bluuebunny/crossref_metadata_2025 huggingface dataset:
Atmospheric Carbon Dioxide: A Fresh Look at Exchange Flux, Isotopic Carbon, Fossil Fuel Emissions and Residence Time
Authors: Taylor Stephen
Published: March 2024

This paper presents a new implementation of a 2-box absolute flow model, enabling the calculation of CO2 transfer between the atmosphere and a mixing reservoir representing the combined effect of the terrestrial and ocean regions. The model uses published values of anthropogenic CO2 fossil fuel emissions (CO2ff), atmospheric CO2 mixing ratio and nuclear weapons bomb yields, to compute atmospheric d13C and Δ14C time-series. The level of agreement between the calculated values and the accepted values for d13C is within ± 0.05 ‰, and for Δ14C is within ± 3‰, spanning 200 years. The model contains only seven internal parameters; these are varied to optimize the fit, leading to reasonable parameter values, indicating the validity of the method. In addition, the model shows how a rising CO2 exchange influx fluctuating with surface temperature is compatible with a nett atmospheric CO2 sink. The study demonstrates that a single CO2 residence time applies to both the 14C bomb pulse and the anthropogenic flux, contrary to the conventional view that "bomb radiocarbon and anthropogenic CO2 do not behave identically." [Joos 1994 Nature 370, 181–182]. It is shown that the difference in behaviour, claimed to be due to seawater chemistry, is not significant in practice since fluctuating bulk carbon dominates fluctuating isotopic ratio. A new analysis of the airborne fraction indicates that the assumption of a time-dependent exchange influx results in a similar residence time for bulk CO2 as for 14C in the nuclear bomb pulse, reinforcing the view that the 12C, 13C and 14C carbon isotopic forms of CO2 behave similarly in the carbon cycle.
A Comprehensive Review of Organ-on-a-Chip Technology and Its Applications in Disease Diagnostics
Authors: Farhang Doost Negar , Srivastava Soumya K
Published: March 2024

Organ-on-a-chip (OOC) is an emerging technology that simulates an artificial organ within a microfluidic cell culture chip. Current cell biology research focuses on in vitro cell culture due to various limitations of in vivo testing. Unfortunately, in vitro cell culture fails to provide an accurate microenvironment, and in vivo cell culture is expensive and has historically been a source of ethical controversy. OOC aims to overcome these shortcomings and provide the best of both in vivo and in vitro cell culture research. The key component of the OOC design is utilizing microfluidics to ensure a stable concentration gradient, dynamic mechanical stress modeling, and accurate reconstruction of a cellular microenvironment. OOC also has the advantage of complete observation and control of the system, which is impossible to recreate in in vivo research. Multiple throughputs, channels, membranes, and chambers are constructed in a polydimethylsiloxane (PDMS) array to simulate various organs on a chip. Various experiments can be performed utilizing OOC technology, including drug delivery research and toxicology. Current technological expansions involve multiple organ microenvironments on a single chip, allowing for studying inter-tissue interactions. Other developments in the OOC technology include finding a more suitable material as a replacement for PDMS and minimizing artefactual error and non-translatable differences.
Descartes’ error with love
Authors: Durand Jean-Olivier
Published: March 2024

We are losing love. By studying porn movies to understand love, I discovered that love originally comes from the body, from positive emotions and vibrations of the wonderful body, from the heart and all other parts of the body, such as sexual organs. António Damásio made Descartes’ error by postulating that feelings increase their power from homeostasis (mechanisms of life regu-lation from bacteria to humans). He made this mistake unconsciously because many people un-consciously have a very bad opinion of sexual organs. We consider them ugly because they come from the prehistoric period. I have combined António and Hanna Damásio’s work (body emotions, thinking and language). I discovered that porn actors do not talk during sex, and this is striking. Porn actors mirror what happens in society. This means that people come from prehistory, do not talk during sex, and still unconsciously behave like primitive animals during sexual intercourse; we do not respect the body sufficiently during sex. Therefore, love, which comes from the body, is smothered and buried. We must very delicately talk to the wonderful, delicious and respectful body to wake up love feelings, body emotions and vibrations during sex. We must invent talking movies with porn films. Language of positive emotions associated with the language of wonderful and delicious body will warm love feelings and will give envy to love through sexual intercourse because António Damásio discovered that emotions are social.
Joint Action of Trichoderma atroviride and a Vegetal Derived-Protein Hydrolysate Improves Yield, Fruit Quality and Economic Profitability of Two Woodland Strawberry Cultivars Grown Under Greenhouse
Authors: Vultaggio Lorena , Allevato Enrica , Consentino Beppe Benedetto , Bellitto Pietro , Napoli Simona , Cannata Claudio , Ntatsi Georgia , Vasto Sonya , Baldassano Sara , La Bella Salvatore , Leto Claudio , Sabatino Leo
Published: March 2024

