Changes In Rules Research Articles

A Study on the Conditions of Fog Generation and the Change Rule of Fog Zone Length in Air Intake Roadway

Fog in mine air intake roadways is a non-negligible disaster that seriously reduces the visibility of the roadway, affects vehicle transportation and the safe passage of personnel, and jeopardizes the safe production of the mine. This paper applies both field testing and numerical simulation to explore fog formation conditions and the effects of inlet air temperature and humidity on the fog zone length within the Wangjialing Mine’s air intake roadway in Shanxi, China. First, based on the consideration of the relationship between the moisture gain of surrounding rock and the temperature with humidity of the air flow, the fog generation and distribution law model of the air intake roadway was established. Based on this model, the critical inlet air temperature and the critical inlet air relative humidity for fogging in the Wangjialing Mine air intake roadway were determined. In addition, we found that the fogging point inside the roadway shifted forward continuously with the increase in inlet air temperature and inlet air relative humidity, and the length of the fog zone expands parabolically in response to these rising conditions.

A Comprehensive Review of Methods for Hydrological Forecasting Based on Deep Learning

Artificial intelligence has undergone rapid development in the last thirty years and has been widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a growing area of research is the use of deep learning (DL) methods in connection with hydrological time series to better comprehend and expose the changing rules in these time series. Consequently, we provide a review of the latest advancements in employing DL techniques for hydrological forecasting. First, we examine the application of convolutional neural networks (CNNs) and recurrent neural networks (RNNs) in hydrological forecasting, along with a comparison between them. Second, a comparison is made between the basic and enhanced long short-term memory (LSTM) methods for hydrological forecasting, analyzing their improvements, prediction accuracies, and computational costs. Third, the performance of GRUs, along with other models including generative adversarial networks (GANs), residual networks (ResNets), and graph neural networks (GNNs), is estimated for hydrological forecasting. Finally, this paper discusses the benefits and challenges associated with hydrological forecasting using DL techniques, including CNN, RNN, LSTM, GAN, ResNet, and GNN models. Additionally, it outlines the key issues that need to be addressed in the future.

Change Detection Based on Existing Vector Polygons and Up-to-Date Images Using an Attention-Based Multi-Scale ConvTransformer Network

Change Detection Based on Existing Vector Polygons and Up-to-Date Images Using an Attention-Based Multi-Scale ConvTransformer Network

Experimental and model research on judging liquid accumulation in pipelines under the action of surfactant

Foam drainage gas extraction is applied in various natural gas extraction scenarios, such as water-bearing gas wells, gas fields with high water content, and wet natural gas pipeline transport, with the goal of enhancing extraction efficiency and lowering production costs. A common issue in foam-carrying liquid gas wells and wet natural gas pipelines is the large errors observed in the prediction model for liquid accumulation onset, derived using ellipsoidal droplets. Additionally, this model is only applicable to a single surfactant type and concentration. To investigate the effects of different types and concentrations of surfactants on the onset of liquid accumulation. This paper re-establishes the critical foam-carrying flow rate model for spherical cap-shaped foam droplets using Newton's laws of motion, through an analysis of their motion state within the air core. Through the critical foam-carrying flow rate test experiments and foam droplet deformation test experiments to obtain critical foam-carrying flow rate model in the surface tension, foam density, Weber number, drag coefficient and other parameters of the change rule and calculation method. The model's validity was further confirmed using field-measured production data from foam-carrying liquid gas wells, demonstrating accurate validation results. Compared to the previous model, this new model treats foam droplets as spherical cap-shape and introduces a dimensionless scaling factor and foaming capacity to quantify the impact of surfactant types and concentrations on foam droplet surface tension and density. This enhances the model's applicability across different types and concentrations of surfactants with greater accuracy. This offers an efficient, precise, and versatile method for predicting liquid accumulation in foam-carrying liquid gas fields, thereby enhancing the efficiency and safety of gas extraction.

