shear heating and temperature-sensitive creep of carbonate horizons, based on experimentally determined creep laws, predicts conditions of stable and unstable shear with strain rates up to 10/s, comparable to seismic velocities of frictional fault surfaces. Applied to intermediate-depth earthquakes of the Tonga subduction zone and the double Wadati–Benioff zone of NE Japan, this mechanism provides an alternative to the generation of earthquakes by dehydration embrittlement, beyond the stability of antigorite serpentine in subduction zones.
Impact of acute stress on murine metabolomics and metabolic flux
Authors: Lee Won Dong , Liang Lingfan , AbuSalim Jenna , Jankowski Connor S.R. , Samarah Laith Z. , Neinast Michael D. , Rabinowitz Joshua D.
Published: May 2023

Plasma metabolite concentrations and labeling enrichments are common measures of organismal metabolism. In mice, blood is often collected by tail snip sampling. Here, we systematically examined the effect of such sampling, relative to gold-standard sampling from an in-dwelling arterial catheter, on plasma metabolomics and stable isotope tracing. We find marked differences between the arterial and tail circulating metabolome, which arise from two major factors: handling stress and sampling site, whose effects were deconvoluted by taking a second arterial sample immediately after tail snip. Pyruvate and lactate were the most stress-sensitive plasma metabolites, rising ~14 and ~5-fold. Both acute handling stress and adrenergic agonists induce extensive, immediate production of lactate, and modest production of many other circulating metabolites, and we provide a reference set of mouse circulatory turnover fluxes with noninvasive arterial sampling to avoid such artifacts. Even in the absence of stress, lactate remains the highest flux circulating metabolite on a molar basis, and most glucose flux into the TCA cycle in fasted mice flows through circulating lactate. Thus, lactate is both a central player in unstressed mammalian metabolism and strongly produced in response to acute stress.
Guardians of the oral barriers
Authors: Buggert Marcus
Published: May 2023

The oral mucosa serves as a frontline defense against many infections. Stolley et al. (2023. J. Exp. Med.https://doi.org/10.1084/jem.20221853) discovered that the oral mucosa houses CD8+ CD103+ resident memory T cells, which are important for protecting against local viral infections in mice.
Robot sensing based on electrical capacitance tomography sensor with rotation
Authors: Liu Xiaofei , Yang Wuqiang
Published: May 2023

The existing sensing technology for industrial robot hands cannot sense inside of an object. To recognise the material and internal distribution of an object when it is grasped, electrical capacitance tomography (ECT) may be used if the object is non-conductive, as ECT can measure the permittivity distribution inside an object from external capacitance measurements. An ECT sensor normally has 8 or 12 electrodes equally distributed around an object. This paper introduces the first attempt to make use of ECT with robot hands. Because the number of electrodes is limited, it is necessary to rotate the object to be imaged mechanically, so that sufficient measurements can be taken. Four aspects of the ECT sensor are discussed based on simulation: (1) the structure of electrodes; (2) the number of rotation times; (3) the starting position of rotation; and (4) the diameter of rotation. Two image reconstruction algorithms are used: the linear-back projection and Landweber iteration with three typical distributions. The results show that the rotational three-electrode ECT structure has good ability to produce useful images, showing the internal distribution of unknown objects.
Effect of the electronic confinement potential on the electron–LO-phonon interaction energy in a quantum well
Authors: Hien Nguyen Dinh
Published: May 2023

We investigated the effect of the electronic confinement potential on the electron–LO-phonon (el–LO-ph) interaction energy in a quantum well by using the variational method. In this work, the el–LO-ph interaction energy in the infinite (I) and finite (F) square potential quantum wells (SPQW) is calculated as a function of the well-width for all four different confined-optical-phonon (COP) models. The result shows that the el-LO-ph interaction energy in a quantum well is affected strongly by the electronic confinement potential for all four COP models. Except for the Ridley-Babiker model, the el-LO-ph interaction energy in the ISPQW is always larger than that in the FSPQW for both the lowest phonon modes of different COP models in the narrow well case. The Fuchs-Kliewer and the Knipp-Reineck models have a good agreement in the description of the el-LO-ph interaction for the ISPQW, while that is the Fuchs-Kliewer and the Huang-Zhu models for the FSPQW. Among the above four models, the Fuchs-Kliewer model is the most effective.
A governing equation of Rossby waves and its dynamics evolution by Bilinear neural network method
Authors: Cao Na , Yin XiaoJun , Bai ShuTing , Xu LiYang
Published: May 2023

