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Multiple object tracking (MOT) in unmanned aerial vehicle (UAV) videos is a fundamental task and can be applied in many fields. MOT consists of two critical procedures, i.e., object detection and re-identification (ReID). One-shot MOT, which incorporates detection and ReID in a unified network, has gained attention due to its fast inference speed. It significantly reduces the computational overhead by making two subtasks share features. However, most existing one-shot trackers struggle to achieve robust tracking in UAV videos. We observe that the essential difference between detection and ReID leads to an optimization contradiction within one-shot networks. To alleviate this contradiction, we propose a novel feature decoupling network (FDN) to convert shared features into detection-specific and ReID-specific representations. The FDN searches for characteristics and commonalities between the two tasks to synergize detection and ReID. In addition, existing one-shot trackers struggle to locate small targets in UAV videos. Therefore, we design a pyramid transformer encoder (PTE) to enrich the semantic information of the resulting detection-specific representations. By learning scale-aware fine-grained features, the PTE empowers our tracker to locate targets in UAV videos accurately. Extensive experiments on VisDrone2021 and UAVDT benchmarks demonstrate that our tracker achieves state-of-the-art tracking performance.

One-shot multiple object tracking (MOT), which learns object detection and identity embedding in a unified network, has attracted increasing attention due to its low complexity and high tracking speed. However, most one-shot trackers ignore that detection and re-identification (ReID) require different representations of features. The inherent difference between these two subtasks leads to optimization contradictions in the training procedure. This issue would result in suboptimal tracking performance. To alleviate this contradiction, we propose a novel dual-path transformation network (DTN) that decouples the shared features into detection-specific and ReID-specific representations. By learning task-specific features, this module satisfies the different requirements of both subtasks. Moreover, we observe that previous trackers generally utilize local information to distinguish targets and ignore global semantic relations, which are crucial for tracking. Therefore, we design a pyramid non-local network (PNN) that allows our network to explore pixel-to-pixel relations with a global receptive field. Meanwhile, PNN considers the scale information to enhance the robustness to scale variations. Extensive experiments conducted on three benchmarks, i.e., MOT16, MOT17, and MOT20, demonstrate the superiority of our tracker, namely DPTrack. The experimental results reveal that DPTrack achieves state-of-the-art performance, e.g., MOTA of 77.1 % and IDF1 of 74.9 % on MOT17. Moreover, DPTrack runs at 14.9FPS, and our lightweight version runs at 26.6FPS with only a slight performance decay.

CrossFit is one of the fastest growing fitness phenomena of the last decade. Considered the largest fitness business today, CrossFit’s widespread popularity has attracted increasing interest from a variety of disciplines. Despite this burgeoning scholarly attention, few analyses have focused on examining CrossFit’s discourse of self-optimization and the role it plays in shaping the ideal image of the CrossFitter. The present paper addresses this question by examining the popular literature on CrossFit using a Critical Discourse Approach (CDA). Findings reveal CrossFit’s understanding of self-optimization as a polyhedral and demanding process that goes beyond physical discipline to encompass all facets of the self. Five main themes of self-optimization are identified in the popular CrossFit literature: 1) failure and weakness, 2) pain and constant preparedness, 3) integral self-work and passionate commitment, 4) constant self-improvement, and 5) community support. Drawing on previous research on the topic, the paper also reflects on the relationship between CrossFit and neoliberalism, suggesting CrossFit as a fertile ground for the humanities and social sciences to further explore the intersections between the fields of health, sport, self-optimization, and identity.

This article is based on a research project about fasting, an ancient practice that is gaining popularity in France due to its potential benefits for well-being, health, and weight loss. This quest for less seems therefore to meet the neoliberal logic of performance. As such, we consider it to be an original form of self-optimization that would consist in doing more with less. Our paper shows that fasting is not only about maximizing the use of the body but also a means of self-management that can promote greater food reflexivity and even lead to lifestyle changes. The material collected combines an analysis of claims made in favor of fasting on the internet, as well as on smartphone apps, and a qualitative study conducted on people who engage in the practice (intermittent or periodic fasting). Two main findings emerged from this research. Firstly, the trajectories that led the interviewees to fasting show that engagement into this “dietary minimalism” requires to distance oneself from dietary norms and, for some, implies a phenomenon of social distinction. Next, the analysis of both purported benefits and concrete practices reveals the importance of the processual dimension: fasting seems to trigger a deconstruction of the everyday through the experience of less. Finally, food and eating appears to be a particular focal point for self-optimization that then could spill over into other areas. As an initial trial, it can open up other methods of optimization and other forms of simplification: “fasting begets fasting.”

Modern social theories often treat digital self-tracking as a form of self-optimisation that is considered paradigmatic for a contemporary society oriented towards rationalisation, continuous achievement of goals, and quantitative growth. This paper aims to complement this perspective by analysing specific digital self-tracking practices as a dietetic form of self-optimisation. Dietetics is a millennia-old therapeutic concept that can be characterized by at least three features: (1) a logic of balance, (2) striving for wholeness, and (3) the centeredness of the individual. Against this background, I analyse practices of sleep and diet tracking as dietetic variants of self-optimisation. Corresponding self-tracking practices aim, for example, at achieving balanced insulin levels or continuous deep sleep. These practices thus are considered optimised when they continuously reproduce an individually targeted functioning routine. In these cases, digital self-tracking as a form of self-optimisation is aimed less at a logic of rationalisation and more at an individual, comprehensive ensemble for maintaining the right balance.

