bluuebunny/crossref_metadata_2025 huggingface dataset:
3D Model Artificial Intelligence-Guided Automatic Augmented Reality Images during Robotic Partial Nephrectomy
Authors: Sica Michele , Piazzolla Pietro , Amparore Daniele , Verri Paolo , De Cillis Sabrina , Piramide Federico , Volpi Gabriele , Piana Alberto , Di Dio Michele , Alba Stefano , Gatti Cecilia , Burgio Mariano , Busacca Giovanni , Giordano Angelo , Fiori Cristian , Porpiglia Francesco , Checcucci Enrico
Published: November 2023

More than ever, precision surgery is making its way into modern surgery for functional organ preservation. This is possible mainly due to the increasing number of technologies available, including 3D models, virtual reality, augmented reality, and artificial intelligence. Intraoperative surgical navigation represents an interesting application of these technologies, allowing to understand in detail the surgical anatomy, planning a patient-tailored approach. Automatic superimposition comes into this context to optimally perform surgery as accurately as possible. Through a dedicated software (the first version) called iKidney, it is possible to superimpose the images using 3D models and live endoscopic images during partial nephrectomy, targeting the renal mass only. The patient is 31 years old with a 28 mm totally endophytic right-sided renal mass, with a PADUA score of 9. Thanks to the automatic superimposition and selective clamping, an enucleoresection of the renal mass alone was performed with no major postoperative complication (i.e., Clavien–Dindo < 2). iKidney-guided partial nephrectomy is safe, feasible, and yields excellent results in terms of organ preservation and functional outcomes. Further validation studies are needed to improve the prototype software, particularly to improve the rotational axes and avoid human help. Furthermore, it is important to reduce the costs associated with these technologies to increase its use in smaller hospitals.
An Alignment-Free Explanation for Collective Predator Evasion in Moving Animal Groups
Authors: Strömbom Daniel , Futterman Catherine
Published: November 2023

Moving animal groups consist of many distinct individuals but can operate and function as one unit when performing different tasks. Effectively evading unexpected predator attacks is one primary task for many moving groups. The current explanation for predator evasion responses in moving animal groups require the individuals in the groups to interact via (velocity) alignment. However, experiments have shown that some animals do not use alignment. This suggests that another explanation for the predator evasion capacity in at least these species is needed. Here we establish that effective collective predator evasion does not require alignment, it can be induced via attraction and repulsion alone. We also show that speed differences between individuals that have directly observed the predator and those that have not influence evasion success and the speed of the collective evasion process, but are not required to induce the phenomenon. Our work here adds collective predator evasion to a number of phenomena previously thought to require alignment interactions that have recently been shown to emerge from attraction and repulsion alone. Based on our findings we suggest experiments and make predictions that may lead to a deeper understanding of not only collective predator evasion but also collective motion in general.
Bulk Operator Reconstruction in Topological Tensor Network and Generalized Free Fields
Authors: Zeng Xiangdong , Hung Ling-Yan
Published: November 2023

In this paper, we study operator reconstruction in a class of holographic tensor networks describing renormalization group flows studied in arXiv:2210.12127. We study examples of 2D bulk holographic tensor networks constructed from Dijkgraaf–Witten theories and find that for both the Zn group and the S3 group, the number of bulk operators behaving like a generalized free field in the bulk scales as the order of the group. We also generalize our study to 3D bulks and find the same scaling for Zn theories. However, there is no generalized free field when the bulk comes from more generic fusion categories such as the Fibonacci model.
Denoising Non-Stationary Signals via Dynamic Multivariate Complex Wavelet Thresholding
Authors: Raath Kim C. , Ensor Katherine B. , Crivello Alena , Scott David W.
Published: November 2023

Over the past few years, we have seen an increased need to analyze the dynamically changing behaviors of economic and financial time series. These needs have led to significant demand for methods that denoise non-stationary time series across time and for specific investment horizons (scales) and localized windows (blocks) of time. Wavelets have long been known to decompose non-stationary time series into their different components or scale pieces. Recent methods satisfying this demand first decompose the non-stationary time series using wavelet techniques and then apply a thresholding method to separate and capture the signal and noise components of the series. Traditionally, wavelet thresholding methods rely on the discrete wavelet transform (DWT), which is a static thresholding technique that may not capture the time series of the estimated variance in the additive noise process. We introduce a novel continuous wavelet transform (CWT) dynamically optimized multivariate thresholding method (WaveL2E). Applying this method, we are simultaneously able to separate and capture the signal and noise components while estimating the dynamic noise variance. Our method shows improved results when compared to well-known methods, especially for high-frequency signal-rich time series, typically observed in finance.
The Perceived Impact of Leading Supplemental Instruction on Student Leaders at a Hispanic-Serving Institution
Authors: Ellison Irina , Haynes Gabriele , Toglia Joan
Published: November 2023

