Analysis and Innovative Strategies of Tax Preferential Policies to Promote the Sustainable Development of Small-Scale Individual Businesses

This study conducted an in-depth analysis of the current tax preferential policies for small-scale individual businesses and compared them with similar policies both domestically and internationally,aiming to reveal the advantages and disadvantages of the current system.After examining the impact of these tax preferential policies on the economic status of individual business owners and the broader social economy,this article proposes a set of innovative tax preferential strategies based on theoretical foundations.By developing these innovative strategies and clarifying their implementation paths,the aim is to promote the sustainable and healthy development of small-scale individual businesses,thereby fostering comprehensive socio-economic progress.The conclusion of this study not only summarizes policy recommendations with practical significance but also provides theoretical support for the optimization and innovation of future related systems.

Pedestrian lane formation with following–overtaking model and measurement of system order

Pedestrian self-organizing movement plays a significant role in evacuation studies and architectural design.Lane formation,a typical self-organizing phenomenon,helps pedestrian system to become more orderly,the majority of following behavior model and overtaking behavior model are imprecise and unrealistic compared with pedestrian movement in the real world.In this study,a pedestrian dynamic model considering detailed modelling of the following behavior and overtaking behavior is constructed,and a method of measuring the lane formation and pedestrian system order based on information entropy is proposed.Simulation and analysis demonstrate that the following and avoidance behaviors are important factors of lane formation.A high tendency of following results in good lane formation.Both non-selective following behavior and aggressive overtaking behavior cause the system order to decrease.The most orderly following strategy for a pedestrian is to overtake the former pedestrian whose speed is lower than approximately 70%of his own.The influence of the obstacle layout on pedestrian lane and egress efficiency is also studied with this model.The presence of a small obstacle does not obstruct the walking of pedestrians;in contrast,it may help to improve the egress efficiency by guiding the pedestrian flow and mitigating the reduction of pedestrian system orderliness.

Measuring Pedestrian Stress Response (MPSR) Using Wearable Technologies

Walkability is an essential aspect of urban transportation systems. Properly designed walking paths can enhance transportation safety, encourage pedestrian activity, and improve community quality of life. This, in turn, can help achieve sustainable development goals in urban areas. This pilot study uses wearable technology data to present a new method for measuring pedestrian stress in urban environments and the results were presented as an interactive geographic information system map to support risk-informed decision-making. The approach involves analyzing data from wearable devices using heart rate variability (RMSSD and slope analysis) to identify high-stress locations. This data-driven approach can help urban planners and safety experts identify and address pedestrian stressors, ultimately creating safer, more walkable cities. The study addresses a significant challenge in pedestrian safety by providing insights into factors and locations that trigger stress in pedestrians. During the pilot study, high-stress pedestrian experiences were identified due to issues like pedestrian-scooter interaction on pedestrian paths, pedestrian behavior around high foot traffic areas, and poor visibility at pedestrian crossings due to inadequate lighting.

Hybrid pedestrian positioning system using wearable inertial sensors and ultrasonic ranging

Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.

IR-YOLO: Real-Time Infrared Vehicle and Pedestrian Detection

Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.

Method of improving pedestrian navigation performance based on chest card

With the development of positioning technology,loca-tion services are constantly in demand by people.As a primary location service pedestrian navigation has two main approaches based on radio and inertial navigation.The pedestrian naviga-tion based on radio is subject to environmental occlusion lead-ing to the degradation of positioning accuracy.The pedestrian navigation based on micro-electro-mechanical system inertial measurement unit(MIMU)is less susceptible to environmental interference,but its errors dissipate over time.In this paper,a chest card pedestrian navigation improvement method based on complementary correction is proposed in order to suppress the error divergence of inertial navigation methods.To suppress atti-tude errors,optimal feedback coefficients are established by pedestrian motion characteristics.To extend navigation time and improve positioning accuracy,the step length in subsequent movements is compensated by the first step length.The experi-mental results show that the positioning accuracy of the pro-posed method is improved by more than 47%and 44%com-pared with the pure inertia-based method combined with step compensation and the traditional complementary filtering com-bined method with step compensation.The proposed method can effectively suppress the error dispersion and improve the positioning accuracy.

