bluuebunny/crossref_metadata_2025 huggingface dataset:
A Research on Manipulator-Path Tracking Based on Deep Reinforcement Learning
Authors: Zhang Pengyu , Zhang Jie , Kan Jiangming
Published: July 2023

The continuous path of a manipulator is often discretized into a series of independent action poses during path tracking, and the inverse kinematic solution of the manipulator’s poses is computationally challenging and yields inconsistent results. This research suggests a manipulator-route-tracking method employing deep-reinforcement-learning techniques to deal with this problem. The method of this paper takes an end-to-end-learning approach for closed-loop control and eliminates the process of obtaining the inverse answer by converting the path-tracking task into a sequence-decision issue. This paper first explores the feasibility of deep reinforcement learning in tracking the path of the manipulator. After verifying the feasibility, the path tracking of the multi-degree-of-freedom (multi-DOF) manipulator was performed by combining the maximum-entropy deep-reinforcement-learning algorithm. The experimental findings demonstrate that the approach performs well in manipulator-path tracking, avoids the need for an inverse kinematic solution and a dynamics model, and is capable of performing manipulator-tracking control in continuous space. As a result, this paper proposes that the method presented is of great significance for research on manipulator-path tracking.
Novel Object Captioning with Semantic Match from External Knowledge
Authors: Du Sen , Zhu Hong , Lin Guangfeng , Wang Dong , Shi Jing
Published: July 2023

Automatically describing the content of an image is a challenging task that is on the edge between natural language and computer vision. The current image caption models can describe the objects that are frequently seen in the training set very well, but they fail to describe the novel objects that are rarely seen or never seen in the training set. Despite describing novel objects being important for practical applications, only a few works investigate this issue. Furthermore, those works only investigate rarely seen objects, but ignore the never-seen objects. Meanwhile, the number of never-seen objects is more than the number of frequently seen and rarely seen objects. In this paper, we propose two blocks that incorporate external knowledge into the captioning model to solve this issue. Initially, in the encoding phase, the Semi-Fixed Word Embedding block is an improvement for the word embedding layer that enables the captioning model to understand the meaning of the arbitrary visual words rather than a fixed number of words. Furthermore, the Candidate Sentences Selection block chooses candidate sentences by semantic matching rather than probability, avoiding the influence of never-seen words. In experiments, we qualitatively analyze the proposed blocks and quantitatively evaluate several captioning models with the proposed blocks on the Nocaps dataset. The experimental results show the effectiveness of the proposed blocks for novel objects, especially when describing never-seen objects, CIDEr and SPICE improved by 13.1% and 12.0%, respectively.
Detection of Software Security Weaknesses Using Cross-Language Source Code Representation (CLaSCoRe)
Authors: Zaharia Sergiu , Rebedea Traian , Trausan-Matu Stefan
Published: July 2023

The research presented in the paper aims at increasing the capacity to identify security weaknesses in programming languages that are less supported by specialized security analysis tools, based on the knowledge gathered from securing the popular ones, for which security experts, scanners, and labeled datasets are, in general, available. This goal is vital in reducing the overall exposure of software applications. We propose a solution to expand the capabilities of security gaps detection to downstream languages, influenced by their more popular “ancestors” from the programming languages’ evolutionary tree, using language keyword tokenization and clustering based on word embedding techniques. We show that after training a machine learning algorithm on C, C++, and Java applications developed by a community of programmers with similar behavior of writing code, we can detect, with acceptable accuracy, similar vulnerabilities in C# source code written by the same community. To achieve this, we propose a core cross-language representation of source code, optimized for security weaknesses classifiers, named CLaSCoRe. Using this method, we can achieve zero-shot vulnerability detection—in our case, without using any training data with C# source code.
Average Turbulence Dynamics from a One-Parameter Kinetic Theory
Authors: Chen Hudong , Staroselsky Ilya , Sreenivasan Katepalli R. , Yakhot Victor
Published: July 2023

We show theoretically that the mean turbulent dynamics can be described by a kinetic theory representation with a single free relaxation time that depends on space and time. A proper kinetic equation is constructed from the Klimontovich-type kinetic equation for fluid elements, which satisfies the Navier–Stokes hydrodynamics exactly. In a suitably averaged form, the turbulent kinetic energy plays the role of temperature in standard molecular thermodynamics. We show that the dynamics of turbulent fluctuations resembles a collision process that asymptotically drives the mean distribution towards a Gaussian (Maxwell–Boltzmann) equilibrium form. Non-Gaussianity arises directly from non-equilibrium shear effects. The present framework overcomes the bane of most conventional turbulence models and theoretical frameworks arising from the lack of scale separation between the mean and fluctuating scales of the Navier-Stokes equation with an eddy viscous term. An averaged turbulent flow in the present framework behaves more like a flow of finite Knudsen number with finite relaxation time, and is thus more suitably described in a kinetic theory representation.
Vertical Divergence Characteristics of Dissolved Inorganic Carbon and Influencing Factors in a Karst Deep-Water Reservoir, Southwest China
Authors: Zhou Zhongfa , Wang Cui , Li Yongliu , Zhang Yongrong , Kong Jie
Published: July 2023

