Balance Of Processes Research Articles

Geographic analysis of soil moisture recorded and estimated in Erbil governorate

Calculating of soil moisture and its monitoring is one of the important processes of water balance and sustainable agriculture. The intended goal of this study is to determine soil moisture values in Erbil Governorate and reveal the correlation coefficient and the degree of influence between its values with the elevation and total annual rainfall. The importance of the study lies In its discussion of the accuracy of extracting soil moisture values using satellite images, by comparing its results with the soil moisture values recorded in the governorate’s climate stations, the study reached a set of conclusions, the most important of which is: The results of using satellite images to estimate soil moisture are inaccurate. It is closer than guessing, and the results of applying the linear regression process indicated that there was a significant statistical relationship between the soil moisture values recorded with the two factors of elevation and the total annual rainfall, where the probability values were less than 0.01 and the values of the degree of influence between them reached 0.583 and 0.491 for each of them, respectively.‏

EOS: Impact Evaluation of Electric Vehicle Adoption on Peak Load Shaving Using Agent-Based Modeling

The increasing adoption of electric vehicles (EVs) by the general population creates an opportunity to deploy the energy storage capability of EVs for performing peak energy shaving in their households and ultimately in their neighborhood grid during surging demand. However, the impact of the adoption rate in a neighborhood might be counterbalanced by the energy demand of EVs during off-peak hours. Therefore, achieving optimal peak energy shaving is a product of a sensitive balancing process that depends on the EV adoption rate. In this paper, we propose EOS, an agent-based simulation model, to represent independent household energy usage and estimate the real-time neighborhood energy consumption and peak shaving energy amount of a neighborhood. This study uses Residential Energy Consumption Survey (RECS) and the American Time Use Survey (ATUS) data to model realistic real-time household energy use. We evaluate the impact of the EV adoption rates of a neighborhood on performing energy peak shaving during sudden energy surges. Our findings reveal these trade-offs and, specifically, a reduction of up to 30% of the peak neighborhood energy usage for the optimal neighborhood EV adoption rate in a 1089 household neighborhood.

Understanding the intricate impacts and mechanism of actions of adaptogens on reproductive function.

Adaptogens, comprising plants and mushrooms, modulate the immune system, energy balance, and various physiological processes, including reproduction. Despite their potential benefits, the impact of adaptogens on reproductive function remains understudied. This review examines the effects of common adaptogens on male and female reproductive functions, highlighting their regulation of neuro-endocrine-immune interactions crucial for reproduction. While existing literature reveals varying impacts on reproductive function, most adaptogens exhibit beneficial effects, modulating neuroimmunology and promoting gonadal steroidogenesis, spermatogenesis, and folliculogenesis through direct mechanisms or suppression of oxidative stress and inflammation. Further experimental research is necessary to elucidate the mechanisms of action of adaptogens, which would significantly advance the management of reproductive disorders and other diseases. Validating these findings in clinical trials is also essential.

The Study of the Balancing Process for Starting Rotors in Heavy-Duty Vehicles: An Industrial Application

In the heavy-duty vehicle industry, unbalance in the armature is one of the most common problems affecting starters’ performance and durability. This research presents a comprehensive study to improve the balancing process for starting rotors in heavy-duty vehicles. The complete manufacturing process of armatures was analyzed to understand the contribution of assembly processes to unbalancing. The analysis revealed that the primary factor leading to high unbalance in these parts is the misalignment of conductors within the armature winding. During assembly, these conductors experience axial movements, resulting in non-uniform mass distribution and causing unbalanced values ranging from 150 to 350 g·mm. These values surpass the permissible limit, making rectification during the balancing process at the end of the assembly impossible. Consequently, a novel alignment tool was designed to address this issue, significantly reducing the effect and achieving the maximum allowable unbalance of 100 g·mm. This allowed the balancing machine used in the process to correct the initial unbalance of the reinforcements in a single work cycle, improving operation efficiency by about 15%.