Supplemental Instruction is an evidence-based academic support program which improves the success of higher education undergraduate students who participate in the program, including students from historically underrepresented populations. Sessions are led by near-peer leaders who have previously successfully completed the course. While the impacts of leading SI programs have previously been demonstrated, there is little research on the specific impacts on historically underrepresented student leaders at Hispanic-Serving Institutions (HSIs). Our study aims to elucidate the impact of leading SI on our diverse population of SI leaders at the largest private HSI in New York State. Data were collected from SI leaders on their reflective perceptions about their experiences as SI leaders through both surveys and focus groups. Our data demonstrate that our diverse SI leaders feel positively about their experiences in the SI program with a focus on three areas of perceived self-improvement: confidence, communication and community. These areas of perceived self-improvement are particularly important as they may lead to higher retention and graduation rates.
The Confluence of Supplemental Instruction (SI) Programme Factors on Selected Student Outcomes in a Historically Disadvantaged University
Authors: Nkonki Vuyisile Joy Jonga , Dondolo Vuyelwa , Mabece Khanyisa
Published: November 2023

This paper sought to describe the combined influences (confluence) of the various aspects of the supplemental instruction (SI) programme on selected student outcomes. It points out that the SI programme’s influence goes beyond the reports about the improvement of marks, throughputs, and retention. It shows that the SI programme bears on the development of academic literacies, graduate attributes, the building of a sense of community, and the inculcation of ethos and practices necessary for academic success. Framed in the positivist paradigm and a quantitative approach, aspects of the supplemental instruction programme such as instructional methods, lecturer’s attitude towards SI, accessibility of the SI leaders, lecturer and departmental involvement, and student–facilitator relationship were correlated with the variables of students’ outcomes. The students’ outcome variables were measured by the acquisition of academic literacies and competencies, improved performance in assessment tasks, sense of community and belonging, and assimilation into a university’s culture and ethos. Using purposive/convenient sampling, 122 students who made extensive use of the SI programme were selected to participate in a survey. Data were analysed statistically using ordinal regression. The study’s findings highlight the need to consider different constructs in the planning and implementation of the SI programme. It provides evidence of students’ successful engagement with supplemental instruction and the factors that contribute to such success. This study helps foster an understanding of the various planning, design, and delivery aspects of the supplemental instruction programme, so that ways of making the SI programme effective are devised. The identified significant factors form the basis for the construction of an SI implementation conceptual framework.
Indian Parents’ Perceptions of Children’s Psychological Wellbeing and Academic Learning during COVID-19
Authors: Bharaj Pavneet Kaur , Hurwitz Sarah , Govindaraju Nirmal , Karumanthra Arya , Jacob Annie , Ravindranath Sreehari , Maltese Adam
Published: November 2023

Indian children experienced large-scale disruption in educational, psychological, and social welfare access when schools abruptly closed due to COVID-19. In addition to education, the Indian public school system provides services such as meals and benefits related to improving gender parity and indirectly preventing child labor, child marriages, and abuse. Therefore, sustained school closures led to an unfolding disaster in terms of learning loss and multiple unknown effects on children’s social and psychological wellbeing. This descriptive study attempts to understand these consequences by asking Indian parents about the emotional, psychological, and academic impacts on their children. Results suggest an adverse impact on children’s education and wellbeing. Families reported higher levels of psychological distress, anxiety, and aggression among children. However, the manifestations and ramifications seem to be different—while families from low-income segments struggled to get access to digital devices, others in upper-income segments had to confront excessive device time use. The results suggest that there is a need for a concerted, sustained, multipronged, differential response from the government and civil society to ensure that families can handle these challenges accordingly.
Blockchain Technology for Monitoring Energy Production for Reliable and Secure Big Data
Authors: Gerardi Marco , Fallucchi Francesca , Orecchini Fabio
Published: November 2023

The growing adoption of renewable energy sources and the need for more efficient and secure energy grids are revolutionizing the energy sector. Electricity monitoring becomes an issue of utmost importance, as current traditional energy meters have several problems in terms of lack of transparency, very high operational costs, and the possibility of being easily tampered with. This paper proposes a new system for electricity production metering that leverages blockchain and IoT for decentralized and secure data recording while protecting user privacy and reducing operational costs. The architecture results in improvements over the traditional energy meter. The system also contributes to the generation of big data that is reliable, traceable, error-proof, and highly resistant to cyber attacks. The architectural project outputs are a smart energy meter, a smart contract on the Ethereum blockchain, and a decentralized application to manage the information recording. The experimental prototype outcomes confirm the use of these new technologies to improve energy metering, enhancing efficiency, transparency, and traceability, with reduced costs and increased user privacy.
Simultaneous Pipe Leak Detection and Localization Using Attention-Based Deep Learning Autoencoder
Authors: Karimanzira Divas
Published: November 2023

