bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on Soil Erosion Driving Forces by Using (R)USLE Framework and Machine Learning: A Case Study in Southwest China
Authors: Ge Yuankai , Zhao Longlong , Chen Jinsong , Li Xiaoli , Li Hongzhong , Wang Zhengxin , Ren Yanni
Published: March 2023

Soil erosion often leads to land degradation, agricultural production reduction, and environmental deterioration, which seriously restricts the sustainable development of regions. Clarifying the driving factors of soil erosion is the premise of preventing soil erosion. Given the lack of current research on the driving factors/force changes of soil erosion in different regions or under different erosion intensity grades, this paper pioneered to use machine learning methods to address this problem. Firstly, the widely used (Revised) Universal Soil Loss Equation ((R)USLE) framework was applied to simulate the spatial distribution of soil erosion. Then, the K-fold algorithm was used to evaluate the accuracy and stability of five machine learning algorithms for fitting soil erosion. The random forest (RF) method performed best, with average accuracy reaching 86.35%. Then, the Permutation Importance (PI) and the Partial Dependence Plot (PDP) methods based on RF were introduced to quantitatively analyze the main driving factors under different geological conditions and the driving force changes of each factor under different erosion intensity grades, respectively. Results showed that the main drivers of soil erosion in Chongqing and Guizhou were cover management factors (PI: 0.4672, 0.4788), while that in Sichuan was slope length and slope factor (PI: 0.6165). Under different erosion intensity grades, the driving force of each factor shows nonlinear and complex inhibitory or promoting effects with factor value changing. These findings can provide scientific guidance for the refined management of soil erosion, which is significant for halting or reversing land degradation and achieving sustainable use of land resources.
Analysis of the Effect of Soil Erosion in Abandoned Agricultural Areas: The Case of NE Area of Basilicata Region (Southern Italy)
Authors: Santarsiero Valentina , Lanorte Antonio , Nolè Gabriele , Cillis Giuseppe , Tucci Biagio , Murgante Beniamino
Published: March 2023

Land abandonment is among the most complex la nd use change processes driven by a multiplicity of anthropogenic and natural factors, such as agricultural over-exploitation, implementation of agricultural policies, socio-economic and climatic aspects. Therefore, it is necessary to deepen the effects of land abandonment based on methodologies that are as multidisciplinary as possible. Environmental and social problems related to abandonment include soil erosion and environmental degradation. Approaches combining GIS (Geographic Information System), remote sensing, and image analysis techniques allow for assessments and predictions based on integrating theoretical models with advanced geospatial and geostatistical models. One of the most widely used models for soil erosion estimation is the Revised Universal Soil Loss Equation (RUSLE). The present work developed a model using remote sensing and GIS tools to investigate some factors of the RUSLE equation to evaluate the adverse effects of soil erosion in areas covered by arable crops and subsequently abandoned. To identify potentially degraded areas, two factors of the RUSLE were related: the C Factor describing the vegetation cover of the soil and the A Factor representing the amount of potential soil erosion. Through statistical correlation analysis with the RUSLE factors, based on the deviations from the average erosion values and mapping of the areas of vegetation degradation relating to arable land, the areas identified and mapped are susceptible to soil degradation.
A Rare B-Myeloid Conversion of Follicular Lymphoma into Clonally Related Acute Myeloid Leukemia: A Case Report
Authors: Yan Xiyue , Liu Juan , Ben Yu , Zheng Weicheng , Hu Pan , Zhang Yaping , Shi Wenyu
Published: March 2023

Follicular lymphoma (FL) is a highly prevalent indolent lymphoma, and the risk of histological transformation is approximately 2–3% per year. Transformation of FL generally occurs in the same lineage (B cell lineage). Another rare form of disease progression is the transformation of neoplastic B-cells to another cell lineage such as acute myeloid leukemia (AML). The low incidence of B-myeloid transformation associated with poor prognosis hinders the establishment of model systems to identify molecular mechanisms. A 64-year-old woman was diagnosed with FL and achieved a satisfactory response after six cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone). Approximately one month after treatment terminated, the disease progressed to AML with an increased white blood cell count and abnormal coagulation. Interestingly, nucleotide sequence analysis of the genomic region encoding the immunoglobulin heavy-chain variable domain showed the possibility of homologous transformation from lymphoma to leukemia cells. Although the patient experienced transient improvement after undergoing treatment with one cycle of idarubicin and cytarabine combined with etoposide, she relapsed and died 8 days after venetoclax salvage therapy. Patient with B-myeloid transformation was associated with an aggressive clinical course and poor prognosis. Conventional strategies for treating histologically transformed AML were ineffective. However, treatment with a Bcl-2 inhibitor could serve as an option. Here we review the literature relevant to this rare histological transformation of FL.
Heavy Metals Levels in Soil, Water and Feed and Relation to Slaughtered Camels’ Tissues (Camelus dromedarius) from Five Districts in Saudi Arabia during Spring
Authors: Abdelrahman Mutassim M. , Alhidary Ibrahim A. , Matar Abdulkareem M. , Alobre Mohsen M. , Ayadi Moez , Aljumaah Riyadh S.
Published: March 2023