B-172 Correlation of Microbiome Sequencing Data and Quantified Short-Chain Fatty Acids by LC-MS/MS in IBD and Non-IBD Stool Samples

Abstract Background SCFAs are the primary metabolites produced by bacterial fermentation of dietary fiber and undigested proteins. They play a crucial role in various metabolic pathways, such as regulating the host’s energy balance and anti-inflammatory processes. The most studied SCFAs are acetic acid, propionic acid and butyric acid, with an approximate molecular ratio of 60:20:20 in healthy adults. A significantly different distribution may indicate a bacterial dysbiosis. While most SCFAs have a positive impact on the host’s health, the impact of branched short-chain fatty acids (bSCFAs), such as isobutyric acid and isovaleric acid, are less well-known. In order to evaluate whether the determination of a broader SCFA panel holds additional diagnostic value, we have developed a sensitive and robust LC-MS/MS method to determine 11 C2 - C7 SCFAs in human fecal samples. Methods The LC-MS/MS method includes acetic acid (AA), propionic acid (PA), butyric acid (BA), valeric acid (VA), caproic acid (CA) and heptanoic acid (HA), as well as the isomers isobutyric acid (iBA), 2-methylbutyric acid (2-MBA), isovaleric acid (iVA), isocaproic acid (iCA) and 2-methylhexanoic acid (2-MHA). After suspending the stool samples in a stabilizing buffer, the tubes were centrifuged and 25 µl of the supernatant was mixed with an internal standard solution (10 isotopically labeled internal standards) and subsequently derivatized. After one hour, the reaction was quenched and samples were injected into an ACQUITY UPLC H-Class (Waters) with an injection cycle of 9.5 min. Analytes were measured in positive mode by ESI-MS/MS on a Xevo TQ-MS (Waters). For quantification, six calibrators and three controls covering the anticipated physiological ranges were used. Results Microbiome sequencing data identified a total of 193 species, most of which belong to the Firmicutes phylum. Next, Actinobacteria and Proteobacteria are in descending order of abundance. In our IBD samples, we see a significant dysbiosis of these ratios and orders in comparison to the screening patients. E.g. in one sample, no Bacteroidetes were found, but a high amount of Actinobacteria (40 %) were sequenced. Corresponding SCFA data detected an AA:PA:BA ratio of 76:11:10, as well as no VA, iCA, CA, 2-MHA and HA, whereas SCFA data from most screening patients showed an AA:PA:BA ratio of 60:20:20 (± 10:10:10). Conclusions After a fast and simple sample preparation and derivatization, the LC MS/MS method allows robust and sensitive measurement of all presented SCFAs from human feces samples. The preliminary analysis of the combined microbiome and SCFA data showed that the detected AA:PA:BA ratio difference could be a valid indicator for a dysbiosis or an altered microbiome, corroborating data from previous studies. While we could detect differences on bSCFAs and longer SCFAs between IBD and non-IBD patient samples in this pilot study, larger patient and control cohorts are needed in order to substantiate our initial promising findings and finally allow a robust evaluation of these parameters as diagnostic tool to monitor and determine the state of the patient microbiome.

Participatory Mapping of Ethnoecological Perspectives on Land Degradation Neutrality in Southern Burkina Faso

In the Sahel region of West Africa, land degradation has raised concerns about the threat of desertification, leading to the establishment of the United Nations Convention to Combat Desertification (UNCCD) in 1994. Over time, the focus has shifted from simply combating desertification to a more comprehensive international program focused on preserving the health of our land by offsetting any damage with restoration efforts by 2030 to sustain ecosystem functions and services. This balancing process—which is in line with the Sustainable Development Goals (SDGs)—is known as Land Degradation Neutrality (LDN). We examine Land Degradation Neutrality (LDN) patterns, namely degradation and rehabilitation processes, by integrating participatory mapping with high-resolution satellite imagery with local stories, observations, historical records, and existing studies. The data elicited an understanding of the processes driving land degradation and adaptation strategies among three distinct ethnic groups of crop and livestock farmers in the village of Yallé in southern Burkina Faso. Some of these people were originally from this region, while others moved from places where the land was already degraded. Participants in the study had diverse experiences and perceptions of land degradation, its drivers, and adaptation strategies, which were influenced by their ethnicity, livelihood activities, and life experiences. These differences highlight the impact of cultural and socioeconomic factors on how people view land degradation, as well as the role of local knowledge in managing the environment. The study emphasizes the necessity of incorporating ethnoecological perspectives into projects focused on Land Degradation Neutrality (LDN) to better understand land degradation and improve land management. This integration can significantly contribute to strengthening global sustainability and community resilience.

