bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Screeners to Identify Risk of Developmental Language Disorder
Authors: Bao Xue , Komesidou Rouzana , Hogan Tiffany P.
Published: February 2024

Purpose:

This review aims to comprehensively summarize, compare, and evaluate screeners used to identify risk for developmental language disorder (DLD), a common learning disability that is underidentified. Screening for DLD is a cost-effective way to identify children in need of further assessment and, in turn, provides much needed supports.

Method:

We identified 15 commercially available English language DLD screeners in North America. We then characterized each screener on 27 aspects in three domains, including (a) accessibility information (acronym, subtest, website, cost, materials included, publish year, examiner qualification, age range, administration time, and administration format), (b) usability features (dialect compatibility, progress monitoring function, actionable follow-up instruction, group assessment capability, and online administration availability), and (c) technical standards (the availability of a technical manual, conceptual definition, the sample size used in classification accuracy calculation, sample distribution, year of sample collection, outcome measure, sample base rate, cutoff score, sensitivity, specificity, positive predictive value, and negative predictive value).

Results:

We obtained sufficient accessibility information from 14 out of 15 (93%) screeners. In contrast, none of the screeners (0%) included comprehensive usability features. Ten screeners (67%) included a range of classification accuracy (70%–100% sensitivity and 68%–90% specificity). We provided areas of strength and weakness for each screener as a quick reference for users and generated screener recommendations for five practical scenarios.

Conclusions:

Our findings presented some DLD screeners that meet most standards and highlight numerous areas for improvement, including improving classification accuracy and clarifying follow-up instructions for children who are identified with DLD risk. Screening for DLD is critical to provide timely early identification, intervention, and classroom support, which in turn facilitates student outcomes.
Speech, Language, Hearing, and Otopathology Results From the International Smith–Magenis Syndrome Patient Registry
Authors: Brennan Christine , Smith Mara Louise , Baiduc Rachael R. , O'Connor Liam
Published: February 2024

Purpose:

Smith–Magenis syndrome (SMS), a rare, genetically linked complex developmental disorder caused by a deletion or mutation within chromosome 17p11.2, is associated with delays in speech-language development, otopathology, and hearing loss, yet previous studies lack comprehensive descriptions of hearing and communication profiles. Here, analyses of patient registry data expand what is known about speech, language, hearing, and otopathology in SMS.

Method:

International speech-language and hearing registry survey data for 82 individuals with SMS were analyzed using descriptive and inferential statistics. Hearing loss, history of otitis media and pressure equalization (PE) tubes, communication mode, expressive/receptive language, and vocal quality were analyzed for all subjects and subjects grouped by age. Statistical methods included descriptive statistics and Pearson's chi-square tests of independence to test for differences between age groups for each variable of interest. Association analyses included Pearson's correlations.

Results:

Hearing and otological analyses revealed that 35% of subjects had hearing loss, 66% had a history of otitis media, and 62% had received PE tubes. Speech-language analyses revealed that 60% of subjects communicated using speech, 79% began speaking words at/after 24 months of age, 92% combined words at/after 36 months, and 41% used sign language before speech. There was a significant association between the age that first words were spoken and the age that PE tubes were first placed. Communication strengths noted in more than 40% of subjects included social interest, humor, and memory for people, past events, and/or facts.

Conclusions:

Significant delays and impairment in speech-language were common, but the majority of those with SMS communicated using speech by age 6 years. Age was a significant factor for some aspects of hearing loss and communication. Neither hearing loss nor otitis media exacerbated language impairment. These results confirm and extend previous findings about the nature of speech, language, hearing, and otopathology in those with SMS.
Verb Tense Production in People With Nonfluent Aphasia Across Different Discourse Elicitation Tasks
Authors: Park Hyejin , Obermeyer Jessica , Paek Eun Jin , Zurbrugg Madeline
Published: February 2024

Purpose:

Verb tense production is known to be impaired in people with nonfluent aphasia. Selective past tense impairment in this population has been reported, but results are inconsistent and lacking at the discourse level. In addition, language production can be affected by discourse elicitation tasks depending on the cognitive linguistic demands and instructions unique to each task. There is limited evidence regarding whether verb tense production in people with nonfluent aphasia is impacted by discourse task demands. Understanding this potential impact is important for clinicians and researchers who are interested in assessing and then identifying effective clinical goals for this population. Therefore, this study aimed to investigate the trends of verb tense production across various discourse elicitation tasks in people with nonfluent aphasia compared to people without aphasia.

Method:

Language samples for 23 people with nonfluent aphasia and 27 people without aphasia were obtained for six discourse tasks from the AphasiaBank database. We calculated ratios of past tense, present tense, future tense, imperative, and unknown verb types to compare which tense was used most frequently within and across the tasks and groups.