Soil, water, and forage contaminated with toxic heavy metals such as Pb, Cd, and Co can affect the meat and liver quality of camels raised in this area which affect human health. This study aimed to determine the concentrations of Pb, Cd and Co in soil, water, feed and young camels’ carcass tissues (meat, liver, whole blood, rumen fluid and rumen tissue) from five districts in Saudi Arabia during the spring. All samples were wet-digested and analyzed by ICP-OES for heavy metals. In the liver, a significantly higher (p < 0.05) concentration of Pb and Co was observed in camels reared in the central and southern districts, while Cd was found significantly higher in the western and northern districts. The concentration of Pb, Cd and Co in meat of camels in the northern district was significantly higher (p < 0.05), and the meat of camels in the west had a higher (p < 0.05) concentration of Co. In addition, the Cd and Co concentrations in rumen fluid samples from camels in the eastern district were significantly higher than in the central district. A negative correlation between the concentration of Pb and Cd in rumen fluid and rumen tissue was reported. The accumulation of Cd, Pb, and Co in meat and liver was below the recommended maximum limit. Therefore, the harmful risk of human consumption of camel meat and liver is not possible.
Experimental Investigations on Wear in Oscillating Grease-Lubricated Rolling Element Bearings of Different Size and Type
Authors: Bayer Gernot , Bartschat Arne , Wandel Sebastian , Baust Sebastian , Poll Gerhard
Published: March 2023

Grease-lubricated rolling element bearings can suffer from wear due to lubricant starvation under certain oscillating operating conditions. Especially for large-scale slewing bearings, such as blade bearings in wind turbines, experimental investigations are complex compared to small-scale reference testing. For an easier manner of testing, it is desirable to know whether the results of small-scale testing are applicable to larger-sized bearings. In this work, three different bearing types were tested and compared to already published results from a small-scale ACBB with a pitch diameter of 60 mm. The newly tested bearing types comprise a downscaled blade bearing (4-point contact double row ball bearing) with a pitch diameter of 673 mm, a small-scale CRTB with a pitch diameter of 77.5 mm and another ACBB with a pitch diameter of 95 mm. Qualitatively, all tested bearings show similar wear behaviour in terms of friction energy when operation parameters are varied. With higher oscillation frequency, damage becomes more severe. The oscillation amplitude shows three distinctive regimes. Within the range of small amplitudes, an increase in amplitude leads to more pronounced damage. We observe a threshold amplitude where this is no longer the case; a further increase in amplitude counteracts wear initiation until a final threshold is reached, beyond which no more wear is observed. These findings are in accordance with the reference results of the small-scale ACBB. Direct comparison between point and line contact shows that the latter is more prone to wear initiation under grease-lubricated, oscillating operating conditions. Furthermore, a previously introduced empirical number shows good performance in assessing critical operating parameters of the different bearing types. Specifically, harmful operating conditions can be classified for all studied bearing types with an accuracy of 78%. This method can be useful to assess operating conditions of greased, oscillating, rolling element bearings, e.g., to assess different pitch controllers or designs of slewing bearings.
Recent Advances in Multi-Site Luminescent Materials: Design, Identification and Regulation
Authors: Tian Junhang , Xie Jihuan , Zhuang Weidong
Published: March 2023

The development of novel phosphor materials with excellent performance and modification of their photoluminescence to meet the higher requirements for applications are the essential research subjects for luminescent materials. Multi-site luminescent materials with crystallographic sites for the activator ions that broaden the tunable range of luminescent spectra and even enhance the luminescent performance have attracted significant attention in the pursuit of high-quality luminescence for white light-emitting diodes. Here, we summarize multi-site luminescence characteristics based on the different kinds of host and activator ions, introduce the identifications of multi-site activator ions via optical analysis, provide a structural analysis and theoretical calculation methods, and introduce the regulation strategies and advance applications of multi-site phosphors. The review reveals the relationship between crystal structure and luminescent properties and discusses future opportunities for multi-site phosphors. This will provide guidance for the design and development of luminescent materials or other materials science.
Metrological Aspects of Assessing Surface Topography and Machining Accuracy in Diagnostics of Grinding Processes
Authors: Kacalak Wojciech , Lipiński Dariusz , Szafraniec Filip , Wieczorowski Michał , Twardowski Paweł
Published: March 2023