Water distribution networks are often susceptible to pipeline leaks caused by mechanical damages, natural hazards, corrosion, and other factors. This paper focuses on the detection of leaks in water distribution networks (WDN) using a data-driven approach based on machine learning. A hybrid autoencoder neural network (AE) is developed, which utilizes unsupervised learning to address the issue of unbalanced data (as anomalies are rare events). The AE consists of a 3DCNN encoder, a ConvLSTM decoder, and a ConvLSTM future predictor, making the anomaly detection robust. Additionally, spatial and temporal attention mechanisms are employed to enhance leak localization. The AE first learns the expected behavior and subsequently detects leaks by identifying deviations from this expected behavior. To evaluate the performance of the proposed method, the Water Network Tool for Resilience (WNTR) simulator is utilized to generate water pressure and flow rate data in a water supply network. Various conditions, such as fluctuating water demands, data noise, and the presence of leaks, are considered using the pressure-driven demand (PDD) method. Datasets with and without pipe leaks are obtained, where the AE is trained using the dataset without leaks and tested using the dataset with simulated pipe leaks. The results, based on a benchmark WDN and a confusion matrix analysis, demonstrate that the proposed method successfully identifies leaks in 96% of cases and a false positive rate of 4% compared to two baselines: a multichannel CNN encoder with LSTM decoder (MC-CNN-LSTM) and a random forest and model based on supervised learning with a false positive rate of 8% and 15%, respectively. Furthermore, a real case study demonstrates the applicability of the developed model for leak detection in the operational conditions of water supply networks using inline sensor data.
Prediction of CO2 in Public Buildings
Authors: Dudkina Ekaterina , Crisostomi Emanuele , Franco Alessandro
Published: November 2023

Heritage from the COVID-19 period (in terms of massive utilization of mechanical ventilation systems), global warming, and increasing electricity prices are new challenging factors in building energy management, and are hindering the desired path towards improved energy efficiency and reduced building consumption. The solution to improve the smartness of today’s building and automation control systems is to equip them with increased intelligence to take prompt and appropriate actions to avoid unnecessary energy consumption, while maintaining a desired level of air quality. In this manuscript, we evaluate the ability of machine-learning-based algorithms to predict CO2 levels, which are classic indicators used to evaluate air quality. We show that these algorithms provide accurate forecasts (more accurate in particular than those provided by physics-based models). These forecasts could be conveniently embedded in control systems. Our findings are validated using real data measured in university classrooms during teaching activities.
A Review of Fuzzy Logic Method Development in Hydraulic and Pneumatic Systems
Authors: Filo Grzegorz
Published: November 2023

Fuzzy logic has been developed since the 1960s. Research related to fuzzy logic application in hydraulics and pneumatics is mainly aimed at energy demand reduction and improvement in operational characteristics. This article summarizes the recent achievements in hydraulic and pneumatic fuzzy logic system design. First, the main application areas have been identified, including control and fault diagnosis. The control systems were additionally grouped according to the main objects of study, such as pumps, actuators, proportional valves, etc. Then, the results of the recent research were presented, and the main features of the designed fuzzy logic units were summarized for each group. Particular attention was paid to types of membership functions used for fuzzification and defuzzification, numbers of fuzzy sets defined for input and output signals, types of fuzzy operators, the applied inference algorithm and the defuzzification method. Based on the analysis of the listed parameters, conclusions were formulated regarding advantages, main issues and difficulties, as well as recommended directions for further development.
A Rigorous Explicit Expression for the Mutual Inductance of Two Co-Axial Thin-Wire Coil Antennas Placed above a Layered Ground
Authors: Parise Mauro , Antonini Giulio , Di Paola Luisa
Published: November 2023

This paper presents a quasi-analytical method that allows the derivation of a rigorous series-form representation for the mutual inductance of two co-axial coil antennas located above an arbitrarily layered earth structure. Starting from Biot–Savart law, which gives the integral representation for the primary vector potential generated by the source coil, the potential reflected by the layered ground is derived, and the resulting total vector potential is then integrated along the external circumference of the receiving coil to give the mutual inductance of the two antennas. The obtained representation for the flux is then evaluated analytically through the usage of the Gegenbauer addition theorem once an accurate, rational approximation is used in place of the factor of the integrand that exhibits branch cuts. It is shown how the resulting explicit solution exhibits the same degree of accuracy as purely numerical approaches like the finite-difference time-domain (FDTD) method and conventional numerical quadrature schemes, while it is less time-demanding than the latter methods.
A Review of Protection Schemes for Electrical Distribution Networks with Green Distributed Generation
Authors: Majeed Ammar Abbas , Altaie Ahmed Sabri , Abderrahim Mohamed , Alkhazraji Afaneen
Published: November 2023