Woodland strawberry (Fragaria vesca L.) is an underutilized plant species, appreciated by consumers for its qualitative features. Utilizing technical means of production, such as plant biostimulants, that can increase crop productivity and quality could be highly important in woodland strawberry cultivation. The scope of the present study was to appraise the influence of two biostimulants (Trichoderma atroviride and plant protein hydrolysate) - used either alone or combined - on plant performance and economic profitability of two woodland strawberry genotypes (‘Alpine’ and ‘Regina delle Valli’). Overall, data showed that ‘Alpine’ had the highest productive performances, whereas ‘Regina delle Valli’ revealed the highest fruit qualitative traits. T. atroviride inoculation and V-PH application significantly boosted plant marketable yield (+20.5% for T. atroviride and +12.9% for V-PH), total sugars (+1.9% for Trichoderma and +1.4% for V-PH) and anthocyanins (+14.1% for T. atroviride and +9.8% for V-PH) compared to non-treated plants. Plants supplied with both biostimulants had higher marketable yield (+34.8%), mean fruit weight (+6.0%), fruit dry matter (+13.8%), total sugars (+3.5%), ascorbic acid (+12.7%), flavonoid (+26.3%) and anthocyanins (+29.9%) compared to non-treated plants. Furthermore, our study revealed that the highest fruit polyphenols concentration was recorded in both genotypes treated with the combination of biostimulants and in ‘Regina delle Valli’ sprayed with V-PH, whereas the highest antioxidant activity was found in ‘Regina delle Valli’ fruit when plants were supplied with both biostimulants. Our study pointed out that the application of microbial and non-microbial biostimulants, especially in combination, might be an useful strategy for improving performances of underutilized species and, therefore, encourage its cultivation, valorisation and economic profitability (+10195.3 €/ha when plants were exposed to both biostimulants).
Prediction of Ground Reaction Forces and Moments and Joint Torques during Level Walking through Optical Motion Capture using a Multibody Dynamics Model and Foot Deformations without Optimization Techniques
Authors: Haraguchi Naoto , Hase Kazunori
Published: March 2024

Predicting ground reaction forces (GRFs) and ground reaction moments (GRMs) through a biomechanical model-based approach offers advantages for biomechanical analysis, particularly in situations where the application of a statistical model is limited by insufficient training data. However, the current prediction method is unsuitable for clinical applications due to its long computational time. The present study developed a new optical motion capture (OMC)-based method to predict GRFs, GRMs, and joint torques. The proposed approach performed the estimation process by distributing external forces, as determined by the equation of motion, between the left and right feet based on foot deformations, thereby predicting the GRFs and GRMs without relying on machine learning or optimization techniques. We investigated the prediction accuracy during walking by comparing a conventional analysis using a force plate with the OMC results. The comparison revealed excellent or strong correlations between the prediction and measurement for all GRFs, GRMs, and lower limb joint torques. The proposed method, which provides practical estimation with low computational cost, facilitates efficient biomechanical analysis and rapid feedback of analysis results, thereby increasing its applicability for kinetics estimation in clinical settings.
Dynamic Simulation of the Leaf Mass Per Area (LMA) in Multilayer Crowns of young Larix principis-rupprechtii
Authors: Wang Jinshan , Zhou Ying , Ji Cuiying , Xie Longfei , Liu Qiang , Zhang Zhidong
Published: March 2024

Leaf mass per area (LMA) is a key structural parameter that reflects the functional traits of leaves and plays a vital role in simulating the material and energy cycle of plant ecosystems. In this study, vertical whorl-by-whorl sampling of LMA was conducted in a young Larix principis-rupprechtii plantation during the growing season at the Saihanba Forest Farm. The vertical and seasonal variations in LMA were analysed. Subsequently, a predictive model of LMA was constructed. The results revealed that the LMA varied significantly between different crown whorls and growing periods. In the vertical direction of the crown, the LMA decreased with increasing crown depth, but the range of LMA values from the tree top to the bottom was, on average, 30.4 g/m2, which was approximately 2.5 times greater in the fully expanded phase than in the early leaf-expanding phase. The LMA exhibited an allometric growth trend that increased during the leaf-expanding phase and then tended to stabilize. However, the range of LMA values throughout the growing period was, on average, 40.4 g/m2. Among the univariate models, the leaf dry matter content (LDMC) performed well (Ra2=0.45, RMSE=13.48 g/m2) in estimating the LMA. The correlation between LMA and LDMC significantly differed at different growth stages and at different vertical crown whorls. The dynamic predictive model of LMA constructed with the RDINC and DOY as independent variables was reliable in both the assessments (Ra2=0.68, RMSE=10.25 g/m2) and the validation (MAE=8.05 g/m2, FI=0.682). Dynamic simulations of crown LMA provide a basis for elucidating the mechanism of crown development and laying the foundation for the construction of an ecological process model..
Intention Recognition in Digital Forensics: Systematic Review
Authors: Kassa Yidnekachew Worku , James Joshua Isaac , Belay Elefelious Getachew
Published: March 2024