The paper presents probabilistic aspects of diagnostics of grinding processes with consideration of metrological aspects of evaluation of topography of machined surfaces and selected problems of assessment of machining accuracy. The processes of creating the geometric structure of the ground surface are described. It was pointed out that the distribution of features important for process diagnostics depends on the mechanism of cumulative effects of random disturbances. Usually, there is a multiplicative mechanism or an additive mechanism of the component vectors of relative displacements of the tool and workpiece. The paper describes a method for determining the classification ability of specific parameters used to evaluate stereometric features of ground surfaces. It is shown that the ability to differentiate the geometric structure of a certain set of surfaces using a selected parameter depends on the geometric mean of the differences in normalized and sorted, consecutive values of this parameter. A methodology is presented for evaluating the ability of various parameters to distinguish different geometric structures of surfaces. Further, on the basis of analyses of a number of grinding processes, a methodology was formulated for proceeding leading to a comprehensive evaluation of machining accuracy and forecasting its results. It was taken into account that in forecasting the accuracy of grinding, it is necessary to determine the deviations, arising under the conditions of multiplicative interaction of the effects of various causes of inaccuracy. Examples are given of processes in which, due to the deformation of the technological system, dependent on the position of the zone and machining force, varying temperature fields and tool wear, the distributions of dimensional deviations are not the realization of stationary processes. It was emphasized that on the basis of the characteristics of the dispersion of the deviation value in the sum set of elements, it is not possible to infer its causes. Only the determination of the “instantaneous” values of the deviation dispersion parameters allows a more complete diagnosis of the process.
Circular Recycling Strategies for LFP Batteries: A Review Focusing on Hydrometallurgy Sustainable Processing
Authors: Vasconcelos David da Silva , Tenório Jorge Alberto Soares , Botelho Junior Amilton Barbosa , Espinosa Denise Crocce Romano
Published: March 2023

The exponential growth of electric and hybrid vehicles in the last five years forecasts a waste problem when their batteries achieve end-of-life. Li-ion batteries for vehicles have been assembled using materials from natural resources (as Li, Fe, Al, Cu Co, Mn and P). Among them, LiFePO4 cathode materials have demonstrated advantages such as charge–discharge cycles, thermal stability, surface area and raw materials availability (against Ni and Co systems). Due to the performance, LFP batteries stand out in heavy duty fleet, achieving 90% of new energy buses in China. To achieve the circular economy, the recycling of LFP batteries may be carried out by pyrometallurgy (thermal processing), hydrometallurgy (aqueous processing) or both in combination. Comparatively, hydrometallurgical processing is more advantageous due to its low energy consumption and CO2 emissions. In addition, Li may be recovered in a high-pure grade. This work is a literature review of the current alternatives for the recycling of LFP batteries by hydrometallurgy, comparing designed processes in the literature and indicating solutions towards a circular economy. The major recycling steps of hydrometallurgy routes such as pre-treatments, leaching and purification steps will be gathered and discussed in terms of efficiency and environmental impact.
Mendelian Randomization Analysis Provides Insights into the Pathogenesis of Serum Levels of Branched-Chain Amino Acids in Cardiovascular Disease
Authors: Jiang Wenxi , Lu Ke , Zhuang Zhenhuang , Wang Xue , Tang Xun , Huang Tao , Gao Pei , Wang Yuan , Du Jie
Published: March 2023

Several observational studies have indicated an association between high serum levels of branched-chain amino acids (BCAAs) and an increased risk of cardiovascular disease (CVD). To assess whether theses associations reflect causality, we carried out two-sample Mendelian randomization (MR). Single-nucleotide polymorphisms (SNPs) associated with BCAA were evaluated in 10 studies, including 24,925 participants. The association between SNPs and coronary artery disease (CAD) were assessed using summary estimates from the CARDIoGRAMplusC4D consortium. Further MR analysis of BCAAs and seven CVD outcomes was performed. The BCAA-raising gene functions were also analyzed. MR analyses revealed a risk-increasing causal relationship between serum BCAA concentrations and CAD (odds ratio 1.08; 95% confidence interval (CI) 1.02–1.14), which was partly mediated by blood pressure and type 2 diabetes. BCAA also demonstrated a causal relationship with ischemic CVD events induced by plaque rupture and thrombosis (false discovery rate <0.05). Two BCAA-raising genes (MRL33 and CBLN1) were preferentially associated with myocardial infarction risk in the presence of atherosclerosis (p < 0.003). Functional analysis of the BCAA-raising genes suggested the causal involvement of two pathophysiological pathways, including glucose metabolism (PPM1K and TRMT61A) related to plaque progression, and the newly discovered neuroendocrine disorders regulating blood pressure (MRPL33, CBLN1, and C2orf16) related to plaque rupture and thrombosis. This comprehensive MR analysis provided insights into the potential causal mechanisms linking BCAA with CVD risk and suggested targeting neuroendocrine disorders as a potential strategy for the prevention of CVD. These results warrant further studies to elucidate the mechanisms underlying these reported causal associations.
Selective Detection of Escherichia coli K12 and Staphylococcus aureus in Mixed Bacterial Communities Using a Single-Walled Carbon Nanotube (SWCNT)-Functionalized Electrochemical Immunosensor with Dielectrophoretic Concentration
Authors: Lee Inae , So Heejin , Kim Jungyoon , Auh Joong-Hyuck , Wall Marisa M. , Li Yong , Ho Kacie , Jun Soojin
Published: March 2023