In deep karst reservoirs, the internal environment is complex, and thermal stratification isnot the only factor controlling the vertical distribution of the DIC concentration. Previous studies have not fully understood the migration and transformation of DIC in a deep-water reservoir. In this study, a deep-water reservoir in southwest China was chosen, and the spatial and temporal characteristics of the DIC concentration, pCO2, δ13CDIC value, and SIc were investigated. It was found that the Pingzhai Reservoir is a double temperature leapfrog reservoir. The DIC concentration, pCO2, Sic, and δ13CDICvalues showed annual cycle variation. During the thermal stratification phase, the DIC concentration, pCO2, Sic, and δ13CDICvalues were significantly different between the surface layer and the lower layer. However, during the mixing and mixed phases, the differences were not significant. The vertical divergence of the DIC in the Pingzhai Reservoir was influenced by the subtemperate layer, human activities, and sources. The formation of the subtemperate layer was due to the submerged flow formed when river water enteredthe reservoir, which provides a channel for DIC from the river to enter the lower layer of the reservoir. Human activities increased the solubility of carbonate rocks in the reservoir, and the source of DIC was one of the factors contributing to the concentration stratification of DIC in the reservoir.
Improved Whale Optimization Algorithm Based on Fusion Gravity Balance
Authors: Ouyang Chengtian , Gong Yongkang , Zhu Donglin , Zhou Changjun
Published: July 2023

In order to improve the shortcomings of the whale optimization algorithm (WOA) in dealing with optimization problems, and further improve the accuracy and stability of the WOA, we propose an enhanced regenerative whale optimization algorithm based on gravity balance (GWOA). In the initial stage, the nonlinear time-varying factor and inertia weight strategy are introduced to change the foraging trajectory and exploration range, which improves the search efficiency and diversity. In the random walk stage and the encircling stage, the excellent solutions are protected by the gravitational balance strategy to ensure the high quality of solution. In order to prevent the algorithm from rapidly converging to the local extreme value and failing to jump out, a regeneration mechanism is introduced to help the whale population escape from the local optimal value, and to help the whale population find a better solution within the search interval through reasonable position updating. Compared with six algorithms on 16 benchmark functions, the contribution values of each strategy and Wilcoxon rank sum test show that GWOA performs well in 30-dimensional and 100-dimensional test functions and in practical applications. In general, GWOA has better optimization ability. In each algorithm contribution experiment, compared with the WOA, the indexes of the strategies added in each stage were improved. Finally, GWOA is applied to robot path planning and three classical engineering problems, and the stability and applicability of GWOA are verified.
Iron-Decorated Nitrogen/Boron co-Doped Reduced Graphene Oxide Aerogel for Neutral Rechargeable Zn-Air Batteries
Authors: Irmawati Yuyun , Balqis Falihah , Persada Pilar Bela , Destyorini Fredina , Yudianti Rike , Iskandar Ferry , Sumboja Afriyanti
Published: July 2023

Zn-air batteries (ZABs) with neutral electrolytes offer a significantly longer lifespan and better recyclability than alkaline ones. However, low-performance bifunctional catalytic activities for oxygen reduction or evolution reaction (i.e., ORR/OER) in neutral electrolytes still hamper their development. Here, we report iron nanoparticle-decorated nitrogen/boron co-doped reduced graphene oxide aerogel (Fe-NBrGO) with distinguished ORR/OER activity, enabling its application in neutral rechargeable ZABs. Taking advantage of the formation of 3D porous structure of graphene aerogel, N/B-moieties active sites, and Fe-containing active sites, Fe-NBrGO exhibits high ORR onset potential (1.074 and 0.817 V) and adequate OER overpotential (476 and 615 mV) in alkaline and neutral electrolytes, respectively. Fe-NBrGO enables the production of a neutral-ZAB with 34 mW cm−2 in peak power density and remains stable for a 284 h (~852 cycles) cycling test. This research highlights the rational design of highly active oxygen catalysts for the widespread implementation of new energy storage technologies.
Facile Synthesis of Ordered Mesoporous Orthorhombic Niobium Oxide (T-Nb2O5) for High-Rate Li-Ion Storage with Long Cycling Stability
Authors: Umeshbabu Ediga , Velpula Divya , Karkera Guruprakash , Satyanarayana Maddukuri , Pasala Vasudevarao , Justin P.
Published: July 2023

Herein, we describe the synthesis and evaluation of hierarchical mesoporous orthorhombic niobium oxide (T-Nb2O5) as an anode material for rechargeable lithium-ion batteries (LIB). The as-synthesized material addresses key challenges such as beneficial porous structure, poor rate capability, and cycling performance of the anode for Li-ion devices. The physicochemical characterization results reveal hierarchical porous nanostructure morphology with agglomerated particles and a 20 to 25 nm dimension range. Moreover, the sample has a high specific surface area (~65 m2 g−1) and pore volume (0.135 cm3 g−1). As for the application in Li-ion devices, the T-Nb2O5 delivered an initial discharging capacity as high as 225 mAh g−1 at 0.1 A g−1 and higher rate capability as well as remarkable cycling features (~70% capacity retention after 300 cycles at 250 mA g−1) with 98% average Coulombic efficiency (CE). Furthermore, the scan rate-dependent charge storage mechanism of the T-Nb2O5 electrode material was described, and the findings demonstrate that the electrode shows an evident and highly effective pseudocapacitive Li intercalation behaviour, which is crucial for understanding the electrode process kinetics. The origin of the improved performance of T-Nb2O5 results from the high surface area and mesoporous structure of the nanoparticles.
Diversity, Genomics and Symbiotic Characteristics of Sinorhizobia That Nodulate Desmanthus spp. in Northwest Argentina
Authors: Zuber Nicolás Emilio , Fornasero Laura Viviana , Erdozain Bagolín Sofía Agostina , Lozano Mauricio Javier , Sanjuán Juan , Del Papa María Florencia , Lagares Antonio
Published: July 2023