EFNN-Nul0- a trustworthy knowledge extraction about stress identification through evolving fuzzy neural networks

This paper presents a novel hybrid architecture, denoted as EFNN-Nul0 (evolving neuro-fuzzy system based on null-unineurons), meticulously crafted for stress identification within the realm of pattern classification. The model seamlessly integrates neural networks, fuzzy systems, and n-uninorms to cultivate knowledge within an adaptive, real-time learning context. Neuro-fuzzy rules, encapsulating interdependencies among input features through IF-THEN type relationships, are formulated utilizing null-unineurons derived from n-uninorms. This construction enables the articulation of both AND- and OR-connections, thereby augmenting the interpretability of the generated rules. The evolution of neurons is facilitated by an extended adaptation of the autonomous data partition method (ADPA). To dynamically interpret the evolution of rules, the paper introduces (i) a mechanism that tracks changes in rules over data stream samples, providing insights into the process dynamics as a structural active learning component, and (ii) a concept for incrementally updating feature weights. These weights encapsulate the varying impact levels of features on stress identification, enabling the reduction of rule length by effectively masking out less significant features. The outcomes of the rules are represented by certainty vectors, recursively updated through an indicator-based recursive weighted least squares (I-RWLS) approach. Neuron activation levels play a pivotal role in determining the weights, ensuring stable local learning. The effectiveness of the proposed model is substantiated through a comprehensive comparison with existing hybrid and evolving approaches in the literature, focusing on binary and multi-class pattern classification. Aspects that identify special characteristics of neuro-fuzzy models related to interpretability will also be demonstrated in this work. The results demonstrate the model's superior performance, characterized by consistently higher accuracy trend lines over time. Furthermore, the model's interpretability is underscored by the coherent neuro-fuzzy rules, contributing to its remarkable accuracy (the EFNN-Nul0 achieved approximately 99% accuracy in stress identification), establishing its efficacy in addressing stress identification within classification problems.

A Content Analysis of Violent Penalties and their Role in Sanitizing NFL Broadcasts

ABSTRACT Using social cognitive theory and notions of sanitized sports violence as a framework, a content analysis of 486 National Football League (NFL) violent penalty calls (unnecessary roughness, roughing the passer) from broadcasts in 2009 and 2019 was conducted. Announcers were largely polarized in their reactions to violent penalties when they were shown on replay. Players were rarely injured and concussions as a key issue were rarely mentioned. Concerns about the effectiveness of NFL rule changes intended to protect players and their influence on announcers’ frustration with perceived over-penalization of the game (and audiences as a potential byproduct) are discussed.

Navigating The Impact of Outsourcing Rule Changes Under the Omnibus Law on Job Creation

The Job Creation Law introduces fundamental changes in employment in Indonesia. This article discusses the impact of changes in outsourcing rules in the Omnibus Law on job creation. Using research methodology involves an in-depth analysis of legislation and secondary data from the legal literature. The results show that changes to outsourcing rules have complex impacts, with the potential for increased investment and efficiency, but also the risk of decreasing workers' rights. The paper concludes the need for responsive regulation to maintain a balance between the interests of companies and workers, ensuring fairness in labor relations. A better understanding of the complexity of changes to outsourcing rules in the Omnibus Law is expected to help improve policies to support sustainable economic growth and worker welfare. Concluded that changes to outsourcing rules can improve a company's investment and operational efficiency, but also create uncertainty and potential impairment of workers' rights and protections. Therefore, responsive legal protection and transparency of information are crucial to maintaining fairness in employment relations. This journal contributes to a better understanding of the complexity of changes to outsourcing rules in the Omnibus Law and raises awareness for better regulatory adjustments to support economic sustainability and worker welfare.