An electrochemical immunosensor has been developed for the rapid detection and identification of potentially harmful bacteria in food and environmental samples. This study aimed to fabricate a microwire-based electrochemical immunosensor (MEI sensor) for selective detection of Escherichia coli and Staphylococcus aureus in microbial cocktail samples using dielectrophoresis (DEP)-based cell concentration. A gold-coated tungsten microwire was functionalized by coating polyethylenimine, single-walled carbon nanotube (SWCNT) suspension, streptavidin, biotinylated antibodies, and then bovine serum albumin (BSA) solutions. Double-layered SWCNTs and 5% BSA solution were found to be optimized for enhanced signal enhancement and nonspecific binding barrier. The selective capture of E. coli K12 or S. aureus cells was achieved when the electric field in the bacterial sample solution was generated at a frequency of 3 MHz and 20 Vpp. A linear trend of the change in the electron transfer resistance was observed as E. coli concentrations increased from 5.32 × 102 to 1.30 × 108 CFU/mL (R2 = 0.976). The S. aureus MEI sensor fabricated with the anti-S. aureus antibodies also showed an increase in resistance with concentrations of S. aureus (8.90 × 102–3.45 × 107 CFU/mL) with a correlation of R2 = 0.983. Salmonella typhimurium and Listeria monocytogenes were used to evaluate the specificity of the MEI sensors. The functionalization process developed for the MEI sensor is expected to contribute to the sensitive and selective detection of other harmful microorganisms in food and environmental industries.
Water Content of Plant Tissues: So Simple That Almost Forgotten?
Authors: Ievinsh Gederts
Published: March 2023

The aim of the present review was to reconsider basic information about various functional aspects related to plant water content and provide evidence that the usefulness of measuring absolute water content in plant sciences is undervalued. First, general questions about water status in plants as well as methods for determining water content and their associated problems were discussed. After a brief overview of the structural organization of water in plant tissues, attention was paid to the water content of different parts of plants. Looking at the influence of environmental factors on plant water status, the differences caused by air humidity, mineral supply, biotic effects, salinity, and specific life forms (clonal and succulent plants) were analyzed. Finally, it was concluded that the expression of absolute water content on a dry biomass basis makes easily noticeable functional sense, but the physiological meaning and ecological significance of the drastic differences in plant water content need to be further elucidated.
Effect of Three Boron Concentrations in Soil on Growth and Physiology in Sweet Cherry Trees
Authors: Arredondo Gerardo , Bonomelli Claudia
Published: March 2023

Boron (B) is an essential element for plants. B availability depends on the physical and chemical characteristics of the soil and the quality of irrigation water. Under natural conditions, both toxic and deficit concentrations can occur and should be managed for crop production. However, the range between deficiency and toxicity is narrow. The objective of this study was to determine the response of cherry trees to deficient (0.04 mg kg−1), adequate (1.1 mg kg−1), and toxic (3.75 mg kg−1) B concentrations in the soil by measuring growth, biomass, photosynthetic parameters, visual symptoms, and morphological changes. Plants treated with a toxic dose had more spurs and shorter internodes than those treated with adequate and deficient doses. The white root weight (50.5 g) at low B concentrations had the most roots compared with the adequate (33.0 g) and toxic (22.0 g) concentrations. The stem weight and biomass partitioning were higher for white roots and stems at B-deficient and -adequate doses than at toxic doses. The net photosynthesis (Pn) and transpiration rate (E) were significantly higher in plants with adequate concentrations of B. Stomatal conductance (Gs) was higher in B-deficient plants. Morphological and visual differences were observed between treatments. The results showed that it is essential to adequately manage B in cherry crops to avoid the adverse effects of both low and toxic concentrations.
General-Purpose Deep Learning Detection and Segmentation Models for Images from a Lidar-Based Camera Sensor
Authors: Yu Xianjia , Salimpour Sahar , Queralta Jorge Peña , Westerlund Tomi
Published: March 2023

Over the last decade, robotic perception algorithms have significantly benefited from the rapid advances in deep learning (DL). Indeed, a significant amount of the autonomy stack of different commercial and research platforms relies on DL for situational awareness, especially vision sensors. This work explored the potential of general-purpose DL perception algorithms, specifically detection and segmentation neural networks, for processing image-like outputs of advanced lidar sensors. Rather than processing the three-dimensional point cloud data, this is, to the best of our knowledge, the first work to focus on low-resolution images with a 360° field of view obtained with lidar sensors by encoding either depth, reflectivity, or near-infrared light in the image pixels. We showed that with adequate preprocessing, general-purpose DL models can process these images, opening the door to their usage in environmental conditions where vision sensors present inherent limitations. We provided both a qualitative and quantitative analysis of the performance of a variety of neural network architectures. We believe that using DL models built for visual cameras offers significant advantages due to their much wider availability and maturity compared to point cloud-based perception.
Measurement and Processing of Thermographic Data of Passing Persons for Epidemiological Purposes
Authors: Tesař Jiří , Muzika Lukáš , Skála Jiří , Kohlschütter Tomáš , Honner Milan
Published: March 2023