In this comprehensive review, we delve into the realm of intention recognition within the context of digital forensics and cybercrime. The rise of cybercrime has become a major concern for individuals, organizations, and governments worldwide. Digital forensics is a field that deals with the investigation and analysis of digital evidence in order to identify, preserve, and analyze information that can be used as evidence in a court of law. Whereas, Intention recognition is a subfield of artificial intelligence that deals with the identification of agents’ intentions based on their actions and change of states. In the context of cybercrime, intention recognition can be used to identify the intentions of cybercriminals and even to predict their future actions. Employing a meticulous six-step systematic review approach, we curated research articles from reputable journals and categorized them into three distinct modeling approaches: logic-based, classical machine learning-based, and deep learning-based. Notably, intention recognition has transcended its historical confinement to network security, now addressing critical challenges across various subdomains, including social engineering attacks, AI black box vulnerabilities, and physical security. While deep learning emerges as the dominant paradigm, its inherent lack of transparency poses unique challenges in the digital forensics landscape. We advocate for hybrid solutions that blend deep learning’s power with interpretability. Furthermore, we propose the creation of a comprehensive taxonomy to precisely define intention recognition, paving the way for future advancements in this pivotal field.
Analyzing the Influence of Speed and Jumping Performance Metrics on Percentage Change of Direction Deficit in Adolescent Female Soccer Players
Authors: Roso-Moliner Alberto , Gonzalo-Skok Oliver , Villavicencio-Álvarez Victor Emilio , Calero-Morales Santiago , Mainer-Pardos Elena
Published: March 2024

Studies show that although female soccer players often have shorter change of direction (COD) deficits than males, indicating different biomechanical profiles, there is lack of research on the impact of physical metrics on COD performance in females. The aim of this study was to analyze whether performance metrics based on speed, and jumping could explain the variation in %CODD in young female soccer players. Thirty-three highly trained adolescent female soccer players (age: 16. ± 0.95 years; height: 160.4 ± 5.22 cm; body mass: 55.7 ± 7.22 kg) performed COD180 tests, 10-m and 30-m sprint test and single leg countermovement and horizontal jumps. Acceleration in the first 10 meters of a sprint was identified as a significant predictor of COD180 performance (R2 = 28%), (R2 = 50%), (p
Importance of Soil Health for Coffea spp Cultivation, from a Cooperative Society in Puebla, Mexico
Authors: Molina-Monteleón Carol Meritxell , Mauricio-Gutiérrez Amparo , Castelán-Vega Rosalía , Tamariz-Flores José Victor
Published: March 2024

The cultivation systems of Coffea spp in a cooperative society in Puebla, Mexico, include rustic, traditional polyculture, commercial polyculture, unshaded monoculture and shaded monoculture. In this work, the properties of the soil were analyzed through physical, chemical, and biological analysis to determine its nutritional status. Composite sample analyses were conducted to determine physical, chemical and microbiological parameters (fungi, actinomycetes, mesophilic bacteria, nitrifying and denitrifying bacteria). Leaf nutrients were determined. Rustic was the cropping system with the highest amount of K (0.76 cmol kg-1) in soil and nutrient assimilation in leaf (N= 2.79%, P= 660.01, K= 17297.22 and Fe= 271.24 mg kg-1) (p= 0.001); in addition to presenting high populations of mesophilic bacteria, fungi and actinomycetes (30.16, 0.59 and 0.83 respectively, x10 6 CFU g-1 soil) and very low nitrification and denitrification rates. The principal component analysis (PCA) (>3.25%) indicated that actinomycetes and K in soil favor the assimilation of Fe, K and P. This Coffea spp cultivation system had a lower impact on soil health than the rest of the systems and favored forest ecosystem conservation.
Molecular Markers and Regulatory Networks in Solventogenic Clostridium Species: Metabolic Engineering Conundrum
Authors: Olorunsogbon Tinuola , Okonkwo Christopher Chukwudi , Ezeji Thaddeus Chukwuemeka
Published: March 2024

Solventogenic Clostridium species are important for establishing sustainable industrial bioproduction of fuels and important chemicals. The inherent versatility of these species in substrate utilization and the range of solvents produced during acetone butanol-ethanol (ABE) fermentation make solventogenic Clostridium an attractive choice for biotechnological applications such as production of fuels and chemicals. The functional qualities of these microbes have thus been identified to be due to complex regulatory networks that play essential roles in modulating the metabolism of this group of bacteria. Genomes of solventogenic Clostridium species have relatively greater prevalence of genes that are intricately controlled by various regulatory molecules than most other species. Consequently, the use of genetic or metabolic engineering strategies that do not consider the underlying regulatory mechanisms will not be effective. Several regulatory factors involved in substrate uptake/utilization, sporulation, solvent production, and stress responses (Carbon Catabolite Protein A, Spo0A, AbrB, Rex, CsrA) have been identified and characterized. In this review, the focus is on newly identified regulatory factors in solventogenic Clostridium species, the interaction of these factors with previously identified molecules, and potential implications on substrate utilization, solvent production, and resistance/tolerance to lignocellulose-derived microbial inhibitory compounds.
The Political Economy of Fears and Concerns of Landslide Survivors: Thematic Analysis of Mental Well‐Being of People Residing in Landslide Susceptible Areas of Kerala, India
Authors: Ratheesh Mon P. , Sekher T.V.
Published: March 2024