Efficient SpMM Accelerator for Deep Learning: Sparkle and Its Automated Generator

Deep learning (DL) technology has made breakthroughs in a wide range of intelligent tasks, such as vision, language, recommendation systems, and so on. Sparse matrix multiplication (SpMM) is the key computation kernel of most sparse models. Conventional computing platforms, such as CPUs, GPUs, and AI chips with regular processing units, are unable to effectively support sparse computation due to their fixed structure and instruction sets. This work extends Sparkle, an accelerator architecture, which is developed specifically for processing SpMM in DL. During the balanced data loading process, some modifications are implemented to enhance the flexibility of the Sparkle architecture. Additionally, a Sparkle generator is proposed to accommodate diverse resource constraints and facilitate adaptable deployment. Leveraging Sparkle’s structural parameters and template-based design methods, the generator enables automatic Sparkle circuit generation under varying parameters. An instantiated Sparkle accelerator is implemented on the Xilinx xqvu11p FPGA platform with a specific configuration. Compared to the state-of-the-art SpMM accelerator SIGMA, the Sparkle accelerator instance improves the sparse computing efficiency by about 10 to 20 \(\%\) . Furthermore, the Sparkle instance achieved 7.76 \(\times\) higher performance over the Nvidia Orin NX GPU. More instances of accelerators with different parameters were evaluated, demonstrating that the Sparkle architecture can effectively accelerate SpMM.

Diabetes prediction model based on GA-XGBoost and stacking ensemble algorithm.

Diabetes, as an incurable lifelong chronic disease, has profound and far-reaching effects on patients. Given this, early intervention is particularly crucial, as it can not only significantly improve the prognosis of patients but also provide valuable reference information for clinical treatment. This study selected the BRFSS (Behavioral Risk Factor Surveillance System) dataset, which is publicly available on the Kaggle platform, as the research object, aiming to provide a scientific basis for the early diagnosis and treatment of diabetes through advanced machine learning techniques. Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. The results show: (1) Random oversampling, ADASYN, SMOTE, and SMOTEENN were used for data balance processing, among which SMOTEENN showed better efficiency and effect in dealing with data imbalance. (2) The GA-XGBoost model optimized the hyperparameters of the XGBoost model through a genetic algorithm to improve the model's predictive accuracy. Combined with the better-performing LightGBM model and random forest model, a two-layer Stacking model was constructed. This model not only outperforms single machine learning models in predictive effect but also provides a new idea and method in the field of model integration. (3) Shapley value analysis identified features that have a significant impact on the prediction of diabetes, such as age and body mass index. This analysis not only enhances the transparency of the model but also provides more precise treatment decision support for doctors and patients. In summary, this study has not only improved the accuracy of predicting the risk of diabetes by adopting advanced machine learning techniques and model integration strategies but also provided a powerful tool for the early diagnosis and personalized treatment of diabetes.