Non-contact temperature measurement of persons during an epidemic is the most preferred measurement option because of the safety of personnel and minimal possibility of spreading infection. The use of infrared (IR) sensors to monitor building entrances for infected persons has seen a major boom between 2020 and 2022 due to the COVID-19 epidemic, but with questionable results. This article does not deal with the precise determination of the temperature of an individual person but focuses on the possibility of using infrared cameras for monitoring the health of the population. The aim is to use large amounts of infrared data from many locations to provide information to epidemiologists so they can have better information about potential outbreaks. This paper focuses on the long-term monitoring of the temperature of passing persons inside public buildings and the search for the most appropriate tools for this purpose and is intended as the first step towards creating a useful tool for epidemiologists. As a classical approach, the identification of persons based on their characteristic temperature values over time throughout the day is used. These results are compared with the results of a method using artificial intelligence (AI) to evaluate temperature from simultaneously acquired infrared images. The advantages and disadvantages of both methods are discussed.
IoT-Enabled WBAN and Machine Learning for Speech Emotion Recognition in Patients
Authors: Olatinwo Damilola D. , Abu-Mahfouz Adnan , Hancke Gerhard , Myburgh Hermanus
Published: March 2023

Internet of things (IoT)-enabled wireless body area network (WBAN) is an emerging technology that combines medical devices, wireless devices, and non-medical devices for healthcare management applications. Speech emotion recognition (SER) is an active research field in the healthcare domain and machine learning. It is a technique that can be used to automatically identify speakers’ emotions from their speech. However, the SER system, especially in the healthcare domain, is confronted with a few challenges. For example, low prediction accuracy, high computational complexity, delay in real-time prediction, and how to identify appropriate features from speech. Motivated by these research gaps, we proposed an emotion-aware IoT-enabled WBAN system within the healthcare framework where data processing and long-range data transmissions are performed by an edge AI system for real-time prediction of patients’ speech emotions as well as to capture the changes in emotions before and after treatment. Additionally, we investigated the effectiveness of different machine learning and deep learning algorithms in terms of performance classification, feature extraction methods, and normalization methods. We developed a hybrid deep learning model, i.e., convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), and a regularized CNN model. We combined the models with different optimization strategies and regularization techniques to improve the prediction accuracy, reduce generalization error, and reduce the computational complexity of the neural networks in terms of their computational time, power, and space. Different experiments were performed to check the efficiency and effectiveness of the proposed machine learning and deep learning algorithms. The proposed models are compared with a related existing model for evaluation and validation using standard performance metrics such as prediction accuracy, precision, recall, F1 score, confusion matrix, and the differences between the actual and predicted values. The experimental results proved that one of the proposed models outperformed the existing model with an accuracy of about 98%.
Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations
Authors: AL-Jumaili Ahmed Hadi Ali , Muniyandi Ravie Chandren , Hasan Mohammad Kamrul , Paw Johnny Koh Siaw , Singh Mandeep Jit
Published: March 2023

Traditional parallel computing for power management systems has prime challenges such as execution time, computational complexity, and efficiency like process time and delays in power system condition monitoring, particularly consumer power consumption, weather data, and power generation for detecting and predicting data mining in the centralized parallel processing and diagnosis. Due to these constraints, data management has become a critical research consideration and bottleneck. To cope with these constraints, cloud computing-based methodologies have been introduced for managing data efficiently in power management systems. This paper reviews the concept of cloud computing architecture that can meet the multi-level real-time requirements to improve monitoring and performance which is designed for different application scenarios for power system monitoring. Then, cloud computing solutions are discussed under the background of big data, and emerging parallel programming models such as Hadoop, Spark, and Storm are briefly described to analyze the advancement, constraints, and innovations. The key performance metrics of cloud computing applications such as core data sampling, modeling, and analyzing the competitiveness of big data was modeled by applying related hypotheses. Finally, it introduces a new design concept with cloud computing and eventually some recommendations focusing on cloud computing infrastructure, and methods for managing real-time big data in the power management system that solve the data mining challenges.
A Novel Dielectric Modulated Gate-Stack Double-Gate Metal-Oxide-Semiconductor Field-Effect Transistor-Based Sensor for Detecting Biomolecules
Authors: Chowdhury Dibyendu , De Bishnu Prasad , Appasani Bhargav , Singh Navaneet Kumar , Kar Rajib , Mandal Durbadal , Bizon Nicu , Thounthong Phatiphat
Published: March 2023

In this article, the performance of n-type junctionless (JL) double-gate (DG) MOSFET-based biosensors with and without gate stack (GS) has been studied. Here, the dielectric modulation (DM) method is applied to detect biomolecules in the cavity. The sensitivity of n-type JL-DM-DG-MOSFET and n-type JL-DM-GSDG-MOSFET-based biosensors have also been evaluated. The sensitivity (ΔVth) improved in JL-DM-GSDG MOSFET/JL-DM-DG-MOSFET-based biosensors for neutral/charged biomolecules is 116.66%/66.66% and 1165.78%/978.94%, respectively, compared with the previously reported results. The electrical detection of biomolecules is validated using the ATLAS device simulator. The noise and analog/RF parameters are compared between both biosensors. A lower threshold voltage is observed in the GSDG-MOSFET-based biosensor. The Ion/Ioff ratio is higher for DG-MOSFET-based biosensors. The proposed GSDG-MOSFET-based biosensor demonstrates higher sensitivity than the DG-MOSFET-based biosensor. The GSDG-MOSFET-based biosensor is suitable for low-power, high-speed, and high sensitivity applications.
Towards Embedded Electrochemical Sensors for On-Site Nitrite Detection by Gold Nanoparticles Modified Screen Printed Carbon Electrodes
Authors: Adiraju Anurag , Munjal Rohan , Viehweger Christian , Al-Hamry Ammar , Brahem Amina , Hussain Jawaid , Kommisetty Sanhith , Jalasutram Aditya , Tegenkamp Christoph , Kanoun Olfa
Published: March 2023