An amalgamation of Green Distributed Generation (GDG) with Distribution Networks (DNs) was developed because its performance became more efficient and sustainable. It increased the challenges in the design and operation of the protection scheme and changed the short circuit current (SCC), voltage profile, power losses, and power flow direction after the GDG penetration. These changes rely on the number, size, location, and environmental influence according to the GDG type. Therefore, many researchers have discussed protection system challenges and presented types of protection approaches to find a robust protection layout for DNs integrated with GDGs to prevent the electrical equipment from being destroyed during abnormal conditions. This paper represents an exhaustive survey of GDG integration with DNs and its effects on protection design challenges. Furthermore, this paper summarizes the modern protection methods and detection technologies, along with their important aspects that have been accessed. One of the important and reliable methods is resetting and coordinating between protection devices (PDs) that operate in the same distribution feeder. This methodology focuses on restricting the main variables and parameters used in the PDs setting after the GDG is embedded to recalculate the suitable setting and coordination. Optimization techniques should be used to find the best setting or location of the protection system in the DNs, in addition to calculating the optimal GDG scale and location. However, international standards are used to specify the suitable equations that satisfy high protection system characteristics to ensure the DNs’ reliability.
Methodology for the Optimization of a Novel Hydro Turbine with a Case Study
Authors: Aggidis George , Židonis Audrius , Burtenshaw Luke , Dubois Marc , Orritt Stephen , Pickston Dominic , Prigov George , Wilmot Luke
Published: November 2023

As the world strives towards its goal of net zero carbon emissions, it is vital that renewable energy sources be optimized to their full potential. A key source of renewable energy is hydropower, more specifically, the Pelton turbine—a highly efficient, widely used, and well-researched piece of turbomachinery. This review proposes a methodology that will aid future research on Pelton turbines and compares relevant literature to assess effective ways to improve upon the Pelton design. The methodology evaluates how both experimental and computational analysis can be utilized in parallel to accelerate the progress of research, giving an example of the adopted workflow presented in a case study. The literature study in this paper focuses on how a variety of bucket parameters can be optimized to improve the efficiency of a Pelton turbine and analyses the accuracy of CFD compared to experimental data from previous research involving Pelton and Turgo turbines. The findings revealed that a water exit angle of 169°–170° proved to be optimal, while modifications to the depth and internal geometry of the bucket seemed to have the greatest impact on the efficiency of Pelton turbines. A short discussion on the potential for utilizing the strengths of both Pelton and Turgo turbines is included to highlight the need for further research in this field. A combination of both simulation and experimental results running in parallel with each other during optimization is found to be beneficial due to advancements in rapid prototyping. By comparing experimental data with simulated data throughout the optimization process, mistakes can be realized early on in the process, reducing time in later stages. Having experimental data throughout the turbine’s development aids the computational process by highlighting issues that may have been missed when only using CFD.
Energy Conservation at Home: A Critical Review on the Role of End-User Behavior
Authors: Marchi Lia , Gaspari Jacopo
Published: November 2023

The recent literature emphasizes the significance of occupants’ behavior in shaping home energy demand. Several policies have been defined and tools and technologies have been developed to raise people’s awareness and encourage energy-saving practices at home, but households’ energy demand keeps rising. The thesis is that the fundamentals on this topic are still unclear and that available tools, strategies and measures should be approached in a more integrated way, as they are not now effective enough to encourage energy savings. How these could be successfully combined is still a major knowledge gap. Thus, this article proposes a critical review of the literature to discuss the potential role of end users in energy conservation at home, preparing the ground for truly effective engagement strategies and tools to encourage behavioral change. To that end, a systematic literature review is performed, including over 130 relevant articles. According to the critical interpretation of their content, after years of technologically driven strategies, the most promising approaches capable of overcoming the intention–action gap are those more user-centered. However, relying solely on the social aspect is not effective. Synergistic integration of the two main clusters of studies has been identified as a promising field of research for the future.
Pore-Scale Modeling of Methane Hydrate Dissociation Using a Multiphase Micro-Continuum Framework
Authors: Liu Zhiying , Xu Qianghui , Yang Junyu , Shi Lin
Published: November 2023

The development of methane hydrate extraction technology remains constrained due to the limited physical understanding of hydrate dissociation dynamics. While recent breakthroughs in pore-scale visualization techniques offer intuitive insights into the dissociation process, obtaining a profound grasp of the underlying mechanisms necessitates more than mere experimental observations. In this research, we introduce a two-phase micro-continuum model that facilitates the numerical simulation of methane hydrate dissociation at both single- and multiscale levels. We employed this numerical model to simulate microfluidic experiments and determined the kinetic parameters of methane hydrate dissociation based on experimental data under various dissociation scenarios. The simulations, once calibrated, correspond closely to experimental results. By comprehensively comparing the simulated results with experimental data, the rate constant and the effective diffusion coefficient were reliably determined to be kd = 1.5 × 108 kmol2/(J·s·m2) and Dl = 0.8 × 10−7 m2/s, respectively. Notably, the multiscale model not only matches the precision of the single-scale model but also presents considerable promise for streamlining the simulation of hydrate dissociation across multiscale porous media. Moreover, we contrast hydrate dissociation under isothermal versus adiabatic conditions, wherein the dissociation rate is significantly reduced under adiabatic conditions due to the shifted thermodynamic condition. This comparison highlights the disparities between microfluidic experiments and real-world extraction environments.
Fuel Performance Analysis of Fast Flux Test Facility MFF-3 and -5 Fuel Pins Using BISON with Post Irradiation Examination Data
Authors: Paaren Kyle M. , Gale Micah , Wootan David , Medvedev Pavel , Porter Douglas
Published: November 2023