Combination aquaphotomics study and LF-NMR to monitor the drying process of honey pills

As one of the factors affecting the quality of honey pills (HP), there are few researches on its quality control and solutions. But water can directly affect the appearance, stability and potency of the HP. In this study, near-infrared spectroscopy was used to monitor the moisture content of HP with different drying conditions, and multiple linear regression analysis was carried out to establish the moisture content prediction model, and the R2 of the model prediction is 0.9532. The visualization of HP drying process were carried out by aquaphotomics method characterizes the status of the water molecular network at different drying stages. At the same time, low-field nuclear magnetic resonance (LF-NMR) information was carried out to analyze the water distribution in the drying process, and further verified the water solvent shell action in the water balance process of aquaphotomics analysis. The surface water of the pill disperses to the air, and the internal water diffuses outwards. We adopted the techniques such as rheology to comprehensively characterize the state of HP, and to evaluate the quality of them by using the dissolution test. The quality state of the pills was analyzed by the aquaphotomics analysis of water species. The above research system provided the scientific basis for revealing the drying process of HP from the viewpoint of aquaphotomics, as well as showed potential for expansion and application to other Chinese traditional medicine products.

How well can satellite altimetry and firn models resolve Antarctic firn thickness variations?

Abstract. Elevation changes of the Antarctic Ice Sheet (AIS) related to surface mass balance and firn processes vary strongly in space and time. Their subdecadal natural variability is large and hampers the detection of long-term climate trends. Firn models or satellite altimetry observations are typically used to investigate such firn thickness changes. However, there is a large spread among firn models. Further, they do not fully explain observed firn thickness changes, especially on smaller spatial scales. Reconciled firn thickness variations will facilitate the detection of long-term trends from satellite altimetry; the resolution of the spatial patterns of such trends; and, hence, their attribution to the underlying mechanisms. This study has two objectives. First, we quantify interannual Antarctic firn thickness variations on a 10 km grid scale. Second, we characterise errors in both the altimetry products and firn models. To achieve this, we jointly analyse satellite altimetry and firn modelling results in time and space. We use the timing of firn thickness variations from firn models and the satellite-observed amplitude of these variations to generate a combined product (“adjusted firn thickness variations”) over the AIS for 1992–2017. The combined product characterises spatially resolved variations better than either firn models alone or altimetry alone. It provides a higher resolution and a more precise spatial distribution of the variations compared to model-only solutions and eliminates most of the altimetry errors compared to altimetry-only solutions. Relative uncertainties in basin-mean time series of the adjusted firn thickness variations range from 20 % to 108 %. At the grid cell level, relative uncertainties are higher, with median values per basin in the range of 54 % to 186 %. This is due to the uncertainties in the large and very dry areas of central East Antarctica, especially over large megadune fields, where the low signal-to-noise ratio poses a challenge for both models and altimetry to resolve firn thickness variations. A large part of the variance in the altimetric time series is not explained by the adjusted firn thickness variations. Analysis of the altimetric residuals indicate that they contain firn model errors, such as firn signals not captured by the models, and altimetry errors, such as time-variable radar penetration effects and errors in intermission calibration. This highlights the need for improvements in firn modelling and altimetry analysis.

Optimizing nitrogen removal in PD/A reactors: Effects of influent composition and temperature on system stability and microbial dynamics

This study investigates the performance and microbial community dynamics in two partial denitrification/anammox (PD/A) reactors with different influent wastewater compositions (differ in the presence/absence of NO2−) subjected to a controlled temperature gradient reduction from mesophilic (30 °C) to room temperature (20.92 °C) over 76 days. Two lab-scale PD/A reactors (R1 and R2), both operated with a total inorganic nitrogen (TIN) concentrations of 70 mg N/L. R1 maintained a NH4+/NO2−/NO3− ratio of 3:3:1 and a COD/NO3− ratio of 2.0, while R2 had an NH4+/NO3− ratio of 3:4, and COD/NO3− ratios of 2.0 and 2.5. Our findings reveal distinct responses to the temperature transitions: the optimization of the NH4+/NO2−/NO3− ratio at 3:3:1 facilitated more stable nitrogen removal as temperatures decreased. This stability can be attributed to the enhanced synchronization between anammox bacteria and denitrifiers, promoting a balanced bioconversion process that is less susceptible to temperature-induced disruptions. Notably, the specific anammox activity (SAA) in both reactors declined linearly with the decrease in temperature, but the relative abundance of anammox bacteria (Ca. Brocadia) in R1 increased from 2.1 % to 9.7 %. Furthermore, the percentage of anammox-related key genes was higher in R1 than in R2, suggesting a microbial mechanism underlying the stable performance of R1. These results underscore the significant impact of influent nitrogen composition on PD/A performance amid temperature gradients and highlight the critical role of optimizing influent ratios for maintaining efficient nitrogen removal. This study offers valuable insights into enhancing the stability of PD/A systems under varying thermal conditions.