Lightweight Cross-Modal Multispectral Pedestrian Detection Based on Spatial Reweighted Attention Mechanism

Multispectral pedestrian detection technology leverages infrared images to provide reliable information for visible light images, demonstrating significant advantages in low-light conditions and background occlusion scenarios. However, while continuously improving cross-modal feature extraction and fusion, ensuring the model’s detection speed is also a challenging issue. We have devised a deep learning network model for cross-modal pedestrian detection based on Resnet50, aiming to focus on more reliable features and enhance the model’s detection efficiency. This model employs a spatial attention mechanism to reweight the input visible light and infrared image data, enhancing the model’s focus on different spatial positions and sharing the weighted feature data across different modalities, thereby reducing the interference of multi-modal features. Subsequently, lightweight modules with depthwise separable convolution are incorporated to reduce the model’s parameter count and computational load through channel-wise and point-wise convolutions. The network model algorithm proposed in this paper was experimentally validated on the publicly available KAIST dataset and compared with other existing methods. The experimental results demonstrate that our approach achieves favorable performance in various complex environments, affirming the effectiveness of the multispectral pedestrian detection technology proposed in this paper.

An Application of RGBD-Based Skeleton Reconstruction for Pedestrian Detection and Occlusion Handling

This study explores the challenges posed by pedestrian detection and occlusion in AR applications, employing a novel approach that utilizes RGB-D-based skeleton reconstruction to reduce the overhead of classical pedestrian detection algorithms during training. Furthermore, it is dedicated to addressing occlusion issues in pedestrian detection by using Azure Kinect for body tracking and integrating a robust occlusion management algorithm, significantly enhancing detection efficiency. In experiments, an average latency of 204 milliseconds was measured, and the detection accuracy reached an outstanding level of 97%. Additionally, this approach has been successfully applied in creating a simple yet captivating augmented reality game, demonstrating the practical application of the algorithm.

A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

An analytical model for estimating rock strength parameters from small-scale drilling data

The small-scale drilling technique can be a fast and reliable method to estimate rock strength parameters. It needs to link the operational drilling parameters and strength properties of rock. The parameters such as bit geometry, bit movement, contact frictions and crushed zone affect the estimated parameters.An analytical model considering operational drilling data and effective parameters can be used for these purposes. In this research, an analytical model was developed based on limit equilibrium of forces in a Tshaped drag bit considering the effective parameters such as bit geometry, crushed zone and contact frictions in drilling process. Based on the model, a method was used to estimate rock strength parameters such as cohesion, internal friction angle and uniaxial compressive strength of different rock types from operational drilling data. Some drilling tests were conducted by a portable and powerful drilling machine which was developed for this work. The obtained results for strength properties of different rock types from the drilling experiments based on the proposed model are in good agreement with the results of standard tests. Experimental results show that the contact friction between the cutting face and rock is close to that between bit end wearing face and rock due to the same bit material. In this case,the strength parameters, especially internal friction angle and cohesion, are estimated only by using a blunt bit drilling data and the bit bluntness does not affect the estimated results.

Weak wide-band signal detection method based on small-scale periodic state of Duffing oscillator

The conventional Duffing oscillator weak signal detection method, which is based on a strong reference signal, has inherent deficiencies. To address these issues, the characteristics of the Duffing oscillator＇s phase trajectory in a small- scale periodic state are analyzed by introducing the theory of stopping oscillation system. Based on this approach, a novel Duffing oscillator weak wide-band signal detection method is proposed. In this novel method, the reference signal is discarded, and the to-be-detected signal is directly used as a driving force. By calculating the cosine function of a phase space angle, a single Duffing oscillator can be used for weak wide-band signal detection instead of an array of uncoupled Duffing oscillators. Simulation results indicate that, compared with the conventional Duffing oscillator detection method, this approach performs better in frequency detection intervals, and reduces the signal-to-noise ratio detection threshold, while improving the real-time performance of the system.