Using the BISON fuel-performance code, simulations were conducted of an automated process to read initial and operating conditions from the Pacific Northwest National Laboratory (PNNL) database and reports, which contain metallic-fuel data from the Fast Flux Test Facility (FFTF) MFF Experiments. This work builds on previous modeling efforts involving 1977 EBR-II metallic fuel pins from experiments. Coupling the FFTF PNNL reports to BISON allowed for all 338 pins from MFF-3 and MFF-5 campaigns to be simulated. Each BISON simulation contains unique power and flux histories, axial power and flux profiles, and coolant-channel flow rates. Fission-gas release (FGR), fuel axial swelling, cladding profilometry, and burnup were all simulated in BISON and compared to available post-irradiation examination (PIE) data. Cladding profilometry, FGR, and fuel axial swelling simulation results for full-length MFF metallic pins were found to be in agreement with PIE measurements using FFTF physics and models used previously for EBR-II simulations. The main two peaks observed within the cladding profilometry were able to be simulated, with fuel-cladding mechanical interaction (FCMI), fuel-cladding chemical interaction (FCCI), and thermal and irradiation-induced creep being the cause. A U-Pu-Zr hot-pressing model was included in this work to allow pore collapse within the fuel matrix. This allowed better agreement between BISON-simulated cladding profilometry and PIE measurements for the peak caused by FCMI. This work shows that metallic fuel models used to accurately represent fuel performance for smaller EBR-II pins may be used for full-length metallic fuel, such as FFTF MFF assemblies and the Versatile Test Reactor (VTR). As new material models and PIE measurements become available, FFTF MFF assessment cases will be reassessed to further BISON model development.
Development of an Improved Decision Support Tool for Geothermal Site Selection in Nigeria Based on Comprehensive Criteria
Authors: Nwaiwu Uchechukwu , Leach Matthew , Liu Lirong
Published: November 2023

Geothermal resource assessment is crucial for the rural electrification of Nigeria. A comprehensive set of criteria was used to appraise promising geothermal sites in Nigeria. The evaluation of the sites was performed using the multi-criteria decision analysis (MCDA) method and taking into account evidence of a wide range of criteria from a set of geological, geophysical, well log, environmental, remote sensing, and geochemical datasets to appraise promising geothermal sites and to add to the current debate on the needed criteria for geothermal development. To gather relevant data, various sources such as bottom-hole temperature (BHT) data from different boreholes and oil and gas wells, aeromagnetic maps, reduced-to-the-pole, magnetic, heat flow, seismic, and geothermal gradient data from aerogravity maps, Bouguer anomaly maps, earthquake epicenter maps, satellite images, and geological maps were obtained from the literature. A case study of the thirty-six states of Nigeria, including the federal capital territory, Abuja (FCT), was conducted to illustrate how these criteria would reveal the technical aspect of the geothermal energy situation. A model was developed to show that the application of a wide range of criteria to the six datasets identified and analyzed in this study reveals that the datasets complement each other and should not be used independently. It can be found from the overall suitability map that more than 20% of the study area is suitable for geothermal energy development. It can also be observed from the map that some of the promising sites in Nigeria may include but are not limited to Bauchi, FCT, Taraba, Ebonyi, Adamawa, Oyo, and Nasarawa states in Nigeria. The opportunities for the further application of the approach are discussed, including the use of the model to help policymakers decide where to invest in the future.
Thermal Destruction of Waste and the Impact of the Presence of Cl and S in Waste on the Emissions of Cu, Ni, and Pb and Their Immobilisation in the Ash Residue
Authors: Król Danuta , Motyl Przemysław , Poskrobko Sławomir , Łuniewski Stanisław
Published: November 2023

This study addresses the pressing environmental problem of the emissions of ecotoxic heavy metals from high-temperature waste combustion processes, including incineration and pyrolysis. Such emissions pose a serious threat to ecosystems and human health. This study investigated the behaviour of the heavy metals Cu, Ni, and Pb during the combustion of various waste materials such as plastic waste, pharmaceutical waste, and pesticide waste. To limit the release of heavy metals into the exhaust gas stream, various additives were used: divanadium pentoxide (V2O5), borax (Na2B4O7), and their mixtures with calcium oxide (CaO). Additionally, this study examined the impact of the content of chlorine heteroatoms (Cl) in burned waste materials on the emission levels of Cu, Ni, and Pb. The findings shed light on the mobility of ecotoxic heavy metals in high-temperature waste incineration processes (1273, 1373 K) and offer insight into strategies to improve their immobilisation in grate residues. At a temperature of 1273 K, V2O5 with CaO reduced Pb emissions by ~65% for plastic waste and by ~40% for pesticide.
Large Eddy Simulation of Flow Characteristics around Cylinders with Crosswise and Streamwise Arrangements in Ocean Energy
Authors: Zhai Weiming , Liu Ming , Huang Changjiu , Cheng Daoxi , Tan Lei
Published: November 2023