Results and Conclusions:

Our findings revealed evidence of verb tense production deficits and a selective past tense impairment in people with nonfluent aphasia. Discourse task effects were shown for people without aphasia but were scarce in people with nonfluent aphasia. This finding could be explained by an overall reduction of verb production and overreliance on present tense production in nonfluent aphasia. These results suggest the potential methodological implications of using different discourse tasks to evaluate verb tense production in people with nonfluent aphasia. Future studies need to evaluate discourse task effects on other aspects of verb production (e.g., moods) and specific task factors (e.g., presence or absence of visual stimulus).

Supplemental Material:

https://doi.org/10.23641/asha.25146242
Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things
Authors: Dhasaratha Chandramohan , Hasan Mohammad Kamrul , Islam Shayla , Khapre Shailesh , Abdullah Salwani , Ghazal Taher M. , Alzahrani Ahmed Ibrahim , Alalwan Nasser , Vo Nguyen , Akhtaruzzaman Md
Published: February 2024

Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help healthcare providers decide about post‐COVID‐19 care and follow‐up where the data privacy is another severe concern. The authors investigate the applicability of a distributed reinforcement learning approach in a Federated Learning (FL) multi‐disciplinary reinforcement system and explores the potential benefits of incorporating Blockchain Technology (BT) in the distributed system. Intermediate dependency features and transactions are avoided by applying Blockchain‐enabled reinforcement FL for the post‐COVID‐19 patient data of IoMT applications. The proposed approach helps to improvise clinical monitoring and ensure secure communication and data privacy in a decentralised manner. The main objective is to improve the efficiency and scalability of the reinforcement FL process in a distributed environment while ensuring data privacy and security through BT for IoMT applications. Results show that proposed approach achieve comparatively high reliability and outperforms the existing approaches.
Data transmission path planning method for wireless sensor network in grounding grid area based on MM‐DPS hybrid algorithm
Authors: Xiao Xianghui , Huang Longsheng , Zhang Zhenshan , Huang Mingxian , Guan Luchang , Song Yunhao
Published: February 2024

At present, in order to conduct non‐destructive testing on the grounding grid of substations under the condition of continuous power supply and no excavation, researchers have applied wireless technology based on electrochemical methods to remotely monitor the corrosion state of grounding conductors online. Nevertheless, wireless signals are affected by the environment when they are transmitted underground. In the field of grounding gird wireless monitoring, how to plan the information transmission path of wireless sensor network (WSN) with high accuracy of data transfer and low energy consumption earns growing research attention. To address the problem of WSN path planning in grounding grid area, a path planning method for WSN based on the hybrid algorithm of map‐matching algorithm and double‐pole search algorithm (MM‐DPS) is proposed in this paper. The map‐matching algorithm is employed to calculate the optimal sampling node number of the data transmission path. On the basis of the optimal sampling node number, the double‐pole search algorithm is employed in seeking out each sensor node of the path, and two groups of path plans are obtained. In the simulation experiment, compared with the A‐star algorithm, the MM‐DPS algorithm shortens the data transmission path length by about 39% and reduces the energy consumption by about 57%. The research work brings a method to alleviate the problem of data transmission underground of WSN in grounding grid area. The method not only ensures the accuracy of data transmission, but also shorts the transmission distance and reduces energy consumption.
System architecture for small‐scale personalized production lines based on industrial Internet
Authors: Li Qiang , Liu Jiaming
Published: February 2024

The rapid development of industrial Internet has resulted in significant changes in industrial manufacturing system architecture. In this study, a system architecture suitable for small‐scale personalized production lines is proposed. The core of this architecture is a three‐layer structure comprising the Internet layer, data layer, and field control layer. The system facilitates the transmission of user‐specific product demands from the Internet to the production line, where the production equipment achieves personalized production through motion control. This system architecture for production lines integrates industrial Internet and smart manufacturing technologies, reducing the complexity of the enterprise system architecture and enhancing the flexibility of the system compared to large‐scale personalized production systems. The effectiveness of this system architecture was validated using a flexible yogurt filling production line and lays a foundation for the transformation of industrial manufacturing from the tradition system to a personalized production.
Variational Bayesian Gaussian mixture model for off‐grid DOA estimation
Authors: Guan Shanwen , Li Ji , Luo Xiaonan
Published: February 2024

Wireless signals are commonly subject to diverse and complex noise interference. The typical assumption of Gaussian white noise often oversimplifies the noise, resulting in reduced accuracy in estimating the direction of arrival (DOA), especially in complex scenarios. To tackle this issue, this paper introduces a new Bayesian model for off‐grid DOA estimation. This model utilizes Gaussian mixture model (GMM)‐based Dirichlet processes (DP) to characterize noise, allowing adaptive adjustments in the number of Gaussian mixture models. Leveraging the factor graph representation of the Bayesian model, a low‐complexity mixed messaging passing algorithm, employing generalized approximate message passing (GAMP) and mean field (MF), is proposed. Simulation results validate the efficacy of the proposed algorithm.
Modelling method for time‐varying suspension system of axial split‐phase bearingless switched reluctance motor
Authors: Wen Fuguang , Xie Kai , Zou Yu , Yuan Ye
Published: February 2024