Shock-induced fracture of dolomite rock in small-scale blast tests

This paper attempts to study dolomite failure using small-scale blast tests.The experimental setup consisted of a cylindrical specimen with a central borehole fitted with a detonation cord inside a copper pipe.The specimen was confined using lead material.During the test,acceleration histories were recorded using sensors placed on the lead confinement.The results showed that heterogeneity and initial cracks significantly influenced the observed failure and cracking patterns.The tests were numerically represented using the previously validated Johnson-HolmquistⅡ(JH-2)constitutive model.The properties of the detonation cord were first determined and verified in a special test with a lead specimen to compare the deformation in the test with that of numerical simulation.Then,the small-scale blast test was simulated,and the failure of the dolomite was compared with the test observations.Comparisons of acceleration histories,scabbing failure,and number of radial cracks and crack density confirmed the overall repeatability of the actual testing data.It is likely that the proposed model can be further used for numerical studies of blasting of dolomite rock.

Study on the Roles of FWUA in Construction, Management and Maintenance of Small-Scale Irrigation and Water Conservancy

In recent years, China has been frequented by floods and droughts which has greatly evoked much concern from the Central Government about rural water conservancy construction. Irrigation is closely related to the "three rural" issues and concerns about the vital interests of farmers. To achieve a virtuous circle of agricultural water supply, it is necessary and urgent to establish Farmer Water User Association (FWUA) to participate in the construction, management and maintenance of small-scale irrigation system. Based on the survey on nationwide "Small-scale irrigation conditions", the roles of FWUA in the construction, management and maintenance of small-scale water conservancy have studied in this study.

Small-Scale Tomato Cultivators’ Perception on Pesticides Usage and Practices in Buea Cameroon

It has been shown that farmers with limited knowledge of the use and safe handling of pesticides may suffer exposure which results in adverse health effects. In Buea, Cameroon, small-scale tomato farmers commonly use pesticides for pest control. Information was obtained from these tomato farmers to determine the extent and types of their pesticide use, their knowledge of pesticide use and effectiveness, and their perception of potential harm resulting from pesticide use. A standardized questionnaire, interviews, field observations and an analytical ranking game were used to describe the pesticide use of 93 tomato farmers. Many farmers (47.6%) used pyrethiod and organophosphorus insecticides and identified these chemicals as the most effective in pesticide control;these are WHO Class II pesticides which are the most hazardous to humans. Most farmers (83.8%) used knapsack sprayers to apply pesticides, with 76.3% using no or partial personal protective equipment (PPE). It was notable that 55.5% of farmers expressed no concern regarding the wind direction (pesticide drift) during spraying. The results showed a significant association between the method of pesticides application and farm size (P < 0.001). Most farmers (85.0%) reported at least one symptom of acute pesticide poisoning following spraying. This study revealed that the tomato farmers have a high exposure to pesticides secondary to inadequate knowledge of the safe and judicious use of pesticides. Strategies that provide training on the appropriate use of pesticides, how to reduce exposure to and health risks of pesticides and alternative options of pest management and control are required. The study also raised concerns that further control of the sale and distribution of pesticides may be indicated.

Processes of small-scale tidal flat accretion and salt marsh changes on the plain coast of Jiangsu Province,China

Large-scaled reclamation modifies the coastal environment dramatically while accelerating the disappearance of salt marshes,which causes the degradation of the coastal ecosystem and the biodiversity function.In this study,we explored the changes of tidal flat and salt marsh coverage in a small-scale tidal flat with an area of ~160 000 m^2 in the plain coast of Jiangsu Province,China.Human activities（e.g.,the construction of dikes） are a crucial contributor that benefits for the tidal flat accretions and the following changes of salt marsh coverage.Located in the front of the man-made ＂concave coastline＂,the study area is suitable for sediment accretion after the dike construction in the end of 2006.On the basis of the annual tidal surface elevation survey from 2007 to 2012,the sedimentation rates in the human influenced tidal flat varied from a few centimeters per year to 23 cm/a.The study area experienced a rapid accretion in the tidal flat and the expansion of the salt marsh,with the formation of a longshore bar,and a subsequent decline of the salt marsh.Breaking waves during the flooding tide brought much sediment from the adjacent tidal flat to the study area,which caused burial and degeneration of the salt marsh.The vertical grain size changes within a 66 cm long core in the study area also demonstrated the above changes in the tidal environment.This study indicates that the responses of small-scale tidal flat changes to reclamation are significant,and the rational reclamation would benefit for the new salt marsh formation in front of the dikes.Further research about the evolution of small scale tidal flat as well as the spatial planning of the polder dike should be strengthened for the purpose to maintain a healthier coastal environment.