The flow around cylinders is one of the most fundamental phenomena in extracting wave energy from ocean waves. Compared with flows around a single cylinder, the investigation of flows around multiple cylinders is still limited and requires further studies to reveal flow characteristics. To this end, large eddy simulations are conducted to investigate the flow around double cylinders with crosswise and streamwise arrangements. Systematic studies on the influence of the number of mesh cells, the first near-wall mesh size, and the transient time step are carried out to achieve accurate and efficient simulations. The drag coefficient, flow separation, and flow pattern for different arrangements under various cylinder spacings are analyzed according to simulation results. For the crosswise arrangement, the flow pattern switches from the single-body regime to the synchronized vortex-shedding regime as the spacing increases. For the streamwise arrangement, the flow pattern develops from the reattachment regime to the vortex-shedding regime as the spacing increases.
Special Issue: “X-Linked Hypophosphatemia”
Authors: Fukumoto Seiji , Hasegawa Yukihiro
Published: November 2023

Rickets and osteomalacia are associated with impaired mineralization in growth plate cartilage and the bone osteoid [...]
The Impact of Top-Layer Sliced Lamella Thickness and Core Type on Surface-Checking in Engineered Wood Flooring
Authors: Grubîi Victor , Johansson Jimmy
Published: November 2023

Surface-checking is a significant quality issue of veneer and sliced lamellae-based wood products. This study explores how surface-checking in sliced lamellae-based engineered wood Flooring (EWF) is influenced by two key structure parameters: core type and top-layer thickness. The core types assessed were a standard solid wood lamellae with a veneer back-end layer (S), a standard solid wood lamellae core with veneer back-end layers on the two sides (DS), and a single-layer oriented strand board (OS) core. The EWF element’s top-layer lamellae were plain sliced at nominal dimensions of 1.5, 2.5, 3.5, and 4.5 mm from freshly sawn slabs of European oak (Quercus spp.). The surface-checking of EWF specimens was quantified based on a digital image correlation (DIC) method, which outputs a surface-checking index. The surface-checking results were evaluated using a Tweedie compound Poisson data distribution to fit a general linear model. The model evaluated the impact of individual factors, sliced lamellae thickness and core type, and their interaction. The checking index confidence intervals were estimated using a bootstrapping technique. Findings reveal a significant interaction between studied factors and provide insight into optimizing top-layer thickness and core construction to diminish surface-checking. A low sliced lamella thickness on standard solid wood lamellae core resulted in low surface-checking, deemed relevant for further research.
Assessing and Mapping Changes in Forest Growing Stock Volume over Time in Bashkiriya Nature Reserve, Russia
Authors: Belan Larisa , Suleymanov Azamat , Bogdan Ekaterina , Volkov Aleksandr , Gaysin Ildar , Tuktarova Iren , Shagaliev Ruslan
Published: November 2023

There is growing recognition that forest ecosystems are a key component in the global carbon cycle, and there is a clear demand for their study. This research is a comparative analysis of forest growing stock volume (GSV) and determination of annual growth in Bashkiriya Nature Reserve (Russia) for 1979 and 2015 using 8395 and 8405 observation plots, respectively. Also, we evaluated the spatial distribution and produced digital maps of the species and their GSV for each year. The results showed that pine and birch were the dominant species (60.5 and 24.8% of the area in 2015, respectively) and there were no significant changes in the area of stands during the 36-year period. We found that the GSV in the reserve had increased by an average of 23.2% over the 36-year period. Specifically, the total forest GSV increased from 7,678,960 in 1979 to 10,003,890 m3 in 2015, representing an annual gain of 0–1.5 m3/ha. The increase in GSV was mainly associated with an increase in birch and pine trees. The annual growth of GSV was determined as 1.8–2.1 and 1.4 m3/ha per year for pine and birch forests, respectively. However, these types of trees belong to the age categories of mature and overmature stands, i.e., with reduced intensity of GSV gain. Digital maps produced as part of this study provide a visual representation of the changes in forest spatial patterns and GSV over time, highlighting areas of the reserve where the stock has increased or decreased. This study leveraged a substantial dataset, which provided valuable retrospective insights into the dynamics of pristine forest ecosystems, allowing for the assessment of changes over a 36-year period. Overall, this study highlights the importance of the ongoing monitoring and assessment of GSV levels, especially in the context of rapidly changing environments and climates.
Temporal Variability in Soil Greenhouse Gas Fluxes and Influencing Factors of a Primary Forest on the Eastern Qinghai-Tibetan Plateau
Authors: Liu Shun , Luo Da , Xu Gexi , Wu Jiamei , Feng Qiuhong , Shi Zuomin
Published: November 2023