The rotor of the axial split‐phase bearingless switched reluctance motor (ASPBSRM) is structured with convex poles. The magnetic flux between the stator and the rotor varies with the rotor position, resulting in time‐dependent displacement stiffness and current stiffness coefficients of the suspension force. This scenario leads to a time‐varying characteristic of the suspension system. This study analyzed the electromagnetic characteristics of the suspension force in the ASPBSRM to characterize the time‐varying suspension system accurately. The study elucidated the hinge relationship between the magnetic flux in the suspension system and the rotor position. Moreover, a mathematical model for the suspension force considering the magnetic flux multitooth hinge was constructed by leveraging the advantages of the Maxwell stress method for the localized modelling and adopting the concept of the main edge magnetic path parallel analysis. Finally, the effectiveness of the model was verified through finite element analysis.
Building the bioeconomy: A targeted assessment approach to identifying biobased technologies, challenges and opportunities
Authors: Holland Claire , Shapira Philip
Published: February 2024

The authors explore opportunities, challenges, and strategies to translate and responsibly scale innovative biobased technologies to build more sustainable bioeconomies. The pandemic and other recent disruptions increased exposure to issues of resilience and regional imbalance, highlighting a need for production and consumption regimes centred more on local biobased resources and dispersed production. The authors review potential biobased technology strategies and identify promising and feasible options for the United Kingdom. Initial landscape and bibliometric analysis identified 50 potential existing and emerging biobased technologies, which were assessed for their ability to fulfil requirements related to biobased production, national applicability, and economic‐, societal‐, and environmental‐benefits, leading to identification of 18 promising biobased production technologies. Further analysis and focus‐group discussion with industrial, governmental, academic, agricultural, and social stakeholders, identified three technology clusters for targeted assessment, drawing on cellulose‐, lignin‐, and seaweed feedstocks. Case studies were developed for each cluster, addressing conversations around sustainable management, use of biomass feedstocks, and associated environmental‐, social‐, and economic challenges. Cases are presented with discussion of insights and implications for policy. The approach presented is put forward as a scalable assessment method that can be useful in prompting, informing, and advancing discussion and deliberation on opportunities and challenges for biobased transformations.
Investigating the characteristics of internal discharge shock waves in gas‐insulated switchgear under varied gap configurations
Authors: Jia Chenglong , Haochu Peng , Zhao Wenbin , Tang Zhong
Published: February 2024

Gas‐insulated switchgears (GIS) are crucial components of high‐voltage power transmission and distribution systems. Internal discharges within GIS have garnered significant attention in the field of power engineering. This study investigates the characteristics of internal discharge shock waves in GIS under an air pressure of 0.3 MPa and three different discharge gap conditions: 1, 1.5, and 2 mm. High‐speed shadowing techniques are used to analyse the propagation speed, morphology, and post‐wave parameters. The study findings reveal that although the characteristics of internal discharge shock waves in GIS noticeably change with the gap size, they also exhibit a consistent trend: as the gap size increases, the initial shock wave accelerates, intensifying the discharge. Simultaneously, the rate of attenuation rises, with the shock wave becoming weaker after ≈30 µs. Furthermore, the post‐wave parameters follow a similar pattern, with an increase in gap size leading to higher parameter values but also a faster decay rate. The parameters decay more rapidly between 10 and 20 µs, slow down between 20 and 30 µs, and ultimately stabilize after around 30 µs. The results of this study hold significant theoretical and practical implications for the monitoring, diagnosis, and prevention of internal discharges in GIS.
Pseudo‐measurement‐based state estimation for railway power supply systems with renewable energy resources
Authors: Pan Zheng , Che Liang , Tu Chunming
Published: February 2024

State estimation is critical for railway power supply systems (RPSSs). Pseudo‐measurement is commonly used in state estimation. However, the fluctuations of renewable generations and railway traction loads in RPSS may introduce data noise, which will jeopardize the accuracy of the generated pseudo‐measurements and thus impact the state estimation. Additionally, when learning the historical measurement data sequences, the traditional pseudo‐measurement model is likely to have overfitting, which will further impact the accuracy of pseudo‐measurements, thereby affecting the accuracy of state estimation. To address these issues, this paper proposes a high‐accuracy pseudo‐measurement‐based state estimation approach for RPSSs. Firstly, a denoising autoencoder‐based method is used to mitigate the impact of data noise on the accuracy of pseudo measurements, and a gated recurrent unit‐based method is used to adaptively learn the historical measurement data sequence, thereby improving the accuracy of pseudo measurements. Next, the pseudo‐measurement weights are obtained by generating pseudo‐measurement variances using the Gaussian mixture model. Finally, the pseudo measurements and real‐time measurements are integrated by weighted least squares to realize the state estimation of RPSS. The effectiveness and accuracy of the proposed method are verified by simulation on a modified IEEE 33‐node system which includes a railway traction substation and renewable generations.
Facial and mandibular landmark tracking with habitual head posture estimation using linear and fiducial markers
Authors: Saad Farhan Hasin , Farook Taseef Hasan , Ahmed Saif , Zhao Yang , Liao Zhibin , Verjans Johan W. , Dudley James
Published: February 2024