Desmanthus spp. are legumes with the ability to associate with diverse α-proteobacteria—a microsymbiont—in order to establish nitrogen-fixing root nodules. A previous investigation from our laboratory revealed that the main bacteria associated with Desmanthus paspalaceus in symbiosis in central Argentina (Province of Santa Fe) were quite diverse and belonged to the genera Rhizobium and Mesorhizobium. To achieve a more extensive view of the local microsymbionts associated with Desmanthus spp., we sampled three different sites in Jujuy and Salta, in northwest Argentina. Matrix-assisted Laser-Desorption-Ionization Time-of-Flight mass spectrometry (MALDI-TOF) typing, 16S-rDNA analysis, and genome sequencing demonstrated that the dominant root-nodule microsymbionts belonged to the genus Sinorhizobium, with some sequenced genomes related to Sinorhizobium mexicanum, Sinorhizobium chiapanecum, and Sinorhizobium psoraleae. An analysis of nodA and nodC markers indicated that, in some of the isolates, horizontal gene transfer appeared to be responsible for the lack of congruence between the phylogenies of the chromosome and of the symbiotic region. These results revealed diverse evolutionary strategies for reaching the current Desmanthus-microsymbiont diversity. What is remarkable beside their observed genetic diversity is that the tolerance profiles of these isolates to abiotic stresses (temperature, salt concentration, pH) were quite coincident with the separation of the sinorhizobia according to place of origin, suggesting possible ecoedaphic adaptations. This observation, together with the higher aerial dry-weight matter that some isolates generated in Desmanthus virgatus cv. Marc when compared to the biomass generated by the commercial strain Sinorhizobium terangae CB3126, distinguish the collected sinorhizobia as constituting valuable germplasm for evaluation in local fields to select for more efficient symbiotic pairs.
Should Cystatin C eGFR Become Routine Clinical Practice?
Authors: Spencer Sebastian , Desborough Robert , Bhandari Sunil
Published: July 2023

Kidney function assessment is crucial for diagnosing and managing kidney diseases. Glomerular filtration rate (GFR) is widely used as an indicator of kidney function, but its direct measurement is challenging. Serum creatinine, a commonly used marker for estimating GFR (eGFR), has limitations in accuracy and sensitivity. Cystatin C, a protein freely filtered by the glomerulus, has emerged as a promising alternative marker for kidney function. It is unaffected by muscle mass and shows stronger associations with cardiovascular disease and mortality than creatinine. Various equations have been developed to estimate GFR using creatinine or cystatin C alone or in combination. The CKD-EPIcreat-cys equation combining both markers demonstrates improved accuracy in GFR estimation, especially for individuals with eGFR values of 45–59 mL/min/1.73 m2. Cystatin C-based estimates of GFR outperform creatinine-based estimates in predicting clinical outcomes and identifying patients at higher risk, particularly in elderly and non-white ethnic groups. Cystatin C offers advantages over creatinine as a marker of kidney function. It is not influenced by non-kidney factors and provides more accurate estimation of GFR, aiding in the early detection of kidney disease and predicting adverse outcomes. Incorporating cystatin C into routine kidney function assessment may improve patient risk stratification and guide clinical decision-making. However, widespread adoption of cystatin C testing requires increased availability and accessibility in clinical laboratories. Further research and implementation efforts are needed to fully realize the potential of cystatin C in kidney function assessment and improving patient outcomes.
Etomidate versus Propofol for Electroconvulsive Therapy in Patients with Major Depressive Disorders in Terms of Clinical Responses to Treatment: A Retrospective Analysis
Authors: Yoon In-Young , Ryu Jung-Hee , Do Sang-Hwan , Min Beomjun , Koo Chang-Hoon
Published: July 2023

General anesthetic agents may be associated with the clinical efficacy of electroconvulsive therapy (ECT), as they may influence seizure quality and duration. Hence, a retrospective study was conducted to compare the clinical effects and seizure variables of etomidate and propofol during ECT. Patients treated with ECT under anesthesia with etomidate (n = 43) or propofol (n = 12) were retrospectively analyzed. Seizure variables (seizure duration, intensity, and threshold) and hemodynamic changes during ECT were assessed and recorded. Clinical responses to treatment were evaluated using the Clinical Global Impression scale and mood at discharge after the course of ECT. Adverse effects were also recorded. The demographic characteristics were similar between the two groups. There were no significant differences in the Clinical Global Impression scale scores, mood at discharge, and adverse effects between the two groups (p > 0.05); however, etomidate was associated with a significantly longer motor (42.0 vs. 23.65 s, p < 0.001) and electroencephalogram (51.8 vs. 33.5 s, p < 0.001) seizure duration than propofol. In conclusion, etomidate showed more favorable seizure profiles than propofol during ECT; however, both agents (etomidate and propofol) were associated with similar clinical efficacy profiles at discharge.
Circularity Indicators as a Design Tool for Design and Construction Strategies in Architecture
Authors: Incelli Francesco , Cardellicchio Luciano , Rossetti Massimo
Published: July 2023