The Factors Hindering the Effective Development of SMEs Businesses in Tanzania a Review Study

The development of SMEs worldwide is dependent upon a favourable business situation. However, SMEs in Tanzania confront a number of obstacles that prevent them from growing, including a lack of funding, inadequate market accessibility, a lack of entrepreneurial expertise and skills, bureaucracy, lack of business training, lack of good infrastructure, a lack of collateral, low production, unfavourable regulations, corruption, the motivation of the business owners, limited access to information, inadequate raw materials and other related factors. The significance of the study is to review on the issues preventing Tanzanian SMEs from developing. The SMEs, businesses have been demanded as the backbone for the growth of economic in almost all the developing countries including Tanzania. In Tanzania it has contributed almost 30% of the national GDP, and almost 20-30% of the total labour force, thus 3-4 million people employed. Therefore the paper has addressed some factors internal, external and other related factors as reviewed that act as the setbacks towards the SMEs development. The study has focused on literature review of different articles, research and case studies done. Mwanza region was chosen as one of the case study because of great opportunity to SMEs in the region, which if could be well utilized could add high Gross Domestic Product (GDP) of the country. The SMEs involved are such as; retail shops, bars, restaurants, hotels, playing stations, decoction centres, stationeries, etc Tanzania To achieve the intended objective, the researcher developed research question that was aimed at assessing the factors affecting performance and development of SMEs, contributions and solutions to SMEs. Data were collected from literature review of paper and cited by the author concerning Tanzania. The finding showed that most of the SMEs fails to develop due to; failure to access financial support, lack of business skills, poor technology used due to lack of awareness, lack of enough government support, high taxes imposed , failure to comply with government regulations, sudden change in climatic conditions and government rules. The study concluded by suggesting and further recommended on the better strategies that SMEs could implement with the government support like; government should always work and collaborate with SMEs in all areas by implementing favourable business policies, financial institutions should impose affordable and easy regulation to access loan that supports the SMES operations. Also the SMEs owners and employees should be given enough skills to help them perform better and copy with the daily change in technology advancement to assure effective and efficiency performance of the SMEs for their future sustainability in Tanzania.

Effect of the impeller blade outlet setting angle on the performance of the helical axial-flow multiphase pump

Effect of the impeller blade outlet setting angle on the performance of the helical axial-flow multiphase pump

Votes Can Be Confidently Bought in Some Ranked Ballot Elections, and What to Do about It

Abstract We show that, in some ranked ballot elections, it may be possible to violate the secret vote. There are so many ways to rank even a handful of candidates that many possible rankings might not be cast by any voter. So, a vote buyer could pay someone to rank the candidates a certain way and then use the announced election results to verify that the voter followed through. We examine the feasibility of this attack both theoretically and empirically, focusing on instant runoff voting (IRV). Although many IRV elections have few enough candidates that this scheme is not feasible, we use data from San Francisco and a proposed election rule change in Oakland to show that some important IRV elections can have large numbers of unused rankings. There is no evidence that this vote-buying scheme has ever been used. However, its existence has implications for the administration and security of IRV elections. This scheme is more feasible when more candidates can be ranked in the election and when the election results report all the ways that candidates were ranked.

Research on Prediction Methods for Eccentric Wear of the Slipper Pair in Axial Piston Pumps and Lubrication Performance Analysis

Abstract The axial piston pump (APP) is the core power component of hydraulic systems. Its friction pair wear can cause the degradation of piston pump performance until the function is completely lost or the service life is terminated. The slipper pair, prone to wear failure, is selected as the research object in this paper. The prediction method for the eccentric wear of the slipper pair is established, and the gradual change rules of the performance with wear accumulation are explored. The micro-surface rough peak contact and the stress state of the slipper pair are analyzed, and the mixed lubrication model of the slipper pair is established based on the elastohydrodynamic lubrication (EHL) model of the slipper pair. Grid discretization of a sealing belt of the slipper pair is carried out based on two-body abrasive wear and Archard adhesive wear models to improve the prediction method for eccentric wear of the slipper pair. The effectiveness of the proposed method is verified by a surface morphology analysis of the worn slipper. The results showed that the wear depth and wear width of the outer edge of the slipper bottom surface are positively correlated with the oil discharge pressure and the inclination angle of the swashplate, and negatively correlated with the rotational speed and the dynamic oil viscosity. The outer edge of the slipper is wedged after eccentric wear, and the hydrodynamic effect of the lubricating oil film of the slipper pair is enhanced. Hence, proper wear can improve the lubrication performance of the slipper pair.