This study compared the accuracy of facial landmark measurements using deep learning‐based fiducial marker (FM) and arbitrary width reference (AWR) approaches. It quantitatively analysed mandibular hard and soft tissue lateral excursions and head tilting from consumer camera footage of 37 participants. A custom deep learning system recognised facial landmarks for measuring head tilt and mandibular lateral excursions. Circular fiducial markers (FM) and inter‐zygion measurements (AWR) were validated against physical measurements using electrognathography and electronic rulers. Results showed notable differences in lower and mid‐face estimations for both FM and AWR compared to physical measurements. The study also demonstrated the comparability of both approaches in assessing lateral movement, though fiducial markers exhibited variability in mid‐face and lower face parameter assessments. Regardless of the technique applied, hard tissue movement was typically seen to be 30% less than soft tissue among the participants. Additionally, a significant number of participants consistently displayed a 5 to 10° head tilt.
Skeleton extraction of hard‐pen regular script based on stroke characterization and ambiguous zone detection
Authors: Xu Zhanyang , Qin Feiyang , Xiong Ningyang , Shi Hongyan , Zhang Jiarui , Lin Wei
Published: February 2024

The Intelligent Evaluation System for Calligraphy Characters (IESCC) is used for teaching calligraphy, and users can learn calligraphy through the modifications given by the system. Chinese character skeleton extraction is an important step in the intelligent evaluation algorithm of calligraphic characters. The skeletons of Chinese characters extracted by traditional refinement algorithms are prone to redundant branches and deformed skeletons, which can lead to skeleton extraction results that do not conform to the topology of the original character. In this study, the focus lies on hard‐pen regular script, and skeleton repair and extraction are performed for these characters. According to the writing characteristics of regular script, the redundant burs are removed and the deformation zone of the thinned skeleton is detected, and then the idea of first splitting is used, then restructuring, to propose a skeleton extraction algorithm based on stroke characterization and ambiguous zone detection for hard‐pen regular script, referred to as SCAD. First, a thinning algorithm is used to extract the skeleton of Chinese characters and remove redundant pixels. By analyzing the stroke characteristics of regular script, the burrs are classified and different conditions are set to detect and remove the burrs. Then the ambiguous zones are detected according to the different kinds of junction points. Then, curvature, stroke width and direction deviation are used to analyze the continuity of stroke segments, and the decision function is used to classify the stroke segments. Finally, the stroke segments with optimal pairings were compensated by interpolation according to the direction trend. This concludes the skeleton extraction. Skeleton extraction is performed on 1000 sample characters, and the SCAD algorithm can extract the skeleton of Chinese characters with an accuracy of up to 98.37%. It is proved that the SCAD method proposed here is a practical and effective method to extract the skeleton of hard‐pen regular script.
Improved single‐layer powder core inductor design procedure for DC‐DC converters
Authors: Kunstbergs Noass , Hinz Hartmut , Roll Dennis , Schofield Nigel
Published: February 2024

One of the early design decisions for DC‐DC converters is the choice of an appropriate magnetic core material. Powder cores in particular are suitable due to their saturation flux density of up to 1.5 T. However, high DC currents constitutes a significant problem since the winding cross‐section rises with the current, which consequently increases AC losses due to skin effects. Another challenge is the reduction of winding layers to decrease proximity losses. This paper presents an improved single‐layer winding design procedure for DC‐DC converter powder cores. The procedure determines the optimum number of parallel cores and stacks. This way, the procedure enables a predefined maximum wire cross‐section for copper loss optimisation and single‐layer winding. The introduced approach defines the optimum switching frequency as a trade‐off between core loss and core volume. Finally, experimental tests with two setups validate 27 kW DC‐DC converters and hence the design procedure using Si‐IGBTs and SiC‐MOSFETs. The results demonstrate that SiC‐MOSFETs reduce core volume by a factor of 3 compared to Si‐IGBTs. Further, the SiC setup reaches high efficiencies of up to 98.53% compared to 98.17% for the Si‐based converter.
Improved design of passive damping for single phase grid‐connected LCL filtered inverter considering impedance stability
Authors: Ali Ramy , Heydari‐doostabad Hamed , Sajedi Shahab , O'Donnell Terence
Published: February 2024

Grid‐connected inverters with an inductor–capacitor–inductor (LCL) filter usually require the implementation of damping in the filter to suppress the resonance associated with the filter and hence ensure internal stability. The value for the damping resistor is commonly chosen as one‐third of the capacitive reactance at the resonance frequency of the LCL filter. However, this commonly‐used principle does not take into account the external stability of the inverter, i.e. the potential for an interaction between the inverter output impedance and the grid impedance. This work discusses a new design for the damping resistor to assure the external stability of the voltage source inverter as well as its internal stability. The analysis shows that the proposed design can ensure the external stability of the voltage source inverter with different grid impedances as well as robustness against the variations of the filter parameters while maintaining low power losses and an acceptable attenuation rate for high‐frequency harmonics. To validate the theoretical analysis, a 1 kW, 110 V laboratory prototype is implemented. The obtained results confirm the applicability of the proposed design approach.
Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration
Authors: Abbas Ghulam , Wu Zhi , Ali Aamir
Published: February 2024