This study addresses the challenges and barriers associated with the implementation of circular economy principles in architectural design and construction practices. It highlights the fragmented knowledge and lack of a unified approach to circular design as a major obstacle hindering the adoption of circularity. The existing frameworks for assessing circularity, such as the Material Circularity Indicator (MCI) protocol and the Level(s) assessment protocol, are applied to two projects with a high degree of deconstruction to understand their applicability in the architectural design process and identify their limitations. The study emphasises the significance of considering structural connectivity and circularity strategies during the concept-design stage, advocating for the incorporation of circularity at various scales beyond the microscale of materials. Furthermore, it emphasises the need for early implementation of Design for Disassembly (DfD) strategies on circularity scoring to enable meaningful comparisons of alternative designs using circularity metrics. The findings reveal the variability of circularity indicators based on the hierarchy of disassembly and highlights an early-stage design approach to deconstruction strategies to achieve circularity in architectural design. Overall, this study upscales the significance of a comprehensive and integrated approach to circularity in architectural design practices.
Relationships between Lip Seal Strength, Tongue Pressure, and Daytime Sleepiness in Japanese Workers: A Cross-Sectional Study
Authors: Minoura Akira , Ihara Yoshiaki , Kato Hirotaka , Murakami Kouzou , Watanabe Yoshio , Hirano Kojiro , Ito Yoshinori , Kokaze Akatsuki
Published: July 2023

This cross-sectional study aimed to examine the relationships between lip seal strength, tongue pressure, and daytime sleepiness in Japanese workers. A self-administered questionnaire which comprised the Epworth Sleepiness Scale (ESS) was completed by 496 workers, and excessive daytime sleepiness was defined by an ESS score of 11 or over. Lip seal strength and tongue pressure were measured in all participants, and multiple regression analyses were performed to examine the effects of lip seal strength and tongue pressure on daytime sleepiness. The median ESS score was 5.0 (25th and 75th percentiles: 2.0 and 8.0), and 42 (8.5%) workers had excessive daytime sleepiness. The median lip seal strength was 13.5 N (11.4, 16.3), and the tongue pressure was 41.7 kPa (35.2, 48.3). Workers with higher ESS scores had significantly lower levels of lip seal strength than those without, following adjustments for age and body mass index (BMI) values (β (95% confidence interval): −0.043 [−0.081, −0.004]). However, tongue pressure was not significantly associated with ESS score after adjustments for age and/or BMI. These results suggest that maintaining moderate lip seal strength may help prevent excessive daytime sleepiness in Japanese workers regardless of age or BMI.
Insights into the Use of Point-of-Care Ultrasound for Diagnosing Obstructive Sleep Apnea
Authors: Kalkanis Alexandros , Testelmans Dries , Papadopoulos Dimitrios , Van den Driessche Annelies , Buyse Bertien
Published: July 2023

Obstructive sleep apnea (OSA) is a sleeping disorder caused by complete or partial disturbance of breathing during the night. Existing screening methods include questionnaire-based evaluations which are time-consuming, vary in specificity, and are not globally adopted. Point-of-care ultrasound (PoCUS), on the other hand, is a painless, inexpensive, portable, and useful tool that has already been introduced for the evaluation of upper airways by anesthetists. PoCUS could also serve as a potential screening tool for the diagnosis of OSA by measuring different airway parameters, including retropalatal pharynx transverse diameter, tongue base thickness, distance between lingual arteries, lateral parapharyngeal wall thickness, palatine tonsil volume, and some non-airway parameters like carotid intima–media thickness, mesenteric fat thickness, and diaphragm characteristics. This study reviewed previously reported studies to highlight the importance of PoCUS as a potential screening tool for OSA.
The Role of Transabdominal Ultrasound Elastography in Gastrointestinal Non-Liver Diseases: Current Application and Future Prospectives
Authors: Paratore Mattia , Garcovich Matteo , Ainora Maria Elena , Del Vecchio Livio Enrico , Cuccia Giuseppe , Riccardi Laura , Pompili Maurizio , Gasbarrini Antonio , Zocco Maria Assunta
Published: July 2023