Traffic Violation Detection System

Travel convenience is impacted by a number of factors, including the condition of the road, traffic, length of trip, accidents, speed, etc. The daily increase in accident rates poses the biggest concern in Sri Lanka. These events not only result in fatalities but also increase the nation's financial losses. Traffic congestion is brought on by road users' lack of discipline and sentiments, which may result in traffic offenses. The goals of this research are to curb any traffic infractions as well as reduce corruption and nepotism on the road. This system was developed as separate three models namely edge server, fine management system and centralized server. Edge server developed in python is to detect traffic violations such as parking, single line cutting, double line cutting, one way and u turn in real time according to the changing rules and constraints configured by the traffic police admin via the fine management system which supports a configurable platform designed using canvas designing tools. Upon edger server identifying violations, the functions in the centralized server responsible to recognize the number plate of the violated vehicle will be triggered and send a sms to driver for further fine management and payment supported by the fine management system. The mobile application controlling server is responsible to track and inform the violations to nearest police officer in any case the system could not rectify the vehicle number plate.

The effects of repeat mild traumatic brain injuries on choroid plexus endothelial cells in-vitro

Chronic Traumatic Encephalitis (CTE) is a degenerative brain disorder seen in college and professional football players, and those that play other contact sports like hockey and soccer. It is characterized by a dementia-like phenotype and declination in memory, executive dysfunction, and mood and is associated with repetitive head trauma, as seen in those contact sports. Even with rule changes to protect the players, it is predicted that, on average, college football players experience 1,400-1,500 head impact exposures per year, or roughly 14 per game (Crisco et al., 2010). This is significant because existing literature provides evidence that it is the accumulation of repetitive head trauma, even mild, that eventually leads to lasting and irreparable damage seen in CTE. This study sought to characterize cytokine signaling in repeat mild traumatic brain injuries (rTBI) in choroid plexus endothelial cells (CPECs), the endothelial barrier of the blood-CSF barrier (BCSFB). We hypothesized that regulatory and pro-inflammatory cytokines and chemokines play a role in exacerbating post-rTBI symptomology even days after initial injury. Identifying key cytokines and their respective timepoints post-injury is important to allow us to better treat TBIs, while also preventing subsequent damage that might progress to CTE. To study this hypothesis, primary human CPECs were subjected to a 12% repetitive mechanical elongation strain using the FlexCell Tension system to mimic mild axonal stretching injury. The elongation mechanical strain was repeated 14 times over a 1-hour period, which is roughly the average number of impacts experienced by players during a one-hour college football game. We collected supernatant over 24-, 48-, 72-, and 96-hours post-injury and examined 36 different cytokines using RND microarrays following manufacturer’s instructions. Controls included cells subjected to no mechanical strain and cells that only received one total mechanical strain. Several notable cytokines and chemokines were altered during this period, including RANTES (CCL5), CXCL12, and macrophage migration inhibitory factor (MIF). RANTES is highly correlated with Alzheimer’s disease, a neurodegenerative disease and CTE relative, and CXCL12 and MIF are highly correlated with inflammatory processes. Many cytokine changes were more pronounced in the period between 24- and 48-hours after injury. However, there were lasting changes compared to the controls up to 96-hours later. These findings can be used to begin to understand the complexity of human CPEC cytokine signaling at the BCSFB when these cells react to the strain forces of repeat mild TBIs like those seen in college football players. This also gives us further insight into the lasting effects of rTBIs and the possible relation to CTE. With these results in mind, we plan to continue to monitor cytokines and chemokines up to two weeks post injury to determine if, and when, cytokine values return to baseline values post-injury. This project was funded by a Senior Research Grant from the Indiana Academy of Science and from a Faculty Research Development Grant from Marian University College of Osteopathic Medicine. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Chemogenetic inactivation of the nucleus reuniens and its projections to the orbital cortex produce deficits on discrete measures of behavioral flexibility in the attentional set-shifting task