Effects of simulated precipitation changes on soil respiration:Progress and prospects.

Soil respiration, the main pathway for transferring terrestrial carbon pool to atmospheric carbon pool, is profoundly affected by the intensification in global precipitation variability in the context of climate change. Nowadays, variable controlling methods and field manipulation experiments are two main methods widely used to investigate the effects of simulated precipitation changes on soil respiration. Yet, due to the heterogeneity of soil properties, vegetation types, and the magnitude of precipitation change, there is substantial inconsistency in the conclusions of simulated precipitation change effects on soil respiration. Here, we analyzed data from domestic and foreign literature, and examined the effects of simulated precipitation change on soil respiration. Firstly, we described the response pattern of soil respiration to soil moisture fluctuation and pointed out that the magnitude and direction of the response of soil respiration to simulated precipitation change depended on whether soil moisture was optimally conditioned at different precipitation treatments. Second, we summarized the response patterns of soil respiration to symmetric increase and decrease in precipitation, which mainly included symmetric and asymmetric responses (positive and negative asymmetric). Meanwhile, the adaptation of plants and soil microorganisms to drought stress and soil oxygen limitation, as well as the reduction of organic substrates, were the main mechanisms accounting for the shifts of soil respiration response patterns to simulated precipitation change from symmetric to asymmetric responses. Third, we identified a significant effect of ambient climate on soil respiration in response to precipitation treatments as increasing duration of the experimental treatments. In addition, cumulative or buffering effects of ambient climatic conditions on precipitation treatment could affect the sensitivity of soil respiration along precipitation gradient by altering hydrothermal conditions. Finally, to accurately assess the implications of precipitation changes on soil carbon balance processes, we proposed three aspects of future precipitation effects on soil respiration for attention: 1) focusing on the phenomenon of "threshold effects" in the asymmetric response of soil respiration along precipitation gradients; 2) distinguishing the intrinsic mechanisms of autotrophic and heterotrophic components in soil respiration in response to precipitation changes; and 3) focusing on the impacts of intensified precipitation variability on soil respiration in the context of future climate extremes. In conclusion, with the intensified variability in global precipitation patterns, clarifying the response mechanism of soil respiration to precipitation changes is of great significance for accurately predicting and evaluating the alterations of soil carbon cycle processes and carbon balance in the context of global changes.

Regulating in-between (in)formality: institutionalising the private rental market in China’s urban villages

The governance of informal settlements in China – primarily urban villages – remains a persistent challenge. Recently, some urban village houses have been transformed into long-term rental apartments (LRAs). This highlights a potentially novel approach to addressing the longstanding informality issue, but how the rental market in urban villages has thus been reshaped remains unknown. Examining the case of Shenzhen’s Yuanfen Village through the lens of regulating informality, this paper reveals that (1) new renovations are facilitated by the intermediary management of LRA companies with government consent; (2) the renovation into LRAs involves a balancing process among stakeholders but leaves the illegal aspects untouched; and (3) while the renovation improves the living environment, low-income households are inevitably displaced. This study contributes to a theoretical and practical understanding of regulating informality by challenging the monolithic formal-informal dichotomy and connecting the conceptualization and materialization of continuous and dynamic property rights that enable new possibilities for effective and inclusive management of urban growth.

Getting slimmer without dieting or exercising: zebra finches can rapidly lose mass while maintaining food intake and decreasing activity.