Being forced to live in an area following a catastrophic landslide may adversely impact people's mental well-being. Unprivileged communities such as Adivasis, Dalits, plantation workers, and people with low incomes in Kerala's hilly districts are forced to live in landslide-affected areas despite their fear. This paper examines the fears and concerns of landslide survivors from the marginalized sections of society from a broader framework of the political economy of mental health. This approach aligns with the assertion made by the World Health Organisation that individual factors do not solely determine mental health but are intricately linked to broader social, political, and economic circumstances. Data were collected through in-depth interviews with fatal landslide survivors and key informants [ ]. The study employed thematic data analysis from in-depth interviews of various fatal landslide survivors since 2018. The three major themes unveiled in the analysis are: 1. post-disaster fears, 2. The factors that triggered fear and concern and 3. Socio-economic marginality and mental health. The study asserts that individuals who are poor and unprivileged are highly susceptible to mental health issues associated with landslides.
Comparative Analysis and Prediction of Sustainable Development in Earthquake Preparedness: A Cross-Cultural Perspective on Montenegro, North Macedonia, and Serbia
Authors: Grozdanić Goran , Cvetković Vladimir M. , Lukić Tin , Ivanov Aleksandar
Published: March 2024

Authorities and governmental bodies strongly emphasize the importance of residents preparing for natural disasters, particularly underscoring the significance of readiness for geophysical hazards like earthquakes. In this study, which represents comparative quantitative research, the levels and predictors of the impact on preparedness for earthquake-induced disasters in South-Eastern Europe countries such as Montenegro, North Macedonia, and Serbia are examined. Using the snowball sampling technique (online questionnaire), a survey of 1245 respondents (Montenegro (n = 400), North Macedonia (n = 345), and Serbia (n = 500) was conducted from February 2023 to February 2024. The paper is based on the central hypothesis that the most significant predictor of earthquake preparedness in Montenegro, North Macedonia, and Serbia is age, followed by gender and education. Multivariate regression analysis was used to determine the extent to which five scores of the subscales (household preparedness, community preparedness, disaster preparation, earthquake risk awareness, reinforced house) were associated with seventh demographic and socio-economic variables. In addition to the mentioned analysis, other statistical analyses such as T-test, one-way ANOVA analysis, and Pearson correlation were also utilized. The results indicate that age emerges as a predictor in various aspects of earthquake-induced disaster preparedness and awareness in most models, followed by education. These findings confirm the significance of respondents' age in determining levels of preparedness and earthquake awareness. Overall, in North Macedonia, respondents recorded the highest ratings (M = 3.52) for household preparedness for earthquakes, compared to Montenegro (M = 2.98) and Serbia (M = 3.26), where the lowest ratings were recorded. Research findings, taking into account cultural characteristics, can serve as a basis for the development of targeted interventions, strategies, policies, and programs aimed at improving the level of societal preparedness for earthquake-induced disasters.
Research Status and Development Trends of Active Control Technology for Pantograph in High-Speed Railways
Authors: Yu Shengdong , Sun Quan , Zhang Dongyuan , Jiang Zan
Published: March 2024

Among the major systems of high-speed rail, the arch network relationship, wheel-rail relationship and fluid-structure coupling relationship are important links affecting the performance of high-speed rail, and also the main control factors affecting the speed limit of high-speed rail. From this perspective, the contact state and interactive relationship between pantograph and catenary are the key factors affecting the forward performance of high-speed rail. As a key component in the pantograph system, the actuator is responsible for adjusting the contact force and position between the pantograph and the contact line. The performance characteristics of the actuator, such as response speed, accuracy, stability and durability, directly affect the control performance of the whole pantograph system. In this paper, the research status of the active control technology of high-speed railway pantograph is reviewed, and the future development direction is pointed out, which provides a new idea for the development of pantograph technology.
Object-Oriented Modeling of Classic Physical Systems using Linear Implicit Equilibrium Dynamics
Authors: Zimmer Dirk
Published: March 2024

Pairs of potential and flow variables have long been established for interfacing object-oriented component models of physical systems. Recently, however, the use of triplets has been discovered for the purpose of robust modeling. New and powerful Modelica libraries have been developed such as the DLR ThermoFluid Stream library or the introduction of the Dialectic Mechanics library. Their use of triplets is entangled with a special modeling approach that uses Linear Implicit Equilibrium Dynamics. In this paper, we study the basic motivation of this approach, its benefits and drawbacks before we finally demonstrate how it beneficially impacts the generation of corresponding simulation code.
The Response of Mixed Layer Depth due to Extreme Weather Events
Authors: Lee Wonhyun , Veeramony Jayaram
Published: March 2024