Ultrasound imaging is the first-line investigation for patients with abdominal symptoms, as it effectively depicts the gastrointestinal tract and enables the diagnosis of multiple pathological conditions. Among different recent ultrasound technological advancements, elastography enables the evaluation of various tissue characteristics, such as neoplastic transformation or fibroinflammatory status. In recent years, ultrasound elastography has been utilized extensively for the study of liver diseases and in numerous other clinical settings, including gastrointestinal diseases. Current guidelines suggest the use of transabdominal ultrasound elastography to characterize bowel wall lesions, to assess gastrointestinal contractility, to diagnose and grade chronic pancreatitis; however, no specific indications are provided. In the present paper, we summarize the evidence concerning the application of different ultrasound elastography modalities in gastrointestinal non-liver diseases.
Quantitative Edge Analysis of Pancreatic Margins in Patients with Chronic Pancreatitis: A Correlation with Exocrine Function
Authors: Ambrosetti Maria Chiara , Grecchi Annamaria , Ambrosetti Alberto , Amodio Antonio , Mansueto Giancarlo , Montemezzi Stefania , Zamboni Giulia A.
Published: July 2023

Background: Many efforts have been made to improve accuracy and sensitivity in diagnosing chronic pancreatitis (CP), obtaining quantitative assessments related to functional data. Our purpose was to correlate a computer-assisted analysis of pancreatic morphology, focusing on glandular margins, with exocrine function—measured by fecal elastase values—in chronic pancreatitis patients. Methods: We retrospectively reviewed chronic pancreatitis patients who underwent fecal elastase assessment and abdominal MRI in our institute within 1 year. We identified 123 patients divided into three groups based on the fecal elastase value: group A with fecal elastase > 200 μg/g; group B with fecal elastase between 100 and 200 μg/g; and group C with fecal elastase < 100 μg/g. Computer-assisted quantitative edge analysis of pancreatic margins was made on non-contrast-enhanced water-only Dixon T1-weighted images, obtaining the pancreatic margin score (PMS). PMS values were compared across groups using a Kruskal–Wallis test and the correlation between PMS and fecal elastase values was tested with the Spearman’s test. Results: A significant difference in PMS was observed between the three groups (p < 0.0001), with a significant correlation between PMS and elastase values (r = 0.6080). Conclusions: Quantitative edge analysis may stratify chronic pancreatitis patients according to the degree of exocrine insufficiency, potentially contributing to the morphological and functional staging of this pathology.
Performance of Nursing Students with a Graphic Novel and a Collaborative Quiz Competition: A Quasi-Experimental Study
Authors: Navarro-Martínez Olga , Silva Josep , Ibáñez-del Valle Vanessa
Published: July 2023

Very few studies analyzing the benefits of gamification in nurse training exist. In this work, we assessed the impact of a quiz group competition and a collective review of a graphic novel on students’ performance, specifically for future nurses during their training. The study was implemented in a geriatric care course for second-year nursing students (n = 63). The effects of gamification were measured with objective (final grades) and subjective (self-evaluation) measures. The average grade of the students who participated in the gamification trial was 12.28% higher than the average grade of the students who did not participate. The final grade was positively correlated with the number of rounds of quizzes played and the score obtained in these quiz activities. Overall, 81.8% of the students indicated that the quizzes helped them to learn. This study provides evidence that gamification can improve student performance in nurse training.
An Unsupervised Fundus Image Enhancement Method with Multi-Scale Transformer and Unreferenced Loss
Authors: Hu Yanzhe , Li Yu , Zou Hua , Zhang Xuedong
Published: July 2023

Color fundus images are now widely used in computer-aided analysis systems for ophthalmic diseases. However, fundus imaging can be affected by human, environmental, and equipment factors, which may result in low-quality images. Such quality fundus images will interfere with computer-aided diagnosis. Existing methods for enhancing low-quality fundus images focus more on the overall visualization of the image rather than capturing pathological and structural features at the finer scales of the fundus image sufficiently. In this paper, we design an unsupervised method that integrates a multi-scale feature fusion transformer and an unreferenced loss function. Due to the loss of microscale features caused by unpaired training, we construct the Global Feature Extraction Module (GFEM), a combination of convolution blocks and residual Swin Transformer modules, to achieve the extraction of feature information at different levels while reducing computational costs. To improve the blurring of image details caused by deep unsupervised networks, we define unreferenced loss functions that improve the model’s ability to suppress edge sharpness degradation. In addition, uneven light distribution can also affect image quality, so we use an a priori luminance-based attention mechanism to improve low-quality image illumination unevenness. On the public dataset, we achieve an improvement of 0.88 dB in PSNR and 0.024 in SSIM compared to the state-of-the-art methods. Experiment results show that our method outperforms other deep learning methods in terms of vascular continuity and preservation of fine pathological features. Such a framework may have potential medical applications.
A Bi-Objective Simulation Facility for Speed and Range Calibration of 24 GHz and 77 GHz Automotive Millimeter-Wave Radars for Environmental Perception
Authors: Xu Tianqi , Yu Danyang , Du Lei
Published: July 2023