The transition of electrochemical sensors from lab-based measurements to real-time analysis requires special attention to different aspects in addition to the classical development of new sensing materials. Several critical challenges need to be addressed including a reproducible fabrication procedure, stability, lifetime, and development of cost-effective sensor electronics. In this paper, we address these aspects exemplarily for a nitrite sensor. An electrochemical sensor has been developed using one-step electrodeposited (Ed) gold nanoparticles (EdAu) for the detection of nitrite in water, which shows a low limit of detection of 0.38 µM and excellent analytical capabilities in groundwater. Experimental investigations with 10 realized sensors show a very high reproducibility enabling mass production. A comprehensive investigation of the sensor drift by calendar and cyclic aging was carried out for 160 cycles to assess the stability of the electrodes. Electrochemical impedance spectroscopy (EIS) shows significant changes with increasing aging inferring the deterioration of the electrode surface. To enable on-site measurements outside the laboratory, a compact and cost-effective wireless potentiostat combining cyclic and square wave voltammetry, and EIS capabilities has been designed and validated. The implemented methodology in this study builds a basis for the development of further on-site distributed electrochemical sensor networks.
Remote Blood Pressure Estimation via the Spatiotemporal Mapping of Facial Videos
Authors: Chen Yuheng , Zhuang Jialiang , Li Bin , Zhang Yun , Zheng Xiujuan
Published: March 2023

Blood pressure (BP) monitoring is vital in daily healthcare, especially for cardiovascular diseases. However, BP values are mainly acquired through a contact-sensing method, which is inconvenient and unfriendly for BP monitoring. This paper proposes an efficient end-to-end network for estimating BP values from a facial video to achieve remote BP estimation in daily life. The network first derives a spatiotemporal map of a facial video. Then, it regresses the BP ranges with a designed blood pressure classifier and simultaneously calculates the specific value with a blood pressure calculator in each BP range based on the spatiotemporal map. In addition, an innovative oversampling training strategy was developed to handle the problem of unbalanced data distribution. Finally, we trained the proposed blood pressure estimation network on a private dataset, MPM-BP, and tested it on a popular public dataset, MMSE-HR. As a result, the proposed network achieved a mean absolute error (MAE) and root mean square error (RMSE) of 12.35 mmHg and 16.55 mmHg on systolic BP estimations, and those for diastolic BP were 9.54 mmHg and 12.22 mmHg, which were better than the values obtained in recent works. It can be concluded that the proposed method has excellent potential for camera-based BP monitoring in the indoor scenarios in the real world.
Design Consideration, Numerical and Experimental Analyses of Mode-Division-Multiplexed (MDM) Silicon Photonics Integrated Circuit with Sharp Bends
Authors: Kuo Pin-Cheng , Chow Chi-Wai , Lin Yuan-Zeng , Gunawan Wahyu Hendra , Hung Tun-Yao , Jian Yin-He , Chen Guan-Hong , Peng Ching-Wei , Liu Yang , Yeh Chien-Hung
Published: March 2023

Due to the popularity of different high bandwidth applications, it is becoming increasingly difficult to satisfy the huge data capacity requirements, since the traditional electrical interconnects suffer significantly from limited bandwidth and huge power consumption. Silicon photonics (SiPh) is one of the important technologies for increasing interconnect capacity and decreasing power consumption. Mode-division multiplexing (MDM) allows signals to be transmitted simultaneously, at different modes, in a single waveguide. Wavelength-division multiplexing (WDM), non-orthogonal multiple access (NOMA) and orthogonal-frequency-division multiplexing (OFDM) can also be utilized to further increase the optical interconnect capacity. In SiPh integrated circuits, waveguide bends are usually inevitable. However, for an MDM system with a multimode bus waveguide, the modal fields will become asymmetric when the waveguide bend is sharp. This will introduce inter-mode coupling and inter-mode crosstalk. One simple approach to achieve sharp bends in multimode bus waveguide is to use a Euler curve. Although it has been reported in the literature that sharp bends based on a Euler curve allow high performance and low inter-mode crosstalk multimode transmissions, we discover, by simulation and experiment, that the transmission performance between two Euler bends is length dependent, particularly when the bends are sharp. We investigate the length dependency of the straight multimode bus waveguide between two Euler bends. High transmission performance can be achieved by a proper design of the waveguide length, width, and bend radius. By using the optimized MDM bus waveguide length with sharp Euler bends, proof-of-concept NOMA-OFDM experimental transmissions, supporting two MDM modes and two NOMA users, are performed.
Recent Developments in Haptic Devices Designed for Hearing-Impaired People: A Literature Review
Authors: Flores Ramones Alejandro , del-Rio-Guerra Marta Sylvia
Published: March 2023