Soil greenhouse gas (GHG) fluxes relate to soil carbon and nitrogen budgets and have a significant impact on climate change. Nevertheless, the temporal variation and magnitude of the fluxes of all three major GHGs (CO2, CH4 and N2O) and their influencing factors have not been elucidated clearly in primary forests on the eastern Qinghai-Tibetan Plateau. Herein, field chamber GHG fluxes from May to November, soil microbial community and enzyme activity were analyzed in a fir-dominated (Abies fargesii var. faxoniana) primary forest. The emission rates of CO2 and N2O ranged between 64.69–243.22 mg CO2 m−2 h−1 and 1.69–5.46 ug N2O m−2 h−1, exhibiting a temporally unimodal pattern with a peak in July. The soil acted as a CH4 sink, and the uptake rate varied between 52.96 and 84.67 μg CH4 m−2 h−1 with the higher uptake rates in June and November. The temporal variation in the CO2 flux was significantly correlated with the geometric mean of enzyme activities, suggesting that the soil CO2 flux was determined by microbial activity rather than soil microbial biomass. The soil N2O flux was positively related to nitrate concentration with marginal significance, probably because N2O was a byproduct of nitrification and denitrification processes. The soil CH4 uptake was closely associated with methanotrophic biomass (18:1ω7c). The results highlight divergent temporal dynamics of GHG fluxes owing to different driving mechanisms and an important CH4 sink in the primary forest soil, helping to evaluate the carbon and nitrogen budgets of primary forests on the eastern Qinghai-Tibetan Plateau.
Characterization of Fermentations with Controlled Temperature with Three Varieties of Coffee (Coffea arabica L.)
Authors: Peñuela-Martínez Aida Esther , García-Duque Jhoan Felipe , Sanz-Uribe Juan Rodrigo
Published: November 2023

Temperature control is the starting point for the development of controlled fermentation and improving coffee quality. The characteristics of coffee varieties can influence fermentation behavior. To evaluate the effect of the coffee variety on the behavior of controlled fermentation and on coffee quality, a completely randomized design was used with three varieties (Castillo, Cenicafé1 and Tabi) and two control temperatures (15 and 30 °C). Spontaneous fermentation was the control for each controlled process. The fermentation time, pH, glucose and lactic acid contents, as well as, the count of mesophiles, yeasts, lactic acid bacteria (LAB) and acetic acid bacteria (AAB), were assessed. The sensory quality of the coffee was classified as very good and excellent based on the variety, with averages above 82 Specialty Coffee Association (SCA) points. The highest values were for the Cenicafé1 variety. Fermentation behaviors were similar among varieties but not based on the given condition. Compared with spontaneous fermentation, the treatment at 15 °C prolonged the degradation of mucilage in more than 24 h; additionally, there were differences in the final pH values, less than 3.5 and close to 4.0, respectively. Quality was not significantly different between the controlled fermentation and the spontaneous fermentation (Wilcoxon test p > 0.05) or between fermentation temperatures (Kruskal–Wallis test p > 0.05).
Maximizing UAV Coverage in Maritime Wireless Networks: A Multiagent Reinforcement Learning Approach
Authors: Wu Qianqian , Liu Qiang , Wu Zefan , Zhang Jiye
Published: November 2023

In the field of ocean data monitoring, collaborative control and path planning of unmanned aerial vehicles (UAVs) are essential for improving data collection efficiency and quality. In this study, we focus on how to utilize multiple UAVs to efficiently cover the target area in ocean data monitoring tasks. First, we propose a multiagent deep reinforcement learning (DRL)-based path-planning method for multiple UAVs to perform efficient coverage tasks in a target area in the field of ocean data monitoring. Additionally, the traditional Multi-Agent Twin Delayed Deep Deterministic policy gradient (MATD3) algorithm only considers the current state of the agents, leading to poor performance in path planning. To address this issue, we introduce an improved MATD3 algorithm with the integration of a stacked long short-term memory (S-LSTM) network to incorporate the historical interaction information and environmental changes among agents. Finally, the experimental results demonstrate that the proposed MATD3-Stacked_LSTM algorithm can effectively improve the efficiency and practicality of UAV path planning by achieving a high coverage rate of the target area and reducing the redundant coverage rate among UAVs compared with two other advanced DRL algorithms.
Countervailing Conflicts of Interest in Delegation Games
Authors: Chiba Saori , Leong Kaiwen
Published: November 2023

In this paper, we investigate optimal delegation mechanisms in the presence of countervailing conflicts of interest in the context of principal–agent problems. We introduce two dimensions of conflict of interest—pandering incentives related to the outside option and project biases. We compare three delegation mechanisms: full delegation, veto-based delegation, and communication (no delegation). Contrary to conventional one-dimensional conflict models, our findings reveal a non-monotonic relationship between pandering incentives and bias. These conflicts counterbalance each other, resulting in a principal’s benefit from delegation not strictly decreasing with increased bias. Surprisingly, delegation to a biased agent can be advantageous in certain scenarios. This research sheds light on the complex dynamics of delegation mechanisms when confronted with countervailing conflicts of interest, offering insights into decision-making in principal–agent relationships.
Differential Expression of Circadian Clock Genes in the Bovine Neuroendocrine Adrenal System
Authors: Earnhardt-San Audrey L. , Baker Emilie C. , Riley David G. , Ghaffari Noushin , Long Charles R. , Cardoso Rodolfo C. , Randel Ronald D. , Welsh Thomas H.
Published: November 2023