The ocean’s mixed layer depth (MLD) plays an important role in understanding climate dynamics, especially during extreme weather occurrences like hurricanes. This study investigates the effects of Hurricane Katrina (2005) on the MLD in the Gulf of Mexico, using the Delft3D modeling system. By integrating hydrodynamics and wave dynamics modules, we simulate the ocean’s response to extreme weather, focusing on temperature, salinity and MLD variations. Our analysis reveals significant cooling and mixing induced by Katrina, resulting in spatial and temporal fluctuations in temperature (~± 4°C) and salinity (~± 2.5 ppt). The MLD is estimated using a simple threshold method, revealing a substantial deepening to ~120 m on August 29th-30th during Hurricane Katrina in the middle of northern Gulf of Mexico, compared to an average MLD of ~20-40 m during pre-storm conditions. It took about 18-days to recover to ~84% of the pre-storm level after Katrina. Compared to the stand-alone FLOW model, the coupled FLOW+WAVE model yields a deeper MLD of ~5%. The MLD recovery and wave effect on the MLD provide insights from various scientific, environmental and operational perspectives, offering a valuable basis for ocean management, planning and applications, particularly during extreme weather events.
Pseudo-Dynamic Tests on Frame-Shear Wall Structure with Precast Concrete Diaphragm
Authors: Han Chun , Dong Xinhong , Su Qunshan , Duan Chunming , Tian Guoping
Published: March 2024

In order to study the way how to improve the spatial action of precast monolithic composite floor slabs, and would replace the cast-in-place surface layer for reduce the weight of structure, using pseudo-dynamic tests on 1/4 scale models of two-span and three-story frame structure. The lateral load tests compared the stresses and displacements with cast-in-place floor frame-shear wall structure (SJ1) and precast monolithic floor frame-shear wall structure with X horizontal braces at the bottom of the floor (SJ2). The results show the X horizontal braces can improve the spatial action. Structural integrity (SJ2) as well as the effective transmission of the horizontal force can be ensured by additional X bracing at the bottom of the rigidity of the floor without cast-in-place concrete topping. The results show that X horizontal braces more effectively transfer horizontal, which provides a beneficial reference for similar research.
Application of Lightweight Design Based on Response Surface Methodology in 410t Hydraulic Climbing Mechanism
Authors: Chengwei Ju , Xianxuan Hu , Xuan Sun
Published: March 2024

The multi-objective optimization design of hydraulic climbing mechanism (the core mechanism of gantry crane) was realized by using the method of combining central composite design (CCD), Kriging and multi-objective genetic algorithm (MOGA). Firstly, the hydraulic climbing mechanism model was established and the appropriate design variables were selected. The mass, maximum deformation and maximum equivalent stress of the hydraulic climbing mechanism was taken as the optimization objectives. Through the comparative analysis of the parameters of wedge block, anchor block, anchor plate、baffle, the parameters that have the greatest impact on the optimization objectives are selected as geometric constraints. Then, according to the results of experimental design, Kriging model was used to establish the response surface optimization model of objective function. Finally, the optimal results were obtained by using MOGA method. The experimental results show that the optimization strategy is reliable, and the mass of the optimized model is reduced by 10.28%. While meeting the actual production requirements, the lightweight design of the hydraulic climbing mechanism is realized, which saves the design cost and improves the material utilization rate.
A Novel Preparation Method of Composite Bolted T-joint with High Bending Performance Based on Prepreg-RTM Co-Curing Process
Authors: Zhang Tao , Luo Zhitao , Deng Jinxin , Cheng Xiaoquan
Published: March 2024

A co-curing resin system consisting of 9368 epoxy resin for prepreg and 6808 epoxy resin for resin transfer molding (RTM) was developed. A corresponding preparation method of novel polymer composite bolted T-joint with internal skeleton and external skin was proposed based on prepreg-RTM co-curing process, and novel T-joints were fabricated. A series of conventional configuration T-joints based on RTM process and T-joints made of 2A12 aluminum alloy were prepared simultaneously. Bending performances were studied on these T-joints experimentally. The results indicate that 9368 epoxy resin and 6808 epoxy resin exhibit good compatibility in rheological and thermophysical properties. The novel T-joints prepared with prepreg-RTM co-curing process show no obvious fiber local winding or resin-rich regions inside, and the interface quality between internal skeleton and external skin is excellent. The main failure modes of the novel T-joint under bending load include separation of skin and skeleton and fracture along the thickness on the base panel; the skeleton carries the main bending load, but there is still load transfer between external skin and internal skeleton through their interface. The internal damages of the novel T-joint are highly consistent with surface damages observed visually, facilitating the detection and timely discovery of damages. The initial stiffness, damage initiation load, and ultimate load of the novel T-joint are 1.65 times, 5.89 times, and 3.45 times that of conventional T-joint, respectively. When considering the influence of density, the relative initial stiffness and relative ultimate load of the novel T-joint are 1.44 times and 2.07 times that of aluminum alloy T-joint, respectively.
Solving Confirmation Time in Sharded Blockchain with PFQN
Authors: Wu Junting , Du Haotian , Chen Jin , Ren Wei
Published: March 2024