While extensive research has focused on enhancing distribution networks through either maximizing Distributed Generation (DG) integration or network reconfiguration at specific times, there is a need for further investigation into concurrently optimal network reconfiguration and DG allocation. To reduce the cost of energy delivered, the cost of energy loss, and voltage deviation, this study gives a dynamic multi‐objective network reconfiguration together with siting and sizing of dispatchable and non‐dispatchable DGs. The widely used IEEE 33‐bus and a large‐scale 118‐bus radial test system are employed while considering the time sequence fluctuations in sunlight irradiation and load. To address the pointed‐out challenge of multiperiod optimal DG allocation and reconfiguration while simultaneously decreasing the cost of energy supplied, the cost of energy lost, and the voltage deviation, a novel Multi‐objective Bidirectional co‐evolutionary algorithm (BiCo) is implemented. For better exploration and exploitation, the proposed algorithm integrating the constraint domination principle evolves the population from the feasible and infeasible search space with the help of a novel angle‐based density section. Simulation results demonstrate that the proposed approach outperforms previously published Multi‐objective Evolutionary Algorithms (MOEAs) by discovering a vast collection of uniformly spaced non‐dominated solutions in a single simulation run. Further, a fuzzy set theory is applied to find the best compromise solution among obtained final non‐dominated solutions. The results establish that the Pareto solutions significantly improved the system's voltage profile, with savings of over 22% compared to the baseline case and an exceptional improvement of over 80% in voltage deviation and power loss.
Coordinated control and energy management combined with cyberattack identification in multi‐microgrid integrated with hybrid renewable‐storage
Authors: Faraji Hossien , Hemmati Reza
Published: February 2024

A comprehensive model is developed for coordinated control of voltage‐frequency‐inertia and identifying multiple cyberattacks simultaneously in two microgrids (MGs). The MGs are integrated with solar units, Wind turbine (WT), hybrid supercapacitor‐battery, and fuelcell. The MGs are modelled and controlled for operation under both an island and connected states. In the proposed method, a data centre is designed in which all the electrical and control signals related to the solar, wind, hybrid supercapacitor‐battery, and Fuel cell (FC) are collected, evaluated, and matched. The data centre comprises the following blocks: voltage‐frequency control, inertia control of WT, and identification of false data injection (FDI) cyberattacks on frequency, power, power/frequency, and voltage. The technique used in this article to identify FDI attacks is based on the real‐time method coupled with logical comparisons conducted in the time domain. This methodology provides prompt and precise detection, allowing for timely preventive measures and strategic responses. After FDI attacks occur, the implemented control system effectively manages and regulates the voltage and frequency at the desired levels, efficiently differentiating between ordinary functioning, faulty states, and potential cyber‐attacks. The unhealthy MG can transfer its load to the healthy MG for safety reasons. The healthy MG is then connected to the external grid and the synchronisation conditions are checked by the proposed control system. The results of the non‐linear simulation performed in MATLAB‐Simulink software confirm that the proposed model successfully operates and controls all resources (i.e. solar/wind/battery/FC), regulates the voltage/frequency under various loading conditions, and identifies FDI cyberattacks.
The ‘Other’ subfamily of HECT E3 ubiquitin ligases evaluate the tumour immune microenvironment and prognosis in patients with hepatocellular carcinoma
Authors: Dong Runyu , Wang Zhixiong , Cao Danping , Li Yanna , Fei Yao , Gao Peng , Zhu Menglin , Chen Zhiqiang , Cai Juan , Zuo Xueliang
Published: February 2024

Primary liver cancer is the sixth most common cancer and the third leading cause of cancer‐related death worldwide. The role of the ‘Other’ subfamily of HECT E3 ligases (E3s) in hepatocellular carcinoma (HCC) remains unknown. The expression of the ‘Other’ HECT E3s was performed using The Cancer Genome Atlas (TCGA) data, and the authors found that the ‘Other’ HECT E3s were differentially expressed in HCC. Prognostic values were assessed using the Kaplan–Meier method and indicated that the high expressions of HECTD2, HECTD3, and HACE1 were associated with a worse clinical prognosis of HCC patients. The expression of HECTD2 was significantly correlated with the infiltration of CD4+T cells and neutrophils. The levels of HECTD3 and HACE1 were notably related to the dendritic cells and memory B cells infiltrated in HCC. In addition, the three previously mentioned genes have shown to be associated with immune checkpoint genes, such as FOXP3, CCR8, STAT5B, TGFB1 and TIM‐3. Moreover, HECTD2 could promote the proliferative activity, cell migration and invasive ability of HCC cells. Collectively, the authors’ study demonstrated that HECTD2 was a novel immune‐related prognostic biomarker for HCC, providing new insight into the treatment and prognosis of HCC.
Meteoroid rotation and quasi-periodic brightness variation of meteor light curves
Authors: Mancuso Salvatore , Barghini Dario , Gardiol Daniele
Published: February 2024