Haptic devices transmit information to the user, using tactile stimuli to augment or replace sensory input. People with limited sensory abilities, such as vision or hearing can receive supplementary information by relying on them. This review analyses recent developments in haptic devices for deaf and hard-of-hearing individuals by extracting the most relevant information from each of the selected papers. The process of finding relevant literature is detailed using the PRISMA guidelines for literature reviews. In this review, the devices are categorized to better understand the review topic. The categorization results have highlighted several areas of future research into haptic devices for hearing-impaired users. We believe this review may be useful to researchers interested in haptic devices, assistive technologies, and human–computer interaction.
“Frankly, My Dear, I Don’t Want a Dam” in the US or in Iran: Environmental Movements and Shared Strategies in Differing Political Economies
Authors: Hoominfar Elham , Radel Claudia
Published: March 2023

In this comparative study, we explore why environmental movements against two neoliberal water transfer projects emerged and how they work in different political economies—a hegemonic capitalist democracy (Colorado, US) and a centralized authoritarian capitalist system (Iran). We apply Polanyi’s and Gramsci’s political–economic theories, using interviews and document analysis to examine and compare movement framing and mobilization and resistance strategies and tactics through this lens. The existing social movement literature leads us to expect fundamental differences, but although we find some differences, particularly in tactics, we find that these environmental movements have unexpected similarities in terms of framing and resistance strategies. Additionally, in both cases, outcomes remain uncertain despite the ostensibly large differences in political opportunities. In Colorado, project developers and social protesters may reach a compromise agreement through the civil society channel of the courts. In Iran, with a centralized state suppressing opponents whereas the project threatens local people’s livelihoods, the environmental movement has assumed a more radical face.
Can the Opening of High-Speed Railway Restrain Corporate Financialization?
Authors: Zhu Ruo-Yu , Tan Ke-Hu , Xin Xiao-Hui
Published: March 2023

Under the background of the economy “shifting from real to virtual”, how to guide real enterprises to return to their main businesses has become an urgent problem to be solved in the stage of microeconomic bodies moving toward high-quality development. Based on the perspective of the opening of high-speed railway (HSR), this paper builds a time-varying DID model to systematically test the relationship between HSR and corporate financialization by matching the data of HSR among 286 cities in China with the data of A-share non-financial companies listed in the Shanghai and Shenzhen stock markets. The results showed that there is a significant negative correlation between HSR and corporate financialization, i.e., the opening of HSR can significantly inhibit corporate financialization. This conclusion still holds after a series of robustness tests. Mechanism analysis found that the opening of HSR can restrain corporate financialization through “crowding-out effects” and “liquidity replenishment effects”. Heterogeneity analysis showed that the inhibitory effect of HSR on corporate financialization is more significant in large enterprises, fiercely competitive industries, and cities with high initial transportation resources. This paper deeply explored the relationship between the opening of HSR and corporate financialization, which not only enriches the existing literature but also provides a useful reference for guiding real enterprises to actively return to their main businesses.
Levels of Neutralizing Antibodies against SARS-CoV-2 in Mothers and Neonates after Vaccination during Pregnancy
Authors: da Silva Filho Antônio Oliveira , Gonçalves Daniel Nazário , de Lima Letícia Karina Ramos , da Silva Alves Dâmocles Aurélio Nascimento , de Andrade Falcão Felipe José , Falcão Rosângela Estevão Alves
Published: March 2023

Background: Maternal vaccination is safe and provides protection against COVID-19 in mothers and neonates, and it is necessary to evaluate its effect on the induction of immune responses through the levels of neutralizing antibodies present in maternal and neonatal blood. Methods: An observational study with transversal analysis was carried out. Included in the research were neonates (<1 month) whose mothers had been immunized whilst pregnant with at least one dose of the vaccine BNT16b and had not shown any symptoms of COVID-19. The blood of the mothers and newborns was collected during the Guthrie test and sent to the laboratory for the detection of neutralizing antibodies against SARS-CoV-2. Results: A total of 162 pairs of mothers and neonates were analyzed with an average age of 26.3 ± 5.97 years and 13.4 ± 6.90 days, respectively. All samples collected present neutralizing antibodies with an average percentage of 91% in the mothers and 92% in the neonates. The most satisfactory immune response was observed in neonates and mothers vaccinated during the second trimester of gestation. Conclusions: The vaccination of expectant mothers with the immunizer BNT162b2 has promoted a robust immunological response in both the mothers and the neonates.
Evaluating primary care transformation: synthesis of findings from UK pilot project reviews
Authors: McSwiggan Emilie , Ng Lauren , Donaghy Eddie , Huang Huayi , Gillies John , Henderson David AG , Thompson Andrew , Wang Harry HX , Mercer Stewart W
Published: March 2023

Background

Pilot 'new models' of primary care have been funded across the UK since 2015, through various national transformation funds. Reflections and syntheses of evaluation findings provide an additional layer of insight into 'what works' in transforming primary care.