Sharding shows great potential for extending the blockchain. The current challenge facing sharded blockchain technology lies in addressing the extended transaction confirmation times caused by isolated states between shards and unbalanced transaction allocation strategies. These factors contribute to an increase in cross-shard transactions and disproportionate shard workload, ultimately resulting in indefinite confirmation delays for cross-shard transactions. A critical priority for sharded blockchain systems is to conduct a comprehensive qualitative analysis to better understand and mitigate the prolonged transaction confirmation times. We introduce a Product-Form Queue Network (PFQN) model to address the transaction confirmation time problem in sharded blockchains and incorporate a new confirmation queue to more accurately simulate the actual transaction confirmation process in the blockchain. In addition, we provide a detailed quantitative analysis of the relationship between network load, consensus efficiency, and security in sharded blockchains, laying a theoretical foundation for achieving robustness and efficiency in sharded blockchains. This research not only contributes to addressing the scalability issues in sharded blockchains but also offers a new perspective for future research directions.
Data Driven Prediction of Severe Convection at DWD. An Overview of Recent Developments
Authors: Müller Richard , Barleben Axel
Published: March 2024

Thunderstorms endager life and infrastructure. Accurate and precise prediction of thunderstorms are therefore helpful to enable protections measures and to reduce the risks. This manuscript presents the latest developments to improve thunderstorm forecasting in the first few hours. This includes the description and discussion of a new Julia-based method (JuliaTSnos) for the temporal extrapolation of thunderstorms and the blending of this method with the numerical weather prediction model (NWP) ICON. The combination of ICON and JuliaTSnow attempts to overcome the limitations associated with the pure extrapolation of observations wit Atmospheric Motion Vectors (AMVs) and thus increase the prediction horizon. For the blending the operational ICON-D2 is used, but also the experimental ICON-RUC, which is performed with a higher data assimilation update cycle. The blended products are evaluated against lightning data. The Critical Success Index (CSI) for the blended RUC product is higher for all forecast time steps. This is mainly due to higher resolution of the AMVs (prediction hours 0-2) and the rapid update cycle of ICON-RUC (prediction hours 2-6). The results demonstrate the potential of the rapid update cycle to improve the short term forecasts of thunderstorms. Also the transition between AMV driven nowcasting to NWP is much smoother in the blended RUC product, which points to the advantages of fast data assimilation for seamless predictions. The CSI is well above the critical value of 0.5 for the 0-2 hour forecasts. However, also with RUC the CSI drops below 0.5 as soon as the last forecast is more than 3 hours away from the last data assimilation, indicating the lack of the model physics to accurately predict thunderstorms. This lack is simply a result of chaos theory. Within this scope the role of NWP in comparison with Artificial Intelligence (AI) is discussed and it is concluded that AI could replace physical short term forecasts in the near future.
Power Consumption Modeling of Airconditioning Units in an Educational Building Using Polynomial and Neural Network Fitting Techniques
Authors: Brucal Stanley Glenn , Africa Aaron Don , Navea Roy Francis , Illahi Ana Antoniette , Ubando Aristotle , Maniquiz-Redillas Marla , Gustilo Reggie , Loresco Pocholo James
Published: March 2024

There are several challenges on how to attain energy efficiency while maintaining balance among factors affecting energy consumption such as power rating and temperature setpoints of cooling units, room temperature and humidity, and indoor air quality (IAQ). A real-time energy and IAQ monitoring system were installed in an educational building to profile the operational power consumption of inverter-based air condition unit (ACU) installed in each room. Polynomial curve and neural fitting regression analysis were applied to the real-time power consumption, indoor temperature and humidity, and carbon dioxide (CO2) level data. The derived models were able to provide the stabilizing indoor thermal and air conditions of the room to reach steady state ACU power consumption. These collected data and calculated parameters can be used to define rules in automating control of cooling appliances for an efficient energy utilization. The regression approaches, using real-time data, have determined the influence of indoor heat conditions and carbon dioxide levels on ACU power consumption. These parameters were utilized to establish consistent values for temperature, humidity, and carbon dioxide levels under stable settings of inverter-based air conditioning units.
Monitoring the Wear Trend in Wind Turbines by Tracking the Fourier Vibration Spectrum and Base Density Support Vector Machine
Authors: Bisu Claudiu , Olaru Adrian , Olaru Serban , Alexei Adrian , Mihai Niculae , Ushaq Haleema
Published: March 2024