It is widely accepted that birds can adaptively regulate body mass in different ecological contexts, but little is known about how birds monitor and interpret their body mass or the mechanisms that allow for rapid changes in mass. Using captive zebra finches (Taeniopygia guttata), we experimentally increased perceived mass via attachment of weighted backpacks and provided birds with either an ad libitum mixed-seed diet or supplementary high-fat diet to investigate: (1) how birds assess their own body mass and (2) the physiological and/or behavioral mechanisms birds may employ to rapidly adjust body mass. In both experiments, and independent of diet treatment, birds with weighted backpacks rapidly lost mass within 2 days of backpack attachment while reducing overall activity and maintaining food intake. Additionally, our data suggest that birds interpret body mass via a physical mechanosensory pathway rather than a physiological pathway: rapid loss of mass between days 0 and 2 was not linked to changes in plasma metabolites (glycerol or triglyceride concentrations). We found no evidence that mass loss was a consequence of stress associated with attachment of weighted backpacks (based on plasma corticosterone measures). Our results suggest that the processes of energy balance and mass regulation involve a greater array of mechanisms than simply matching 'energy in', through the amount of food consumed, to 'energy out', dictated by activity. Zebra finches were able to decrease body mass through other, unidentified, mechanisms even while maintaining dietary intake and reducing overall activity.

Glycine betaine: A multifaceted protectant against salt stress in Indian mustard through ionic homeostasis, ROS scavenging and osmotic regulation.

Salt stress is a prevalent environmental issue that disrupts the redox balance and metabolic processes in plants, leading to reduced crop growth and productivity. Currently, over 6.74 million hectares in India are salt-affected, and about 75% of this land lies in states that are the major cultivators of edible oilseed crops (rapeseed-mustard). Therefore, this study focused on the efficacy of glycine betaine (GB) supplementation in mitigating the detrimental effects of salt stress in Brassica juncea L. (Indian mustard) plants. Indian mustard plants were subjected to salt stress [0, 50, 100, and 150 mM sodium chloride] 20 days after sowing (DAS), while a foliar spray of 20 mM GB was applied to the foliage at 50 and 70 DAS. The data showed that salt stress substantially reduced growth, photosynthetic rate, membrane stability, and yield by significantly increasing lipid peroxidation, ion toxicity, cell death, electrolyte leakage, and reactive oxygen species accumulation that triggered oxidative stress. Supplementation with 20 mM GB provided tolerance to plants against salt-induced toxicity since it substantially increased growth, biomass, water content, nutrient uptake, and photosynthetic efficiency. Additionally, GB enhances the accumulation of osmolytes, enhances the antioxidant defence system, improves ionic balance, and enhances cell viability. Taken together, the obtained data provides deeper insights into the beneficial effect of the exogenous GB application that could have biotechnological uses to enhance crop stress tolerance in challenging environments.

Halogen-free epoxy flame retardant & promoter with diimidazole skeleton improves overall properties of epoxy resins

In order to solve the widespread problem in the field of flame retardancy epoxy(FREP), for the deterioration of the overall properties, we designed a novel structural flame retardant & promoter DOPO-CDI and synthesized it using a simple nucleophilic addition one-step method, which exhibits remarkable flame retardant and curing promotion, the flame retardant and promote mechanism of DOPO-CDI on neat EP is illustrated in Fig 0a, which obtained excellent overall properties shown in Fig 0b. Compared with neat epoxy, it has high flame retardancy, low additives results in an limiting oxygen index(LOI) of up to 37.5 % and a V-0 rating of UL-94, a lower curing exothermic peak temperature, a shorter curing time. And in terms of mechanical properties, the excellent strength of epoxy has been further enhanced, flexural strength and tensile strength are increased by 13.3 % and 21.6 % respectively. Moreover, the toughness of epoxy, which is generally lacking, has been greatly improved, in particular, compared with neat epoxy, the impact strength of epoxy with 3 wt% DOPO-CDI increased by 103.6 %. Unlike most FREP, glass transition temperature(Tg) of the epoxy with the introduction of DOPO-CDI raises to 165.6 °C, which is a significant improvement compared to that of the neat epoxy, in terms of combustion behavior, DOPO-CDI has a considerable inhibitory effect on the combustion exotherm and smoke emission. This work explores a way to balance processing, mechanical and thermal properties when preparing FREP, which has great potential for application.