Effect of a static pedestrian as an exit obstacle on evacuation

Building exit as a bottleneck structure is the last and the most congested stage in building evacuation.It is well known that obstacles at the exit affect the evacuation process,but few researchers pay attention to the effect of stationary pedestrians(the elderly with slow speed,the injured,and the static evacuation guide)as obstacles at the exit on the evacuation process.This paper explores the influence of the presence of a stationary pedestrian as an obstacle at the exit on the evacuation from experiments and simulations.We use a software,Pathfinder,based on the agent-based model to study the effect of ratios of exit width(D)to distance(d)between the static pedestrian and the exit,the asymmetric structure by shifting the static pedestrian upward,and types of obstacles on evacuation.Results show that the evacuation time of scenes with a static pedestrian is longer than that of scenes with an obstacle due to the unexpected hindering effect of the static pedestrian.Different ratios of D/d have different effects on evacuation efficiency.Among the five D/d ratios in this paper,the evacuation efficiency is the largest when d is equal to 0.75D,and the existence of the static pedestrian has a positive impact on evacuation in this condition.The influence of the asymmetric structure of the static pedestrian on evacuation efficiency is affected by D/d.This study can provide a theoretical basis for crowd management and evacuation plan near the exit of complex buildings and facilities.

Pedestrian evacuation simulation in multi-exit case:An emotion and group dual-driven method

This paper analyzes the characteristics of emotion state and group behavior in the evacuation process.During the emergency evacuation,emotion state and group behavior are interacting with each other,and indivisible.The emotion spread model with the effect of group behavior,and the leader-follower model with the effect of emotion state are proposed.On this basis,exit choice strategies with the effect of emotion state and group behavior are proposed.Fusing emotion spread model,leader-follower model,and exit choice strategies into a cellular automata(CA)-based pedestrian simulation model,we simulate the evacuation process in a multi-exit case.Simulation results indicate that panic emotion and group behavior are two negative influence factors for pedestrian evacuation.Compared with panic emotion or group behavior only,pedestrian evacuation efficiency with the effects of both is lower.

The Human Dimension in the UNESCO Kogelberg Biosphere Reserve:Integrating Livelihood Issues of Small-Scale Fisheries with the Conservation of Natural Resources

Fisheries management worldwide struggles to strike a balance between protecting resources,ensuring fair access to resources and promoting economic effectiveness and stability.The transition to a participatory democracy in South Africa in 1994 resulted in the transformation of government institutions and an extensive process of legislative reform regarding

Small-Scale Duplications Play a Significant Role in Rice Genome Evolution

Genes are continually being created by the processes of genome duplication （ohnolog） and gene duplication （paralog）. Whole-genome duplications have been found to be widespread in plant species and play an important role in plant evolution. Clearly un-overlapping duplicated blocks of whole-genome duplications can be detected in the genome of sequenced rice （Oryza sativa）. Syntenic ohnolog pairs （ohnologues） of the whole-genome duplications in rice were identified based on their syntenic duplicate lines. The paralogs of ohnologues were further scanned using multi-round reciprocal BLAST best-hit searching （E〈e^-14）. The results indicated that an average of 0.55 sister paralogs could be found for every ohnologue in rice. These results suggest that small-scale duplications, as well as whole-genome duplications, play a significant role in the two duplicated rice genomes.

Effect of high-or low-speed fluctuations on the small-scale bursting events in an active control experiment

Active control of a fully developed turbulence boundary layer(TBL) over a flat plate has been investigated with a statistical view. The piezoelectric(PZT) oscillator is employed to produce periodic input into the inner region of the TBL.A wall probe is fixed upstream of the oscillator to identify the high-or low-speed fluctuations as the detecting signals.Then, the impact of the detecting signals on the small-scale bursting process is investigated based on the data acquired by the traversing probe downstream of the oscillator. The results indicate that the small-scale bursting intensity is restrained more apparently at high-speed detecting fluctuations but less impacted at low-speed detecting fluctuations. Furthermore, the perturbed-scale fluctuations arrange the small-scale bursting process in the near-wall region. The detecting signals have an obvious impact on this arrangement, especially the high-intensity regions of the small-scale bursting events: the vibration enhances the intensity at high-speed detecting signals but weakens it at low-speed detecting signals in these regions, which gives a direct evidence on how detecting signals interfering the small-scale bursting process.