To make wind power more competitive, it is necessary to reduce turbine downtime and reduce costs associated with wind turbine Operation and Maintenance (O&M). Incorporating machine learning in developing condition-based predictive maintenance methodologies for wind turbines can enhance their efficiency and reliability. This paper presents a monitoring method that utilizes Base Density for the Support Vector Machine (BDSVM) and the evolutionary Fourier spectra of vibrations. This method allows smart monitoring of the function evolution of the turbine. A complex optimal function (FO) for 5-degree order has been developed that will be the boundary function of the BDSVM to timely determine the magnitude, frequency, and place of the failure occurring in wind turbine drive.
Forecasting Lake Nokoué Water Levels Using Long Short-Term Memory Network
Authors: Dabire Namwinwelbere , Ezin Eugene C. , Firmin Adandedji M.
Published: March 2024

The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of lake Nokoue in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Lake Nokoue, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.
Integrating Local Science and School Science: The Benefits for Preserving Local Wisdom and Promoting Students’ Learning
Authors: Kasi Yohanes Freadyanus , Widodo Ari , Samsudin Achmad , Riandi Riandi , Novia Novia , Sukmawati Wati , Shidiq Ari Syahidul
Published: March 2024

Integrating local science into science learning benefits students and the culture. However, science teaching tends to focus only on the scientific content presented in the books but ignores the local culture. This paper explores local science in community cultural activities to be implemented in science learning to introduce students to cultural values following the concept of science. It identifies local science, describes the oral arguments produced by the tribal council, and analyzes the lesson plan by five science teachers in the Nagekeo district, East Nusa Tenggara. The data used in this analysis are observation and identification, interviews, and assessment sheets. The findings show that the local science in Nagekeo cultural activities that can be integrated into science learning includes the traditional unit and measurement systems, Newton's laws in their application to the traditional game, biodiversity in the traditional hunt, the concept of heat transfer, and its application in the construction of traditional houses, and vibrations, waves, and sounds in the traditional musical instrument. Recommendations from this research are embracing local science in science learning to provide meaningful learning for students and preserve local culture for each generation in the future so that it does not become extinct. 
The Implementation of Guided Inquiry Learning Model with Edmodo to Improve Students’ Learning Outcomes on Acid-Based Subject Matter
Authors: Beskara Hasrilia , Danial Muhammad , Sulastry Taty
Published: March 2024

This study aims to determine whether guided inquiry learning assisted by Edmodo can improve the learning outcomes of high school students on acid-base subject matter. The research method used is a quasi-experiment with a quantitative approach; the research design used is a posttest-only control group design. The research subjects were students of class XI MIPA 5 (experimental group), consisting of 29 students, and class XI MIPA 6 (control group), consisting of 26 students. Data collection techniques used learning outcome tests and observation sheets to implement the learning process. The results of descriptive analysis showed that the experimental class obtained an average value of learning outcomes higher than the control class, which amounted to 81.3 for the experimental class and 71.5 for the control class. The results of inferential statistical analysis of student learning outcomes showed that the data of the two groups were not normally distributed and came from a homogeneous population. Hypothesis testing using the Mann-Whitney test obtained asymp. Sig. < α (0.001 < 0.05) so that H0 is rejected and Ha is accepted. Therefore, guided inquiry learning assisted by Edmodo can improve the learning outcomes of high school students on acid-base subject matter.
Profile of Self-Regulated Learning on First-Year Students at Science Education Department in Online Learning
Authors: Patriot Evelina Astra , Laksono Pandu Jati
Published: March 2024

Online learning requires students to study independently and manage lectures according to the time set. Researchers need to know the criteria for self-regulated learning of first-year students at the Physics Education Department. This paper aims to determine self-regulated learning during online learning. The study used a quantitative research approach with a survey method. The Online Self-Regulated Learning Questionnaire (OLSQ) collected the data, a 20-item scale with a 5-point Likert-type response format. The sample of this study was 131 students of physics and chemistry education study programs. Each was randomly selected to see how their respective study programs implemented independent learning activities during online learning. The results showed that each indicator of independent learning in online learning received a positive response through the OLSQ instrument that had been distributed. The disciplined behavior indicator has a higher percentage, followed by the exercise self-control indicator. Generally, the pre-service students have self-regulated learning with high criteria. This result can provide a good contribution and open for further research. The implication of this research can be a reference for lecturers to improve online and self-regulated learning quality.
Resiliencia empresarial y COVID. Un estudio local para el estado de Chihuahua, México
Authors: Martínez Morales Javier , González Milán David de Jesús , Avila Arce Adanelly
Published: March 2024