Meteor light curves are sometimes known to display flickering: rapid, quasi-periodic variations in brightness. This effect is generally attributed to the rotational modulation of the ablation rate, which is caused by the time-varying cross section area presented by a nonspherical rotating meteoroid to the oncoming airflow. In this work we investigate the effects that the rotation of a meteoroid of given shape (spherical, cubic, or cylindrical) has on the meteor’s light curve, given state-of-the-art experimental laboratory estimates of the drag and lift coefficients of hypersonic flow (Mach number > 5) around various shaped objects. The meteoroid’s shape is important in determining these two forces, due to the different response of the drag and lift coefficients according to the angle of attack. As a case study, the model was applied to a fireball observed on 2018 April 17 by the PRISMA network, a system of all-sky cameras that achieves a systematic monitoring of meteors and fireballs in the skies over the Italian territory. The results show that this methodology is potentially able to yield a powerful diagnostic of the rotation rate of meteoroids prior to their encounter with the atmosphere, while also providing essential information on their pre-fall actual shapes.
Tracing the rise of supermassive black holes
Authors: Andika Irham T. , Jahnke Knud , Onoue Masafusa , Silverman John D. , Fitriana Itsna K. , Bongiorno Angela , Brinch Malte , Casey Caitlin M. , Faisst Andreas , Gillman Steven , Gozaliasl Ghassem , Hayward Christopher C. , Hirschmann Michaela , Kocevski Dale , Koekemoer Anton M. , Kokorev Vasily , Lambrides Erini , Lee Minju M. , Michael Rich Robert , Trakhtenbrot Benny , Megan Urry Claudia , Wilkins Stephen M. , Vijayan Aswin P.
Published: February 2024

We report the identification of 64 new candidates of compact galaxies, potentially hosting faint quasars with bolometric luminosities of Lbol = 1043–1046 erg s−1, residing in the reionization epoch within the redshift range of 6 ≲ z ≲ 8. These candidates were selected by harnessing the rich multiband datasets provided by the emerging JWST-driven extragalactic surveys, focusing on COSMOS-Web, as well as JADES, UNCOVER, CEERS, and PRIMER. Our search strategy includes two stages: applying stringent photometric cuts to catalog-level data and detailed spectral energy distribution fitting. These techniques effectively isolate the quasar candidates while mitigating contamination from low-redshift interlopers, such as brown dwarfs and nearby galaxies. The selected candidates indicate physical traits compatible with low-luminosity active galactic nuclei, likely hosting ≈105–107 M⊙ supermassive black holes (SMBHs) living in galaxies with stellar masses of ≈108–1010 M⊙. The SMBHs selected in this study, on average, exhibit an elevated mass compared to their hosts, with the mass ratio distribution slightly higher than those of galaxies in the local Universe. As with other high-z studies, this is at least in part due to the selection method for these quasars. An extensive Monte Carlo analysis provides compelling evidence that heavy black hole seeds from the direct collapse scenario appear to be the preferred pathway to mature this specific subset of SMBHs by z ≈ 7. Notably, most of the selected candidates might have emerged from seeds with masses of ∼105 M⊙, assuming a thin disk accretion with an average Eddington ratio of fEdd = 0.6 ± 0.3 and a radiative efficiency of ϵ = 0.2 ± 0.1. This work underscores the significance of further spectroscopic observations, as the quasar candidates presented here offer exceptional opportunities to delve into the nature of the earliest galaxies and SMBHs that formed during cosmic infancy.
On mean-field control problems for backward doubly stochastic systems
Authors: Song Jian , Wang Meng
Published: February 2024

This article is concerned with stochastic control problems for backward doubly stochastic differential equations of mean-field type, where the coefficient functions depend on the joint distribution of the state process and the control process. We obtain the stochastic maximum principle which serves as a necessary condition for an optimal control, and we also prove its sufficiency under proper conditions. As a byproduct, we prove the well-posedness for a type of mean-field fully coupled forward-backward doubly stochastic differential equation arising naturally from the control problem, which is of interest in its own right. Some examples are provided to illustrate the applications of our results to control problems in the types of scalar interaction and first order interaction.
Managing Bullwhip Effect in Acoustic Guitar Manufacturing: A Case Study Through Vendor Managed Inventory (VMI) Approach
Authors: Muhammad Baisa Said , Afdil Reynaldi Muhammad , Imran Arif
Published: February 2024