Automotive millimeter-wave radars are widely used to measure kinematic parameters of surrounding objects in the environmental perception of automated vehicles and typically operate in frequency bands of around 24 GHz and 77 GHz. The 24 GHz and 77 GHz automotive millimeter-wave radars are similar in their speed and range measurement principles; however, they are distinct in their accuracies when measuring the above kinematic parameters because of the different carrier frequencies and bandwidths. In order to evaluate the kinematic parameter measurement performances of automotive millimeter-wave radars for environmental perception, this paper proposes a calibration method and establishes a bi-objective simulation facility for the speed and range calibration of 24 GHz and 77 GHz automotive millimeter-wave radars. The feasibility of the proposed calibration method and the accuracy of the established bi-objective simulation facility are verified by the results obtained via experiments conducted on two 24 GHz and 77 GHz millimeter-wave radar samples. According to the speed and range calibration results of the two millimeter-wave radar samples, the 77 GHz millimeter-wave radar sample possesses superior speed measurement accuracy compared with the 24 GHz sample. Additionally, the range measurement errors of the 77 GHz millimeter-wave radar sample are much smaller than those of the 24 GHz sample. This indicates that the 77 GHz millimeter-wave radar sample is more accurate and reliable than the 24 GHz sample. Finally, the 77 GHz millimeter-wave radar sample was tested for its speed and range resolving ability. The results confirm that the bi-objective simulation facility can satisfy the calibration requirements of speed resolution up to 0.01 m/s and range resolution up to 0.1 m. The proposed calibration method and the established simulation facility can easily satisfy the speed, range and resolution calibration requirements of 24 GHz and 77 GHz millimeter-wave radars with high precision and wide range, and can achieve more economical, comprehensive and traceable performance testing on both 24 GHz and 77 GHz automotive millimeter-wave radars for environmental perception.
Selection of Organic Fluid Based on Exergetic Performance of Subcritical Organic Rankine Cycle (ORC) for Warm Regions
Authors: Siddiqui Muhammad Ehtisham , Almatrafi Eydhah , Saeed Usman , Taimoor Aqeel Ahmad
Published: July 2023

The organic Rankine cycle (ORC) exhibits considerable promise in efficiently utilizing low-to-medium-grade heat. Currently, there is a range of organic fluids available in the market, and selecting the appropriate one for a specific application involves considering factors such as the cycle’s thermodynamic performance, plant size, and compatibility with turbomachinery. The objective of our study is to examine the exergetic performance of the ORC with internal heat regeneration. We analyze 12 different organic fluids to evaluate their suitability based on parameters like exergy efficiency and heat exchange area requirements. Additionally, we investigate the need for internal heat regeneration by comparing the overall exergy performance with a simpler ORC configuration. To ensure broad applicability, we consider source temperatures ranging from 150 to 300 °C, which are relevant to industrial waste heat, geothermal sources, and solar energy. For each case, we calculate specific net power output and the UA value (heat exchanger conductance) to gain insights into selecting the appropriate organic fluid for specific source temperatures. Cyclohexane, benzene, isopropyl alcohol, and hexafluorobenzene show poor exergy efficiency due to their high boiling points. Pentane and cyclopentane provides the highest exergy efficiency of 62.2% at source temperature of 300 °C, whereas pentane is found to be the most suitable at source temperatures of 200 and 150 °C with exergy efficiency of 67.7% and 61.7%, respectively. At 200 °C source temperature, RE347mcc achieves 65.9% exergy efficiency. The choice of organic fluid for a given heat source is highly influenced by its critical properties. Moreover, the normal boiling temperature of the organic fluid significantly impacts exergy destruction during the condensation process within the cycle.
Turpentine as an Additive for Diesel Engines: Experimental Study on Pollutant Emissions and Engine Performance
Authors: Chivu Robert Mădălin , Martins Jorge , Popescu Florin , Uzuneanu Krisztina , Ion Ion V. , Goncalves Margarida , Codău Teodor-Cezar , Onofrei Elena , Brito Francisco P.
Published: July 2023

The need for reducing fossil fuel consumption and greenhouse gas (GHG) emissions in internal combustion engines has raised the opportunity for the use of renewable energy sources. For the progressive replacement of fossil fuels like diesel, those derived from the sustainable management of forest resources may be a good option. In Portugal, pine trees (pinus pinaster) are among the most widely cultivated tree species. Turpentine can be extracted from their sap without harming the tree. Turpentine is known to be a good fuel with a lower viscosity than regular diesel but with a comparable caloric value, boiling point and ignition characteristics, although it is not widely used as a compression ignition fuel. Moreover, recent research has highlighted the possibility of substantially increasing the turpentine yield through biotechnology, bringing it closer to economic viability. The present study investigates the performance, pollutant emissions and fuel consumption of a 1.6 L four-cylinder direct-injection diesel engine operating with several blends of commercial diesel fuel and turpentine obtained from pine trees. The aim of this study was to assess whether it would be possible to maintain or even improve the performance, fuel consumption and GHG and pollutant emissions (HC, NOx, CO and PM) of the engine with the partial incorporation of this biofuel. Turpentine blends of up to 30% in substitution of regular diesel fuel were tested. The main novelties of the present work are related to (i) the careful testing of a still-insufficiently studied fuel that could gain economical attractiveness with the recent developments in yield improvement through biotechnology and (ii) the tests conducted under fixed engine load positions typical of road and highway conditions. The addition of this biofuel only slightly impacted the engine performance parameters. However, a slightly positive effect was observed in terms of torque, with an increase of up to 7.9% at low load for the 15T85D mixture and 6.8% at high load being observed. Power registered an increase of 9% for the 15T85D mixture at low speed and an increase of 5% for the 30T70D mixture at high speed when compared to the reference fuel (commercial diesel fuel). While the efficiency and fossil GHG emissions were improved with the incorporation of turpentine, it had a mixed effect on polluting emissions such as unburned hydrocarbons (HC) and smoke (PM) and a negative effect on nitrogen oxides (NOx). NOx emissions increased by 30% for high loads and 20% for low loads, mainly as an indirect effect of the improvement in the engine performance and not so much as a consequence of the marginally higher oxygen content of turpentine relative to commercial diesel fuel.
Energy and Cost Analysis of an Integrated Photovoltaic and Heat Pump Domestic System Considering Heating and Cooling Demands
Authors: Arenas-Larrañaga Mikel , Santos-Mugica Maider , Alonso-Ojanguren Laura , Martin-Escudero Koldobika
Published: July 2023