Influence of pairing in examiner leniency and stringency ('hawk-dove effect') in part II of the European Diploma of Anaesthesiology and Intensive Care: A cohort study.

The European Diploma of Anaesthesiology and Intensive Care (EDAIC) Part II examination is a supranational examination for anaesthesiologists. We explore the impact of examiner pairing on leniency and stringency, commonly referred to as the 'hawk-dove effect'. We investigate the potential variations in grading approaches, resulting from different examiner pairs and their implications for candidate performance. Retrospective cohort, observational design. EDAIC Part II examination data from 2021 to 2023. Three hundred and twenty-five examiners across 122 EDAIC Part II examination sessions. We analysed the influence of examiner leniency and examiner pairing on candidate performance in the EDAIC Part II using many-facet Rasch modelling. The study's main outcome measure was determining a leniency score among the examiner population. The study also aimed to assess how examiner pairing influenced candidate performance, as measured by their scores in the examination. During the study period, the number of examiners who participated in 2021, 2022 and 2023 were 253, 242 and 247, respectively. The median sessions attended were 7.0 (3 to 10). The examination data revealed a mean leniency score of 0 [95% confidence interval (CI) -0.046 to 0.046], with the standard deviation being one-third that of the candidates' ability scores. There were 1424 different pairs of examiners, with most pairs (97%) having only a one-point difference in marking. The mean leniency score for the pair of examiners was -0.053 (95% CI -0.069 to -0.037). The variations in grading approaches associated with different pairings emphasise the potential for the 'hawk-dove effect' to influence candidate performance and outcomes. Understanding these variations can guide curriculum development, examiner training and coupling, ensuring a balanced and equitable assessment process. None.

Method for vibration suppression in rotary machines using multiple automatic ball balancers

An automatic ball balancer (ABB) is a device that is used to automatically balance an eccentric rotor; these are typically used in rotary machines with unknown or variable imbalances. The typical construction of an ABB consists of several balls in a ring race. The balls can move freely inside the race, which changes the eccentricity radius and phase angles relative to the rotor. The automatic balancing process requires an ABB unit to be installed on an eccentric rotor's axis; thus, its application is quite limited and usually requires the redesign of a rotary machine. This paper presents a new method for eliminating vibrations in rotary machines by using multiple ABBs that are mounted away from the rotor's axis. In this application, ABBs can be considered to be unbalanced rotary masses with adjustable eccentricity radii and phases. Theoretically, this ability allows for the total reduction of the inertial force from an eccentric rotor; however, the parameters of the ABBs must be set correctly. The process of setting the eccentricity radius and phase in each ABB occurs due to a self-synchronization phenomenon and generally depends on the physical parameters of either a rotary machine or ABBs. Both analytical and numerical investigations that were based on the mathematical model of a system of a rotary machine with a pair of ABBs allowed us to formulate basic rules to apply such a system in existing rotary machines without interference on the rotors.

Water Balance and Water Treatment Process Analysis in Water Control for Environmental Performance Assessment (Case Study at Jakarta, Indonesia)

Water Balance and Water Treatment Process Analysis in Water Control for Environmental Performance Assessment (Case Study at Jakarta, Indonesia)

Design and implementation of dynamic balance in ultra-high speed IP network

Abstract Nowadays, with the rapid development of IP network service demand, network construction is also accelerating, IP network is expanding at a higher rate, and gradually moving toward ultra-high speed networks above 40G. In view of the problems of inconsistent IP packet order, random IP packet length and traffic burst brought by the application environment of high traffic, high bandwidth and high concurrency in ultra-high speed IP network, this paper introduces a kind of dynamic balance processing technology of ultra-high speed IP network based on information label. By optimizing the IP processing architecture, a two-level scheduling architecture of multi-board and multi-module is established, and VPN is established in ultra-high speed IP network by using dynamic balance processing technology and order preserving technology to realize high performance IP processing, so as to achieve ultra-high speed data transmission.