The Bullwhip Effect is a condition where differences arise between the supply and demand numbers within supply chain management. This acoustic guitar manufacturing faces challenges resulting from demand fluctuations, supply chain complexities, and inventory inefficiencies, which often lead to the Bullwhip Effect. The company experiences fluctuations in both demand and supply, consequently leading to inventory accumulation in its warehouses. This study aims to reduce the Bullwhip Effect score in acoustic guitar manufacturing by implementing the Vendor Managed Inventory (VMI) method. VMI acts as a regulatory mechanism during distribution, ensuring better control over dispatched products by incorporating forecasting techniques such as single exponential smoothing, double exponential smoothing, and linear regression. Before implementing VMI, the Bullwhip Effect scores were 1.42 for Retailer 1 and 1.69 for Retailer 2. After the successful implementation of VMI, significant reductions in the Bullwhip Effect scores were observed, with scores of 0.48 and 0.91 recorded for Retailer 1 and Retailer 2, respectively.
Suppliers Evaluation Based on Vendor Performance Indicator (VPI) and Analytical Hierarchy Process (AHP)
Authors: Adi Mukti Lutfi , Yuniar  , Ulfa Afifah Alif
Published: February 2024

Evaluation of supplier performance is an important factor in the supply chain process because it can be one of the company’s strategies to increase customer satisfaction. In selecting suppliers, most companies only focus on the sole consideration of price and raw material availability. This approach makes the supplier selection suboptimal, resulting in non-conformance to order specifications and delivery delays. This study conducted a supplier performance evaluation to provide an assessment of suppliers, enabling the company to identify the strengths and weaknesses of each supplier using the Vendor Performance Indicator (VPI) framework Quality, Cost, Delivery, Flexibility, and Responsiveness, which consists of a total of 13 sub-criteria and employs the Analytical Hierarchy Process (AHP). Based on results, the weighted values for suppliers I, K, L, M, and J were 0.285, 0.275, 0.185, 0.142, and 0.112, respectively. Based on the result, it is recommended that the company adopts a periodic to effectively monitor supplier performance, for better supplier selection and enhanced operational efficiency.
Unravelling the FOG Deposit Sources Characteristic in the South Jakarta City Wastewater Network
Authors: Angelin Andrea , Dwi Maulidiany Nopa
Published: February 2024

DKI Jakarta is the largest wastewater contributor in Indonesia, where 75% of it comes from domestic activities. Typically, effluent will enter the river via a system of wastewater pipelines. Numerous wastewater networks have been observed to have FOG deposits (FD), particularly in South Jakarta. FD is an accumulation of oil and grease in sewerage systems that results in blockages and gas accumulation, leading to explosions in closed networks. Despite the impact being well known, there are currently very few studies that focus on Indonesia’s FD, particularly FD in Jakarta’s centralized wastewater network. This study aims to analyse the main sources and characteristics of wastewater that forms FD. Samples from two locations were used to compare the conditions of sewerage without FD and those with FD (A and B, respectively). Results showed that Padang restaurants and catering are the main sources of pollutants affecting FD formation. The FOG concentration in sample B was 2x107 times higher than in sample A, while the TSS concentration was 1.8x104 times higher. The dominant free fatty acid (FFA) in sample B was palmitic acid (51%), resulting in a dense precipitate structure and composition.
Development of scientific potential and introduction of innovative solutions to ensure competitiveness and further development of the agro-industrial complex of Russia
Authors: Zolkin Alexander L. , Matvienko Evgeny V. , Shmoilov Andrey N. , Rudnev Sergey G. , Urusova Avgustina B.
Published: February 2024

Appearance of a large number of modern, technological solutions in the field of agrarian complex of the Russian Federation, as well as the possibility of constant and rapid development of the potential of science in this area shall help the country in the development of this area as a whole. Of course, some unique features, signs of the challenges of the present shall be pointed out. They, as practice shows, have a significant impact on the entire system as a whole. Today it is important and necessary to be especially attentive to various trends and modern solutions. All this affects the development of the agrarian complex, which is important for Russia. Now it is required to point out some problems, as well as solutions in the field of technical, and most importantly, economic, scientific and professional development. If timely attention is not paid to key points, concepts and processes, then a completely unpleasant situation with all the negative consequences and phenomena may arise in the country in terms of studied direction.
The process of decomposition of tricalcium phosphate by phosphoric acid with partial replacement of P2O5 to sulfuric acid
Authors: Arislanov Akmaljon , Shamshidinov Israiljon , Usmanov Ilkham , Normatov Gayrat , Isomiddinov Oybek
Published: February 2024

The article covers the decomposition of tricalcium phosphate with thermal phosphoric acid with a concentration of 20, 30 and 40% P2O5 with the replacement of 10, 20 and 30% P2O5 with sulfuric acid and it has been established that, regardless of the content of ammonium nitrate, magnesium sulfate or their combined presence in phosphoric acid, with an increase in the proportion of sulfuric acid, the content of both total and aqueous forms of SO3 in the acidic pulp increases. The highest results of the decomposition coefficient were obtained when phosphoric acid was evaporated to a content of 32.22-25.77% P2O5 and 5.54-9.76% SO3. The SO3 content of both total and aqueous forms in dried products increases with increasing proportion of sulfuric acid. When the proportion of sulfuric acid increases to 20%, the degree of decomposition increases to 93.45% and to 99.55% when replacing 30% P2O5 with sulfuric acid.
Recipe development and quality assessment of enriched crispbreads
Authors: Skripko Olga
Published: February 2024