La resiliencia empresarial se define como la capacidad de las organizaciones para hacer frente a condiciones adversas o de incertidumbre, siendo capaces de crear soluciones distintas a problemas existentes, donde la generación de cambios deriva de los procesos de innovación propios de los individuos que la conforman, siendo este factor clave en la transformación y flexibilización de la organización. La crisis económica derivada de la contingencia sanitaria por COVID-19 ha resultado un reto para las empresas. Este trabajo indaga sobre los determinantes de la resiliencia empresarial en micro y pequeñas empresas de Hidalgo del Parral, Chihuahua (México). Se evidencía algunos determinantes de resiliencia empresarial, mostrando elementos que caracterizan una probabilidad alta, media, baja o nula resiliencia, identificando elementos clave relacionados con la continuidad empresarial, o la antigüedad de la misma
CURRENT PERSPECTIVES OF PROTEOMICS FOR THE IDENTIFICATION AND CHARACTERISATION OF INSECT-DERIVED PROTEINS WITH ALLERGENIC POTENTIAL
Authors:   Department of Physiology, Cytobiology and Proteomics, Faculty of Biotechnology and Animal Husbandry, West Pomeranian University of Technology in Szczecin, Szczecin, Poland, CABAŁA Sandra , HEROSIMCZYK Agnieszka ,   Department of Physiology, Cytobiology and Proteomics, Faculty of Biotechnology and Animal Husbandry, West Pomeranian University of Technology in Szczecin, Szczecin, Poland
Published: March 2024

Currently, pet owners can easily access a broad array of commercial pet products specifically formulated to meet the unique nutritional needs of their cats and dogs. The trend towards organic pet foods, prioritizing whole ingredients over processed ones, is gaining more and more attention, emphasizing sustainability in sourcing dietary proteins. Insects, rich in essential amino acids, emerge as promising protein substitutes, though they do carry potential risks of triggering adverse food reactions, such as allergies in pets. This, in turn, provides a fertile ground for advanced proteomic analysis, facilitating comprehensive identification and quantification of allergens from edible insects. This includes defining immune epitopes originating from these allergens, thus fostering the discovery of potentially new proteins with allergenic potential and aiding in the in vitro diagnosis of allergen sensitization. This review presents the latest advancements in edible insect-derived allergens and the proteomic investigations conducted to analyse them. We offer insights into classical and advanced proteomic approaches designed for identifying and quantifying these allergens in various food matrices. Additionally, we focus on recent studies concerning the characterization of novel insect allergens, exploring sensitization and cross-reactivity mechanisms, with a specific emphasis on pets.
Virtual Reality and Surgical Simulation Training for Orthopaedic Surgery Residents
Authors: Kuhn Andrew W. , Yu Justin K. , Gerull Katherine M. , Silverman Richard M. , Aleem Alexander W.
Published: March 2024

Background:

The demonstrated benefits of virtual reality (VR) in orthopaedic surgical training are numerous. However, it is relatively unknown how best to implement VR into an already established orthopaedic resident education curriculum and how trainees will engage and use these technologies longitudinally.

Methods:

This was an exploratory, qualitative research study performed in accordance with Consolidated Criteria for Reporting Qualitative Research guidelines. Orthopaedic surgery residents at a single institution were recruited during the 2022 to 2023 academic year. Semistructured interviews were conducted. Data were analyzed through grounded theory methodology, beginning with open coding, followed by axial coding, and concluding with selective coding that describes orthopaedic surgery residents' current perceptions of VR as a training tool.

Results:

Six residents participated in interviews before thematic saturation was achieved. Average interview length was 13:27 (±2:59) minutes. Residents felt that currently, VR is most useful for interns and junior residents as an educational adjunct for learning anatomy, surgical exposures, and the steps of a procedure in a risk- and judgment-free arena. There seems to be a “ceiling effect” with VR given current technological limitations, and residents remarked that there is an associated “opportunity cost” with using VR technology. Some residents may find it more time-efficient to study texts, videos, or surgical guides rather than use VR. Cost (limited number of headsets) and technological barriers (i.e., hardware, software, and Wi-Fi issues) were some of the described barriers to VR utilization. Residents felt that there needs to be dedicated technological support to help with these issues. At this time, given these limitations of VR, many preferred VR as an optional educational adjunct rather than as a required curricular tool or assessment of surgical competency.

Conclusions:

There is current utility for VR in orthopaedic surgical training. Future technological advances may make VR more central to resident education. This study describes resident perceptions about the technology and best use practices for the technology.

Level of Evidence:

Qualitative Study, Level V Evidence
Corrosion Rate Analysis of Steam Boiler Superheater
Authors: Wibisono Satria Agung , Fahruddin A’rasy
Published: March 2024

Superheaters play an important role in converting saturated steam to the point of superheating. The condition of the superheater needs to be considered, if there is rust it will reduce the performance of the superheater in heating steam to the point of superheat. Rust / corrosion is the enemy of dangerous metals. Corrosion is defined as a deterioration in the quality of metals due to electrochemical reactions with their environment In corrosion events, metals undergo oxidation, while oxygen (air) undergoes reduction. The corrosion event itself is an electrochemical process, which is a process (change / chemical reaction) that involves electricity. Certain parts of the metal act as the negative pole (negative electrode, anode), while the other part acts as the positive pole (positive electrode, cathode). Electrons flow from the anode to the cathode, resulting in corrosion. By calculating the corrosion rate of superheaters with material A-213 T22 can be a consideration for using materials that are more resistant to rust or become a consideration in estimating repair time.