The nucleus reuniens (RE) of the ventral midline thalamus is a critical node in the communication between the orbitomedial prefrontal cortex (OFC) and the hippocampus (HF). While RE has been shown to directly participate in memory-associated functions through its connections with the medial prefrontal cortex and HF, less is known regarding the role of RE in executive functioning. Here, we examined the involvement of RE and its projections to the orbital cortex (ORB) in attention and behavioral flexibility in male rats using the attentional set shifting task (AST). Rats expressing the hM4Di DREADD receptor in RE were implanted with indwelling cannulas in either RE or the ventromedial ORB to pharmacologically inhibit RE or its projections to the ORB with intracranial infusions of clozapine-N-oxide hydrochloride (CNO). Chemogenetic-induced suppression of RE resulted in impairments in reversal learning and set-shifting. This supports a vital role for RE in behavioral flexibility – or the ability to adapt behavior to changing reward or rule contingencies. Interestingly, CNO suppression of RE projections to the ventromedial ORB produced impairments in rule abstraction – or dissociable effects elicited with direct RE suppression. In summary, the present findings indicate that RE, mediated in part by actions on the ORB, serves a critical role in the flexible use of rules to drive goal directed behavior. The cognitive deficits of various neurological disorders with impaired communication between the HF and OFC, may be partly attributed to alterations of RE -- as an established intermediary between these cortical structures.

Study on flow behavior of fresh concrete in elbow using the dense discrete phase approach

The presence of an elbow in the pipe during pumping can cause serious problems such as separation and clogging of the concrete. It is difficult to accurately and intuitively observe the internal information of the pump tube. This work used the Dense Discrete Phase Model (DDPM) to investigate the flow behavior of fresh concrete in the elbow. Firstly, the accuracy of the simulation model is verified. Then, the DDPM is used to research the flow behavior of fresh concrete in the elbow at different inlet velocities, and the changing rules of flow velocity, pressure loss, and particle migration are revealed. This work provides a solution to ensure the normal pumping process and effectively predict the pump pressure loss.

Modelling and Impact Analysis of Combined Dam Failure of Small Tandem Reservoir Groups in Hilly Areas

Numerous small reservoirs in hilly areas play a significant role in flood control and profit-making in the basin, but there is also a risk of dam failure when encountering special circumstances such as excessive flooding, which may cause large losses downstream. In this paper, we take the small reservoirs in Shandong Province as the research object, analyze the hydraulic topology of three types of tandem reservoirs, generalize the shape of the breach by using the transient lateral local one-break to the end, calculate the dam-break flooding process by using the quadratic parabolic method, and simulate the dam-break by using the MIKE21 model based on the principle of the two-dimensional incompressible Reynolds mean stress equation for the incompressible fluid, and analyze the peak flow under various combinations of dam-break flow by setting various combinations of the number of dam-breaks and the timing of dam-break simulation. By setting various combinations of dam failure numbers and timing, we analyzed the changing rules of peak dam failure flow, inundation area and other elements under various combinations, and sought the most unfavorable combinations and parameters such as the timing of dam failure, and the results of the analyses can provide technical support for the assessment of the risk of dam failure in the tandem reservoirs in the hilly area and the risk correspondence.