Modern technologies in the food industry are aimed at developing new types of food products that have the ability to influence human health; the consumption of these products helps prevent diseases, maintain health and longevity. The article presents the results of research on the creation of a new food ingredient from soybean grain, grape pomace and succinic acid. Joint processing of these raw materials makes it possible to obtain a soybean-grape protein-carbohydrate additive to enrich the chemical composition and increase the nutritional value of products. By means of mathematical modeling, the optimal parameters of the soybean-grape powder technology were established. A study of the chemical composition made it possible to establish that the powder contains a significant amount of vegetable protein - more than 22%, fat - more than 10%, carbohydrates - more than 46%, with a third of them being insoluble fractions - dietary fiber, and the additive also contains significant amounts of minerals substances and vitamins. These results made it possible to use the developed soybeangrape protein-carbohydrate powder as an enriching component of the crispbread recipe.
Intellectual control of the electrolysis process in the production of caustic soda
Authors: Yusupbekov Nodirbek , Sattarov Olim , Akhmatov Abdumalik , Nematov Maruf , Kosimboeva Mokhinur
Published: February 2024

This article is based on the modeling of the operating mode of the membrane electrolyzer in the production of caustic soda through a neural network. In the course of work, a neural network model of the operation of the electrolyzer element was developed. Neural network software was used to create and train neural networks. The purpose of this work is to create an accurate model of the electrolyzer element using the following tasks was to create: the process of designing optimal structures of neural networks and their training, creating an electrolyzer model by training neural networks, as well as processing the modeling results. As a result of this work, a neural network model was developed, which allows to quickly and accurately calculate the result of the operation of the electrolyzer under any initial conditions.
Improving the training of employees of logging enterprises in the field of labor protection
Authors: Sivakov Vladimir , Buglaev Anatoly , Zaikin Anatoliy , Orekhovskaya Alexandra , Nurullin Aidar , Razetdinov Ilgiz
Published: February 2024

The improvement of the traditional training system is currently relevant due to the complexity of technology and production processes, especially logging. Improving the effectiveness of training is possible due to the widespread use of digitalization of training. The purpose of the work is to determine the directions of application of new digital technologies to improve the effectiveness of training in the field of labor protection at logging enterprises. The use of electronic courses and multimedia technologies along with traditional training makes the learning process more informative, the use of electronic simulators and simulators allows you to work out practical working skills. The most modern teaching methods include the use of augmented and virtual reality technologies, artificial intelligence, which can significantly increase interest in learning and its effectiveness.
Numerical simulation of distribution of pollutant in channel
Authors: Gimaltdinov Ilyas K. , Stolpovskij Maxim V. , Kochanova Ekaterina Yu. , Nasyrov Azat A.
Published: February 2024

The paper presents the problem of the propagation of a pollutant (phenol) emission in a channel through which pure water flows. The mathematical model of the presented problem is based on the continuity equations. The distributions of the main parameters of the system are constructed. It is shown that in the absence of ledges, the pollutant flow moves in the channel in the form of a jet with a clearly defined core. In this case, the presence of ledges, due to the turbulence of the flow, leads to the emergence of rather large areas of pollution along the height of the channel. The dynamics of changes in the concentration of a pollutant along the height of the channel has been studied. It is shown that in the case of a working pollution source, the highest concentration is observed near the free surface of the channel. In the case when the source is not working, the highest concentration is observed at the bottom.
Features of static distributions of the mass of parts of rose hips
Authors: Abdurokhmonov Shavkatjon , Umirov Nashir , Ismaylov Kholiq
Published: February 2024

The article presents the need to use a systematic approach to assessing machine performance which is possible only on the basis of the widespread use of mathematical methods and electronic computing. Machines and experimental results on the distribution of masses of rose hips of the Rosa Conina variety and their parts (shell, seeds), as well as theoretical models in the form of analytical expressions that adequately describe the experimental data are described in the article.
Optimization of Window Design in Hospital Rooms for Effective Access to Daylight
Authors: Rodríguez Paula , Campano Miguel A. , Domníguez-Amarillo Samuel , Acosta Ignacio J.
Published: February 2024

Proper access to natural light entails a multitude of consequences for human beings, making it a highly significant aspect within the hospital setting. In consequence, it is imperative to undertake an appropriate optimization of windows in architectural design to reduce energy consumption and mitigate environmental impact, while concurrently enhancing the well-being of occupants. The aim of this study is to quantify the relative effectiveness in terms of energy consumption and natural lighting of hospital room windows, analyzing how a set of key design variables –size, proportion, position, and orientation– influence in one of the primary lighting dynamic metrics, Daylight Autonomy (DA). The results indicate that it is recommended to prioritize horizontal window designs over floor-to-ceiling alternatives, allocate a minimum area of 1.20m²to the south (greater on the north side), favor central positioning on the facade, and emphasize a southern orientation for optimal illumination.