Aim

To identify good practice in policy design, implementation, and evaluation for primary care transformation.

Design & setting

A thematic analysis of existing pilot evaluations in England, Wales, and Scotland.

Method

Ten studies presenting evaluations of three national pilot studies — the Vanguard programme in England, the Pacesetter programme in Wales, and the National Evaluation of New Models of Primary Care in Scotland — were thematically analysed, and findings synthesised in order to identify lessons learnt and good practice.

Results

Common themes emerged across studies in all three countries at project and policy level, which can support or inhibit new models of care. At project level, these included the following: working with all stakeholders, including communities and front-line staff; providing the time, space, and support necessary for the project to succeed; agreeing on clear objectives from the outset; and support for data collection, evaluation, and shared learning. At policy level, more fundamental challenges related to the parameters for pilot projects, in particular, the typically short-term nature of funding, with an expectation of results within 2–3 years. Changing expectations about outcome measures or project guidance part-way through project implementation was also identified as a key challenge.

Conclusion

Primary care transformation requires coproduction and a rich, contextual understanding of local needs and complexities. However, a mismatch between policy objectives (care redesign to better meet patient needs) and policy parameters (short timeframes) is often a significant challenge to success.
DETERMINISTIC FINITE STATE MACHINE FOR SEARCH OF CONTAINERS IN STACK
Authors: Malikova T. , Solov'eva E. , Radochinskaya A.
Published: March 2023

This paper considers the prospects of digitalization in the warehouse cargo handlingsystem, as well as the

impact of modern IT technologies on the logistics of a sea container terminal. The technological process of

container transshipment in the operational areas of the terminal and formation of auxiliary stacks for further

transfer of cargo between different transport means, their temporary storage and transformation (from containerized

form to general cargo and back), as well as the implementation of secondary operations (checking,

weighing, etc.) are the object of research. From an operational point of view, the formation of an auxiliary stack

is a time-taking technological operation, as it requires the selective search and withdrawal from the general

stack of a certain number of containers that make up the logistic flow of cargo moved to the relevant operational

zone. The method of research is automatic programming of the simulated technological process. In this case,

the simulation object is described by a finite automaton which is then converted into code. The main purpose

of the automaton is to implement the control function. In the context of this research work, the control actions

are aimed at the reloader and program the sequence of its actions to find the target containers in the stack. A

mathematical model of the search and withdrawal of the target containers from the stack in the terminal storage

area by means of a computerized control system, as well as a transition graph of the finite automaton with

control rules (codes) are the results of this research. The application of above mathematical facility to modeling

of technological processes makes it possible to present a unified logic of management of the prestacking process

in operational areas of the terminal
The struggle for Pokuttya and the polish-moldovan war 1506-1510
Authors: Balukh Oleksii ,   Yuriy Fedkovych Chernivtsi National University
Published: March 2023

The struggle for Pokuttya between Poland and Moldova has been going on with varying degrees of success for four decades. It all started during the reign of the Moldavian voivode Stephen III. In 1491 he marched on Pokuttya, trying to annex it to his state. He managed to do it. However, only for a while. The next attempt to return the Penance was made by Stephen the Great ten years later, in 1502. She was successful. However, on July 2, 1504, the voivode died. The son of Stephen III Bogdan, later nicknamed the Blind, became the ruler of Moldavia. And already in 1505 he returned Pokuttya to Poland. His goal was to marry the sister of King Alexander I of Poland, Elizabeth Jagiellonian. In 1506 Alexander Jagiellonian died. The king was his younger brother Sigismund I the Elder, who abandoned the planned alliance. This has led to a sharp deterioration in relations with Moldova. Therefore, in August 1506 Pokuttya was captured by the troops of Bohdan III. The Polish army under the command of S. Khodetsky and M. Kamenetsky drove the Moldavians out of Pokuttya, and later defeated their army near Chernivtsi. Taking advantage of the participation of King Sigismund I's troops in the Second Lithuanian-Moscow War, on June 29, 1509, Bohdan III began a campaign in Pokuttya, Podillya and the Ruthenian Voivodeship. In particular, the Moldovan army laid siege to Kamyanets, Halych, Lviv and Rohatyn. However, the campaign ended in failure. None of these cities was taken. The answer was not long in coming. The Polish army under the leadership of the Grand Crown Hetman M. Kamenetsky devastated several Moldavian cities across the Dniester. On their way out, near Khotyn, on October 4, the Poles were attacked by the Moldavian army, but the long battle did not reveal a winner. Therefore, on January 23, 1510, a peace treaty was signed. As a result of the signing of the Polish-Moldavian peace treaty of 1510, the war between Poland and Moldavia was ended, conflicts were settled, and hospodar Bogdan III received Poland and Hungary as allies. However, Pokuttya remained part of Poland.