This paper studies an extended evolution equation of large-scale waves by means of bilinear neural network method, which is obtained from local Cartesian coordinate system of the basic equation set by using scaling analysis method and perturbation expansions method. First, we convert the equation into a Hirota equation by using variable transformation. Then, we give the structure framework and the model of the bilinear neural network. We build the test function in two dimensions: depth and breadth. With choosing appropriate activation functions and neuron coefficients, we get many rational function exact solutions, including rogue waves and interaction phenomenon consisting of rogue wave and soliton wave. At last, the figures of these exact solutions are exhibited by selecting suitable value of parameters. We think that these results are very important in ocean dynamics.
A non-invasive optical method for anaemia detection
Authors: Chamola Paritosh , Mittal Poornima
Published: May 2023

The latest non-invasive biomedical electronic sensors are capable of providing continuous reliable information, for instance oxygenation level of blood, level of glucose etc. These biomedical sensors are in general based on the electro-chemical or spectral properties of the substances. The absorption of blood in infrared and visible range is prominently determined by haemoglobin. The coefficient of absorption for blood is different at different wavelengths. This optical absorption characteristic of the blood yields the vital information on the composition of the blood. Haemoglobin is primarily used to measure the status of anaemia, in developing countries like India and other African countries numerous people with greater health needs don’t have access to proper diagnostic facilities. Therefore, an introduction of portable, low cost and non-invasive Haemoglobin detector will give a vast opportunity for screening the population suffering with anaemia. The present article purposes a non-invasive method of haemoglobin detection comprising of an organic photovoltaic cell and three LED’s sources i.e., blue, green and red which are used with their respective radiation spectral range of 450–495 nm, 495–570 nm and 620–750 nm to illuminate an area of the skin on finger, this transmitted light after interacting with tissues is detected by an arrangement of Coumarin 30 : C60/NN′-QA/ZnPc active layer based organic solar cell. Thus, the approach provide in this article presents a simple, biocompatible and flexible means for assessing blood haemoglobin level by utilizing an multi spectral optical processing method. The method developed herein could further be integrated to wearable electronic devices.
Eco-friendly Co-Mg-La nanoferrites for an efficient MB removal for wastewater treatment applications
Authors: AlHammad M S , Mansour S F , Al-Wafi Reem
Published: May 2023

Improving effective and thrifty photocatalysts was deemed an outstanding approach for pollution handling. Here, a novel magnetic Co0.5Mg0.5LaxFe2-xO4 nanoparticle photocatalysts were synthesized via a combustion approach for the harmful methylene blue (MB) dye degradation. These samples were labeled as Co0.5Mg0.5Fe2O4 (CMLF0), Co0.5Mg0.5La0.03Fe1.97O4 (CMLF1), Co0.5Mg0.5La0.06Fe1.94O4 (CMLF2), Co0.5Mg0.5La0.09Fe1.91O4 (CMLF3), Co0.5Mg0.5La0.12Fe1.88O4 (CMLF4), and Co0.5Mg0.5La0.15Fe1.85O4 (CMLF5). A sequence of characterizations, including XRD, STEM, and UV–Vis-DRS, was exploited to examine the structure, morphology, constituent elements, and optical features of the CMLF ferrite nanoparticles. Despite the substitution process, an amazing decrement result for the lattice parameter (8.3748 to 8.3610 Å) and crystallite size (21.87 to 13.95 nm) is a large La cation at the expense of a smaller Fe one. The band-gap behavior of the CMLF nanoferrites is unique; it increases from 1.528 eV at the CMLF0 to 1.547 eV at the CMLF3 and decreases to 1.526 eV at the CMLF4 and 1.520 eV at the CMLF5. Two justifications accounted for this behavior. The nanoferrite CMLF5 has the highest photodegradation efficiency, 96.09%, after 60 min. Three hypotheses were introduced to explain this result. After five cycles, the degradation efficiency of the nanoferrite CMLF5 maintained its high performance with 95.09%, 94.87%, 94.76%, 93.59%, and 93.44%, respectively. These outcomes validate the outstanding photocatalytic efficiency, recyclability, and stability of the CMLF5 photocatalyst in its task to degrade the harmful MB dye, making it acceptable for wastewater treatment applications.