This paper presents an analysis of technologically mediated self-relations that materialise in the use of self-tracking (ST) devices and data to monitor and track one’s bodily, emotional, habitual, or productivity-related aspects. Based on ethnographical research and postphenomenological framing, two analytical concepts are employed: self-care and self-control. While seemingly opposed, both simultaneously appear and co-exist in ST practices that transcend mere self-optimisation. The dialectic interplay between self-control and self-care provides uncertainty-reducing confirmation of prior hunches, emotionally relieving reminders and algorithmic recommendations, detailed data that might be helpful in the future for pattern recognition or treatments, and an orientation that offers safety with regard to current and future decisions. Self-tracking technologies can be seen as assisting self- and life-regulation that can ultimately support personal balance and harmony. The article contributes theoretically to ST literature by extending the concept of self-optimisation to include the balancing of needs and desires between self-responsibility and gratification, goal-tracking and self-affirmation, discipline and letting go.

The emergence phenomena of swarm intelligence exist widely in nature and human society. People have been exploring the root causes of the emergence of swarm intelligence and trying to establish general theories and models for the emergence of swarm intelligence. However, the existing theories or models do not grasp the essence of swarm intelligence, so they lack generality and are difficult to explain various phenomena of the emergence of swarm intelligence. In this paper, a contradiction-centered model for the emergence of swarm intelligence is proposed. In the model, the internal contradictions of individuals determine their behavior and properties; individuals are related and interact within the swarm because of competing and occupying environmental resources; interactions and group potential affect the internal contradictions of individuals and the contradictions’ distribution in the swarm; and the swarm intelligence is manifested as the specific distribution of contradictions. This model completely explains the condition, force, approach, form, and process of the emergence of swarm intelligence. For validating this model, several swarm intelligence systems were analyzed and implemented in this paper. The experimental results show that the model has good generality and can be used to describe the emergence of various swarm intelligence.

The present paper aims to propose a new method for neutralizing contradictions in neural networks. Neural networks exhibit numerous contradictions in the form of contrasts, differences, and errors, making it extremely challenging to find a compromise between them. In this context, neutralization is introduced not to resolve these contradictions, but to weaken them by transforming them into more manageable and concrete forms. In this paper, contradictions are neutralized or weakened through four neutralization methods: comprehensive, nullified, compressive, and collective. Comprehensive neutralization involves increasing the neutrality of all components in a neural network. Nullified neutralization is employed to weaken contradictions among different computational and optimization procedures. Compressive neutralization aims to simplify multi-layered neural networks while preserving the original internal information as much as possible. Collective neutralization is achieved by considering as many final networks as possible under different conditions, inputs, learning steps, and so on. The proposed method was applied to two data sets, one of which consisted of irregular forms resulting from natural language processing. The experimental results demonstrate that comprehensive neutralization could enhance the neutrality of all components and represent features across a broader range of components, thereby improving generalization. Nullified neutralization enabled a compromise between neutrality maximization and error minimization. Through compressive and collective neutralization of a large number of compressed weights, it became possible to interpret compressed and collective weights. In particular, inputs that were considered relatively unimportant by conventional methods emerged as highly significant. Finally, these results were compared with those obtained in the field of the human-centered approach to provide a clearer understanding of the significance of contradiction resolution, applied to neural networks.

In order to clarify the contradictory mechanism between tire rolling resistance and grip performance, ten (10) 205/55 R16 radial tires with different tread patterns were selected as the research objects. Using VIC-3D non-contact strain measurement system, the pattern deformation in the contact area under vertical load was tested and the relevant deformation parameters of the contact area were extracted. Correlation analysis was used to establish the relationship between the identified deformation parameters and tire performance indicators. Then the contradiction mechanism between tire rolling resistance and grip performance was identified. The mechanism is such that, in order to improve the grip performance of the tire, it is necessary to reduce the transverse tensile strain of the tread in the contact area and increase the longitudinal tensile strain of the tread, but with the increase of the longitudinal tensile strain, the rolling resistance of the tire will also increase, which leads to the contradiction between tire rolling resistance and grip performance. In order to better understand and solve this contradiction, a finite element model of 205/55R16 tire with complex pattern was established. The influence of the number and width of transverse grooves in outer shoulder area on tire rolling resistance and grip performance was analyzed by numerical simulation, where it was identified that, the longitudinal tensile deformation of the tread is the main cause of contradiction between the two performances. An optimized design of concave transverse groove with narrow groove in the middle and wide groove at both ends was proposed in the outer shoulder area to resolve the contradiction. Compared with the original scheme, the rolling resistance of the optimized scheme was reduced by 2.112 N, and the grip force saw an increase of 10.196 N, and thus delivering a cooperative improvement of tire rolling resistance and grip performance.

PurposeChina's population–land contradiction is a crucial issue, and by deeply analyzing causes of wasting arable land, this article recommends some policies to avoid waste.Design/methodology/approachBased on the current high-, middle- and low-class differentiation in the agricultural products' consumption structure against urban residents' rapid income growth, this article proposes that agricultural products with distinctive regional characteristics should be developed according to regional natural agricultural resources and market demand, so as to ensure that China's scarce arable land can be used effectively.FindingsChoices in regional agricultural production relate to operational farmers' enthusiasm for profitability and production, residential farmers' ability to ensure their own food security, agriculture's sustainable development and arable land resources' optimal allocation. Therefore, the varietal structure of agricultural products and regional production layout should be compatibly decided according to consumer demand and resource endowment.Originality/valueDuring the process of industrialization and urbanization, wasting of arable land has become a social development problem. On the basis of agriculture's regional resource endowment, this article reconstructs the functional positioning of various Chinese agricultural regions and solves the difficult problem of consumption structure transformation and homogeneous competition through the geographical division of labor, thereby optimizing allocation of arable land resources.