Knowledge of circadian rhythm clock gene expression outside the suprachiasmatic nucleus is increasing. The purpose of this study was to determine whether expression of circadian clock genes differed within or among the bovine stress axis tissues (e.g., amygdala, hypothalamus, pituitary, adrenal cortex, and adrenal medulla). Tissues were obtained at an abattoir from eight mature nonpregnant Brahman cows that had been maintained in the same pasture and nutritional conditions. Sample tissues were stored in RNase-free sterile cryovials at −80 °C until the total RNA was extracted, quantified, assessed, and sequenced (NovaSeq 6000 system; paired-end 150 bp cycles). The trimmed reads were then mapped to a Bos taurus (B. taurus) reference genome (Umd3.1). Further analysis used the edgeR package. Raw gene count tables were read into RStudio, and low-expression genes were filtered out using the criteria of three minimum reads per gene in at least five samples. Normalization factors were then calculated using the trimmed mean of M values method to produce normalized gene counts within each sample tissue. The normalized gene counts important for a circadian rhythm were analyzed within and between each tissue of the stress axis using the GLM and CORR procedures of the Statistical Analysis System (SAS). The relative expression profiles of circadian clock genes differed (p < 0.01) within each tissue, with neuronal PAS domain protein 2 (NPAS2) having greater expression in the amygdala (p < 0.01) and period circadian regulator (PER1) having greater expression in all other tissues (p < 0.01). The expression among tissues also differed (p < 0.01) for individual circadian clock genes, with circadian locomotor output cycles protein kaput (CLOCK) expression being greater within the adrenal tissues and nuclear receptor subfamily 1 group D member 1 (NR1D1) expression being greater within the other tissues (p < 0.01). Overall, the results indicate that within each tissue, the various circadian clock genes were differentially expressed, in addition to being differentially expressed among the stress tissues of mature Brahman cows. Future use of these findings may assist in improving livestock husbandry and welfare by understanding interactions of the environment, stress responsiveness, and peripheral circadian rhythms.
Selective Sweeps in Cattle Genomes in Response to the Influence of Urbanization and Environmental Contamination
Authors: Velayudhan Silpa Mullakkalparambil , Alam Shahin , Yin Tong , Brügemann Kerstin , Buerkert Andreas , Sejian Veerasamy , Bhatta Raghavendra , Schlecht Eva , König Sven
Published: November 2023

A genomic study was conducted to identify the effects of urbanization and environmental contaminants with heavy metals on selection footprints in dairy cattle populations reared in the megacity of Bengaluru, South India. Dairy cattle reared along the rural–urban interface of Bengaluru with/without access to roughage from public lakeshores were selected. The genotyped animals were subjected to the cross-population–extended haplotype homozygosity (XP-EHH) methodology to infer selection sweeps caused by urbanization (rural, mixed, and urban) and environmental contamination with cadmium and lead. We postulated that social-ecological challenges contribute to mechanisms of natural selection. A number of selection sweeps were identified when comparing the genomes of cattle located in rural, mixed, or urban regions. The largest effects were identified on BTA21, displaying pronounced peaks for selection sweeps for all three urbanization levels (urban_vs_rural, urban_vs_mixed and rural_vs_mixed). Selection sweeps are located in chromosomal segments in close proximity to the genes lrand rab interactor 3 (RIN3), solute carrier family 24 member 4 (SLC24A4), tetraspanin 3 (TSPAN3), and proline-serine-threonine phosphatase interacting protein 1 (PSTPIP1). Functional enrichment analyses of the selection sweeps for all three comparisons revealed a number of gene ontology (GO) and KEGG terms, which were associated with reproduction, metabolism, and cell signaling-related functional mechanisms. Likewise, a number of the chromosomal segments under selection were observed when creating cattle groups according to cadmium and lead contaminations. Stronger and more intense positive selection sweeps were observed for the cadmium contaminated group, i.e., signals of selection on BTA 16 and BTA19 in close proximity to genes regulating the somatotropic axis (growth factor receptor bound protein 2 (GRB2) and cell ion exchange (chloride voltage-gated channel 6 (CLCN6)). A few novel, so far uncharacterized genes, mostly with effects on immune physiology, were identified. The lead contaminated group revealed sweeps which were annotated with genes involved in carcass traits (TNNC2, SLC12A5, and GABRA4), milk yield (HTR1D, SLCO3A1, TEK, and OPCML), reproduction (GABRA4), hypoxia/stress response (OPRD1 and KDR), cell adhesion (PCDHGC3), inflammatory response (ADORA2A), and immune defense mechanism (ALCAM). Thus, the findings from this study provide a deeper insight into the genomic regions under selection under the effects of urbanization and environmental contamination.