The integration of photovoltaic panels and heat pumps in domestic environments is a topic that has been studied extensively. Due to their electrical nature and the presence of elements that add thermal inertia to the system (water tanks and the building itself), the functioning of compression heat pumps can be manipulated to try to fulfill a certain objective. In this paper, following a rule-based control concept that has been identified in commercial solutions and whose objective is to improve the self-consumption of the system by actively modulating the heat pump compressor, a parametric analysis is presented. By making use of a lab-tested model, the performance of the implemented control algorithm is analyzed. The main objective of this analysis is to identify and quantify the effects of the main parameters in the performance of the system, namely the climate (conditioning both heating and cooling demands), the photovoltaic installation size, the thermal insulation of the building and the control activation criteria. A total of 168 yearly simulations have been carried out. The results show that the average improvement in self-consumption is around 13%, while the cost is reduced by 2.5%. On the other hand, the heat from the heat pump and the power consumed increase by 3.7% and 5.2%, respectively. Finally, a linear equation to estimate the performance of the controller is proposed.
Effective Parameters of a Compression-Ignition Engine Powered by a Mixture Consisting of Ethyl-Tetra-Butyl Ether and Diesel Fuel
Authors: Mitan-Zalewska Paulina , Klyus Oleh , Kozak Maciej
Published: July 2023

The present article presents the results of analytical research on the possibility of using a mixture consisting of diesel oil and ethyl-tertiary-butyl ether in different percentages of EETB to power compression-ignition engines. The calculations were carried out for a four-stroke diesel engine intended for use as a power generator, among other things. In order to illustrate and verify the correctness of the calculations, a mathematical model was built that confirmed the correctness of the calculations. The calculations focused on a thorough analysis of the elemental composition (content of individual elements) of the fuel and, in particular, the carbon content in the fuel. A calculation algorithm was applied for mixing diesel fuel with ethyl-tertiary butyl ether in a share of EETB 5% + 95% ON, 10% EETB + 90% ON, 20% EETB ++80% ON, 30% EETB + 70% ON, 40% EETB + 60% ON. In this study, it determined the parameters of the working medium, the parameters of the environment and residual gases, and the processes (charge filling, compression, combustion, expansion) and effective parameters of the engine. The calculations used in this study led to heat balance, and a summary of the obtained results and their comparison with diesel oil are also described in this study. The results show the feasibility of using a mixture of ethyl-tertiary-butyl ether as a fuel in diesel engines. The results are very similar to those for 100% diesel. The results of our calculations confirming the possibility of using ether for fuel and thus maintaining similar engine operating parameters.
Rheological Behavior of Cement Paste: A Phenomenological State of the Art
Authors: El Bitouri Youssef
Published: July 2023

With the interest aroused by the development of modern concretes such as printable or self-compacting concretes, a better understanding of the rheological behavior, directly linked to fresh state properties, seems essential. This paper aims to provide a phenomenological description of the rheological behavior of cement paste. The first part is devoted to the most common testing procedures that can be performed to characterize the rheological properties of cement suspensions. The second one deals with the complexities of the rheological behavior of cement paste including the non-linearity of flow behavior, the viscoelasticity and yielding, and the structural build-up over time.
Automatic Extraction of the Spatial Distribution of Picea schrenkiana in the Tianshan Mountains Based on Google Earth Engine and the Jeffries–Matusita Distance
Authors: Xu Fujin , Xu Zhonglin , Xu Changchun , Yu Tingting
Published: July 2023