Design of van der Waals heterostructures composed of g-C3N4 and III-V materials for solar cell

As society develops, people pay more attention to the application of solar cell to harvest inexhaustible solar power, which has a benefit of greenness and cleanness. In this paper, we construct 14 heterostructures composed of g-C3N4 and Ⅲ-Ⅴ materials based on first-principles calculations. We systematically analyse their stability property and find a periodic rule of binding energy change about the atomic number of Ⅲ-Ⅴ material. We select 9 stable van der Waals (vdWs) heterostructures and further analyse their band alignment and power conversion efficiency (PCE). We find GaAs-D is a type-Ⅱ heterostructure with indirect band gap of 1.38 eV and the PCE reaches 15.2%. The construction of GaAs-D effectively promotes the optical absorption in visible-spectrum compared with two monolayers. This paper systematically analyses the stability of constructed vdWs heterostructures composed of g-C3N4 and Ⅲ-Ⅴ materials, electronic band structures and their potential application as solar cell.

Can Bank Density Provide Insights on the Appropriation of Disaster Relief Funds? Evidence from the Paycheck Protection Program

In response to the COVID-19 pandemic, Congress in conjunction with the Small Business Administration (SBA) created the Paycheck Protection Program (PPP) to help small business owners retain employees. We improve on previous literature exploring the relationship between bank density and PPP loan dispersion by implementing precisely geocoded data to map loans to commuting zones. Revisiting results in Deming and Weiler (2023), we confirm the statistically significant relationship between bank density and PPP loans per small business. We consider three distinct periods of lending to analyze how changes in the PPP loan program rules might have impacted dispersion. The coefficient in the regression of loans per small business on bank density is largest in the final wave of lending, and in commuting zones with high loan densities. This suggests that having additional bank branches in the commuting zone may have helped facilitate rapid dispersion of relief funds to high demand areas during the program.

Supply chain network optimization for emergency materials considering demand satisfaction

AbstractIn order to effectively guarantee the smooth supply of emergency materials under public health emergencies, first, we predict the number of daily infected people based on the modified SEIRD infectious disease dynamics model and accordingly construct the dynamic demand prediction model of emergency materials so as to catch the change rule of the demand for emergency materials with greater precision. Subsequently, under the premise of demand satisfaction, we optimize the supply chain network of emergency materials and embed two insurance strategies in the supply system in advance: multi‐source purchase and buffer production capacity, to enhance the stability of supply chain by sacrificing part of the cost. Next, a bi‐objective linear programming model based on minimizing system cost and maximizing demand satisfaction is proposed with the intention of realizing the design of emergency materials supply chain network, which balances the risk and cost. Finally, through the analysis of the example, we find that compared with the traditional supply chain network of emergency materials, the total satisfaction rate of the supply chain network optimized by balancing cost and risk is increased by 11.70%, while the cost is increased by only 2.04%, which fully verifies the validity of the optimized design of supply chain network of emergency materials.

Analisis Tingkat Kepuasan Pasien terhadap Pelayanan Poli Rawat Jalan di RSUD dr. Abdoer Rahem Situbondo Menggunakan Metode Algoritma C4.5

The aftermath of the COVID-19 pandemic has had a real impact in all areas of life, especially in the health sector. Therefore, there are consequences of this phenomenon, namely changes in rules and services in the health sector, especially in hospitals. With this change, patients feel different services and rules in the hospital, this has an impact on the hospital, namely the assessment of patient satisfaction with the hospital. The purpose of this study is to measure the accuracy, precision, and recall of the patient satisfaction level grouping. In addition, it also analyzes the shortcomings of hospital services. The method used to build a patient satisfaction classification model is the C4.5 algorithm. C4.5 algorithm is one method that can solve cases that are often used in classification technique problems. The result of the C4.5 algorithm is in the form of a decision tree as in other classification techniques. Based on the results of 3 tests conducted for patient satisfaction at RSUD dr. Abdoer Rahem Situbondo using rapid miner and with the decision tree, the greatest accuracy is 95.38%.