As a distinct species in the Tianshan Mountains (TS) of Central Asia (CA), Picea schrenkiana plays a significant role in water purification, soil and water conservation, and climate regulation. In the context of climate change, rapidly and accurately obtaining its spatial distribution has critical decision-making significance for maintaining ecological security in the arid area of CA and the sustainable development of the “Silk Road Economic Belt”. However, conventional methods are extremely challenging to accomplish the high-resolution mapping of Picea schrenkiana in the TS, which is characterized by a wide range (9.97 × 105 km2) and complex terrain. The approach of geo-big data and cloud computing provides new opportunities to address this issue. Therefore, the purpose of this study is to propose an automatic extraction procedure for the spatial distribution of Picea schrenkiana based on Google Earth Engine and the Jeffries–Matusita (JM) distance, which considered three aspects: sample points, remote-sensing images, and classification features. The results showed that (1) after removing abnormal samples and selecting the summer image, the producer accuracy (PA) of Picea schrenkiana was improved by 2.95% and 0.24%–2.10%, respectively. (2) Both the separation obtained by the JM distance and the analysis results of eight schemes showed that spectral features and texture features played a key role in the mapping of Picea schrenkiana. (3) The JM distance can seize the classification features that are most conducive to the mapping of Picea schrenkiana, and effectively improve the classification accuracy. The PA and user accuracy of Picea schrenkiana were 96.74% and 96.96%, respectively. The overall accuracy was 91.93%, while the Kappa coefficient was 0.89. (4) The results show that Picea schrenkiana is concentrated in the middle TS and scattered in the remaining areas. In total, 85.7%, 66.4%, and 85.9% of Picea schrenkiana were distributed in the range of 1500–2700 m, 20–40°, and on shady slope and semi-shady slope, respectively. The automatic procedure adopted in this study provides a basis for the rapid and accurate mapping of the spatial distribution of coniferous forests in the complex terrain.
Reducing Carbon Intensity of Food and Fuel Production Whilst Lowering Land-Use Impacts of Biofuels
Authors: Attfield Paul V. , Bell Philip J. L. , Grobler Anna S.
Published: July 2023

Science and technology are critical for developing novel and sustainable production of food, fuel, and chemicals in a manner that significantly reduces anthropogenic contributions to climate change. Although renewable energy is gradually displacing fossil fuels for grid energy, oil-based transport fuels remain major contributors to global greenhouse gas emissions. Currently, bioethanol and biodiesel can partially replace petroleum, but these renewables are far from perfect in terms of long-term sustainability and the volumetric expansion needed to fully replace oil. Biofuels made in biorefineries using sugars or oils derived from plants grown on prime food-producing land only partly offset CO2 emissions relative to petroleum and present problems with respect to land-use change. Here, we provide alternative ideas for lignocellulosic biorefineries that coproduce bioethanol, nutritious protein-rich yeast biomass for animal feeds, and carbon-rich solid residuals that represent green coal or sequestered carbon. A concept of how these biorefineries could be linked to renewable power-to-X, where X can be bioethanol, protein, sequestered carbon, or multiple carbon-carbon based synthetic fuels and chemicals, is presented. We also discuss aspects of the present and future roles for microorganisms in lignocellulosic biorefineries and power-to-X bio/chemical refineries.
Effects of Fire Frequency Regimes on Flammability and Leaf Economics of Non-Graminoid Vegetation
Authors: Lamounier Moura Arthur , Negreiros Daniel , Fernandes Geraldo Wilson
Published: July 2023

Fire is an ecological factor that strongly influences plant communities and functional traits. Communities respond differently to fire, either decreasing or increasing in flammability and resource acquisition strategies. This study aimed to investigate the influence of fire over traits associated with flammability and the plant economic spectrum in a stressful and infertile mountainous grassland located in the Espinhaço mountain range in Brazil. Non-graminoid plant species were sampled in 60 5 m × 5 m plots distributed in three fire frequency categories. We measured several traits related to flammability—leaf dry matter content (LDMC), twig dry matter content, leaf area, bark thickness, branching architecture, plant height, leaf toughness (LT), and specific leaf area (SLA). Traits responded differently to the increase in fire frequency. For instance, the LDMC and LT were lower while the SLA was higher at high fire frequencies, indicating a trend towards reduced heat release and fire residence time. This shift resulted in the dominance of plants with a relatively more acquisitive strategy. This study brings evidence that traits respond coordinately towards a reduction of flammability with the increase in fire frequency and are strong indicators of the filtering role that fire plays as a disturbance on rupestrian grassland vegetation.
Hydrogel-Based Biosensors for Effective Therapeutics
Authors: Quazi Mohzibudin Z. , Hwang Jimin , Song Youngseo , Park Nokyoung
Published: July 2023

Nanotechnology and polymer engineering are navigating toward new developments to control and overcome complex problems. In the last few decades, polymer engineering has received researchers’ attention and similarly, polymeric network-engineered structures have been vastly studied. Prior to therapeutic application, early and rapid detection analyses are critical. Therefore, developing hydrogel-based sensors to manage the acute expression of diseases and malignancies to devise therapeutic approaches demands advanced nanoengineering. However, nano-therapeutics have emerged as an alternative approach to tackling strenuous diseases. Similarly, sensing applications for multiple kinds of analytes in water-based environments and other media are gaining wide interest. It has also been observed that these functional roles can be used as alternative approaches to the detection of a wide range of biomolecules and pathogenic proteins. Moreover, hydrogels have emerged as a three-dimensional (3D) polymeric network that consists of hydrophilic natural or synthetic polymers with multidimensional dynamics. The resemblance of hydrogels to tissue structure makes them more unique to study inquisitively. Preceding studies have shown a vast spectrum of synthetic and natural polymer applications in the field of biotechnology and molecular diagnostics. This review explores recent studies on synthetic and natural polymers engineered hydrogel-based biosensors and their applications in multipurpose diagnostics and therapeutics. We review the latest studies on hydrogel-engineered biosensors, exclusively DNA-based and DNA hydrogel-fabricated biosensors.